European Retail Research 2010: Volume 24 Issue II

Dirk Morschett, Thomas Rudolph, Peter Schnedlitz, Hanna Schramm-Klein, Bernhard Swoboda (Eds.) European Retail Research

GABLER RESEARCH Editors Dirk Morschett, University of Fribourg, Switzerland, [email protected] Thomas Rudolph, University of St. Gallen, Switzerland, [email protected] Peter Schnedlitz, Vienna University of Economics and Business, Austria, [email protected] Hanna Schramm-Klein, Siegen University, Germany, [email protected] Bernhard Swoboda, University of Trier, Germany, [email protected] EDITORIAL ADVISORY BOARD In the editorial advisory board, a number of distinguished experts in retail research from different countries support the editors: – Steve Burt, University of Stirling, UK – Michael Cant, University of South Africa, South Africa – Gérard Cliquet, University of Rennes I, France – Enrico Colla, Negocia, France – Ulf Elg, Lund University, Sweden – Martin Fassnacht, WHU - Otto Beisheim School of Management, Germany – Marc Filser, University of Dijon, France – Thomas Foscht, University of Graz, Austria – Juan Carlos Gázquez Abad, University of Almeria, Spain – Arieh Goldman, Hebrew University, Israel (†) – David Grant, University of Hull, UK – Andrea Gröppel-Klein, Saarland University, Germany – Herbert Kotzab, Copenhagen Business School, Denmark – Michael Levy, Babson College, USA – Cesar M. Maloles III, California State University, USA – Peter J. McGoldrick, Manchester Business School, Manchester University, UK – Richard Michon, Ryerson University, Canada – Dirk Möhlenbruch, University Halle-Wittenberg, Germany – Heli Paavola, University of Tampere, Finland – Luca Pellegrini, IULM University Milan, Italy – Barry Quinn, University of Ulster, Northern Ireland – Will Reijnders, Tilburg University, The Netherlands – Thomas Reutterer, Vienna University of Economics and Business, Austria – Jonathan Reynolds, Oxford, UK – Sharyn Rundle-Thiele, University of Southern Queensland, Australia – Brenda Sternquist, Michigan State University, USA – Gilbert Swinnen, Universiteit Hasselt, Belgium – Ikuo Takahashi, Keio University, Japan – Waldemar Toporowski, University of Goettingen, Germany – Volker Trommsdorff, Technical University Berlin, Germany – Gianfranco Walsh, Koblenz-Landau University, Germany – Barton Weitz, University of Florida, USA – Joachim Zentes, Saarland University, Germany

Dirk Morschett, Thomas Rudolph, Peter Schnedlitz, Hanna Schramm-Klein, Bernhard Swoboda (Eds.)

European Retail Research 2010 | Volume 24 Issue II

RESEARCH

Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.d-nb.de.

”Jahrbücher zur Handelsforschung“ were first published at: Physica-Verlag (1986-1988) Gabler Verlag (1989-1999/2000) BBE-Verlag (2000/01-2004) Kohlhammer Verlag (2005-2007) The 24th Volume Issue II is sponsored by

1st Edition 2011 All rights reserved © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011 Editorial Office: Stefanie Brich | Sabine Schöller Gabler Verlag is a brand of Springer Fachmedien. Springer Fachmedien is part of Springer Science+Business Media. www.gabler.de No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the copyright holder. Registered and/or industrial names, trade names, trade descriptions etc. cited in this publication are part of the law for trade-mark protection and may not be used free in any form or by any means even if this is not specifically marked. Umschlaggestaltung: KünkelLopka Medienentwicklung, Heidelberg Printed on acid-free paper Printed in Germany ISBN 978-3-8349-2709-5

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Preface EUROPEAN RETAIL RESEARCH is a new bi-annual that is in the tradition of the reputable book series “Handelsforschung” (Retail Research) which has been published by Prof. Dr. Volker Trommsdorff in Germany for more than two decades. Since 2008, this publication is edited by a team of five retail researchers from Austria, Germany, and Switzerland. The aim of this book series is to publish interesting and innovative manuscripts of high quality. The target audience consists of retail researchers, retail lecturers, retail students and retail executives. Retail executives are an important part of the target group and the knowledge transfer between retail research and retail management remains a crucial part of the publication’s concept. EUROPEAN RETAIL RESEARCH is published in two books per year, Issue I in spring and Issue II in fall. The publication is in English. All manuscripts are double-blind reviewed and the book invites manuscripts from a wide regional context but with a focus on Europe. We respect the fact that for many topics, non-English literature may be useful to be referred to and that retail phenomena from areas different from the US may be highly interesting. The review process supports the authors in enhancing the quality of their work and offers the authors a refereed book as a publication outlet. Part of the concept of EUROPEAN RETAIL RESEARCH is an only short delay between manuscript submission and final publication, so the book is – in the case of acceptance – a quick publication platform. EUROPEAN RETAIL RESEARCH welcomes manuscripts on original theoretical or conceptual contributions as well as empirical research – based either on large-scale empirical data or on case study analysis. Following the state of the art in retail research, articles on any major issue that concerns the general field of retailing and distribution are welcome, e.g. - different institutions in the value chain, like customers, retailers, wholesalers, service companies (e.g. logistics service providers), but also manufacturers’ distribution networks; - different value chain processes, esp. marketing-orientated retail processes, supply chain processes (e.g. purchasing, logistics), organisational processes, informational, or financial management processes; - different aspects of retail management and retail marketing, e.g. retail corporate and competitive strategies, incl. internationalisation, retail formats, e-commerce, customer behaviour, branding and store image, retail location, assortment, pricing, service, communication, in-store marketing, human resource management; - different aspects of distribution systems, e.g. strategies, sales management, key account management, vertical integration, channel conflicts, power, and multichannel strategies.

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Preface

Basically, we seek two types of papers for publication in the book: - Research articles should provide a relevant and significant contribution to theory and practice; they are theoretically well grounded and methodologically on a high level. Purely theoretical papers are invited as well as studies based on large-scale empirical data or on case-study research. - Manuscripts submitted as more practice-oriented articles show new concepts, questions, issues, solutions and contributions out of the retail practice. These papers are selected based on relevance and continuing importance to the future retail research community as well as originality. In addition, the editors will invite articles from specific authors, which will also be double blind reviewed, but address the retailing situation in a specific country. Manuscripts are reviewed with the understanding that they are substantially new, have not been previously published in English and in whole, have not been previously accepted for publication, are not under consideration by any other publisher, and will not be submitted elsewhere until a decision is reached regarding their publication in EUROPEAN RETAIL RESEARCH. An exception are papers in conference proceedings that we treat as work-in-progress. Contributions should be submitted in English language in Microsoft Word format by e-mail to the current EUROPEAN RETAIL RESEARCH managing editor or to [email protected]. Questions or comments regarding this publication are very welcome. They may be sent to anyone of the editors or to the above mentioned e-mail-address. Full information for prospective contributors is available at http://www.european-retailresearch.org. For ordering an issue please contact the German publisher “Gabler Research” (www.gabler.de) or a bookstore. We are very grateful for editorial assistance provided by Marcus Aschenbrenner. St. Gallen, Siegen, Trier, Vienna and Fribourg, Fall 2010 Thomas Rudolph, Hanna Schramm-Klein, Peter Schnedlitz, Bernhard Swoboda Dirk Morschett (managing editor for Volume 24 Issue II)

