Advances in Hospitality and Leisure. Volume 4 (Advances in Hospitality and Leisure)

ADVANCES IN HOSPITALITY AND LEISURE Series Editor: Joseph S. Chen Recent Volumes: Volume 1: Advances in Hospitality and...

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ADVANCES IN HOSPITALITY AND LEISURE Series Editor: Joseph S. Chen Recent Volumes: Volume 1:

Advances in Hospitality and Leisure, edited by Joseph S. Chen

Volume 2:

Advances in Hospitality and Leisure, edited by Joseph S. Chen

Volume 3:

Advances in Hospitality and Leisure, edited by Joseph S. Chen

ADVANCES IN HOSPITALITY AND LEISURE VOLUME 4

ADVANCES IN HOSPITALITY AND LEISURE EDITED BY

JOSEPH S. CHEN Indiana University, Bloomington, USA

United Kingdom – North America – Japan India – Malaysia – China

JAI Press is an imprint of Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2008 Copyright r 2008 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-7623-1489-8 ISSN: 1745-3542 (Series)

Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print

LIST OF CONTRIBUTORS Katerina Annaraud

School of Hotel and Restaurant Management, University of South Florida, FL, USA

Robert J. Blomme

Hotelschool The Hague, The Hague, The Netherlands

Ana Bobirca

Academy of Economic Studies, Faculty of International Business and Economics, Bucharest, Romania

David Y. Chang

School of Hotel and Restaurant Management, University of South Florida, Sarasota, FL, USA

Po-Ju Chen

Rosen College of Hospitality Management, University of Central Florida, Orlando, FL, USA

Miau Feng Chi

Computer Science and Information Technology, National Taichung Institute of Technology, Taichung, Taiwan

Cristiana Cristureanu

Academy of Economic Studies, Faculty of International Business and Economics, Bucharest, Romania

Toma´s F. Espino-Rodrı´guez

Department of Economics and Business Management, University of Las Palmas de Gran Canaria, Spain

Petra Glover

Monash University, National Centre for Australian Studies, Australia ix

x

LIST OF CONTRIBUTORS

Zaher Hallab

Department of Leadership in Hospitality and Leisure Services, California State University, CA, USA

Shih-Yun Hsu

Department of Leisure and Recreation Management, Asia University, Taichung County, Taiwan

Tak-Kee Hui

NUS Business School, Department of Decision Sciences, National University of Singapore, Singapore

Kyungmi Kim

Department of Animal Science, Food and Nutrition, Southern Illinois University, Carbondale, IL, USA

Choon-Chiang Leong

Nanyang Business School, Nanyang Technological University, Singapore

Jennifer C. H. Min

Department of Tourism, Hsing Wu College, Taipei County, Taiwan

Bruce Prideaux

James Cook University, School of Business, Australia

Manuel Rodrı´guez-Dı´az

Department of Marketing, University of Las Palmas de Gran Canaria, Spain

Paul D. Rompf

University of Central Florida, Rosen College, Orlando, FL, USA

Denver E. Severt

University of Central Florida, Rosen College, Orlando, FL, USA

Matthew Smith

University of Tennessee, Knoxville, TN, USA

Debbie M. Tromp

Hotelschool The Hague, The Hague, The Netherlands

Arjan van Rheede

Hotelschool The Hague, The Hague, The Netherlands

List of Contributors

xi

David Wan

NUS Business School, Department of Management and Organization, National University of Singapore, Singapore

Wei-Ching Wang

The Graduate Institute of Business Administration, National Chia-yi University, Chiayi City, Taiwan

Chung-Chi Wu

Department of Recreation Sport and Health Promotion, National Pingtung University of Science and Technology, Pingtung, Taiwan

AIMS AND SUBMISSION GUIDELINES Advances in Hospitality and Leisure (AHL), a peer-review publication, aims to promote seminal and innovative research outputs pertaining to hospitality, leisure, tourism, and lifestyle. Speciﬁcally, the series will encourage researchers to investigate new research issues and problems that are critical but have been largely ignored while providing a forum that will disseminate singular thoughts advancing empirical undertakings both theoretically and methodologically. The fourth issue includes nine full papers and three research notes. As for data exploration, nine papers deploy primary research to collect ﬁrst-hand information while three manuscripts use secondary data to develop marketing strategies and make predictions. The contributors to the issue come from seven nations entailing Australia, The Netherlands, Romania, Singapore, Spain, Taiwan, and the United States. For submission to future issues, please review the following guidelines: Originality of Manuscript: The manuscript should represent an original work that has never been published elsewhere nor is being considered for publication elsewhere. Style and Length of Manuscript: 12 pt Times Roman font; double spacing; APA; 7,000 words (Full Paper) or 4,000 words (Research Note). Layout of Manuscript: First page: title of paper and author information; second page: title of paper, 100–120 word abstract, and keywords; third page and beyond: main text, appendix, references, ﬁgures, and tables. Text of Manuscript: For literature review articles, please include introduction, critical literature review, problems in past research, and suggestions for future research. For empirical research papers, please include introduction, methods, ﬁndings and discussions, and conclusion. AHL requires electronic submission. Please use an email attachment with Microsoft Word format to the editor Dr. Joseph Chen ([email protected]) or send a diskette to Tourism Management Program, Department of PRTS, HPER Building #133, Indiana University, Bloomington, Indiana 47405, USA. xiii

EDITORIAL BOARD EDITOR-IN-CHIEF Joseph Chen Indiana University, Bloomington, USA

ASSOCIATE EDITORS Yuksel Ekinci (Europe) Oxford Brookes University, UK

Tzung-Cheng Huan (Asia) National Chia-Yi University, Taiwan

EDITORIAL REVIEW BOARD North America

Europe

Rachel Chen University of Tennessee, USA

Marcjanna Augustyn University of Hull, UK

Dogen Gursoy Washington State University, USA

Metin Kozak Mugla University, Turkey

Colin Johnson San Jose State University, USA

Fre´de´ric Dimanche European School of Business, France

Anna Mattila Pennsylvania State University, USA

A´lvaro Matias University of Evora, Portugal

William Norman Clemson University, USA

Nina Prebensen Tromso University, Norway

Haemoon Oh Iowa State University, USA

Marianna Sigala University of Aegean, Greece

H. G. Parsa University of Central Florida, USA

Helmut Wachowiak Intl. U. of Applied Sciences, Bad Honnef, Germany

John Williams University of New Orleans, USA xv

xvi

Asia/Paciﬁc Tak-Kee Hui National University of Singapore, Singapore Bruce Prideaux James Cook University, Australia

EDITORIAL BOARD

PREDICTORS OF TURNOVER INTENTIONS OF HIGHLY EDUCATED EMPLOYEES IN THE HOSPITALITY INDUSTRY Robert J. Blomme, Debbie M. Tromp and Arjan van Rheede ABSTRACT As management-level turnover is increasing rapidly, one of the major challenges for the hospitality industry is to retain highly educated and highly skilled employees. As the psychological contract approach to the employment relationship had not been investigated with regard to the hospitality industry, it became the subject of this study. The results demonstrate that psychological contract measures, in particular job content, can explain why there is a substantial amount of variance in intention among highly educated hotel employees with regard to leaving the organization, especially when the mediating role of affective commitment is taken into account. In this paper, managerial implications are discussed, and recommendations for further research are made.

Advances in Hospitality and Leisure, Volume 4, 3–28 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00001-5

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ROBERT J. BLOMME ET AL.

INTRODUCTION One of the major challenges for the hospitality industry is to retain highly educated and highly skilled employees. Research studies in the Netherlands suggest that management-level turnover is increasing rapidly (Reijnders, 2003; Blomme, 2006). One research study amongst graduates of the Hotelschool The Hague (Blomme, 2006) has shown that within 6 years after graduation, about 70% of all graduates leave the hospitality industry. More widely set up research studies carried out in a large number of hotel organizations in the Netherlands seem to conﬁrm this tendency (Reijnders, 2003). From an international perspective, Walsh and Taylor (2007) also suggest that retaining highly educated staff is becoming a primary challenge for the hospitality industry. In addition, Hoque (1999a, 1999b) emphasizes the importance of HRM for the retention and the development of highly educated staff. This phenomenon of an increasing management-level turnover rate is not only related to the hospitality industry, but also becoming important in other industries. The changes in the employee–employer relationship are a result of the rapid changes in society and industries in the last 30 years (Ten Brink, 2004; Schalk, 2005; Torka, 2003). Before the 1980s, the employee–employer relationship was stable and predictable. Job security and promotion were offered by the employer, and employees offered hard work and loyalty (Herriot & Pemberton, 1996; Sims, 1994). Since the 1980s, organizations have increasingly been confronted with a changing environment and increasing competition, resulting in a continuous struggle for survival. Employees were allowed to stay with an employer if they could add value to the organization in different roles, thereby becoming more employable (Hiltrop, 1996). As a result, employees were willing to work for an employer if they were provided with enough opportunities for development and were able to improve their ‘‘market value’’ (Hall & Mirvis, 1995; Sims, 1994; Gasperz & Ott, 1996). Thus, it seems that since the 1980s, the employee–employer relationship has become more individualized with a greater emphasis on ﬂexibility and employability (Anderson & Schalk, 1998; Sparrow, 2000; Roehling, Cavanaugh, Moynihan, & Boswell, 2000). Ten Brink (2004) argues that periods of economic prosperity and the increasing scarcity of highly competent personnel have caused the position of employees to become stronger compared with that in previous decades.

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5

The Importance of Keeping Management-Level Turnover Low Although management-level turnover is inevitable, a high turnover has a signiﬁcant negative impact on the productivity and proﬁts of an organization. Hillmer, Hillmer, and McRoberts (2005) suggest that the costs of hiring and supervising a new replacement co-worker, rather than dealing with a coworker who is leaving, can amount to 70% of his annual salary. This ﬁgure is supported by Hinkin and Tracey (2000, 2006). In addition, a high turnover rate may lead to the erosion of the company’s implicit knowledge base (Coff, 1997), which is one of the important key variables for competitive advantage (Barney, 1991, 1992; Reed & DeFillippi, 1990; Lado & Wilson, 1994; Sanchez & Heene, 1996, 1997; Blomme, 2003). In the resource-based view as an inﬂuential research stream within strategy literature (de Wit, 1994; Shore, Porter, & Zahra, 2005; Barney, 1991), the accumulation and deployment of valuable and rare intangible and tangible resources, which are difﬁcult to imitate, are a way of gaining competitive advantage (Blomme, 2003; Zahra & Nielsen, 2002). Intangible resources occupy a central role in the resource-based perspective (Blomme, 2003; Grant, 1991; Reed & DeFillippi, 1990). Intangible resources are hard to imitate because they are not visible at ﬁrst sight, and even when they are spotted, competitors can hardly decipher which resources are being used and how they are used (Reed & DeFillippi, 1990). Also, the development cycle is hard to compress for some intangibles (Shore et al., 2005). Hence, an organization’s human resources are a prime intangible resource to look for competitive advantage because they take time to develop, and are hard for outsiders to understand and difﬁcult to imitate. Human resources also form an important leverage for the organization to develop and utilize other key assets in ways that create and sustain a competitive advantage (Blomme, 2003; Zahra & George, 2002; Lado & Wilson, 1994). The possibilities for leverage can be described as the organization’s capabilities (Dierickx & Cool, 1989). The way in which intangible resources, which may lead to competitive advantage, can be leveraged can be described as organizational competencies (Nelson, 1991; Rumelt, 1987; Blomme, 2003), core competencies (Prahalad & Hamel, 1980; Sanchez & Heene, 1997), organizational capabilities (Stalk, Evans, & Shulman, 1992; Ulrich & Lake, 1990), or organizational capital (Prescott & Visscher, 1980; Ranson, 1987). A highly skilled labour force can harness and exploit service-based competencies in ways that lead to competitive advantage (Blomme, 2003; Lado & Wilson, 1994; Barney, 1986).

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Other strategic streams seem to conﬁrm that human capital is an important variable in creating added value and competitive advantage (Becker & Gerhart, 1996; Miles & Snow, 1978). Research studies on the relation between investments in human capital and the ﬁrm’s performance seem to provide evidence that human resources are an important variable (Huselid, 1995; Delery & Dotty, 1996; MacDufﬁe & Kochan, 1991; Snell & Dean, 1992). Lado and Wilson (1994) argue that organizations that are unable to hire and retain highly skilled staff will either hinder or possibly destroy the development of organizational competencies and competitive advantage. Both the speciﬁc skills of employees and the amount of trust in the employee–employer relationship provide an indication as to whether or not organizational competencies will be enhanced or diminished (Lado & Wilson, 1994; Walton, 1985; Blomme, 2003, p. 106). As such, we can argue that the nature of the employment relationship is an important variable for the construction of organizational competencies and competitive advantage.

The Employment Relationship The construction and maintenance of mutual commitment in the employment relationship are important indicators for employee turnover (Meyer & Allen, 1997). The way in which commitment is built in the employment relationship has been the topic of several research studies (Rousseau, 1989; Guest, 1998; Robinson, 1996). Coyle-Shapiro, Taylor, Shore, and Tetrick (2005) distinguish ﬁve perspectives on the employment relationship and the way in which trust is built. These are: the social exchange perspective, the justice view perspective, the industrial relations perspective, the legal perspective and the economic perspective. The ﬁrst perspective is the social exchange view, in which the employment relationship is considered as an exchange of tangible and intangible beneﬁts (Coyle-Shapiro et al., 2005; Shore & Coyle-Shapiro, 2003). The emphasis on the exchange of intangible beneﬁts makes this perspective differ from the economic exchange perspective. Eisenberger, Huntington, Hutchioson, and Sowa (1986) argue that the fulﬁlment of important socio-emotional needs is similar to the fulﬁlment of the individual needs for respect, caring and support in interpersonal relationships. Trust and the norm of reciprocity are the basis for this type of exchange (Huiskamp & Schalk, 2002). Another perspective is the justice view of the employment relationship. In this view, a justice perspective captures how individuals perceive their exchange relationship in terms of reciprocal fairness (Coyle-Shapiro et al.,

Predictors of Turnover Intentions of Highly Educated Employees

7

2005, p. 120). Folger and Cropanzano (1998) argue that in this view, not only the perceived reciprocal fairness should be considered but also the moral mandates about social conduct held by society in general, which is an important regulator of the perceived fairness of management actions. The third perspective is the industrial view of the employment relationship. The key assumptions are the existence of an inherent conﬂict between employer and employee and the perspective that employer and employees are collective parties involved in continuous negotiation processes (Kelly, 2005). The industrial view tends to emphasize the regulation of the relationship at national, industrial and organizational levels. The legal view tends to emphasize the legal aspect of the employment relationship. The ways in which the expectations and obligations between the individual employee and the employer are justiﬁed and legally contracted are the object of this perspective. The last perspective is the economic view of the employment relationship. In the economic view, the employee and the employer are two distinctive parties who strive to maximize the beneﬁts in their relationship (Block, Berg, & Belman, 2005). Employers seek to maximize proﬁt and only participate in different forms of employment relationship if this increases competitive advantage. The employee party, as a collective or individual, seeks to maximize the utility of his returns by engaging in different forms of labour participation depending on the wage offered (Coyle-Shapiro et al., 2005). The tangible beneﬁts are emphasized in this perspective. However, these ﬁve perspectives use different angles. When using them to understand management-level turnover in the hospitality industry, their use as a complementary framework can provide a more comprehensive lens through which the employment relationship can be viewed. In this uniﬁed perspective, the individual – inﬂuenced by societal values – is part of a collective, interacting with the employer, who, in turn, is subject to market competition and is located in a societal and cultural context. Tangible and intangible assets are a part of the interaction process, and it is the extent to which expectations and perceptions are met that leads to the development of trust in the relationship. One particular approach which is aligned with this uniﬁed perspective is the perspective of the psychological contract.

The Psychological Contract The concept of the psychological contract originates from the 1960s. Argyris (1960) conducted a research study on the relationship between plant

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foremen and their employees. His research study led to the assumption that, when a foreman used a more ‘‘understanding’’ management style respecting the informal culture of the employees’ workgroup, a relationship would develop whereby employees would exchange higher productivity and fewer grievances for the foreman’s willingness to provide acceptable wages and job security. Argyris considered this relationship as the psychological work contract (Argyris, 1960, pp. 95–96). Levinson was another researcher who conducted research into the psychological contract (Levinson, Price, Munden, Mandl, & Solley, 1962). Levinson et al. used an interview methodology and examined a sample of more than 800 employees of privately owned organizations to investigate the kinds of experiences employees undergo at work and the consequences these have on their mental health. The research study emphasized the intangible aspects of work and conceptualized an informal agreement between an individual employee and the organization employing him, whereby each party held expectations of the other that originated prior to employment, and if fulﬁlled, satisﬁed their needs in the relationship. This informal agreement, which can be considered as a psychological contract, provides the structure and support that each party needs to satisfy a natural need for dependence and the need to be allowed to negotiate over this dependence over time. Schein (1965, 1970, 1980, 2001) was also an important contributor to the psychological contract. Schein maintains that the contract is a critical foundation for the employment relationship. His important contributions were the emphasis on the importance of a strong match between each party’s expectations, the importance for each party to be allowed to retain some power to enforce each view of the contract and the criticality of the contract as an interaction between parties and thus the importance of considering the perspective of each (Schein, 1970). Schein emphasized the interactive nature of the contract and stressed the need to be cautious and to focus only on one party’s perspective. Although the three authors mentioned above introduced a new approach with regard to the employment relationship in this period, their work can be characterized by limited conceptualization and virtually no empirical research. Rousseau (1989) conceptualized the psychological contract as an individual-level cognition and made this the object of her research studies. Focusing on employee’s perceptions, she deﬁnes the psychological contract in terms of ‘‘individual beliefs regarding the terms and conditions of a reciprocal agreement between that focal person and another party’’ or as

Predictors of Turnover Intentions of Highly Educated Employees

9

‘‘individual beliefs in a reciprocal obligation between the individual and the organization’’ (Rousseau, 1989, pp. 121–123). Morrison and Robinson (1997) deﬁne the psychological contract as the employee’s beliefs about reciprocal and promissory obligations between himself and the organization. Although the psychological contract is an individual-level construct, it reﬂects beliefs about tangible and intangible items that are to be exchanged in the context of a dyadic relationship. According to Rousseau (1995, p. 6), obligations are commitments to future action and refer to attitudes and intentions. The emphasis on the employee’s belief about what should be exchanged is an important characteristic of the psychological contract (Robinson, 1996). Another important characteristic is that the psychological contract is inherently perceptual and subjective (Rousseau, 1989; Ten Brink, 2004). Shore and Tetrick (1994) stressed that this was a set of beliefs shaped by multiple sources of input and by cognitive and perceptual biases. As such, a psychological contract may differ from the formal, written legal contract but is very real to the individuals who hold them. Behaviour and attitudes are inﬂuenced quite signiﬁcantly by an individual’s perception of his obligations, and perceptions of how well the other party’s obligations have been fulﬁlled (Morrison & Robinson, 2005; Shore & Tetrick, 1994; Robinson, 1996; Lester, Turnley, Bloodgood, & Bolino, 2002; Tekleab & Taylor, 2003). The lack of fulﬁlment of aspects of the psychological contract will lead to a violation of the contract, with a change in attitudes and of behaviour as a consequence (Rousseau, 1989; Morrison & Robinson, 1997). Rousseau (1989) suggests that a violation of the psychological contract may lead to strong emotional reactions such as anger, resentment and a sense of injustice. Regarding behaviour, Robinson and Rousseau (1994) conducted a research study in which they found that violation of the psychological contract may lead to an increase in employee turnover. As such, the notion of a psychological contract provides a framework within which behaviour and employee attitudes, such as the intention to leave an organization, can be researched and interpreted (Korcynzski, 2002; Hancer & George Thomas, 2003).

The Use of the Psychological Contract within the Hospitality Industry Research studies on highly educated staff turnover in the hospitality industry often concentrate on the numbers of employees who are moving from one organization to another within the hospitality industry or to other industries. Highly educated staff can be deﬁned as employees who have

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followed a higher education at a bachelor’s or master’s level successfully (Hoque 1999a, 1999b; Reijnders, 2003; Blomme, 2006). Lucas and Deery (2004) argue that little research has been done on the motivation of these mobile employees, which can lead to employees actually leaving within the context of the psychological contract of employees and the possible violations of the contract (Hancer & George Thomas, 2003). The few research studies which have been done on the retention of highly educated staff and the role of HRM in this are often related to the hospitality industry in a speciﬁc country (Hoque, 1999a, 1999b; McGunnicle & Jameson, 2000). A positive exception is the research study done by Walsh and Taylor (2007) among 718 graduates of Cornell University School of Hotel Administration on the relation between the commitment of the employee and the intention to leave. Although they did not mention the concept of the psychological contract, they made use of several related elements. In this research study, a strong relation was found between the intrinsic aspects of the job and the intention to leave (Walsh & Taylor, 2007, p. 177). Employees look for learning opportunities, and therefore challenging jobs prevent highly educated staff from leaving.

Empirical Research Design In empirical research, many researchers (Coyle-Shapiro, 2001; Craig & Tetrick, 1999; Robinson, 1995, 1996; Robinson & Rousseau, 1994; Robinson & Morrison, 2000; Tekleab & Taylor, 2001) have used or based their measuring constructs of the psychological contract on Rousseau’s questionnaire (1990). Some researchers have added employer’s obligations to Rousseau’s constructs of the psychological contract. One speciﬁc attempt to cover a broad set of frequently used elements of the psychological contract is Van Dijk’s questionnaire (1997), which was based on the research studies carried out by Schalk, Frees, and Van den Bosch (1995) and on items found in the literature (Herriot, Manning, & Kidd, 1997; Morrison & Robinson, 1997; Rousseau, 1990). Van Dijk (1997) distinguishes 11 items in the psychological contract. These are: job content, development opportunities, job security, work climate, intra-organizational mobility, work– family balance, autonomy, salary, performance-related pay, clarity about the task, and promotion opportunities. Besides these 11 items, affective commitment can also be a strong predictor for employee attitudes and behavioural intentions (Meyer & Allen, 1997; Ten Brink, 2004). Furthermore,

Predictors of Turnover Intentions of Highly Educated Employees

11

different attempts have been made to conduct empirical research studies on the employee’s attitudes and behavioural intentions based on Rousseau’s (1990) constructs (Herriot et al., 1997; Kotter, 1973). As such, two research objectives can be highlighted: the relation between items of the psychological contract and the intention to leave, and the relation between affective commitment and the intention to leave. Apart from the scarce use of the psychological contract in research studies as a framework in the hospitality industry to explain employee turnover, not much attention has been paid to the relation between age and the related phase in the life course and the psychological contract of employees working in the hospitality industry. For example, in the research study Walsh and Taylor (2007), no distinction is made among the respondents based on age. Nemiroff and Colarusso (1990) suggest that, during adulthood, the perspectives of human beings change dynamically as they get older. Different research studies (Gould, 1978; Levinson, 1978) suggest that different stages in adulthood can be distinguished. Each stage has a core theme as an attractor for the development process. Roughly, three stages for adulthood can be distinguished (Freese & Schalk, 1995). The early adulthood stage (22–32 years) can be described as the age at which founding a family and building a career are the main themes. In the middle adulthood stage (33–44 years), more attention is given to family life and the education of children. The value of having a career decreases, and the importance of work pleasure, social recognition and self-actualization grows. In the late adulthood stage (45–65 years), besides work pleasure, the balance between autonomy and interdependency becomes more important (Sekaran & Hall, 1989). Empirical research studies (Freese & Schalk, 1995) in different industries conﬁrmed this categorization of age groups. Also, exploratory research studies to the psychological contract of highly educated employees in the hospitality industry seemed to support this categorization of age groups for further research (Reijnders, 2003; Blomme, 2006). Schalk (2005) indicates that these changing perspectives and needs will lead to a change in ideas and needs about important obligations of the employer and themselves. Hence, the psychological contract of employees will change during the life course (Huiskamp & Schalk, 2002). The predicting variables for turnover intentions will be different for each stage of development. Hence, a third research objective can be put forward: the inﬂuence of age on the relationship between the psychological contract and the intention to leave.

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Research Objectives We are examining: (1) The predictors in the psychological contract for the intention to leave. (2) The relation between affective commitment and the intention to leave. (3) The inﬂuence of age on the relationship between the psychological contract and the intention to leave.

METHODOLOGY Sampling Data for this study was collected in December 2005 with the help of the alumni of Hotelschool The Hague. A total of 4,192 registered alumni were invited by mail to ﬁll in the online questionnaire using a personal code. Out of these 4,192 alumni, 2,231 alumni were above the age of 65 or deceased. In total, 1,961 alumni belonged to the age category of 22–65. The respondents were graduates of the Hotelschool The Hague, who were working all over the world. In total, 580 people ﬁlled in the questionnaire between 3 February 2006 and 21 March 2006, majority (83%) of which responded before the end of February. After the closing of the questionnaire, we had a response rate of 29.5%. A large amount of mail (approximately 200 letters) was returned because of faulty addresses, which would have otherwise increased the response rate a little. We distinguished three groups of graduates based on questions in the questionnaire as to whether they worked inside or outside the hospitality industry (‘‘Did you work in the Hospitality Industry after leaving school?’’ and ‘‘Do you work in the Hospitality Industry nowadays?’’). In this paper, we will only consider the group of people who worked in the hospitality industry after graduation and who still work there.

The Instrument The questionnaire started off with speciﬁc questions on the respondent’s gender, exact age and current position. Following these opening questions, we continued with questions related to the measures of the psychological contract and two measures of employee obligation: external mobility

Predictors of Turnover Intentions of Highly Educated Employees

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intentions and affective commitment. These are measured using a validated questionnaire from Ten Brink (2004). Ten Brink based this on a questionnaire developed by Van Dijk (1997), who in turn based his questionnaire on Schalk et al. (1995) and on items found in the literature (Herriot et al., 1997; Meyer & Allen, 1997; Morrison & Robinson, 1997; Porter, 1980; Rousseau, 1990). The scale of affective commitment is based on a Dutch translation of the commitment questionnaire developed by Meyer and Allen (1997; see Den Hartog, 1997). The scale of external mobility intentions is based on a questionnaire by Ten Brink (2004). In Table 1, the 11 psychological contract scales, affective commitment and intention to leave are presented along with an example question (item). The respondents had to answer these questions with the same 5-point Likert scale, 1 (totally disagree) to 5 (totally agree). This shows the number of items per scale, using Cronbach’s alphas, and means and standard deviations. The reliabilities of the scales are more than sufﬁcient, as all Cronbach’s alphas are well above .75.

Data Analysis We used the Statistical Package for Social Sciences (SPSS; Windows 14.0 software) for statistical analyses. Mean scores and Pearson correlations were computed for all psychological contract variables, affective commitment and intention to leave. Multiple regression analyses were used to examine the contribution of the psychological contract variables in explaining both intentions to leave for the total group of respondents and for different age groups. Using the Baron and Kenny (1986) method, we tested whether affective commitment mediates the relationship between the psychological contract variables and the intention to leave.

RESULTS AND ANALYSIS Respondents A total of 247 (12.6%) valid respondents have been used in the analysis. The characteristics of the respondents are provided in Table 2. Of them, 64% of the respondents are male and 36% are female. Most respondents are in the age groups 22–32 and 33–44 (mean=39.7). The working status indicates that our analysis is not only about the ‘‘working conditions’’

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Table 1.

Scales of Psychological Contract and Employee Obligation. Scales

Psychological contract 1 Job content, e.g. My organization offers me comprehensive and diverse work 2 Development opportunity, e.g. My organization offers me work that gives me the opportunity to learn 3 Job security, e.g. My organization offers me an employment contract offering job security 4 Intra-organizational mobility, e.g. My organization offers me support with intra-organizational mobility 5 Work–family balance, e.g. My organization offers me policies that support working parents 6 Work atmosphere, e.g. My organization offers me a good working atmosphere and nice colleagues 7 Autonomy, e.g. My organization offers me the freedom to give my work a personal interpretation 8 Salary, e.g. My organization offers me a competitive salary 9 Performance-related pay, e.g. My organization offers me performancerelated pay 10 Clear task description, e.g. My organization offers me a clear description of the task 11 Promotion opportunity, e.g. My organization offers me promotion opportunities Employee obligation 12 Affective commitment, e.g. I really feel as if the organization’s problems are my own 13 Intention to leave, e.g. I look at vacancies for jobs in other organizations

No. of Items

Cronbach’s Alpha

Mean

SD

4

.859

4.32

.56

7

.884

3.72

.75

3.39

1.13

1

3

.863

3.39

.91

4

.766

3.26

.84

7

.883

3.89

.66

3

.851

4.20

.64

2

.773

3.01

.96

3.17

1.24

3.43

.91

3.43

1.04

1

3

.878

1

9

.898

3.71

.72

6

.924

2.65

.95

in the hospitality industry in The Netherlands (56%), but also about the ‘‘working conditions’’ of those in the entire international hospitality business (both in Europe and the rest of the world (26 and 18% respectively).

Predictors of Turnover Intentions of Highly Educated Employees

Table 2.

Gender Male Female Age

15

Descriptive Analysis. N

%

157 90

64 36

Age groups 22–32 33–44 45–65

105 86 56

43 35 23

Working status The Netherlands Rest of Europe (not NL) Rest of the world (not Europe)

138 63 45

56 26 18

Mean

SD

39.3

9.87

Bivariate Correlations Inter-correlations of the psychological contract measures and employee obligations are presented in Table 3. Moderate to strong correlations were found between job content, development opportunities, work atmosphere, autonomy and promotion opportunities on the one hand, and affective commitment and intention to leave on the other. The more positive the respondents were about these job elements, the higher their score on affective commitment and the lower their score on intention to leave. Weaker correlations were found for the ‘‘remaining’’ psychological contract measures and affective commitment and intention to leave. In addition, affective commitment and intention to leave are highly correlated (r= .60, po.000).

Regression Analyses Multiple regression analyses were conducted to examine which psychological contract measures explain the most variance in intention to leave (Table 4). The analyses were controlled for age and gender. In the total group of respondents, job content and promotion opportunities were found to be signiﬁcant predictors, explaining 35.8% of the variance in intention to leave. The more positive the respondents were about their job content and promotion opportunities, the less were their intentions to leave the

0.54 0.37

0.23 0.28

0.18

0.47

0.49 0.21 0.20

0.31

0.30

0.20 0.21

0.21

0.39

0.38 0.29 0.20

0.19

0.32

2.

0.51 0.37

0.60

po.001; po.01; po.05.

1. Intention to leave 2. Affective commitment 3. Job content 4. Development opportunity 5. Job security 6. Intraorganizational mobility 7. Work–family balance 8. Work atmosphere 9. Autonomy 10. Salary 11. Performancerelated pay 12. Clear task description 13. Promotion opportunities

1.

Table 3.

0.46

0.29

0.53 0.21 0.25

0.59

0.18

0.33 0.39

0.66

3.

0.68

0.46

0.46 0.28 0.33

0.66

0.12

0.41 0.56

4.

0.34

0.27

0.23 0.20 0.10

0.39

0.12

0.42

5.

0.61

0.26

0.28 0.13 0.26

0.40

0.07

6.

0.01

0.08

0.19 0.16 0.05

0.25

7.

0.52

0.48

0.67 0.30 0.36

8.

0.31

0.29

0.22 0.24

9.

Pearson Inter-Correlations among Study Variables.

0.35

0.25

0.51

10.

0.37

0.24

11.

0.34

12.

16 ROBERT J. BLOMME ET AL.

35.8% 34.7% 33.73

44.9% 43.8% 39.33

0.10

0.29

0.40

0.11 0.07

b

b

44.8% 42.0% 16.04

0.41 0.22 0.17

_

0.20 0.12

b

a

49.1% 46.5% 19.08

0.29 0.23

0.41

0.18 0.14

b

b

22–32 Years (n=105)

26.9% 23.3% 7.47

0.27

0.41

_

0.04 0.10

b

a

36.3% 33.2% 11.57

0.24

0.52

0.05 0.09

b

b

33–44 Years (n=86)

39.8% 35.1% 8.44

0.26

0.57

_

0.13 0.13

ba

57.9% 53.6% 13.73

0.28

0.32

0.53

0.02 0.01

bb

45–65 Years (n=56)

Note: Values are standardized regression coefﬁcients (b) of the ﬁnal model with signiﬁcance of t, except for the regression model where rows represent R2 and F values. po.001; po.01; po.05. a Regression analysis without affective commitment, corrected for age and gender, psychological contract measures entered stepwise. b Regression analysis including affective commitment, corrected for age and gender, psychological contract measures entered stepwise.

Regression model Explained variance R2 Adjusted R2 F value

0.45 0.14

_

Step 2 Affective commitment

Step 3 Job content Promotion opportunities Salary Work–family balance Performance-related pay

0.27 0.08

b

a

Total Group (N=247)

Separate Hierarchical Stepwise Regression Analyses to Explain Intention to Leave for the Total Group and for Different Age Groups.

Step 1 Age Gender

Table 4.

Predictors of Turnover Intentions of Highly Educated Employees 17

18

ROBERT J. BLOMME ET AL.

organization. In a second analysis, affective commitment was entered before the psychological contract measures to test for mediation. It was found that affective commitment partially mediated the relationship between job content (as well as age) and intention to leave, as the beta coefﬁcient dropped from .43 to .25 ( .27 to .11) and the signiﬁcance level dropped from po.001 to po.01 (po.001 to po.05). Also, affective commitment mediated the relationship between promotion opportunities and intention to leave, as the beta coefﬁcient is no longer signiﬁcant. Salary popped up merely as a signiﬁcant predictor; the more positive the respondents were about their salary, the less were their intentions to leave. To explore whether the psychological contract measures are equally important in different stages of adulthood, we conducted the same analyses for three different age groups. In the youngest age group (22–32 years), job content, salary and promotion opportunities best explained the intention to leave, where job content was totally mediated by affective commitment (R2=49.1%, po.000). In the age group 33–44 years, the most important variables explaining the intention to leave were job content and work–family balance where, again, job content is entirely mediated by affective commitment (R2=36.3%, po.000). Thus, besides high scores on job content, high scores on work–family balance go together with low scores on intention to leave for this age group. For the oldest group (45–65 years), intention to leave was best explained by job content and performance-related pay (R2=57.9%, po.000). The more the organization offers performancerelated pay, the higher the intention to leave. Job content was partially mediated by affective commitment, as the beta coefﬁcient dropped from .57 to .32.

IMPLICATIONS AND CONCLUSIONS Theoretical Implications This analysis has demonstrated that psychological contract measures can explain a substantial amount of variance in intention to leave the organization among highly educated hotel employees, especially when the mediating role of affective commitment is taken into account. In addition, the exploratory analyses revealed that at different stages of adulthood, different factors might play a role when considering the intention to leave the organization.

Predictors of Turnover Intentions of Highly Educated Employees

19

Of all the psychological contract measures, job content appeared to be the most signiﬁcant predictor of the intention to leave, followed, to a lesser extent, by promotion opportunities and salary. Thus, the greater the extent to which individuals ﬁnd that their jobs include challenging, comprehensive and diverse work, the less likely they are to leave their organizations. This effect was partially mediated by affective commitment, i.e. the more that respondents perceive their job as one which includes challenging, comprehensive and diverse work, the more they are committed to the organization, and in turn, the less likely they are to leave the organization. This is in line with the study by Walsh and Taylor (2007), who found that challenging work was an important factor inﬂuencing affective commitment, organizational commitment and, in turn, turnover intentions. Walsh and Taylor used a more comprehensive deﬁnition of challenging work, including development opportunities and autonomy. Indeed, these aspects are highly correlated with job content, and as such, did not emerge as a separate explanatory variable in our analyses. It is striking that the scores on job content are relatively high compared with employees in other organizations (527 manufacturing, government, hospital and bank employees and farmers in Ten Brink (2004)), reﬂected in the high mean score and the range that extended from 3 to 5 on a 5-point scale. Thus, even the most negative respondents had a neutral attitude towards the item to what extent their jobs include challenging, comprehensive and diverse work. Nevertheless, neutral or slightly positive attitudes were related to high turnover intentions. In terms of the psychological contract, this might mean that the expectations among hotel management school alumni are rather high, and that a slight violation of this expectation towards the negative side is what makes them consider leaving the organization. Promotion opportunities and salary were also related to turnover intentions. The more the respondents agreed to the fact that their organization offered them promotion opportunities and competitive salaries, the less inclined they were to consider leaving the organization. Although these results may partly be caused by an overrepresentation of younger respondents, for which these factors are particularly important (see later in this discussion), additional analyses revealed that the interaction between age and these two factors were non-signiﬁcant. Thus, it seems that promotion opportunities and salary play a role with regard to intention to leave for individuals in the 33–44 age group as well, although these factors play a less signiﬁcant role for the youngest respondents. It was shown that affective commitment is an important variable in explaining the intention to leave (Meyer & Allen, 1997; Guest, 1998;

20

ROBERT J. BLOMME ET AL.

Ten Brink, 2004; Walsh & Taylor 2007). From the correlation analyses, it can be concluded that job content, autonomy, work atmosphere and development opportunities are moderately to strongly related to affective commitment to the organization. These ﬁndings are supported by the studies of Ten Brink (2004) and Walsh and Taylor (2007). As was found in their studies, extrinsic rewards like salary showed weak correlations with affective commitment to the organization. Other important factors to consider when explaining affective commitment are management-related support, communication, trust and conﬁdence (Ten Brink, 2004; Walsh & Taylor, 2007). These factors were found to be directly related to affective commitment, and were also found to operate as a mediating variable between psychological contract measures and affective commitment. These latter factors might also be more directly related to intention to leave, but this requires further study. Age was a signiﬁcant variable in explaining the intention to leave the organization. The younger the respondents, the more likely they were to leave the organization. This effect was also partially mediated by affective commitment: the younger the respondents, the less committed they were to their organization and the higher were the intentions to leave. In addition, age seems to be a moderator variable, as in different age groups, different factors are important in explaining the intention to leave. This is in line with the theoretical conceptions discussed in the introduction (Freese & Schalk, 1995). However, job content is the most important explanatory variable for each age group. Although it should be borne in mind that the sample sizes of the three subgroups are small, these analyses resulted in some meaningful ﬁndings. In the youngest age group, in which the respondents had just started their career, promotion opportunities and salary seem to be important additional factors in explaining the intention to leave. This is in line with a previous research study carried out by Freese and Schalk (1995). In the age group 33–44 years, work–family balance was an important additional variable in explaining the intention to leave. The higher these respondents rated the ﬂexibility to combine work and private matters, the less likely they were to leave the organization. These ﬁndings seem to support Schalk’s (2005) conceptual framework. For the older group (45–65 years), performance-related pay was an important additional explanatory variable after job content. The more they perceived their organization as having a policy of performance-related pay, the more likely they were to leave the organization. As discussed in the introduction, the need to become more autonomous with regard to choice of goal and interesting activities may be a possible reason for this relationship (Sekaran & Hall, 1989).

Predictors of Turnover Intentions of Highly Educated Employees

21

Additional analyses showed that both the interaction between work–family balance and age, and between performance-related pay and age were signiﬁcant in explaining the intention to leave. A limitation of this study is that all the variables were measured at the same time, and thus one cannot infer any causal relationships. Although it seems likely that a positive attitude about the job content reduces turnover intentions, one cannot say this deﬁnitely unless it is tested in a longitudinal study. In addition, the attitude towards leaving the organization was measured as intentions. The decision of an individual to actually leave the organization might be dependent on other or additional factors. Here again, a longitudinal study in which the hotel employees are followed throughout their career would yield valuable results. Finally, in this study, job content has proven to be an important predictor. Although this study has shown the importance of job content, further research into the aspects that makes a job satisfactory is necessary.

Practical Implications The ﬁndings of this research study provide some important suggestions for managers in hospitality organizations to concentrate on the key predictors of the psychological contract for the explanation of turnover intentions. We can distinguish predictors for turnover intentions for all the age categories and the speciﬁc predictors for speciﬁc age categories. Before going into the practical implications, it is important to know how the psychological contract is inﬂuenced in an organization. According to Rousseau (1995), it is only the individuals who develop psychological contracts and not organizations. Organizations provide individuals with a context in which psychological contracts can evolve and develop. Rousseau (1995) describes this organizational context as contract makers. Primary contract makers are individuals who act as agents representing the organization and its policies, and inﬂuence psychological contracts by direct exchange and interaction (Rousseau, 1995; Guest, 1998). Secondary contract makers are administrative procedures such as business policies, organizational structure and HRM procedures. As such, the organization can inﬂuence the psychological contract of employees directly through its agents and indirectly through administrative contract makers. One of the strongest generic negative predictors for turnover intentions among all ages is job content, which is also an important predictor for affective commitment. A job refers to the extent to which employees are

22

ROBERT J. BLOMME ET AL.

satisﬁed with their jobs. One way of looking at satisfaction in the job is the job demands-control approach put forward by Karasek. Job satisfaction is dependent on two variables (Karasek, 1979; Fox, Dwyer, & Ganster, 1993): how much the job demands of employees and the possibilities for people to have control over their job. Excessive work demands can lead to higher levels of psychological strain and job dissatisfaction. The impact of these demands may be offset by the perception that one has control over important aspects of the job environment. Indeed, highly challenging and demanding work combined with high control is considered by Karasek (1979) to indicate an active job that has beneﬁcial outcomes for individuals. At the other extreme, low-demanding work with low levels of control will lead to strain and reduced job satisfaction. Also, the combination of highly demanding work with low levels of control will lead to strain because anxiety will be created about the job performance and the personal consequences of not completing the work in a speciﬁed time frame. Lowdemand work combined with high levels of control will lead to boredom and dissatisfaction. As such, jobs which are perceived as challenging and have enough possibilities for control may lead to a lower intention for employee turnover. The practical implication of this perspective for managers is the design of jobs. Because individuals will become more experienced and taskmature in a speciﬁc job over time, managers should design jobs with ﬂexible boundaries: employees can obtain more tasks in a speciﬁc job (e.g. activities, responsibilities, intrinsic development opportunities) with the provision of more control opportunities (e.g. autonomy, power). The other generic predictor, which has a negative relation with turnover intentions, is affective commitment. Empirical research into how primary and secondary contractors can affect affective commitment is scarce (Sonnenveld, 2006). The more conceptual literature on increasing affective commitment indicates the use of primary and secondary contract makers to get the interests of the employees aligned with the interests of the organization (Arthur, 1994; Huselid, 1995; Appelbaum, Bailey, Berg, & Kalleberg, 2000). The practical implications for management is to concentrate on the alignment of individual interests with the interests of the organization, and, as previously discussed, to pay attention to job content, which is an important positive predictor for affective commitment. In the 22–32 age category, salary and promotion opportunities are important negative predictors for turnover intentions. Individuals are building a career and family life, and salary and the opportunity for promotion to raise income are important in this stage of life. Practical implications for managers may be twofold. First, management should know

Predictors of Turnover Intentions of Highly Educated Employees

23

whether the promotion possibilities and salary heights in their organization are perceived as unfair by employees in comparison with the conditions in other industries. Too much perceived unfairness by employees with too little compensation from other job characteristics may lead to turnover intentions. Secondly, care should be taken in the communication in the recruitment process of new staff, to align the perceptions of new personnel with realistic possibilities for salary and promotion in the organization. Consistency in promises related to salary and promotion opportunities are important to prevent violation of the psychological contract (Rousseau, 1995). In the 33–44 age category, the family–work balance is a negative predictor for turnover intentions. Work in the hospitality industry is known to be hard and involves long working hours at irregular moments (Hoque, 1999a), which means that adjustments between work and family life may become troublesome. The practical implications for managers are that they should take into account the needs of employees in this age group by expanding the control possibilities for employees to adjust work life and family life. The use of secondary contract makers such as HRM policies may play an important role in preventing this aspect of the psychological contract from being violated. In the 45–65 age category, performance rewards are a positive predictor for turnover intentions. The practical implications for management may be to develop HRM policies to meet the demands of this category of employees.

Conclusions Turnover intentions can be explained with the concept of the psychological contract. The psychological contract can be used as a basis to deﬁne and to execute HRM in the hospitality industry. As a ﬁnal implication, managers need to realize that they are acting as primary contract makers, directly inﬂuencing not only policies and procedures, but also the development of the psychological contract of their employees. In this research study, insight into the possible predictors for turnover intentions have been provided, which can serve as a tool for HRM in hospitality organizations.

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Snell, S. A., & Dean, J. W. (1992). Integrated manufacturing and human resource management: A human capital perspective. Academy of Management Journal, 35, 457–504. Sparrow, P. R. (2000). The new employment contract: Psychological implications for future work. In: R. J. Burke & C. L. Cooper (Eds), The organization in crisis: Downsizing, restructuring and privatization. Oxford, UK: Blackwell. Sonnenveld, M. (2006). The signalling effect of HRM on psychological contracts of employees: A multi-level perspective. Ph.D. thesis. Rotterdam: Erasmus University. Stalk, G., Evans, P., & Shulman, L. E. (1992). Competing on capabilities: The next rules of corporate strategy. Harvard Business Review, 70(2), 57–69. Tekleab, A. G., & Taylor, M. S. (2001). Aren’t two parties in an employment relationship? Antecedents and consequences of organization–employee agreement on contract obligations and violations. Paper presented at the annual conference of the Academy of Management, Washington, DC. Tekleab, A. G., & Taylor, M. S. (2003). Easing the pain: Determinants and effects of psychological contract violation. Paper presented at the annual conference of the Academy of Management, Toronto. Ten Brink, B. E. H. (2004). Psychological contract: A useful concept? Ph.D. thesis. Amsterdam: Kurt Lewin Instituut Vrije Universiteit. Torka, N. (2003). Flexibel maar toch betrokken. Ph.D. thesis. Enschede: Twente University. Ulrich, D., & Lake, D. (1990). Organizational capability. New York, NY: Wiley. van Dijk, D. (1997). Vragenlijst psychologisch contract: Van flexibiliseren van de arbeid naar de ontwikkeling van een vragenlijst over het psychologisch contract. Master’s thesis. Amsterdam: Vrije Universiteit. Walton, R. E. (1985). From control to commitment in the workplace. Harvard Business Review, 63, 76–81. Walsh, K., & Taylor, M. S. (2007). Developing in-house careers and retaining management talent. What hospitality professionals want from their jobs? Cornell and Restaurant Administration Quarterly, 48(2), 163–182. Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203. Zahra, S. A., & Nielsen, A. P. (2002). Sources of capabilities, integration and technology commercialization. Strategy Management Journal, 23, 377–398.

EXPLORING UNSPOKEN WORDS: USING ZMET TO DEPICT FAMILY VACATIONER MENTAL MODELS Po-Ju Chen ABSTRACT This study adopted the Zaltman Metaphor Elicitation Technique (ZMET) because of its sophisticated imaging techniques in eliciting mental models. Scholars across disciplines have been exploring paradigms beyond positivism due to the question about the adequacy of quantitative measures to capture complete accounts and to deal with vital problems. The marketing literature also advocates the need of a new methodology to examine consumers’ underlying thought and behavior that might help alleviate the industry’s inability to translate research findings directly into practices. This study elicited tourists’ mental models, which were depicted on an integrated consensus map with three metaphoric themes. Marketers might translate these metaphoric themes directly into practices. The results of this study strongly support the use of qualitative methodology, more specifically the ZMET, as a means for obtaining the underlying tourists’ behavior that often remain far beyond the reach of traditional research methods.

Advances in Hospitality and Leisure, Volume 4, 29–51 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00002-7

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INTRODUCTION Demographic and individual lifestyle shifts have affected the hospitality and tourism industry. During the last half of the twentieth century, demographic changes led to alterations in family structure (Belch & Willis, 2002). Even though the family structure has changed and diversiﬁed (Chesworth, 2003; Gardyn, 2001; Kang & Hsu, 2005; Schneider & Vogt, 2005), the family is still the fundamental unit in our society (Zabriskie & Heyne, 2003). Further, people are now more interested in spending more quality time with their families (Zabriskie & Heyne, 2003). One way that families do this is to take vacations together (Gram, 2005). A national study in the USA showed that ‘‘73 percent of married-with-children adults have gone on a vacation with their spouse and kids at least once in the past year’’ (Gardyn, 2001, p. 44). In Europe, ‘‘large numbers of people, and particularly families with children, go away at least once a year (Aderhold, 2003)’’ (Gram, 2005, p. 2). Although family vacations are now shorter, they are more frequent (Belch & Willis, 2002). This trend has great inﬂuence on the marketing strategies of the travel and hospitality industry (Gardyn, 2001; Gram, 2005; Kang & Hsu, 2005; Seema, 2001). The travel and tourism industry has tailored its marketing strategies toward the family vacation market. For example, the hotel chain, Howard Johnson, has made the family leisure travel market (e.g., accommodations for multi-generation families) its primary target (Walsh, 2003) and Premier Cruise Line offers an entire ﬂeet of cruise ships for families with children (Zabriskie & Heyne, 2003). This increasing fascination with family vacations has raised questions about family members as consumers and as travelers (Belch & Willis, 2002). To date few studies have examined family travelers and their underlying behavior (Carr, 2006; Chesworth, 2003; Kang & Hsu, 2005; Madrigal, Havitz, & Howard, 1992; Nickerson & Jurowski, 2001). The lack of understanding of family vacationers’ travel behavior poses problems for hospitality and tourism marketers who want to increase their share of the family vacation market (Carr, 2006; Gardyn, 2001; Kang, Hsu, & Wolfe, 2003). Furthermore, research methodologies have been an issue among social science researchers.

Research Methodology Debate The quantitative–qualitative research debate among scholars across disciplines has been quietly taking place over the last 30 years. This debate has generated further understanding of the strengths and limitations of these

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techniques (Heath, 1998). While both quantitative and qualitative techniques are valid and useful research tools, quantitative has dominated scientiﬁc research for the last six decades (Walle, 1997). Qualitative methodology has been mostly adopted in studies where researchers ‘‘are interested in understanding and interpreting the meanings and experiences of their informants’’ (Spiggle, 1994, p. 492). Aaker, Kumar, and Day (2003), Creswell (1998), Spiggle (1994), and Schwandt (1997) have suggested that consumers’ feelings, thoughts, intentions, and behaviors can be obtained only through qualitative data collection methods. According to Chen (2006, p. 205), for the understandings and interpreting the meanings and experiences of tourists, researchers may: ‘‘use data collected through interviews, visual observations and written documents to build informants’ mental models for the understanding of social and cultural phenomena. An individual’s mind constructs ‘small-scale models’ of reality as a result of perception, imagination and knowledge in order to anticipate events, to reason, and to underlie explanation (Craik, 1943). Thus, individuals’ mental models represent their cognition, affects, and overt behavior, and therefore explain individuals’ underlying behavior (Johnson-Laird, 1983; Peter & Olson, 2001).’’ These particular needs of meanings and experiences in certain types of research have led scholars to choose qualitative, rather than quantitative, approaches. Moreover, the marketing literature has been debating about the need of a new methodology to examine consumers’ underlying thought and behavior that might alleviate the industry’s inability in translating research ﬁndings and theoretical knowledge directly into practices (Downward & Mearman, 2004; Pritchard & Havitz, 2006; Zaltman, 1997). Other scholars support this view. Jones’ (1995, p. 2) British Medical Journal editorial, on Pope and Mays’ (1995) articles on qualitative research, emphasizes that ‘‘while distinguishing between qualitative and quantitative techniques, [the authors] will emphasise that the two approaches should be regarded as complementary rather than competitive.’’ These debates of research tools have drawn the social sciences and humanities ‘‘closer together in a mutual focus on an interpretive, qualitative approach to research and theory’’ (Denzin, Dezin, & Lincoln, 2003, p. vii).

Qualitative Research in Hospitality and Tourism Most early tourism seminal work was based on ‘‘qualitative research (Boorstin, 1964; Cohen, 1972, 1973, 1979; Graburn, 1976, 1983; MacCannell, 1973, 1976; Smith, 1977)’’ and was ‘‘published in non-tourism journals [e.g., sociology]’’

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(Riley & Love, 2000, p. 165). Riley and Love also report that, ‘‘tourism researchers were less familiar with qualitative methods than researchers are today’’ (p. 165). Social science research has struggled for decades to accept the qualitative research methodology. Jones (1995, p. 2) argues that ‘‘scientists have had difﬁculty in accepting the research methodologies of the social sciences, in which the generation of hypotheses often replaces the testing of hypotheses, explanation replaces measurement, and understanding replaces generalisability.’’ Furthermore, the qualitative methodology has been widely adopted, but not so much in the United States and Canada (Maykut & Morehouse, 1994). This under-utilization of qualitative methodology is more apparent in tourism and hospitality research (DeCrop, 1999; Walle, 1997). Based on a cursory review of publications in tourism-related journals, Riley and Love (2000, p. 175) ﬁnd that less than 5% of the literature published in Journal of Travel Research, Tourism Management, and Journal of Travel and Tourism Marketing is qualitative and about 20% of the articles in Annals of Tourism Research are qualitative. This situation has started to change. Several social science scholars have questioned ‘‘the adequacy of quantitative measures to capture complete accounts (Jamal & Hollinshead, 2001)’’ of tourists’ underlying experiences due to critiques about, for example, the ‘‘statistical abstraction and measurement validity, which question whether quantitative analyses are able to ‘fully address questions of understanding and meaning’ in the experience (Riley & Love, 2000, p. 166)’’ (Pritchard & Havitz, 2006, p. 26). These ‘‘purely statistical tools are being supplemented with more qualitative methods’’ because quantitative/rigorous methods ‘‘are often incapable of dealing with vital problems facing marketing and tourism scholars’’ and ‘‘disciplines close to tourism (such as marketing) have had to deal with similar issues’’ (Walle, 1997, p. 526). Pritchard and Havitz (2006, p. 31) argue that researchers who encountered problems by using quantitative methods have often considered ‘‘the merit of using qualitative data to evaluate experience (Seaton, 1997).’’ It has also been argued that ‘‘different methods of analysis can be indicative of different levels of abstraction of a layered tourism reality’’ (Downward & Mearman, 2004, p. 119). Thus, the interest in qualitative research has increased several fold among North American social scientists (Creswell, 1998; Denzin et al., 2003; Downward & Mearman, 2004; Gerrish, Lacey, & Weinberg, 2006; Riley & Love, 2000; Walle, 1997). Study Objectives The need for a better understanding of family vacationers’ underlying behaviors and the merits of using qualitative methodology to obtain such

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meanings and experiences require the attention of hospitality and tourism researchers. Thus, the objective of this study is to present a renovated, grounded, and relatively new qualitative research methodology, the Zaltman Metaphor Elicitation Technique (ZMET), in hospitality and tourism research and to elicit mental models of family vacationers. By adopting this relatively new methodology the author hopes to discover tourists’ inner experiences and underlying behaviors that could lead to alleviating the industry’s inability to translate research ﬁndings and theoretical knowledge directly into practices.