Contents The Classic Conceptualisation and Classification of Distribution Service Outputs – Time for a Revision? ...................................................................................................................1 Walter van Waterschoot, Piyush Kumar Sinha, Steve Burt, Joeri De Haes, Thomas Foscht and Annouk Lievens Internal Marketing, Market Orientation and Organisational Performance: The Mythological Triangle in a Retail Context ........................................................................33 Prokopis K. Theodoridis and George G. Panigyrakis Information is Useful, but Knowledge is Power! Loyalty Programmes and how they can Benefit Retailers ........................................................69 Steve Worthington and Josh Fear Modelling the Impact of 3D Authenticity and 3D Telepresence on Behavioural Intention for an Online Retailer .......................................................................93 Raed Algharabat and Charles Dennis Integrated Retail Channels in Multichannel Retailing: Do Linkages between Retail Channels Impact Customer Loyalty?............................................................................111 Hanna Schramm-Klein Country Reports The Retail Industry in Spain....................................................................................................129 Maria Puelles, José Antonio Puelles and Susana Romero Retailing in Italy - Players, Strategies and Trends ..................................................................167 Cristina Ziliani, Edoardo Fornari, Sebastiano Grandi, Maria Grazia Cardinali, Daniele Fornari, Francesca Negri and Davide Pellegrini

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The Classic Conceptualisation and Classification of Distribution Service Outputs – Time for a Revision? Walter van Waterschoot, Piyush Kumar Sinha, Steve Burt, Joeri De Haes, Thomas Foscht and Annouk Lievens

Abstract Distribution service outputs structurally play a pivotal role in retail and channel management. This paper critically assesses the nature of Bucklin’s classic formulation, which is concerned with numerically expressible economic benefits resulting from the execution of the distribution function within a perfectly operating economic channel. It is distinguished from postclassic extensions, which provide alternative multi-functional or institutional approaches. The paper captures both approaches in a generic higher-order customer value scheme, which also redefines and broadens the traditional economic benefits. The proposed generic framework also extends to any marketing sub-field and provides the potential for more focused theoretical and empirical research.

Keywords Distribution Service Outputs, Retail(ing) Services, Consumer Benefits

Walter van Waterschoot, Department of Marketing, University of Antwerp, Antwerp, Belgium. Piyush Kumar Sinha, Department of Marketing, Indian Institute of Management, Ahmedabad, India. Steve Burt, Institute for Retail Studies, University of Stirling, Stirling, Scotland. Joeri De Haes, Department of Marketing, University of Antwerp, Antwerp, Belgium. Thomas Foscht (corresponding author), Department of Marketing, Karl-Franzens-University Graz, Graz, Austria (Tel: +43 316 380 7200; E-mail: [email protected]). Annouk Lievens, Department of Marketing, University of Antwerp, Antwerp, Belgium.

Received: January 11, 2010 Revised: July 29, 2010 Accepted: August 16, 2010

EUROPEAN RETAIL RESEARCH Vol. 24, Issue II, 2010, pp. 1-32

D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_1, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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Cause for Concern over a Classic Concept?

To this very day, distribution service output discussions are as prominent in almost any channel management or retailing textbook – or in any corresponding chapter in general marketing textbooks – as they were during previous decades. Distribution service outputs (DO) are typically considered to be one of the cornerstones of our discipline, fostering an understanding of distribution in general, as well as a means of conveying conceptual channel insights and empirical knowledge in particular. The common denominator in these discussions is the conceptualisation and vocabulary summarised by Bucklin in the second half of the 1960s (1966, 1972). Bucklin identified four main DO categories: market decentralisation, delivery time, lot size, and variety. Bucklin’s authoritative summary has become a classic conceptualisation within the discipline. Yet, in spite of its classical status and general acceptance, questions can be raised about its current applicability and relevance. Indeed, although pertinent in earlier decades, one may question the suitability of this traditional classification in the current channel environment and wonder whether, and how, it might have to be revisited. The subject matter covered by DO is structurally, and even unavoidably, central to the discipline. A relevant conceptualisation and classification of utilities, values, and/or benefits enjoyed by customers as a consequence of distribution efforts is quintessential for both academics and managers. It is helpful in addressing channel management issues such as customer preferences and segmentation; performance and efficiency analyses of the channel and/or of individual channel members; the development of (multiple) channel strategies and of vertical and horizontal distribution systems; and the delineation of strategic groups of channel agents and competition among them. In itself, therefore, there can be no discussion about the relevance of the conceptual and empirical field covered by distribution outputs. However, the ‘classic’ DO can now be challenged with respect to their capacity (and actual role) to serve as the unquestioned representative conceptualisation, in terms of both suitability and representativeness. Questions can be raised as to whether the classic DO needs to be revisited, and if so, how this might be achieved. These questions are what this paper aims to address. The aim of this paper is to critically assess the current relevance of the ‘classic’ DO concept. We start by reviewing and interpreting the ‘classic’ and ‘post-classic’ DO conceptualisations and continue by analysing the corresponding content of channel management and similar textbooks. We then consider whether the DO concept should be broadened beyond the traditional considerations of economic benefits and financial price elements, and of physical goods and physical channels. Consequently, a revised generic DO concept is proposed, along with a generic customer value framework, to capture both specific and related DO concepts. Finally, we conclude with suggestions for a further research agenda.

van Waterschoot, W., et al.

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The ‘Classic’ Distribution Service Outputs Concept

The ‘classic’ distribution service outputs are a traditional set of (typically) numerically expressible operational concepts, providing specific economic benefits for the customer, following from the execution of the distribution function, by whoever assumes that function partly or completely (Bucklin 1966; 1972).

2.1.

Historical Roots

The historical roots of the classic DO go back to the emergence, mainly by the end of the 19th century, of a new exchange model resulting from substantially changing market circumstances in the Western world, (Fullerton 1988; van Waterschoot et al. 2006; van Waterschoot and De Haes 2008). This emerging exchange model was literally new at the time, even if today it is either implicitly or intuitively assumed by marketing researchers and practitioners and to some extent also by economists. This new exchange model differed dramatically from the one traditionally assumed by economists at the time. The new model implied heterogeneous, more or less non-transparent (actual as well as potential) buyers markets, structurally necessitating four generic exchange functions: a product conception function, a pricing function, a communication function, and a distribution function (see Figure 1). The new exchange model broke away from traditional economics and gave rise to a new discipline called marketing. In its early days, however, the new discipline – in spite of its dissident nature – was still greatly influenced by traditional economics before becoming a truly multidisciplinary body of thought. It was therefore rightly called marketing economics by some (Alderson 1954, p. 37). Traditional economics, for its part, reacted conservatively, slowly, and reluctantly to the emergence of the new exchange framework. Consequently, marketing (economics) and traditional economics mainly developed in parallel to each other, but with some interaction. The classic distribution service outputs are the crystallisation of (distribution) evolutions within marketing (economics), but also result from the crossfertilisation with evolving traditional economics. Figure 2 provides a chronological overview of the major contributions to the classic DO conceptualisation and classification. The first explicit date on the time axis is 1902 when the term marketing was formally used for the first time as a course title by the Harvard Business School (Bartels 1962). Other dates refer to the year of publication of major DO ideas. The first half of the 20th century was influenced by two schools of marketing thought. The institutional school focused on the activities of typical channel participants, such as wholesalers or retailers, while the functional school focused on the functions that were carried out within the channel, such as sorting or accumulating merchandise (Sheth et al. 1988). The conceptual development of DO in the latter part of the century was influenced primarily by a functionalist

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school that approached the topic from a systems or interactive perspective, addressing issues such as the optimal allocation of distribution activities among participants within a channel. The upper part of figure 2 identifies contributions from general economics and the lower part contains the contributions and less abstract definitions derived from marketing economics (Alderson 1954, p. 37). The figure also shows the interaction between general economics and marketing economics, leading to Bucklin’s integration. Figure 1: The New Exchange Model

Source: van Waterschoot et al. (2009).

Bucklin’s (1966) publication provided a clear definition of the DO concept and its four main classes: market decentralisation, lot size, waiting time, and variety. Although Bucklin (1966; 1972) did not explicitly name or discuss the subclasses of market decentralisation and variety, which had been proposed by earlier authors, his texts and modelling imply these dual ideas. Bucklin’s (1966) typology contains by far the most representative traditional DO integration and has become the classic reference based on its enduring popularity in textbooks (see Table 1).