METHODOLOGY Research Tool Selection The ZMET is appropriate for this study because of a number of considerations. Firstly, qualitative research methods provide researchers with the tools to achieve a better understanding of the social and cultural contexts of people’s real lives (Myers, 1997). Secondly, tourists’ mental models can be obtained only through qualitative data collection methods (Aaker et al., 2003). Thirdly, the measurement of mental models can be best achieved through open-ended interview techniques (Kearney & Kaplan, 1997). Fourth, ZMET provides a set of grounded in-depth interview procedures under graphical image-guided conversation (Zaltman & Coulter, 1995). And ﬁnally, DeCrop and Snelders (2004, p. 1013) argue that the ‘‘major advantage of grounded theory over other qualitative methods is that it provides guidelines for rigorous data analysis with explicit procedures and research strategies.’’ ZMET also provides grounded theory guidelines (e.g., purposive sampling) and grounded research procedures (e.g., open coding) for trustworthiness and rigor in data collection and analysis. ZMET’s grounded procedures provide self-correcting mechanisms during data collection and data analysis phases, thus achieving the required rigor and trustworthiness of qualitative research (Chen, 2006; Creswell & Miller, 2000; Glaser, 1978; Johnson, 1997; Lincoln & Guba, 1985; Mathison, 1988; Patton, 2002; Walle, 1997; Zaltman & Coulter, 1995). The Zaltman Metaphor Elicitation Technique According to Zaltman and Coulter (1995), ZMET is a hybrid methodology built upon grounded theory. It supports theoretically based designs such as the use of photography (Denzin, 1989) and sensory images as metaphors

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(Damasio, 1994; Gibbs, 1994) for eliciting non-verbal communication and thoughts (thoughts occur as images), in-depth personal interviews (Fern, 1982; Mishler, 1986) for discovering hidden feelings and thoughts, the Kelly Repertory Grid (Kelly, 1963) for validity and reliability, and the laddering technique (Reynolds & Gutman, 1988) for eliciting deep constructs. This methodology employs ‘‘steps to establish credible qualitative research based on the guidelines set forth by Wallendorf and Belk (1989), Webb et al. (1981), Miles and Huberman (1994), Lincoln and Guba (1985), Kirk and Miller (1986), and Strauss and Corbin (1990)’’ (Zaltman & Coulter, 1995, p. 48). ZMET is capable of building the connections and skeletal structure that the traditional laddering technique provides, but can also provide more in-depth understanding of important personal constructs and their relationships. Researchers could use these discovered constructs and their relationships to build diagrams that depict consumers’ mental maps. ZMET is, therefore, designed to reveal consumers’ mental models through metaphors and to map these models for knowledge and marketing actions. Moreover, ZMET requires participants to gather and/or generate ‘‘images’’ to elicit and probe the metaphors that represent their thoughts and feelings about taking family vacations. According to Coulter, Zaltman, and Coulter (2001, p. 8) pictures or images represent lower-order concepts and the higher-order personal constructs and are used as the stimuli during the interview because ‘‘much communication is nonverbal and that pictures can serve as entry points for exploring customer concepts (Ball & Smith, 1992; Weiser, 1988).’’ These insights tend to be far deeper and clearer than the insights gained simply from verbal discussions. Therefore, by being part of the research team and using their own pictures to guide the interview, participants would provide more complete and accurate mental models.

ZMET Interview Technique Each interview is a one-on-one, graphical image-guided conversation. If the Participant brings in more than a prescribed number of pictures, she or he would be asked to sort the pictures representing similar concepts. Six steps of ZMET interview are employed to surface key constructs and determine their interrelationships. The steps of each interview are: (1) Storytelling: The participant is asked to tell a story about each of the pictures that she or he had collected for the interview. Each picture or image will be used as a guide or stimulus since thoughts and feelings are

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(3)

(4)

(5)

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activated from internal or external stimuli (Peter & Olson, 2001; Vitterso, Vorkinn, & Vistad, 2001). Most ZMET interviewers agreed that the interviewees were enthusiastic and ready to tell their stories. ‘‘Because human memory and communication is story-based (Schank, 1990) and Participants have been thinking about the topic for a week to 10 days, it is not surprising that Participants come to the interview with a particular agenda or story they want to tell’’ (Zaltman & Coulter, 1995, p. 41). Missed images and issues: The participant is asked to describe pictures that cannot be found and to describe stories that relates to each of the missing pictures. This step is important because the Participants might have difﬁculty obtaining the pertinent pictures during the preparation period. Metaphor elaboration: The participant is encouraged to explore additional thoughts and feelings embedded in his or her way of expression by being asked to widen the frame of one or more selected pictures and describe what else might enter the picture that reinforces the original idea. The metaphor-elicitation step is closely associated with visual stories or collages. This step probes the consumer’s subconscious mind to uncover hidden thoughts and feelings (Zaltman, 2003, p. 35). Sensory images: The participant is asked to use senses (taste, touch, smell, color, sound, emotional feeling) to describe their feelings and thoughts. It is the ‘‘concern how we perceive changes to pictures, sounds and forces over time. ‘Sound Metaphors’ and ‘Touch Metaphors’ are all concerned with direct mappings between a sensory artifact and some quantitative information. For example, a particular color, sound volume or surface hardness represents a particular data value’’ (Nesbitt, 2000, p. 28). Sensory metaphors are powerful mechanisms for bringing unconscious thought to the level of awareness at which verbal articulation can occur (Lakoff, 1993). The vignette: The participant is asked to create a short movie that describes his or her thoughts and feelings about the topic to be elicited. This step is ‘‘based on theories involving psychodrama (Hubel, 1988; Zeki, 1993)’’ and the fact that vignette analysis allows for ‘‘the elicitation of heretofore unrevealed thoughts, because different ideas might emerge with the activation of different areas of the brain (Collins, 1991, p. 9)’’ (Coulter et al., 2001, p. 8). The purpose of creating a vignette was to solicit additional understanding of Participants’ feelings and thoughts and to validate the information provided through storytelling.

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(6) The digital image: The participant is asked to create a summary image or collage from his or her own images to express important issues. When the reconstructed images are completed, the participant is then asked to tell stories that the images or collages represent, as if he or she were explaining the images to someone who has not been present during the interview. The interview steps are designed to uncover the research topic to be elicited (e.g., family vacationers’ mental models). Each step provides a different opportunity for identifying and understanding the participant. The following sections present this study’s sample selection, data collection, and data analysis as suggested by ZMET.

DATA COLLECTION Sample Criterion This study used purposive sampling, as prescribed by ZMET. Purposive sampling enhances sample coverage, seeks in-depth interview and information-rich cases, and provides a framework for analysis (Patton, 2002). Furthermore, under the purposive sampling technique the interviewer compares concepts discussed during an interview with those concepts recorded from prior interviews with other Participants. Thus, ‘‘these procedures enable researchers (interviewers) to judge whether theoretical saturation might have been achieved during an interview’’ (Chen, 2006, p. 207). As suggested by ZMET, 20 family vacationers, from two major tourism destinations, the USA and Aruba, were invited to participate in this study. All informants were either students of universities located at the two major tourism destinations or family members of students. A relatively small sample size of these invited informants should be sufﬁcient for this phenomenological study because they would ‘‘experience similar structural and social conditions’’ (Seidman, 1998, p. 48). Guest, Bunce, and Johnson (2006) suggest that for studies with the aim of understanding ‘‘common perceptions and experiences among a group of relatively homogeneous individuals, twelve interviews should sufﬁce’’ (p. 79). This study, with 20 Participants, exceeds the minimum number of samples to warrant data saturation.

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The selected informants (Participants) for this study consisted of members of both traditional (e.g., married couple with children) and non-traditional families (e.g., single parent with children) who had taken at least one vacation together in the past 12 months, and ranged in age from their late teens to their late ﬁfties. These Participants were of interest because they might share common perceptions and experiences, had an emotional attachment to their families, were highly involved in family leisure, and had potentially experienced the beneﬁts of taking family vacations. All Participants were asked to take 1 week to gather images or pictures that depicted their thoughts and feelings about family vacations. Each Participant was given an instruction letter stating the purpose of the interview and guidelines for gathering pictures and images. Some Participants had spent several hours and some others had spent a few days in preparation for the interview. Each participant brought more than nine pictures or images to the interview. For each Participant, an approximately two-hour, face-to-face interview was conducted under the graphical imageguided conversation.

Interviewing Steps and Procedures The sorting of pictures and the six steps of ZMET interview were employed to reveal their mental models with key constructs and their interrelationships. During interviews, Participants might be unwilling to answer questions, unable to answer questions (give inaccurate answers because the information is part of the subconscious mind), or reluctant to answer questions because they perceive those questions as an invasion of privacy or having a negative impact on their ego (Aaker et al., 2003; Dann, 1981). The means-end laddering technique provides the interviewer with the means to overcome such obstacles. In each step the interviewer used probes in laddering to uncover the relationships between concepts (see Reynolds & Gutman, 1988, for the laddering technique). It is important for the interviewer ‘‘to probe, not prompt, consumers’ thoughts and feelings. In probing, the interviewer encourages Participants to open up, to look through more windows on their thinking and share what they see’’ and an effective probe ‘‘enables participants to respond in multiple, often unexpected, ways’’ (Zaltman, 2003, p. 108). A laddering technique may use the ‘‘why’’ questions to go up the ladder and ‘‘how’’ questions to go down the ladder. For example, in an effort to ladder up from key concepts presented by study Participants, probes such

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as, ‘‘Why is ____ important to you?’’ may be used. Using this technique can lead to a deeper understanding of important constructs and their connections (relationships between constructs). The means-end laddering technique was used across all of ZMET interview process steps to discover and cross-validate the causal relationships among constructs. Participants’ underlying thoughts and feelings require researchers to elicit Participants’ non-verbal cues and to enable their thoughts as images. ZMET interview steps guided Participants to reveal their mental models with metaphors (concepts or constructs). The metaphors expressed by Participants provided the paths for researchers to uncover Participants’ underlying feelings and thoughts and the relationships between those concepts or constructs (Lakoff & Johnson, 1980; Ortony, 1993). Each interview was tape-recorded and transcribed.

DATA ANALYSIS Open Coding and Labeling Data analysis began with the Open Coding process. This process began with a detailed work on assembling of visual images in order to cross-examine Participants verbatim. Open Coding deals with labeling and categorizing of phenomena as described by the data sets (i.e., pictures and interview transcripts). Labeling of concepts was an important task (Glaser, 1998). The challenge was to connect the stories (as represented by the images) for further validation or to discover new connected ideas. However, according to Zaltman and Coulter (1995, p. 43), that social scientists such as Glaser and Strauss (1967), Lincoln and Guba (1985), Miles and Huberman (1984), and Strauss and Corbin (1990) ‘‘have established guidelines for developing classiﬁcation schemes and coding of data.’’ Labels were derived almost exclusively from Participants’ own words, phrases, or metaphors. Metaphors are a source of ideas; they provide the best means for understanding human mental models (Ortony, 1993). In order to arrive at well-grounded interpretations of Participants’ concepts and metaphors, the coding was examined and re-examined to ensure their support by text or image evidence (Christensen & Olson, 2002). These concepts were categorized into constructs according to their similarities. The relationships among these elicited constructs were then analyzed. The transcribed data were also examined and re-examined for ideas or relationships between constructs. When two ideas were related, a linkage

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between the relevant constructs was established. For example, the statement, ‘‘Family vacation takes my mind off from things. The vacation works as an escape’’ is relevant to the construct ‘‘Relaxed/Rejuvenated.’’ The statement from the same Participant, ‘‘you are going to be so much happier in life because having a family vacation makes my life balanced,’’ is relevant to the construct ‘‘Balance-In-Life.’’ These two statements can be translated as: ‘‘Since I go on vacation with my family once in a while [I am looking forward to being relaxed and taking my mind off from daily stresses], and therefore, I am taking one step forward to balance my life.’’ This analysis produced a relationship (linkage) between the two statements. Hence, the construct ‘‘Relaxed/Rejuvenated’’ links to the construct ‘‘Balance-In-Life’’ as a construct dyad. This process was iteratively processed, as suggested by Glaser (1998, 2004), to obtain well-grounded interpretations (Strauss & Corbin, 1990). Metaphor Elaboration Analysis was then conducted to explore Participants’ additional thoughts and feelings embedded in their minds or to reinforce what Participants had already expressed. Sensory image, vignette, and digital image analyses were then taken. The purpose of these analyses was to elicit additional insights into Participants’ feelings and thoughts and to validate the information provided through story telling. The sensory and digital image data in this study reinforced the ﬁndings derived from visual data. However, the vignette analysis rarely resulted in new discoveries.

Qualitative Rigor and Trustworthiness Trustworthiness (credibility, transferability, dependability, and conformability) is a term that has been used in qualitative research instead of ‘reliability’ and ‘validity,’ which are used in quantitative research (Lincoln & Guba, 1985; Johnson, 1997; Mishler, 2000; Patton, 2002). To ensure qualitative rigor and trustworthiness, triangulation methods may be used in qualitative research (Creswell & Miller, 2000; Denzin, 1978; Johnson, 1997; Mathison, 1988; Patton, 2002). To further establish trustworthiness and rigor, certain strategies should be built into each phase of a qualitative research (Morse, Barrett, Mayan, Olson, & Spiers, 2002). These strategies should include procedures that would act as a self-correcting mechanism in order to achieve the quality of the research. As discussed earlier, ZMET is built upon grounded theory and provides built-in procedures (e.g., the use of Kelly Repertory Grid, procedures based on credible qualitative research) for trustworthiness and rigor. In addition to the prescribed grounded

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procedures, ZMET multiple interview steps provide the opportunity to uncover an important idea that might be missed in the previous interview steps. While these multiple steps were designed to uncover Participants’ mental models and to bring new ideas to the surface, they also provide the researcher with a prescribed mechanism to automatically validate the Participants’ concepts that have been expressed in each step. Therefore, each step validates the ideas from previous steps, a process known as convergent validity (Zaltman, 1997; Zaltman & Coulter, 1995). That is, the demonstration of validity will be sufﬁcient to establish conﬁdence in the ﬁndings in qualitative research (Johnson, 1997; Lincoln & Guba, 1985; Patton, 2002). Researchers use the ‘‘member check’’ process, a technique for ‘‘establishing credibility’’ (Lincoln & Guba, 1985, p. 314) and a suggested procedure in triangulation methods to conﬁrm that the research’s analysis and interpretation matched the informants’ original intended meanings (Creswell & Miller, 2000; Glaser, 1978; Johnson, 1997; Mathison, 1988; Morse et al., 2002; Patton, 2002). This self-correcting mechanism performs a similar function as that of ‘‘member check’’ recommended in qualitative research (Morse et al., 2002). Guba and Lincoln (1994) suggest strategies such as research members’ audits during coding and categorizing. This study adopted ZMET prescribed procedures and guidelines established by scholars (e.g., code book). The purpose of the ‘‘code book’’ (Kumar, 2005) is to facilitate other researchers’ review of the validity of the initial constructs. The author adapted the ‘‘code book’’ approach by using ‘‘lexicon’’ analysis (i.e., the associated text of each initial construct was re-examined and shortened to form a lexicon). In order to ensure that the generated constructs were unique, meaningful to the study, and strengthened the validity of the constructs (beyond what ZMET grounded procedures and guidelines provided), another researcher, using the ‘‘cook book’’ as a guide, also reviewed the initial constructs and their relationships. This triangulation review process eliminated some constructs, combined some with others, or labeled them differently. The ﬁnal construct list consisted of 33 constructs labeled by metaphors or phrases with apparent meanings.

Consensus Map Construction By using the discovered constructs and their relationships, researchers can draw consensus maps. Consumers’ mental models are depicted by these diagrams with the interrelated concepts or constructs of an individual

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consumer or the sampled group of consumers under study. An individual map for each Participant was created ﬁrst. These maps contained all constructs and their relationships that the individual Participant mentioned or expressed in the transcript text or images. These individual maps depicted each individual’s mental models and were then used to construct the overall consensus map. A proprietary software package was used to integrate all the individual maps into an integrated consensus map for all Participants. This software package also can produce consensus maps of Participants’ constructs or mental models at different levels of ‘‘consensus.’’ The next step was to produce the integrated consensus maps of all Participants’ mental models at different levels of ‘‘consensus.’’ A consensus level is simply the number of Participants who have mentioned the relationship between two constructs. For example, if eight Participants mention the relationship between the construct ‘‘Togetherness’’ and the construct ‘‘Good times-enjoying-having Fun,’’ then the Consensus Map will highlight the link between these two constructs at a consensus level of eight or lower. Set at 1, the lowest level the consensus map contains all possible connections among constructs. With a large number of connection links, consensus maps can be difﬁcult to understand. Generally, consensus maps should be based on one-fourth of the number of Participants (Zaltman & Coulter, 1995). The Integrated Consensus Map was found to be most meaningful and intelligible when set at a consensus level of 6 (with 23 constructs out of a total of 33).

FINDINGS Consensus maps reﬂect the researchers’ understanding of how the metaphors and mental models were organized and linked in Participants’ minds. Guided by the research objective and through a review of the Integrated Consensus Map, three metaphoric themes were uncovered (Fig. 1). Each metaphoric theme consists of linked constructs. Each theme is highlighted via a ‘‘color-coded’’ path, and each theme leads to the ‘‘core’’ construct ‘‘Balance-In-Life’’ and then to one of the four end-value-constructs (i.e., ‘‘Enhanced Self-Esteem,’’ ‘‘Happiness,’’ ‘‘Satisﬁed-Fulﬁlled,’’ and ‘‘Sense of Accomplishment’’) representing the end values of family vacation. Researchers have studied family leisure patterns that affect families’ functioning. Zabriskie (2000), using the two general leisure patterns and family functioning needs for both stability and change, identiﬁed and tested a family leisure functioning model. This model consists of two categories: core

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Fig. 1.

Themed Integrated Consensus Map.

and balance. The core category includes mostly inexpensive home-based family activities that most families do regularly and that require little or no planning. The balance category consists of activities that are less common and not home-based (e.g., family vacations) and other recreational activities (e.g., family trips to theme parks). The core family leisure provides an experience of closeness and familiarity (i.e., security) and thus, promotes family stability. The balance family leisure (e.g., family vacation) provides new experiences that serve as inputs for the family to be challenged, to develop, and to evolve. Balance category activities require planning and investment of time, money, and other resources. Functions resulting from family vacation, as reﬂected by the three discovered metaphoric themes, contribute to both core family leisure (e.g., family stability such as bonding associated with family interactions) and balance leisure (e.g., the development of working family unit resulted from gained new experiences from planned activities). Highlights of each theme are discussed below. The ﬁrst metaphoric theme, Vacation Decision-making, depicts Participants’ feelings and thoughts about their planning process experiences. This theme includes ‘‘Planning-Preparation’’ (e.g., time and budget), ‘‘Information Seeking’’ (e.g., seeing a travel agent), ‘‘Destination-Schedule’’ (e.g., destination choices and ﬁnal decision-making), and ‘‘Anticipation’’ (e.g., pre-vacation emotions) constructs. Most Participants reported that

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their yearly family vacation planning had become a family ritual. One Participant stated, ‘‘I deserve a vacation with my family,’’ and another said ‘‘We always spend our summer vacations at the shore. But we always spent a lot of time planning for it.’’ Adolescents had a positive view of family vacation: ‘‘We must have a family vacation once a year no matter what.’’ One young female added: ‘‘Family vacation is very important to me, especially living away from home.’’ However, one of the Participants had not taken family vacation annually. He said: ‘‘Hard to take time off [from school and work]. My family vacation happens once in a blue moon.’’ Similar to what past literature (Kang & Hsu, 2005) has reported, Participants described vacation planning as a difﬁcult task. One Participant, a male in his late teens, said ‘‘A lot of preparation goes into family vacations. This guy [depicted in a picture] looks real intense, so it’s kind of planning a trip. You have to be intense about it to really get it done.’’ A young female explained the difﬁculty of deciding on a destination: ‘‘we [parents and two sisters] went with another family with three sons. There were so many of us with different schedules. We had to work around everyone’s different schedules and everyone had to agree on the same place to go to.’’ Another mother stated her preference for her own freedom: ‘‘If there is bad weather on a vacation, it is very frustrating. I hate crowds on vacation. I like peaceful environments where you have your own space to do what you want.’’ A majority of Participants indicated that the ﬁnal decisions were made by agreement among all family members (and friends who were taking the same trip). Only a few Participants (teenage students) reported that they usually were not involved in the family vacation decision-making. Most Participants claimed that at the end of the vacation planning process, they felt fulﬁlled (e.g., gained new knowledge, see construct ‘‘Exploring-Learning’’), relieved (the difﬁculty task was accomplished, see construct ‘‘Sense of Accomplishment’’), were proud (being able to have a vacation, see construct ‘‘Enhanced Self-Esteem’’), and were eager (see construct ‘‘Anticipation’’). Participants were extremely happy with their life (see construct ‘‘Happiness’’) while waiting to go on their vacations. All Participants were eager while looking forward to starting their vacations. The second metaphoric theme, Personal Relevant Beneﬁts, depicts personally relevant values that vacationers pursued. Beneﬁts were the consequences and end values resulting from family vacationers’ goal-driven pursuits. This theme includes all constructs related to consequences (e.g., ‘‘Excited,’’ ‘‘Good Times-Enjoying-Having Fun,’’ ‘‘Relaxed-Rejuvenated,’’ ‘‘Exploring-Learning,’’ and ‘‘Being-Well-Rounded-Person’’). Participants

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equated going on a family vacation with ‘‘freedom.’’ As one female exclaimed, ‘‘I choose this picture because for me it represents freedom. All those birds can go wherever they want.’’ Another said: ‘‘You are in another destination and you are free to do whatever you like to.’’ Several other Participants echoed their joy on their regained freedom. They testiﬁed: ‘‘You have the free time to spare and nothing to be attached too,’’ ‘‘I have so much fun with my family and enjoyed every minute of it;’’ and ‘‘This is a picture of a cup of coffee and coffee gives you energy. y Nothing could make us tired because we were just so excited and had so much fun. Even after being out in the sun all day we still wanted to go out at night and enjoy the nightlife.’’ Shopping was one of the freedoms that they enjoyed while on vacation. One young Aruba female exclaimed, ‘‘I chose this picture because behind me is the famous Roman Coliseum and that represents, for me, ‘power.’ I do not go out often for shopping. However, when I go I feel beautiful. y France is the ideal place to buy things. I feel beautiful in France!’’ Acquiring knowledge while on vacation was another beneﬁt (e.g., ‘‘I see things that I never saw before.’’). The ‘‘freedoms’’ offered the vacationers a carefree lifestyle that included fun, relaxation, rejuvenation, excitement, and balance in life. In summary, this theme indicates that the beneﬁts vacationers gained from their family vacations were self-actualization, self-enrichment, selfexpression, regeneration, renewal of self, a sense of accomplishment, enhancement of self-image, and emotional well-being. The third metaphoric theme, Family Interactions, was associated with family relationships and family leisure activities. The Family Interactions theme includes the constructs ‘‘Conﬂict,’’ ‘‘Bonding,’’ ‘‘Frustrated-Disappointed-Sad,’’ ‘‘Support,’’ ‘‘Forgiving-Forgetting,’’ ‘‘Proud of My Family,’’ ‘‘Cherish,’’ and ‘‘Love-Sharing/Giving Oneself’’ and ‘‘Togetherness.’’ This theme indicated that all Participants valued the opportunity to interact with family during family vacation time and saw social relationships (e.g., bonding) as the major reason for taking family vacations. Several Participants provided their testimonials. ‘‘It always feels good to do something to make someone else feel happy.’’ ‘‘You feel you have a duty to fulﬁll and you enjoy it.’’ ‘‘My parents have always been there for me. The vacation helped. It was like a band-aid. It gave us a chance to get over it.’’ ‘‘All the thing[s] we do together help [to] ﬁx problems.’’ ‘‘Being together is the most important [thing] in a family vacation. Spending quality time together is something that I enjoy and my family enjoys.’’ ‘‘My parents and sister are my best friends.’’ ‘‘You are forced to bond while you are on vacation.’’ ‘‘Usually we talk over the phone but we get to spend more time

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talking during family vacation. Now he’s more of an older friend than a father.’’ ‘‘I just love the relationship we have and to be able to talk to my parents just about anything.’’ ‘‘Something you will remember for the rest of your life.’’ ‘‘Our family vacations become a tradition. Family traditions, that you can carry on to the next generation.’’ While a family vacation has positive family beneﬁts, it also might produce negative experiences such as conﬂict (Shaw, 1997). A number of Participants reported that family conﬂicts erupted during vacations. The typical examples of family conﬂicts reported were: ‘‘With six people in a family, there [are] bound to be some minor fractions;’’ ‘‘The problems between [household] members can be aggravating at some point in time;’’ ‘‘If you and your family [are] crowded in[to] a small hotel room everyday for a week, some fractions will likely happen.’’ Other than these few family minor conﬂicts reported, no other negative outcomes mentioned. The reasons could be that Participants might have tolerated minor inconveniences (e.g., ‘‘all family members cramped in a single hotel room’’) or dissatisfaction (e.g., ‘‘some restaurants were too expensive’’). Most of these conﬂicts were settled quickly. As one female said, ‘‘My mom, sister and dad know me better than anyone and they know how to make me mad. I feel like when you are getting together with your family that you don’t get to see often then the last thing you should do is spend your time ﬁghting.’’ Another Participant referred to an inconvenient situation and said: ‘‘What would be the point of me making a big deal about it?’’ ‘‘Don’t ruin the family vacation’’ was one Participant’s response to minor irritations. Overall, Participants cherished the bonding, the support, the love and sharing, and togetherness that family vacations offered. These ﬁndings are consistent with past research such as: ‘‘enjoy an overall net positive effect or pleasant feelings’’ (Gilbert & Abdullah, 2002, p. 352); ‘‘children like to shop and were pleased with the shopping experience’’ (Nickerson & Jurowski, 2001, p. 27); improving quality of life (Hobson & Dietrich, 1994); and ‘‘more concerned with creating balance in their lives’’ (Joplin, Shaffer, Lau, & Francesco, 2003, p. 17).

DISCUSSION AND CONCLUSIONS This study makes several noteworthy ﬁndings. ZMET allowed the collection of rich data for the understanding of family vacationers’ underlying affect and cognition that directed their overt behavior. These family vacationers’

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mental models represented by the three metaphoric themes, Vacation Decision-making, Personal Relevant Beneﬁts, and Family Interactions, can be translated into marketing actions. These themes and a few particular ﬁndings such as ‘‘freedom,’’ and ‘‘family ritual,’’ permitted the researcher to explain the sample Participants’ characteristics and behaviors in ways that quantitative techniques could not (cf. Aaker et al., 2003; Creswell, 1998; Schwandt, 1997; Spiggle, 1994). For example, the Participants’ nonconscious goal pursuit of ‘‘freedom’’ might not have been discovered if a survey questionnaire were used in this study. Hospitality and tourism industry marketers could translate these underlying concepts, represented by the three metaphoric themes, into actions. The centrality of all three metaphoric themes is ‘‘Balance-In-Life.’’ All actions should aim at the consequences of balance in life. For example, the second metaphoric theme (Personal Relevant Beneﬁts) provides the insights of life balance that family vacationers seek. The industry could devise activities that meet tourists’ inner preferences expressed by this theme (e.g., various activities, for individuals or group, throughout the day and night for those who can say ‘‘Nothing could make us tired’’). These activities could be offered on site or near the hospitality establishment. Activities that can be enjoyed even in inclement weather, or activities (less rowdy such as tennis) for some individuals who desire alternative activities to be provided under some speciﬁc or unpredicable conditions (e.g., ‘‘bad weather on a vacation, it is very frustrating. I hate crowds on vacation’’) should also be offered. Similarly, accommodations should also be offered to meet all types of preferences (e.g., large non-traditional family units). Marketers could also devise ‘‘freedom’’ as a central theme in their designs of facilities and activities that would meet family vacationers’ desire of ‘‘freedom,’’ a carefree lifestyle vacation. These family vacationers’ mental models obtained through ZMET were the major contributions to the discovery of the three metaphoric themes and other unique ﬁndings (e.g., ‘‘freedom’’). One major advantage of ZMET is that the study Participants saw themselves as part of the research team. Therefore, Participants were more willing to reveal their hidden feelings and thoughts. In addition, consensus maps are a powerful data analysis tool that facilitates researchers’ understanding of how the metaphors and mental models were organized and linked in Participants’ minds. More importantly to the practitioners, hospitality and tourism marketers could use the Themed Integrated Consensus Map to implement their marketing strategies. That is, the underlying metaphorical meanings of the themes revealed in Participants’ mental models through ZMET could be directly translated

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into hospitality and tourism marketing strategies. Both academics across disciplines and practitioners have challenged the traditional marketing research methodology. DeCrop (1999), Downward and Mearman (2004), and Walle (1997) have questioned the adequacy of quantitative measures to capture tourists’ underlying experiences. More recently, Pritchard and Havitz (2006, p. 26) also argue that the industry has an ‘‘inability to successfully integrate ﬁndings into practice’’ and ‘‘such problems often result from a methodological bias that shuns ‘qualitative-based data [or methods] where researchers directly asked tourists what they perceive about their tourism experience and the industry that services it (Jackson, White, & Schmierer, 1996, p. 798).’’’ Riley and Love (2000, p. 165) in their examination of the state of qualitative tourism research also ﬁnd that ‘‘researchers have questioned quantitative research because it cannot fully address questions of understanding and meaning (Havitz, 1994; Henderson & Bedini, 1995; Hollinshead, 1996b; Riley, 1996; Walle, 1997), and they have begun to explore paradigms beyond positivism (Dann, 1996; Hollinshead, 1996a).’’ Furthermore, ‘‘McCleary (1992) and Dann et al. (1988), who both suggested that qualitative research made signiﬁcant and valuable contributions to the knowledge base’’ (Riley & Love, 2000, p. 167). As qualitative research ‘‘has struggled to ﬁnd its present position in health services research’’ (Jones, 1995, p. 2), it seems that hospital and tourism scholars would also have to struggle to establish a solid ground in qualitative research. Hence, hospitality and tourism researchers and scholars need to increase the momentum of pushing the initial interests in qualitative methodology to a higher ground. The results of this study strongly support the use of qualitative methodology as the means to alleviate the industry’s inability to translate research ﬁndings into practices. According to Zaltman (2003), ZMET has been used for product branding and marketing research by over 6,000 projects in more than 20 countries and in more than 25 international companies, including Coca-Cola, AT&T, Eastman Kodak, General Motors, Paciﬁc Gas and Electric, Polaroid, Procter and Gamble, and Reebok. Zaltman argues that more than 95% of consumers’ decisionmaking process takes place in the subconscious, yet traditional marketing methods barely scratch the surface of this gold mine. ZMET helps ‘‘consumers express their thinking through metaphors. The insights gained through these processes often remain far beyond the reach of traditional research methods’’ (Zaltman, 2003, p. xiv). The innovated grounded ZMET is, therefore, recommended for future hospitality and tourism research.

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ACKNOWLEDGMENTS The author wishes to extend her sincere appreciation to Dr. Jerry Olson, founding partner of Olson Zaltman Associates, LLC, and Professor of Emeritus of Marketing at Penn State University, and to Dr. Gerald Zaltman, founding partner of Olson Zaltman Associates, LLC, and the Joseph C. Wilson Professor of Business Administration at the Harvard Business School, for their assistance, and permissions to use the patented Zaltman Metaphor Elicitation Technique (ZMET) and the proprietary software package for this academic research. Special thanks are also due to Olson Zaltman Associates and its staff for providing assistance and training in ZMET.

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INTERVENTION ANALYSIS OF INBOUND TOURISM: A CASE STUDY OF TAIWAN Jennifer C. H. Min ABSTRACT An accurate tourism forecast is critical to destination countries as a foundation for tourism-related decision making and efficient tourism planning. The purpose of this study is to evaluate how Taiwan’s inbound tourism was affected by the September 21st Earthquake in 1999 and the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003, one of the mega earthquakes in the 20th century and most catastrophic health hazard in the past hundred years in Taiwan, respectively. According to the empirical findings, Taiwan’s inbound tourism was brutally devastated by the two calamities, particularly during the SARS outbreak. The inbound tourism was more heavily influenced by the SARS epidemic and recovered from the SARS shadow was greater compared with the recovery after the September 21st Earthquake.

INTRODUCTION Tourism has emerged as a signiﬁcant worldwide industry. It contributed an average 3.6% to Gross Domestic Product (GDP), more than US$6 trillion in Advances in Hospitality and Leisure, Volume 4, 53–74 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00003-9

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economic activity and 8.7% of total employment worldwide in 2006 (World Travel and Tourism Council, 2007). According to the World Tourism Organization (WTO), tourism demand has enjoyed a record high with total visitor arrivals topping 842 million, representing a 4.6% growth in volume over 2005. The WTO further estimated that international arrivals are expected to hit nearly 1 billion by the year 2010 and 1.6 billion in 2020 (WTO, 2006). Given these ﬁgures, forecasting of international tourist arrivals is of some importance to countries in order to provide essential information for planning and decision-making, particularly given the perishable nature of tourism products and services. For this reason, the search for appropriate modeling techniques to improve forecasting accuracy has been of great interest to many researchers (Song, Witt, & Jensen, 2003). At the same time, the tourism industry is susceptible to exogenous changes or extreme events that come in a variety of forms (Mansfeld, 1999; Kim, Chun, & Lee, 2005). Natural disasters such as earthquakes, tsunamis, hurricanes, tropical cyclones, ﬂoods, volcanic eruptions and epidemics, or man-induced disasters such as wars, terrorist attacks, terrorist threats, political instability, high levels of crime and violence, and economic factors such as a sharp ﬂuctuation in exchange rates can all contribute to a tourism crisis. Many tourism researchers share the view that international visitors are heavily concerned about personal security and safety (Sonmez & Graefe, 1998; Coshall, 2003) and ‘‘ytourism can only thrive under peaceful conditions’’ (Pizam & Mansﬁeld, 1996). Unfortunately, tourism disasters appear to have increased in frequency and severity in recent years. Such external shocks and crisis situations cause declines in tourism demand (Coshall, 2003), particularly if the events occur in peak holiday seasons, adversely affecting the level of business in tourist destinations (Ryan, 1993), and are something that government authorities and tourism practitioners cannot ignore. Events such as earthquakes (Huan, Beaman, & Shelby, 2004; Huang & Min, 2002; Mazzocchi & Montini, 2001), ﬂoods (Faulkner & Vikulov, 2001), hurricanes (Chandler, 2004), tsunamis (Henderson, 2007; Shareef & McAleer, 2007), epidemic disease (Min, 2005; Zeng, Carter, & Lacy, 2005; Mason, Grabowski, & Du, 2005), political instability (Gartner & Shen, 1992; Soemodinoto, Wong, & Saleh, 2001; Beirman, 2002), crime and violence (Pizam, 1999), terrorism threats and attacks (Sloboda, 2003; Coshall, 2003; Hitchcock & Putra, 2005), and ﬁnancial crises (Henderson, 1999; Law, 2001) have all caused severe declines in tourist arrivals in various travel destinations and had far-reaching consequences on regional tourism. While it is evident that the hazards that occur in tourism destinations will have negative inﬂuence on tourism demand in those attractions, the

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importance of accurate forecasts for the tourism industry, in both the short and long term, must also be recognized. Questions of signiﬁcance include: factors that affect tourism demand in tourist destinations, the extent of decline in tourist arrivals, the status of the recovery from catastrophes, and whether these unpredicted tragedies have a temporary or long-term impact on tourism demand for the tourist destination. It is vital for travel practitioners and academic researchers to understand how tourist arrivals are adversely affected by misfortunes to enable sound prompt responses to be developed. It is also crucial to pay sufﬁcient attention to establishing a forecasting model for the aftermath of hazards as the impact of such exceptional external events can cause the mean levels of tourism demand in a time-series to change. The models allow tourist authorities to evaluate the pattern and duration of the events effect on the crisis.

The Study Objectives The objectives of this study are to apply one forecasting approach, ARIMA with intervention model (also known as intervention analysis), to two reallife cases in Taiwan in order to assess how inbound tourists have been affected during and after these disasters. The September 21st earthquakes in 1999, and the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003, are the largest natural disaster in the 20th century and most catastrophic health hazard in the past hundred years in Taiwan, respectively. Intervention analysis is adopted not only to assess the impact of the two events, but also to compare the recovery status from both. International tourism demand regarding Taiwan is then represented. The paper is set out as follows: (1) to present the motives and objectives of the study, including the importance of forecasting tourist arrivals relative to the impact of disastrous events; (2) to review the detrimental consequences of the September 21st earthquake and the SARS illness, providing a detailed description of how international tourism was affected, and how government authorities in Taiwan coped with the challenges of mitigating the impacts on tourism; (3) to introduce the intervention analysis adopted by the current study, and previous research of the intervention models in tourism-related literature; (4) to analyze the conceptual models proposed by the study; and (5) to discuss the ﬁndings, and compare the rebound differences between these two catastrophes. The paper concludes with a summary of the main points and suggestions for future research.

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JENNIFER C. H. MIN

BACKGROUND In recent times, two crises, the September 21st Earthquake of 1999 and the SARS outbreak in 2003, have cast dark clouds over the tourism industry of Taiwan. Although as calamities they have quite different features (the one involving extensive infrastructure damage and the other an epidemic), they are both well-known international events, and negatively inﬂuenced the island’s economy as well as its international tourism demand.

The September 21st Earthquake 1999 The largest ever natural disaster in Taiwan was an earthquake that hit the island on September 21, 1999. The so-called September 21st Earthquake, measuring 7.3 on the Richter scale, rocked Taiwan and ﬂattened several towns, resulting in the deaths of over 2,400 people, more than 13,000 people were injured, and in excess of 100,000 left homeless. Because the September 21st Earthquake struck at 1:47 a.m., all residents were at home during the quake. As a consequence, building collapse became the most dominant cause of fatalities. The epicenter was in an inaccessible mountain vicinity, difﬁcult to get to at the critical moments and reachable only by helicopters. Most necessary roads or bridges in the affected regions were ruined due to the fault rupture. Thus, it made the rescue work tremendously complicated and postponed the ﬁnal casualty toll. In addition, water, sewage, gas, and power systems on the island were extremely sensitive to vibration and were forced to shut down. Hardest hit among the many electronics companies at Hsinchu Scientiﬁc Park were some silicon-chip makers, which account for about 10% of the world’s market in semiconductors. Undoubtedly, the September 21st Earthquake shook the island’s economy in the second half of 1999. The greatest effects of the September 21st Earthquake were felt instantly by the tourism industry, since it damaged tourist facilities at numerous popular destinations. The worst damage was in central Taiwan, near the epicenter in Nantou County. Nearby theme parks such as the Formosan Aboriginal Culture Village were hurt badly during the peak season for tours in the quarter. Li Shan (Pear Mountain), a vacation and fruit-growing village, was cruelly ravaged by the devastating earthquake. The internationally renowned Sun Moon Lake scenic area, normally attracting throngs of visitors, was also severely damaged. The short-term reconstruction cost has been estimated to be more than US$16 million.

Intervention Analysis of Inbound Tourism: A Case Study of Taiwan

57

In addition to scenic areas, a large number of listed ancient monuments and unlisted historic buildings were also harshly damaged. Some historical buildings away from the faults also suffered seriously. Although reconstruction proceeded rapidly, the scale of damage was so great that repairs were not completed soon. In the meantime, trafﬁc to some scenic spots located in the afﬂicted areas was diverted or cut altogether. As a result, the post-quake rescue operations diminished many individuals’ desire to travel there during the initial period following the disaster. The media frenzy and misleading reports that the quake had engulfed the entire island also frightened away many potential tourists. According to the Tourism Bureau report, during the January–August period of 1999, visitor arrivals recorded a 15% growth as compared with the same period the year before, which had been reviving as Asia recovered from the ﬁnancial turmoil of 1997–98. However, there was a dramatic reduction in tourist arrivals during the post-quake period. The number of visitors from abroad declined by 15% during the period from September to December when compared with the same period in 1998, and the number of visitors to 230 major scenic spots dropped by 27% (Taiwan Tourism Bureau, 2000). The room occupancy rates of hotels for international tourists plummeted by an average of about 60%, and international airline reservation cancellations soared to 210,000 for the September–December period of 1999 (Travel Trend News, 1999). Statistics showed that government-operated scenic spots suffered losses amounting to approximately US$19.5 million, and privately operated tourist enterprises suffered losses of about US$119 million (Taiwan Tourism Bureau, 2000). For a long period, the island had never experienced such an earthquake as the one on September 21st.

Implementation of Tourism Revitalization Measures after September 21st Earthquake For the tourism industry, it was the most crucial challenge to both the government and tourism practitioners. The Tourism Bureau of Taiwan implemented a series of measures to reinvigorate island tourism. In order to mitigate the negative media coverage, more than 400 representatives of overseas media and major foreign tour wholesalers were invited for familiarization tours of the areas affected by the earthquake. Moreover, international promotion based on the theme of ‘‘tour Taiwan at ease’’ was carried out to entice foreigners to visit the island. Additional promotional activities were carried out to encourage tourism. The annual Taipei

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JENNIFER C. H. MIN

International Travel Fair was held at Taipei in November. The 4-day fair featured 520 booths manned by tourism professionals from 40 countries and areas throughout the world, and attracted more than 60,000 visitors. Being held during the aftermath of the earthquake, the fair not only had a signiﬁcant positive effect on the revitalization of domestic tourism but also immensely enhanced the overall image and position of Taiwan on the international tourism stage. Another positive development was the Johnnie Walker Classic golf tournament held in Taiwan during the same month. The tournament attracted reporters from more than 20 major golﬁng magazines and tourism media from Japan, Hong Kong, Singapore, Australia, and United States. The Tourism Bureau took advantage of the tournament and placed ‘‘Goodwill Taiwan’’ and ‘‘After the quake, Taiwan goes on,’’ a 30-s commercial on the CNN cable news network in Asia and North America. Because visitors from Japan have been the major inbound market segment in Taiwan, the placement of ‘‘easy heart publicity’’ advertisements in major Japanese media was strengthened. Furthermore, promotion seminars were held jointly with large Japanese air carriers in Tokyo, Fukuoka, Osaka, and Nagoya, and posters were posted throughout Tokyo railways and bus stations. Finally, a marketing program of ‘‘Go, Taiwan’’ was carried out in cooperation with China Airlines and Japan Asia Airways. The Taiwanese government also made other efforts to stem the dramatic decline in inbound tourist ﬂows. The government played a signiﬁcant role to help bring facilities in scenic areas back into operation efﬁciently. The Tourism Bureau assisted in the reconstruction of public facilities under a program of relief loans for tourist industries in the stricken areas. This program permitted large and small tourism operators to apply for low-interest loans from small and medium business banks. Operating capital loans were also provided by the Central Bank of China. Furthermore, assistance was provided for carrying out nationwide inspections of scenic and recreational areas. An announcement was made of those areas that had passed safety inspections so that the public could travel without safety concerns. Nevertheless, to attract tourists to Taiwan, there was still a need to substantially reduce the overall prices of taking a trip to Taiwan during the early recovery stage. Since tourists from Japan and Hong Kong dominated the inbound market in Taiwan, ranking ﬁrst and second, respectively, there were signiﬁcant discounts of ticket fares for routes from the above regions. In addition, many of Taiwan’s international tourist hotels mailed promotional materials to every previous Japanese guest to rescue the sharply declining Japanese market (Travel Trend News, 1999).

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The SARS Outbreak 2003 The effect of the SARS outbreak in many destinations hit global tourism activity severely, especially in East Asia, which had otherwise shown clear signs of recovery from the shadow of terrorist attacks, the Iraq War, and a worldwide economic setback during 2000–2002. In fact, tourist ﬂows had seen a strong increase in the Asia-Paciﬁc region, representing an 8.3% growth in 2002 (World Tourism Organization, 2003). However, from November 2002 onwards, SARS spread rapidly through jet travel to at least 26 countries on ﬁve continents, resulting in more than 8,000 reported probable cases, including 900 deaths (World Health Organization, 2003a). As a result, international tourism went through considerably difﬁculties with an epidemic that brought the steady growth of Asian and Paciﬁc tourism temporarily to an abrupt halt. SARS is a respiratory disease caused by infection with a new coronavirus, spread primarily by close person-to-person contact. Its outbreak brought global anxiety because of its novelty, ease of transmission, and the speed of its spread via international air travel, combined with extensive/ exaggerated media coverage. The ﬁrst SARS case (at that time called atypical pneumonia) was reported in November 2002 in Foshan, Guangdong Province, China. The World Health Organization (WHO) did not take any measures at the initial stage of the SARS outbreak until March 2003. On March 12, WHO issued a global alert about cases of severe atypical pneumonia following mounting reports of its spread to different areas such as Hong Kong, Hanoi, Singapore, and Toronto. Three days later, WHO named the mysterious illness after its symptoms and declared it to be ‘‘a worldwide health threat’’ and the ﬁrst pandemic of the 21st century, one that was spread by air travel along international routes. WHO further suggested travelers to be aware of the symptoms, issued advice to airlines, and made recommendations to national authorities for implementing heightened surveillance for cases of SARS (World Health Organization, 2003b). The purpose of these travel advisories was to limit the rapid spread of infection through travel. Taiwan had to cope with the third-largest SARS outbreak, and its ﬁrst patient was reported on March 15. By April and May, SARS had spread rapidly over the island, and increasing numbers were reported each day as panic gripped the island. On May 8, WHO declared Taipei on the travel advisory list, and warnings were extended to the rest of Taiwan on May 21; this was the harshest travel warning in WHO history. Following the

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JENNIFER C. H. MIN

announcements, 30 nations imposed additional restrictions on travelers from Taiwan, and up to 48 nations warned international tourists not to visit (Taiwan Tourism Bureau, 2003). By June, the number of newly infected patients showed a decline, and by early July was down to zero, at which point the crisis was considered over. Accordingly, WHO lifted Taiwan from its SARS travel advisory list on June 17, and removed it from the list of areas with recent local transmission on July 5. The impact of SARS was extreme. The virus damaged Taiwan’s tourism industry and impeded the ﬂow of tourists. In 2003, Taiwan received around 2.2 million visitors, a decline of 24.5% from the previous year. Before the SARS outbreak, visitor arrivals to Taiwan to the beginning of 2003 had boomed, reaching more than 259,000 visitors in February, the highest ﬁgure ever recorded for that month (Taiwan Tourism Bureau, 2004). However, the number of visitors from abroad decreased with an unprecedented slump in inbound travel demand of 50% during the period March 19–May 18, compared to the same period in 2002. During March–June, room occupancy rates of international hotels dropped nearly 40%, and the number of cancellations of ﬂights climbed to 1,000. Scheduled conferences and business conventions were cancelled, and major tourist events were called off or postponed. Faced with dramatic decreases in tourist bookings, many travel agencies and tourism-related ﬁrms were driven out of business, others were forced to impose pay cuts and deﬁnite or indeﬁnite leave without pay (Taiwan Tourism Bureau, 2003). According to a Tourism Bureau report, international arrival numbers fell in the second quarter by 71.54% from a year earlier as a result of the SARS outbreak. These declines slowed to 19.7 and 11.1% in the third and fourth quarter, respectively (Taiwan Tourism Bureau, 2004).

Post-SARS International Tourism Recovery Measures In order to halt the steep decline in tourism and mitigate negative media coverage, more than 2,000 representatives of overseas media and major foreign tour wholesalers were invited to a ‘‘Tour Taiwan at Ease’’ trip aimed at improving their understanding of Taiwan’s recovery from the SARS epidemic. International promotions based on the theme ‘‘Fly Taiwan Fly’’ were carried out to entice foreigners to visit the island. The international Taipei Chinese Food Festival was held in Taipei from August 7–10, 2003, with the aim of promoting Chinese culinary culture, expanding tourist

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61

promotion, reestablishing Taiwan as a tourist destination, and developing tourist resources. Held during the SARS recovery stage, the event had a signiﬁcant positive effect by immensely enhancing the overall image and position of Taiwan on the international tourism stage. Because Japan is Taiwan’s main source of visitors, the government and private sectors jointly rolled out various tourism promotion measures and new tour destinations to attract Japanese tourists to the island after July 5, when WHO removed Taiwan from its list of SARS-affected regions. Advertising was carried out for tourism promotions through major print and electronic media channels in Japan. Post-SARS promotions emphasized the safety of travel in the island under the themes ‘‘Exhausted in Japan, Rest Up in Taiwan’’ and ‘‘Take it Easy.’’ The Taiwan Visitors Association was commissioned to work with domestic tour operators to organize tourism promotional events for the Japanese market. Furthermore, the Tourism Bureau sent a delegation to hold promotional events in August to inform the Japanese public about the post-SARS recovery status of Taiwan. For other tourist markets, advertising on the themes of gourmet travel and hot spring tours were taken out in Hong Kong, Singapore, and Malaysia. A promotional ‘‘road show’’ was also arranged in the above markets, the ﬁrst time the bureau has held large-scale direct-to-consumer promotions. In both the US and European markets, ads highlighting the beauty of Taiwan were shown on CNN Headlines News and Discovery Channel. In addition, media representatives, travel writers, and tour operators were invited to take part in tours from July to September to highlight the safety of traveling in Taiwan, and special tour packages were introduced in several major visitor source markets after the end of SARS crisis. Additional promotional activities targeting various markets were also carried out to encourage tourism, such as rafﬂing off f10,000 coupons for 5,000 travelers in the Japanese market, US$588 coupons for a 3-day tour in the US market, etc. These swift countermeasures were adopted to revitalize the Japanese and US markets and encourage tourism back to the island. Following the disastrous September 21st Earthquake and the SARS outbreak, Taiwan’s tourist-related organizations were put in the difﬁcult position of dealing with declining tourism revenues. Although the Taiwanese government and tourism practitioners swiftly adopted a series of countermeasures to reverse the dramatic decline in tourism ﬂows, an unprecedented wide-scale cancellation of bookings caused by the two events signiﬁcantly impacted the island’s tourism industry.

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JENNIFER C. H. MIN

LITERATURE REVIEW As stated previously, accurate forecasts can aid tourism authorities and practitioners take better decisions. A forecast of tourist arrivals is especially decisive in providing reliable estimates of revenue in order to avoid shortages or surpluses in goods and services (Wang & Lim, 2005). Recognizing the importance of accurate forecasts to the tourism industry, forecasting techniques that predict international tourism ﬂows have been widely adopted and related empirical ﬁndings published. Among a variety of forecasting techniques, Box–Jenkins autoregressive integrated moving average (ARIMA) is widely used in modeling and forecasting because of its value, regardless of a stationary or nonstationary time series, and with or without seasonal components (Lim & McAleer, 2002). In particular, univariate Box–Jenkins forecasting models yield relatively accurate performances with international tourism demand (Witt & Witt, 1995; Lee, Oh, & O’Leary, 2005). Intervention analysis can be treated as an extension of ARIMA modeling. Initial work conducted by Box and Tiao (1975) provided an analytical framework for examining the effect of two interventions, the opening of the Golden State Freeway, and enforcing a new law concerning oxidant data in Los Angeles. Intervention analysis is a useful technique when the impact of exogenous events occurs at known time points. McDowall, McCleary, Meidinger, and Hay (1980) pointed out that intervention analysis measures whether an intervention has had a signiﬁcant impact and investigates the form of that impact. It has been used successfully, therefore, to measure and assess the consequences of exceptional external events such as various types of economic crises, environmental impacts such as natural or man-made disasters, ﬁnancial crises, political and economic policy initiatives or changes, technological change, work stoppages, sales promotions, advertising, and so on (Box & Tiao, 1975; Chang & Lin, 1997; Goh & Law, 2002; Kapombe & Colyer, 1999; Girard, 2000; Lai & Lu, 2005; Sharma & Khare, 1999; Goh, 2005; Min, Wu, & Wu, 2006). The application of this analysis has been extensive in tourism-related literature. In Bonham and Gangnes (1996), an intervention model was used to analyze the effect on hotel revenues of a hotel room tax initiated by Hawaii in January 1987. The ﬁndings indicate that there was no signiﬁcant permanent effect of the room tax on either the level or growth rate of aftertax hotel room revenue. A study by Lee et al. (2005) employed intervention analysis to assess the status of recovery after the September 11 terrorist attacks on US air passenger transport demand. Empirical results show that

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63

the demand for US air passenger transport had not yet fully recovered from the attacks, but the demand appeared to increase gradually. One study conducted by Coshall (2003) examined the impact of three interventions; the US bombing of Libya in 1986, the Lockerbie air disaster in 1988, and the Persian Gulf crisis during 1990–1991, on UK air passenger movements to Canada, the Near East, the Middle East, and several European destinations using time-series intervention models. The same method employed in further research by Coshall (2005) analyzed the impact of ﬁve potential interventions; the Libyan bombing in 1986, the destruction of the Pan Am ﬂight over Lockerbie in late December 1988, the Persian Gulf war during 1990–1991, the UK foot and mouth epidemic in February 2001, and the New York and Washington attacks of September 11, 2001, to expenditures made by overseas tourists in the United Kingdom and to UK tourists’ expenditure abroad. Min et al. (2006) evaluated how Taiwanese outbound tourists have been affected by the SARS outbreak and then built a model of outbound demand in the aftermath of the SARS illness adopting SARIMA with intervention model. Two studies, one by Goh and Law (2002) and another by Lai and Lu (2005), compared different forecasting approaches for forecasting the accuracy of Hong Kong tourism demand and air travel demand, respectively. The results showed that intervention analysis outperformed all other techniques when signiﬁcant intervention in the series existed. In light of the above, the two profound inﬂuences on demand for travel to Taiwan, the September 21st Earthquake and the SARS illness, can be viewed as intervention events in Taiwan’s international tourism. It is vital, therefore, to include interventions in the forecasting model to improve the robustness of forecasts. This is one of the ﬁrst attempts at adopting intervention analysis through these two real-life disasters in tourism management.

METHODOLOGY Most tourism studies have employed time-series data to determine the levels of tourism demand. The number of tourist arrivals from a country of origin to a foreign destination is one variable often used to measure international tourism demand (Lim & McAleer, 1999). The deﬁnition of an international tourist is a person who is not resident and visits the destination country for a stay of 1–365 nights for the following purposes: leisure (recreation, holiday, health, study, religion, and sport), business, family, missionary, or meetings

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JENNIFER C. H. MIN

(Wall & Mathieson, 2006, p. 13). The procedure for most intervention studies is to use the longest data span (the pre- or postintervention observations) to ﬁnd a plausible set of ARIMA models (Enders, 2004; Coshall, 2003). The variable, ‘‘number of tourists,’’ published monthly by the Taiwan Tourist Bureau, with data from January 1979 to August 2006, is the indicator chosen in this analysis. The analysis was carried out using the statistical package SAS/ETS 9.1.

Intervention Model Approach Intervention analysis was originally developed by Box and Tiao (1975). In such an analysis, a time series may be subjected to an external shock or intervention, the impact of which may be permanent or temporary, gradual or abrupt. Suppose an observed time-series sequence of N observations is measured at equal time intervals. The full intervention impact assessment model may be written as (Yaffee & McGee, 2000): XX Y t ¼ Nt þ f ðI t Þ (1) t

where Yt denotes the series of monthly inbound arrivals to Taiwan; I t denotes the discrete explanatory (intervention) variables, which are the September 21st earthquake and SARS at time t (i.e., September 1999 and April 2003, respectively), and represents binary deterministic variables. N t denotes the stochastic noise component determined by a univariate ARIMA model; it always assumes a (p, d, q)(P, D, Q)s structure. Eq. (1) is in two parts and can be described as follows. Noise Indicator Nt is considered a noise series, representing the background observed series Y t without intervention effects and always assumes a SARIMA ðp; d; qÞðP; D; QÞ structure, which is a seasonal multiplicative ARIMA model. Dynamic Indicator If we have k intervention factors, the extended model may be written as: Yt ¼

k X j¼1

vj ðBÞzIjt þ

kX þm j¼kþ1

vj ðBÞxTjt þ

yðBÞ t fðBÞ

(2)

Intervention Analysis of Inbound Tourism: A Case Study of Taiwan

65

where the supercripts I and T refer to transferable variables, k and m, respectively; zIjt is the jth intervention series; and stochastic input xTjt should be prewhitened with its own ﬁlter, vj ðBÞ, to denote its impulse function: vj ðBÞ ¼

oj ðBÞ bj x dj ðBÞ

(3)

where os ðBÞ ¼ o0 o1 Bo2 B2 os Bs and dj ðBÞ ¼ 1d1 B dj Br are sj and rj degrees of B polynomials. Modeling The intervention analysis is an interactive procedure for constructing a timeseries model and includes four practical stages for ﬁnding a good model: identiﬁcation, estimation, diagnostic checking, and forecasting (Box & Jenkins, 1976).

EMPIRICAL RESULTS The data series in this study consists of monthly inbound arrivals from January 1979 to August 2006 shown in Fig. 1. An initial plot of the data of total inbound arrivals revealed irregular variations as well as an upward trend. The pattern contains a very clearly observable decline from the 292nd observation (April, 2003), which was caused by the SARS outbreak. 350000

250000 200000 150000 100000

Intervention Events

year

Fig. 1.

Time-Series Plot from January 1979 to August 2006.

2005

2003

2001

1999

1997

1995

1993

1991

1989

1987

1985

1983

0

1981

50000 1979

total inbound arrivals

300000

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JENNIFER C. H. MIN

Another reduction in tourist arrivals could also be noticeably identiﬁed from the 248th observation (September, 1999), related to the September 21st Earthquake. These two tragedies in this study, the September 21st Earthquake and SARS, had a great inﬂuence on the international tourism demand for Taiwan, and can be regarded as intervention events.

Preintervention Model The appropriate model for noise component Nt was identiﬁed prior to the known interventions, the September 21st Earthquake and the SARS outbreak, and the ﬁrst 248 observations from January 1979 through August 1999, were used for the identiﬁcation process. The diagrams of the original autocorrelation function (ACF) and the augmented Dickey– Fuller tests show that the inbound series is ﬁrst and seasonal differences stationary. The appropriate preintervention model was determined by checking the ACF diagram and the Ljnug–Box Q statistic. The preintervention model SARIMA (0,1,1)(0,1,1)12 tentatively ﬁtted the data well, and the estimate for the ﬁrst 248 inbound arrivals were obtained by maximum likelihood estimation as: ð1BÞð1B12 ÞZ t ¼ ð10:54849BÞð10:67004B12 Þat

(4)

SARIMA Model with Intervention and Permanent Effect Box, Jenkins, and Reinsel (1994) indicated that the effects of an intervention are temporary and will die out over time t, and then a pulse function is used. The inbound series in this study indicates that the ﬁrst impact of the September 21st Earthquake and SARS interventions started to take effect in September 1999 and April 2003, respectively. The intervention variables xt1 and xt2 are set to value 1 for September 1999 and April 2003, and 0 otherwise. According to Fig. 1, the effect of the single impulse lasted more than 1 month in the SARS impact, a second drop in May 2003 suggested a numerator lag, and the following exponential increase suggested a denominator lag in the transform function (Brocklebank & Dickey, 2003). We expect that the September 21st Earthquake had a similar type of intervention as the SARS incident and set the two intervention models in the form ðo01 o11 BÞ=ð1d11 BÞ xt1 and ðo02 o12 BÞ= ð1d12 BÞxt2 .

Intervention Analysis of Inbound Tourism: A Case Study of Taiwan

67

The maximum likelihood estimates of the SARIMA model with intervention are: o01 o11 B o02 o12 B ð1y1 BÞð1y12 B12 Þ xt1 þ xt2 þ at 1d11 B 1d12 B ð1BÞð1B12 Þ 0:146510:24804B 0:816481:46530B Yt ¼ xt1 þ xt2 10:77014B 10:58343B Yt ¼

þ

(5)

ð10:61184BÞð10:76488B12 Þ at ð1BÞð1B12 Þ

Table 1 presents the results of the estimation and shows that all estimate parameters are signiﬁcant with very small p-values. The Ljung–Box Q statistic is not signiﬁcant and indicates the SARIMA model with intervention does ﬁt well. Twenty-four lags of the sample ACF of the residuals are computed and displayed in Fig. 2. The sample ACF appears to be ‘‘clean,’’ indicating the residuals are random and the autocorrelations are within the 95% conﬁdence interval. The permanent effect of the SARS incident can be investigated by adding one level shift variable Lt , and deﬁning the level shift variable value to be 1 prior to April 2003, and 0 otherwise. The coefﬁcient of permanent effect l2 ¼ 0.0097, with standard error 0.0849, is not signiﬁcant. This means the permanent effect is not signiﬁcantly different from 0, indicating no permanent effect after the intervention event. This is equivalent to the term o2 B=ð1BÞ PðTÞ t , with permanent effect o2, and the transfer function suggested by Box and Tiao (1975) as following:

o1 B o2 B þ PðTÞ o0 þ 1dB 1B t

(6)

Table 1. Full-Intervention Model by Maximum Likelihood Estimation. Parameter

Estimate

Standard Error

t Value

p-value

Lag

y1 y12 o01 o11 d11 o02 o12 d12

0.61184 0.76488 0.14651 0.24804 0.77014 0.81648 1.46530 0.58343

0.04423 0.04031 0.05750 0.06165 0.07545 0.05726 0.06251 0.02118

13.83 18.97 2.55 4.02 10.21 14.26 23.44 27.55

o0.0001 o0.0001 0.0108 o0.0001 o0.0001 o0.0001 o0.0001 o0.0001

1 12 0 1 1 0 1 1

Variable

MA(1) MA(12) 9/21 Earthquake 9/21 Earthquake 9/21 Earthquake SARS SARS SARS

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JENNIFER C. H. MIN

Fig. 2.

Estimated Residual ACF on ARIMA Model with Intervention.

The inﬂuence of change rate d in event SARS, impacting the effect of transfer function It of the inbound series, is considered in the intervention model as follows: It ¼

o02 o12 B xt 1d12 B

¼ ðo02 o12 BÞð1 þ d12 B þ d212 B2 þ d312 B3 þ Þxt

(7)

¼ o02 xt þ ðo02 d12 o12 Þxt1 þ d12 ðo02 d12 o12 Þxt2 þ d212 ðo02 d12 o12 Þxt3 þ The same procedure to test the permanent effect of the earthquake is also applied. The results show that the coefﬁcient of permanent effect l1=0.0091282 with standard error 0.12089 is not signiﬁcant, indicating no permanent effect after the earthquake.

Intervention Analysis of Inbound Tourism: A Case Study of Taiwan

69

In the denominator of the transfer function of the SARS intervention, the change rate d12 ¼ 0:58343 indicates a faster approach to the preintervention level than that of the September 21st Earthquake with d11 ¼ 0:77014. Fig. 3 is a comparison of the difference between the impacts of September 21st Earthquake and SARS on inbound tourism, and Table 2 shows the impact of these two events on tourist numbers. 0.0%

the % of change

-10.0% -20.0% -30.0% -40.0% -50.0% -60.0% -70.0% -80.0% -90.0%

1

2

3

4

5

6

7

8

9

10

11

12

observation the September 21st Earthquake

Fig. 3.

SARS

Comparison between the September 21st Earthquake and SARS for Impact on Inbound Tourism.

Table 2.

Impact of the Two Events on Tourist Numbers.

September 21st Earthquake

SARS

Year/ Month

Impact in %

% Change on previous month

Year/ Month

Impact in %

% Change on previous month

1999/09 1999/10 1999/11 1999/12 2000/01 2000/02 2000/03 2000/04 2000/05 2000/06 2000/07 2000/08

13.6 30.3 24.3 19.3 15.2 11.9 9.3 7.3 5.6 4.4 3.4 2.6

– 16.7 6.0 5.0 4.1 3.3 2.6 2.0 1.7 1.2 1.0 0.8

2003/04 2003/05 2003/06 2003/07 2003/08 2003/09 2003/10 2003/11 2003/12 2004/01 2004/02 2004/03

55.8 85.7 67.8 48.4 32.0 20.1 12.3 7.4 4.4 2.6 1.5 0.9

– 29.9 17.9 19.4 16.4 11.9 7.8 4.9 3.0 1.8 1.1 0.6

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JENNIFER C. H. MIN

These two events occurred during the past decade, and both caused a dramatic decline in the number of tourist arrivals. According to Fig. 3 and Table 2, the drop in inbound arrivals after the SARS outbreak was clearly more severe compared with the September 21st Earthquake during the ﬁrst six observations following each intervention. This may be because the September 21st Earthquake struck only the central region of the island, whereas the travel warnings for the SARS illness issued by WHO extended to the whole island. For the impact caused by the earthquake, as illustrated in Table 2, the biggest decline in tourist arrivals fell in October 1999; since the earthquake occurred in late September, the impact for this month was not signiﬁcant. In the aftermath of the quake, the Taiwan government and tourism practitioners immediately adopted a series of countermeasures to encourage tourism. Routes of travel in Taiwan were designed such that international tourists would avoid the damaged scenic areas, for example, and tourism demand improved gradually. On the other hand, the fast spreading of the SARS virus caused fear and uneasiness for local residents and potential tourists from the beginning of the outbreak, and no one could predict when a vaccine would be discovered to eradicate SARS. The Taiwan government had no strategic response to the impact of a declining tourist market, though much effort was devoted to infection control procedures to prevent the disease from spreading further. The ﬁgures show an over 50% decline in visitor arrivals during April–June, particularly severe in May, to levels the island had never witnessed before. Comparing the recovery status from both events, the rebound status for the SARS impact was more robust than that of the September 21st Earthquake. As time passed, the Taiwan government established methods and procedures for SARS education, prevention, and treatment. In June, tourism rebounded from rock bottom numbers in May, which had been at a 67.8% decline. This ﬁgure is signiﬁcant because WHO removed Taiwan from its SARS travel advisory list in this month. At the same time, tourism organizations focused on an aggressive revitalization campaign in an effort to alleviate the difﬁculties brought about by the tourism shortfall and to attract tourist ﬂow. Although the psychological impact still generated fear with some potential travelers, the effectiveness of the campaign was evident in the increasing inﬂow of tourist trafﬁc after June. Table 2 indicates that the change in tourist arrivals caused by the September 21st Earthquake was much less than that caused by the SARS outbreak, but levels recovered more gradually. As shown in Fig. 3, the drop in inbound arrivals caused by the SARS illness surpassed those caused by the earthquake after the ninth observation, but only by a very small degree. It

Intervention Analysis of Inbound Tourism: A Case Study of Taiwan

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may be that tourism recovery from the earthquake was not as straightforward, as it took a longer time to rebuild the industry to predisaster levels as destroyed roads were reconstructed and ruined tourist facilities brought back into operation. In other words, while inbound tourism was more heavily inﬂuenced by the SARS epidemic, tourism recovery was swifter compared with the recovery after the September 21st Earthquake.

CONCLUSIONS This study employs intervention analysis to assess and compare the status of recovery after both the 1999 Earthquake and the 2003 SARS epidemic of international tourism demand in Taiwan. In terms of intervention analysis, the model has been used to study the impact of exceptional external events. The SARIMA with intervention model of the present research not only evaluated intervention effects, but also incorporated the intervention into the inbound time-series model to improve parameter estimates and forecasts. The empirical results presented in this paper have shown that Taiwan’s inbound tourism was immediately and severely affected by the two calamities, especially the SARS outbreak. The impact on inbound arrivals was greater at the beginning of the SARS outbreak, but recovery from the SARS intervention occurred in a similar time as recovery after the earthquake. In addition, although both of these events undermined the island’s tourism industry and impeded the ﬂow of tourists, inbound trafﬁc had almost returned to precatastrophe levels a year after these traumas, indicating the pulse impact on inbound movement of both the catastrophes. From these ﬁndings, government and tourism practitioners can learn to appreciate the dynamics of tourist behavior after negative occurrences. This study is not without limitations. The fact that only a univariate approach to inbound tourist arrivals was considered means that a variety of factors that affect demand, such as exchange rates, GDP, etc., were not considered. It is necessary in the future therefore to employ multiple time series to response variables through one or more explanatory variables. An autoregressive moving average with exogenous variables (ARMAX) technique can also be applied that investigates the dynamic relationships between variables. Accurate forecasts can assist the tourism sector to take signiﬁcant actions, manage tourism investments, develop accommodation, and devise comprehensive marketing approaches. Another potentially major limitation should be mentioned. It is important to recognize the possible pitfalls inherent in generalizing the results of this study based entirely on the

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cases of the September 21st Earthquake and the SARS impact. In this regard, other man-made or natural disasters, such as the September 11 terrorist attacks in 2001 and the Asian tsunami in late 2004, could be employed to enrich the ﬁndings and make the results more widely applicable. In addition, the model and methodology used in this article can readily be adapted to analyze the effects on, and recovery status of, air travel demand and tourism-related stock performance in Taiwan during and after the disasters’ occurrences. There is no doubt that the ﬂow of tourism is signiﬁcantly and immediately impacted by disastrous events. This paper employs a method that allows recovery status during and after the occurrence of a negative impact to be ascertained. In addition, this study clearly illustrates how the Taiwan government dealt with an unprecedented situation and developed measures for tourism recovery to diminish its harmful effects. This study can serve as a reference for the tourism industry of individual countries in employing proven methods and prompt strategies when they face such crises in the future.

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ANALYZING ROMANIA’S COMPETITIVENESS AS A TOURISM DESTINATION Ana Bobirca and Cristiana Cristureanu ABSTRACT The objective of this paper is to present an analysis on the competitiveness of Romania as a tourism destination, based on Porter’s diamond model. The model developed in this paper seeks to capture the main elements of competitiveness highlighted in the literature, while appreciating the special issues involved in exploring the notion of destination competitiveness as emphasized by tourism researchers. An overview of the Romanian tourism industry is included to test the findings of the proposed research model. Throughout the analysis, the paper also focuses on the most competitive export products and their prospects for improvement. The study allows for the identification of different tourism products potential, and can be used by industry and government to identify opportunities for competitiveness enhancement.

INTRODUCTION Tourism has become a ﬁercely competitive business for destinations the world over. Competitive advantage is no longer natural, but increasingly Advances in Hospitality and Leisure, Volume 4, 75–99 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00004-0

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man-made, driven by science, technology information, and innovation. As such, it is not simply the stock of natural resources of Romania that will determine its share on the tourism market, but rather how these resources are managed and integrated with other competencies to create a competitive advantage. To ensure that the beneﬁts from increasing globalization and integration are shared, all countries need to make certain that they achieve the necessary level of competitiveness. In the tourism sector, traditional models fail to give responses to questions such as: Why are countries that are characterized by an abundance of natural tourism attractions like sea, sun and beach, as well as cultural resources, losing competitiveness? Or, why are many destinations in developing countries, characterized by an abundance of resources and cost advantages, not able to create wealth and prosperity in tourism? The failure to provide responses to these questions advocates the need to set out new strategies for enhancing tourism destination competitiveness. The implications of this new conceptualization regard approaches, competitive resources, structures, and strategic actions. The constantly growing number of travel destinations and the enhanced quality of existing ones are putting great pressure on all stakeholders responsible for a given destination to ﬁnd better ways to compete in the tourism marketplace and to do so in a sustainable manner. The ﬁrst step in achieving this goal is to understand better those forces and success factors that determine the competitiveness of major tourism destinations. Success factors of a speciﬁc destination can then be identiﬁed and integrated to ensure sustainable growth for the destination within a competitive environment. The competitiveness of Romania as a tourism destination has been insufﬁciently analyzed, and the currently available results have not been used so far for the design of an efﬁcient economic tourism policy. Therefore, Romanian tourism can be considered potentially stronger in natural attractiveness (i.e. based on natural resources) than in its value-added products (e.g. cultural, wellness, business etc.). The aim of this paper is to present an analysis of the competitiveness of Romania as a tourist destination. To this end, the article is constructed as follows: ﬁrst, a literature review of the concept of destination competitiveness is presented. The second part of the paper sets out in detail the methodological framework for assessing tourism destination competitiveness. In the third part, the results of Romania’s tourism competitiveness analysis are revealed, subsequently supported, in the fourth part, by a statistical investigation of the tourism industry in Romania. The article

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concludes by illustrating potential strategies for Romania’s tourism development and by identifying research issues that require further study.

TOURISM DESTINATION COMPETITIVENESS The literature reveals various approaches in deﬁning, understanding, and measuring competitiveness. Perspectives in various disciplines indicate that competitiveness is a multi-faceted concept. Dwyer (2001, p. 44) regards the notion of competitiveness as associated with three major groups of thought. These are: (1) a comparative advantage and/or price competitiveness perspective (Bellak & Weiss, 1993; Cartwright, 1993; Durand & Giorno, 1987; Fagerberg, 1988; Fakiolas, 1985; Hilke & Nelson, 1988; Hodgetts, 1993; Porter, 1990; Rugman, 1991; Rugman & D’Cruz, 1993); (2) a strategy and management perspective (Day & Wensley, 1988; D’Cruz & Rugman, 1993; Ghoshal & Seok Ki, 1986; Grant, 1991; Kogut, 1985; Mahmoud, Rice, & Anders, 1992; Mahoney & Pandian, 1992; Mathur, 1992; Parsons, 1983; Peters, 1988; Porter, 1985, 1990, 1999; Porter & Millar, 1985; Powell, 1992a, 1992b; Yip, 1989); (3) a historical and socio-cultural perspective (Aaker, 1989; Franke, Hofstede, & Bond, 1991; Hofstede, 1980, 1983; Hofstede & Bond, 1988; Kennedy, 1987; Porter, Sachs, & McArthur, 2001). While economists have placed emphasis on price and country-speciﬁc economic characteristics of competitiveness, management and strategy researchers have concentrated on ﬁrm-speciﬁc characteristics, whereas the focus of sociologists and political theorists has been on various social, political, and cultural characteristics underlying the notion of competitiveness. Moreover, each group has suggested different indicators to explain or measure competitiveness (Dwyer, 2001, p. 45). The deﬁnitions offered in the literature provide both a micro and a macro connotation for the term competitiveness. From a macro perspective, competitiveness is a national concern and its ultimate goal is to improve the real income of its citizens. It is a very broad construct, encompassing all social, cultural, and economic variables affecting the performance of a nation in international markets (Dwyer, 2001, p. 45; Yoon, 2002, p. 32). On the other hand, from a micro perspective, it is seen as an organizationlevel phenomenon; organization-speciﬁc behaviors determine competitiveness. To be competitive, any organization must provide products and

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services for which customers or clients are willing to pay a fair return or price. In the long run and in a free enterprise system, competitiveness is measured by the ability of the organization to stay in business and to protect the organization’s investments, to earn a return on those investments, and to ensure jobs for the future (Porter, 1980, p. 113; Dwyer, 2001, p. 45). The current literature has tended to regard competitive advantage as value-added activities by ﬁrms and organizations, while de-emphasizing comparative advantage as a source of international competitiveness (Dwyer, 2001, p. 48). For a tourism destination, comparative advantage would relate to inherited or endowed resources such as climate, scenery, ﬂora and fauna, while competitive advantage would relate to a destination’s ability to use these resources over the long-term, such as quality of management, skills of workers, service levels, and government policy (Crouch and Ritchie, 1999, p. 142). The importance of these two pillars of international destination competitiveness will be brieﬂy discussed. Comparative advantages concern a destination’s factor endowments, both naturally occurring, as well as created. They are close to primary tourism supply (natural, cultural, and social attractiveness) and can never be reproduced with the same attractiveness. Porter (1990, p. 20), Crouch and Ritchie, (1999, p. 42), and Hill (2000, p. 130) identify ﬁve broad categories of endowments: human resources, physical resources, knowledge resources, capital resources, and infrastructure. In a tourism context, it seems appropriate to add historical and cultural resources, as an additional resource strategy and to expand the infrastructure category to include tourism superstructure (Crouch & Ritchie, 1999, p. 142). Crouch and Ritchie (1999, p. 143) argue that a country’s natural resources are an important source of comparative advantage in tourism. Where comparative advantages constitute resources available to a destination, competitive advantages relate to a destination’s ability to use these resources effectively over the long-term (Hamel & Prahalad, 1993, p. 56; Thompson, 1997, p. 23; Crouch & Ritchie, 1999, p. 143). Competitive factors refer to secondary tourism supply. They can be produced and improved by tourist ﬁrms or governmental policy. A destination endowed with a wealth of resources may not be as competitive as a destination lacking in resources, because the latter might be utilizing the little it has much more effectively. A destination that has a tourism vision, shares this vision among all stakeholders, acknowledges and understands both its strengths and weaknesses, develops a positioning strategy and implements it successfully may be more competitive because of its effective strategic approach.

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The most important of these is the ability of the tourism sector to add value to its products. The primary attractiveness can be a source for higher value added, but the value is only created through performing activities; it can occur that the comparative advantage is lost due to the uncompetitive secondary tourism supply. Thus, the support of tourism stakeholders is essential for successful development and sustainability of tourism and could help to improve destination competitiveness. As a result, the tourism destination will receive beneﬁts from enhanced competitiveness. A large number of variables appear to be linked to the notion of ‘‘destination competitiveness.’’ These include objectively measured variables such as visitor numbers, market share, tourist expenditure, employment, value added by the tourism industry, as well as subjectively measured variables such as ‘richness of culture and heritage,’ ‘quality of the tourism experience,’ etc. Thus, for example, competitiveness has been deﬁned as ‘the ability of a destination to maintain its market position and share and/or to improve upon them through time’ (d’Harteserre, 2000, p. 23). Hassan deﬁnes competitiveness as ‘the destination’s ability to create and integrate value-added products that sustain its resources while maintaining market position relative to competitors’ (Hassan, 2000, p. 239). According to other researchers, destination competitiveness is associated with the economic prosperity of residents of a country (Buhalis, 2000; Crouch & Ritchie, 1999). This is consistent with the view espoused by the World Economic Forum (Porter et al., 2001). Development designed to attract international visitors may have a range of purposes. Ultimately, however, it seems reasonable to focus attention on economic prosperity. That is, nations (or destinations) compete in the international tourism market primarily to foster the economic prosperity of residents. Although the end result of achieving destination competitiveness might well be enhanced by economic prosperity for residents, it should be emphasized that the link between tourism market share and economic contribution is not always obvious. Thus recent studies of tourism’s economic contribution to an area using computable general equilibrium modeling reveal that the expansion of tourism will often ‘crowd-out’ other economic sectors, resulting in a change in the composition of industry, rather than an expansion of economic activity (Adams & Parmenter, 1992; Dwyer & Forsyth, 1998; Dwyer, Forsyth, Madden, & Spurr, 2000; Dwyer, Forsyth, & Spurr, 2003). Poon (1993) suggests four key principles which destinations must follow if they are to be competitive: put the environment ﬁrst; make tourism a leading sector; strengthen the distribution channels in the market place; and build a dynamic private sector.

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Hassan (2000) has recently introduced a new model of competitiveness that focuses on environmental sustainability factors associated with travel destinations. Hassan posits four determinants of market competitiveness. These are comparative advantage (includes those factors associated with both the macro and micro environments that are critical to market competitiveness); demand orientation (the destination’s ability to respond to the changing nature of the market demand); industry structure (existence or absence of an organized tourism-related industry); and environmental commitment (the destination’s commitment to the environment). Underlying his model is a conviction that ‘‘a global perspective to understand key determinants of market competitiveness is critical for the tourism industry to sustain its growth and vitality’’ (Hassan, 2000, p. 239). The most detailed work undertaken by tourism researchers on overall tourism competitiveness is that by Crouch and Ritchie, who claim that in absolute terms the most competitive destination is the one that brings about the greatest success, that is, the most well-being for its residents, on a sustainable basis. Crouch and Ritchie (2000) state that competitiveness is illusory without sustainability. Thus, the most competitive destination is the one that most effectively creates sustainable well-being for its residents. This view is supported by Hassan (2000, p. 113), who deﬁnes destination competitiveness as ‘‘the destination’s ability to create and integrate value added products that sustain its resources, while maintaining market position relative to its competitors.’’ The systematic model of destination competitiveness proposed by Crouch and Ritchie (1999) points out that it is necessary to investigate and understand the relationships of interplay among the determinants of competitiveness. Furthermore, it has been suggested that a systematic analysis of the comparative and competitive advantages contributing to destination competitiveness is done. The national competitiveness model and its four determinants, proposed by Porter (1990), can be used as a fundamental source for explaining the determinants of destination competitiveness (Ritchie, 1993). These determinants are factor conditions (e.g. skilled labor, infrastructures), demand conditions (e.g. basic tourism services), related and supporting industries, and ﬁrm strategy, structure, and competition. Porter’s (1990) national ‘‘diamond’’ addresses competition in terms of the determinants of national advantage, in particular industries or industry segments. Whereas the ﬁve forces model could be applied at the level of the organization in the tourism industry, the national diamond model suggests the fundamental structure of competition among national tourism industries; that is, the nation as a tourism destination.

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After a thorough investigation of different methods for evaluating tourism destination competitiveness, we have selected Porter’s diamond model as a method for assessing the competitiveness of Romania as a tourism destination, based on the fact that various authors are supporting this view and recommend the use of the selected method for destination competitiveness assessment. Crouch and Ritchie (1999, p. 141) and Grant (1995, p. 340) claim that Porter’s diamond model is the best model for evaluating competitive advantage at a national level. A more speciﬁc rationale for the selection of this method is related both to the special features of the Romanian tourism market, as detailed below, and to the lack of reliable, recent, and detailed national statistics, that would normally favor a quantitative analysis.

DESTINATION COMPETITIVENESS ANALYSIS OF ROMANIA The study analyzes the potential comparative and competitive advantages that Romanian tourism may have, using Michael Porter’s Diamond Analysis Model, given in detail below (Fig. 1). Comparative advantage focuses on inherited factors of production, such as cheap labor, energy or natural resources, whereas competitive advantage is created through interlinked factors, which are often costly and difﬁcult for other countries to duplicate. Factor Conditions The various factor conditions are: (a) geography, (b) tourism products, (c) cost of labor, (d) infrastructure, (e) number of outlets for the development of high-skilled labor, (f ) cultural attitude towards tourism. (a) Romania has a temperate climate and a diversiﬁed landscape, ranging from mountains to hills and plains. It also has seaside resorts on the Black Sea coast, and the most important wildlife reserve in Europe (the Danube Delta). (b) Regarding the potential for developing different tourism products, natural health spas, and mineral waters are abundant; Romania also beneﬁts from cultural vestiges (from Greek and Roman ruins to Saxonbuilt medieval towns in Transylvania or the famous painted monasteries of Northern Moldova). (c) Wages are lower than in many parts of Europe, but (d) the Romanian infrastructure, which was built mainly in the 1960s–1970s and was targeted for mass tourism, has not been updated adequately since

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+ Varied geography + Varied tourism products + Cheap labor + Good cultural attitude toward tourism - Worn out but improving infrastructure - Low government promotion

Medium

+ Strong IT industry for support +/- Low number of capable suppliers - Few clusters

Low

+ Tourism development is priority for current government -/+ Delayed privatization -/+ Low competition within industry -/+ Focus on low-end of the market -/+ Weak but improving promotion of Romania as a holiday destination - Weak management and marketing skills

Strategy Structure Rivalry

Factor Conditions

Demand Conditions

Related & Supporting Industries

Low

+ Large population base -/+ Low but increasing sophistication of domestic demand - Domestic demand low / low purchasing power

Low Medium

Fig. 1.

Romanian Tourism Industry Diamond Analysis.

the 1980s and it is currently in a worn-out state. In the late 1990s, investment was targeted for improving the existing infrastructure and for building new facilities. Hotels were upgraded, widening the range of possible accommodations. However, four- and ﬁve-star accommodation facilities represent only 7.7% of the total number of establishments. Romania lacks necessary human resources, especially highly skilled labor in the tourism ﬁeld. (f ) On the other hand, Romanians have a strong, cultural tradition of hospitality that can be easily transferred into the tourism industry with proper training.

Demand Conditions The demand conditions are: (a) population base, (b) evolution of purchasing power (in the transition period), (c) international demand for Romanian tourism products, (d) characteristics and level of domestic demand.

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(a) With more than 22 million inhabitants, Romania is one of the largest countries in Europe, which means it possesses a greater chance for the use of facilities by domestic groups. (b) However, the purchasing power of Romanians is relatively low, and consequently, there is less pressure for hotels to upgrade their quality, because the majority of the market cannot afford three- to four-star hotels. Due to the dramatic drop in domestic purchasing power during the economic transition period, domestic demand for tourism has fallen drastically, particularly hitting the resorts targeting the lower-end of the market. Moreover, the higher-income segments of the population have taken advantage of the opening of the borders and traveled to foreign destinations. Thus, in 2006, the expenditures by Romanian tourists traveling abroad have been around US$454 million while Romanian receipts from foreign tourists visiting the same year were around US$467 million. (c) In the 1970s, most of Romania’s foreign tourists originated from European countries such as Germany, Great Britain, France, Italy, the Scandinavian countries; and from other socialist countries (East Germany, Czechoslovakia, and Poland). Beginning in the 1980s, the number of foreign tourists decreased signiﬁcantly. During the 1990s, the decreasing trend in the number of foreign tourists continued, falling from 6.5 million foreign visitors in 1990 to 5.2 million in 1999 and rebounding to 5.8 million in 2006. (d) Domestic tourists are increasingly traveling abroad and are now more likely to demand a higher quality and customer service in their home country.

Strategy and Structures The strategy and structures include: (a) extent of privatization, (b) level of competition among industry players, (c) regional competition, (d) focus of the market, (e) marketing and promotion activities. (a) The delay of government policy regarding privatization has severely hampered the competitiveness of the industry. (b) In terms of level of competition among industry players, there is some competition among the tier three- to four-star hotels and little among the pensions. Nationwide, accommodation facilities are scattered and those that are not in the same locale do not compete directly with each other. (c) In the same manner, the higher the competition in the region, the more likely it is that Romanian companies will have to upgrade their abilities to stay competitive. (d) Romania’s tourist industry caters mainly to the low-end market, which is not attractive to foreign tourists. (e) While creating a competitive market

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position is vital to the long-term success of a destination (Chen & Uysal, 2002, p. 1), the Romanian government has only recently taken more sophisticated measures to market Romania as a valued destination. At the same time, industry management and work skills are below world standard.

Related and Supporting Industries Related and supporting industries are: (a) number and importance of local suppliers, (b) clusters, (c) IT industry support. (a) The Romanian distribution and promotion networks are weak within the country. (b) There is little coordination or clustering among tour operators, except through the vehicles of business tourism organizations. (c) On the other hand, the strong Romanian IT industry can be an asset when automating the reservation systems and online marketing of tourism ﬁrms.

FACTS AND FIGURES SUPPORTING THE RESULTS As a result of applying Porter’s diamond model, the competitiveness of Romania as a tourism destination appears to be low, with prospects for improvement. Statistical data conﬁrm this assertion, as detailed in this section. Travel and tourism industry is not yet an important contributor to Romanian’s GDP and employment; in 2006, the travel and tourism industry contributed by 1.9% to the country’s GDP and accounted for 151,000 jobs, representing 1.6% of total employment (WTTC, 2006). Furthermore, it is estimated that visitor exports for the year 2006 represented only 1.1% of GDP (WTTC, 2007). Over the next 10 years, though, travel and tourism in Romania is forecasted to achieve an annualized real growth rate of 6.7%, taking the GDP’s share of travel and tourism to 5.8% in 2016. There is also a positive outlook for visitor exports, which are forecasted to grow at 8.5% per year, over the next 10 years, ranking Romania the fourth in the world, conﬁrming the expectations of an increase in competitiveness. It is also encouraging that, after 11 years of negative tourism balance, with a diminishing deﬁcit trend after 2001 ( 97 million Euro in 2001, 74 million Euro in 2002, 27 million Euro in 2003, 28 million Euro in 2004), the

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tourism balance has become slightly positive since 2005 (Romanian National Bank, 2006).

Factor Conditions The country has a wealth and diversity of natural resources, which form much of the ‘‘raw products’’ of tourism. This includes the Black Sea coast, the Danube and other river systems; the Carpathian and other mountain ranges and the Danube Delta Biosphere Reserve. Furthermore, there are 13 national parks and 13 natural reserves encompassing 7% of the country’s surface, with a great biodiversity, comprising many species of ﬂora and fauna unique to Europe. Romania has numerous villages and an attractive countryside offering excellent opportunities for rural tourism. A third of Europe’s natural springs are in Romania. There are 29 spa resorts designated as being of national importance and an additional 32 of local importance, which represent a major resource for health and beauty tourism, and also for medical treatments. The Romanian coast stretches 245 km from the Danube Delta in the north to the Bulgarian border and features long stretches of beach with major tourist resorts and ports. Over half of the country’s accommodation stock is on the coast. The religious built heritage also constitutes an important asset. There are 30 UNESCO World Heritage Sites including wooden churches, painted monasteries and fortresses, accompanied by a network of towns featuring a wealth of architectural monuments with several well preserved historic town centers. The road network is extensive, but remains below European standards. Planned infrastructure improvement projects should largely resolve this deﬁciency by 2015. The rail network is one of the most extensive in Europe. Much of the rolling stock requires modernization, and the electriﬁcation of more lines is essential. The network of regional airports is also quite broad, some of them having international scheduled services in addition to charter service. Bucharest has two airports with direct connections and frequent services to most European and regional capitals. The cruise trafﬁc on the Danube is increasing and sea-going cruise ships visiting Black Sea harbors are more frequent. Romania beneﬁts from a quite extensive hospitality network. The accommodation sector is now all but fully privatized, with 4,710

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accommodation units in 2006, compared to 3,873 accommodation units in 2005, representing a growth of 11.29% with respect to 2004. The total number of hotels was 969 in 2005, out of which: 8 were ﬁve-star hotels, 67 – four-star hotels, 260 – three-star hotels, 446 – two-star hotels, and 188 – onestar hotels. 65.43% of the hotel stock was at the lower-end of the market, encompassing one- and two-star hotels. In 2006, 70% of accommodation units were still two-star or lower. There has been an increase in the numbers of city hotels and particularly rural and urban guest houses in recent years. The supply of lower quality accommodation exceeds demand. On the contrary, there is an increasing demand, both domestic and foreign, for higher quality accommodation.

Demand Conditions Development of the tourism industry in Romania began in the 1960s and 1970s, based on a large domestic demand, on an inﬂux of incoming tourists from the former Soviet bloc countries (especially East Germany, Poland, Czechoslovakia, and the Soviet Union) and on a small number of budget tourists from Western Europe. Romania was mainly known for its ‘‘sea, sand, sun’’ products, health spas, and beautiful landscapes, while tourists were especially attracted by Romania’s low prices and rustic accommodation. Following the turning point of 1989, the Romanian tourism sector experienced a drastic decline, due to a dramatic drop in the purchasing power of tourists from the socialist countries, the lifting of restrictions on travel outside the Eastern bloc, and a paradoxical rise and continuous growth in the outbound demand. Suddenly, Romania was forced to compete with tourism destinations outside the Eastern bloc. Hence, it quickly became a net importer of tourism services. After years of declining visitor numbers and under-investment in development and modernization, Romania’s travel and tourism industry is slowly regaining proﬁle and pace. As Romania is advancing its development of the infrastructure and is improving its governance and legal systems, after its European Union (EU) accession at the beginning of 2007, the travel and tourism sector is supposed to play an ever increasing role, particularly in creating sustainable jobs for the country’s important rural population. If managed effectively, travel and tourism can be an important catalyst for the development of other economic sectors in Romania, such as manufacturing,

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Table 1.

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Foreign Visitors to Romania – 2006.

Origin

Visits

EU Non-EU Europe North America Israel Japan Rest of World

2,803,000 2,886,000 164,000 62,000 14,000 108,000

Total

6,037,000

Source: National Institute of Statistics (2007). Available at: https://statistici.insse.ro

construction, and other services. It can also help to preserve the country’s primary assets, namely its natural and cultural environments. In 2005, Romania received 5,839,374 foreign visitors, distributed as follows: 57.32% from its neighboring countries1 (26.07% from Hungary, 24.58% from the Republic of Moldova, 6.67% from Bulgaria), 14.59% from EU countries (6.06% from Germany, 4.64% from Italy, 2.21% from Austria, 1.88% from France, and only 0.5% from Spain). From non-EU Europe, the percentage was 11.77 (5.62% from Ukraine, 3.44% from Turkey, 2.53% from Serbia and Montenegro, 0.28% from Switzerland) and 2.05% from the US. The share of the Asian countries is insigniﬁcant (National Institute of Statistics, 2006). In 2006, the number of foreign visitors increased to 6,037,000, distributed as follows (Table 1). International tourist arrivals in all accommodation facilities have been steadily increasing for several years: 5.22% more foreign tourists in 2005 in comparison with 2004, and 56.28% more in comparison with 2001. Hotels received 89.44% of the total international tourist arrivals, followed by urban guest houses (3.27%), motels (1.55%), villas (1.54%), and rural guest houses (1.23%). Data on international tourist arrivals by market share offer a different structure by country of origin (WTTC, 2006): Italy is on the top position, with 13.62%, followed very close by Germany (13.41%), then by France (8.04%), Hungary (6.31%), United Kingdom (5.78%), Israel (5.09%), Austria (3.73%), Netherlands (2.93%), Spain (2.89%), and Turkey (2.23%). More than 5 million international visitors arrive in Romania by road (85%),2 about 700,000 visitors by air (12%),3 and the rest of the visitors by rail and by sea.

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Strategy and Structures Given the existing economic potential, much enhanced by the recent accession to the EU, the hospitality sector is set to develop over the coming years. The current trend is to invest in three- and four-star hotels. Although there are plans for a Q-label in hotels and star grading is underwritten by law, in general there is little standardization of accommodation stock, whether in terms of hotels, motels, bed and breakfasts, campsites or resorts, and concentration of facilities mirrors the traditional Romanian tourism products. The Romanian government has not invested adequately to ensure that Romanian products are promoted. For example, in 2004, the Romanian government tourist promotion budget was US$20 million. While this is high for Romanian standards, compared with government promotion budgets in Turkey, of US$75 million and in Greece, of US$150 million, it is insufﬁcient. The National Tourism Administration (NTA) does not currently have a clear strategy based on full and deep understanding of market characteristics and trends for the marketing of Romania. A series of market surveys was carried out in 2006, but no use has been made so far of the ﬁndings and conclusions to shape a coherent marketing and promotional strategy or program, based on a ranking of source markets. The mix of current marketing and promotional activities (i.e. ofﬁces abroad, tourism fair participation, web site, collateral materials, advertising) is not coordinated or designed to fulﬁll speciﬁc strategic objectives. There is insufﬁcient exposure of Romania and its tourist product offering in the media of main tourist source markets, leading to, at best, an unclear perception of the country as a serious and bona ﬁde tourist destination. In consequence, tour operators do not recognize a groundswell of demand for Romania from their customer base and do not actively consider introducing new programs to the country. In-depth knowledge of Romania and its tourist product offering is poor among tour operators and travel agency personnel in main tourist source markets. Romania does not have either a clear or strong image in the marketplace, and its destination branding gives mixed messages. The NTA is currently not regarded positively as a marketing organization, either by the Romanian tourism private sector or by regional or local administrations around the country. Left unchanged in terms of structure, personnel and systems, it will not achieve the necessary close and productive

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working partnerships necessary to lead to the establishment of Romania as a major tourism destination.

Related and Supporting Industries Financing is generally considered inadequate in the sector as well. Many small and medium-sized enterprises are unable to get ﬁnancing to refurbish their accommodation facilities and make other capital improvements. High collateral demands are often one of the barriers to receipt of such ﬁnancing. While linkages and networks are becoming stronger, they are still relatively weak compared to countries like Hungary and the Czech Republic. Many foreign tour operators are simply unaware of the Romanian market. The general low use of technology is another factor that makes Romanian tourism less competitive. Outside of the capital of Bucharest, computer usage and access to the Internet is patchy. Without a more reliable and sophisticated group of tour operators and small hotel owners with access to computers and the Internet, the ability to take advantage of growth in online reservations and promotions will not be captured. As a conclusion of this analysis, we can state that the facts and ﬁgures related to the Romanian tourism industry (as a quantitative assessment) conﬁrm not only the results of the competitiveness qualitative assessment based on Porter’s diamond model, but also the choice of the research method.

STRATEGIES FOR ROMANIA’S TOURISM DEVELOPMENT The planning of tourism development in Romania is still fragmented and uncoordinated. It has become obvious that the present process, although covered by extensive legislation, is failing to respond to the needs of tourism and its future development. Hence, a clear planning framework hierarchy should be established by the government to provide strategic guidance for the national development process.

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To remedy the current deﬁciencies mentioned above with respect to human resources involved in tourism, at minimum, the following actions should be taken: launching tourism awareness campaigns combined, where appropriate, with customer care training in schools (primary and secondary levels), among public sector employees and tourism staff at all levels. There should be established a series of regional Hospitality Training Institutes to deliver vocational training in addition to the development of up-to-date occupational standards. Romania presents a more favorable investment environment than many other countries in the region. Rates of VAT and corporation tax are generally lower and the accommodation sector enjoys a favorable 9% VAT rate. The presence of many European banks as well as a healthy Romanian banking sector means that loan facilities are becoming more competitive. Much of the investment in major new and renovated hotels has come from Romanian investors, but the involvement of renowned international hotel companies in management contracts has raised the proﬁle of the tourism sector among international investors. Many local investors have become involved in tourism, particularly in the guest house sector, but often with limited experience in the hospitality industry. While this sort of investment is welcome, guidance is clearly needed to encourage further investment and to avoid costly errors. There is currently a plethora of legislation relating directly to tourism. It is proposed that this should be consolidated in order to remove any anomalies, simplify comprehension, and improve ease of implementation. The tourism industry has also recognized the need to innovate its accommodation facilities, attractions, and products in order to develop the tourism sector, which requires public sector support and coordination. The following actions are indispensable for the accommodation sector: continued construction of new four- and ﬁve-star properties in selected areas with designs compatible with the environment and surroundings; upgrading of mid-range accommodation to meet higher visitor expectations; conversion of some low-grade accommodations to be used for other purposes – student accommodation, ofﬁces, etc. – or complete removal from the sector; signiﬁcant upgrade of some low-range accommodation to at least three-star level; continued improvements to all levels of accommodation, including units in national parks and nature reserves; review of the classiﬁcation system and introduction of a star rating system based on quality of service standards. Furthermore, improvements to existing attractions and the introduction of ‘‘new’’ attractions in tourism circuits is recommended, including

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museums and heritage attractions (museums and memorial buildings designated as of national or local importance should receive preferential consideration in respect of resources and technical assistance), salt mines (as an attraction for medical treatment and other tourism purposes), caves (to develop visitor access, thematic lighting, interpretation and visitor reception facilities and promote them as visitor attractions), and narrow gauge railways (with a particular appeal to visitors, combining heritage with activity and enjoyment of the countryside). Conversion of traditional Romanian tourism products (mass tourism – sun and beach and skiing) into more sophisticated products (spa, meetings, incentives, conferences, and exhibitions (MICE), cultural and heritage tourism, urban tourism, countryside, wine and culinary tourism, eco-, geo-, and active tourism) should be the main concern of the product strategy in the Romanian tourism industry. The new or improved tourism products should be designed by developing the traditional ones, such as coastal tourism, spa tourism, business tourism, rural tourism, cultural tourism, ecotourism, and adventure tourism. Coastal tourism experienced a decrease in visitor trafﬁc during the transition period, as the product offer failed to match increased visitor expectations. The reasons behind this situation are deep-rooted. What had previously been integrated resort developments under state control and management had evolved into hundreds of medium to small commercial operations with little relationship with each other. In the period since privatization, both the domestic and international tourist markets have matured and are now demanding a more sophisticated range of products and services. With fragmented ownership and no clear strategic direction, the seaside resorts have found it difﬁcult to respond to changing markets and have suffered as a result. Continued efforts are required to attract low cost carriers to seaside airports to increase destination publicity, as well as passengers. Studies into solutions of the beach erosion problem are on-going, but even if they provide successful solutions, there will still be a need for an increase in offbeach activities to fulﬁll the demands of today’s market, which requires ‘beach plus’ – not just beach activities, but additional excursions, inland activities, attraction visits, shopping, etc. Individual operator initiatives in upgrading and diversifying their product offer are essential but can only partly resolve the fundamental problems. For these to be solved, individual local resort authorities need to develop, on the one hand, integrated tourism development plans to give their resorts a clear direction, which will meet today’s market needs and provide season

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extending reasons to visit; on the other hand, resort management companies with all stakeholders as shareholders should be formed in order to overcome the disputes and deterioration in quality and variety of service provision that fragmented ownership has created. Spa tourism which is one of the most important products of specialized tourism in Romania is based on niche markets and oriented to senior highincome consumers. Currently, there are over 70 health resorts in Romania. Many of these resorts and spas are located in the Carpathian Mountains in Transylvania, close to the more than 3,000 mineral water springs – representing one-third of all Europe’s mineral and thermal springs. The main reasons for the development of such products are the demand of an aging European population, the opportunity to increase the average length of stay of tourists, as well as tourism receipts. In order to assist with the regeneration of spa resorts, the following actions should be taken: researching the domestic and foreign market demand for traditional spa treatment; investigating the expectations of foreign markets of spa resorts including details of facilities, treatments and activities; creating communication channels to spa clients; developing marketing campaigns (both by the NTA and spa resorts) to identiﬁed market segments; vesting of the concessions for the distribution of spring waters, muds, gases, and other natural therapeutic resources with local authorities to ensure equitable access for the common good; and preparing integrated resort development plans, with emphasis on the restoration of heritage buildings, as a pre-requisite to applications for funding. Romania, a member of NATO since 2004 and member of the EU since the beginning of 2007, with many conference and business centers, and with modern accommodation facilities in Bucharest as well as other towns, has a growing potential to develop the MICE sector. Conference facilities are available, albeit in short supply, as there are only 48 such facilities around the entire country. According to the Romanian Convention Bureau (RCB), some 900 conferences and events are held each year in the capital, thus MICE represents another important form of specialized tourism. In order to establish Romania as a competitive destination for international meetings and conventions commensurate with its membership of the EU, and to improve the seasonality of tourism, action must be taken to research the optimum size and conﬁguration of multi-purpose convention centers for major cities to meet potential market demand; develop purposebuilt convention centers as private/public sector partnerships; and upgrade

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the marketing of Romania as a destination for international meetings through a collaboration between the NTA and the RCB. Rural tourism is present in many regions of Romania but its major concentration is in the plains and mountainous regions, the Black Sea coast and the Danube Delta. At present, there are 4,000 tourist boarding houses throughout Romania, mainly for the domestic demand. The value of rural tourism products could be enhanced with gastronomic, wine, or handicraft attractions. Such an initiative would require partnerships and industrial links in every main region in order to develop and promote each destination and community, as well as cooperation among stakeholders in a chain of projects with shared information (cluster relationships). Although there has been a signiﬁcant increase in recent years in both the quality and quantity of rural accommodation, the formation of more local cooperatives of rural tourism products – attractions, accommodation, activities, and retailers – is still needed in order to focus visitor attention on particular areas of the country. Also, more non-accommodation product development is required in order to improve the range of visitor attractions and activities offered. In particular, opportunities exist for the environmentally sustainable expansion of visitor activities in protected areas, which can have a signiﬁcant beneﬁcial impact on local community suppliers in, and around, the protected areas. Better advance publicity of traditional rural events is also needed to facilitate visitor planning. Furthermore, it is recommended that the NTA give priority public relations and promotional assistance to the various rural associations, as the range of products and activities they foster represents some of the most important core values of Romania’s brand image. Cultural tourism is centered in four main locations: the painted monasteries of the Bucovina region;4 the castles, fortresses, and churches in the Northern region and in Transylvania; the art galleries and historical and contemporary sites in cities such as Bucharest, Brasov, Constanta, Sibiu, the last having a special signiﬁcance as the 2007 European Capital of Culture. Their maintenance and improvement for visitor enjoyment and appreciation is imperative. This requires improvement in visitor reception facilities, interpretation, as well as the provision of retail facilities and catering where appropriate. The visual arts, whether in museums or galleries, require similar presentation support. There is a deﬁciency in advance publicity for many cultural attractions, in time to permit tour planning and promotion, thus better event data collection and dissemination is required.