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Figure 2: The Historical Evolution of the Classic Distribution Service Output Concept and Classification

2.2.

Interpretation of the ‘Classic’ Distribution Service Outputs Framework

Bucklin’s framework is concerned with the translation of non-traditional forms of economic utility viz. time, place, and possession utility (Alderson 1954). These forms of utility become relevant once the 19th century economists assumption of the coincidence of production and consumption in time and space is relaxed. Non-traditional forms of economic utility require less abstract, more operational, constructs. However, as these constructs remain essentially economic in nature, they fit best within the discipline of marketing economics (Alderson 1954), which represented a transition stage between 19th century general economics and modern multidisciplinary marketing. The interpretation of marketing economics differed however from that of general economics because of the important role distribution began to play. In marketing economics, the distribution function was performed by one or more channel participants and was governed by channel mechanisms of a strictly economic nature within a normative channel (Bucklin 1966). The pricing function remained unaffected, since channel participants were still price takers. The communication function became more important, to the extent that information gaps existed. However, its role was not to persuade customers on subjective, perceptual grounds, as their behaviour was still viewed as rational and economic. Similarly, product differentiation was still largely regarded as being objective and functional. From the 1950s, marketing thinking became genuinely multidisciplinary; therefore the underlying nature of the classic DO concept may have become anachronistic.

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In spite of some similarities between the abstract utility concepts from general economics and the operational concepts of marketing economics, there is no one-to-one correspondence between them. “Delivery time, for example, is related to both time and place utility. Place affects the service because greater distance typically imposes more costly means for providing fast delivery. Market decentralisation is related most closely to ownership utility, but may play a role in time utility as well” (Bucklin 1966, p. 8). Market decentralisation consists of two sub-classes. The first is a benefit offered to the customer by bridging a geographic gap (Alderson 1954), termed spatial decentralisation (or spatial convenience) by Coughlan et al. (2006). The second is a benefit offered to the customer by bridging an information gap (Stigler 1961). Furthermore, time-utility may be delivered by the financial function or by the production function. Variety also consists of two sub-classes. The traditional sub-class is one of breadth of assortment, referring to the number of product-categories being distributed together (Weld 1915). Depth of assortment, seen as the availability of several alternatives within a product category, is the second sub-class and is also recognisable in the discussions on sorting by Alderson (1954) and Bucklin (1966). In terms of functionality, the classic outputs have a rather strong – even if imperfect – commonality. With respect to their primary origin, five of the six DO classes and sub-classes result from the distribution function. This should not exclude, however, secondary functionality interacting with the primary function. A comparison can be made with marketing mix instruments, which typically serve one primary marketing mix function, next to several secondary ones (van Waterschoot/Van den Bulte 1992; van Waterschoot/De Haes 2001). The sixth DO sub-class, informational decentralisation, does, however, have a different origin, as it is a primary output of the communication function and is only linked to the distribution function in a secondary fashion. The historical and conceptual relationship between non-traditional utility forms and classic DO interpretations suggests that the outputs themselves are of a multi-conceptual nature. As stated earlier, classic DO in their traditional descriptions typically fit the assumptions of the marketing economics discipline. They are concerned with economic benefits, with barely any perceptual or subjective interpretation. The exception is the sub-class depth of assortment, which logically fits a differentiated, heterogeneous market. In contrast to most of the other classic DO, depth of assortment is a service output that is closely aligned to multidisciplinary marketing assumptions. Even when objectively differentiated markets exist, subjective differentiation naturally follows – especially in consumer markets. The sub-class depth of assortment is, therefore, an outlier in terms of assumed market background. As argued above, the subclass information decentralisation is an outlier in terms of functional origin. But these two nuances notwithstanding, we may logically accept that the different classic DO categories

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basically belong to the same family, are part of the same concept, and consist of four related core classes. The discussions leading to the classic integration typically make use of illustrations taken from the field of consumer goods, usually physical goods of a relatively elementary nature, at the (brick and mortar) retail stage of the distribution channel. The original sources contain no explicit arguments about the applicability of the concept to subfields of marketing, such as service marketing, non-profit marketing, and e-marketing. The limitations of the original setting may explain the choice of the expression distribution service outputs, suggesting intangible distribution values added to tangible goods.

3.

Post-classic Distribution Service Outputs Frameworks

A number of frameworks have followed from the original conceptualisation, which have implications for how the DO concept is interpreted and applied (see Figure 3). In comparison to classic DO, most post-classic DO frameworks take a fundamentally different stance. They no longer consider DO as the benefits resulting from the execution of the distribution function alone. Instead, they look at DO as the benefits resulting from a broader set of related functions. Post-classic DO models typically add communication and production functions, in various forms, to the distribution function. Figure 3: The Historical Evolution of the Post-Classic Distribution Service Output Frameworks

By adding communication, subjective issues like product and channel differentiation should theoretically become important. However, the only explicitly subjective element is ambiance,

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as proposed by Betancourt and Gautschi (1988). In all other instances communication is still considered to be objective. The post-classic DO frameworks simply extend the classic normative channel view of marketing economics. Through the addition of elements like installation and warranties, post-classic DO-frameworks also incorporate production functions. These shifts are conceptually so enormous that the resulting typologies should be seen not merely as adaptations or improvements, but as different, albeit related, schemes. In addition, the institutional interpretation (who performs these activities) that was sporadically evident in the first half of the 20th century, is present in some of these contributions. These shifts from the traditional viewpoint are important in the sense that they reflect distinct but related concepts and classifications. Post-classic DO-models do not, however, solve the questions raised by the classic conceptualisation and classification, but rather confirm and extend them to related viewpoints. Customer values are still essentially confined to economic motivation. Furthermore, it is also doubtful whether the post-classic typologies (as with classic DO) successfully meet the desirable classificatory properties identified by Hunt (1991). The requirements of collective exhaustiveness, mutual exclusiveness, positive definition of the classificatory dimensions, and resulting types seem not to be fully present in all instances. On the positive side, the applicability to industrial marketing is much more explicitly made in the post-classic models than in the classic conceptualisation, but other marketing sub-fields are still not explicitly dealt with. Post-classic frameworks, therefore, only serve to make the earlier questions more pertinent and complex. However, before attempting to answer them, it is important to establish which particular view of DO is taken and to identify the appropriate terminology to be used. The four DO-views that seem most relevant are: - distribution-function (service) outputs (DFO) – the classic view - exchange-function (service) outputs (EFO) - exchange- and production-functions (service) outputs (EPFO) - distribution-specialist (service) outputs (DSO) – the institutional approach. We shall return to this typology later in the paper.

4.

Time for a Revision?

Part of the answer to the question of whether it is time for a revision of the classic DO can be found in the way the classic concept and classification is being conveyed to end users via channel management (and similar) textbooks. Textbooks typically contain crystallised knowledge (van Waterschoot/Gijsbrechts 2003). They are typical of the retail stage of the communication of knowledge. Textbooks are generally indicative of what belongs to the accepted body of thought of the discipline. They may report or reflect shortcomings in that body of thought (for which textbook authors are not necessarily to blame). They may suggest

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new directions of thought; they may provide inspiration as to which ideas seem more relevant and which seem less relevant. Table 1: Categorical Summary of Textbook Content Analysis Discussion of Classic DO Concepts &

Largely Explicit/ Literal/ Identical/Identified

Somewhat Explicit/ Literal/ Identical/Identified

Limited to classic DO without any extended concepts

Stern et al. 1996, pp. 16-17 (DFO)

Bradley 1995 (DSO); McCarthy and Perrault 1993 (DSO/DFO); Pride and Ferrell 1991 (DSO/DFO)

Somewhat extended beyond classic DO in number or nature of concepts

Baker 2000a (EPFO);

Doyle 2002 (EPFO);