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Eco-, geo-, and adventure tourism is speciﬁc for the mountains, hills, along the Danube River and in the Danube Delta. Many of the mountainous areas are pristine lands, untouched by pollution, with fresh air and beautiful sites. Mountains are an attraction not only during winter season for skiing, but during spring, summer, and autumn as well. Leisure activities consist of hiking, hunting, ﬁshing, bird-watching, horseback riding, rafting on rivers, bungee jumping,5 and other less effort intensive sports like golf and tennis.6 Also, the many caves in the mountains are ideal places for adventure tourism and eco or geotourism. The natural and national parks are a strong attraction for tourists, too.7 Tourism along the Danube is still underdeveloped, but there are some projects underway to include the Danube in the tourism circuit, including medium long-term projects to modernize and upgrade the infrastructure. The Danube Delta is a biosphere reservation, with reed islands, inland lakes, oak forests, lianas, and sand dunes. Fishing, hunting, and bird-watching are major activities in the Delta, with a great potential for growth. Although the cruise trafﬁc on the Danube has been increasing rapidly in recent years, giving many tourists their ﬁrst impressions of Romania, the reception facilities at the docking points in Romania do not meet the standards of those provided by other countries through which the river ﬂows. To enhance these visitors’ experience, at least the following actions are required: provision of a central information point for cruise operators to communicate ship manifests, etc; coordination of harbor fees and charges into a uniform system that is competitive with other Danube countries; improvement of docking facilities, harbor reception facilities and landside access to and from docking facilities. With respect to marketing initiatives, a strategy based on a number of target market segments should be drawn up from a study of international tourism trends. The principal market segments could be: (a) International and domestic: Short breaks trips to Bucharest and, in time, other cities to which low cost carriers operate; business (including conferences) to Bucharest and other industrial/commercial locations in line with the rise in business activity following Romania’s accession to the EU; Black Sea coastal resorts – both among domestic tourists and from principal international markets of Germany, France, and Scandinavia as the resorts upgrade and diversify their offerings; health and wellness market – with existing spas developed to target the most appropriate sub-segments of the market; cultural/heritage tourism – probably the largest market opportunity focused on a series

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of ‘‘hubs’’ or ‘‘gateways’’ and featuring ‘‘tour circuits’’ either around ‘‘clusters of attractions’’ close to a single hub or linking together multiple hubs; adventure/sports – principally targeted at younger age groups. (b) International (mainly): Nature- and local community-based activities, lodging, etc. (collectively termed ecotourism, or more accurately, geotourism) i.e., small-to-mid scale operations in various parts of the country (especially in the Carpathians and the Danube Delta) and marketed as individual attractions and as part of an ecotourism circuit; young travelers – no European country has sought to identify itself as the principal destination for young travelers. Romania offers a good range of outdoor activities – both in summer and winter; it has a growing program of music, sports, and other events in Bucharest and elsewhere in the country; and it offers relatively low costs. These are all attributes that appeal to young travelers. (c) Domestic (mainly): Winter sports – in line with the growing interest for outdoor winter recreation among Romanians. However, with little growth potential in international markets because of the low height of slopes and lack of guaranteed snow and relatively difﬁcult access compared with other European ski centers; and recreation/theme parks – developed on the outskirts of major urban centers and resort areas (e.g. Bucharest, Constanta) to provide diversiﬁed entertainment facilities. Examples might include water parks, thrill rides, and folk/ culture parks (the last named also being an attraction for international tourist markets). By strategically targeting key products with export prospects, the tourism industry could realize its potential. Efforts should be focused on promoting products that will reduce the dependence of the tourism sector on the summer season, especially through the promotion of spa and conference tourism, as well as more sophisticated all-inclusive packages. In conclusion, this study analyzes the competitiveness of Romania as a tourism destination. Following the current literature, it established four main groups of variables. On the basis of obtained qualitative results, conﬁrmed by facts and ﬁgures related to the current status of the Romanian tourism industry, we revealed areas where improvements should be made. This research represents only one step in the analysis of Romania’s competitiveness as a tourism destination. Since it listed some of the main dimensions and indicators only, it is pivotal to further explore the

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importance of different attributes of destination competitiveness in more detail, in order to improve and maintain Romania’s competitive position as a tourism destination on the international market.

NOTES 1. This explains why, for 2005, international tourist arrivals in all accommodation facilities were of only 1,429,911, representing 24.63% of total arrivals, out of which 81.99% from European countries, 8.44% from Asia, and 7.66% from North America (National Institute of Statistics, 2006). 2. There are 198,817 km of roadways in Romania, including 228 km of expressways. 3. There are 17 airports in Romania, out of which 4 are international. Regular and charter ﬂights of Romanian air carriers and foreign airlines connect Bucharest with the world’s major airports. Henri Coanda International Airport, one of the largest in South-Eastern Europe, received 3,035,511 passengers in 2005 and is expected to handle 4 million passengers by the end of 2007. 4. The ‘‘Golden Apple’’ distinction of the International Federation of Tourism Journalists and Writers (a UNESCO ofﬁce) was granted to the painted monasteries of Bucovina. 5. Rasnoava Gorges in the Postavaru Mountains is the second highest bungee jumping place in Europe. 6. After a prohibition period during the communist regime, golf is intensely promoted and the golf ﬁelds are being improved. In 2004, the Romanian Golf Federation was set up, afﬁliated to R&A (the golf’s world rules and development body and organizer of The Open Championship), United States Golf Association, and International Golf Federation. There are three golf clubs in Romania: in Pianu de Jos (county Alba) – ﬁeld with nine holes, in Breaza (on the Prahova Valley) – ﬁeld with nine holes, and in Bucharest, near Herastrau Park – ﬁeld with six holes. 7. Retezat National Park (at the same time national park and biosphere reservation), Piatra Craiului National Park, Vanatori Neamt Natural Park, Bucegi National Park, Rodnei Mountains National Park, Domogled-Valea Cernei National Park, Apuseni Natural Park, Calimani National Park.

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SERVICE PERFORMANCE MEASUREMENT: DEVELOPING CUSTOMER PERSPECTIVE CALCULATORS FOR THE HOTEL INDUSTRY Choon-Chiang Leong ABSTRACT The purpose of this research was an attempt to improve the applicability of the balance scorecard, in particular the customer perspective, in the hospitality industry. The objective of the study was to investigate a more structured customer-centric performance measurement framework customized for the hotel industry. Hence, this paper presents the ‘‘Customer Calculator’’ which had been developed based on the Customer Equity model proposed by Rust et al. (2000a). Qualitative examinations by interviewing hotel management were conducted to test the applicability of the customer-centric measurement framework. The customer scores facilitate hotel decision-makers who can pinpoint the important drivers of customer relations, which are in need of further action and improvement. The framework can also be employed by the stakeholders to assess hotel performance in general.

Advances in Hospitality and Leisure, Volume 4, 101–120 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00005-2

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INTRODUCTION The changing global landscape had brought about an unexpected increase in volatility of all business sectors, which rendered ﬁnancial measurements less reﬂective of performance. The international hotel industry was facing many changes, as summarized by Litteljohn (1997). Dynamic changes to the hotel industry, especially the increased bargaining power of the customer, are rendering ﬁnancial performance measurement systems inadequate in assessing the customer’s view of the hotel’s performance. Researchers Ghosh, Leong, and Lee (1999) recommended a multifaceted performance measurement system for the hotel industry. Clearly, a framework that is customercentric in nature may be necessary for such a predominantly service-oriented industry to better reﬂect the main driving force behind hotels’ revenue – its customers. As the hotel guest plays a dominant role in the hotel’s service delivery and revenue generation, the need for customer focus in performance measurement is crucial. As such, holistic tools, which incorporate both ﬁnancial and nonﬁnancial measurements, such as the balanced scorecard (BSC), are gradually being introduced in hotels. The BSC is a widely acknowledged panacea for the problems of ﬁnancial performance measurements since its introduction by Kaplan and Norton (1992) and has been widely implemented worldwide since then. Recent ﬁgures show that approximately 50% of Fortune 1000 companies in North America and about 40% in Europe utilize this holistic performance measurement tool. Like many other tools, the BSC is not without its shortcomings. Despite its popularity, the complexity and time involved in development and implementation may result in costs outweighing beneﬁts from improved organizational performance (Newing, 1994). Hence, management may opt for partial implementation of the BSC which would result in its inability to be used as the overall goal congruency system previously intended (Dinesh & Palmer, 1998). Ittner and Larcker (2003) found that many top executives simply ordered their middle management to come up with key performance indices (KPIs) for each of the four perspectives, regardless of their business unit’s strategy or objectives. This resulted in the KPIs being criticized as unstructured and the BSC hence being described as a ‘‘smorgasbord.’’ Moreover, there is a lack of trust in the reliability of non-ﬁnancial KPIs under the BSC due to the plethora of methods to measure various nonﬁnancial aspects of performance, which had subsequently caused a lack of comparability of measurements across organizations. However, the application of BSC has been evident in some hotels across the world such as the Hilton and Marriot hotel chains (Huckestein & Duboff, 2000).

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In light of the limitations of the non-ﬁnancial perspectives of the BSC given above, a structured conceptual framework that can establish the relationship between these various KPIs would arguably be an improvement as management would then have a clearer picture of the organization’s performance. For improving the measurement of the hotel’s performance from the Customer Perspective of the BSC, a customer-centric conceptual framework was developed. This framework would utilize the Customer Equity model presented by Rust, Danaher, and Varki (2000a), to identify its main components, due to the similarity between the KPIs under the BSC’s Customer Perspective and the constructs under the Customer Equity framework. The objectives of this study were: ﬁrst, to develop a customer-centric performance measurement framework that may enable hotels to better assess performance from the Customer Perspective of the BSC; and second, to examine the applicability of the resulting customer-centric performance measurement framework for measuring the performance of hotels from the Customer Perspective.

LITERATURE REVIEW Performance Measurement Performance measurement is integral to the planning and control cycle of organizations (Barnard, 1962), useful for external and internal reporting to stakeholders and for control. Proper measurements enhance shareholders’ value creation and revenue growth (Hamid, 2002). Within the organization, it sets standards and targets, tracks progress, motivates, communicates organizational strategic intent, and inﬂuences behavior modiﬁcation (Takikonda, 1998). In recent years, many researchers have been critical of the continued usage of ﬁnancial performance measurements arguing they are too backward looking and not predictive of future performance. Also, ﬁnancial measurements are non-holistic and more outcome rather than process-focused (Ittner & Larcker, 1998; Yeniyurt, 2003). Previously successful measurements are becoming obsolete, dysfunctional, and obstructive to improvement (Takikonda, 1998). Financial accounting measurements have also been deemed lagging indicators, non-predictive of future performance (Denton & White, 2000). A revolution of ﬁnancial performance measurements was occurring in a variety of industries (Eccles, 1991; Neely, 1999). As the dynamic and rapidly changing competitive

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environment has important implications on the organization, it is important that performance measurement systems are effectively managed to remain appropriate and provide information relevant to issues of current importance (Neely et al., 1996; Kennerley & Neely, 2003). More attention needs to be paid to non-ﬁnancial dimensions (Harris & Mongiello, 2001), which are essential for corporate survival and competitive advantage (Philips, 1999). Speciﬁcally in the hotel industry, Brown and McDonnell (1995) have in fact suggested constantly updating performance measurements to accurately reﬂect a hotel’s unique strategy, i.e. speciﬁc activities and kinds of products and services offered. Also, measurements reﬂecting the complex nature of the service delivery process are needed to be implemented throughout the hotel to ensure actions are aligned to strategies and objectives (Fitzgerald, Johnston, Brignall, Silvestro, & Voss, 1991; Lynch & Cross, 1991). A study of averages such as RevPar by Enz, Canina, and Walsh (2001) found hotel performance frequently overstated, with no measure of value creation (Lehn & Makhija, 1996). This need for the incorporation of non-ﬁnancial criteria is especially critical for the hotel industry due to its customer-centric nature (Ghosh et al., 1999). The importance of the customer and non-ﬁnancial performance measurements to the hotel industry cannot be over-emphasized. The customercentric nature of the hotel industry has been ascertained over the years with reasons postulated such as the experiential nature of the hotel and the pervasive presence of the customer at the center of the hotel’s service delivery (Reuland, Choudry, & Fagel, 1990; Carman, 1990; Hepple, Kipps, & Thomson, 1990; Kivela, 1996; Blum, 1997). Literature has supported the relationship of non-ﬁnancial dimensions such as customer satisfaction and loyalty to ﬁnancial performance measurements such as proﬁtability (Heskett, Jones, Loveman, Sasser, & Schlesinger, 1994; Anderson, Fornell, & Lehmann, 1994). Hotel managers in current practice are recognizing that a critical operational success factor is to fulﬁll the multifaceted needs of their hotel guests (Geller, 1985). There is also ample empirical evidence in Singapore of the usage of non-ﬁnancial criteria such as customer satisfaction in hotels’ performance measurement (Ghosh et al., 1999). Several performance measurements covering a wider spectrum of attributes, including non-ﬁnancial dimensions, have been developed. Studies have produced several notable non-ﬁnancial measurement systems for dimensions such as service quality (SERVQUAL) (Parasuraman, Zeithaml, & Barry, 1988), brand strength (Prasad & Dev, 2000), customer satisfaction

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(Jones & Ioannou, 1993; Behara, Fontenot, & Gresham, 1995; Heide, Gronhaug, & Engset, 1999; Yu & Dean, 2001), and customer loyalty (Kandampully & Suhartanto, 2000). In addition, holistic approaches, such as the Scandia navigator, the Market Metrix Hotel Index (Barsky, 2001), and the well-known Balanced Scorecard are attempting to introduce ‘‘balance’’ and strategic planning into performance measurements (Kaplan & Norton, 1992), and accommodate dynamic shifts within the business environment. The BSC emerged in the 1990s as a signiﬁcant resolution to the failures of ﬁnancial performance measurements and to function as the cornerstone measurement of an organization’s current and future success. Its four components, the Financial, Customer, Internal Business and Innovation, and Learning Perspectives, form a comprehensive framework that translates an organization’s strategic objectives into a coherent set of KPIs to motivate improvements in critical areas and hence drive change in competitive performance (Kaplan & Norton, 1993, 1996a). As an information system, the BSC facilitates information processing by ﬁltering out unnecessary information and reducing information overload faced by decision-makers (McWhorter, 2003). The Customer Perspective is deﬁned as the ‘‘performance of the organization in the eyes of the customer.’’ Customers’ concerns mainly fall into four categories of time, quality, performance and service, and cost (Kaplan & Norton, 1992). Some KPIs used in the Customer Perspective include number of repeat customers, customer brand preference, response time per customer request, and customer satisfaction (Pizam & Ellis, 1999; Ghosh et al., 1999).

METHOD In this study, the ﬁrst stage was to develop a customer-centric performance measurement framework, customized to the hotel industry. This framework was developed based on the Customer Equity model (Rust et al., 2000a) to structure the KPIs of the BSC’s Customer Perspective. The ﬁnal resulting customer-centric performance measurement framework, termed the Customer Calculator, can be used to derive a hotel performance score (i.e. the Customer Score).

The Customer Equity Measurement Framework The Customer Equity model (Rust et al., 2000a; Rust, Lemon, & Zeithaml, 2000b) departs from the outdated view of only looking at product proﬁtability

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or Brand Equity. It comprises three actionable drivers (Value, Brand, and Retention) established after a series of factor analyses were conducted across several industries. Researchers reveal the ‘‘voice of the customer’’ and correspond to distinctly managed elements of modern marketing practice, i.e. customer value management, brand equity management, and customer relationship management. The three drivers: Value Equity, Brand Equity, and Retention Equity allow the organization to apportion and direct its limited resources according to its business strategy to attain the greatest impact on proﬁtability as the organization’s environment changes. Value Equity Rust et al. (2000a, 2000b) proposed two approaches which may best achieve value enhancement: to give more of what the customer wants or to reduce what the customer has to sacriﬁce. They also found that the failure to enhance and measure value and customer priorities may result in value migration and loss of market share. Three key antecedents of Value Equity have been identiﬁed through examination of the literature: quality, price, and convenience. Zeithaml (1988) deﬁnes perceived quality as the ‘‘consumer’s judgment about a product’s overall excellence or superiority.’’ Convenience was found to contribute to perceptions of value, as a higher value abstraction, and sacriﬁces made in terms of time and effort have been found to reduce value in the eyes of less price conscious consumers. Researchers had further identiﬁed ﬁve main dimensions of service quality: tangibles, responsiveness, empathy, reliability, and assurance (Parasuraman et al., 1988). It is imperative that service organizations like hotels go beyond merely attaining ‘‘zero defects’’ to ‘‘delighting’’ the customer in-service delivery (Kano, Seraku, Takahashi, & Tsuji, 1984; Oliver, Rust, & Varki, 1997). From the consumers’ perspective, price is what is given up for what is obtained. It is often used as an extrinsic cue for quality and appears to function as a surrogate for quality when consumers have inadequate information about intrinsic attributes. The linkage of convenience to customer value and customer choice has also emerged. An empirical study found that guests in a luxury hotel listed a ‘‘worry-free’’ stay as a top priority (Du`be & Ranaghan, 1999).

Brand Equity For this research, a narrower deﬁnition of Brand Equity was adopted: ‘‘the customer’s subjective and intangible assessment of the brand, above

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and beyond its objectively-perceived value’’ (Rust et al., 2000b). They identiﬁed three antecedents of Brand Equity: customer brand awareness, customer attitude toward the brand, and customers’ perceptions of brand ethics. Simon and Sullivan (1993) had ﬁrst established advertising factors as the link between brand awareness and Brand Equity, and this link was recently further afﬁrmed by Chaudhuri (2002). In particular, inconsistent marketing mix variables and brand communications were found to affect Brand Equity. Good corporate citizenship has been demonstrated substantially in the literature to have a strong relationship with consumer brand choice (Grifﬁn, Babin, & Darden, 1992; Weaver, Trevino, & Cochran, 1999; Bone & Corey, 2000). Corporate citizenship encompasses many issues such as human rights, the environment, economics, work–family, philanthropy, and community relations (Center for Corporate Citizenship at Boston College, 2002). It refers to an organization being socially responsible by giving back to the community in which they operate. In the hotel industry, this may range from operating an environmentally conscious hotel that follows good waste management and energy conservation procedures, to a socially responsible hotel that observes good precautionary measures to ensure the well being of guests and the local community. In this study, the term ‘‘brand ethics’’ was substituted with ‘‘corporate citizenship.’’

Retention Equity Rust et al. (2000b) presented a narrowed-down deﬁnition of Retention Equity: ‘‘the incremental tendency of the customer to stick with the brand, above and beyond the customer’s objective and subjective assessments of the brand, arising from relationship management.’’ Extensive research had shown a link between customer retention and organizational success. In recent years, notably for the hospitality industry, there has been a growing interest in developing loyal customers through relationship marketing and a large focus so far on transactional tactics such as customer loyalty programs. For a more relevant application to the hotel industry in the present study, Rust et al.’s ﬁve antecedents of Retention Equity have been narrowed to three: customer loyalty rewards, special recognition and treatment, and customer knowledge. To secure retention of a customer in a competitive market, the supplier’s total value package has to meet the targeted customer’s requirement over and above its competitors. This is especially so for the hotel industry which is characterized by high parity of products and services. A hotel may gain a guest’s sustainable loyalty

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through treating them with individual care and delivering relevant values. Properly designed databases aid organizations such as hotels in tracking guests’ preferences, and enable the delivery of customized services. Such customization has been found to increase customer-returning rates.

Questionnaires A questionnaire was developed to complement the Customer Calculator under the various drivers of the framework. A preliminary questionnaire customized to the hotel industry was ﬁrst constructed, closely following the sample questionnaire of Rust, Lemon, and Narayandas (2004). It was further reﬁned through two pilot tests and an interview with a BSC practitioner. The ﬁnal questionnaire comprised of 27 questions in four sections. Section A contained questions to gather demographic data of respondents. Section B contained sub-drivers’ questions for identifying the different service points in a hotel. It provided measurement of the hotel performance at each service point and also accounted for the fact that a customer might not have been in contact with all the service points. Section C contained sub-drivers’ forced response questions. A fourpoint Likert scale was adopted to eliminate a ‘‘neutral’’ option. Section D contained questions to determine weights attribution. A scale of 10 was used for ease of indication of customer-perceived weights to each attribute. A ﬁeld study was conducted in two Singapore ﬁve-star hotels, Hotel A and Hotel B, to test the reliability of the Customer Calculator framework. A stratiﬁed sample of 200 respondents was taken from each hotel. A series of Pearson’s two-tailed correlation tests were carried out to assess the reliability of the data collected in the ﬁeld study. The F-statistics ( f 2) value was calculated to determine the strength of the correlation (Cohen, 1988). The Customer Score was then calculated and analyzed through two analyses, i.e. Score Analysis and Weight Analysis, to demonstrate the usefulness of the Customer Calculator. The reliability for each main driver of the Customer Calculator was tested using the Pearson correlation ‘‘r.’’ The three main drivers and nine subdrivers adopted for the hotel’s performance from its guests’ perspective were transposed onto a calculator template, similar to the Risk Calculator created by Simons (1999). This template provides a more structured organization of the drivers. A scoring system was formulated to aid the derivation of a performance score under this framework. The ﬁnal developed framework, with its scoring

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system, was named the Customer Calculator. The performance score derived was termed the Customer Score. Under this scoring system, respondents were classiﬁed into two groups, ‘‘repeat’’ customers and ‘‘ﬁrsttime’’ customers, and similar statistical calculations were performed for both customers. The main driver for Value Equity (A) was examined ﬁrst. The ﬁrst sub-driver score (SA1), Price, was calculated by taking the mean score of the responses to all relevant questions measuring this sub-driver. This was repeated for the other two subdrivers, Quality and Convenience, to obtain their scores (SA2 and SA3). The formula for the sub-driver scores is as follows: S ki ¼ Mean score of all relevant questions measuring each sub-driver i (1) where k indicates the main drivers (A–Value Equity, B–Brand Equity, C–Retention Equity) and i the sub-drivers (sub-driver 1, sub-driver 2, subdriver 3). Next, each sub-driver score (Ski) was multiplied by its corresponding weight (Wki). By summing up the weighted score of the three sub-drivers, the main driver score (MA) for Value Equity was obtained. Using Eq. (1), we calculate score (Mk) for each main driver k: X Mk ¼ W ki S ki (2) where Mk is the sum of weighted sub-driver scores for main driver k, and Wki the weight in percentage of each sub-driver i of the main driver k. The above steps were repeated to calculate the main driver score (MB) for Brand Equity, and Retention Equity (MC) for ‘‘repeat’’ customers. The Retention Equity score for ‘‘ﬁrst-time’’ hotel customers was calculated separately by taking the mean score which measured Retention Equity. To obtain the performance of the hotel in the eyes of each customer, En, the corresponding weight attributed to each main driver (Wk) was multiplied by the main driver score (Mk) derived in Eq. (2). It is presented as follows: X En ¼ W kMk (3) where En is the sum of weighted main driver scores, n the nth respondent, Wk the weight in percentage terms of the main driver k, and Mk the score of the main driver k. The hotel’s overall performance score (C ), which reﬂects the average performance of the hotel in the eyes of all its customers, was calculated by taking the grand mean of the hotel performance score (En) of each

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respondent as follows:

P

En N where N is the total number of respondents. C¼

(4)

FINDINGS AND DISCUSSIONS Distribution of Stratified Samples Based on the guest proﬁle provided by the hotels under study, a stratiﬁed sampling plan was designed, using ‘‘purpose of stay’’ as the basis of stratiﬁcation. The sample collected had 200 guests from each hotel. The number of ﬁrst-time and repeat customers from Hotel A were 95 and 105, respectively, while that from Hotel B were 104 and 96, respectively. Distribution of respondents collected by stratiﬁed sampling method from Hotel A and Hotel B are presented in Table 1.

Reliability Tests for the Questionnaire Tool The results of correlation test for reliability of the questionnaire tool are presented in Table 2. Correlation coefﬁcients signiﬁcant at the 0.01 level of the two-tailed test were highlighted. All questions tested as shown in the table are highly correlated. Reverse-scale questions had always been used by Table 1.

Distributions of Stratiﬁed Samples Collected from Hotel A and Hotel B. Hotel A

Hotel B

Total

%

Type of travelers Free and Independent Corporate Leisure/tour group Others Total

88 66 16 30 200

50 100 6 44 200

138 166 22 74 400

34.5 41.5 5.5 18.5 100

Visitation First-time customer Repeat customer Total

95 105 200

104 96 200

199 201 400

49.75 50.25 100

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Table 2. Results of Correlation Test for Reliability of the Questionnaire Tool. Hotel A

Hotel B

Correlation test for reversed scale question Question 14 Question 14

Question 16

Pearson correlation N Pearson correlation N

1

Question 16 0.269

Question 14 1

Question 16 0.150

200 0.269

200 1

200 0.150

200 1

200

200

200

200

Correlation test for Value driver Question 9 Question 9

Value driver

Pearson correlation N Pearson correlation N

1

Value driver 0.518

Question 9 1

Value driver 0.489

200 0.518

200 1

200 0.489

200 1

200

200

200

200

Correlation test for Brand driver Question 17 Question 17

Brand driver

Pearson correlation N Pearson correlation N

1

Brand driver 0.322

Question 17 1

Brand driver 0.312

200 0.322

200 1

200 0.312

200 1

200

200

200

200

Correlation test for Retention driver for ‘‘Repeat’’ customers Question 23 Question 23

Pearson correlation N Retention driver Pearson correlation N

1

Retention driver 0.434

Question 23 1

Retention driver 0.666

105 0.434

105 1

96 0.666

96 1

105

105

96

96

Correlation signiﬁcant at the 0.05 level (two-tailed). Correlation signiﬁcant at the 0.01 level (two-tailed).

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marketing researchers in questionnaires to test respondents’ understanding of questions and hence to determine the reliability of their responses. To determine the reliability of the responses collected for this study, the reverse-scale question, i.e. Q16: ‘‘I prefer not to be associated with the hotel,’’ was ﬁrst recorded. Next, a Pearson’s correlation test between the recorded variable and Q14: ‘‘I have a positive attitude towards the hotel,’’ was then conducted. A signiﬁcant correlation between the answers to these two questions afﬁrmed the reliability of the response, i.e. the respondent was paying attention when answering the questionnaire (Zikmund, 2003). From the results in Table 2, Hotel A was signiﬁcantly correlated at the 99% conﬁdence level with a Pearson’s correlation coefﬁcient r value of 0.269. For Hotel B, the questions were signiﬁcantly correlated at the 95% conﬁdence level with r value of 0.150. Thus, it can be concluded that the data reliability from both hotels was high. A summary of Pearson correlation (r) and F-statistics ( f 2) for Hotel A and Hotel B is presented in Table 3. All the r values obtained from the three correlation tests conducted for each hotel showed that the test variables were signiﬁcantly correlated at a 99% conﬁdence level. This proved the sub-driver questions’ reliability to measure their corresponding main driver. For both hotels, the f 2 values obtained for the Value driver (Hotel A: 0.367, Hotel B: 0.314) and Retention driver (Hotel A: 0.232, Hotel B: 0.797) tests indicated a medium-to-large effect size between the test variables, thereby reﬂecting that the composite main driver score and the general main driver score are strongly correlated. Thus, it can be concluded that the sub-driver questions reliably measure their corresponding main driver to a large extent. However, the f 2 values obtained in the Brand driver test for both hotels (Hotel A: 0.116, Hotel B: 0.108) indicated a small effect size between the test variables, thereby reﬂecting that the composite main driver score and the general main driver score are correlated to a smaller extent. This could be attributed to the Table 3.

Pearson Correlation (r) and F-Statistics ( f 2) for Hotel A and Hotel B. Hotel A f2

r Value driver test Brand driver test Retention driver test

0.518 0.322 0.434

Hotel B

0.367 0.116 0.232

f2

r Large Small Medium

0.489 0.312 0.666

0.314 0.108 0.797

Medium Small Large

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abstractness of the Brand Equity sub-drivers questions, causing difﬁculties in interpretation for some respondents. Evidence on the Usefulness of the Customer Calculator The data collected from both hotels were fed into the Customer Calculator. The Customer Score was subsequently calculated and analyzed through two analyses, i.e. Score Analysis and Weight Analysis, to demonstrate the usefulness of the Customer Calculator. Table 4, for example, presents the Customer Calculator of Hotel A and the respective scores of the ﬁrst-time customers. The Customer Scores for ﬁrst-time customers and repeat customers of Hotel A and Hotel B are summarized in Table 5. Generally, both Hotel A and B had a Customer Score above the mid-point score of 2.5, indicating both were performing above average in the eyes of their customers. A fourpoint Likert scale was adopted to eliminate a ‘‘neutral’’ option. An analysis of ‘‘ﬁrst-time’’ Customer Scores disclosed that the Brand driver has the lowest score relative to the other two main drivers for both hotels, and was thus singled out as the poorest performing driver (Hotel A: 74.8%; Hotel B: 74.0%). From the results of the Weight Analysis, it could be seen that the Value driver for both hotels was the most important to ‘‘ﬁrst-time’’ customers, with a relatively highest weight of 56.6 and 62.5% for Hotels A and B, respectively. Therefore, a decision based on Weight Analysis could be made regarding the direction of management attention to the three Value subdrivers. Alternatively, the hotel could choose to rely on the Score Analysis and improve its performance on the weakest performing driver identiﬁed. The breakdown of the Brand driver showed that the awareness sub-driver scored the lowest for both hotels suggesting that their customers might be paying sufﬁcient attention to their publicity and marketing efforts. From the results of the Weight Analysis, it was found that among the other two sub-drivers, the attitude sub-driver was more important to customers for both Hotels A and B, with a relatively high weight of 38.0 and 45.8%, respectively. This mitigated the consequence of poor performance in the awareness sub-driver, as it was not the most important to customers. This also suggested that the hotels could either choose to improve their awareness sub-driver or put effort in maintaining the high score for the attitude subdriver since it was the most important Brand sub-driver to customers. Analysis of ‘‘Repeat’’ Customer Scores From the results of the Score Analysis, Hotels A and B scored the lowest for the Retention driver, i.e. 69.8 and 71.8%, respectively. From the result of the Weight Analysis, it could be seen the Value driver for Hotels A and B was the

N/A

N/A

Note: N/A, Not Applicable.

Weight (N/A)

Weight (N/A)

Weight (WC=17.6%)

2. Special recognition and treatment:

1. Customer loyalty rewards:

N/A

Weight (N/A)

3. Customer knowledge:

Score SB3=3.04

Score SB2=3.27

Score SB1=2.56

C. Retention Equity:

Weight (WB3=33.0%)

Weight (WB2=38.0%)

Weight (WB1=29.0%)

3. Corporate citizenship:

Score SB3=3.28

Weight (WA3=32.0%)

Weight (WB=25.8%)

Score SA2=3.25

Score SA1=3.13 2. Customer attitude towards brand:

Weight (WA2=34.8%)

Weight (WA1=33.2%)

3. Convenience:

1. Customer brand awareness:

2. Quality:

1. Price:

Sub-Drivers (i)

P M C ¼ W Ci S Ci Score MC=3.33

P M B ¼ W Bi SBi Score MB=2.99

P M A ¼ W Ai SAi Score MA=3.22

Main Driver Score (Mk)

Customer Calculator for Hotel A: ‘‘First-Time’’ Customer.

B. Brand Equity:

Weight (WA=56.6%)

A. Value Equity:

Main Driver (k)

Table 4.

P C ¼ E n =n Score C=3.18

Hotel’s overall Customer Score

P En ¼ W k M k Score En/4

Customer Score of nth Respondent

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Service Performance Measurement

Table 5.

Summary of Customer Scores for Hotel A and Hotel B.

First-time customers Repeat customers

Table 6.

115

Hotel A

Hotel B

3.18 (N=95) 3.00 (N=105)

3.17 (N=104) 3.13 (N=96)

Summary of Score and Weight Analyses for Hotels A and B. First-Time Customer

Repeat Customer

Main driver

Sub-driver

Main driver

Sub-driver

Hotel A Poorest performing

Brand

Awareness

Retention

Recognition red ﬂag

Hotel B Poorest performing

Brand

Awareness

Retention

Knowledge red ﬂag

most important to ‘‘repeat’’ customers, with weights of 50.2 and 57.3%, respectively. Similar to the earlier analysis for ﬁrst-time customers, a decision would be made to rely on the ﬁndings of either analysis. From the result of the breakdown of the Retention driver, the recognition sub-driver scored the lowest among the other two sub-drivers for Hotel A (68.3%). This indicated ‘‘repeat’’ customers did not feel recognized as ‘‘special.’’ For Hotel B, the knowledge sub-driver scored the lowest (70.8%), signaling ‘‘repeat’’ customers felt their needs and wants were not adequately identiﬁed and met. Referring to the Weight Analysis, the recognition sub-driver was relatively the most important to customers for Hotel A (38.7%) among the other two sub-drivers. This raised a ‘‘red ﬂag’’ for Hotel A, as this important recognition sub-driver had been identiﬁed in the earlier Score Analysis as the poorest performing sub-driver. Hence, more effort could be required to make ‘‘repeat’’ customers feel specially treated through personalized services. For Hotel B, the high importance placed by customers on the knowledge sub-driver (35.7%) indicated that customers who had stayed with the hotel before expected the hotel to retain information about them. A ‘‘red ﬂag’’ for Hotel B was also raised, as it had scored relatively poor for this sub-driver among the other two sub-drivers. Thus, Hotel B might need to increase effort in obtaining more knowledge of customers’ needs and wants, and effectively utilizing them. For ‘‘ﬁrst-time’’ customers, there were no ‘‘red ﬂags’’ raised for both hotels. However, for ‘‘repeat’’ customers, both hotels

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have to focus on the ‘‘red ﬂags’’ (Hotel A: recognition sub-driver, Hotel B: knowledge sub-driver). ‘‘Red ﬂags’’ were raised when the hotel performed poorly in the most important driver to the respondents (Table 6).

CONCLUSION The literature review had established ﬁnancial performance measurements as less predictive of future performance. Despite the beneﬁts of nonﬁnancial measurements, they were not as prevalent as ﬁnancial performance measurements due to reliability problems. A pressing issue arises as the importance of non-ﬁnancial performance measurements and the customer, particularly for hospitality organizations such as hotels, cannot be overlooked. One tool that comprises both ﬁnancial and non-ﬁnancial measurements is the BSC. However, BSC implementation costs had deterred many hotels from adopting the full BSC system. Moreover, managers who had implemented the BSC criticized it for its ‘‘smorgasbord’’ nature. Thus, the Customer Equity model was selected to offering an alternative to the existing Customer Perspective of the BSC. The Customer Calculator was ﬁrst developed comprising three actionable main drivers, i.e. value, brand, and retention, and nine sub-drivers from the Customer Equity model which measures the hotel’s performance from the customer’s perspective with the Customer Score. A questionnaire tool was also developed to complement the implementation of the Customer Calculator. The results of the ﬁeld tests conducted at two large hotels showed that the questionnaire tool reliably measured the three actionable main drivers and nine sub-drivers. The strength of reliability was found to be particularly high for questions measuring the corresponding sub-drivers of the Value and Retention main drivers. To further examine the applicability of the Customer Calculator in the hotel industry, a demonstration of its usefulness through Score and Weight Analyses of the Customer Scores derived from the ﬁeld tests’ data was conducted. The analyses showed how the Customer Scores facilitate decision-making, as hotel management, limited by time and resources, can pinpoint and better understand the more important main driver(s) and sub-driver(s) in need of further action and improvement. The limitation in this study was attributed to resource constraints where the administration of the questionnaire was limited to two hotels within a short time period of a few weeks. As hotels normally have seasonal occupancy with different types of customers during different parts of the

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year, the data collected for this study may not be as accurate a reﬂection of the composition of customers in the hotel as compared to data collected over a longer period. Ideally, the questionnaire tool could have been administered to a greater number of hotels and covered a longer period to better establish its applicability. Over the data collection period, difﬁculty was faced in getting hotel customers in tour groups to complete the questionnaire as they were usually on tight schedules, which resulted in the limitation mentioned in sample analysis. Also, some customers in certain strata with no control over their choice of hotels, such as tour groups, were unable to provide accurate responses to questions regarding hotel room rates, and could only base their judgment on proxies such as food and beverage charges. Several implications for future research could be drawn from the abovementioned limitations. First, research could be conducted across more hotels to investigate the relationship between the Customer Score and the hotel’s ﬁnancial performance indicators. Second, research could be carried out over a longer time period to obtain a more representative sample of hotel customers. Third, with translation into other languages, the administration of the questionnaire would not be limited to non-English speaking guests. It can be studied how to implement the Customer Calculator uniformly across the hotel industry. If a signiﬁcant portion of local hotel management were to adopt this framework, the Customer Score could eventually be used as a monitoring tool by the local hotel association. Perhaps a standardized performance ranking system, currently absent in the industry, could then be instituted to enhance competitiveness among the hotels.

ACKNOWLEDGMENT The author acknowledges with thanks the contributions at the initial stage of this research from our students at the Nanyang Business School, Nanyang Technological University, Singapore: Haidee Heah Wenwei, Ho Shufang, and Melissa Woo Meiyan.

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EXPERIENCE USE HISTORY AND TYPOLOGY OF SUBSTITUTABILITY AMONG HIKERS Chung-Chi Wu, Shih-Yun Hsu and Wei-Ching Wang ABSTRACT The purpose of this investigation was to identify the association between Experience Use History (EUH) and types of substitution choices of hikers with the perspectives of activity involvement and place attachment. On-site surveys were distributed by systematic sampling technique to obtain a representative sample of hikers with 51% response rate. The theoretical expectation was confirmed by these data. Findings indicated that among four EUH classifications, Veterans and Visitors who perceived higher levels of activity involvement and relatively lower levels of place attachment tended to make resource substitutability, while Locals who scored highest on place attachment chose to make temporal substitutability and Beginners who scored lower on both activity involvement and place attachment were apt to make both resource and activity substitutability. Suggestions and managerial implication are further discussed.

INTRODUCTION As the use of popular recreation destinations grows tremendously, recreationists might be adversely affected by some negative changes Advances in Hospitality and Leisure, Volume 4, 121–137 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00006-4

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(e.g., crowding or conﬂict) in recreation settings and change their patterns of use in recreation activities. When the demand for speciﬁc recreation resources outstrips the supply of those resources, substitutability becomes a particular problem (Cordell, 1976). Moreover, types of substitution recreationists choose as coping strategies might inﬂuence their overall satisfaction. By modifying their behavior, recreationists could negotiate the constraints facing them and thus continue to participate in the same activity (Roberson & Regula, 1994; Jackson, Crawford, & Godbey, 1993). Thus, efforts are needed to understand the substitute behavior among different types of recreationists. On the other hand, due to the variety of individual components, recreation behavior might differ among various types of recreationists. To differentiate among recreationists, experience may be an important variable or concept, which may also lead to differences in recreation attitudes, preferences and behavior (Manning, 1999). Many studies have found experience to be related to a variety of variables, including perceived crowding (Vaske, Donnelly, & Heberlein, 1980); conﬂict (Driver & Bassett, 1975); route selection (McFarlane, Boxal, & Watson, 1998); place attachment (Anderson, 1981; Moore & Graefe, 1994; Bricker & Kerstetter, 2000); activity involvement (Havitz & Dimanche, 1997) and willingness to substitute (Vaske et al., 1980). This might suggest that past experience could have much inﬂuence on the behavior of recreationists. The relationship between past experience and substitute behavior has been observed in many studies (Vaske et al., 1980; Manfredo & Anderson, 1987; Hammitt, Backlund, & Bixler, 2004). Findings suggest that more experienced or expert recreationists are likely not to substitute because of their affective emotion to a place or activity. Furthermore, as the frequency and experience increase, habitual use patterns and affective bonds of recreationists may be created with certain resource sites or activities. Some of them may become very committed and loyal to certain sites and products and be reluctant to use alternative sites and products, respectively (Havitz & Dimanche, 1997). Although the relationship between past experience and substitutability has been examined in many studies, few studies appeared to explore the typology of substitutability alternatives (Shelby & Vaske, 1991; Hall & Shelby, 2000). Also, when measuring past experience, previous investigations have focused on the amount of experience. The construct of use experience history has been used in just few studies to differentiate the categories of past experience and to examine its relationship with recreation-related behavior (Schreyer, Lime, & Williams, 1984; Williams, Schreyer, & Knopf, 1990; Hammitt, et al., 2004). However, as Manning (1999) suggested, not only the amount of experience but also the type of

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experience may be important in inﬂuencing recreation-related attitudes, preferences and behavior. Therefore, to incorporate both the amount and the type of experience, the Experience Use History (EUH) could be used to measure past experience based on three experience-related variables. While there is evidence to suggest that past experience is likely to inﬂuence recreationists’ willingness to substitute, the types of experience based on EUH in the choice of substitutability alternatives remains unclear. Thus, the purpose of the paper is to investigate the relationships between EUH classiﬁcations of hikers and substitutability alternatives chosen along hiking trails around Taipei, Taiwan. The constructs of place attachment and activity involvement are used to explain the relationship between past experience and substitutability.

LITERATURE REVIEW EUH refers to the amount and the type of past experience, usually measured with total visits, total years of use and frequency per year of participation with an activity at a speciﬁc site and other sites (Schreyer et al., 1984; Manning, 1999). Three variables, including (1) the number of times the respondent ﬂoated (or other activity) the study river, (2) number of rivers the respondent had ﬂoated and (3) total number of river trips the respondent had made, were used to form an index measure of EUH (Schreyer et al., 1984). Based on combinations of the three use experience variables, respondents could be categorized into several classiﬁcations. Because both the levels of experience and the participating frequency at the study site as well as alternative sites were estimated, the classiﬁcations based on EUH helps a lot to segment the market and deﬁne target customers by categorizing recreationists. Previous investigations have observed the signiﬁcant differences among classiﬁcations of EUH. Based on the combinations of three use experience variables, Schreyer et al. (1984) identiﬁed six types of river users as novices, beginners, locals, collectors, visitors and veterans. Signiﬁcant differences were found among these six experience levels of recreationists in terms of participation motivations, perceived conﬂicts and attitudes toward management practices. A follow-up study (Williams et al., 1990) applying the EHU construct suggested that the motivations of recreationists grow increasingly complex with increasing experience. However, based on the variables of EHU, only three levels of experience (novices, visitors and veterans) were identiﬁed. Petrick, Backman, Bixler, and Norman (2001) used the concept of

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EUH as segmentation criteria to classiﬁed golf users and found different behavior among them based on the classiﬁcation. A recent study by Hammitt et al. (2004) also corroborated differences among EUH categories, suggesting that locals and veterans were signiﬁcantly different from the beginners and visitors on place bonding and part of substitutability. In this study, only four classiﬁcations of recreationists were identiﬁed based on the combinations of low and high levels of total years and times last year ﬁshing the study river and other local rivers. In summary, EUH has been demonstrated in past studies to be an important reference when categorizing customers, especially recreationists. Past experience could likely be segmented into different numbers of category based on the EUH variables. These variables primarily aimed at the total years and times participating in the activity at the study site and other sites (Fig. 1).

A Typology of Substitutability Several researchers have investigated changes associated with substitutability. However, as noted by Brunson and Shelby (1993), most of the studies had limited the substitute strategies to resource substitutes and resource and activity substitutes, rather than the full array of substitute strategies. For the full array of substitutability, a typology developed by researchers studying substitution behaviors was adopted in this study

EUH on the study site

EUH on Substitute sites

Fig. 1.

Beginners

Visitors

Low

Locals

Veterans

High

Classiﬁcation of Hikers Based on Experience Use History (EUH) on Study Site and Substitute Site.

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(Shelby & Vaske, 1991). According to the typology, substitutability may have potentially spatial, temporal and activity dimensions. The multiple dimensions of substitutability are illustrated in Fig. 2. The upper left cell in the matrix represents the situations when recreationists may decide to participate in the same activity at the same location, but substitute a difference time period. The upper right cell represents situations when recreationists may choose the same activity, but substitute a different location. The lower left cell represents situations in which recreationists may choose to participate in a different activity at the original intended location, and the lower right cell represents situation in which recreationists may choose to substitute both the original activity and the location. Based on the activity and resource dimensions, the typology of substitutability could be classiﬁed into temporal substitution, resource substitution, activity substitution and both resource and activity substitution. Relationship of Past Experience and Substitutability Previous studies of substitutability decision making have identiﬁed that level of past experience, frequency of participation, skill level and monetary investment were important to individuals’ willingness to substitute (Vaske et al., 1980; Snow, 1980; Vaske, Donnelly, & Shelby, 1990, Manfredo & Anderson, 1987; Hammitt et al., 2004). Based on recreation specialization Resource Same

Temporal substitute

Resource substitute

Activity

Same

Different

Different

Activity substitute

Resource and activity substitute

Fig. 2.

A Typology of Substitution Alternatives. Note: Shelby and Vaske (1991). Reprinted with permission.

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theory (Bryan, 1977; Ditton, Loomis, & Choi, 1992), it can be expected that those with well-developed skills, large investments and more experience are less likely to make a substitutability decision. Particular patterns of experience preferences are likely to transcend into behavioral choices (Iso-Ahola, 1980) and have inﬂuence on their willingness to substitute other activities for the original one. In a study concerning substitutability in recreational ﬁshing, Ditton and Sutton (2004) have identiﬁed the activity-speciﬁc motivations for ﬁshing which might lead the recreationists to be less willing to substitute another activity. The importance of ﬁshing was negatively related to willingness to substitute. Another study concerning the inﬂuence of activity importance and similarity on perception of recreation substitutes for ﬁshing activity has shown that 95% of the participants were willing to ﬁsh in another but similar setting when the original place was not available (Manfredo & Anderson, 1987). It is consistent with the ﬁndings of Ditton and Sutton (2004) that compared the group of ﬁshing ‘‘regulars’’ or ‘‘insiders’’ who have a strong emotional attachment to a speciﬁc activity, ‘‘strangers’’ and ‘‘tourists’’ who could identify another outdoor activity or another place more easily. Therefore, for experienced or specialized participants, the commitment to a speciﬁc activity makes them less likely to identify another outdoor activity that would provide them with the same satisfaction or enjoyment. However, there were also studies that identiﬁed the positive relationship between level of experience and willingness to substitute. A study (Vaske et al., 1980) had found that more experienced recreationists were more sensitive to any changes on the setting or activity; thus, they were likely affected by any change around recreational settings and tended to have substitutability. Schreyer and Lime’s (1984) ﬁndings suggested that individuals with more experience are more likely to engage in more problem-focused coping strategies such as displacement and avoidance. On the other hand, the knowledge base of experienced or expert recreationists would offer them more information about places for substitutability. Thus, if substitutability is needed, it could be expected that more experienced participants may look for another place rather than identify a new activity. Hall and Shelby (2000) found a higher proportion of displacers among highly experienced visitors as well as non-displacers among relative newcomers. Thus, it could be concluded that recreationists with more experience are more uneasy with changes and aware of a greater range of alternative sites. They are more likely to have temporal or resource displacement. However, the relationship was not signiﬁcant. Anderson (1981) has suggested that the relationship between past experience and substitutability of recreationists was not signiﬁcant because of their attachment to a speciﬁc place. Therefore, the actual inﬂuence

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of past experience to substitutability remains unclear although the relationship between the two was conﬁrmed.

Activity Involvement and Place Attachment as Explanations to Substitute Behavior Activity involvement and place attachment are important constructs in leisure context. Both constructs provide insight into the underlying motivations for recreationists’ engagement in speciﬁc leisure pursuits and visitation to speciﬁc recreation settings (Kyle, Graefe, Manning, & Bacon, 2004). Adapted from the consumer behavior literature, involvement was composed of importance, pleasure, perceived probability and consequence of risk (Laurent & Kapferer, 1985). Building on Laurent and Kapferer’s scale, McIntyre and Pigram (1992) conceptualized activity involvement as consisting of attraction, centrality to life and self-expression. Attraction refers to the importance and pleasure associated with the activity. Centrality of lifestyle refers to the position the activity occupies within an individual’s overall life. Finally, self-expression is the identity afﬁrmation derived through activity engagement. An involvement proﬁle including the empirical indicators of the three dimensions together can be seen to relate to an individual’s engagement in a speciﬁc leisure activity, or type of activity, and thus indicate the overall relevance or meaning of that activity in the context of the individual’s life (Wiley, Shaw, & Havitz, 2000). Previous investigations have shown that past experience and the frequency of participation is positively related to activity involvement (Havitz & Dimanche, 1997; Kuentzal & McDonald, 1992; Schreyer et al., 1984; McIntyre & Pigram, 1992). More experienced recreationists tend to perceive higher level of activity involvement. The particular activity is more important, interesting and meaningful to them than less experienced recreationists. On the other hand, more experienced recreationists are thought to perceive greater knowledge of alternatives, but at the same time are more prone to be displaced (Havitz & Dimanche, 1997, 1999; Watson, Roggenbuck, & Williams, 1991; Hammitt et al., 2004). Therefore, when a substitution is needed to be made, recreationists with higher activity involvement level are expected to make resource substitution rather than participating in other activities. In a study concerning ﬂy-anglers, Manfredo and Anderson (1987) found that 95% of the anglers would ﬂy-ﬁsh someplace else rather than ﬁnd substitute activities. Ditton and Sutton (2004) suggested that recreationists who place high importance on activity-speciﬁc motivations for ﬁshing are less willing to substitute another activity.

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For place attachment, the construct in the leisure context is relatively new compared to the investigations in the environmental psychology and geography literatures. It is believed that through the development of an attachment to a place within the geographic landscape, people develop a bond that may provide meaning to them with the perspectives of human geographers and environmental psychologists (Tuan, 1980; Kyle et al., 2004, adapted from Altman & Low, 1992). It has been conceptualized in the leisure literature that the place attachment consists of the two major dimensions of place identity and place dependence (Williams, Patterson, Roggenbuck, & Watson, 1992; Moore & Graefe, 1994; Williams & Vaske, 2003). Place identity refers to ‘‘the symbolic importance of a place as a repository for emotions and relationships that give meaning and purpose of life’’ (Williams & Vaske, 2003). Williams et al. (1992) suggested that place dependence is a functional attachment, reﬂecting the importance of a resource in providing amenities necessary for desired activities. Research focusing on place attachment and substitution has suggested that the greater the attachment, the less likely a recreationist is willing to make a resource substitution. In a study of backcountry users, the results showed that willingness to substitute was associated with lower place attachment scores (Williams et al., 1992). Kaltenborn (1998) found that residents who had developed sense of place were less likely to be displaced from their recreation patterns and places than those with weaker sense of place. Mesch and Manor (1998) also suggested that a strong bond to a particular place might be associated with low use of resource substitution. Thus, it is expected that once the habitual use patterns and affective bonds with certain resource places are formed, recreationists are unwilling to make resources substitution. Based on the EUH classiﬁcation and previous studies, the following relationships were hypothesized among the four EUH categories of hikers, types of substitutability, activity involvement and place attachment (Table 1). 1. Locals, having more experience with the study site but less experience with others, will have the highest level of place attachment with the study site and high medium level of activity involvement. Thus, they tend to make temporal substitutability instead of activity substitutability and other kinds of substitution alternatives. 2. Veterans, who have considerable experience in both the study site and other sites, are mostly concerned with the activity. Therefore, they will substitute another site for the same activity.

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Table 1. Hypothesized Relationships among Experience Use History, Activity Involvement, Place Attachment and Type of Substitutability. Experience Use History Veterans Locals Visitors Beginners

Activity Involvement

Place Attachment

Type of Substitutability

High Medium Medium Low

High medium High Low Low medium

Resource substitute Temporal substitute Resource substitute Resource and activity substitute

3. Visitors, having more experience with other sites than the study site, will have high medium level of activity involvement and lowest level of place attachment. Therefore, they will be apt to make place substitutability. 4. Beginners, with rare experience at both the study site and others but with curiosity about the study site, will have lowest level of activity involvement and low medium level of place attachment. They will tend to make both activity and resource substitutability.

METHODS Data Collection Data were collected from National Kuanyinshan scenes hiking sites in Taiwan between November 2005 and April 2006. On-site surveys were distributed on a random sample of weekdays and weekends. Sampling occurred at the entrance site and summit of the trails. A systematic sampling technique (Babbie, 1995) was employed to obtain a representative sample of hikers. Every ﬁfth hiker over the age of 18 was approached. Of the 500 surveys distributed on-site, 255 usable questionnaires were returned back (response rate=51%). Measurement Experience Use History EUH was measured by asking hikers total times and total years they hiked at the study site as well as other sites to assess frequency last year and total years of hiking. Four variables were used to form the EUH classiﬁcation

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based on former research (Schreyer et al., 1984; Manning, 1999; Hammitt et al., 2004). These four variables were the total years and times last year hiking at the study sites and other sites. Computing EUH In order to account for various combinations of EUH at the study sites and others, an index ratio of EUH suggested by Hammitt et al. (2004) was computed. An account for EUH was computed for each hiker of the study sites by summing their years of hiking at the study sites with the frequency last year hiking at the study sites and then divided into Low and High groups on the median value of the sum. Medians were used as the bases of segmentation rather than means because of some outlier values for some extremely experienced hikers. The same procedure was followed for the years and frequency of hiking on other sites. Four combinations of Low and High levels of EUH were identiﬁed for hikers including: Veterans (n ¼ 92): Hikers with high EUH at both the study site and other sites. Locals (n ¼ 51): Hikers with high EUH at the study site but low EUH at other sites. Visitors (n ¼ 39): Hikers with low EUH at the study site but high EUH at other sites. Beginners (n ¼ 73): Hikers with low EUH at both the study site and other sites. Typology of Substitutability Substitutability of hikers was measured by asking hikers about their substitute strategy if they could not hike at the study site. Four choices based on the typology of Substitutability suggested by Shelby and Vaske (1991) were listed. Hikers were asked, ‘‘if you could not hike at Kuaninshan, what would you do’’? They could choose to go hiking at another time or other places, do some other activity at the same site or go to other places and do other activities. Analysis The hypotheses were addressed with w2 test of association and crosstabs to compare the percentage of the four EUH types to the substitution alternatives. The nominal data were submitted to w2 analysis with EUH as the independent variable. This provides a test that indicates whether the distribution of responses differs signiﬁcantly for the four groups.

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Because the constructs of activity involvement and place attachment were used to explain the reason why different experience levels of hikers would make various kinds of recreation substitution, analysis of variance (ANOVA) was used to test for mean differences among the four classiﬁcations of EUH in activity involvement and place attachment.