Berman 1996 (EPFO/ DSO); Couglan et al. 2006 p. 43 (DFO); Kotler 2000 (EPFO/

Jobber 1995 (DSO/EPFO); Jobber 2001 (DSO/EPFO); Levy and Weitz 1992

DFO); Pelton et al. 2002 (EPFO); Stern et al. 1996, p. 196

(DSO/EPFO); Pelton et al. 2001 (DSO/EPFO); Rosenbloom 1999

(EPFO)

(EPFO); Shaw and Ennis 2000 (EPFO/DSO)

Classifications

Implicit/ Not Literal/ Not Identical/Not Identified

Lambin 2000 (EFO)

Armstrong and Kotler 2005 (EPFO); Baker 2007 (EFO); Boyd et al. 1995 (EPFO/DSO); Bradley 2003 (EPFO); Bradley 2003 (DSO); Couglan et al. 2006 p.58 (EPFO); Davidson et al. 1988 (DSO/EPFO); Jobber 2006 (EPFO); Kotler and Armstrong 2005 (EPFO); Kotler et al. 1996 (EPFO); Lambin 2007 (EFO); Levy and Weitz 2007 (EPFO/DSO); Lucas et al. 1994 (DSO); Mason et al. 1993 (DSO) ; Mullins et al. 2006 (DSO/EPFO); Newman and Cullen 2002 (DSO); Peter and Donnelly 1995 (EPFO); Peter and Donnelly 2004 (EPFO); Rosenbloom 2004 (DSO/EPFO); Sullivan and Adcock 2002 (DSO)

Substantially extended beyond classic DO in number and nature of concepts

Kotler and Keller

Bearden et al. 1995 (DSO/EPFO); Bearden et al.

2006 (EPFO)

2005 (DSO/EPFO); Best 2000, pp. 204-205 (EPFO); Best 2005 (EPFO); Berman and Evans 2007 (EPFO); Brassington and Petit 1997 (DSO/EPFO); Brassington and Petit 2003 (DSO); Doyle and Stern 2006 (EPFO); Levy and Weitz 1995 (DSO); Perrault and McCarthy 2005 (EPFO); Pride and Ferrell 2007 (EPFO); Stern et al. 1996, pp. 196-218 (DSO); Urban and Star 1991 (EPFO/DSO); Zikmund and dAmico 1996 (EPFO/DSO)

Note: DFO = Distribution-function (service) outputs; DSO = Distribution-specialist (service) outputs; EFO = Exchange-functions (service) outputs; EPFO = Exchange-and-production-functions (service) outputs.

Textbook authors can be seen as experts situated close to end users – skilled and well informed about the body of thought being published and also orientated towards the needs of the end users of knowledge. Their wisdom, expertise, and insight are available on paper. In brief, studying textbook discussions is similar to making use of the knowledge of textbook authors in the form of a virtual think tank. We therefore carried out a content analysis of some 60 international textbooks on channel management and retailing and, additionally, also of some textbooks on general marketing management which contained a substantial DOdiscussion. In view of the subject matter, a relatively wide time span is called for, which

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might even cover a whole century. However, it is arguably more feasible and relevant to choose a more recent period. By focusing on textbooks published during the last two decades, recent shifts could be studied. Practically speaking, the textbooks were taken from the university library of two of the authors, who also served as judges for the content analysis. Next to a convenience element, the sample also implies a major judgment element, since the budget constraint of that library requires a deliberate selection of only the highest quality textbooks. The judges are educators, researchers and authors of papers and textbooks in the area studied and also academic advisors for library orders in the same field. The DO discussions were critically analysed in terms of how closely they matched the original Bucklin publication. The basic interpretation of the textbook authors was studied in terms of institutional versus functional views. In addition, the added elements, if any, were studied together with possible explicit comments on the classic conceptualisation. Finally, attention was paid as to how DO were generally communicated e.g. in terms of origin, background, relevance, completeness and field of application. The summary of the results of the textbook content analysis is available in Tables 1 and 2 and reflect the following main conclusions: - Textbooks, almost without exception, include at least the core elements of the classic summary provided by Bucklin. Bucklin’s summary has become traditional subject matter of textbooks, apparently belonging to the accepted and unquestioned heritage of the discipline. Textbooks also very often include the classification (or elements thereof) of Alderson, which is closely akin to Bucklin – be it in micro-economic jargon. The Bucklin and Alderson concepts and terminology are often blended by textbook authors. - Most textbooks, however, reproduce the classic distribution service outputs in a relatively improvised way. The reproduction typically does not take place in a very precise, literal, identical, and identified way. The discussions of classic distribution outputs are, instead, of a more or less implicit, not literal, nature – not completely identical and not identified. For example, no literal quotes are used and only seldom is a literature reference added. A comparison of the textbook sub sample from this decade, with the one belonging to the previous decade, reveals that the direct link with the original Bucklin publications weakens over time, in spite of the apparently permanent popularity of the classic classification. - At first glance, textbook discussions and definitions look quite similar. However, when they are given a closer look, they are seen to contain deviant viewpoints in terms of the fundamental origin of distribution service outputs. Some textbooks rely on a functional origin, in line with Bucklin’s view or with post-classical views, whereas others predominantly describe an institutional background. Sometimes text excerpts within the same textbook may mutually differ in this respect. - As is the case with post-classical academic publications, the (growing) majority of textbooks often add different types of functions and outputs to the classic ones – albeit in an

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informal way. There appears to be a similarity among textbooks in the sense that they typically expand beyond the classic DO. But, in this respect, a closer look reveals that this is not true. The content is far from identical, even if there is some common theme, which is not formally identified or discussed. The added functions and outputs are not systematically based on any standard conceptual or empirical framework. Textbook discussions represent many variations on a theme. They are typically intelligent improvisations, which do have commonalities, but which are not formally based on any common framework and have not yet been summarised in any common framework. Table 2: Numerical Summary of Textbook Content Analysis Explicit Reproduction Classic DO

Reliabilities 1

Largely explicit

15 %

No hesitation

59 %

Somewhat explicit Implicit

19 % 66 %

Hesitation 1 expert Hesitation 2 experts

37 % 4%

Perfect match2 Partial match

61 % 35 %

Extensions of classic DO No extensions Somewhat extended

9% 63 %

Substantially extended

28 %

3%

No match

(Multi-)functional vs. Institutional View Dominant view only DFO EFO EPFO DSO Dominant or secondary view DFO EFO EPFO DSO

Reliabilities

3%

Both experts 1 interpretation

3

44 %

6% 50 % 41 %

One expert 2 interpretations Both experts 2 interpretations

37 % 19 %

7% 4% 51 % 38 %

4

Perfect match Partial match

54 % 31 %

No match

15 %

Note: 1 No hesitation means that both experts were certain about their judgment. Hesitation means that one expert (both experts) found it difficult to draw a conclusion. 2 Perfect match means that both experts agree on both dimensions. A partial match means they agreed on only one of the two dimensions. 3 Reflects the number of DOinterpretations the experts recognized in the textbook excerpts. 4 A perfect match means that both experts agree on both dimensions. A partial match means that in case of multiple interpretations at least one of the views matched.

- Whereas classical distributions service outputs – in line with their background in marketing economics – focus on functional customer needs, textbook discussions often also include benefits which are other than functional. For example, emotional benefits (such as store

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atmospherics) are discussed. There is no common framework, but again textbooks contain intelligent, more or less similar variations on a theme. - Some of the textbooks explicitly underscore the relevance of DO for less traditional applications such as service distribution. Most of them, however, remain silent in this respect. Textbooks also remain silent with respect to the explicit integration of DO into a more encompassing framework, and about any explicit delineation of the field of application. By reading between the lines of the discussions, the necessity of an embracing framework becomes apparent. Overall, although the classic conceptualisation enjoys an enduring popularity, closer investigation of textbook descriptions confirms that this typology (increasingly) suffers from different types of sclerosis, pressure, and confusion. It is clear that textbook authors struggle with the anachronisms of the classic concept, and they combine it with related concepts. This blurring of the original concept suggests that its current value and applicability urgently requires further examination and revision. The content analysis of textbooks also suggests some concrete directions for any revision. The earlier review showed that the classic DO concept was originally developed for physical goods sold in physical stores. It was concerned with numerically expressible economic benefits to the customer, resulting from the execution of the distribution function. The emphasis was therefore typically more on quantifiable benefits and less on possible qualitative aspects. The price paid for these benefits was expressed in financial terms, resulting from pure market forces (within the so-called normative channel). One outcome is that the classic concept remains underutilised outside its original field. It is rarely applied to other sub-fields such as service marketing, even when there does not seem to be any objective grounds for this. Another issue is that its grounding in marketing economics makes it anachronistic from the perspective of the current multidisciplinary body of marketing thought. Any revisions to the classic concept so far have not tackled these fundamental issues – they merely extend the debate to related concepts. Even Bucklin et al. (1996) mention the lack of integration of relevant theory in the context of industrial markets. Despite these shortcomings, DO represent a structurally central concept within the marketing discipline. As such, the area requires a clear conceptualisation; and the absence of any generally accepted core framework is a hallucinating, objectionable idea. Any alternative concept, denoting the benefits delivered by a major exchange function, would also be structurally central to the discipline. There is, therefore, a clear justification for a revision of the classic conception. Thus we propose a revision agenda comprised of four stages.

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Revision Agenda Stage I: Broadening the Classic Conceptualisation of Distribution Service Outputs

The first stage in the revision agenda requires the classic concept to be explicitly enlarged and made compatible with the general assumptions of the overall marketing field (e.g., by the inclusion of non-economic, emotional benefits) and with the peculiarities of any specific subfield (e.g., service marketing).

5.1.

Beyond Economic Utilities and Monetary Price Elements

Wilkie and Moore (1999), in their extensive deliberation on the scope of marketing and its contributions to society, concluded that marketing not only produces economic benefits for consumers, but also provides a whole range of social and psychological benefits: “Marketing encompasses more than […] the economic calculus that reports on the system as if it were a relentless machine spewing out streams of utilities. Instead we examine briefly the aggregate marketing system as a human institution composed of people living their lives on a variety of fronts” (Wilkie/Moore 1999, p. 198). They argued that the overall marketing system generated identifiable non-economic benefits in a whole range of situations. Skipper and Hyman (1990) suggest that this perspective can be extended to the major subsystems and functions of marketing, including distribution. The previous, predominantly deductive, reasoning underlying theory can be compared to the inductive results from studies. Tauber (1972), for example, asked, “Why do people shop?” as opposed to, “Why do people shop in more than one store?” (Comparison-shopping) and, “Why do people shop where they do?” (Store patronage). The question considers the satisfactions that shopping activities per se provide, in addition to those obtained from the merchandise purchased. The implication is that DO concepts should be broadened beyond purely economic utilities to reflect reality. Just as the benefits of the distribution function extend beyond economic utilities, the disadvantages or costs following from it will also extend beyond financial costs. Baker et al. (2002) indicate that even within an abstract framework of economic behaviour, modern economists incorporate more than just the financial price of a transaction and emphasise considerations other than time/effort costs in retail settings. Environmental psychologists such as Mehrabian and Russell (1974) regard these costs “as consumers negative affective reactions to a store and/or its environment”. Although these considerations have arisen from the context of retailing consumer goods, it is likely they hold – to a differing extent – in other channel settings and at other channel levels. Thus, it is important to allow for non-monetary price elements in a more comprehensive DO-concept.

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5.2.

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Beyond Physical Consumer Goods in Physical Stores

The typical channel descriptions of Bucklin (1966) and his predecessors only concerned physical goods sold in physical stores. However, as part of the process of attaining economic equilibrium in a channel, other DO occur at channel levels preceding the retail level (Breyer 1964). The organisation of any trade is characterised by the extent to which the functions are divided among middlemen. Yet this aspect of within-channel interaction is seldom discussed, especially in connection with DO aspects at the retail level. Although economic service outputs will predominate at these intermediate levels, non-economic service outputs also exist. It is logical that they might also appear in other marketing settings (Skipper/Hyman 1990). Service marketing is a situation where distribution, production, and communication coincide (Berry 1980; Zeithaml/Bitner 1996). As a result, concepts derived from the (separate) execution of such functions – a classical DO concept – would be non-applicable. However, we propose that the production of a service and its distribution are not conceptually identical. The execution of the respective functions delivers distinct utilities or benefits, even in the situations where there is overlap. Lovelock (1983) argues that the methods of service delivery differ in the case of the customer coming to the service organisation or vice versa, and also between the availability of a single service outlet versus a multiple set (see also Rosenbloom 2004, p. 497). If the production and distribution of services were identical and coincidental from every point of view, they would be strategically and tactically inseparable. Hence one would not be able to vary the distribution elements while keeping the service product constant. Similarly, the production of the service product and its communication are not identical. In situations where production and communication of the service product do coincide, different combinations of the two can be planned and implemented. Thus, there is no reason to doubt the applicability of the classic DO concept to service marketing. Lovelocks paper provides no explicit discussion of non-economic DO, yet many of his examples illustrate a range of non-economic satisfactions or dissatisfactions. The emergence of e-marketing also represents a challenge for the DO concept. Bucklin and his predecessors developed the concept when physical distribution and the dissemination of information largely coincided. Information followed “the linear flow of the physical value chain” (Evans/Wurster 1997, p. 73). An earlier discussion of that issue was conducted by English (1985). The widespread connectivity between almost all market parties irrespective of size and location changed the rules of value creation, questioning the relevance of the traditional DO concept. The Internet is simply a means of communication between consumers, marketers, and millions of other organisations within a channel structure that allows the diversion of all or part of distribution activity to other channel members (Coupey 2001; Bello et al. 2002). On one hand an additional challenge in e-commerce-environments is the aspect of disintermediation which is emphasised strongly in one part of the discussion (Peterson et al.

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1997; Tamilia et al. 2002). On the other hand, re-intermediation also takes place and can also be seen as a new challenge for distribution considerations. Coupey (2001) suggests that the increased participation of Internet-based organisations will take three main forms: information brokers, transaction brokers, or marketplace concentrators. Mottner et al. (2002) developed a typology of Internet retailers, and they came up with three clusters – namely the product focused retailer, the retailer with a micro segment focus, and the developed intermediaries (see also Tamilia et al. 2002). However, the resulting marketing phenomena do not necessarily entail new types of utilities or satisfactions (see e.g. Young et al. 2007) nor new functions. Emarketing is still concerned with the delivery of known types of benefits and functions by new and existing channel members in different combinations (Coughlan et al. 2006, p. 451; Rosenbloom 2004, p. 437). One aspect upon which the discussion is focused in many works is the efficiency or performance aspect of the Internet (Peterson et al. 1997; Bello et al. 2002; Tamilia et al. 2002). Although it seems to make sense to consider the Internet-specific issues to some extent isolated, the Internet basically cannot be considered in isolation or limited to online commerce (Peterson et al. 1997, p. 330). Therefore, the Internet and e-marketing do not make the DO concept irrelevant, rather they reinforce the need for a sound conceptualisation in order to analyse, describe, forecast, and prescribe these new phenomena and choices such as multi channel retailing (Levy/Weitz 2007; Wallace et al. 2004).

5.3.

The Limitations of the DO Application Fields

The question arises as to whether DO become a concept without limitation as a result of our broadening proposals. The application fields of individual marketing exchange functions are wider than the combined ‘marketing’ field and only limited by their own particular subject matter (see Figure 4). Communication is broader than marketing communication. The same goes for distribution. The conceptual borderline of the marketing discipline is determined by the combined application of all four generic marketing exchange functions between any organisation and any public (Kotler/Levy 1969a; 1969b; Lazer 1969; Luck 1969; Marketing Staff of the Ohio State University 1965; Hunt 1976b). Conceptually speaking, therefore, the application field of DO is broader than the marketing discipline. However, the overlap is complete from the point of view of the marketing field itself. From this interpretation it follows that DO is both relevant and applicable to any marketing sub field, such as service marketing or e-marketing. One can argue that marketing exchange cannot possibly take place in any marketing subfield, unless the classic DO are generated as a consequence of the particular distribution approach.