RESULTS Experience Use History The mean number of total years hiking (both the study sites and others) was 12.86. On average, the respondents had hiked at the study sites for 5.34 years with the highest 45 years and lowest less than 1 year. Respondents made an average of 10.18 hiking trips at the study sites last year. For hiking at other sites, hikers had 7.52 years of participation with a number of 12.57 times last year. Signiﬁcant differences were found between four classiﬁcations of hikers on their hiking experience (Table 2).

The Association of EUH and Substitutability There were evidences that levels of past experience will affect recreationists’ choice of substitution alternatives. In this study, EUH was used to identify different levels of past experience of hikers. Among four classiﬁcations of EUH, it is hypothesized that ‘‘Locals’’ who have more experience with the study site but less experience with others will tend to stay at the same setting because of their attachment to a speciﬁc place. Their experience in hiking leads them to make temporal substitutability instead of activity substitutability. ‘‘Veterans’’ who have considerable experience in both the study site Table 2.

Mean Values of the Experience Use History (EUH) Variables Comprising the Four EUH Classiﬁcations of Hikers.

EUH Variables Years hiking at the study sites Times last year at the study sites Years hiking at other sites Times last year at other sites po0.05.

Veterans

Locals

Visitors

Beginners

F

10.37 15.47 12.99 20.52

3.06 18.75 3.77 2.67

3.26 1.77 9.41 22.41

1.69 2.20 2.25 4.19

35.37 48.06 42.50 58.46

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and other sites are more concerned with the activity. Therefore, they will substitute another site but remain with the same activity. ‘‘Beginners’’, with rare experience at both the study site and others, will tend to make both resource and activity substitutability, while ‘‘Visitors’’, having more experience with other sites rather than the study site, will be apt to make place substitutability. w2 analyses were performed with EHU as the independent variable. Signiﬁcant differences were found among the EUH types in their behavior intention of substitutability. In support of these hypotheses, w2 test of association revealed that veterans and visitors tend to make resource substitute (69.6%) while locals will make temporal substitute (47.1%) [w2(9) ¼ 74.96, po0.05, Table 3]. The results also supported the behavior of beginners who were hypothesized to make both resource and activity substitute because of their low scores in place attachment as well as activity involvement and lack of information base to make resource substitute. Thus, they will go to other places for different kinds of activities when they could not hike at the original site chosen.

Differences Among Four EUH Classifications in Activity Involvement/Place Attachment Measures of activity involvement and place attachment were tested and both were found to vary signiﬁcantly among the four EUH classes of hikers. The pattern of means hypothesized was exactly matched for the variables of overall activity involvement and place attachment (Tables 4 and 5). Activity involvement was scored highest by Veterans (M ¼ 54.13), then high medium Table 3.

w2 Test of Association for Differences in Recreation Substitutability by Experience Use History.

Experience Use History

Typology of Recreation Substitutability Activity substitute

Veterans Locals Visitors Beginners

4 6 4 6

(4.3%) (11.8%) (10.3%) (8.2%)

Resource substitute 64 17 22 26

w2(9, N ¼ 255) ¼ 74.96, po0.000.

(69.6%) (33.3%) (56.4%) (35.6%)

Activity and resource substitute 9 4 8 35

(9.8%) (7.8%) (20.5%) (47.9%)

Temporal substitute 15 24 5 6

(16.3%) (47.1%) (12.8%) (8.2%)

Total

92 51 39 73

(100%) (100%) (100%) (100%)

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Table 4.

Veterans Locals Visitors Beginners

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Mean Differences between Experience Use History Classes of Hikers and Activity Involvement. N

Mean

F-Value

Post Comparison

92 51 39 73

54.13 51.61 53.56 45.92

12.44

1, 2, 3W4

po0.05.

Table 5.

Veterans Locals Visitors Beginners

Mean Differences between Experience Use History Classes of Hikers and Place Attachment. N

Mean

F-Value

Post Comparison

92 51 39 73

26.56 26.63 23.13 23.38

12.41

1, 2W3, 4

po0.05.

by Locals (M ¼ 51.61) and Visitors (M ¼ 53.56) and lowest by Beginners (M ¼ 45.92) as hypothesized. For place attachment, Locals (M ¼ 26.63) had the highest level of place attachment, then Veterans (M ¼ 26.56), while Visitors (M ¼ 23.13) and Beginners (M ¼ 23.38) had the lowest level.

DISCUSSION The purpose of this investigation was to identify the association between EUH and types of substitution choices of hikers with the perspectives of activity involvement and place attachment. The theoretical expectation was conﬁrmed by these data. These ﬁndings indicated that among four EUH classiﬁcations, Veterans and Visitors who perceived higher levels of activity involvement and relatively lower levels of place attachment tended to make resource substitutability, while Locals who scored highest on place attachment chose to make temporal substitutability and Beginners who scored lower on both activity involvement and place attachment were apt to make both resource and activity substitutability. Viewing our ﬁndings in light of activity involvement, the association between Veteran’s and Visitor’s

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involvement with activity and their choice of substitution alternatives implied that higher levels of activity involvement led hikers to substitute places rather than activity. In support of previous research, experienced recreationists, especially who are inclined to a particular activity, are less willing to substitute another activity (Manfredo & Anderson, 1987; Ditton & Sutton, 2004). On the other hand, the knowledge base of recreationists with more experience is large enough to offer them more places for resource substitution (Havitz & Dimanche, 1997, 1999; Watson et al., 1991; Hammitt et al., 2004). Thus, if substitutability is needed, it could be expected that Veterans who have considerable experience in both the study site and other sites may look for another place rather than identify a new activity. Visitors, though having comparably less experience in the study site, also score high on activity involvement and tend to make resource substitution due to their plentiful experience in other sites. Findings were consistent with the theoretical expectations. From place attachment perspective, these ﬁndings also indicate that stronger bonds with a certain place were associated with low use of resource substitution and vice versa. While Locals who score high on place attachment were more inclined to make temporal substitution, Visitors and Beginners who score low on place attachment were inclined to evaluate resource substitution and both resource and activity substitution more favorably. In support of past researches, the greater the attachment, the less likely a recreationist is willing to make a resource substitution (Williams et al., 1992; Kaltenborn, 1998; Mesch & Manor, 1998). Although both temporal substitution and activity substitution refers to the same places, it is interesting that Locals tend to make temporal substitution instead of activity substitution. This might be explained with the construct of activity involvement that Locals who score high on place attachment also score high medium on activity involvement because of their preferences to hiking. Thus, they are likely to go for hiking at another time at the same site rather than just stay at the same place but substitute the activity. A recent work by Kyle et al. (2004) also supports the notion that Locals whose knowledge of setting alternatives is somewhat limited are more likely to be dependent on the resource for their desired leisure experiences. It is interesting that Locals tend to make temporal substitution (47.1%); however, quite a few number of Locals (33.3%) stated that they will make resource substitution when they could not hike at the original site. This might be explained by their high scores on activity involvement. Although Locals had developed their dependence and affective bonding to the study site, most of them are highly involved in hiking. Thus, some of the Local

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hikers might also try to seek another site as their hiking resources. In addition, we found that some Veterans (16.3%) and Visitors (12.8%) tend to make temporal substitution rather than resource substitution. As previous researches have found that activity involvement is an antecedent of place attachment (McFarlane et al., 1998; Moore & Graefe, 1994; Schreyer & Lime, 1984), the more importance recreationists place on activity, the more attachment they might perceive on the setting. Therefore, some of the Veterans and Visitors will choose to make temporal substitution although they have broad knowledge base on the substitute alternatives. Another issue concerning past experience of recreationists is the classiﬁcation of EUH. Instead of just accounting for the amount of experience, it incorporates both the amount and the type of experience. Although past experience indices have been criticized in some ways, an index measure of past experience still remains a logical approach to capturing the construct validity of this complex concept (Hammitt et al., 2004). Using median, but not mean or exact number, to determine experience levels was empirically meaningful when measuring recreational activities that include both various experience levels of participants and considerable numbers of resource alternatives such as hiking. It is worth noticing that some recreationists who hike a few years in the study site with high frequency are misleading to be classiﬁed as beginners rather than as locals when comparing their numbers of years and times last year at the study site to elder hikers with extremely high numbers of years and times. However, compared with their own years and times with other sites, the amount and frequency they hike in the study site are much higher than for other places. Thus, those ‘‘Beginners’’ but not ‘‘locals’’ might also be bonded to the study site with high level of place attachment although their years and times at the study site could not rival to veterans who have considerable experience in both the study site and other sites. Keeping these cases in mind, we suggested that a ratio for EUH was computed for each hiker of the study site by summing their years of hiking with the frequency last year hiking at the study site and dividing by the sum of their years of hiking and frequency last year at other sites.

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McIntyre, N., & Pigram, J. J. (1992). Recreation specialization reexamined: The case of vehiclebased campers. Leisure Sciences, 14, 3–15. Mesch, G. S., & Manor, G. (1998). Social ties, environmental perception and local attachment. Environmental and Behavior, 30, 504–519. Moore, R. L., & Graefe, A. R. (1994). Attachments to recreation settings: The case of rail-trail users. Leisure Sciences, 16, 17–31. Petrick, J. F., Backman, S. J., Bixler, R., & Norman, W. C. (2001). Journal of Leisure Research, 33(1), 56–70. Roberson, R. A., & Regula, J. A. (1994). Recreational displacement and overall satisfaction: A study of central Iowa’s licensed boaters. Journal of Leisure Research, 26(2), 174–181. Schreyer, R., & Lime, D. (1984). A novice isn’t a novice: The inﬂuence of experience use history on subjective perceptions of recreation participation. Leisure Sciences, 6, 131–149. Schreyer, R., Lime, D., & Williams, D. (1984). Characterizing the inﬂuence of past experience on recreation behavior. Journal of Leisure Research, 16, 34–50. Shelby, B., & Vaske, J. (1991). Resource and activity substitutes for recreational salmon ﬁshing in New Zealand. Leisure Sciences, 13, 21–32. Snow, R. (1980). A structural analysis of recreation activity substitution. Unpublished doctoral dissertation. Texas A&M University, College Station. Tuan, Y. F. (1980). Rootedness versus sense of place. Landscape, 24, 3–8. Vaske, J. J., Donnelly, M. P., & Heberlein, T. A. (1980). Perceptions of crowding and resource quality by early and more recent visitors. Leisure Sciences, 3(4), 367–381. Vaske, J. J., Donnelly, M. P., & Shelby, B. (1990). Comparing two approaches for identifying recreation activity substitutes. Leisure Sciences, 12, 289–302. Watson, A. F., Roggenbuck, J. W., & Williams, D. R. (1991). The inﬂuence of past experience on wilderness choice. Journal of Leisure Research, 23, 2–36. Wiley, C. G. E., Shaw, S. M., & Havitz, M. F. (2000). Men’s and women’s involvement in sports: An examination of the gendered aspects of leisure involvement. Leisure Sciences, 22, 19–31. Williams, D. R., Patterson, M. E., Roggenbuck, J. W., & Watson, A. F. (1992). Beyond the commodity metaphor: Examine the emotional and symbolic attachment to place. Leisure Science, 14, 29–46. Williams, D. R., Schreyer, R., & Knopf, R. (1990). The effect of experience use history on the multidimensional structure of motivations to participate in leisure activities. Journal of Leisure Research, 22, 35–54. Williams, D. R., & Vaske, J. J. (2003). The measurement of place attachment: Validity and generalization of psychometric approach. Forest Science, 49, 830–840.

AT-DESTINATION REFERRALS, TIE STRENGTH, AND SATISFACTION Paul D. Rompf and Denver E. Severt ABSTRACT This paper combined an at-destination decision-making model with the theory of tie strength to find out information related to the referrals that travelers received and used at a major tourist destination in the southeastern United States. At-destination decisions included lodging, eating and dining, entertainment, recreation, and travel. The data indicated eating and dining, recreation, and entertainment decisions are made in large numbers at the destination. The first research question involved referral source and frequency for at-destination decisions, revealing many third-party decision-makers. Friends and family members were the most requested and local residents the least requested referral sources. The second research question inquired as to whether satisfaction scores from the referred experience differed across referral source. The researchers suggested that referrals have different perceived levels of trust, expertise, and ties, and potentially will render different sales levels. Due to this, the satisfaction outcome was measured by referral source. Results showed that referred satisfaction scores were highest from local resident referrals followed by friends and relatives – one a strong tie and one a strong–weak tie. Finally, more neutral satisfaction scores were reported from other information sources. The article closes by offering possible explanations for these differences and by providing suggestions for additional at-destination decision-making and outcome research. Advances in Hospitality and Leisure, Volume 4, 139–160 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00007-6

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INTRODUCTION Imagine that you have just traveled a considerable distance and are now at your intended destination. For any number of reasons, decisions on speciﬁc settings for the delivery of travel-related services (e.g., dining, recreation, and entertainment experiences) have been deferred to this moment and locality. Changes in your advanced bookings are also under reconsideration. Although an experienced traveler, you are generally unfamiliar with the destination and the local service venues that possibly meet your service needs. The opening scenario is not atypical for today’s travelers, but is rather consistent with a portion of travel decision-timing for services to be delivered at a destination. Irrespective of where the purchase decision is made, purchase behavior models have generally portrayed a rational, multiattribute evaluative process. The purchase decision has been posited to begin with a systematic informational search to obtain and then weigh the attributes associated with the products, brands, and ﬁrms desired. The comparison process eventually translates into a behavioral intention to purchase the product, which occurs before the actual purchase (Fishbein & Ajzen, 1975). Engel, Blackwell, and Miniard (1990) characterized an informational search as a motivated activation of information stored in memory and/or the acquisition of information from the external environment. If one’s internal memory provides sufﬁcient information to make a venue determination, then an external search may be unnecessary. In contrast, if you do not have appropriate memory schema relevant to the task or, for this occasion, a more novel experience is desired, one timeconserving and risk-minimizing strategy would be to rely on other people for referrals to speciﬁc service venues, especially when the decision is made while at the destination. The traveler may initially know the ‘others’ providing referrals well, moderately, or not at all. A long-time friend or a relative compared to a complete stranger are bi-polar opposites on a time-based ‘relationship’ dimension. Referrals received, acted upon, and subsequently reported levels of satisfaction from ‘locals’ at a destination encapsulate the focus of this research paper. The relationship or tie between a traveler and an unknown ‘local’ is different. A friend or relative is generally perceived as trusted to be a ‘strong tie.’ The complete stranger is someone the traveler has a weak relationship with, and is a ‘weak tie.’ However, cases in which a visitor acts on referrals received from a weak tie implies an element of ‘trust.’ A weak tie that is

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trusted is referred to in the literature as a ‘strong weak tie.’ The origin of strong–weak ties has been investigated in the tie strength literature (Granovetter, 1973, 1982, 1983) in job settings including social networking, but it has not been examined in the hospitality and leisure-travel context. The following research questions guided the investigation on atdestination resources utilized by visitors to the destination: First, what referral sources of information are taken and used by visitors seeking information on travel-related services while they were at the destination? Second, are there differences in the satisfaction levels associated with referrals from the different information sources utilized by the visitors?

LITERATURE REVIEW Consumer (and Travel) Decision Models Extensive research on consumer purchase behavior has evolved well beyond the original Fishbein model of purchase behavior (Ajzen & Fishbein, 1980; Bettman, Johnson, & Payne, 1990; Engel et al., 1990; Funkhouser & Parker, 1999; Olshavsky & Granbois, 1979; Petty & Cacioppo, 1986; Rompf, DiPietro, & Ricci, 2005; Sirakaya & Woodside, 2005), resulting in the identiﬁcation of complex and interrelated search and decision processes. As a consequence, research on consumer-decision processes has grown exponentially for the last three decades as search options have increased with technological advances (Sirakaya & Woodside, 2005). The investigation of the traveler’s use of information sources before departure has been extensive, resulting in information search and decision strategies becoming a central research stream in tourism studies (Fodness & Murray, 1997; Gursoy & Chen, 2000). Many former theories and models assumed a static and linear process with little variation (Hwang & Fesenmaier, 2004), leaving room for studies to consider travel dynamics and idiosyncratic differences that may exist between travel segments (DiPietro, Severt, Rompf, & Ricci, 2005). However, at-destination information search studies are limited. Several factors have been found to have an inﬂuence on information sources used and attributes processed by consumers regarding a purchase decision. These included consumers’ involvement level (Petty & Cacioppo, 1986), peer and informational social inﬂuences (Cohen & Golden, 1972), and situational factors (Rosen & Olshavsky, 1987). Engel et al. (1990) developed a comprehensive model of consumer purchase behavior from

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demand stimulus to postpurchase behaviors. In the model, need recognition, search activity, and alternative evaluations were moderated by personal and environmental factors. In addition, consumer contexts to include the inﬂuence of promotional message, habitual buying practices, and brand loyalty were integrated into their model.

At-Destination Travel Decisions and Third-Party Referrals Rompf et al. (2005) noted an inadequacy of the Engel et al.’s (2005) model relative to at-destination decision-making, stating that the model was not adequately ‘yfashioned to the landscape of at-destination purchase decisions for travel-related services’ (Rompf et al., 2005, p. 12), and proposed a new model based on adaptations from Engel et al. (1990) and a further model by Rosen and Olshavsky (1987) (see Fig. 1). The new model, portraying at-destination informational searches and moderated by a set of situational factors, was more speciﬁc and relevant to at-destination travel decisions. These factors included time constraints, lack of interest, perceived high risk, and limited expertise (Rosen & Olshavsky, 1987). A further addition of third-party referrals as part of an information search and decision strategy, including a potential decision-transfer strategy, was perceived to save the traveler decision-making time, add interest or novelty to the travel decision, and lower the perceived risk of the travel decision. Referrals are considered a critical component in the travelers’ information acquisition process (Peter & Olson, 1999). For a variety of reasons, consumers frequently transfer the travel decision to someone they perceive as more knowledgeable or having a higher level of expertise relevant to the decision at hand. In particular, many travelers have reported researching venue information as frustrating, exhausting, and stressful (Schwartz, 2004). Funkhouser and Parker (1999) concluded that a purchase decision has the potential to be vastly complex, possibly creating frustration and confusion for the traveler. In turn, this may lead to a state of decision inaction. A traveler seeking and acting upon a third-party referral becomes a rational alternative to a state of inaction. The use of a local expert may also provide a sense of conﬁdence in that someone from the local area is providing a recommendation founded on his/her familiarity with the enterprise, and it may even be a place that he/she actually frequents adding authenticity to the referral. A further visitor motivation for using local residents has been labeled the ‘novelty seeker’ or ‘variety seeking’ traveler (Vogt & Fesenmaier, 1998). Vogt and Fesenmaier (1998) associated variety

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Environmental Influences

Need Recognition

Culture Social Class/ Peer Group Family Situation

Informational Search

Individual Differences

Alternative Evaluation

Consumer Resources Motivation Level of Involvement Knowledge or Expertise Attitudes Personality Lifestyle Demographics

3rd Party

Referral

Purchase Decision

Expertise Trustworthiness

At-Destination Situational Factors Time Constraints Lack of Interest Perceived High Risk Limited Expertise

Personal Outcome

Gratuitous Referral

Fig. 1. At-Destination Visitor Purchase Behavior Model. Source: Partially adapted from models by Engel et al. (1990); Rosen and Olshavsky (1987); as printed in Rompf et al. (2005).

seeking with the desire for a mixture of stimuli in the environment, and it is at least partially attributed to situational factors. In 1987, the National Restaurant Association (NRA) studied the sources of information utilized by diners to select a restaurant facility when they were away from their local community (Gallup Organization, 1987). The primary focus of the investigation was advertising formats such as electronic, print, and display media. Also reported was the pivotal role that ‘local townspeople’ played in the selection of a venue for the desired dining experience. Almost 80% of the survey respondents indicated they were ‘very inﬂuenced’ (45%) or ‘somewhat inﬂuenced’ (34%) by a local resident. A visitor typically will pre-select the ‘local expert’ and initiate a request for a speciﬁc venue referral that is generally bounded by a relatively

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immediate timeline. As a result, Rompf (2001) speculated that a recommendation provided in this context had a high probability of being acted upon. Rompf further drew a critical distinction between at-destination referral activities in general and those he deemed to be genuinely gratuitous and personal in nature. He posited that a traveler typically seeks and therefore hopes to obtain a personal recommendation that is not tainted by monetary or other forms of remuneration, and labeled this genuine type of referral a ‘gratuitous referral.’ As a concept, gratuitous referrals closely align with the word-of-mouth (WOM) literature in that the provider of the WOM referral is said to not proﬁt by money or other incentives when the receiver acts to patronize the beneﬁting entity being referred (Schiffman & Kanuk, 1997). WOM research has been associated with positive (negative) WOM behaviors along with an intention to return (exit), and have not greatly focused on the WOM source (Anderson, 1998). Additionally, WOM research has emphasized a need for follow-up investigations to determine if and how often a referral may be followed (Brown & Reingen, 1987), which will be attempted here.

Referral Sources and Tie Strength Theory The relationship between a traveler and a referrer at a destination ranges from strong to weak. ‘Tie strength’ or the strength of a tie, founded on the basis/nature of a relationship, has been studied from many contexts including shared information within organizations and work teams, but to this point has not been explored from the point of view of visitors’ receiving travel-venue referrals while being at the destination. Tie strength has also been studied in conjunction with WOM behavior, and, in this regard, it was postulated that a stronger tie (and perceptions of a strong tie) or relationship would result in a greater willingness to receive and act upon a referral. In the travel literature, the existence of tie strength is manifested both anecdotally and empirically in the rather dominant use of family and friends in both information gathering and decision-making. Tie strength has a foundation in social networks (Granovetter, 1973), and some examples of these have been recognized as having a short time frame in a work context (e.g., a special project work team), a relatively longer time frame (normal work relationships), or derived from a social context, (e.g., your long-term neighbors). Granovetter proposed tie strength to be a function of frequency of contact between individuals. Reciprocity or payback intent may also enter the equation, with high reciprocity usually

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indicating stronger ties and a lasting friendship. Weak ties were considered to result from infrequent contacts and randomness. Strong ties have been proposed to facilitate the ﬂow of rich, detailed, and redundant information between individuals and groups. In contrast, weak ties have been posited to facilitate a broader exchange with potentially new information by incorporating a wider set of contacts and knowledge resources (Granovetter, 1973, 1982; Hansen, 1999; Haythornthwaite, 2000). Highlighting this point, Granovetter (1983) stated, ‘yindividuals with few weak ties will be deprived of information from distant parts of the social system and will be conﬁned to the provincial news and views of their close friends’ (p. 202). Finally, the notion of strong–weak ties evolved and was investigated whereby, though the tie was weak, somehow a chemistry of trust and helpfulness created a proxy for a strong tie. A further outcome, supported by some empirical evidence, established that the strong–weak ties could result in more novel and useful information for the intended party. Intuitively, a weak tie with a low level of trust is not likely to develop into a viable information exchange (Hansen, 1999).

Tie Strength, Trustworthiness, and a Third-Party Decision Strategy When ‘knowledge’ is explicit, the trust in the competence of the knowledge source is not as critical since the knowledge stands alone and can be understood apart from competence of the source. For example, explicit knowledge at a destination may be a simple answer to the question, ‘Where is the closest drug store?’ In contrast, ‘tacit’ knowledge entails insights, intuitions, and beliefs that are tightly intertwined with the experience and competence of the source (Bateson, 1978; Polanyi, 1966), and is subjective and may further be difﬁcult to articulate (Brown & Duguid, 1991; Nonaka, 1994; Tyre & von Hippel, 1997). Decisions requiring tacit knowledge include answers to questions such as, ‘Where is the best ﬁne dining seafood restaurant?’ A visitor receiving and following tacit knowledge needs to have higher trust in the competence of the information source before asking the person. Empirical studies have found that weak relationships (weak ties) that are strongly trusted provide the most novel and useful information in an information exchange (Levin & Cross, 2004). They further found additive effects of perceived trustworthiness in weak ties stating, ‘ycontrolling for the effects of perceived trustworthiness allowed us to uncover the hidden

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beneﬁts of weak ties in knowledge exchanges, beneﬁts that had been suppressed when perceived trustworthiness was not considered as a concept separate from tie strength’ (Levin & Cross, 2004, p. 1486). Travelers in general, and particularly the adventuresome, risk averse, inexperienced, and disinclined decision makers, may choose to confer with a perceived ‘expert’ at a destination to obtain information to meet their travelservice needs. Recent research, supported by anecdotal evidence, indicates the perceived local expert, who in many instances is a stranger to the traveler, could just as likely be a member of the local community as the traveler selected opportunistically (Gallup Organization, 1987; Rompf & Ricci, 2003). Documented sources of information from ‘locals’ at a destination include, but are not limited to, friends and relatives who live at the destination, local residents with whom a visitor may have had brief ‘face time,’ employees in travel-related service enterprises, retail clerks, and policemen. In these instances, the traveler frequently obtained and elected to utilize a personal recommendation from someone they perceived to be knowledgeable and trustworthy. Whether a strong or weak relationship tie existed was possibly irrelevant to the visitor. Realistically, all categories of locals may not be perceived by a visitor to be equals in meeting his/her preferred criteria of ‘trust,’ ‘expertise,’ and the provision of a ‘personal’ recommendation. For example, public sources of information locally (e.g., a visitor’s bureau) may solely promote member enterprises to the exclusion of non-members. Even if these sources are not limited to the promotion of member services, there is a general requirement to equitably promote all facilities in the region to inquiring visitors, therein negating the ability to obtain a genuine ‘personal’ recommendation. Similarly, a recent article in the Miami Herald (Hanks, 2006) openly exposed the widespread practice of ‘pay offs’ to concierges for restaurant, nightclub, tour, car rental, and day cruise referrals. Fig. 2 is a narrowly focused extension to Rompf et al.’s (2005) model, with ‘Tie Strength,’ ‘Expertise,’ and ‘Trustworthiness,’ and ‘Personal Referral’ posited as separate constructs. Their respective paths lead to the ultimate determination by a visitor to use (or not) any/all information provided. Since the investigation’s focal point was a decision-transfer strategy, only a direct path from ‘3rd Party Referral’ to ‘Purchase Decision’ is portrayed in this limited model. As a generalization, recommendations by family and friends are likely to be highly trusted and sought after. Levin and Cross (2004) proposed that tie strength may be strong between new strangers that are perceived as

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Perceived Expertise

3rd Party Referral

Trustworthy

Purchase Decision Tie Strength

Satisfaction Outcome

Fig. 2.

Personal Referral

An Alternative At-Destination Decision Strategy Model for Direct Referrals.

competent and benevolent (i.e., ‘expertise’ and ‘trustworthy’). Following the Levin and Cross’ (2004) premise, we used relationship closeness and frequency of contact as determinants of tie strength asserting that ‘friends and relatives’ may anchor the high end on a tie strength continuum and ‘casual face time with a local resident’ may anchor the low end of the actual tie strength continuum. Providers of services at a destination, travel-related or otherwise (e.g., visitor center, concierge, cab driver, etc.), are proposed to line the interior points of this relationship continuum. Summarizing, on one end are trusted friends and relatives who provide personal referral information that is highly sought after, likely acted upon, and generally produces a highly satisfying outcome. On the other end of the continuum is a strong–weak tie formed from a casual temporary relationship that is trusted. Referrals from this latter source are also posited as having a high likelihood of being acted upon and result in a highly favorable experience outcome. In the central core are information sources that are possibly more explicit, are readily convenient and thus utilized, and which may provide less tacit knowledge, and may potentially result in more neutral levels of satisfaction in comparison to referrals from the extreme ends of the continuum.

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RESEARCH METHODOLOGY This study signiﬁcantly departed from the majority of previous studies on visitor information sources and decision strategies for services delivered at a destination by interviewing travelers as they departed a major tourist destination. A pre-tested survey instrument initially collected information on multiple decision points (pre-trip, in-transit, and at-destination) for general categories of travel-related services (i.e., lodging, eating, entertainment, recreation, and transportation). Subsequent sections of the questionnaire probed the sources and utilization of information for decisions made once the visitor arrived at a destination. Speciﬁcally, a series of questions explored (a) the sources of referral information at the destination for travel-related service decisions across the identiﬁed service categories including lodging, entertainment, eating, recreation, and transportation, (b) whether a referral to speciﬁc business was requested and received, (c) whether a recommendation was followed if a speciﬁc enterprise was recommended, and (d) the level of satisfaction associated with referrals that were taken. All referrals recalled by respondents were recorded and then compared for referral sources along with the associated level of satisfaction for those referrals taken. The delineated sources of information at the destination utilized in this study included: ‘friends and relatives,’ ‘visitor center staff,’ ‘hotel staff,’ ‘auto service station attendants,’ ‘car rental service personnel,’ ‘local residents I happened to meet here,’ and an ‘other’ source. These were elected for inclusion based on categories identiﬁed in past research. Finally, social demographic, trip purpose, and travel party characteristics were collected from respondents.

Data Collection Respondents were intercepted as they were preparing to leave an international airport. Approximately 50 million visitors travel to the destination annually with the two dominant purposes of travel being leisure and convention/meeting attendance. However, the area has a diversiﬁed economic base and attracts a large number of business travelers as well. Randomly intercepting the departing traveler was seen as providing the greatest potential for polling visitors across all travel purpose intentions (e.g., business, leisure and mixed). The preferred option for interviewing departing visitors would be at the airport gates, but this was no longer an option due to ‘9–11’ and other

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security issues. An alternative best option was determined to be the collection of information from the ﬂy-drive segments as they returned their rental vehicles. By contacting corporate and regional ofﬁces of car rental agencies with facilities on or adjoining the airport, two nationwide rental agencies elected to participate. One represented off-site car rentals that shuttle travelers to the airport, and the other was an on-site car rental agency whereby travelers are free to walk to the concourse after they turn in their rental cars. Restricted access between car rental and air terminal to departing clients was provided after they returned their car. On-site airport access was granted by store and by airport authorities. Systematic scheduling allowed for rental return intercepts during peak, moderate, and off-peak times throughout all days of the week over a 30-day period. Three 4-h blocks of time were established for the sampling intervals (6 am–10 am; 10 am–2 pm; 2 pm–6 pm), with a return site visited every other day with time blocks being rotated by day of visit. After the completion of their rental-car transaction, respondents at both locations were approached and requested to participate in the study. For the off-site location, a more ﬂexible intercept time was provided during a shuttle bus transit to the airport terminal. Respondents were asked to recall information from the referrals associated with the trip. Due to the recency of the trip, it was expected that some of the bias associated with memory recall would be reduced. The survey instruments were completed using verbal protocol or self-administration depending on the preference of the respondent. Verbal protocol was the preferred data collection method at the airport, since less than an approximately 10-min window of opportunity was found as a traveler progressed from the rental agency to the ticket counter. If a respondent was traveling as part of a travel party, only one survey was used, eliminating the possibility of multiple data counts for the same trip. Typically, other members of the travel party had a natural curiosity regarding the investigation, usually assisting the respondent in completion of the survey.

FINDINGS Respondent Profile A total of 345 useable questionnaires (349 returned) were completed and analyzed using SPSS 14. Respondent demographics are presented in Table 1.

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Table 1.

Proﬁle of Respondents.

Characteristics

N

Trip purpose Business Pleasure Business and pleasure Personal reasons

339

Gender Female Male

338

Number of adults in travel party 1 2 W2

340

Children in travel party Yes No

340

Educational level Lacked high school degree High school graduate Some college, technical, or AA degree Bachelor’s degree Some graduate studies Master’s degree Professional degree Doctoral degree

331

Residential address Domestic International

329

Household income Under $20,000 $20,001–$40,000 $40,001–$60,000 $60,001–$80,000 $80,001–$100,000 More than $100,000

322

Count

%

45 225 38 32

13 66 11 10

182 156

54 46

58 200 82

17 59 24

147 193

43 57

9 46 97 93 24 37 12 12

2 14 29 28 7 11 4 4

262 67

80 20

4 26 64 49 60 96

1.3 8.7 21.4 16.4 20.1 32.1

A slight majority of women (54%) versus men (46%) are represented in the respondent data. Pleasure travel accounted for two-thirds (66%) of the trip purpose, with the remainder being closely divided between business, business and pleasure, and personal (13, 11, and 10, respectively).

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Respondents were generally well educated, with more than 50% reporting a bachelor’s degree or higher level of education, and an additional 29% reporting some college or a technical/AA degree. Eighty percent of the travelers were domestic. However, as may reasonably be expected, given our location, the international respondents represented a rate that was more than twice the actual overall percentage of international visitors to the destination. More than two-thirds of the respondents reported household incomes greater than 60,000, and almost one-third (32%) reported their income to be greater than 100,000.

Locus of and Comparative Frequency of Decisions for Travel-Related Services Table 2 reports travelers’ place or locus of purchase decisions for the speciﬁed travel-service categories. As may be expected, lodging and transportation decisions were primarily made before departure. Also, it is no surprise that 10% of respondents reported making these decisions intransit or at the destination as well. Eating and dining decision patterns were almost a complete reversal to the lodging and transportation decision pattern, with 17% reporting some form of dining decision prior to departure. There is almost a 50/50 split for entertainment and recreation decisions being made prior to departure and at the destination. Table 2. Category of TravelRelated Decision Lodging (N ¼ 336) Eating and dining (N ¼ 337) Entertainment (N ¼ 305) Recreation (N ¼ 276) Transportation (N ¼ 337)

Locus of Service-Venue Decisions by Service Category. AtPre-Departure In-Transit Pre-Departure, In-Transit, and Destination and Atand At(%) Destination (%) Destination At-Destination (%) (%)

PreDeparture (%)

InTransit (%)

304/91

6/2

16/5

7/2

1/0.3

2/1

33/10

29/9

236/70

19/6

15/5

4/1

130/43

16/5

126/41

22/7

2/1

6/2

127/46

18/7

115/42

10/4

1/0.4

5/2

303/90

4/1

25/7

2/1

2/1

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PAUL D. ROMPF AND DENVER E. SEVERT

The remainder of this section will focus solely on information sources and decision strategies of visitors while at the destination. Respondents were requested to ﬁrst report on the local sources of information they utilized in an external information search and then whether they requested and received a speciﬁc venue recommendation. To the latter, 58% of those responding (157 of 270) indicated that they requested and received a speciﬁc enterprise referral. However, whether the remaining respondents (and nonrespondents) either ‘did not ask for’ or ‘did ask but did not receive’ a speciﬁc referral, as well as whether the traveler had sufﬁcient internal knowledge to make the respective decisions, was unable to be determined from the data. Of additional relevance, it was not unusual for respondents to report using more than one source of information at the destination for a decision and to further report using the same source for multiple decisions. Table 3 provides detailed information on the local sources of external information used by visitors, and is displayed according to type of travelservice category. Friends and relatives are the overwhelming source reported by respondents for all categories of services, with the exception of transportation-service decisions made at the destination. Hotel staff generally represented the second most used local source, but the reported frequencies are approximately half of those for friends and relatives. Visitor center staff is third in the hierarchy of local sources, and their frequencies are approximately half of those reported for hotel staff. Although the frequencies for ‘local residents I happen to meet’ are a distant fourth, they are evident to varying degrees across all travel-service categories. Table 4 provides the results for those visitors who reported requesting and receiving a speciﬁc venue referral, and whether the referral recommendation was followed. It also reports the satisfaction level of the venue associated with the decisions taken from referrals. As may readily be expected, no source of information and speciﬁc referral at the destination was reported to be followed all the time. Although the referral frequencies are not equivalent across information sources in each of the travel-service categories, hotel staff generally had the highest percentage of visitors following a referral recommendation. Friends & relatives were a close second. Some of the reasons as to why respondents volunteered for not following a recommendation were a perceived lack of expertise, lack of trust, change of plans, and a desire for something new/different. Finally, respondents were requested to rate their level of satisfaction for the service received and referrals taken by the source of information on a scale of 1–5 (1 ¼ highly dissatisﬁed; 5 ¼ highly satisﬁed). It is important to

2 2 8

5 5 20 12 1 7

28 3 10 1

%

73 8 26 2

N

Lodging

4 8 6 7

107 30 66 19 2 9 21 25

N

41 12 25 7 1 3 8 10

%

Eating and Dining

6 4 2 1 1

96 21 41 6 1 4 16 14

N

37 8 16 2 0.4 2 6 5

%

Entertainment

External Information at the Destination.

1 1

7 1

93 22 43 5 2 4 11 10

N

36 8 16 2 1 2 4 4

%

Recreation

Note: Overall N ¼ 262 (multiple responses per person were allowed due to multiple decisions made per trip).

‘Other’ sources Internet Advertising media Other commercial third party referral Drive by Police

Referral source Friends and relatives Visitor center staff Hotel staff Restaurant staff Auto service station staff Car rental staff Local residents I happen to meet ‘Other’ sources

Travel-Service Category

Table 3.

13 2 1

42 3 16

39 4 12 3

N

16 1 6

15 2 5 1

%

Transportation

At-Destination Referrals, Tie Strength, and Satisfaction 153

Friends and relatives Visitor center staff Hotel staff Restaurant staff Auto service station staff Car rental staff Local residents

Source of Information

0.922

1.085

1.103 1.040

1.098

0.996 0.815

4.42

3.97

3.90 4.13

3.83

4.09 4.43

4 4

11 2

5

47

n

1 4

11 0

4

39

‘N ’ Who followed

5 13

2

45 14

16

64

n

2 9

1

39 9

6

57

‘N ’ Who followed

Eating and dining

3 11

1

24 3

13

61

n

2 8

1

21 0

10

49

‘N ’ Who followed

Entertainment

4 9

2

25 5

15

59

n

3 6

1

21 1

10

47

‘N ’ Who followed

Recreation

17

6 1

3

27

n

13

5 0

2

22

‘N ’ Who followed

Transportation

Lodging

1 ¼ Highly dissatisﬁed; 5 ¼ Highly satisﬁed

SD

Speciﬁc Recommendation Provided and Did/Did Not Follow the Recommendation

Level of Satisfaction

Table 4. Referred Experience Satisfaction, Referral Type, and Referrals Followed or Not Followed by Referral Source.

154 PAUL D. ROMPF AND DENVER E. SEVERT

At-Destination Referrals, Tie Strength, and Satisfaction

155

point out that the frequencies of requests from visitors vary greatly across the sources and venue categories. As posited, referrals taken from friends and relatives were highly rated on the satisfaction scale (M ¼ 4.42; SD ¼ 0.922), but their potential ranking for delivering the highest level of satisfaction had a challenger, ‘Local residents I happened to meet’ (M ¼ 4.43; SD 0.815). The remaining at-destination sources were within 715 one-hundredth of ‘4.0’ value on the scale. Restaurant staff and car rental staff were rated slightly higher than the visitor center and hotel staffs on this dimension.

DISCUSSION This research primarily examined the external sources and referral decision strategies utilized by visitors for travel-related service venues while they were at a destination. Initially, the research sought to answer, ‘How numerous were the sources and what were the relative frequencies of use across speciﬁc travel-service categories?,’ ‘Was a speciﬁc recommendation requested and received?,’ and ‘Did the respondent follow the recommendation?’ Subsequently, the satisfaction levels associated with referrals from the different sources were investigated. It had been posited that the ‘tie strength’ between a visitor and information source might provide valuable insight for the interpretation and understanding of these results. However, visitors’ perceptions of ‘tie strength,’ ‘expertise,’ ‘trustworthiness,’ and ‘whether a personal referral’ was provided were never directly measured in the study. Based on the literature, these have been implicitly inferred from the category label attached to a referral source by the respondent. Speciﬁcally, we expect that strong tie strength relationships and perceived strong–weak tie relationships will be associated with referrers of information that are higher in expertise, trustworthiness, and are perceived to be a personal or a more customized referral. The study provided theoretically support these relationships.

External Information Sources Utilized by a Visitor by Travel-Service Category Strongly supported by this study is the existence of a considerable number of decisions deferred to the destination as proposed by Rompf (2001). In particular, the destination is a signiﬁcant decision point for dining,

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entertainment, and recreation decisions, and it also is the locus for some lodging and transportation decisions. Although many travelers may have a level of internal knowledge relevant to these decisions, the current study suggests that a large number of visitors to a community seeks external sources of information, especially from ‘locals,’ to make those decisions. In examining the external sources utilized by visitors, inferences drawn from tie strength theory were supported through the dominant use of friends and relatives over any other source. Not to be underestimated, atdestination sources of relative proximity and convenience (e.g., hotel concierge, restaurant staff, etc.) were also prominently used. Also noteworthy, a local resident having limited face-time with a visitor, while not as often determined to be the central referral source, apparently plays a critical role in providing information, particularly direct referrals. Where a referral is solicited and given, the results further provide evidence of a high probability of the visitor accepting the recommendation and acting favorably upon it. This was generally consistent across all categories of referral providers. The proposed limited model of visitors’ at-destination decisions incorporating the concept of tie strength are presented in Fig. 2. Referrals from locals with strong ties to the visitor were a preferred source of information and had higher levels of satisfaction from the service experience. Also supported is the concept of an actual weak tie that is perceived as strong, based on a moderated high level of trust with the referrer, to become a strong–weak tie. These ties from trusted strangers were also a reported source of information and had the second highest level of satisfaction. This provides theoretical support for our research questions revealing that strong ties and strong–weak ties are referral information sources also lending support for the visitor referral criteria proposed by Rompf (2001). The gratuitous nature associated with a referral creates, and is in all reality, a more trustworthy recommendation and may further be higher in authenticity. Authenticity is argued here because the recommendation is likely more experience-based and not founded on a payment for referral, a membership fee to be in the referral set, or be the hundredth recommendation in a week that hotel staff may have been asked to provide. These ﬁndings for owner/managers of travel-service enterprises imply that traditional forms of promotion appealing to the traveler do have a role in a marketing plan, but that the enterprise should also be more communitycentric and incorporate promotional strategies and tactics directed toward members of the community. The concept of tie strength has relevance and

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provides some insight into this. As a generalization, we as consumers like to do business with those we know, whom we perceive as friends, and with those we trust. This relationship becomes the incentive and basis for referring others to the enterprise.

LIMITATIONS The population and sampling frame, although from a major travel destination, was composed of ﬂy-drive travelers departing a destination. The results may not be representative travelers to the destination using alternative means of transportation. The researcher has made inferences about the tie strength between information sources and visitor, without explicit measurement. The inference is based on the assumption that more often than not, strong ties and a higher level of trust exist between the traveler and his/her friends and family, and more neutral ties and levels of trust exist between travelers and traditional travel-information sources such as restaurant, hotel, and visitor center staff. Finally, an inference was made regarding the existence of strong–weak ties to be associated with respondent’s use of a local resident with whom he/she had casual ‘face time,’ and from whom a referral was obtained and followed. The distinction between entertainment and recreation venues may not be fully understood by respondents. When such a question was raised by a respondent, the interviewer replied that recreation was considered to be participatory and entertainment was considered to be more viewer oriented. This was not seen to be detrimental to the study but is noted as a word of caution for interpretation of the results. Finally, information sources for transportation services may have been biased because the data was collected at the rental car return. In conclusion, higher level statistical testing was not feasible, given the large differences in respondents’ selection or sample of information source as well as travel-service category. Frequencies, mean calculations, and crosstabulations provided useful statistics in the investigation of referral sources, frequency of usage, and satisfaction outcome with a referred experience.

SUGGESTIONS FOR FUTURE RESEARCH The tie strength scale should be tested to provide additional support for the theory of tie, strength to at-destination referrals along with expertise and

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trustworthiness. Though the researcher’s assertions related to ties with the traveler are likely correct, empirical evidence from the tie strength scale would provide further support for the assertions made. Similarly, qualitative studies should be undertaken with travelers to supply collaborating evidence of the posited gratuitous referral criteria actually being sought, and whether the strong tie and the strong–weak-tie referral actually provide more authentic referrals that may be more accurate.

CONCLUSIONS Given the ﬁndings, it becomes important for destination leaders to determine which enterprises are delivering requisite service levels to the traveler. The provision of more referrals to businesses with a better track record in service experience may assist in enhancing the overall travel experience for destination visitors, elevating the destination’s image as well. Information sources such as convention and visitors bureau (CVB) and paid-referrals may want to experiment with referral systems where referrals are made on the basis of service-experience outcome rather than on the basis of member fees and an obligatory remuneration-based referral list. Due to the diversity and potentially large number of businesses within a destination, this decision would have to be a destination-wide initiative. Finally, initiatives to reward business providers of better visitor experiences is just one step that can be taken toward enhancing the destination’s image. Of course, implementing this through a referral system poses a complex scenario for the leadership of a destination.

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SERVICE QUALITY EVALUATION AND MULTIATTRIBUTE ATTITUDE MEASUREMENT: THE CASE OF A CHAIN STEAKHOUSE IN TAIWAN David Y. Chang and Katerina Annaraud ABSTRACT Many research studies have found that service quality has a direct impact on a company’s profitability. Given the increasing competition in the steak restaurant business in Taiwan, the restaurant industry has noticed the importance of service quality. This study empirically assessed customers’ perceptions and expectations of service to measure service quality of a chain steakhouse in Taiwan. By applying the three-column SERVQUAL model approach coupled with part of the Fishbein model, the study was able to (a) analyze the service gaps existing in the service delivery process to measure service quality and customer satisfaction and (b) conduct a multiattribute attitude measure to evaluate a customer’s attitude toward the service measure attributes of the same brand name restaurants in different locations. As service quality has a direct impact on a company’s profits, the research findings are important, particularly to the examined chain steakhouse. These findings offer implications to improve the service quality for restaurant operations and further support the company in gaining a competitive advantage in the increasingly viable steak restaurant business in Taiwan. Advances in Hospitality and Leisure, Volume 4, 161–184 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00008-8

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INTRODUCTION Over the past two decades, the issues of service quality and customer satisfaction have occupied an important position in research for the hospitality industry. During the last 10 years, various types of new steakhouses or steak-serving restaurants have been established in Taiwan. The number of these new competitors has increased tremendously from 1998 to 2006 as the number of people who select steaks as the dine-out choice in Taiwan has grown greatly. Competition becomes serious as steakhouse management seeks to maintain old customers and attract new ones at the same time. To win the severe competition, restaurateurs must strive to improve the qualities of products and services offered since service quality overall has become a focus for restaurant management and development in Taiwan. Research has shown that service quality has a direct impact on a company’s proﬁtability. However, it is possible that some discrepancies between the service provided by the restaurant and the services perceived by the customers might exist. Knowing a customer’s perception of the service delivered can help measure the service quality and in turn aid in management decision making for company executives. The argument that service quality impacts business proﬁts has long been apparent (Baker & Crompton, 2000; Zeihaml & Bitner, 2000) and thus it is asserted that the restaurants in Taiwan are no exception. Superior quality of service is one factor within the control of the hospitality industry that can crucially add value to its product and lead to customer loyalty (Lee, Barker, & Kandampully, 2003). While there is no guarantee of a satisﬁed customer’s repeat visit, it is almost certain that a dissatisﬁed customer will not return (Soriano, 2002). Therefore, the concept of service quality has been the subject of many research studies in a variety of service industries. Many of these research studies focused mostly on the United States, Australia, and Europe (Davidson, 2003, Lee et al., 2003; Tsang & Qu, 2000; Wong, Dean, & White, 1999). Most of these studies have investigated the service quality of the hotel business but comparably less research has focused on the restaurant industry. Very few paid attention to the restaurant business in Taiwan. The primary purpose of conducting this study is to understand (a) the restaurant’s service quality through customers’ perceptions of service delivered, (b) customers’ satisfaction levels, and (c) customers’ attitudes or assessment regarding the same brand name restaurants in different locations. Because this study was sponsored by a chain steakhouse company, the ﬁndings are expected to provide useful administrative suggestions and a

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better guideline to improve and assure the consistency of service quality for each restaurant property in different locations across the country. The outcome of the research is important for the restaurant operators in Taiwan to comprehend their strengths and weakness. Finally, a contribution can be made to the body of literature on the related subject.

BACKGROUND OF THE STUDY OBJECT The study object, a chain steakhouse in Taiwan, is owned and operated by a corporation which has different restaurant brand names across the nation providing different styles of steak-related meals targeting various groups of customers. The case selected in the study is one of the company’s branded chain steak restaurants termed X Steakhouse for this research at the request of the company. Under the same brand name, the steakhouse offers a unique style of standardized combo steak meal. Spending less than $20 (USD), a customer can enjoy a delicious meal package including several courses: appetizer, antipasto, salad, soup, entre´e (a steak), dessert, and soft drink. Each of these courses, with the exception of the appetizer, has more than one choice for the customer to select from and therefore the customer can create his or her own series of courses for the meal. The company has around 20 X Steakhouses in Taiwan at the time this study was conducted. Revenue generated from this brand alone was more than $3 million (USD) in 2006. Based on the service style and food quality, this type of steakhouse is considered an ‘‘easy, cozy, and family’’ dining place that ﬁts comfortably between the styles of luxury and casual restaurants.

LITERATURE REVIEW In today’s hospitality business world, the critical measure of success lies in an organization’s ability to satisfy customers through continuous excellent service (Gabbie & O’Neil, 1996). In other words, the service provided to customers by a company directly impacts the company’s proﬁts as it is directly related with customers’ perceptions of services and satisfaction, and thereby developing customer retention and loyalty (Baker & Crompton, 2000; Zeihaml & Bitner, 2000). This is an important concept because researchers have found that it costs a lot more to attract new customers than to retain current customers (Oliver, 1999; Rosenberg & Czepiel, 1983) and it is more likely for repeat customers to develop steadfast loyalty

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toward the business. The contemporary business world is attributing increasing importance to measuring customer satisfaction to sustain proﬁtability (Baggs & Kleiner, 1996). However, for restaurant business, having repeat customers is one thing, ensuring an excellent dining experience for them is another. The key is to constantly improve customer satisfaction and a feeling of delight through the delivery of good services. In the last two decades, the hospitality industry has witnessed exponential growth and increased competition (Lee et al., 2003; Zeihaml & Bitner, 2000). An ideal objective for all service/hospitality businesses should be to provide a ‘‘zero-defect’’ service to win customers. However, this is very difﬁcult because service is a complex topic with many unique and intangible characteristics (Berry & Parasuraman, 1991). The challenge is to measure service quality provided through an understanding of customers’ perceptions of the service provided.

Measuring Service Quality Service quality might be described as an integration of quality theory and theories of marketing and services. It actually has been recognized as one of the key factors in determining the success of a hospitality business. The reason for this is noticeable in that customer satisfaction is a crucial element of proﬁtability as stated earlier. Like researchers in other service industries, hospitality researchers have directed their attention to the relationship among customer satisfaction, repeat sales, and business proﬁts. A number of researchers suggest that customer satisfaction can be secured through highquality products and services (Getty & Getty, 2003; Tsang & Qu, 2000; Gabbie & O’Neil, 1996; Gupta & Chen, 1995). Pizam and Ellis (1999) stated that, in contrast to material products or pure services, most hospitality experiences are a combination of both products and services. Customer’s satisfaction with a hospitality experience such as a hotel stay or a restaurant meal is a sum total of satisfactions with the individual elements or attributes of all products and services that make up the experience. However, the center of complexity in understanding customers’ hospitality experiences, as being commented by researchers, is due to the extent of customer participation in the service process (Parasuraman, Zeithaml, & Berry (PZB), 1985; Kandampully, 1997). Customer’s involvement in the service delivery process makes the opinions and feelings of a customer important in measuring the outcome and quality of services a company provided.

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Edvardsson (1996) stressed that the concept of service should be dealt from the customer’s point of view, since it was the customer’s perception of the outcome that constituted the service and further determines the service quality. The notion of ‘‘service’’ can mean different things to different customers and it is an experience, and therefore more difﬁcult to deﬁne or measure. Mack, Mueller, Crotts, and Broderick (2000) stressed the need for businesses to talk to their customers, to get to know their customers’ expectations, and make efforts to retain the customers and sustain proﬁts. Getty and Getty (2003) believed that no matter how much effort is placed into producing quality service, it is the perception of customers that really matters. However, the customer’s perception of service is actually strongly inﬂuenced by an emotional and experiential reaction from the services provided by the service providers. It is important for a service business to know whether or not there is a discrepancy in service perceived and expected by the service receivers (customers). Such a discrepancy is commonly referred to as the ‘‘gap’’ in service literature. Oliver’s (1981) work perhaps is an early example that studied the gap between a customer’s expectation and perception and suggested that gap measurement is a very critical concept to understand the relationship between a customer’s satisfaction level and service quality. PZB’s SERVQUAL (1985) and their sequential research work in 1994 (Parasuraman, Zeithaml, & Berry, 1994a, 1994b, 1994c) perhaps were some of the most notable studies which made similar arguments to Oliver’s (1981) with reference to service quality. PZB have been trying to investigate how to measure and manage quality in services since 1985. They deﬁned perceived service quality as ‘‘a global judgment, or attitude, relating to the superiority of the service.’’ They linked the concept of service quality to the concepts of perceptions and expectations from the customer’s point of view. This linkage, as stated in their studies, is that ‘‘Perceived quality is viewed as the degree and direction of discrepancy between consumers’ perceptions and expectations.’’ Therefore, PZB suggested that customers’ assessments of overall service quality are based on the gap between their expectations and their perceptions of service performance levels. This argument supported Oliver’s earlier work in 1981 and was also advocated later by Miller (1977) who considered ‘‘understanding the gap between a customer’s expectation and perception about a service’’ to be the ‘‘First Law’’ for studying service quality. PZB revised their SERVQUAL instrument in 1988 to measure service quality by subtracting a customer’s perception score of the service provider’s performance from a customer’s expectation score. Subsequent researchers have been adopting this equation to understand customer satisfaction

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through the measure of service quality score in that higher service quality is found resulting in higher satisfaction. Since then, SERVQUAL has been broadly applied in hospitality literature to measure the service quality (Wuest, Tas, & Emenheiser, 1996) and service quality and customer satisfaction have been identiﬁed as the two main elements of the customer service process (Susskind, Borchgrevink, & Brymer, 2000). However, quality can mean different things to different customers and it is a sum total of service experiences (Pizam & Ellis, 1999) for an individual. Consequently it is more difﬁcult to deﬁne or measure. According to Johns and Howard (1998), quality measurements only have operational value if they are able to indicate the way in which service was or was not satisfactory. For restaurant businesses, the measurement of service quality is made during the actual delivery of the service. This is the expectancy and disconﬁrmation theory established in hospitality literature that is mainly derived from PZB’s SERVQUAL model (Parasuraman, Zeithaml, & Berry, 1985, 1988, 1994a) discussed earlier. PZB deﬁned service quality into ﬁve dimensions, Reliability, Responsiveness, Assurance, Empathy, and Tangibles, in the SERVQUAL model. Using them as the service attributes, researchers can measure the service quality gap in each of them. Although the limitations of using SERVQUAL have been noticed, such as measuring time and scale (Garuana, Ewing, & Ramaseshan, 2000), several researchers have extended the work to discuss the measuring and evaluating the validity and reliability of service quality. Another reason to follow the footsteps of the model and the previous successful work is that there are sufﬁcient empirical research studies to support its adoption. Researches have conﬁrmed that SERVQUAL validly and reliably measured the quality of the service provided by hospitality businesses (Stevens, Knutson, & Patton, 1995; Nel & Pitt, 1993). In addition, the SERVQUAL model is simple, inexpensive, and easy to implement (Heung, Wong, & Qu, 2000).