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Figure 4: Application Field of Exchange Functions

The specific origin, form and magnitude of DO, however, depend on many situational aspects. Different fields of application like e-marketing might have typical compositions of classic DO in comparison to other fields. But by definition, they unavoidably imply classic DO in one form or another. The marketing approach of insurance brokers for example cannot but imply consequences in terms of classic DO. For example, if they decide to sell travel insurance online, waiting time and decentralisation are affected dramatically in comparison to a more traditional approach. Also non-profit organisations like Oxfam operating (e-)stores need to make marketing mix decisions just like any other retail store chain, unavoidably implying consequences in terms of classic DO. For non-classic DO considerations, however, the matter is somewhat different. They are not strictly unavoidable from a functional perspective, whereas classic DO are necessary to fill distribution gaps, because otherwise no exchange could possibly come about. For example, if channel participants together do not deliver sufficient decentralisation benefits, then no exchange will take place. Non-classic DO, however, are not strictly necessary to fill distribution gaps. Theoretically consumers might purchase fashion clothing without any atmospheric benefits being offered by the distribution process. However, atmospherics may be very important and even decisive in creating and maintaining store and brand preference. So, whereas classic DO do prevail by definition in any actual channel, this is not the case for non-classic

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DO. That said, non-classic DO like psychological, social and epistemic benefits may play a part in any situation, even if that is more likely for some situations (e.g. in retailing) than for others. This does, however, not mean even at distribution stages, which are typically more rational and less emotional, that non-classic DO might not be at play (see examples in Figure 5 and 6). So, from the point of view of an encompassing or generic scheme, nonfunctional need categories have to be available for any situation and cannot a priori be excluded. The encompassing framework should therefore be universal, all embracing and generic and consequently leave room for any situation including less common ones.

6.

Revision Agenda Stage II: Incorporating Distribution Service Ouputs into a Generic Higher Order Concept

The second stage in the proposed revision requires the classic DO concept to be redefined within a generic or higher order conceptualisation. This shifts the focus from the ‘classic’ concept per se to a higher order concept. The ‘classic’ concept is no longer an isolated concept, but becomes one of a set of mutually related sub-concepts generated by a more fundamental or all-embracing concept. A revised classic distribution service output framework can fairly easily capture both a broadening of motivation categories (e.g., social needs), as well as a broadening in terms of types of marketing applications (e.g., service marketing). Even a broadened DO concept, however, is on its own not capable of hosting a number of closely related concepts. This is an insurmountable difficulty arising from the non-distributive functions and corresponding outputs put forward in the post-classic DO views. This structural problem for any revised classic DO concept, and the corresponding necessity for a higher order concept, follows from the nature of generic exchange functions (e.g., distribution and communication), the nature of marketing channels, and corresponding specialists, as well as from the nature of other channel participants – producers, consumers and their possible generation of service outputs. By definition, the generic distribution function and its inherent specific distribution functions provide distribution service outputs and nothing but distribution service outputs. The provision of distribution benefits by channels, channel participants, and intermediaries on the other hand does not possess this one-to-one relationship. By definition the predominant function(s)/activity of distribution specialists/intermediaries are distribution activities, and so by definition their predominant output consists of distribution service outputs. In line with their definition, however, distribution specialists may combine their distribution activities with other sorts of activities (such as communication or production) without losing their character as distribution specialists completely, as long as the latter activities are secondary. Practically speaking, such combinations occur more and more frequently. Distribution channel interme-

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diaries assume responsibility for customer instructions, advice, installation, repairs, etc. This trend is a major explanation for the existence of the post-classic DO concepts. As a result, distribution specialists may – and actually do – not only exclusively deliver distribution benefits/values but, more often than not, also deliver outputs/consumer benefits related to other functions (of an exchange and/or of a production nature). Vice versa, channel participants other than distribution specialists, for example those specialised in production or consumption or in exchange functions other than distribution, may themselves assume distribution functions to some extent, and consequently deliver distribution benefits, without losing their prime mission. Communication specialists (e.g., Internet infomediaries) may also engage in distribution; e.g., by delivering virtual products such as video films. Thus, because on the one hand distribution specialists and channels may also provide benefits other than distribution benefits, and because on the other hand nondistribution specialists or other sorts of channels may also deliver distribution benefits, a strictly distributive only framework is too limited to capture mixed cases/concepts. The relatively hybrid family of related concepts extends beyond strict distribution concepts. To be capable of capturing these post-classical concepts (which is highly desirable), a more embracing or higher concept is required. This is not only advisable; it is much needed and unavoidable. Simply ignoring post-classic developments (and similar future ideas) is not an option. A purely distributive based framework can therefore not possibly serve as a generic concept for hosting them. Either an explicit conceptual conflict would be created – due to claiming to embrace concepts which cannot possibly be embraced – or an implicit conceptual conflict would arise – as a result of vague or wrong definitions or labelling as is more or less the case to date. So a higher order concept is needed – one which is capable of hosting classical as well as any of the post-classical (or related) ideas. A higher order scheme helps define and interpret channel concepts more sharply, distinguishing them from only seemingly similar ones or interpreting mixed cases etc. Moreover, the proposed higher order concept is completely in line with the most fundamental concepts of the discipline, like the typical marketing/exchange framework (assuming four generic exchange functions; and two major types of channels) as well as the marketing mix concept. A higher order scheme does not mean, however, that a purely distributive framework would become meaningless or non-existent. The classic (even revised) DO-framework does represent a major sub-concept and -classification. Generally speaking, traditional economic roles are becoming increasingly hybrid. This multiple functionality complicates economic analysis. For example, many marketing channels are mixtures of a distribution channel and a communication channel as a result of how their technical and commercial format is conceived and also because of how they are being used by customers. Within the consumer learning/decision process some distribution channels (e.g.,

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the service oriented ones) are often used as communication channels much more than as distribution channels; and sales ultimately materialise in the relatively cheaper ones (van Waterschoot et al. 2008). A higher order scheme is therefore helpful for interpreting their specific role in complex marketing/channel environments – not only for better conceptual insight, but also for improved practical analysis, planning and strategy. A higher order scheme is realistic in that it helps with mapping and interpreting these hybrid roles and interplays, while at the same time leaving room for more traditional isolated perspectives. It increases the likelihood of capturing reality and is capable of capturing corresponding theoretical developments and of hosting both classic DO and non-classic DO.

7.

Revision Agenda Stage III: Developing a Generic Higher Order Scheme

A higher order generic scheme based upon customer values intrinsically generates a number of sub-concepts. These should be distinguishable on the basis of positively defined generic dimensions. In other words, a high level generic scheme itself needs a generic classification of sub-concepts. Logically, the framework that is needed is not just a channel framework, but a broader marketing service output framework. Closely related concepts should be mapped in a clear and compatible way. The generic typology should rely as much as possible on elements that have received consensus and approval in the discipline and are therefore not open to debate or confusion. We envisage four dimensions to this framework (see Tables 3 and 4).

7.1.

Functional Versus Institutional Origin of Customer Values

The first dimension in Table 3 distinguishes between marketing/exchange functions and production functions. The second dimension separates marketing/exchange and production specialists (i.e., institutions). Within the resulting classification, the functional and institutional approaches would be identifiable with a revised classic DO concept corresponding to any output resulting from the distribution function (DFO). It would refer to any type of satisfaction or dissatisfaction delivered or caused as a result of the execution of the distribution function by whoever assumes it. Similarly, distribution specialist outputs (DSO) would refer to any type of satisfaction or dissatisfaction delivered by a distribution specialist as a result of the execution of any combination of exchange (and production) functions. These two dimensions allow the identification of not just the classic DO concept, but also a set of more remotely related concepts (such as communication benefits delivered by manufacturers) next to the smaller set of more closely related concepts. These two dimensions provide the sources of customer satisfaction, but alone are not sufficient to form a generic classification. What is also needed to complete the customer value framework is a representative classification of customer satisfactions and dissatisfactions, or positive and negative customer need categories.

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Table 3: Dimensions 1 and 2 of a Generic Perceived Customer Value Scheme

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Table 4: Dimensions 3 and 4 of a Generic Perceived Customer Value Scheme

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7.2.

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Positive versus Negative Customer Values According to Fundamental Underlying Motives

Earlier it was argued that distribution service outputs involve non-economic (social and emotional) benefits alongside economic benefits. It can also be argued that specific activity classes like distribution can potentially affect any customer need category addressed by marketing activities in general. Lambins (2000, p. 105-111) overview of need classifications details three alternative typologies in chronological order: Maslow (1943); Rokeach (1973); and Sheth/Newman/Gross (1991). The last typology is the most appropriate option as it combines empirical findings and a theoretical grounding. It starts from the axiomatic proposition that consumer choice is a function of multiple consumption values including those beyond simple economic utilities. Each consumption value is consistent with various components of the models advanced by Maslow (1943), Katona (1953), Katz (1960), and Hanna (1980). In addition, the definition of functional or economic values takes into account perceptual phenomena. The consumption values identified are independent, relate additively and contribute incrementally to choice. This classification possesses the generic quality of collective exhaustiveness and exclusiveness required by Hunt (1991), which suggests that it can be extended to other customer settings – in particular business-to-business settings where typically noneconomic motives are less important. The five values identified on the third dimension of the generic scheme (see Table 4) are economic (in perceived terms) or functional, social, emotional, epistemic, and conditional values. The fourth dimension of the generic scheme concerns the dis-utilities, or negative (perceived) values, that customers derive from the adoption of products or services. The disutility following from the payment of a monetary price for a product is the most typical example. This monetary price may, explicitly or implicitly, concern the product or service as well as the acquisition process and its elements (Bell et al., 1998). Positive and negative customer values need not necessarily belong to the same category; and even when they do, they need not necessarily be compensatory. This argument may be more applicable to non-monetary costs, as in case of the affective influence of the environment (Baker et al. 2002, p. 122). Zeithaml’s (1988) notion of non-monetary costs also focused on the negative effect stemming from store environments. This perspective is also consistent with the argument that positive and negative effects are distinct constructs (Babin et al. 1998; Watson et al. 1988) and that a negative effect has a stronger impact on consumers (Babin/Darden 1996). Researchers in economics and marketing have treated them as distinct items (Bender 1964); thus there is a need to consider positive and negative customer values separately.

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Revision Agenda Stage IV: Deepening the Distribution Service Outputs Concept

The ultimate aim of a generic conceptualisation is to contribute to theory formation and practical insight and research. The previous revision leads to a system of fundamental subconcepts of a relatively abstract nature under the umbrella of an even more general scheme. This framework, and in particular the revised DO concept and classification, must be capable of intrinsically hosting any operational concept or category of service output. The distance between the abstract and practical levels must systematically be bridged. This bridging we call deepening, to indicate that the framework is supplemented with compatible sub-concepts and sub-classifications. The idea is for the scheme to cover the widest range of aspects, applications, and settings. The subsystems should be compatible with the generic system and also with the behavioral and technical insights of the discipline.

8.1.

Desirable Properties of Operational DO Classifications

Empirical studies typically deal with DO at a relatively narrow operational level. Classic and related DO can be measured at different hierarchical levels of abstraction. In the field of marketing, this idea has been represented by the metaphor of a means-end-chain (Gutman 1982), and mapping of need hierarchies has involved research techniques referred to as laddering (Botchen/Thelen 1999). More operational levels of need fulfilment (and corresponding measurement) would be vertically located underneath more abstract or fundamental levels of need fulfilment. Need fulfilment at relatively low levels would contribute (although not always via obvious paths) to need fulfilment at higher levels in the hierarchy, as represented in Figure 5 (Rokeach 1973). Figure 5: A Representation of the Hierarchy of Customer Needs Values

Needs

Wants

Benefits derived from sets of attributes e.g. waiting time

Benefits derived from individual attributes e.g. opening hours, queuing time

In the means-end-chain, the highest or most generic/abstract level is that of customer values.

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The lowest most specific/operational level would be where needs are expressed as the satisfaction or benefit derived from individual attributes. An attribute of a shop would, for example, be that it is cozy. The satisfaction derived from this attribute would be coziness, which in generic terms fits the category of emotional needs (Lambin 2000, p. 109). Between the attribute and generic level, a shorter or longer chain of embracing sublevels may exist. Classic (and related) DO have been commented upon throughout this paper as operational counterparts of more abstract forms of economic utilities. But classic DO still represents a level of detail above the ultimate attribute level. Each classic DO can indeed be expressed in several more specific or operational ways. Each classic DO category represents the benefit or satisfaction derived from a set of possible attributes (Haley 1968). The same presumably holds for related DO, too. The original historical marketing setting gave rise to predominantly quantitative, numerically expressible attributes. In a more current marketing setting, attributes reflecting quality and uncertainty differences have become much more important (Coughlan et al. 2006; Parasuraman et al. 1985; 1988; Morschett et al. 2005). For example, retail formats with ever changing product ranges play a different role in the channel in comparison to formats with very steady assortments. The traditional quantitative measures capture only one expression of these more abstract ideas. Moreover, all of these aspects should be considered to be interrelated. This is illustrated by the variety of goods and services offered. Very often waiting time and decentralisation are only determined in respect to the core of product variety. A retail network would provide availability of core merchandise through the density of outlets and long opening hours. In contrast, auxiliary products might have different service output characteristics. For instance, a non-standard size might only be available after a delivery time of three weeks, but would be delivered free to the customers home. These many and varied combinations are not only of strategic and managerial importance, but also impact upon operational classifications in academic studies. In addition, any sub-classifications ought to satisfy the traditional classificatory requirements to foster comparability among empirical studies.

8.2.

The Status of Operational Classifications in Empirical Studies

The screening of empirical studies was not a prime objective of this paper. However, in the literature search we came across empirical or related studies which allowed us to formulate some tentative views on operational classifications. These are drawn from comparison of two cases, judgmentally selected from these studies. Both of these selected studies aim to arrive at a representative list of store attributes, in the sense of determining the largest common denominator, capturing most of the enormous variation typically found in idiosyncratic empirical studies. Both were prepared by vested academics and published in major academic journals. Both aim at integration and are concerned about continuously re-inventing the wheel.

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The first study (Alba et al. 1997) examined the implications of electronic shopping for consumers, retailers and manufacturers. It compared six retail formats, in terms of implied benefits and costs to the consumer, based on an extensive literature study resulting in an a priori classification of 14 customer benefits or corresponding store attributes. This list was inspired by the different phases in the consumers buying process including clothing. The second study (Erdem et al. 1999) is focused on the clothing industry. The authors prepared a pragmatic list of eleven store attributes, also on the basis of extensive literature study, which were next grouped by means of factor analysis. Table 5 provides the full list of attributes from both studies and the sets. Alba’s study contains 14 attributes grouped into five sets, whereas Erdem groups eleven attributes into three sets. No headings or attributes in the two integrative studies match. Empirical studies seem to underscore very strongly the need for a generic typology and compatible sub-typologies. Empirical studies typically generate pragmatic DO-lists of their own (Erdem et al. 1999). Our study indicates that researchers tend to invent the wheel over and over again and that users lose time in achieving comparability and compatibility but still remain under informed. Table 5: Sets of Store Attributes in Two Integrative Empirical Studies Alba et al. (1997)

Erdem et al. (1999)

Heading (N=5)

Attribute (N=14)

Attribute (N=11)

Heading (N=3)

Providing alternatives for

Number of categories

Quality of merchandise

Merchandise

consideration

Alternatives per category

Fairness on adjustments Helpfulness of salespersons

Screening

Selecting consideration set

Providing information for

Quantity

selecting

Quality Comparing Alternatives

Other benefits

Social Interaction Personal Security Entertainment

Reputation for fashion Brands carried by store Class of clientele Physical attractiveness of the

Status

store Ordering and fulfilment:

Locations for placing or-

Convenience of location

transaction costs

ders Supplier delivery cost Customer transaction cost

General level of prices Credit arrangements Special sales or promotions

Supplier facility costs Delivery time

Source: Alba et al. (1997) and Erdem et al. (1999); only rankings are slightly adapted.