Measuring Multiattribute Attitudes As discussed in the literature, the SERVQUAL model (PZB, 1985, 1988) is a satisfaction measurement technique to investigate the gaps in the service level performed by a company from the customer’s point of view. However, empirical studies have suggested that the customer’s perception of service is inﬂuenced by both situational factors and organizational factors. The literature is replete with articles supporting the ﬁndings about the attributes

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that differentiate service organizations from their manufacturing counterparts (Shostack, 1977, 1984; Thomas, 1978; Barrington & Olsen, 1987; Zeithaml, Parasuraman, & Berry, 1990; Reeves & Bedinar, 1994). Researchers believed that all businesses can be classiﬁed on a continuum with tangible/intangible-dominant (Shostack, 1977, 1984) or equipment/ people-based activity (Thomas, 1978) anchoring on and being characterized by the activities on both ends of a spectrum. Chase (1978) articulated this idea and described the continuum as the degree of contact between the customer and the service providers. However, service itself is an intangible element in the customer-service provider exchange and is difﬁcult to measure quantitatively because the end product (i.e., the service) results from an exchange of human action and behavior (Schneider & Bowen, 1992). While seeking services, customers hold the expectation of being treated with courtesy and of receiving services consistent with their expectations and perceptions. To engage in excellent customer service, employees must possess not only the motivation to perform their service duties but also an aptitude to perform them (Susskind et al., 2000). Employees’ customer service behavior is likely to be difﬁcult to predict and control due to multiple inﬂuences on employees’ behavior and attitudes in the service-based workplace (Schneider, Wheeler, & Cox, 1992). Therefore, for a chain operation business, using a standard measure to ensure consistency in service quality is important. Unfortunately, the modiﬁed SERVQUAL model, although it works well in measuring service quality for restaurant business, it does not provide the mechanism to measure customers’ attitudes toward its ﬁve attributes for the service quality of the same branded restaurants in different locations. One can ﬁnd from the discussions above that the model provides aggregated information about each service attribute in order to assess customer satisfaction. However, customers’ attitudes toward a different restaurant’s service on the ﬁve service measure attributes cannot be assessed at the same time. In other words, a customer might see a discrepancy on the service quality across different restaurants but such a discrepancy cannot be identiﬁed by the implementation of the model’s threecolumn format. To a chain restaurant operation, knowing its customers’ attitudes toward service quality and whether or not each property is delivering the same level of service quality is very important. The Fishbein model (Ajzen & Fishbein, 1980) is a technique for multiattribute attitude measurement. It is a model to account for the relationship between attitudes, beliefs, and behaviors. Their theory is based on the assumption that one’s behavior results from a cognitive process in which one systematically processes all available information. Fishbein

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hypothesized that a person’s behavioral intentions are determined by his or her attitudinal or personal component. The personal attitude toward other’s performance refers to the person’s judgment of being in favor of or against such a performance. Therefore, the subjective feeling is mutually formed based on the means of how to perform or act under the pressure of other’s perception of accepted or expected norm. The Fishbein model (Ajzen & Fishbein, 1980) has been tested in many situations and has been useful in understanding and predicting many types of behavior such as dental hygiene (Toneatto & Binik, 1987), contraceptive use (Miller & Grush, 1986), smoking (Marin, Marin, Perez-Stable, Otero-Saabogal, & Sabogal, 1990), moral behavior in sports (Vallerand, Deshaies, Cuerrier, Pelletier, & Mongeau, 1992), and evaluation of service (Masmanidis, Vassiliadis, & Mylonakis, 2006). In applying the theory of reasoned action (Ajzen & Fishbein, 1980) with the SERVQUAL model (PZB, 1988) to evaluate service quality, a customer’s attitude represents a summary evaluation of a psychological object captured in the ﬁve attributes as good/bad, harmful/beneﬁcial, pleasant/unpleasant, and likeable/dislikable (Ajzen & Fishbein, 2000). Restaurant customers’ attitudes are their evaluations on the service performance conducted by the service providers to meet their speciﬁc needs, which in turn affect their attitudes and preferences. Therefore, using Ajzen and Fishbein’s work to capture customers’ attitudes toward the ﬁve service measure attributes of SERVQUAL on the same branded restaurant in different locations can help understand the difference in the service quality across different restaurants.

Service Gaps Zeihaml and Bitner (2000) stated that in order to manage service quality, it was important to manage the gaps between expectations and perceptions on the part of management, employers, and customers. However, the most important gap was the one between customers’ expectations of services and their perceptions of the services actually delivered. This is the scope of the study and is also the gap addressed by PZB and other researchers mentioned earlier. It holds true in its importance for service quality research. This therefore is the Gap 1 that needs to be measured in this study. By adopting PZB’s three-column format SERVQUAL, two other gaps are also found between each column and need to be studied. Gap 2 is the one between ‘‘My Perception of Service Performance’’ and ‘‘My Minimum Service Level’’;

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Gap 3 is between ‘‘My Perception of Service Performance’’ and ‘‘My Desired Service Level.’’ Because the research also aims to understand whether or not there is a difference in overall service qualities among chain restaurants in different locations, this possible difference is the Gap 4 for the study. In summary, the gaps selected for measurement in this study are: Gap 1: The discrepancy between ‘‘My Perception of Service Performance’’ and ‘‘My Expected Service Level.’’ Gap 2: The discrepancy between ‘‘My Perception of Service Performance’’ and ‘‘My Minimum Service Level.’’ Gap 3: The discrepancy between ‘‘My Perception of Service Performance’’ and ‘‘My Desired Service Level.’’ Gap 4: The discrepancy between the service quality evaluated by customers’ attitudes on the service attributes among different locations of chain restaurants.

METHODOLOGY Based on the prior research studies, to achieve the research objectives, the SERVQUAL instrument (PZB, 1988), and the theory of Ajzen and Fishbein (1980) are adopted. The former is an approach for satisfaction measurement while the latter is a technique for multiattribute attitude measurement.

Survey Design According to PZB’s study (1994c) the SERVQUAL should be administered in a three-column format with each of the columns being headed for each of the items ‘‘My Minimum Service Level,’’ ‘‘My Desired Service Level,’’ ‘‘My Perception of Service Performance.’’ PZB believed that this threecolumn approach should be adopted because it has a greater diagnostic value and is capable of speciﬁcally indicating the position of the zone of tolerance and the perceived service level relative to the zone (PZB, 1994a). Therefore, in implementing the SERVQUAL approach, the major part of the survey was designed based on the three-column approach and ﬁve attributes deﬁned in the SERVQUAL model (PZB, 1988). A ‘‘think tank’’ was organized and the members of the think tank met for approximately 4 h and ﬁfteen minutes to discuss and deﬁne the variables/factors for each of the ﬁve attributes deﬁned in the SERVQUAL model (PZB, 1988). The meeting

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was moderated and guided by the researcher to conduct an in-depth discussion on the service-related topics in connection with the restaurant style to elicit the evaluation factors for service quality measurement. The think tank was composed of 10 people from 8 different restaurant locations. The think tank members were handpicked by the company’s CEO. They were all in top management positions in their restaurants with at least two years of work experience in the X Steakhouse operation. They all once worked as a front-line server in the company’s restaurants. Based on the result of the think tank meeting, 27 variables/statements were developed. Several factors were used to best describe and measure an attribute of the SERVQUAL model (Table 1). For example, the ‘‘cleanliness of y,’’ ‘‘suitable de´cor,’’ ‘‘designs of menus,’’ ‘‘comfortable seats & dining area,’’ ‘‘convenient parking,’’ and ‘‘employees appearance’’ were identiﬁed to measure the attribute Tangibles. The factors, such as ‘‘quickly correct mistakes,’’ ‘‘employee anticipate guests’ needs,’’ ‘‘food served promptly,’’ ‘‘give supports to other employees,’’ and ‘‘frequency of stop-by and checking’’ aid to measure the attribute Responsiveness. Other factors like ‘‘warm and friendly greetings,’’ ‘‘polite and courteous employees,’’ ‘‘making efforts to let customers feel special,’’ and ‘‘reassurance on the corrected errors or mistakes’’ are used to measure the attribute Empathy. All 27 of these evaluation factors are included in the ﬁrst part of the survey. Each factor was measured on a scale of 1 (extremely low) to 10 (extremely high). The second part of the survey was designed to evaluate the ﬁve SERVQUAL attributes for the restaurant where the customer just dined. There were two questions in this part. A customer was asked to give a score on the same scale (1–10) regarding his or her expectation from the restaurant about each attribute. This question was included because, as suggested in the literature reviewed above, the SERVQUAL instrument does not provide a scale or attributes to deal with a customer’s expectation of service quality or to directly capture the reﬂections on the service experience received. Therefore, it is necessary to ask the respondents to express their expectations of the service experience in relation to all attributes of all the services. The second question was to measure the importance of the ﬁve attributes. This is an adoption of the Fishbein model (Ajzen & Fishbein, 1980, 2000) for multiattribute attitude measurement. Aggregated scale measurement was used, in which participants were requested to distribute 100 points among the ﬁve attributes based on the importance perceived. Demographic questions were asked in the last part of the survey.

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Table 1. Service Evaluation Factors Identiﬁed. Service Measure Attributes Reliability

Service Evaluation Factors (1) (2) (3) (4) (5)

Food or service provided exactly as requested Taste of food Appearance of food Availability of staff when needed Dependable and well-trained employees

Responsiveness

(6) (7) (8) (9) (10)

Quickly correct mistakes Employee anticipate guests’ needs Food served promptly Five supports to other employees Frequency of stop-by and checking

Assurance

(11) (12) (13) (14) (15) (16)

Knowledge about things asked Making sure that customers feel comfortable Consistency of food served Consistency of service provided Accurate check (any human or machine errors?) Accurate reservation

Empathy

(17) (18) (19) (20)

Warm and friendly greetings Polite and courteous employees Making efforts to let customers feel special Reassurance on the corrected errors or mistakes

Tangibles

(21) Cleanliness of dining areas (22) Cleanliness of rest rooms (23) Suitable de´cor to create a comfortable dining place (24) Designs of menus (25) Comfortable seats and dining area (26) Convenient parking (27) Employees appearance (clean, neat, and appropriately dressed)

Data Collection The survey was distributed using person-to-person technique to the restaurant customers of the think tank members’ eight restaurants. In Taiwan’s restaurant industry, 10% is usually charged as the service fee (which is similar to gratuity but it goes to the company) and added to the customer’s check. This service fee was waived for the customers who were willing to participate in the research. To keep up with the table turnover and maintain a smooth business operation, the survey respondents were escorted

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to another room after their meals to complete the survey. A few trained employees were present in the room to provide guidelines and instructions on how to answer the survey questions. To reduce any possible bias and measurement errors of the analysis, a screening process was also conducted when surveying restaurant customers. The think tank members believed that a customer’s opinion is likely to be swayed by his or her group members especially when a large group of people are dining together. Therefore, a party of eight or more was not offered the opportunity to do the survey to avoid possible duplicate data. Data was collected over a 2-month period of time and 1,543 completed questionnaires were collected. Some questionnaires appeared to be unusable due to the scores assigned, which either had an unacceptable value (e.g., blank or text-type value) or exceeded the designated score range (e.g., a zero point or a value greater than 10 or 100). Finally, 1,048 questionnaires were usable for research resulting in 67.92% response rate.

FINDINGS AND DISCUSSION Demographic Information The key demographic proﬁle of the survey respondents is presented in Table 2. Females like to visit the X Steakhouse (58.83%) more than men. The largest volume of customers are those who are between 35 and 45 years old (38.37%). However, those who are older than 55 years of age (2.91%) are unlikely to visit X Steakhouse. The collected and usable sample sizes from each restaurant are also exhibited in Table 2, which presents a limited variance across the sample sizes.

Service Quality and Satisfaction Measurement As mentioned, the SERVQUAL model (PZB, 1988) is adopted to measure the service quality of the restaurant. Table 3 presents the mean values of the ﬁve service measure attributes of SERVQUAL and their service evaluation factors. Adopting PZB’s (1988) concepts of perceived service and expectation of service, the values presented in Table 3 were used for the overall assessment

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Table 2. Key Demographic Proﬁle of the Survey Respondents. Gender Male Female

431 617

41.17% 58.83%

Age 15–25 years Older than 25–35 years Older than 35–45 years Older than 45–55 years Older than 55–65 years Older than 65 years

221 402 250 145 20 11

21.11% 38.37% 23.82% 13.79% 1.88% 1.03%

Restaurants

Collected Samples

Restaurant Restaurant Restaurant Restaurant Restaurant Restaurant Restaurant Restaurant

196 182 206 192 175 198 182 212

1 2 3 4 5 6 7 8

Usable Samples 130 126 142 136 106 132 120 156

12.40% 12.02% 13.55% 12.98% 10.11% 12.60% 11.45% 14.89%

of a customer’s satisfaction level. The difference between expectations and perceptions of service performance can help in understanding a customer’s satisfaction level. Moreover, according to Berry and Parasuraman (1991), the desired satisfaction is the level of service the customer hopes to receive and the adequate satisfaction comes from the level of service that customers ﬁnd at least acceptable. Customer satisfaction results from the interaction of levels of expectations about anticipated performance and evaluations of perceived performance (Miller, 1977). That is, the satisfaction score presented in Table 4 is calculated using perception score minus expectation score. In addition, as denoted in the table, by comparing the perception score with the overall score that indicates an adequate level of service, the score for the measure of service adequacy (MSA) can be calculated. Using a similar approach, by comparing the perception score with the score of the customer’s desired service level, the score of the measure of service superiority (MSS) is obtained. ‘‘MSA’’ and ‘‘MSS’’ are the terms used by Berry and Parasuraman (1991). The values of MSA and MSS can help in understanding the service gaps identiﬁed by PZB (1988, 1994a) between the

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Table 3. Service measure Attribute

Mean Values of SERVQUAL Attributes and Their Evaluation Factors. Service Evaluation Factor

(1) Perceived Service Score

(2) Adequate Service Score

(3) Desired Service Score

(1) (2) (3) (4) (5)

8.43 9.03 9.23 8.20 8.15

8.23 8.51 8.01 8.30 7.83

8.56 8.52 8.13 8.55 8.02

Responsiveness

(6) (7) (8) (9) (10)

8.56 8.18 7.86 7.87 8.16

8.16 8.43 8.02 7.59 7.50

8.32 8.51 8.42 8.12 7.50

Assurance

(11) (12) (13) (14) (15) (16)

7.99 8.32 8.64 8.13 9.93 9.00

8.11 8.24 8.76 7.80 8.90 9.00

8.56 8.47 8.58 8.20 9.91 9.54

Empathy

(17) (18) (19) (20)

8.60 8.40 7.70 7.80

8.26 7.92 7.56 7.53

9.21 9.03 8.05 8.02

Tangibles

(21) (22) (23) (24) (25) (26) (27)

8.43 7.89 8.07 8.20 7.86 7.63 8.13

8.22 8.54 8.83 8.09 8.81 8.05 8.10

8.91 8.86 8.83 8.66 8.58 8.55 8.48

Reliability

Note: (1) is the SERVQUAL column of ‘‘My Perception of Service Performance’’; (2) is the SERVQUAL column of ‘‘My Minimum Service Level’’; (3) is the SERVQUAL column of ‘‘My Desired Service Level.’’

restaurant and its customers. The results of these measurements are exhibited in Table 4 and Fig. 1. From the visual inspection on Fig. 1, X Steakhouse overall provides a good service to its customers with room for improvement as the service performance level perceived by customers is mostly above the ‘‘minimum

8.61 8.13 8.67 8.13 8.03 41.56

8.56 8.57 8.66 8.53 8.33 42.65

Perception Expectation

0.05 0.44 0.01 0.40 0.30 1.09

(1) Satisfaction 1 5 2 4 3

Ranking

8.18 7.94 8.47 7.82 8.38 40.78

Adequate service 0.43 0.19 0.20 0.31 0.35 0.78

(2) MSA

1 4 3 2 5

8.36 8.17 8.88 8.58 8.70 42.68

Ranking Desired service

Gap Analysis: Evaluation of Satisfaction, Adequate Service, and Desired Service

Scores of Satisfaction, Adequate Service, and Desired Service.

0.25 0.05 0.21 0.45 0.67 1.12

(3) MSS

1 2 3 4 5

Ranking

Note: (1) Satisfaction Score ¼ Perception ScoreExpectation Score; (2) MSA Score ¼ Perception ScoreAdequate Service Score; (3) MSS Score ¼ Perception ScoreDesired Service Score.

Reliability Responsiveness Assurance Empathy Tangibles Overall score

Service Measure Attributes

Table 4.

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9.00 8.80 8.60 8.40 8.20 8.00 7.80 7.60 7.40 7.20 Reliability

Responsiveness Perceived Service

Fig. 1.

Assurance Adequate Service

Empathy

Tangibles

Desired Service

Gaps between Perceived, Adequate, and Desired Services.

service level’’ (i.e., adequate service) but below the level of ‘‘desired service.’’ The smallest service gap between the perceived and desired services exhibited in the ﬁgure is on the attribute Responsiveness indicating that the restaurant’s service is attentive and quick and almost reached the higher end of service quality related to this attribute. However, the customer’s perception of service quality related to attribute Tangibles is quite below the minimum service level accepted (i.e., not adequate) and the desired service level. The restaurant should pay close attention to this attribute for service improvement. The overall service satisfaction score is 1.09 which raises a ﬂag regarding the overall service quality as the respondents are not satisﬁed with the service provided. However, this is a small number and any possible service issues should be rectiﬁable. Responsiveness ranked no. 5 with a negative value of 0.44 because the customers are concerned about the food order not being served promptly (m ¼ 7.86) and employees do not seem to support each other during the peak business hours (m ¼ 7.87). Based on the discussions conducted by the think tank members, a possible reason is that the restaurant usually has very good business but might be short-handed or the employees are not well-trained due to the use of many part-time servers.

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The attribute Empathy also has a negative value (0.40) ranked no. 4. Two major factors causing this result are ‘‘reassurance on the corrected errors or mistakes’’ (m ¼ 7.80) and ‘‘making efforts to let customers feel special’’ (m ¼ 7.70). This might also be an issue related to busy business and not enough good-quality servers. Another attribute receiving a negative score is Tangibles (0.30). This is a surprise result to the think tank because the company is very comfortable with the setup, decoration, and cleanness of the dining areas. The evaluation factors, such as ‘‘parking,’’ ‘‘comfortable seats and dining area,’’ and ‘‘cleanliness of rest rooms’’ all received a score lower than 8. According to the management’s interpretation, this result might have something to do with the location of the restaurant (in the city), small dining areas, and noises generated from good and busy business. In addition, menu design also has room for improvement. Because several courses make up the entire package meal and almost each course (other than the standardized appetizer course) has more than one choice for a customer’s selection, ﬁtting all items and descriptions in one big menu does not seem to be an effective design. Perhaps a thin booklet type of menu is more suitable for comfortably displaying all the choices and descriptions of each course and facilitates customers browsing information and understanding the combination of the order. Overall the customers feel slightly unsatisﬁed with the service. MSA and MSS scores can provide further information on this issue. Statistical ﬁndings suggest that a positive overall MSA score (0.78) indicates that the perceived service performed is above the service that customers consider to be adequate. However, the attribute Empathy received the lowest point (7.82). This is consistent with the concerns about the professionalism of restaurant employees discussed earlier. In general, the MSA values suggest that the top two service gaps exist in Reliability (0.43) and Empathy (0.31) for the service delivery process. Although Tangibles (8.38) is considered the second most adequate attribute slightly lower than Assurance (8.47), this result is not consistent with the satisfaction level measured previously. This is an interesting ﬁnding because the customers are obviously not satisﬁed with the tangible factors discussed earlier, such as parking, menu design, seats, dining areas, etc. One of the possible explanations could be that the speciﬁc concerns on these tangible factors for overall satisfaction analysis do exist but customers still view X Steakhouse as a ﬁne dining place when taking other service attributes into consideration. Another possible solution to understand this inconsistency is using MSS for further interpretation.

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The overall MSS score is negative (1.12) suggesting that X Steakhouse falls short of the service levels that customers desire. Tangibles in this case has the smallest MSS (0.67) suggesting that customers are not happy with the noticeable factors mentioned, such as parking, space, menu, seating, and noise. This conﬁrms the ﬁnding in the satisfaction analysis and helps explain the inconsistency between MSA and satisfaction analysis. The company should address this issue seriously. Tangibles and Assurance both score high, 8.70 and 8.88 respectively, which discloses the elements of the service on which customers really stress. They deserve management’s attention. When considering both MSA and MSS values together, Reliability (ranking as the ﬁrst) seems to be the greatest advantage contributing to the service quality and Tangibles (ranking as the last) needs some improvements. The ﬁndings of satisfaction, MSA and MSS analyses together can provide some valuable information for the improvement of the service quality. Fig. 1 gives a visual inspection of the relative relationship among ‘‘perceived service,’’ ‘‘adequate service,’’ and ‘‘desired service.’’ The ﬁgure clearly indicates that the service level that customers perceived is mostly above the ‘‘at least acceptable’’ service level (i.e., the adequate service) but is mostly below what customers hope to receive (i.e., the desired service). This ﬁnding perhaps can offer important information to the company for marketing strategy and future business development. Multiattribute Attitude Measurement The Fishbein model (Ajzen & Fishbein, 1980) is well known to consumer researchers and can help measure restaurant customers’ attitudes toward the SERVQUAL’s ﬁve attributes. However, it is not necessary to adopt its complicated mathematical equation for the research; instead, the model is being modiﬁed using Solomon’s theory (2002) to ﬁt the need of the study. Statistical results after adopting the modiﬁed Fishbein model (Ajzen & Fishbein, 1980) for multiattribute attitude measurement are exhibited in Table 5. The score for multiattribute attitude measurement is calculated using the following equation (Solomon, 2002): XX Bijk X Ijk Aijk ¼ n n Where, A is the overall attitude toward the restaurant, B the strength of the belief that the restaurant has any particular attribute (i), i the SERVQUAL attribute of a restaurant, j the restaurant, k the customers of a restaurant,

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Multiattribute Attitude Measurement for Each Restaurant.

Restaurant

SERVQUAL Attributes Reliability Responsiveness Assurance Empathy Tangibles

Mean values of SERVQUAL attributes (b) for each restaurant attributes (I) 1 8.46 7.94 2 8.72 8.54 3 8.63 8.86 4 8.61 8.13 5 8.73 8.15 6 8.86 8.21 7 8.57 8.08 8 8.39 8.28 Importance of attributes (I) 0.21 0.19 Restaurant

Attribute score

Multiattribute attitude measurement 1 8.24 2 8.66 3 8.70 4 8.34 5 8.40 6 8.50 7 8.33 8 8.44 Total 67.60 Mean of attitude 8.45

and average importance of 8.47 8.64 9.06 8.67 8.77 8.96 8.55 8.85 0.20

8.08 8.89 8.45 8.17 8.15 8.26 8.18 8.33 0.19

8.21 8.52 8.53 8.12 8.15 8.16 8.24 8.32 0.21

Relative importance (%)

Ranking

12.19 12.81 12.88 12.34 12.42 12.57 12.32 12.48 100

8 2 1 6 5 3 7 4

I the customer evaluation of the goodness or badness of the attribute (i), n the total number of customers. As stated earlier, the second question included in the second part of the survey was to measure the importance of the ﬁve SERVQUAL attributes for a restaurant. By adopting Solomon’s equation above, a customer’s attitude toward a restaurant’s service was measured based on the sum of the products deriving by multiplying the mean values of SERVQUAL attributes and their respective mean value of importance. Statistical results as exhibited in Table 5 suggest that there are no great differences among the examined restaurants. Restaurant 3 has the highest total mean attitude (8.70) and Restaurant 1 has the lowest total mean attitude (8.24). The variance between these two restaurants is little. The relative importance

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presenting a very close 12% can also conﬁrm this interpretation. This ﬁnding suggests that customers of X Steakhouse hold a very close evaluation system to assess the services delivered in the same brand name restaurants and the same level of service quality might have been provided by the company across different restaurants in different locations. From the point of view of the SERVQUAL attributes, Restaurant 3 has achieved the highest score in the Assurance attribute (m ¼ 9.06), while Restaurant 1 shows the lowest score in the Responsiveness attribute (m ¼ 7.94). This lowest value in Restaurant 1 is also the lowest score among all examined restaurants suggesting that management in Restaurant 1 should re-evaluate the variables of the Responsiveness attribute, such as ‘‘quickly correct mistakes,’’ ‘‘employee anticipate guests’ needs,’’ ‘‘food served promptly,’’ ‘‘give supports to other employees,’’ and ‘‘frequency of stop-by and checking’’ to identify the source of this issue. Interestingly, the Responsiveness attribute is also ranked in last place with the lowest satisfaction score (0.44) in the previous analysis. This is a consistent result indicating the true concerns customers have. The company should conduct a thorough study on the stafﬁng and daily business operation to carry out any necessary improvements. Overall, although there is no great discrepancy in assessments across the eight restaurants, those restaurants with scores below the mean of attitude (8.45), Restaurant 1, 7, 4, and 5, might still want to inquire into the evaluation factors of each service attribute to understand what might be responsible for the low scores. Restaurant 3, the most desired and high quality restaurant compared to the rest, does not have a huge lead in this assessment and probably wants to look into its attributes of Empathy and Tangibles for improvements as well. From the table, the Tangibles apparently is one of the most important attributes but has the lowest values in MSA and MSS measurement. The company should not take this ﬁnding lightly. Another point worthy to mention is that the results presented in Table 5 suggest that the company has reached a standardized business operation and development for its X Steakhouse brand. This is strength to gain market shares quickly.

CONCLUSION Based on the results and discussions above, the measurement and evaluations of the service gaps are completed and the research objectives are achieved with multiple contributions. In other words, the researchers are

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able to (a) evaluate the service quality in X Steakhouse, (b) realize customers’ satisfaction levels of X Steakhouse, (c) understand customers’ attitudes toward SERVQUAL’s service attributes, (d) discover whether or not there is a big variance in service provided among the restaurants under the same brand name, (e) determine the strong and weak points for service improvements, and (f) generate managerial perspectives to help decision making for the examined restaurants and their parent company. As addressed by many researchers, service quality has an impact on a company’s proﬁts because it is directly related with a customer’s perception of services and satisfaction, and thereby developing customer retention and loyalty (Baker & Crompton, 2000; Zeihaml & Bitner, 2000). The ﬁndings of this empirical research can provide useful administrative suggestions for taking necessary actions to improve the service quality for chain restaurant business in order to face the growing competition in Taiwan’s restaurant industry. The research followed the well-recognized SERVQUAL model to measure service quality and adopts part of the Fishbein model for the multiattribute attitude measurement to achieve the research objectives. Although the research methodology is well designed and established, it is important to consider the limitations of the study. One limitation comes with the implementation of the SERVQUAL model. The evaluation factors/ statements are very conceptual and hard for the respondents to grasp the essentials of the questions quickly. This not only causes tremendous efforts in data collection but also creates many unusable questionnaires and reduces the response rate. A second limitation is that the examined objects are not from the same region of the country but two of them are from different parts of the nation. This might slightly distort the ﬁndings as customers in different areas tend to hold different value systems and dining habits. Although there is no big discrepancy across the study objects in the end, this should have been prevented. For future research, the use of a more comprehensive model is recommended and the gaps existing in the service providers should be studied as well. Another possible topic for future study would be to develop another comprehensive model that will work with an instrument like SERVQUAL to measure customers’ expectations directly.

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USING POPULATION PROJECTIONS TO IDENTIFY ASPECTS OF FUTURE TOURISM DEMAND Petra Glover and Bruce Prideaux ABSTRACT Identifying future tourism demand is a critical aspect for tourism decisionmakers to ensure the long-term success of products, services and destinations. This paper discusses how population change, an important driver of tourism demand, may impact future demand patterns. It discusses potential impacts of projected demographic change, especially those resulting from the related aspects of population ageing and changing family structures. A case study amongst Baby Boomers and Generation Y on the Gold Coast, Australia, illustrates how demand patterns may develop over the next 15 years. The study incorporates different population scenarios as projected by the Australian Bureau of Statistics and shows a great diversity of demand amongst both generations. It is suggested that scenarios be used to analyse potential impacts of other determinants to obtain a better understanding of future tourism demand, thus expanding the scope of traditional forecasting methods.

Advances in Hospitality and Leisure, Volume 4, 185–209 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00009-X

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INTRODUCTION Understanding future tourism demand is an important part of tourism management and planning. National tourism organisations such as Tourism Australia regularly publish updated forecasts for inbound, outbound and domestic tourism in Australia (Tourism Forecasting Committee, 2006a, 2006b, 2007). Traditional forecasting methods often examine short-term future developments based on quantitative results using methods such as univariate and multivariate analysis or time-series models (Frechtling, 2001; Makridakis, Wheelwright, & Hyndman, 1998). However, these methods have limitations particularly in the long term and are not usually able to predict crises or disasters that may severely disrupt tourism ﬂows (Prideaux et al., 2003). As a result, alternative forecasting methods, particularly for the medium and long term have found their way into the forecasting literature, including Delphi panels, scenarios, customer intention surveys, and analogies (Frechtling, 2001; Makridakis et al., 1998; Morrell, 2001). One of the major drivers of future demand is demographic change (Foot, 1996, 2004; McRae, 1996). Since demographic characteristics are often associated with speciﬁc aspects of tourism behaviour, they play an important part in understanding tourism demand. Similarly, as populations change over time, the demand for destinations, transport modes, and tourism activities also changes. However, the size and age composition of a country’s population cannot be predicted accurately because of uncertainty about future fertility rates, level of immigration and life expectancy (Australian Bureau of Statistics, 2003). To account for such uncertainties, the Australian Bureau of Statistics (ABS) issues population projections or scenarios that describe alternative potential demographic compositions of the future Australian population. The aim of this paper is to apply the ABS population scenarios in a tourism context to examine the possible implications of demographic change on future tourism demand using Gold Coast, Australia as a case study. Speciﬁcally, the paper reviews a range of impacts that may occur over time as a consequence of changes in the composition of two generations (Generation Y and Baby Boomers) in the Australian population. The paper combines existing research into the future composition of the Australian population undertaken by the ABS with ﬁeld work that collected data on the views of generation groups about their anticipated future travel demand patterns. While the paper deals speciﬁcally with demographic change, other external inﬂuences may also affect future tourism demand. These include

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economic factors, technological innovations and advancement, investment in tourism infrastructure, political and legislative developments, environmental planning and impact issues, trading development and safety concerns (French, Craig-Smith, & Collier, 2000; Goeldner & Ritchie, 2003; World Tourism Organization, 1995). In this paper, population change represents an example of how scenarios (in this paper developed by the ABS) may be used to create alternative views of the future that may inform the tourism industry and the government of the type and form of adaptations that may be needed in the development of tourism products, destinations and policies.

THE VALUE OF SCENARIOS FOR TOURISM PLANNING While scenarios have been employed successfully in the past for strategic planning purposes by organisations such as Royal Dutch/Shell, the Electrolux Group, British Airways, Motorola, Queensland Main Roads and Queensland Transport and the European Union (Bertrand, Michalski, & Pench, 1999; Department for Transport & Department of Main Roads, 1999; Schwartz, 1998; van der Heijden, 1996), their use in a tourism context is limited. Altinay, Altinay, and Bicak (2002) examined the development of the tourism industry in Cyprus using two political scenarios, the realisation of which depends on a governmental decision regarding economic integration of North Cyprus with Turkey or federation with South Cyprus. More recently, Yeoman, Galt, and McMahon-Beattie (2005) examined how the war in Iraq may affect tourism ﬂows to Scotland. The major difference between traditional forecasting methods and scenarios lies in the underlying assumptions about the predictability of the future. While traditional forecasting methods aim to predict the future by extrapolating past trends while factoring in some allowance for changes in key variables, scenario planning assumes that the future cannot be accurately predicted. Rather, scenarios speciﬁcally address the uncertainties that are inherent in the future (Ringland, 1998; van der Heijden, 1996) to produce a number of possible futures. The major source of uncertainty about the future stems from the range of potential paths that the future may take (Tydeman, 1987). The problem encountered by traditional forecasting lies in the accuracy of the forecast point (Ringland, 1998) since, as Wack (1985, p. 73) noted, ‘‘No single ‘right’

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projection can be deduced from the past.’’ Further, some future developments may be considered to be more likely or more desirable than others (Lindgren & Bandhold, 2003). Consciously or unconsciously, decisionmakers may be tempted to take into account only the future developments that they deem preferable or probable in order to limit the number of potential factors to be taken into consideration (Lindgren & Bandhold, 2003). Barbieri Masini (1983) recognised a dilemma between knowledge on the one hand, and desire and fear on the other, which may lead to investigating the impacts of a desired or an undesired future which may not be the most plausible. Scenario planning addresses the uncertainty of the future by considering a range of alternative futures. In essence, a set of scenarios represents alternative possible views of the future (van der Heijden, 1996) which explore what could happen by asking ‘‘What ify?’’ questions about a business’ operations in its changing environment. In this way, scenario planning can be described as a method of understanding the dynamics that shape the future. According to Porter (1985, p. 446), scenarios are ‘‘internally consistent view[s] of what the future might turn out to be.’’ They are neither right nor wrong but interpret what could happen in the future under the assumption of a certain set of factors. As a result, scenario planning adopts a broader view than forecasting by analysing the driving forces behind demand rather than only forecasting demand levels (van der Heijden, 1996). In addition to preparing an organisation for a range of possible futures, the development of scenarios can help achieve competitive advantage because they allow the organisation to understand a whole window of opportunities (Hamel & Prahalad, 1996; MacKay & McKiernan, 2004 after Shoemaker, 1992). One of the major challenges of scenario planning is that deﬁnite answers to a problem are not readily apparent. The qualitative images and intuitive patterns of future development are often very different to the types of information that decision-makers are conversant with (Lindgren & Bandhold, 2003; van der Heijden, 1996). Construction of scenarios can also be very time consuming, and as a consequence top-level managers tend not to become involved (Lindgren & Bandhold, 2003). Finally, scenario planning must not be regarded as a panacea for understanding future developments (MacKay & McKiernan, 2004). Where uncertainties become too prevalent, scenarios cease to be useful. Despite these drawbacks, scenario planning is according to O’Brien (2004, p. 710) ‘‘y an established method for describing and assessing the impact of future uncertainty on an organisation.’’

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Scenario planning may facilitate a proactive approach to both adapting to the changing business environment as well as shaping it (Tydeman, 1987). The process can be used to support: prediction/forecasting the future by identifying and estimating the value of the variables of interest relevant to a decision-making group. exploring/describing the future by developing an understanding of the context, complex interactions and relationships between relevant variables and their changes over time. planning/anticipation of plausible futures by gaining insights into likely implications of change to enable the organisation to take appropriate action. engineering change/prescribing the best or at least a better future by determining the characteristics of desirable futures and ways of achieving them. The ABS has adopted the position that its population projections ‘‘are not intended as predictions or forecasts, but as illustrations of growth and change in the population which would occur if certain assumptions (y) were to prevail over the projected period’’ (Australian Bureau of Statistics, 2003, p. 1). The ABS population projections illustrate that depending on the assumptions made, outcomes can vary widely.

DEMOGRAPHIC CHANGE AS A DETERMINANT OF TOURISM DEMAND As discussed previously, a range of interrelated external factors as well as changes within these factors impact future tourism demand. This expectation is reinforced by a framework developed by Martin and Mason (1998) who suggest that economic change, new technology and social change inﬂuence the demand for leisure activities. The same should be expected to apply to tourism demand given that many authors (Bourguignon, 2004; Godbey, 2003; Kelly, 1988; Kelly & Godbey, 1992; Leiper, 1990; Veal & Lynch, 2001) consider tourism to be a special form of leisure. As the interrelated impacts of demographic change modify the character of a society (Morrell, 2001), market shifts caused by change force suppliers to adapt tourism products, services and destinations so that their characteristics and features match the changing demand.

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A number of research studies have examined the impact of demographic variables on tourism demand including spending patterns (Jefferson, 1991), choice of destination (Mohsin & Ryan, 2004), use of commercial accommodation (Peterson & Lambert, 2003) and distance travelled (Reece, 2004). According to Foot (1996), demography is the most powerful, yet most neglected, tool available to understand the past, anticipate the future and assist business decision-making and strategy formulation. Demographic trends represent a powerful underlying force that shapes market development (Aaker, 2005). Similarly, McRae (1995) suggests that demographic change is likely to be an important force of change and thus needs to be recognised by the tourism industry. Although demographic changes are unlikely to have an immediate effect on a company’s ﬁnancial results, they may become critical in the medium to long term (Foot, 1996). The impact of population changes may be easily overlooked because changes of this nature are relatively slow and gradual (OECD, 1979). Nevertheless, if they are not acknowledged, remedial action may be too late, resulting in substantial economic and social costs. Demographic characteristics such as age, income, family size and employment status objectively describe consumers and have an important inﬂuence on the design of the optimal marketing mix (Assael, 1998), which includes product characteristics, pricing decisions, selection of distribution channels and advertising activities (Kotler, Armstrong, Brown, & Adam, 1998). This implies that decisions regarding these four major elements of the marketing mix are consumer-driven, and the analysis of consumer needs precedes the design of marketing strategies including product development. Corporate marketing plans need to factor in demographic changes when deciding on product designs, sales prices, distribution channels and advertising campaigns. As a consequence, demographically driven market shifts have important implications for marketing strategies and business operations (Assael, 1998; Foot, 1996; Salt, 2001). Where tourism destinations fail to recognise changing demand patterns, their attractiveness can be expected to decline leading to a reduction in the number of visitors. For example, the Isle of Man, a prosperous and rapidly expanding tourism destination at the end of the 19th century, failed to monitor changing demand trends or to invest in tourism facilities during the 20th century. Failure by many of the Island’s hotels to update their rooms resulted in a decline in visitors who switched to newer and more modern destinations such as Spain (Cooper & Jackson, 1989). A similar trend became apparent in Spain at the beginning of the 1990s when after years of growth many Spanish coastal resorts experienced a signiﬁcant decrease in

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international tourist numbers. The 1970s style of large budget-priced multistorey hotels that had underpinned growth had become outdated and were no longer competitive (Morgan, 1991). In both examples, the destinations had failed to recognise that tourists’ preferences and expectations had changed. The failure to anticipate demand changes of this nature may result in the emergence of a product gap where the existing supply structure does not match changes in consumer demand (Glover & Prideaux, forthcoming), resulting in loss of tourists to other more attractive destinations. Norfolk Island (Prideaux, Crosswell, & Ng, 2002) is one documented example of a destination currently facing a product gap. In the Australian context, four major demographic changes are likely to occur in the mid-term future: population ageing; population growth; domestic migration and international immigration; and changes in family structures (Australian Bureau of Statistics, 1999; DIMIA, 2004; DLGP, 2001). These projected changes demonstrate the importance of recognising the impact that demographic factors exert on tourism demand, particularly in the longer term. In commenting on these trends, Foot (1996, p. 7) noted: ‘‘y when it comes to predicting behaviour, the most useful demographic variable is the age composition of the population. (y) If you know how many people of each age are around today, you can make a reliable forecast about how those same people will behave tomorrow.’’

ABS POPULATION PROJECTIONS FOR AUSTRALIA The most recent population projections were issued by the ABS in 2003 and outlined three projection series: high (Series A), medium (Series B) and low (Series C). These projections reﬂect the various assumptions summarised in Table 1, including fertility and immigration rates, as well as life expectancy (Australian Bureau of Statistics, 2003). Based on Australia’s current fertility rate of 1.77 (Australian Bureau of Statistics, 2007), the size of the Australian population is projected to increase from 19.6 million in 2002 to 24.5 million in 2020 (Series A), 23.4 million under Series B and 22.3 million under Series C. By 2051, the projections indicate that the size of the population might range from 31.4 million (Series A) to 23.0 million (Series C). The difﬁculty of projecting the population size lies in uncertainties regarding younger generations’ future attitudes towards family and future government policy, which may inﬂuence both family values and immigration patterns. While the size of younger and coming generations is difﬁcult to project because it depends largely on their

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Table 1. ABS Assumptions for Population Projections.

Total fertility rate (babies per woman)a Net overseas migration (persons per year)b Life expectancy at birthc Male (years) Female (years)

Series A

Series B

Series C

1.8 125,000

1.6 100,000

1.4 70,000

92.2 95.0

84.2 87.7

84.2 87.7

Source: Based on data extracted from Australian Bureau of Statistics (2003, p.1). a From 2011. b From 2005/06. c From 2050/51.

willingness to have children and at what age they will have them (Hugo, 2003), the size of the older population is relatively easy to project because the members of this generation are already alive today. Further, immigration policy is an external factor that also inﬂuences the size of the population. As shown in Table 1, the population projections are based on the assumption that net overseas migration will add between 70,000 and 125,000 persons annually to the Australian population. In addition to overseas migration, interstate migration is expected to change the population distribution (Australian Bureau of Statistics, 2003). The median age of the Australian population is expected to increase from 35.9 years in 2002 to between 40.4 and 42.3 years in 2021 and to rise further between 46 and 49.9 years in 2051. This rise in the median age is reﬂected by a declining proportion of children (under 15 years) and a growing proportion of older people, aged 65 and over. While the proportion of children was larger than the proportion of people aged 65 years and over in 2002, it is expected to be smaller in all projection series in both 2021 and 2051. Considering the current retirement age of 65 years, the proportion of the working population (15–64 years) is expected to decrease to varying extents under all projection series (Australian Bureau of Statistics, 2003). In real terms, the number of children is expected to increase slightly only under projection Series A, but to decline by up to 800,000 in 2021 and 1.2 million by 2051 under Series C. At the same time, the number of people aged 65 and over is expected to increase under all projection series. By 2021, it is expected to grow by 1.9–2 million people, and by 2051 their number is expected to increase at least two and a half times to between 4.3 and 6.4 million people (Australian Bureau of Statistics, 2003). Table 2 provides the

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Table 2. Current and Projected Characteristics of the Australian Population. 2002

Population size (million) Median age (years) Proportion aged 0–14 (%) Proportion aged 15–64 (%) Proportion aged 65+ (%) Population aged 0–14 (million) Population aged 15–64 (million) Population aged 65+ (million)

2021

2051

Estimate

A

B

C

A

B

C

19.6 35.9 20.3 67.0 12.7 4.0 13.1 2.5

24.5 40.4 17.6 63.8 18.6 4.3 15.6 4.6

23.4 41.2 16.1 64.9 19.0 3.8 15.2 4.4

22.3 42.3 14.4 65.8 19.8 3.2 14.7 4.4

31.4 46.0 15.2 56.5 28.3 4.8 17.7 8.9

26.4 46.8 14.0 58.9 27.1 3.7 15.5 7.2

23.0 49.9 12.0 58.3 29.7 2.8 13.4 6.8

Source: Based on data extracted from Australian Bureau of Statistics (2003, pp. 79–82, 84).

details about all the three projection series for 2021 and 2051, while Fig. 1 shows the age structure of the Australian population expected in 2021. Finally, household structures are also expected to change with a projected decline of the average household size from 2.6 to between 2.2 and 2.3 persons (Australian Bureau of Statistics, 1999). Since the 1970s and 1980s, the Baby Boomers family unit of a couple with children has declined while the number of childless parents and one-parent families has increased. This trend appears likely to continue in the future and will lead to a greater diversity of family structures amongst Generation Y. While couples with children represented 60% of all family units in 1976 and 56% in 1986 (Australian Bureau of Statistics, 1999, 2002) when the Baby Boomers raised their children, their proportion is expected to drop to between 31% and 44% by 2021 (Australian Bureau of Statistics, 1999). While couples without children represented 28% of families in 1976 and 30% in 1986, they are expected to grow to between 39 and 47%. Over the same period, one-parent families are expected to increase from 7 (1976) and 8% (1986) to between 14 and 20%.

IMPLICATIONS OF POPULATION PROJECTIONS FOR FUTURE TOURISM DEMAND The three population projections show an obvious change in the age structure of the Australian population. Under all the three projection series, the proportion of older people is expected to increase signiﬁcantly while the

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male female

Projection Series A male female

Projection Series B male female

Projection Series C

Fig. 1.

Projected Age Pyramids for Australia in 2021. Source: Based on data extracted from Australian Bureau of Statistics (2003, pp. 80–82).

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proportion of children will decline. This phenomenon is referred to as population ageing (Alvarado & Creedy, 1998). As a result, tourism preferences and expectations of the older age group will become more predominant in the population in the future than they are today. Despite the assumption that older people today are ﬁtter and healthier than they used to be (Patterson, 2002), tourism activities undertaken by the older travellers are different from those preferred by younger travellers. In general, older travellers are less adventurous, more risk-averse, and more in favour of quiet and relaxing holidays. Further, when compared to younger travellers and despite increasing levels of health and ﬁtness, older people are generally more prone to physical disabilities, injury, illnesses and ailments than younger people. Some differences regarding the current tourism demand characteristics amongst Australians will be presented later. By 2021, the number of people over 65 years of age in Australia is projected to increase by at least 75%. Consequently, a signiﬁcant effect on the level of tourism demand displayed by this age group can be expected. The three projection series show little variance regarding the number of people in this age group. Therefore, the differences that can be expected for tourism demand from this age group are likely to be small. However, by 2051, the difference between the three population projections will be noticeable. One impact is likely to be evident on the size of the working population because the larger the proportion of older people, the more likely an increase in retirement age. A policy of this nature has already been discussed by the Australian government as a means of reducing the ﬁnancial strains on social security, healthcare and retirement funds and to maintain current productivity levels (Commonwealth of Australia, 2002; Productivity Commission, 2005). Thus, the level of population ageing is likely to have an impact on the time and ﬁnancial resources that the older population has at its disposal for tourism activities. Consequently, an increase to 8.9 million Australians at the age of 65 and over by 2051 under Series A could mean that a smaller proportion of this population will be able to travel than under Series C with 6.8 million people. However, the actual number of travellers may be identical. While it is very likely that the number of travellers over the age of 65 will increase signiﬁcantly in the future, destinations need to prepare for a change in the types of products and services demanded by this age group. Prideaux et al. (2002) found, for example, that in the case of Norfolk Island there was a danger that tourism demand would fall because of the focus of the island’s tourism industry on the current generation of seniors (pre-war generation) while the next generation of seniors (Baby Boomers) were largely ignored.

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Research has found that the social, political and economic conditions that are prevalent in the formative years of each generation will have an impact on individual and generational attitudes and beliefs later in life (Eyerman & Turner, 1998; Meredith & Schewe, 1994; Strauss & Howe, 1991). As a result, preferences for tourism activities can be expected to be inﬂuenced by generational membership. One outcome is that future generations of seniors (i.e. Generation Y) will have different expectations when compared to the current cohort of seniors who include a declining number of the pre-war generation and an increasing number of Baby Boomers. Another signiﬁcant impact on tourism demand may result from the number and proportion of children under the age of 15 years. Series A predicts slightly more children in Australia by 2021 while Series B and C indicate that the number of children will decline. Under the assumption that travel propensity remains unchanged, there may be either a need to increase the number of child-friendly tourism products and services (Series A) or reduce investment in child-friendly tourism products (Series B and C). In addition to the total number of children, the development of family structures has a role to play. It may be possible that an increase in the number of single parents will lead to a higher number of parents who are not able to afford the time or money to holiday with their children, leading to decline in demand even though total numbers have increased. Other impacts may also be expected. Rather than having one family holiday with both parents each year, children of separated parents may go on two holidays, one with each parent. In this case, the demand for childfriendly products and services could increase despite a decline in the total number of children. At the same time, the expected increase in childless couples could signiﬁcantly reduce the demand for holiday accommodation with two or more bedrooms. Similarly, the dependence on school holidays may fall shifting tourism demand to the less popular low season, thus reducing seasonal ﬂuctuations. Under the assumption that childless couples have a higher disposable income than couples with children, tourism expenditure amongst people of childbearing age may increase. For example, while a family with children may opt for a drive holiday, a couple without children may be able to afford to ﬂy to a more distant destination. Thus, the extent to which Australians refrain from having children will have varying impacts on the possible changes to aggregate tourism demand. While travel opportunities may change with family composition, the working population’s ability to travel may also depend on population change. It has been mentioned before that retirement age may be lifted as a result of population ageing. The extent to which Australians over the age of

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65 are retained either in a full-time or part-time capacity in the workforce may have an inﬂuence on the capacity to take holidays. A possible decline in the labour force may result in employees not being allowed to take time off work for fear of reduced productivity and insufﬁcient output. Under the three projection series, the proportion of the people of working age (15–64) will decline to varying levels. This will lead to a deﬁciency in the number of employees available for work in tourism and related industries. Considering that young Australians spend an increasingly long time in education, the actual size of the working population can be expected to be even smaller.

GOLD COAST CASE STUDY To develop a more detailed knowledge of how changes in demand are affected by demographic change, a survey was undertaken on the Gold Coast, Australia to identify possible future trends in tourism demand based on generation membership. The results of this survey are considered in parallel with the population scenarios developed by the ABS and will give the tourism industry some idea of how the future composition of the workforce will impact tourism demand. The Gold Coast is a major Australian coastal holiday destination with 3.6 million (81%) domestic and 830,000 international (19%) tourists in 2006 (International Visitor Survey, 2006; National Visitor Survey, 2006) and was selected because of its cosmopolitan nature and its ability to attract a wide range of age groups.

TOURISM DEMAND IN AUSTRALIA AND ON THE GOLD COAST Statistics on recent tourism demand characteristics conﬁrm that tourism preferences differ between members of different age groups. This is demonstrated by a selection of tourism characteristics obtained from the National Visitor Survey (2005). The comparison is drawn between two age brackets 20–29 and 40–59 because they roughly represent the older members of Generation Y, and the Baby Boomers, the two generations discussed in the case study. A total of 72,846 domestic overnight trips were taken in Australia during the year 2005 (National Visitor Survey, 2005). New South Wales was the most visited state, followed by Victoria and Queensland. Although the

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proportion of visits to each state was very similar for the three age groups, differences emerged for individual regions within each state. For example, in Queensland the most visited region was Brisbane (25% of all overnight trips to Queensland), followed by the Gold Coast (20%) and the Sunshine Coast (16%). While this pattern is reﬂected by the 40–59 year age group, the favourite destination for the younger group (20–29 year olds) was the Gold Coast, followed by Brisbane and the Sunshine Coast. Furthermore, Harvey Bay was more popular amongst the 40–59 year olds, than amongst the younger age group. The one destination holiday is, by far, the most common with 89% of all overnight trips made to only one destination. However, the proportion of one-destination holidays was higher amongst 20–29 year olds (91%) than amongst 40–59 year olds (88%). This is also reﬂected in the length of stay. While holidays of 1–3 nights were the most common, a larger proportion of 20–29 year olds (74%) undertook such short holidays than 40–59 year olds (70%). At the same time, the older age group was more likely to engage in holidays of 8–14 nights’ duration (7% compared with 5%). Differences are also evident in the choice of accommodation and activities. The most popular form of accommodation for 40–59 year olds was hotels, resorts and motels. Approximately 40% of all trips taken by this group used such facilities. In contrast, only 29% of 20–29 year olds stayed in such accommodation, while the majority of their trips (51%) included staying with friends and relatives. This type of accommodation was used for 36% of all trips amongst 40–59 year olds. Outdoor and nature activities were most popular amongst both age groups, followed by sports and other active outdoor activities. It is evident that Baby Boomers were slightly less likely to engage in such outdoor and nature activities (21%) compared with the 20–29 year olds (23%). In contrast, activities relating to arts, heritage and festivals were more popular amongst 40–59 year olds (15%) than 20–29 year olds (11%). Differences are also evident regarding individual activities. The younger age group was more likely to visit family and friends on their overnight trip (53%), which reﬂects the preference for staying with friends and relatives. Amongst the 40–59 year olds, approximately 45% of overnight trips included visiting friends and relatives. A comparison with the same age brackets in the year 2000 indicates that some changes have occurred and demonstrates the inﬂuence that the members of the two generations have exerted on tourism patterns as they have moved into the respective age brackets. Over the time period between 2000 and 2005, the 40–59 year age group has become more interested in outdoor activities. While 33% of the domestic overnight trips amongst this age group included

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outdoor or nature activities in 2000, this had increased to 37% by 2005. During the same period, amongst 20–29 year olds participation in sports and outdoor activities fell from 29 to 23%. Similarly, on the Gold Coast, sports and other active outdoor activities became less popular (from 22 to 19%) amongst 20–29 year olds. However, their participation in outdoor and nature activities increased from 55 to 63% between 2000 and 2005. Signiﬁcant changes have also occurred regarding the length of stay. In 2000, 40% of overnight trips to the Gold Coast taken amongst 20–29 year old were only one night long but then fell to 34% by 2005. Over the same period, this age group took two and three night trips more, which increased from 18 to 21% and from 11 to 14%, respectively. In contrast, the 40–59 year olds’ proportion of stays of one night remained relatively stable while they took more three night trips (11–13%).

METHODOLOGY The aim of this research is to examine ‘‘anticipated’’ demand for leisure travel in 2020 using the Gold Coast as a case study. Two generation groups were selected for this study. Baby Boomers who have mostly ﬁnished having their family are anticipated to have a relatively clear view of their future travel expectations. Members of Generation Y, on the other hand, are starting families and will be less certain on how this will impact their future travel expectations. A self-administered survey was conducted between December 2005 and January 2006 to identify the type of holidays that tourists expect to undertake in the future. The survey questionnaire asked individual tourists about their expectations for their personal life situation in the year 2020 and for their anticipated tourism activities and preferences. The ﬁrst part of the survey included questions about respondents’ expectations of time and ﬁnancial resources that they will have available in the future, their family situation and place of residence. In the second part of the survey instrument, respondents provided their opinion regarding statements about their personal tourism demand in the future. The statements were derived from a Delphi study and a series of focus group interviews that had been conducted earlier. A Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) was used because this method has been acknowledged as an effective method of measuring respondents’ opinion (Nardi, 2003). An additional group of questions asked for demographic data including the year of birth, gender, current family composition and place of residence.

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The year of birth was split into generation categories to enable differentiation between Baby Boomers, Generation X and Generation Y. In this research, only Baby Boomers and Generation Y were tested to identify potential tourism demand in the future. Baby Boomers were born between 1946 and 1965 (Australian Bureau of Statistics, 2004), while Generation Y were born between 1978 and 1987 (Marconi, 2001; Tulgan, 2000), although some researchers have extended the years for Generation Y to as late as 1994 (Edmondson, 1995), 1997 (Hicks & Hicks, 1999; Tapscott, 1998) or 1998 (Tulgan, 1996). Only those members of at least 18 years of age were included in this study. Convenience sampling resulted in 273 usable responses, while eight responses had to be discarded because not all questions were answered. Prior to administration, the survey instrument was piloted and some minor amendments made. Surveys were distributed once potential respondents had agreed to participate giving a response rate of 100%. Few people rejected participation but no records were kept on the number of rejections. Prior to presenting the survey results and discussion, their signiﬁcance with regards to demographic change, selected tourism characteristics amongst Generation Y and the Baby Boomers are outlined.

FINDINGS AND DISCUSSION The survey results indicate that population ageing and the related changes in age composition and family structures may have a signiﬁcant impact on future patterns of tourism demand in Australia. Of the 273 respondents who participated in the study, 48% belonged to Generation Y and 52% were Baby Boomers. Forty-ﬁve percent of respondents were male and 56% were female. Totals do not add up to 100%, some answers were missing. Generation Y displayed a relatively even split between male and female respondents, while more of the Baby Boomer respondents were female than male. The split between single respondents (48.4%) and those in couple relationships (50.5%) was almost even. However, as Fig. 2 shows, there was a distinct difference between the two generations. Approximately three in four members of Generation Y were single while the reverse was true of the Baby Boomers with approximately 75% being in a couple relationship. About 46% respondents had children. As can be expected from the age brackets to which each generation belongs, the majority of Generation Y (93.9%) was childless, while the majority of Baby Boomers (83%) had children (see Fig. 3).

Using Population Projections to Identify Aspects of Future Tourism Demand 80% 72.7%

73.0%

Gen Y BB

70%

201

60% 50% 40% 25.5%

30%

26.5%

20% 10% 0%

couple

single

Fig. 2.

Proportion of Singles and Couples.

100%

93.9%

90%

83.0%

80%

Gen Y BB

70% 60% 50% 40% 30% 15.6%

20% 10%

3.8%

0% children

Fig. 3.

no children

Proportion of Respondents with Children.

Future Expectations Respondents were asked to respond to a series of statements that included general life expectations and expectations about their travel behaviour in the year 2020. The results are summarised in Fig. 4.

202

PETRA GLOVER AND BRUCE PRIDEAUX have more money (BB) have more money (Gen Y) have more time (BB) have more time (GenY) have dependent children (BB) have dependent children (GenY) take more short breaks (BB) take more short breaks (Gen Y) take longer holidays (BB) take longer holidays (GenY) take more holidays overseas (BB) take more holidays overseas (Gen Y) take more holidays in Australia (BB) take more holidays in Australia (Gen Y) travel more frequently (BB) travel more frequently (Gen Y) price will be more important (BB) price will be more important (Gen Y)

mainly visit placesnot previously visited (BB) mainly visit places not previously visited (Gen Y) travel mainly outside school holidays (BB) travel mainly outside school holidays (Gen Y) stayin one place (BB) stay in one place (Gen Y)

0% strongly disagree disagree

Fig. 4.

20%

40% agree neutral

60%

80%

100%

strongly agree missing

Respondents’ Expectations.

As previously mentioned, population ageing has two major implications for future tourism demand: (1) The growing proportion of the older population including Baby Boomers will result in their demand patterns becoming more prevalent.

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The size of the older population is relatively easy to project over the next 15 years. (2) The smaller proportion of children implies smaller families and fewer families with children, which affects the demand of the younger generations, including Generation Y. The number of children and future family compositions are more uncertain and thus more difﬁcult to project because they depend on the younger generations’ family values. The survey results showed that Baby Boomers expected to have more time and money available for travelling, and 75% of Baby Boomer respondents expected to travel more frequently in 2020. Only 5% felt that they would have less time to travel. Baby Boomers are likely to continue having a strong interest in short breaks with approximately 59% of Baby Boomer respondents believing that they would take more short breaks. Longer stays are also likely to increase with 70% expecting to take longer holidays. Although there is a preference for domestic holidays, international destinations are also popular. Eighty percent of Baby Boomers expected to travel in Australia more often, while 60% thought they would travel overseas more often. This is coupled with a signiﬁcant interest in exploring new destinations, demonstrated by 86% of Baby Boomers expecting to mainly visit destinations that they had not visited before. The interest in touring holidays and one-destination holidays was relatively balanced. Of them, 37% did not expect to stay in only one destination while 36% believed that this would be the case. Despite the general expectation of having more money available for travel, just over half of the Baby Boomers believed that price would become a more important factor in their decision-making. With regards to the timing of their holidays, 72% expected to travel mainly outside of school holidays. These results conﬁrm the widespread expectation that Baby Boomers will be travelling in large numbers, and that the travel market for this group is likely to expand. It also shows some diversity in the market with strong interests in both domestic and international destinations, as well as short breaks and longer holidays. It may also be expected that once retired, Baby Boomers will travel at any time of the year, avoiding the traditional school holidays’ peak seasons. This may reﬂect price consciousness and an effort to avoid peak crowds. One emerging problem that will have begun to impact in 2020 is the fall in the ratio of 15–64 year olds (the group who provide the nation’s workforce) to retired people in the 65+ age group. The ratio will decline from 1:5.24 in 2002 to 1:3.39 (Series A) or 1:3.34 (Series C) by 2021, creating severe labour shortages that will have an impact on tourism.

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While population ageing directly affects tourism demand in Australia as a result of the size of the Baby Boomer generation, the impacts on Generation Y are less direct. Many of the impacts depend signiﬁcantly on Generation Y’s future family structures and their willingness to start families. As discussed above, this uncertainty was incorporated in the ABS projections through three different assumptions on fertility rates, and it is reﬂected in the survey results. Although the majority (58%) of Generation Y respondents expected to have dependent children by the year 2020, 21% were undecided, and a further 21% disagreed. This conﬁrms that a variety of family structures are likely to emerge which have their own implications for future tourism demand. The range of family structures is somewhat reﬂected in the expectations for travelling mainly outside school holidays. Forty percent of Generation Y respondents believed that this would be the case, while 22% disagreed and a signiﬁcant proportion (37%) was undecided. Greater diversity in travel patterns is also reﬂected in the expectations for longer holidays and short breaks. Sixty percent of Generation Y showed a strong interest in more short breaks and 57% believed that they would take longer holidays although there is already a large proportion of Generation Y taking holidays of more than 2 weeks’ duration. It is likely that couples with children will continue to take the traditional 1–2 week summer holidays while childless couples may be more prone to taking frequent short breaks. It is interesting to note that both Baby Boomers and Generation Y display very similar expectations for short breaks. Both generations also expressed similar expectations regarding touring holidays. While 40% of Generation Y disagreed that they would mainly stay in one place, 31% agreed and 29% were undecided. Again, the relatively even split of answers may be attributed to different family types since couples with children may ﬁnd it easier to remain in one place while childless couples are more likely to tour. Members of Generation Y expect to travel both in Australia and overseas. Seventy-three percent of Generation Y respondents showed an interest in international holidays, and 68% expected to travel domestically more often. Although both generations expect to travel to domestic as well as overseas destinations more frequently, the reason for Generation Y’s stronger desire to travel overseas may be related to their travel experiences at a young age. However, it is possible that considerations of cost and practicality will play a signiﬁcant role for future Generation Y parents and childless couples in choosing domestic over international destinations. Like the Baby Boomers, the vast majority of Generation Y (87%) expects to mainly visit destinations that they have not previously visited.

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This case study shows that population ageing may have a signiﬁcant impact on travel patterns due to two developments. First, the size of the Baby Boomer generation and their keen interest in travel is likely to increase the overall size of the travel market in the future as Baby Boomers retire. Their desire for both domestic and overseas holidays and for both short breaks and long stays is likely to increase the diversity of the future senior travel market. At the same time, the projected change of family structures amongst Generation Y, which is partly due to lower fertility rates, will add to the diversity of the travel market. Australian and overseas destinations, short breaks and longer holidays as well as travel during and outside of school holidays creates a range of travel patterns. Destination planners need to respond to such diversity by creating appropriate product and service offers and improving their unique selling proposition to beneﬁt from speciﬁc market segments. However, the interest of both generations in exploring new destinations suggests that it may become increasingly difﬁcult for destination planners to encourage repeat visitation and to build loyal relationships across all generations.

CONCLUSION This paper illustrates how demographic change, although slow, is an important driver of future tourism demand. The marketing orientation paradigm suggests that potential impacts of demographic change should be considered in the planning processes to ensure that future products and destinations meet future consumers’ demands. Despite the slow rate of change, which implies that changes in the population structure are more relevant in the medium to long term than in the short term, such changes are worthwhile considering given the time-frames involved in returning a proﬁt on infrastructure investments. ABS population projection scenarios highlight the difﬁculty of this task, given the uncertainties involved in projecting future population structures. The use of scenarios, representing alternative views of the future on the basis of different assumptions about key drivers, combined with consumer surveys of anticipated future demand patterns is suggested as a methodology that can assist in estimating the potential impact of demographic change on future tourism demand. The ABS population projections represent a set of three scenarios of the future population and may thus form the basis on which tourism demand scenarios can be developed. An ageing population over the next 15 years and beyond implies that the older population’s

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tourism demand characteristics become more important for planners. Baby Boomers’ likely future demand patterns require particular attention because they will become the next generation of seniors. Nevertheless, the extent of population ageing is uncertain since it depends on future fertility rates, which are largely inﬂuenced by the younger generations. The way in which fertility rates develop in the future has an even greater impact on the younger generations’ tourism demand since they are closely connected with the development of family structures. The future distribution of couples with children, childless couples, single parents and singles will affect tourism demand amongst younger generations, especially Generation Y. To assist tourism decision-makers in their planning processes, scenarios should be used to help understand the driving forces behind future demand and the different paths that they may take. The extent and coverage of tourism forecasting can thus be enhanced by incorporating uncertainties into the planning process. It will also contribute to understanding qualitative aspects of future demand, thus providing more depth to existing forecasting methods. In addition to understanding future tourism arrivals at a destination derived from traditional forecasting methods, scenarios will provide a picture of the changing patterns of tourism demand that may be expected. To achieve a more complete understanding of future tourism demand, scenarios should be used to analyse the potential impacts of other determinants on tourism demand. The combination of these scenarios will assist in understanding the driving forces behind and their potential range of impacts on future tourism demand. This will be a valuable contribution to assisting tourism providers in planning for and developing the products, services and destination that future tourists are likely to demand.

ACKNOWLEDGEMENTS This research is an outcome of a project funded by the Sustainable Tourism Cooperative Research Centre, established by the Australian Commonwealth Government.

REFERENCES Aaker, D. A. (2005). Strategic market management (7th ed.). Hoboken, NJ: Wiley. Altinay, L., Altinay, M., & Bicak, H. A. (2002). Political scenarios: The future of the North Cyprus tourism industry. International Journal of Contemporary Hospitality Management, 14(4), 176–182.

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WHAT TYPE OF OUTSOURCING RELATIONSHIP SHOULD HOTELS MAINTAIN? A MODEL BASED ON INTERNAL AND RELATIONAL STRATEGIC VALUE Toma´s F. Espino-Rodrı´ guez and Manuel Rodrı´ guez-Dı´ az ABSTRACT Outsourcing is an important phenomenon in hotel sector. It is changing from a tactical to a strategic perspective, with greater scope and relevance to the creation of competitive advantages. The opening up of hotels to outsourcing and strategic alliances improves individual competitiveness, but also has strong repercussions on destinations, especially those in a stage of maturity and requiring new approaches to improve competitiveness. This change in interorganizational relationships to a strategic perspective requires new theoretical and practical frameworks to make it easier for hotels to outsource their operations with greater potential for competitive advantage. This work proposes the types of relationship and degree of process integration required for relational capabilities to be achieved in the hotel sector when operations are outsourced. Finally, a series of conclusions are presented. Advances in Hospitality and Leisure, Volume 4, 213–227 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00010-6

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INTRODUCTION One of the main problems for companies in general, and for hotels in particular, is to establish a suitable strategy to develop fruitful long-term relationships with other companies in order to achieve their business objectives. Various works have examined the relationships between ﬁrms operating in the tourist sector without indicating what type of interorganizational relationship the hotel should maintain with the service companies depending on the type of operation (Evans, 2001, Lafferty & Van Fossen, 2001; Chathoth & Olsen, 2003). The linkages between organizations within a tourism destination context, particularly in the hotel context, become a critical factor in achieving strategic leverage (Pavlovich, 2003). Thus, the research question arises; what form do these linkages take to create a coherent network of service companies that the hotels can use? Moreover, the life cycle of tourism destinations determines conditions of great uncertainty and chaos, which obliges the companies and institutions involved to reconsider the destination’s strategic planning and the strategic relationships in order to re-launch destinations, increase the adaptability of organizations or enhance the ability to innovate (Russell & Faulkner, 2004). This aspect is of special importance when the hotel sector is on the verge of chaos and requires rejuvenation measures often requiring the development of innovative ideas, both to offer service quality and to reduce service production costs. As Selin and Chavez (1995) indicate, ‘‘crisis is often the catalyst for collective action through partnerships.’’ In those circumstances, hotels must modify their strategies in order to maintain a costs structure that distances them from maximum entropy or disappearance, by opening up to the outsourcing of operations by means of strategic alliances, joint-ventures, partnership relationships. This article proposes a model of strategic evaluation of relational capabilities in the outsourcing hotel operations in line with two key aspects involved with decision taking: the internal and the relational views that enable hotels to expand the outsourcing operations to third parties. The article deﬁnes the type of interorganizational relations that should be maintained when the hotel opts to outsource a hotel activity. The next section explains the theoretical perspectives underlying the design of the model. The model to evaluate outsourcing is then presented, followed by an application of the model in the hotel sector. The conclusions of the study are presented in the ﬁnal section.

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THEORETICAL PERSPECTIVES This section opens with a theoretical review from a microeconomic view of the resource and capability theory (Wernerfelt, 1984; Barney, 1991) and the relational theory (Dyer & Singh, 1998).

Internal View Addressing the outsourcing decision in a strategic way requires a deep understanding of the core competences, which form the basis for future competitive advantage (Bettis, Bradley, & Hamel, 1992). In order to understand the sources of sustainable competitive advantage, Barney (1991) establishes the hypothesis that a company’s resources can be heterogeneous and immobile. Competitive advantages stem from the ownership of valuable resources that permit companies to perform activities better, or at a lower cost, than their competitors (Collis & Montgomery, 1995). However, not every ﬁrm resource has the potential to be a source of sustainable competitive advantage. Barney (1991) states that, to have that potential, the resource must have the following four attributes: it must be (1) valuable (2) rare, (3) imperfectly imitable and (4) non-substitutable. Hotel ﬁrms should assess those four attributes, which would enable them to classify operations into three groups, namely, high, medium and low strategic value activities.

Relational View The relational view contributes a new dimension to the deﬁnition of ﬁrm strategies, since competitiveness increasingly depends on the networks the ﬁrms operate in, and on the level of cooperation between companies that maintain a relationship over time. In this context, the relationships between hotels and the service companies subcontracted to perform determined activities are a key element for the improvement of competitiveness, the social and economic development of destinations by means of strengthening the small and medium size companies that support the hotels (Kirsten & Rogerson, 2002) and the repositioning of mature tourism destinations in order to maintain the level of service offered, but at a lower cost. In this context, the creation and consolidation of relational capabilities take on special importance because ﬁrms operating in a network achieve competitive

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advantage not only through strengthening their internal capabilities, but also through the idiosyncratic relationships with services companies that lead to an associative competitive advantage (Rodrı´ guez-Dı´ az & EspinoRodrı´ guez, 2006). Lambert, Emmelhainz, and Gardner (1996) identify the different types of relationship that ﬁrms can maintain, based on the degree of process integration that they can achieve through cooperation (Lambert et al., 1996). Table 1 shows the different types of relationship that hotels and suppliers can maintain. To identify the type of partnership that the hotel has with its suppliers it is necessary to know the following aspects: orientation to the partnership (shortterm vs. long-term), strength of the relations (strong vs. weak), the level of involvement of the organizations (Knemeyer, Corsi, & Murphy, 2003). One important type of relations is the Type III relationship, which is the most common among ﬁrms that have achieved process integration to obtain competitive advantage and core relational capabilities (Zhao & Stank, 2003). Therefore, those activities are important and necessary, since they are used to protect the core competences and the ﬁrm can outsource them, but through determined closed contracts based on alliances or very close cooperation.

Table 1.

Types of Relationships and Characteristics.

Types of Relationship

Characteristics

Arm’s length

Multiple transactions between two parties over time, with no commitment agreements or joint operations. The organizations involved recognize each other as partners and, on the basis of a limited collaboration, coordinate activities and planning within a narrow perspective, applied to a functional area or a division in each organization. Involves a process that goes beyond coordinating activities, which are fully integrated. This relationship is maintained in the long-term and involves many divisions and functions in each of the participating organizations. The organizations are signiﬁcantly integrated and each party considers the other an extension of its own company, such partnerships generally not having any ‘‘end date.’’ Relationships between organizations deﬁned in speciﬁc agreements with regard to characteristics and period of duration. The maximum level of coordination and integration is attained as a consequence of a proprietary relationship between the parties. This case does not mean outsourcing of core activities.

Partnerships Type I

Partnerships Type II Partnerships Type III Joint ventures Vertical integration

Source: Adapted from Lambert et al. (1996).

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A MODEL OF EVALUATION OF OUTSOURCING This section begins by setting out the model of evaluation of the outsourcing strategy, and explaining the different parts and the strategic meaning of each of the boxes in the matrix. This will contribute to the analysis of the outsourcing strategy in a destination or sector over a determined period of time, to deﬁning the possibilities of improving competitive advantage and developing relational capabilities as well as to the planning of cooperation relationships with supply companies. Finally, there is an analysis of the principal diagonal in the hotel sector, giving actual examples of how it materializes in cooperation practices in the different activities that the empirical study places in the diagonal. The joint analysis of the internal and relational strategic value of activities provides useful information for the deﬁnition of the outsourcing strategy. Fig. 1 contains a double entry matrix, which refers to internal strategic value, on one hand, and to relational strategic value, on the other. The matrix comprises three different areas, the main diagonal, the area below the diagonal and the area above the diagonal.

Principal Diagonal This represents the balanced situation of a sector at a given moment of time regarding outsourcing or strategic alliances, and the section to which

Arm’s length Integration

Type II Type III

Strategic relational value of the activity

Type I

Relational / Internal

Low

Strategic value of activity Medium

C Activities not generating relational capabilities

Potential activities to plan the creation of relational capabilities

Potential relationships to generate relational capabilities

B Potential activities of relational capabilities

Relationships not exploited to develop relational capabilities

Fig. 1.

High potential to develop relational capabilities

High Activities generating relational capabilities but there are no suitable partners or adequate planning Activities generating relational capabilities but cooperation must be deepened A Activities generating relational capabilities

Model of Evaluation of Outsourcing.

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companies must move in order to deﬁne their outsourcing strategies. The diagonal has three boxes, A, B and C, where companies that outsource activities should position themselves in order to obtain relational capabilities, maintain long-term relationships with suppliers or simply perform speciﬁc transactions with third party service companies. A model of evaluation of outsourcing includes all the activities that have low strategic values and are easily substitutable and imitable and, therefore, the hotel should normally outsource them using a Type I or Arm’s length relationship, where there may not be speciﬁc investments or expectations of continuity of the relationship (Heide & John, 1990; Hoyt & Huq, 2000). The activities included in B have medium strategic values and, consequently, the hotel outsources them to service companies following a Type II relationship. Lastly, the activities in section A constitute the focal company’s core competence and the hotel should only outsource them if a highly qualiﬁed supplier is available (Espino-Rodrı´ guez & Padro´n-Robaina, 2005) and there is a possibility of developing a Type III relationship. Proposition 1. If the operations are located on the main diagonal, they are not exploiting all the advantages offered by outsourcing. Many competitors are located on this diagonal and relations will be very similar to those that competitors have with other suppliers. Therefore, it is more difficult to develop competitive advantages by means of outsourcing.

Section above the Diagonal This section represents the activities with a high potential to develop relational capabilities since ﬁrms attach medium–high strategic values to them, but no service company is available that meets the requirements of relationships with a medium – high level of integration of processes. These relationships are Type I or Type II. In this situation, ﬁrms have three alternatives: (1) retain the activities in-house, since they cannot ﬁnd service companies that guarantee the development of relational capabilities; (2) plan the creation of relational capabilities by developing close cooperation with service companies; and (3) outsource the activities in spite of the suppliers being unable to generate relational capabilities, and thus run the risk of reducing the internal strategic values and competitiveness and the quality of the service offered to end consumers. This section may also illustrate how to plan the future development of relational capabilities since ﬁrms can identify their wishes to improve their competitiveness by

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increasing the internal strategic value of determines activities with the aim of developing relational capabilities in one of the two following ways. Firstly, if the focal company does not outsource the activities, it ﬁnds a supply company that is willing to collaborate closely. Secondly, if it does outsource the activities, but no suitable companies are available, both companies must reorient themselves to more team work (Costa, 2003). However, if the providers are unwilling to increase cooperation they must be replaced by others with greater disposition and culture for inter-ﬁrm coordination and process integration, especially at a tactical level (Frohlich & Westbrook, 2001). In this context, managers can plan for the future by positioning the activities according to their desired strategic values. At that point, they will begin to plan the relationships that will lead to a movement of the activities along the diagonal. Proposition 2. The hotel activities with a medium or high strategic value must be the object of strategic planning in order to increase the strategic relational value and consequently the ability to influence competitive advantage.

Section Below the Diagonal This includes those activities where the probability of qualiﬁed service companies being available is high, and those companies are willing to consolidate long-term relationships with intensive integration of processes, that is, Type I and II relationships. In these cases, the service companies appropriate the rents because of their high level of efﬁciency and efﬁcacy, while the focal companies decide not to appropriate the rents for three possible reasons. The ﬁrst is that they have narrow mental models and are not open to new ways of increasing competitiveness by developing relational capabilities and by innovation in performing the activities. The second is that they do not wish to intensify relationships with third party companies because they consider that they are currently at the desired level. The third reason is that they have not discovered the real potential of service companies to perform the activities more efﬁciently and effectively, thus generating additional rents that constitute the creation of relational capabilities (Rodrı´ guez-Dı´ az & Espino-Rodrı´ guez, 2006). In this section as the ﬁrm outsources low strategic value operations with Type II or III relationships (below the diagonal), it will be in a better position to differentiate itself from the competition and gradually increase the strategic value of the operation (Cox, 1996).

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Proposition 3. When, in the case of activities with low or medium internal strategic value, there are suppliers able to offer high relational value, they should be outsourced with the aim of increasing internal strategic value and consequently strengthen the competitive advantage.

APPLICATION OF THE MODEL TO THE HOTEL SECTOR In order to apply the model it is necessary to identify the different activities of the hotel process as well as the strategic value of each of the activities. Previous studies identify the strategic value of the different hotel operations. The internal strategic value applied to the hotel sector permits the classiﬁcation of hotel operations into three groups (high strategic value operations, medium strategic value operations and low strategic value operations) (Espino-Rodrı´ guez & Padro´n-Robaina, 2005). Group A in Table 2 contains strategic value services that are sources of competitive advantage and that are suitable to generate the core competences of the hotel. Finally, as they are the least transferable and most nonsubstitutable services and the most liable to generate value for the hotel, they are not very prone to outsourcing. The type of relationship required is Type III, or the development of internal relations. However, there may be a certain level of desired outsourcing of some of the services in this group. These are services that, if outsourced, require a high integration of speciﬁc resource processes in the relationship, and shared routines that stem from values based on cooperation in determined routines (Kale, Singh, & Perlmutter, 2000). Therefore, it is necessary to generate inimitable relationships that result in inimitable, non-substitutable activities created from the tacit part of relationships characterized by shared knowledge, spontaneous methods to resolve problems and the trust to share ideas that the hotel and service companies can jointly develop and apply. Normally, hotels are reluctant to outsource this group of activities (Espino-Rodrı´ guez & Padro´n-Robaina, 2005), which should only be outsourced when a high level of strategic relational value is ensured. Group B includes services that, in general, have medium strategic value and comprise the complementary competences and are essential to offer a good hotel service. This type of activity requires Type II relationships or strategic alliances, which are necessary for outsourcing. Managers can achieve this type of relationship by opening up to a partner or partners and protecting against opportunist behavior.

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Table 2. Activities Grouped According to their Strategic Value. Group Group A: Core activities

Group B: Complementary activities

Group C: Non-core activities

Activity Reception Reservations Purchasing and receiving Kitchen Restaurant Bars Sales activity Administration General maintenance Hotel leisure activities Employee training Personnel selection Information systems Promotion and advertising Common areas cleaning Room cleaning Laundry Swimming pool maintenance Gardening Safety and security

Source: Espino-Rodrı´ guez and Padro´n-Robaina (2005, p. 715).

Group C comprises the activities that are the most standardized and homogeneous for the hotel and comprise the non-core operations of the hotel sector. These are usually the activities that the hotel considers outsourcing ﬁrst. However, the activities in this group that the hotel outsources are probably performed within a Type I, or arm’s length, relationship since they are perfectly imitable, substitutable and do not generate rents for the hotel. This means that there is no integration of processes or speciﬁc relations that permit the generation of those rents (Fig. 2). For outsourcing to increase, hotel managers need a model to guide them in their choice of type of relationship that enables them to maintain or increase their competitive advantage by using outside suppliers. The matrix in Fig. 2 shows the current situation of the destination according to an internal evaluation by the focal hotel companies of the different activities and their respective conditions if the hotel were to outsource them or if it created strategic alliances with other companies. However, a change of mentality is needed, as well as some modiﬁcations in the matrix that permit the company to differentiate itself from competitors

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Relational strategic value of the activity Type III Type II Type I Integration Arm’s length

Relational / Internal

Fig. 2.

Internal strategic value of the activity Low Medium High -Common areas cleaning -Room cleaning Section above -Laundry C -Swimming pool the diagonal maintenance -Gardering -Safety and security -General maintenance -Leisure activities - Employee training -Personnel selection B -Information systems -Promotion and advertising -Reception -Reservations -Purchasing and receiving Section below A -Kitchen the diagonal -Restaurants -Bars -Sales activity -Administration

Evaluation of Outsourced Activities in the Hotel Sector According to the Model.

when it outsources a service. For example, in most cases, the hotel outsources the laundry service, as well as safety and security, but one question arises: Can a ﬁrm develop idiosyncratic relationships with a supplier in such a way that the relations are unique and speciﬁc in comparison to those of competitors who have outsourced the services? However, only from this relational perspective can there be an increase in the outsourcing of services that have higher strategic importance for the hotel, such as kitchen, restaurant, leisure activities, etc.

Analysis of the Main Diagonal in the Hotel Sector Fig. 2 sets out the evaluation of the outsourcing strategy and the creation of the relational capabilities of the different hotel operations based on process integration. In the reality of the hotel sector, there are different examples of

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outsourcing activities or strategic alliances according to their position on the diagonal. In the case of activities classiﬁed as ‘‘A’’, that is, activities with real potential to develop relational capabilities, one outstanding example is the marketing activity, where hotel chains, such as RIU Hotels, reach agreements with tour operators, delegating a considerable part of the sales process to them. This is a clear example where the strategic value of an activity is high, while a third party company performs it within a model of maximum process integration. In fact, RIU Hotels, a worldwide hotel chain with establishments around the world, has recently acquired 9% of the shares of TUI, the leading European tour operator, in order to consolidate their position in the market. Other examples of relational capabilities are the agreements between hotel companies and restaurant companies, such as those between Marriott Hotels and Ruth’s Chris Steakhouse, Studebakers, Benihana, Trader Vic’s and Pizza Hut (Strate & Rappole ,1997). In the case of Type B activities, the strategic value of information systems is increasing in the hotel sector. Examples of this are Leading Hotels of the World and Relais & Chateaux, where hotel companies consider linking to the website, opening a web page on the Internet and sharing databases (Cline, 2000). Insofar as this type of activity is considered to have a higher strategic value, and collaboration agreements are made with other companies with whom processes are integrated and mutually relevant information shared, it is moving toward the creation of a core competence and becoming a Type A activity. Finally, in the case of Type C activities, it is difﬁcult to obtain a rapid idiosyncratic differentiation that reaches the maximum level, Type A. However, promoting activities like cleaning and gardening may steadily increase their strategic importance in such a way that the speciﬁc qualities and skills of the individuals performing them produce idiosyncratic effects through long-term cooperation, thus favoring the quality of the service. Moreover, many hotels outsource the laundry service while expressing a wish to maintain control of the service in the hotel with the aim of improving control of the laundered items, rejecting sub-standard items, reducing transport costs, offering hotel guests a faster personal laundry service, reducing delivery errors, etc. That approach requires the hotel and the laundry company to reach certain agreements on quality that clearly set out the speciﬁcations and conditions to be complied with. This type of approach generates a better service to the end consumer and permits additional rents through cost reductions and process integration between the hotel and laundry company, thus forming, for example, a Type II relationship with the consequent improvement in the outsourced service. This matrix can be used by hotels to differentiate themselves from the competition in terms of their

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Table 3.

Elements Determining the Strategic Relational Value.

Attributes Level of joint planning of the activity Beneﬁts obtained after the start of the outsourcing relationship Hotel services provider’s ﬂexibility and level of adaptability when changes are requested Level of integration, commitment, communication and collaboration between the supplier and the hotel Long-term orientation in the outsourcing relationship Elements that govern the relationship: price, authority and trust Supplier’s knowledge of the processes and competitive strategy of the hotel Conﬁdentiality of important aspects of the hotel Extent to which the outsourcing relationship permits access to the hotel’s skills and capabilities and complements them Degree to which the outsourcing relationship is valuable, rare and non-substitutable

relationships; for example, the laundry or gardening service may be outside the diagonal, with a Type I or II relationship, which would increase its relationship strategic value and its importance to competitive advantage, provided that the hotel takes advantage of the opportunity. However, in the case of hotel activities that are above the diagonal; for example, sales or food and beverage operations, the hotels use a Type I or arm’s length relationship to manage the outsourcing and must be aware that they are losing competitive capability by not having suitable suppliers available and, in the relatively short term, the strategic value reduces. The hotel can maintain or increase its competitive advantage only through planning and the existence of suppliers with whom to maintain closer relationships (Type III). This work should not end without indicating a series of variables and aspects that hotels should ask themselves about to determine the type of partnership that they have with their suppliers and so identify the potential for strategic relational value. The following questions should be asked for each operation in order to determine the strategic relational value. The greater the compliance with the 10 attributes shown in Table 3, the greater the capacity to develop relational capability.

CONCLUSIONS The model we have proposed can be of great use in the increasing of outsourcing in the sense that each hotel can develop its own model of

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outsourcing; in other words, it can decide which operations to outsource and what type of interorganizational relationship to maintain (Type I, Type II, Type III or arm’s length). This matrix can help the hotel to establish its outsourcing strategy, which be useful in differentiating it from the competition and so improve its competitive advantage. Hotels may move their operations from Box C to Box B or A (Fig. 2) and so obtain a differentiation in its outsourcing strategy and improve its competitive advantage. Hotels with higher levels of outsourcing have better organizational results (Espino-Rodrı´ guez & Padro´n-Robaina, 2005); therefore, it is important to develop strategic alliances in order to generate relational capabilities, since only they can guarantee the competitiveness of the focal companies, and consequently of the destinations. The development of relationships between companies inﬂuences the destinations’ levels of adaptability by offering creative and innovative alternatives to maintain competitiveness in the different stages of their lifecycles, especially the later stages. The outsourcing of operations to specialist service companies is a growing phenomenon, which has great potential in the destination under study (Lam & Han, 2005; Lamminmaki, 2007). Destinations whose evolution has almost reached chaos, or that are in the advanced stages of their life-cycles, require new strategic approaches, where hotels increasingly focus on their core competences and develop their relationships by opening up to other service companies. Implementing a relational strategy requires a highly complex decision making process and so, there is a need for theoretical models that help facilitate the creation of interorganizational relations (McIvor, 2005). The objective is to create and reinforce relational capabilities, not only to develop associative competitive advantage of the collaborating companies, but also to strengthen relational capabilities as a consequence of a better market position, thus favoring the creation of synergies and additional rents and so reducing the transaction costs (Dyer, 1997). Another important aspect of the paper is that the strategic evaluation provides different aspects in order to discern how the strategic conception of activities will evolve over time. This is because the matrix is dynamic and will co-evolve to the extent that companies begin to improve their skills, strategic evaluations and cooperation with service companies. This means a change of mental model regarding what is core or non-core and represents an extremely interesting way to innovate in aspects related to the customers’ perception of quality. In this context, those hotels in a determined destination that advance in their evaluations and relationships more than other companies will be able to obtain competitive advantage through

226 TOMA´S F. ESPINO-RODRI´GUEZ AND MANUEL RODRI´GUEZ-DI´AZ

anticipation. When the level of relational capabilities increases, the hotel beneﬁts initially but, in the ﬁnal instance, the end beneﬁciary will be the tourism destination (Rodrı´ guez-Dı´ az & Espino-Rodrı´ guez, 2006). One of the principal implications of the proposed model is related to tourist destinations. In this respect, destinations are complex adaptive systems as a result of the interaction of multiple public, private and social agents that co-evolve parallel to the destination’s life-cycle (Farrell & Twining-Ward, 2004). The proposed model is characterized by being dynamic and is, therefore, of great help in analyzing both the overall level of orientation toward interorganizational relationships by means of outsourcing and strategic alliances at a given time. In the proposed model, entrepreneurial activity plays a critical role (Russell & Faulkner, 2004) since service companies that are willing to cooperate must be created. The model permits comparative analyses of different destinations, which makes it possible to compare how competitive and relational strategies are developed according to the life-cycle stage of the destinations. Although the model was applied to the principal operations of the hotel sector, it could be applied to other types of tourism ﬁrms. Future studies should validate the model and its application to tourism.

REFERENCES Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. Bettis, R. A., Bradley, S., & Hamel, G. (1992). Outsourcing and industrial decline. Academy of Management Executive, 6(1), 7–22. Chathoth, P. K., & Olsen, M. D. (2003). Strategic alliances: A hospitality industry perspective. International Journal of Hospitality Management, 22(4), 419–434. Cline, R. S. (2000). E-commerce: The pace picks up. Hotels, 34, p. 71. Collis, D. J., & Montgomery, C. (1995). Competing on resources: Strategy in the 1990s. Harvard Business Review, 73(4), 118–128. Costa, A. C. (2003). Work team trust and effectiveness. Personnel Review, 32(5), 605–622. Cox, A. W. (1996). Relational competence and strategic procurement management: Towards and entrepreneurial and contractual theory of the ﬁrm. European Journal of Purchasing and Supply Management, 2(1), 57–70. Dyer, J. (1997). Effective interﬁrm collaboration. How ﬁrms minimize transaction cost and maximize transaction value. Strategic Management Journal, 18, 535–556. Dyer, J., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679. Espino-Rodrı´ guez, T. F., & Padro´n-Robaina, V. (2005). A resource-based view of outsourcing and its implications for organizational performance in the hotel sector. Tourism Management, 26(5), 707–721.

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Evans, N. (2001). Collaborative strategy: An analysis of the changing world of international airline alliances. Tourism Management, 22(3), 229–243. Farrell, B. H., & Twining-Ward, L. (2004). Reconceptualizing tourism. Annals of Tourism Research, 31(2), 274–295. Frohlich, M. T., & Westbrook, R. (2001). Arcs of integration: An international study of supply chain strategies. Journal of Operations Management, 19, 185–200. Heide, J. B., & John, G. (1990). Alliances in industrial purchasing: The determinants of joint action in buyer–supplier relationships. Journal of Marketing Research, 27, 24–36. Hoyt, J., & Huq, F. (2000). From arms-length to collaborative relationships in the supply chain. An evolutionary process. International Journal of Physical Distribution and Logistics Management, 30(9), 750–784. Kale, P., Singh, H., & Perlmutter, H. (2000). Learning and protection of proprietary assets in strategic alliances: Building relational capital. Strategic Management Journal, 21, 217–237. Kirsten, M., & Rogerson, C. M. (2002). Tourism, business linkages and small enterprise development in South Africa. Development Southern Africa, 19(1), 29–59. Knemeyer, A. M., Corsi, T. M., & Murphy, P. R. (2003). Logistics outsourcing relationships: Customer perspectives. Journal of Business Logistics, 24(1), 77–110. Lafferty, G., & Van Fossen, A. (2001). Integration the tourism industry: Problems and strategies. Tourism Management, 22(1), 11–19. Lam, T., & Han, M. (2005). A study of outsourcing strategy: A case involving the hotel industry in Shanghai, China. International Journal of Hospitality Management, 24(1), 41–56. Lambert, D. M., Emmelhainz, M. A., & Gardner, J. T. (1996). Developing and implementing supply chain partnerships. The International Journal of Logistics Management, 7(2), 1–17. Lamminmaki, D. (2007). Outsourcing in Australian hotels: A transaction cost economics perspective. Journal of Hospitality and Tourism Research, 31(1), 73–110. McIvor, R. (2005). The outsourcing process: Strategies for evaluation and management. Cambridge, UK: Cambridge University Press. Pavlovich, K. (2003). The Evolution and transformation of a tourism destination network: The Waitomo Caves, New Zealand. Tourism Management, 24(2), 203–216. Rodrı´ guez-Dı´ az, M., & Espino-Rodrı´ guez, T. F. (2006). Developing relational capbilitites in hotels. International Journal of Contemporary Hospitality Management, 18(1), 25–40. Russell, R., & Faulkner, B. (2004). Entrepreneurship, chaos and the tourism area lifecycle. Annals of Tourism Research, 31(3), 556–579. Selin, S., & Chavez, D. (1995). Developing an evolutionary tourism partnership model. Annals of Tourism Research, 22(4), 844–856. Strate, R. W., & Rappole, C. L. (1997). Strategic alliances between hotels and restaurants. The Cornell Hotel and Restaurant Administration Quarterly, 38(3), 50–61. Wernerfelt, B. (1984). A resource-based view of the ﬁrm. Strategic Management Journal, 5, 171–180. Zhao, M., & Stank, T. P. (2003). Interactions between operational and relational capabilities in fast food service delivery. Transportation Research Part E: Logistics and Transportation Review, 39(2), 161–173.

CHINESE TOURISTS VISITING SINGAPORE: PULL AND PUSH FACTORS Tak-Kee Hui, David Wan and Miau Feng Chi ABSTRACT China looks set to become the fourth largest outbound tourist generating country in the world by 2020 (World Tourism Organisation, 1997). Tourists from Mainland China are the second most important source of tourist arrivals in Singapore. A better understanding of the Chinese tourists’ needs and expectations will be helpful in positioning the country to attract them. The data collected at Singapore Changi International Airport are segmented to different groups under various demographic factors. This study shows that there exist motivational differences among gender, income, age as well as travel frequencies. The findings are useful to the marketers to establish their strategic plans in targeting at different groups of Chinese visitors.

INTRODUCTION Since the intensiﬁcation of its open door policy in the 1990s and the corresponding increase in the disposable income of the Mainland Chinese, China has begun to develop its outbound tourism (Zhang, Pine, & Zhang, 2000). Advances in Hospitality and Leisure, Volume 4, 229–244 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00011-8

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With the country looking set to become the fourth largest outbound-touristgenerating country in the world by 2020 (World Tourism Organisation, 1997), more interest towards China’s outbound travel market has been generated among both academics and practitioners alike (Zhang & Heung, 2001a). Singapore, with its strategic position, is one of the popular destinations in South-East Asia. Tourists from Mainland China are now one of the most important sources of tourist arrival for Singapore, with visitor arrival from the country having the highest growth rate of 28% for the month of January 2004 (Singapore Tourism Board, 2004). In fact, China is ranked second among the top 12 markets of visitor arrivals for the same period, accounting for 12.2% of the total tourist arrivals. As one of the few Asian Paciﬁc countries that have China’s National Tourism Administration (CNTA) ofﬁcial approval for overseas holiday (Zhang & Heung, 2001b), Singapore is in a good position to tap into the huge Chinese market. Furthermore, Qu and Zhang (1996) have projected Singapore’s annual growth rate in tourist arrivals to decrease by 0.5% from 1995 to 2005. The country can turn to potential Chinese tourists to stimulate growth. In order to achieve this, it will have to better understand the needs and expectations of Chinese travellers so as to provide them with quality travel experience. Indeed, Singapore can ill afford to lose out in this competition for tourist money. This is because throughout the Paciﬁc, countries are vying to net the relatively afﬂuent Chinese tourists. Brooke (2004) even compares these visitors with the big-spending Arab tourists of the 1970s and the Japanese shoppers of the 1980s and 1990s. Singapore as a place for visit has been marketed as ‘‘a vibrant, cosmopolitan, youthful city-state where tradition and modernity, East and West, meet and intermingle harmoniously’’ (Singapore Tourism Board, 2002), and it is now projected as ‘‘uniquely Singapore’’ (Singapore Tourism Board, 2004). However, little research has been done to ascertain whether these attributes are congruent with what the Chinese are looking for when choosing their travel destinations. Using a framework of push and pull factors, this paper aims to contribute to the dearth of local studies on the Mainland Chinese tourists market by examining whether there are any signiﬁcant differences in travel motivations among various social demographic attributes such as gender, age and income. In addition, this paper would also like to investigate whether there are any signiﬁcant perceptual differences among the different travel frequency groups. All these information could help Singapore to strategically plan and organise its marketing and promotional activities in China (McCabe, 2000; Gursoy & McCleary, 2004).

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The ﬁndings should also help practitioners to effectively tailor their promotional efforts to meet the different needs of the Chinese tourist market.

LITERATURE REVIEW Prior to 1978, China had imposed travel restrictions, both within and outside of the country, for fear of Western ideological contamination (Zhang & Heung, 2001a). However, in the signiﬁcant year of 1978, the Communist Party of China (CPC) Central Committee decided to shift its emphasis from political struggle to economic construction, of which tourism was later considered as an economic activity. Tourism in China developed rapidly since then. With China’s imminent entry to the WTO, the country will be more open to the world, and the world will be more open to China (Zhang et al., 2000). This two-way openness will reduce entry–exit barriers for international visitors, and facilitate tourist ﬂow. China’s outbound travel market will then become a major source of tourist arrival for the world. The main reasons for the growth of China’s tourism sector can be attributed to the implementation of its open policy and an increase in the disposable income of the Chinese people (Zhang et al., 2000). From 1993 to 1999, China’s annual real Gross Domestic Product (GDP) growth of 7–13% was, on average, the highest among the major countries in the region (Zhang & Heung, 2001b). Another source estimated that between 1992 and 2003 China’s per capita income grew at a compound annual rate of more than 13% (Chuang, 2004). Although motivation is only one variable explaining tourist behaviour, it is often regarded as one of the most important variables because it is both an impelling and compelling force behind all behaviour (Baloglu & Usyal, 1996). People travel because they are pushed into making this decision by internal forces and pulled by external forces of the destination attributes (Uysal & Jurowski, 1993). The push factors for a vacation are socio-psychological motives, while the pull factors are motives aroused by the destination rather than emerging exclusively from within the traveller himself. Crompton (1979) identiﬁed nine motives for travelling, which can be categorized as being located either toward the socio-psychological end or the cultural end of the continuum. Examples of socio-psychological motives are: escape from a perceived mundane environment, relaxation, prestige and enhancement of kinship relationships. Cultural motives (the pull factors) include, for example, novelty and education.

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Knowledge about the interaction of these push and pull factors can aid marketers and developers of tourism destination areas determine travelers’ needs and expectations (Uysal & Jurowski, 1993). Much research is directed towards pull factors to explain why people travel to a certain destination. For example, Chen and Hsu (2000) focused on image attributes measuring the total attractiveness of overseas destinations to Korean tourists. Hu and Ritchie (1993), on the other hand, seek to determine the relative importance of selected attributes in contributing to the overall attractiveness of a tourism destination. These studies however ignore the socio-psychological motives behind destination selection. Crompton (1979) noticed that a number of travel motives are not place speciﬁc. Also, motivation is multidimensional. Tourists seek to satisfy not one single need but a number of distinct needs simultaneously (Baloglu & Usyal, 1996). Hence, an analysis of both the push and pull factors would yield a more comprehensive picture of travel motivations. Despite the growing importance of China as a tourist-generating country, there are only a handful of studies on the Mainland Chinese market (Qu & Li, 1997; Zhang & Lam, 1999; Heung, 2000; Ryan & Mo, 2001). Qu and Li (1997) investigated Chinese travellers’ satisfaction levels with their Hong Kong tour with regard to tourism infrastructure and facilities, Hong Kong residents’ attitudes, services provided in hotels, restaurants and shops, the transportation system and the environment. Destination selection attributes such as accessibility, cost, ease of applying for visa, safety and scenery were also assessed. Heung (2000) focused on the needs, expectations and satisfactions of Chinese travellers towards hotel services and examined hotel attributes such as ‘‘quietness of the room,’’ ‘‘swimming and gymnasium facilities’’ and ‘‘friendliness and helpfulness of hotel staff.’’ Ryan and Mo (2001) reported their ﬁndings derived from a sample of 400 ‘‘well-educated and above-average’’ Chinese tourists to New Zealand and noted that their main motive was to see new places not previously visited, and to have a relaxing holiday. They also found that some of them were using their holiday to explore the educational and investment opportunities. In fact, about 15% indicated a return visit. Even fewer studies have examined Chinese tourist motivation to travel using a framework of push and pull factors. Zhang and Lam (1999) identiﬁed Chinese travellers’ motives for travelling to Hong Kong using the push and pull factors as a conceptual model. They proceeded to ﬁnd out how different their motivations were in comparison with travellers from other markets and looked for patterns among travel motivations and social demographic attributes. Their approach focused not just on the pull factors as in other research (Heung, 2000; Qu & Li, 1997) but also on the role of the push factors. It is based on such an analytical framework of push and pull factors

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that this paper will attempt to uncover the relationship between travel motivations and social demographic factors. This will, in turn, help the tourism marketers/managers gain a better understanding of the Chinese visitors’ needs and expectations so that different marketing segmentation programs can be designed to attract more Chinese visitors to repeat their visits.

RESEARCH METHODOLOGY Sample and Data Collection Since the bulk of the Chinese travellers come to Singapore by air, the Singapore International Changi Airport is selected as a venue for collecting data. The data are collected using the systematic random sampling scheme. Respondents are asked to complete a questionnaire that is designed to ﬁnd out travellers’ motivations and their demographic proﬁle. The questionnaire is divided into two sections. Section A deals with the respondents’ travel motives while Section B covers the demographic factors. The travel motivation variables are adopted from Zhang and Lam’s (1999) study on Chinese visitors. Due to the geographical and cultural differences, some minor changes to the items are done. To eliminate the language barrier, a Chinese version of the questionnaire is used instead of on-the-spot translation.

Data Analysis The data are segmented and analysed according to different groupings. Each motivational item based on gender, four income groups, four age groups and three travel frequency groups is examined. Since most of the demographic factors, except gender, have more than two groups for comparison, one-way ANOVA analysis will be used to detect group differences on both the pull and push factors. If there exists a signiﬁcant difference, the Tukey–Kramer procedure is used to ﬁnd out which groups are statistically different (Levine, Stephan, Krehbiel, & Berenson, 2005). As for the gender factor, the independent samples’ t-test is used to see whether there is any signiﬁcant difference between the male and female respondents. The use of these two analyses requires that the data set of different groups come from a normally distributed population. To test the normality of the data, the Bowman–Shelton statistics is calculated (Newbold, Carlson, & Thorne, 2003). The usual Q–Q plot as provided by the Excel package is also

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used to detect the normality assumption. If the assumption is violated, the alternative non-parametric tests such as Kruskal–Wallis and Wilcoxon rank sum test will then be used to replace the ANOVA and the independent samples’ t-tests (Levine, Stephan, Krehbiel, & Berenson, 2005).

EMPIRICAL FINDINGS Demographic Characteristics of Respondents Table 1 presents the respondents’ demographic proﬁles. 40% of the 124 respondents were males and half were single. About 80% of the respondents fell within the age group of 16–45 years. About 48% were professional and senior white-collar workers. The majority of the respondents (69%) visited Table 1.

Characteristics of the Survey Respondents.

Socio-Demographic Variable

Percentage

Socio-Demographic Variable

Percentage

Gender Male Female

40 60

Marital status Single Married Other

50.0 37.9 12.1

Age (years) Below 15 16–30 31–45 46–60 61 and above

1.6 47.6 31.5 15.3 4.0

Educational level Primary school Junior high school Senior high school Technical/vocational University or postgraduate Other

0.0 5.6 17.7 20.2 54.1 2.4

Profession Owner Professional or technical Senior white collar Junior white collar Skilled worker Unskilled worker Farming/ﬁshing Others (housewife, student etc.)

2.4 12.1 33.9 29.9 12.9 3.2 3.2 2.4

Monthly income level Less than RM1,000 RM1,000—1,999 RM2,000–2,999 RM3,000–3,999 RM4,000–4,999 RM5,000–5,999 RM6,000–6,999 RM7,000 or above

2.4 26.6 26.7 20.2 14.5 3.2 2.4 4.0

No. of visits to Singapore First time Two to four times Five times or more

69.4 21.0 9.6

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Singapore for the ﬁrst time, while close to 10% of them had visited Singapore for more than ﬁve times. About 54% of the respondents were highly educated with at least a university degree. As for the income level, 7 in 10 earned between US$121 (RM1,000) and US$483 (RM3,999) per month.

Ranking of the Push and Pull Factors As shown in Table 2, the most important motive among all the push factors is ‘‘Increasing knowledge about a foreign destination’’ (mean score ¼ 3.27). This is different from Zhang and Lam’s (1999) ﬁnding where this factor is ranked as the top four with a mean score of 3.01. Their highest ranking statement is ‘‘Seeing something different’’ with a mean score of 3.17. The second-highest ranking factor in our case goes to ‘‘Experiencing a different Table 2.

Importance Ranking of the Push and Pull Factors.

Push factors Q1. Visiting cultural and historical attractions Q2. Increasing knowledge about a foreign destination Q3. Experiencing a different lifestyle Q4. Fulﬁlling my dream of visiting a place Q5. Visiting a destination that would impress my friends or family Q6. Facilitating family and kinship ties Q7. Being able to share my travel experiences after returning home Q8. Escaping from daily routine Q9. Physically resting/relaxing Q10. Finding thrills or excitement Pull factors Q11. International cosmopolitan city Q12. Capital of modern technology Q13. Uniqueness of local people’s lifestyle Q14. Shopping paradise Q15. Variety of food Q16. Convenience of transport Q17. Positive attitude of Singaporeans and service staff to mainland tourists Q18. Quality of accommodation facilities Q19. Beautiful scenery Q20. Similar cultural background and common language (e.g. Mandarin)

Mean Score

Ranking

2.7661 3.2742 3.2419 3.1613 2.8145 2.1129 3.0323 2.8710 2.9839 2.7097

8 1 2 3 7 10 4 6 5 9

2.9597 2.9355 2.9758 3.2177 3.3790 3.2097 2.9194

8 9 7 5 3 6 10

3.3306 3.5242 3.8468

4 2 1

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TAK-KEE HUI ET AL.

lifestyle’’ (mean score ¼ 3.24). The lowest ranking goes to the statement ‘‘Facilitating family and kinship ties’’ (mean score ¼ 2.11). This is again inconsistent with Zhang and Lam’s (1999) study where facilitating family and kinship ties is ranked as the second highest with a mean score of 3.03. Since most of the Mainland Chinese in Zhang and Lam’s (1999) survey came from Guangdong (Southern part of China), it is not surprising that their respondents have strong family ties with people in Hong Kong. As for Singapore, the family ties will be less strong because most of the Chinese Singaporeans are in their second and third generations. The highest ranking statement among all the pull factors is ‘‘Similar cultural background and common language’’ with a mean score of 3.85, followed by ‘‘Beautiful scenery’’ (mean score ¼ 3.52) and ‘‘Variety of food’’ (mean score ¼ 3.38). The results are again different from Zhang and Lam’s (1999) ﬁnding where their top ranking statement goes to ‘‘Positive attitude of HK residents and service staff to mainland tourists’’ with a mean score of 3.81. In our study, the word ‘‘HK resident’’ is replaced with ‘‘Singaporeans’’ and is ranked last with a mean score of 2.92. The score reveals that there is still a lot of room for improvement if Singapore wants to attract more visitors from Mainland China.

Motivational Factors and Demographic Characteristics Both Bowman–Shelton statistics and the Q–Q plot conﬁrm that the normality assumptions of almost all groups are met. For simplicity, the results are not shown here. As such, the parametric tests are used for the whole study. Tables 3–6 present the results of analysis of variance (ANOVA) and the corresponding t-test statistics. The tables reveal that, across all the demographic variables, some signiﬁcant differences occur for both the push and pull motivational factors. First, perceptual differences between males and females are examined. Table 3 indicates that, generally speaking, both genders have similar views on the various factors. Only items 7 (Being able to share travel experiences after returning home), 12 (Capital of modern technology) and 20 (Similar cultural background and common language) exhibit signiﬁcant perceptual differences between the two genders. In terms of mean scores, these three attributes are more important to males than females. For example, men seem to be more inclined towards technology than females, and hence the status of the country’s technological development may appeal more to them. For the other dimensions, there is no signiﬁcant perceptual difference. Both genders value the variable ‘‘Increasing knowledge about a foreign

Chinese Tourists Visiting Singapore: Pull and Push Factors

Table 3.

237

Male and Female Perceived Importance of the Push and Pull Factors. Mean Score

Push factors Q1. Visiting cultural and historical attractions Q2. Increasing knowledge about a foreign destination Q3. Experiencing a different lifestyle Q4. Fulﬁlling my dream of visiting a place Q5. Visiting a destination that would impress my friends or family Q6. Facilitating family and kinship ties Q7. Being able to share my travel experiences after returning home Q8. Escaping from daily routine Q9. Physically resting/relaxing Q10. Finding thrills or excitement Pull factors Q11. International cosmopolitan city Q12. Capital of modern technology Q13. Uniqueness of local people’s lifestyle Q14. Shopping paradise Q15. Variety of food Q16. Convenience of transport Q17. Positive attitude of Singaporeans and service to mainland tourists Q18. Quality of accommodation facilities Q19. Beautiful scenery Q20. Similar cultural background and common language (e.g. Mandarin)

p-Value

Male

Female

2.9184 3.3878 3.1837 3.3061 3.0000

2.6667 3.2000 3.2800 3.0667 2.6933

0.2311 0.3552 0.6074 0.2467 0.2043

2.0408 3.3061

2.1600 2.8533

0.4145 0.0204

3.0816 3.0204 2.8163

2.7333 2.9600 2.6400

0.0722 0.6875 0.3182

3.1837 3.2245 3.1633 3.4286 3.3469 3.2245 2.8163

2.8133 2.7467 2.8533 3.0800 3.4000 3.2000 2.9867

0.061 0.0064 0.1004 0.0822 0.7964 0.9046 0.4025

3.4490 3.6735 4.0408

3.2533 3.4267 3.7200

0.3475 0.2296 0.0422

p-valueo0.05.

destination’’ as above average. Similarly, for ‘‘Variety of food’’, they also have the same view. For the variable ‘‘Shopping paradise,’’ the difference in opinion is rather marginal. It is interesting to note that the male respondents value this factor higher than their female counterparts. Results in Table 4 indicate that among the different income groups, there are signiﬁcant perceptual differences towards the push factors. For example, the lower the income group, the higher the perceived importance on ‘‘Gaining more knowledge about Singapore’’ and ‘‘Experiencing a different lifestyle.’’ This may be due to the reason that people from the lower income group do

238

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Table 4.

Comparison of Push and Pull Factors for Different Income Groups. Mean Score

Signiﬁcant Difference

Group 1

Group 2

Group 3

Group 4

F-Ratio

3.2222

2.6724

2.5000

2.1250

3.5833

3.3793

2.7727

2.5000

3.4444

3.3448

3.0000

2.2500

Q4. Fulﬁl dream of visiting a place

3.4444

3.3103

2.6364

2.2500

Q5. Visit a destination that would impress friends or family Q6. Facilitate family and kinship ties Q7. Being able to share travel experiences after returning home Q8. Escape from daily routine Q9. Physically resting/relaxing Q10. Find thrills or excitement

3.1667

2.8966

2.3636

1.8750

2.0556

2.1379

2.1818

2.0000

3.8522 Groups 1 and 4 4.8732 Groups 1 and 3, 4 4.1862 Groups 4 and 1, 2 5.3635 Groups 1, 2 and 3, 4 3.9409 Groups 1 and 4 0.1951

3.2500

3.2069

2.5455

2.1250

5.1516 Groups 1, 2 and 3, 4

2.7500 2.9722 2.9722

3.0517 3.0690 2.6897

2.7727 2.8636 2.4091

2.3750 2.7500 2.5000

1.3025 0.5441 1.7825

2.9722

2.6897

2.4091

2.6250

1.6732

3.1389

2.9483

2.4545

3.2500

3.0556

3.0172

2.7273

3.0000

2.7303 Groups 1 and 3 0.5492

3.1111 3.2778 3.2500 2.8889

3.2759 3.4138 3.0000 2.7931

3.3182 3.5000 3.5455 3.2273

3.0000 3.2500 3.6250 3.1250

0.3263 0.2349 2.0203 1.0585

3.4444

3.2586

3.6818

2.3750

3.4167

3.5690

4.0000

2.3750

3.9444

3.9138

4.0909

2.2500

Push factors Q1.Visit cultural and historical attractions Q2. Increase knowledge about a foreign destination Q3. Experience a different lifestyle

Pull factors Q11. International cosmopolitan city Q12. Capital of modern technology Q13. Uniqueness of local people’s lifestyle Q14. Shopping paradise Q15. Variety of food Q16. Convenience of transport Q17. Positive attitude of Singapore residents and service Q18. Quality of accommodation facilities Q19. Beautiful scenery Q20. Similar cultural background and common language (Mandarin)

Between groups

2.8263 Groups 3 and 4 4.5022 Groups 2, 3 and 4 10.654 Groups 1, 2, 3 and 4

Note: Income Group 1:oRM2,000, Group 2: RM2,000—3,999, Group 3: RM4,000—5,999, Group 4: WRM6,000. p-value o 0.05.

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not get as much chance to visit Singapore, compared to people from the higher income group. In addition, the prestige associated with visiting Singapore (to impress friends or family) is perceived as more important to those from the low-income group. Among the pull factors, Table 4 reveals that visitors from the middleincome group perceived ‘‘Quality of accommodation’’ and ‘‘Scenery of Singapore’’ to be more important than ‘‘Modern technology’’ when compared with people from the highest income group. In terms of ‘‘Similar culture and common language,’’ there is a signiﬁcant perceptual difference between the highest income group and all the other groups. This could imply that visitors from this high-income group do not face the same language barrier, as they are most probably people who are highly educated and are able to speak English. Table 5 indicates that there are signiﬁcant differences between push factors and age groups. Group 4 (those who are above 60 years old) is different from the other three groups with respect to visiting cultural and historical attractions, increasing knowledge about a foreign destination, fulﬁlling the dream of visiting a place and visiting a destination that would impress one’s friends or family. The elderly seem to value these activities more than the young. As for the pull factors, there exists no signiﬁcant difference among different age groups except for ‘‘Variety of food.’’ The younger generation appears to pay more attention to food diversity. Table 6 reveals that signiﬁcant differences exist between certain push factors and travel frequencies. For example, the ﬁrst-time visitors perceived that travelling to Singapore is more prestigious and provides them knowledge. When people have been here for more than ﬁve times, it is understandable that they will place lesser importance on prestige and knowledge. As for the pull factors and travel frequencies, responses turn out to be signiﬁcantly different for the following. Variety of food and convenience of transport become more attractive for visitors as travel frequency increases. It may be due to the reason that many of the ﬁrst-time travellers visit Singapore in groups arranged by their travel agencies. They thus do not have to worry about transportation and eating outlets. The mean scores for the statement ‘‘Similar cultural background and common language (Mandarin)’’ decrease in importance as travel frequency increases and there is a signiﬁcant difference between ﬁrst timers and frequent visitors. With respect to ‘‘Uniqueness of local people’s lifestyle’’ and ‘‘Shopping paradise,’’ there are signiﬁcant differences between Group 2 (those who have been here for two to four times) and the rest. The former group values Singapore’s reputation as a shopping paradise and the uniqueness of its

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Table 5.

Comparison of Push and Pull Factors for Different Age Groups. Mean Score

Push factors Q1. Visiting cultural and historical attractions Q2. Increasing knowledge about a foreign destination Q3. Experiencing a different lifestyle Q4. Fulﬁlling my dream of visiting a place Q5. Visiting a destination that would impress my friends or family Q6. Facilitating family and kinship ties Q7. Being able to share my travel experiences after returning home Q8. Escaping from daily routine Q9. Physically resting/relaxing Q10. Finding thrills or excitement Pull factors Q11. International cosmopolitan city Q12. Capital of modern technology Q13. Uniqueness of local people’s lifestyle Q14. Shopping paradise Q15. Variety of food Q16. Convenience of transport Q17. Positive attitude of Singaporeans and service to mainland tourists Q18. Quality of accommodation facilities Q19. Beautiful scenery Q20. Similar cultural background and common language (e.g. Mandarin)

Signiﬁcant Difference

Group 1

Group 2

Group 3

Group 4

F–Ratio

Between groups

2.6066

2.7692

2.7895

4.6000

5.7508

3.3770

2.9231

3.2105

5.0000

7.2772

Groups 4 and 1, 2, 3 Groups 4 and 1, 2, 3

3.3279

3.1026

3.0000

4.2000

2.4714

3.2951

2.9231

2.8421

4.6000

4.9032

2.7377

2.8974

2.4211

4.6000

4.781

2.1311

2.1795

2.1053

1.4000

1.5264

2.9016

3.1026

3.0526

4.0000

1.852

2.5902 3.0000 2.8361

3.0769 3.0256 2.7436

3.2632 2.8947 2.2632

3.2000 2.8000 2.6000

2.9198 0.1845 1.7915

3.0000

3.0513

2.6316

3.0000

0.7172

2.7705

3.0256

3.3684

2.6000

2.2313

2.8852

3.0000

3.3684

2.4000

1.7058

3.2623 3.7541

3.2564 3.1538

3.1053 2.9474

2.8000 2.2000

0.3497 6.3721

3.3934 3.1552

3.0000 2.6410

3.1579 2.7895

2.8000 2.8000

1.4366 2.0787

3.2951

3.2821

3.6316

3.0000

0.6053

3.7377 4.0164

2.2821 3.6923

3.2632 3.6316

3.8000 3.8000

1.7722 1.3955

Groups 4 and 1, 2, 3 Groups 4 and 1, 2, 3

Groups 1 and 2, 3, 4

Note: Group 1: Ageo30, Group 2: Age=31–45, Group 3: Age=46–60, Group 4: Age W60. p-value o 0.05.

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Table 6. Comparison of Push and Pull Factors for Different Travel Frequency Groups. Mean Score

Signiﬁcant Difference

Group 1

Group 2

Group 3

F-Ratio

Between groups

3.0465

2.0769

2.2500

10.8919

3.6512

2.3846

2.5000

26.1015

Groups 1 and 2, 3 Groups 1 and 2, 3

3.3372 3.4302

2.9615 2.5385

3.1667 2.5833

1.5107 10.0362

Q5. Visit a destination that would impress friends or family

3.0233

2.5000

2.0000

5.1288

Q6. Facilitating family and kinship ties Q7. Being able to share my travel experiences after returning home Q8. Escaping from daily routine Q9. Physically resting/relaxing Q10. Finding thrills or excitement

2.0581 3.2093

2.2308 2.6923

2.2500 2.5000

0.69457 4.4124

2.8488 2.9651 2.8256

3.0000 3.0385 2.5000

2.7500 3.0000 2.3333

0.27093 0.07634 2.20792

2.9767 2.9302 3.0116

2.9615 3.0000 4.0000

2.8333 2.8333 3.0000

0.0933 0.1237 9.4428

Q14. Shopping paradise

3.0116

4.0000

3.0000

9.4428

Q15. Variety of food

3.186

4.0000

3.4167

5.7264

Q16. Convenience of transport

2.9767

3.8462

3.5000

8.2874

Q17. Positive attitude of Singaporeans and service to mainland tourists Q18. Quality of accommodation facilities Q19. Beautiful scenery Q20. Similar cultural background and common language (e.g. Mandarin)

3.0000

2.7308

2.7500

0.8549

3.2907 3.4884 3.9302

3.6923 3.8846 3.8846

2.8333 3.0000 3.1667

2.5080 2.6981 3.7466

Push factors Q1. Visiting cultural and historical attractions Q2. Increasing knowledge about a foreign destination Q3. Experiencing a different lifestyle Q4. Fulﬁlling my dream of visiting a place

Pull factors Q11. International cosmopolitan city Q12. Capital of modern technology Q13. Uniqueness of local people’s lifestyle

Groups 1 and 2, 3 Groups 1 and Groups 2, 3 Groups 1 and 2, 3

Groups 2 and 1, 3 Groups 2 and 1, 3 Groups 1 and 2 Groups 1 and 2

Groups 1 and 3

Note: Group 1: ﬁrst time, Group 2: two to four times, Group 3: ﬁve times or more. p-value o 0.05.

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people’s lifestyle. In fact, they also value high on the ‘‘Variety of food’’ and the ‘‘Convenience of transport.’’ Although some other variables such as ‘‘Quality of accommodation facilities,’’ ‘‘Beautiful scenery’’ are insigniﬁcant, this group of people still value them high compared with other groups. All these reasons may explain why they still like to repeat their visits to Singapore.

CONCLUSION The number of Chinese visitors to Singapore and this part of the world is expected to increase rapidly. This is because of the fast pace of wealth creation in China, relaxation of foreign exchange control and ease of restrictions on overseas travel as well as the Chinese thirst for travel. This study reveals that pull factors seem to be more important in the minds of the Chinese tourists. The four highest mean scores in Table 2 belong to the pull category. They are, in order of importance, have similar cultural background and common language; beautiful scenery; variety of food; and quality of accommodation facilities. Push factors however should not be ignored either, as the Chinese appear to visit Singapore not just because of the country’s unique attractions and facilities, but also because of their intrinsic need to travel (e.g. increasing knowledge about a foreign destination and experiencing a different lifestyle). Singapore would do well to explore the areas in which she can improve so that the Chinese visitors’ needs and expectations are met. Other than their different views on Singapore as the capital of modern technology, both males and females score similarly on their needs to travel. For age, signiﬁcant differences exist more in terms of the push factors but not in the pull factors. As for income levels and travel frequencies, there are signiﬁcant differences with respect to both pull and push factors. One implication is that more attention can be paid to the diverse needs of the Chinese visitors along the lines of income groups and travel frequencies. For example, most people visiting Singapore from Mainland China are ﬁrst timers. Their needs are different from those who have travelled here before. Marketing efforts should focus on those factors that are valued by this group as they form the majority of visitors, e.g. the country’s cultural and historical sites can be promoted as a unique South-East Asian experience. In terms of ranking priorities, both male and female visitors consider similar cultural background/common language and Singapore’s beautiful scenery as top favours. The males rank quality of accommodation facilities and shopping paradise as their third and fourth reasons for coming here. As for the ladies, their respective reasons are variety of food and experiencing a

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different lifestyle. Interestingly, the female travellers consider Singapore’s reputation as a shopping paradise as their seventh reason to travel. Ranking priorities also differ signiﬁcantly among different age groups. For those who are 60 or below, the primary reason to come is to experience similar cultural background/common language. For those who are above 60 years old, their primary motive is to increase knowledge about a foreign destination. Among the ﬁrst-time visitors to Singapore, their most important reason for coming is because of similar cultural background and common language. However, for those who have been here for two to four times, it is the variety of food, shopping paradise as well as the uniqueness of local people’s lifestyle that make them come back. Finally, it is the convenience of transport and the variety of food that matter to those who have been in Singapore for ﬁve times or more. As China continues to ease restrictions on overseas travel, there is great potential in outbound Chinese tourism. To grab a fair share of this lucrative market, Singapore will need to better understand the needs and wants of the Chinese. This study has uncovered some of the issues and concerns that are signiﬁcant to the Chinese tourists. Future research can focus on identifying and testing more of the push and pull factors to further deﬁne the areas important to the Chinese visitors. The ﬁndings differ from Zhang and Lam’s (1999) survey of Chinese visitors to Hong Kong in terms of the ranking of both push and pull factors. This is understandable as Hong Kong and Singapore are very different in terms of racial composition, and cultural and historical heritage. Geographically speaking, Hong Kong is so much closer to Mainland China while Singapore is part of South-East Asia. That is why Singapore can offer their Chinese visitors a very different experience. As our sample size is relatively small compared with some other studies, the results can only serve as a preliminary ﬁnding. Also, the list of push and pull factors that are studied are not exhaustive. Other relevant and important factors may be left out. Lastly, travel motivation is only one of the many variables that explain tourists’ destination preference behaviour. Therefore, researchers should also consider other variables such as travellers’ perceived inhibitors and situational constraints in their decision-making process.

REFERENCES Baloglu, S., & Usyal, M. (1996). Market segments of push and pull motivations: A canonical correlation approach. International Journal of Contemporary Hospitality Management, 8(3), 32–38.

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Brooke, J. (2004). Asia’s red carpet for China’s rich tourists. Business Times (May 14). Chen, J. S., & Hsu, C. H. C. (2000). Measurement of Korean tourists’ perceived images of overseas destinations. Journal of Travel Research, 38(4), 411–416. Chuang, P. M. (2004). Chinese tourist spending could hit $7.2 billion. Business Times (April 24). Crompton, J. (1979). Motivation for pleasure vacation. Annals of Tourism Research, 6, 408–424. Gursoy, D., & McCleary, K. W. (2004). An integrative model of tourists’ information search behavior. Annals of Tourism Research, 31(2), 353–373. Heung, V. C. S. (2000). Satisfaction levels of Mainland Chinese travellers with Hong Kong Hotel Services. International Journal of Contemporary Hospitality Management, 12(5), 308–315. Hu, Y. Z., & Ritchie, J. R. B. (1993). Measuring destination attractiveness: A contextual approach. Journal of Travel Research, 32(2), 25–34. Levine, D. M., Stephan, D., Krehbiel, T. C., & Berenson, M. L. (2005). Statistics for managers using Microsoft Excel. Upper Saddle River, NJ: Prentice Hall. McCabe, A. S. (2000). Tourism motivation process. Annals of Tourism Research, 27(4), 1049–1052. Newbold, P., Carlson, W. L., & Thorne, B. (2003). Statistics for business and economics. Upper Saddle River, NJ: Prentice Hall. Qu, H., & Li, I. (1997). The characteristics and satisfaction of Mainland Chinese visitors to Hong Kong. Journal of Travel Research, 35(4), 37–41. Qu, H., & Zhang, H. Q. (1996). Projecting international tourist arrivals in East Asia and the Paciﬁc to the year 2005. Journal of Travel Research, 35(1), 27–34. Ryan, C., & Mo, X. (2001). Chinese visitors to New Zealand – Demographics and perceptions. Journal of Vacation Marketing, 8(1), 13–27. Singapore Tourism Board. (2002). Marketing Singapore. Available at: http://www.cybrary.com.sg/ pages/fact.html Singapore Tourism Board. (2004). Fact sheet: Performance of the tourism sector as at January 2004. Available at: http://www.cybrary.com.sg/pages/fact.html Uysal, M., & Jurowski, C. (1993). An empirical testing of the push and pull factors of tourism motivations. Annals of Tourism Research, 21, 844–846. World Tourism Organisation. (1997). Budgets of national tourism administrations. Madrid: WTO. Zhang, H. Q., & Heung, V. C. S. (2001a). Guest editorial: Special issue on China. Journal of Vacation Marketing, 8(1), 5–6. Zhang, H. Q., & Heung, V. C. S. (2001b). The emergence of the Mainland Chinese outbound travel market and its implications for tourism marketing. Journal of Vacation Marketing, 8(1), 7–12. Zhang, H. Q., & Lam, T. (1999). An analysis of Mainland Chinese visitors’ motivations to visit Hong Kong. Tourism Management, 20, 587–594. Zhang, G., Pine, R., & Zhang, Q. H. (2000). China’s international tourism development: The present and future. International Journal of Contemporary Hospitality Management, 12(5), 282–290.

TOURISM ECONOMIC IMPACTS: THE CASE OF EQUINE CAMPING IN SOUTHERN ILLINOIS Kyungmi Kim, Zaher Hallab and Matthew Smith ABSTRACT The purpose of this study was to measure the economic benefits generated from equine camping and to increase awareness of tourism development in southern Illinois. A total of 370 survey questionnaires were collected at equine camping sites. Descriptive analysis revealed that most respondents had at least a high school education with an average annual household income of $64,000. The largest group of respondents by occupation was professionals. About 40% of respondents traveled to southern Illinois with five individuals in a group. The local expenditure model illustrated that nonlocal equine campers brought about 16 million dollars to southern Illinois in 2004. The economic benefits as measured suggested the potential of further developing equine camping as a major tourism activity in this area.

INTRODUCTION Tourism plays a major role in the economy of Illinois. In 2004, over twentyfour billion dollars in tourism revenue was generated from direct travel expenditures in the state (Illinois Bureau of Tourism, 2005). The Illinois Advances in Hospitality and Leisure, Volume 4, 245–260 Copyright r 2008 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1745-3542/doi:10.1016/S1745-3542(08)00012-X

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Bureau of Tourism (2005) also reported that the payroll paid by Illinois travel related ﬁrms, directly attributed to travel totaled nearly $7.8 billion, generated 300,000 jobs, and created about 3 billion in tax revenue for the government. The economic beneﬁts of tourism in Illinois were estimated in the categories of international and domestic tourist expenditures, payroll, employment, state and local tax receipts from industry sectors such as public transportation, auto transportation, lodging, food service, entertainment and recreation, and general retail trade. In 2004, tourists’ spending on public transportation was in the highest category ($6.1 billion), their expenditures on food service ($5.7 billion) ranked second, followed by auto transportation ($5.1 billion) and lodging industry ($4.1 billion) (Illinois Bureau of Tourism, 2005). The report from the Illinois Bureau of Tourism also illustrated the rank of all counties in Illinois by tourists’ expenditure level; the report clearly demonstrated that most of tourists’ expenditures ($20 billion) generated by involvement in tourism-related activities occurred in Chicago and the neighboring urban areas (about 10 counties out of 102 counties). Recreational tourism activities in Illinois such as horseback riding, winery, hunting, ﬁshing, etc. are primarily experienced in rural areas. The total economic impact generated from these activities contributes a small portion of the tourism impact on the State; nevertheless, the economic importance of those recreational activities and the beneﬁts they generate are critical to the economy of rural communities in Illinois. Horseback riding is one of the most popular year-round activities for visitors in the southernmost region of Illinois; however, its economic impact alone has not been measured. Horseback riders usually bring their private horses and stay at numerous private horse camps in and around the Shawnee National Forest, the largest public forested area in the state, which is uniquely positioned to provide visitors with a wide range of outdoor recreational opportunities (Shawnee National Forest, 2006). A total of ten facilities situated in seven counties (Alexander, Johnson, Gallatin, Pulaski, Pope, Hardin, and Union County) have 1,133 campsites and 121 privately owned cabins for accommodation purposes. The privately owned campgrounds and resorts provide access to the Shawnee National Forest and accommodate campers and their equines. During 2003, the Shawnee Forest Horse Camp Association hosted approximately 38,288 visitors and various events including the most major one: ‘‘The 9 Day Trail Ride,’’ which attracted about 2,500 equine campers. The number of visitors counted in 2003 consisted of those who stayed at least one night or more at campsites. The purpose of this study was to measure the economic impact generated from equine camping (one of the major tourist activities in the southern

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247

Illinois), to emphasize its economic magnitude, and to increase state ofﬁcials’ awareness of tourism’s role in the regional economy; their awareness is essential if support for future tourism development in southern Illinois is to materialize. In addition, the research may ﬁnd methods to measure the economic impacts of tourism activities on small regions by combining a small-scale survey and existing data. Tourism Impact Studies There are many different methods that exist for estimating tourism’s economic impact on a tourist destination. One of the popular methods is collecting data from the supply side and measuring the economic impact by using a Keynesian Multiplier Model, which is a measure of the magnitude of regional economic growth generated by the tourism industry (Gelan, 2003; Smith, 1995). However, Gelan (2003) argued that this multiplier model overestimates the direct economic impact generated by tourism. Another method utilizes an impact model from an Input–Output Matrix for a provincial, state, or national economy; the model allows the examination of the ﬂow of tourism speciﬁc input and output by exploring tourism receipts in supply side and expenditures in demand side. Even though this method has been known for its most popular estimation method among researchers, it also has its limitations. It does not capture the dynamic interactions with other sectors in the economy and it usually overestimates some economic variables such as employment (Crompton, Kee, & Shuster, 2001; Dwyer, Forsyth, & Spurr, 2004). To overcome the limitations of the above-mentioned models, several researchers have tried to develop an alternative technique, a strategy labeled as the Computable General Equilibrium (CGE) model. The CGE model represents a much more careful, and advanced approach to estimate economic impacts. The nature of this model implies the possibility of all sectors in the economy being incorporated into a single model; this method allows for examination of shocks or special events in one sector that may have effects on other sectors (Narayan, 2004). The disadvantages of this model is that it requires a signiﬁcant amount of time and cost in order to collect extensive data accruing changes in various sectors, which is the biggest challenge in a small region. More examples on assumptions, advantages, and limitations underlying the use of all the previously discussed methods are well documented in the literature (Archer & Fletcher, 1996; Daniels, Norman, & Henry, 2004; Dwyer, Forsyth, & Spurr, 2004; Frechtling, 2006; Narayan, 2004; Pearce, 1981; Zhou, Yanagida, Chakravortt, & Leung, 1997).

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Local Expenditure Model Small regions have limitations collecting data on employment, and income as well as state and local taxes generated from tourism-related activities. Several studies have tried to overcome such limitations and attempted to implement a model at the local community level that requires less cost and less time and is able to provide basic information pertaining to the economic impacts of tourism on the community (Smith, 1995). Walpole and Goodwin (2000) in their tourism economic impact study used a local expenditure model; the researchers examined the magnitude and distribution of tourism employment and revenue generated to the community from an Indonesian Park. In doing so, they used a small-scale survey method implemented on both businesses (the supply side) and tourists (the demand side). They estimated the level of leakage from the local economy based on proportional expenditures on the import of externally produced goods and services. Even though the researchers speciﬁed that they used a small-scale survey method in their project, their efforts to gather communityrelated data concerning employment, revenues, and the leakage estimation should not be considered insigniﬁcant. Another example on local economic impact studies can be found in the Stynes and Sun’s Sequoia and Kings Canyon National Parks study (2003). Stynes and Sun (2003) estimated economic impacts using the updated National Park Service Money Generation Model which allows an estimation of spending, job and income attributed to the park. The researchers found that park visitors spent $65 million and generated $22.3 million in direct personal income and supported 1,243 jobs in the area. One additional local impact model developed by Frechtling (2006) is based on data derived from simple visitor surveys and information collected from the lodging sector. Frechtling mentioned that the estimation of visitors’ expenditures should include non-residents only and have a signiﬁcant time period, a speciﬁc geographic area, and time frame. This research followed Frechtling’s guidelines on visitors’ expenditure survey and calculated the economic impact using data published in 2005 by the Illinois Bureau of Tourism. The total visitors’ expenditure calculated in this study was based on the following three separate sources of expenditures: accommodation, campground expenditures per trip per group, and expenditures on off-site campground activities per trip per group (Pearce, 1981). The employment, payroll, state tax, and local tax impacts on southern Illinois were estimated based on counties’ tourism economic impact data generated by the Illinois Bureau of Tourism in 2005. Automobile and other en-route expenditures

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were not included because study questions related only to on-site and offsite campground visitor expenditures and accommodations. Therefore, as Smith mentioned in 1995, the total value of tourist expenditures at the destination might be greater than the reported sum.

METHODOLOGY Sampling Design Mail survey for this study was conducted in the spring of 2004. Fifteen hundred questionnaires were distributed to visitors at campground sites in southern Illinois. Visitors were asked to mail back the completed survey in a pre-paid return envelope after ﬁnishing their trip. If the visitors were in a group, the survey instrument was given to only a person in that group. Completing and returning the survey was voluntary. In addition there was no incentive offered to participants and no follow-up was pursued. A total of 370 survey questionnaires were collected (a 24.6% response rate). Among the 370 returned questionnaires, local respondents (visitors who reside in the study region) were eliminated based on zip code. A total of 341 survey questionnaires were further analyzed. All respondents speciﬁed that they stayed at least one night in southern Illinois. Research Instrument A survey instrument was developed to identify expenditure behaviors and socio-demographic characteristics of southern Illinois equine campers; the questionnaire consisted of three parts: (1) various information on visitor expenditures during the equine trip, (2) other trip characteristics, and (3) equine campers’ socio-demographic proﬁles. Respondents were asked to circle the number in a related category that most closely corresponded to their trip and expenditure characteristics.

RESULTS Descriptive Data Analysis Data analysis of the study consisted of two steps. The ﬁrst step conducted a descriptive analysis of demographic, trip, and expenditure characteristics of

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respondents. The second step consisted of employing a local expenditure method to estimate the economic impact of equine camping activity on southern Illinois. Descriptive analysis of this study revealed that 36.3% of respondents who visited southern Illinois horse campgrounds had a high school educational background. Approximately 31% of respondents had some college experience and about 19% of respondents had earned college degrees. Eleven percent of respondents had postgraduate degrees. Total household income of respondents varied from under $20,000 to over $100,000. The annual household income of the largest group of respondents (18%) fell in the range of $50,000–$60,000. The second largest group (15.7%) earned an approximate annual income between $60,000 and $70,000 and the third largest group (15%) made over $100,000. The average household income for all respondents was about $64,000. In regard to occupation proﬁle, the largest group of respondents (18%) consisted of professionals such as lawyers, educators, or doctors. The second largest group of respondents (12%) consisted of trade and technical specialists while the third largest group (11.3%) consisted of retirees (Table 1). In terms of respondents’ trip characteristics, the results revealed that the majority (40.5%) stayed at horse camps for at least 4 days per trip. The second largest group (35.1%) stayed at horse camps for more than 5 days per visit. In terms of distance traveled, Table 2 shows that the largest group of respondents (27.4%) traveled from destinations that are between 201 and 400 miles away from southern Illinois horse camp recreational sites. About 24% of visitors traveled from locations that are between 100 and 200 miles away from the sites. The average distance traveled to southern Illinois campsites was about 200 miles. Even though, most visitors came from Illinois (58.4%), all respondents mentioned that they stayed at least one night in southern Illinois. The remaining visitors came from Indiana (9.8%), Iowa (6%), Wisconsin (4.5%), Kentucky (3.9%), and Tennessee (3.5%). Surprisingly, visitors from Missouri (even though a neighboring state) were only 1%. In regard to the number of individuals traveling in a group, about 41% of respondents, the largest group, traveled to southern Illinois horse camps in groups consisting of more than ﬁve individuals in each. The second largest group (26%) had two people in a group. The third largest group (19%) had four people. The average group size consisted of about four people. In terms of the number of trips to southern Illinois for equine camping, the majority of respondents (38%) visited southern Illinois horse camps more than ﬁve times per year. Twenty-two percent of respondents visited twice per year. About 17% of respondents visited only once a year. The average number of

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251

Table 1. Respondents’ Socio-Demographic Characteristics. Frequency

Percent

8 121 103 64 37

2.4 36.3 30.9 19.2 11.1

Income M ¼ $63,973a Under $20,000 $20,000–$29,999 $30,000–$39,999 $40,000–$49,999 $50,000–$59,999 $60,000–$69,999 $70,000–$79,999 $80,000–$89,999 $90,000–$99,999 Over $100,000

9 17 32 32 54 48 25 23 19 46

3.0 5.6 10.5 10.5 17.7 15.7 8.2 7.5 6.2 15.1

Occupation Non-employed Senior management Middle management Sales/marketing Manufacturing Clerical/administration Professional Trade/technical Labor Farming/ﬁshing Homemaker Government/military Student Self/employed Retired Other employment

4 10 22 14 12 18 66 40 23 20 4 14 4 21 38 26

1.2 3.0 6.5 4.2 3.6 5.4 17.6 11.9 6.8 6.0 1.2 4.2 1.2 6.3 11.3 11.7

Education level Grade school High school Some college Four year college Graduate school

a

M, The average household income.

trips taken by all respondents to southern Illinois horse camps was approximately three trips per year. The type of accommodation patronized by visitors varied from private horse camps to hotel/motel facilities. The majority of respondents (83%) stayed in private horse camps. The remaining visitors (about 17%) stayed in hotel/motels, state parks, and forest service campgrounds (Table 2).

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Table 2. Respondents’ Trip Characteristics. Variables

Frequency

Percent

8 21 53 136 118

2.4 6.3 15.8 40.5 35.1

32 78 82 93 55

9.4 22.9 24.1 27.4 16.2

Number of individuals in the traveling party 1 2 3 4 More than 5

9 87 41 64 139

2.6 25.6 12.1 18.8 40.9

Number of trips per year 1 trip 2 trips 3 trips 4 trips More than 5

58 75 47 28 128

17.3 22.3 14.0 8.3 38.1

Type of accommodation facilities Hotel/motel Private horse camps State parks Forest service campground Bed/breakfast Other None

18 282 4 19 0 9 8

5.3 82.9 1.2 5.6 0.0 2.6 2.4

Length of stay at the horse camp 1 day 2 days 3 days 4 days More than 5 days Distance from residence to the horse camp Under 50 miles 50–100 miles 101–200 miles 201–400 miles Over 400 miles

Table 3 displays expenditure characteristics of the respondents. Expenditures were divided into two categories: on-site campground expenditures and off-site campground expenditures. During the equine camping experience, the average group of respondents spent $181 at on-site campground and $187 at off-site campground locations. Their most favorite off-site hospitality

The Case of Equine Camping in Southern Illinois

Table 3.

253

Respondents’ Expenditure Characteristics. Frequency

Percent

Per visit, how much money do you spend at the campground? Less than $30 17 $30–$50 27 $50–$75 26 $75–$100 47 $100–$200 94 $200–$300 47 Over $300 79

3.6 8.1 7.8 14.2 28.3 14.2 23.8

Expenditure on off-site activities Less than $50 $50–$100 $100–$200 $200–$400 Over $400

30 91 97 67 45

9.1 27.6 29.4 20.3 13.6

314 262 174 142 131 97 82 60 49 46 39 27 23 20 17 11

92.1 76.8 51.0 41.6 38.4 28.4 24.0 17.6 14.4 13.5 11.3 7.9 6.7 5.8 5.0 3.2

Other tourism activities (multiple answers) Restaurants National Forest Historic attractions Shopping mall/centers Antique/craft shops Festivals/special events Lakes Lodging Museums Wine trail Barn trail Other Sporting events Orchard trail Gaming/off track betting Golf

and tourism activities varied and consisted of some of following: dining, visiting national forests and other historic/natural attractions, visiting malls and antique/craft shops, and playing golf. Ninety-two percent of respondents frequented restaurants and 77% of them visited the Shawnee National Forest (Table 3). The average expenditure per visit per group at on-site and off-site campground was calculated by ﬁrst multiplying the middle value of each category by the number of respondents in each category. Then, these values were summed and divided by the total number of respondents.

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Estimation of Economic Benefits from Equine Camping The direct economic impacts generated from the recreational activity of equine camping are summed up based on three different visitor expenditure sources: accommodations, on-site campground expenditures, and off-site campground expenditures. Next, by using the total direct expenditure generated from the equine camping activity and the domestic travel impact report on Illinois counties for 2004, the researchers in this study were able to provide an estimate of the impact in payroll, employment, state tax, and local tax generated from the equine camping activity. This study did not estimate the indirect effect or the induced impact of the equine camping activity. To investigate the economic impact of equine camping on southern Illinois the total visitors’ expenditure on accommodation was estimated by multiplying the following components: the average daily rate of various accommodation facilities, the visitors’ average length of stay, and the number of groups who stayed in each accommodation facility. The average daily rates of all commercial lodging establishments in seven counties were investigated and reported in Table 5. Respondents indicated that they enjoyed equine camping in southern Illinois for an average of 4 days per visit. Shawnee Forest Horse Camp Association reported that in 2003, 38,288 individuals visited southern Illinois with the purpose of engaging in equine camping. Then, the number of individuals staying at each accommodation facility was calculated using two different data: the percentages of accommodations patronized by survey respondents and the total number of visitors reported by the Shawnee Forest Horse Camp Association. In the survey, 83% of respondents indicated that they stayed at private horse camp facilities belonging to ten campground associations; that meant about 31,741 individuals out of 38,288 were considered guests at private horse camps and the remaining visitors stayed at hotels or motels, state parks, or other facilities. Those individuals were divided by the average number of people (3.65) in the travel party (extracted from the survey results) to ﬁnd out the number of groups who stayed at various accommodations. Table 4 illustrates the number of groups who stayed at various accommodation facilities. For example, at private horse camps, 31,741 individuals were divided by the average number of people in the travel party (3.65 people), resulting in 8,696 groups staying at private horse camps. Five hundred and ﬁfty six groups stayed in hotels and motels, 126 groups stayed in state parks, and 587 groups stayed at forest service camps ground (Table 4). Finally, the total amount of money spent by visitors at each accommodation facility was calculated by multiplying the following components: the total

The Case of Equine Camping in Southern Illinois

255

Table 4. Accommodation Facilities Patronized by Visitors. Accommodation Category

The Number of Groups per Patronized Accommodation Facility

Hotel/motel

5.3% of 38,288 ¼ 2,029 individuals 2,029 /3.65 ¼ 556 groups 82.9% of 38,288 ¼ 31,741 individuals 31,741/3.65 ¼ 8,696 groups 1.2% of 38,288 ¼ 459 individuals 459/3.65=126 groups 5.6% of 38,288 ¼ 2,144 individuals 2,144/3.65 ¼ 587 groups 0% 2.6% of 38,288 ¼ 995 individuals 995/3.65 ¼ 273 groups 2.4% of 38,288 ¼ 919 individuals 919/3.65 ¼ 252 groups

Private horse camp State parks Forest service campgrounds Bed and breakfast Other None Total visitors: 38,288

Table 5. Accommodation Category

Hotel/motel Private horse camp State park Forrest service campground Bed and breakfast Other None Total

Respondents’ Total Expenditure on Accommodation Facilities. Number of Groups per Patronized Accommodation Facility

Average Daily Rate

556 8,696 126 587

$62 $20 $15 $5

4 4 4 4

0 272 252

$78 $0 $0

4 days 4 days 4 days

10,489 group

Average Length of Stay days days days days

Total Spending

$137,888 $695,680 $7,560 $11,740 0 0 0 $852,868

number of groups staying at each commercial accommodation, the average daily rate of each accommodation facility, and the average length of stay. In Table 5, the total expenditure amount was $137,888 at hotels and motels, $695,680 at private horse camps, etc. Next, expenditures at each accommodation facility were summed up to obtain visitors’ total spending on accommodation. The results are displayed in Table 5. The total spending by visitors in

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all accommodation facilities was $852,868. The total economic beneﬁt to all accommodation facilities generated from the recreational activity of equine camping was calculated by multiplying the total amount of money spent at all accommodation facilities by the average annual number of trips taken groups (3.39) to southern Illinois campsites Y 1 ¼ $852; 868 3:39; which was $2; 891; 222 Second, the total amount of on-site (at equine campgrounds) expenditure was calculated. Respondents’ average on-site expenditures at equine campgrounds were $180.5 per group per visit. The annual amount of total respondents’ on-site expenditures was calculated by multiplying the following components: respondents’ average expenditures per group, the annual average number of respondents’ trips to southern Illinois, and the number of groups visited southern Illinois. Y 2 ¼ $180:50 3:39 10; 489 ¼ $6; 418; 166 Third, the total amount of off-site (outside the campgrounds) expenditure in southern Illinois was calculated. The average group’s expenditure on offsite activities was $187 per visit. The annual amount of off-site expenditure was calculated by multiplying the group’s average expenditure, the annual average number of trips to southern Illinois, and the number of groups visited southern Illinois. Y 3 ¼ 187 3:39 10; 489 ¼ $6; 649; 292 The total economic beneﬁts from the equine camping activity in southern Illinois were obtained by summing up all three expenditures which amounted to a total of $15,958,680. Next, visitors’ expenditures related to equine camping activity were compared with visitors’ expenditures on all other travel activities in seven southern Illinois counties. Expenditures related to equine camping were $15.96 million (36% of the total expenditures) in comparison to $43.54 million generated from all travel activities in the seven counties. The economic impact of travel on Illinois counties was prepared by the Research Department of the Travel Industry Association of America (TIA) for the Illinois Bureau of Tourism. TIA also reported on the economic impact generated to each Illinois County. The expenditure, payroll, employment, state tax, and local tax impact generated from all tourist activities for the study regions were extracted from the above-mentioned report and illustrated in Table 6. Next, 36% of the positive economic impacts on payroll, employment, state tax, and

The Case of Equine Camping in Southern Illinois

Table 6.

257

The Economic Impact of Travel on Illinois Counties in 2004.

Name of County

Expenditure Payroll (Millions) (Millions)

Employment (Thousands)

State Tax (Millions)

Local Tax (Millions)

Alexander Gallatin Hardin Johnson Pope Pulaski Union

4.69 2.70 5.51 16.38 4.35 3.18 6.73

0.69 0.38 0.91 2.72 0.74 0.53 0.90

0.03 0.02 0.04 0.10 0.03 0.02 0.04

0.32 0.18 0.34 0.97 0.25 0.21 0.47

0.12 0.14 0.38 1.13 0.30 0.10 0.19

Total

43.54

6.87

0.28

2.74

2.36

Economic impact from equine camping

15.82(36.3%)

2.49

0.102

0.99

0.86

Note: The economic impact of travel on Illinois Counties 2004 was prepared for the Illinois Bureau of Tourism by the Research Department of the Travel Industry Association of America, Washington, DC August, 2005.

local tax were considered as a result of equine camping activities. Equine camping activities in seven counties generated approximately $15.96 million in visitor expenditures, $2.49 million in payroll, 102 new positions, $0.99 million in state taxes, and $0.86 million in local taxes.

CONCLUSION It should be emphasized that this study was undertaken to determine the following: the economic impacts generated from equine camping activity in the southernmost counties of Illinois, characteristics and spending habits of the equine camper, and the importance of equine as a tourist activity in southern Illinois. It was noticeable that state and/or federal governments, as well as nonproﬁt organizations own the majority of land where horse trails exist in the lower southern Illinois counties. Tourism-related businesses ensure livelihood for many southern Illinoisans and are also vital commodities to government tax revenue that in turn contributes to the general economy of the region. The equine camp industry in southern Illinois made signiﬁcant economic contributions in 2004; equine camps contributed an estimate of $15,958,680 in visitors’ expenditures and this ﬁgure accounted for 36% of total visitors’ expenditures on all travel-related activities in the region. This ﬁgure may indicate that equine camps contribute more economic beneﬁts than any other

258

KYUNGMI KIM ET AL.

tourist activity in the region. Tourism developers and planners should consider the substantial economic impact of equine camping on southern Illinois and try to support the expansion of this industry for the betterment of the local economy. In addition, this study revealed interesting ﬁndings about the following variables: (1) the distance traveled by visitors to reach southern Illinois equine camping sites, (2) the number of traveling individuals in a group, (3) the socio-demographic proﬁle of visitors, and (4) their spending habits. First, the average distance traveled to reach equine camping sites was around 200 miles. According to the survey results, the largest group of visitors (58.4%) came from Illinois, followed by groups from Indiana (10%), Iowa (6.3%), Wisconsin (4.6%), and Kentucky (4%). The majority of visitors to the southern Illinois region enjoyed tourism-related activities such as horseback riding and equine camping followed by entertainment, dining, sightseeing, and shopping. Interestingly, visitors from Missouri, a neighboring state of Illinois, accounted for only 1% in terms of the number of visitors. This study conveyed that a substantial percentage of visitors (about 9%) came from central states such as Wisconsin (4.6%) and Michigan (3.6%). Such ﬁndings imply that the camping sites in southern Illinois may need to formulate a unique positioning strategy directed at northern middle states like Wisconsin and Michigan stressing the comparative advantage that their camping sites have over those of their competitors. The competitive strategy may also include upgrading equine camping sites in southern Illinois or maintaining roads to southern Illinois. In targeting the various states, southern Illinois needs to add tailored advertising and promotional programs that suit each of the various markets in the different states since each may require unique marketing messages and activities. Second, visitors came to equine camping sites in large groups. The largest group of respondents (41%) reported that they traveled with more than ﬁve individuals. This may convey that equine camping attracts multi-generational family gatherings, such as grandparents, parents, and children. The above ﬁgure may also convey the possibility of more than two families traveling together to visit equine campsites. The second largest group of respondents (26%) had two individuals in its traveling party. Therefore, the promotion of equine camping sites targeting families and couples may be a good idea for attracting more visitors. Based on the signiﬁcant number of couples and families, camping sites may incorporate images and messages on their websites and brochures that reﬂect such a reality (e.g. families having a good time; family bonding).

The Case of Equine Camping in Southern Illinois

259

Third, the proﬁle of the equine camper was not the stereotypical weekend budget camper. The majority of respondents (57%) had some college education and/or graduated from a 4-year college with professional or trade/ technical occupations. In addition, the average household income of respondents was around $64,000. This ﬁgure is far above the median United States household income ($44,347 for the year 2003) and the median Illinois household income ($45,153 for the year 2003). Ownership by respondents of trucks, trailers with living quarters, equine and tack indicate their having the means to make major purchases. Such information may provide camping sites with some marketing implications in regard to pricing strategies and the appropriate media channels (e.g. special interest magazines and newsletters) they should use in advertising and promoting their products and services to these markets. Fourth, the equine camper does not just travel to ride his/her horse, but also to engage in other tourism-related activities. It was noted that dining out (92%), shopping at malls (40%) and antique shops (39%), as well as enjoying historical and culture sites (49%) are also a part of the equine camping visitor experience. Such ﬁndings imply the possibility to establish partnership between camping sites and other regional tourism-related businesses such as restaurants, wineries, antique shops, malls, museums, and historical attractions. It is recommended that future studies be undertaken in several directions. First, similar research should focus on stakeholders (owners of equine camps and hospitality/tourism businesses, non-proﬁt government ofﬁcials, etc.) to cross validate equine camping’s economic impacts on southern Illinois. Secondly, similar research should be conducted to ﬁnd out about southern Illinois residents’ general perceptions on equine camping and its diverse impacts. Local residents may perceive that the horse camping recreational activity generates various positive economic and socio-cultural impacts. For example, they may perceive that their region’s services/facilities and attractions may be upgraded due to the economic beneﬁts generated by equine camping activities. Lastly, it should be noted that the ﬁndings of this study are limited to camping sites in southern Illinois. It is therefore recommended for similar studies to be conducted in other tourist sites such as wine trail and golf trail and in various geographical areas, including those destinations perceived as southern Illinois’ competitors. Such research initiatives may reveal opportunities and/or limitations for future recreational tourism. It is also recommended for future comparative studies to be conducted between southern Illinois and other markets.

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REFERENCES Archer, B., & Fletcher, J. (1996). The economic impact of tourism in the Seychelles. Annals of Tourism Research, 23(1), 32–37. Crompton, J., Kee, S., & Shuster, T. (2001). A guide for undertaking economic impact studies: The springfest example. Journals of Travel Research, 40(1), 79–87. Daniels, M., Norman, W., & Henry, M. S. (2004). Estimating income effects of a sport tourism event. Annals of Tourism Research, 31(1), 180–199. Dwyer, L., Forsyth, P., & Spurr, R. (2004). Evaluating tourism’s economic effect: New and old approaches. Tourism Management, 24(3), 307–317. Frechtling, D. (2006). An assessment of visitor expenditure methods and models. Journal of Travel Research, 45(1), 26–35. Gelan, A. (2003). Local economic impacts: The British open. Annals of Tourism Research, 30(2), 406–425. Illinois Bureau of Tourism. (2005). The economic impact of travel on Illinois counties. IL: Illinois Bureau of Tourism. Narayan, P. K. (2004). Economic impact of tourism on Fiji’s economy: Empirical evidence from the computable general equilibrium model. Tourism Economics, 10(4), 419–433. Pearce, D. (1981). Estimating visitor expenditure: A review and a New Zealand case study. International Journal of Tourism Management, 2(4), 240–252. Shawnee national Forest website. (2006). http://www.fs.fed.us/r9/forests/shawnee/about/ niche_statement/index.php Smith, S. L. J. (1995). Tourism analysis (2nd ed.). Great Britain. Stynes, D., & Sun, Y. (2003). Impact of visitor spending on local economy: Sequoia and Kings Canyon National Park in 2002. East Lansing, MI: Department of Park, Recreation and Tourism Resources, Michigan State University. Walpole, M., & Goodwin, H. (2000). Local economic impacts of dragon tourism in Indonesia. Annals of Tourism Research, 27(3), 559–576. Zhou, D., Yanagida, J., Chakravortt, U., & Leung, P. (1997). Estimating economic impacts from tourism. Annals of Tourism Research, 24(1), 76–89.

SUBJECT INDEX Australia, 58, 162, 185–186, 191, 194–197, 200, 202–204

Inbound tourism, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71

Baby boomers, 185–186, 193, 195–200, 202–206 Balanced score card, 102, 105

Job content, 3, 10, 14–22 Model, 17, 41, 55, 62–68, 71–72, 75, 80–81, 84, 89, 101, 103, 105, 116, 139, 141–143, 146–147, 156, 161, 166–170, 172, 178, 181, 213–215, 217–226, 232, 245, 247–248 Motivation, 10, 142–143, 167, 231–233, 243

Camping, 245–247, 249–259 Chinese visitor, 229, 233, 242–243 Competitiveness, 75–81, 83–85, 87, 89, 91, 93, 95–96, 117, 213, 215, 218–219, 225 Consensus map, 29, 40–42, 46 Core competence, 215–216, 218, 220, 223, 225 Customer equity, 101, 103, 105, 116

Outsourcing, 213–218, 220–226 Population projections, 185–187, 189, 191–193, 195, 197, 199, 201, 203, 205 Psychological contract, 8, 10, 19 Push and pull, 230, 232, 235–238, 240–241, 243

Economic beneﬁts, 245–246, 254, 256–257, 259 Economic impact, 245–248, 250, 254, 256–259 Experience use history, 129

Recreation substitution, 131 Referral, 139, 141–144, 146–148, 152–158 Restaurant, 143, 145–146, 153–157, 161–164, 166–168, 170–174, 176–181, 221–223 Romania, 75–77, 79, 81–96

Forecast, 53, 62, 187, 191 Gap theory, 161, 165–166, 168–169, 173, 175–177, 180–181 Generation Y, 185–186, 193, 196–197, 199–200, 203–206 Globalization, 76

Satisfaction, 22, 104–105, 122, 126, 139–141, 143, 145, 147–149, 151–157, 161–167, 169, 172–173, 175–178, 180–181, 232

Hotel industry, 101–102, 104–105, 107–108, 116–117 261

262 Service quality, 104, 106, 161–170, 172, 176, 178, 180–181, 214 SERVQUAL, 104, 161, 165–170, 172, 174, 178–181 Strategic alliances, 213–214, 217, 220–221, 223, 225–226 Taiwan, 53, 55–61, 63–67, 69–72, 123, 129, 161–163, 165, 167, 169, 171, 173, 175, 177, 179, 181

SUBJECT INDEX Tourism demand, 54–56, 62–63, 66, 70–71, 185–187, 189–191, 193, 195–197, 199–206 Tourism destination, 36, 54, 75–81, 83–87, 89, 91, 93, 95–96, 190, 214–215, 226, 232 Turnover, 3–7, 9, 11, 13, 15, 17, 19, 21–23, 171 ZMET, 29, 31, 33–41, 43, 45–47

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