Price

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9.

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Conclusions and Future Research

Classic DO can be seen as the lagged crystallisation of evolution in marketing thought during the late 19th and early 20th centuries. The classic integration by Bucklin was, however, already anachronistic at its very moment of publication. Although it exhibits an excellent fit with the marketing economics discipline, it is less in tune with modern multidisciplinary marketing thought. Subsequent revisions to the concept have not tackled this issue. They do not even concern the classic concept per se, but rather develop related concepts as they involve quite dramatic shifts in conceptualisation. They imply other exchange and/or production functions and/or take an institutional stance. They also typically remain marketing economics concepts in terms of their underlying assumptions. It is also clear that textbook authors struggle with the anachronisms of the classic concept. Another concern is that the classic concept remained underutilised outside its original field. Consequently, the classic DO-concept requires a revision. First, the classic concept should be broadened and made compatible with the assumptions and boundaries of the overall marketing field. Second, it should be redefined within the scope of a generic higher order concept; and third, the delineation of this generic concept must itself encompass a generic classification of its inherent sub-concepts. The generic dimensions chosen constitute an embracing customer value scheme representing the most fundamental explanatory forces and effects of customer satisfaction delivery. The scheme is compatible with the disciplines overall boundaries, and its major categories are compatible with recent research findings in marketing. The proposed scheme also allows researchers to distinguish between the classic DO and any closely or remotely related service output concept. The scheme withstands the tests of classificatory requirements such as collective exhaustiveness, mutual exclusiveness of its categories, positive definition of its dimensions, and absence of all-other categories. It is also in line with other centrally vested concepts like the marketing mix concept. To implement the proposed scheme, the relationship between the generic scheme and specific operational customer benefits needs to be mutually harmonious. This represents the fourth stage of our proposed revision programme. Marketing is predominantly an empirically orientated discipline. Yet, like any scientific discipline, it has both a theoretical and an empirical side. It should be meritorious in terms of both deductive and inductive knowledge production, and these should interact. This paper attempts to discern and summarise crucial issues at the more abstract level of DO-thinking. The aim is to help pave the way for a better alignment with empirical work. The proposed generic system should therefore be capable of hosting any operational concept or category of service output. The categories in the proposed generic scheme are conceived at the general level of customer values. As the ultimate aim is to foster theory formation and practical applicability, the scheme needs to be deepened. The gap be-

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tween the abstract and the practical level must systematically be bridged. This requires both vertically and horizontally compatible sub-concepts, sub-classifications, and operational measures. Scales or measures – just like sub-typologies – are needed to deepen the proposed generic framework and to make it operational. They can be of a very operational, practical, down to earth level, or vice versa be of a more general nature, depending on the specific subject matter at hand. Scales may focus on specific distribution levels, or alternatively try to cover complete channels. Examples of the latter could be scales measuring the image or emotional impact of complete channels from an ecological-footprint-perspective, or from a fairtrade-perspective. In many instances, though, customers and more in particular consumers (if they are the ones specifically being studied) will often perceive the retail stage alone, and measures aimed at covering the overall channel would hardly make sense. This mutual systematic bridging represents a formidable challenge for future research. The diverse literature offers an implicit consensus concerning the basic options of a generic scheme. This paper represents an endeavour to schematise that consensus. However, our limited exploratory literature search of operational studies reveals a significant issue. Empirical studies typically rely on pragmatic, ad hoc DO classifications, and generate DO classifications of their own, typically based on selective literature research and on common sense. As such they suffer from a lack of comparability. This is all the more so, as little attention is paid to classificatory properties. Consequently, a relatively inefficient situation seems to exist, with a continuous re-invention of the wheel to some extent. It is our belief that inductive research is not sufficiently contributing to a substantial body of knowledge, but rather to a vast set of tiny dispersed islands of knowledge. We feel there is a strong need for initiatives to consolidate accepted conceptual and empirical knowledge and to make this more accessible and transparent. This ambition applies in the first place to the original DO, as they represent collective nouns rather than individual benefits. The main improvement of the strictly classic DO even lies here. Waiting time for example is a concept that is essentially multi-dimensional. It may relate to any aspect of the delivery of a product or service: need assessment, financing, installation, delivery of auxiliary services etc. Waiting time can be measured objectively, but also subjectively. The same goes for the other classic DO as well. It is advisable that the classic notion of DO should be studied more thoroughly, explicitly and systematically taking into account their implicitly hierarchical nature, their essential multi-dimensionality and interactivity and also their subjective next to their objective nature. As a logical extension, interactivity should next be studied between classic DO and non-classic DO. This type of research is occasionally carried out, but typically in a non-integrated, more or less isolated way. For example, waiting time studies at supermarket check outs may investigate the impact of television programs (like e.g. World cup matches) on perceived waiting time (Bailey and Areni 2006). However, it is advisable to situate this type of study in the broader framework of DO, as this

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improves comparison, completeness, integration, fosters theory building and clarifies new research directions. Of course it is possible for academics to ignore the fact that a classic concept runs the risk of becoming obsolete and/or isolated and to remain indifferent about this possibility. Of course it is possible to accept that corresponding empirical research would risk taking the form of unmapped discovery of small isolated islands of knowledge. Of course it is possible not to bother about theoretical and empirical synergies not taking place and not to bother about unrealised cross fertilisation. Of course it is possible to remain indifferent and not accept the challenge of constructively integrating classic concepts into newer, broader, and more consistent conceptual and empirical knowledge development. Market developments make a strong case for academics not to downplay such issues: not to cynically pose the so-what-question, but instead to take a more constructive attitude. Multiple distribution channels are becoming the rule rather than the exception. The same goes for communication channels. Moreover, the latter may become intertwined with distribution channels. Intermediaries and producers are more often than not essentially hybrid. They add all sorts of exchange and/or production functions to their original specialisation. Similarly, consumers are not becoming any simpler in themselves. Rising affluence leads to multiple need fulfillment following from single purchases within a particular product or service category. Consumers may use different purchase task definitions within a product or service category, and their multi-purpose behavior makes them even less predictable and difficult to group into lucrative segments. This complexity is increased by a multitude of changes in the market environment such as technical or legal evolutions that are often difficult to predict. Last but not least, life cycle evolutions of products and channels affect this complex multiplicity of customer values in general and distribution service outputs in particular. Distribution service outputs do represent an unavoidable concept in any exchange setting. The more complex that setting is, the higher the need for a sophisticated (set) of concept(s) and the greater the need for a representative conceptual framework fostering not only theory development, but also empirical research. Complexity should not be ignored, denied or fled from, but should be mastered by mapping and integrating related concepts and by bringing them into line with empirical research and vice versa.

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Internal Marketing, Market Orientation and Organisational Performance: The Mythological Triangle in a Retail Context Prokopis K. Theodoridis and George G. Panigyrakis

Abstract This study aims to empirically investigate the relationships that, until now, in a retail context, have been mostly conceptually based, within a ‘mythological triangle’, i.e. as the impact of Internal Marketing and Market Orientation on Organisational Performance. After the validation with SEM analysis of all three constructs, findings clearly indicate that Internal Marketing indeed has a positive significant effect both on Market Orientation and on Organisational Performance. Market Orientation has a positive effect on Organisational Performance. The role of marketing as a philosophy and function focusing both internally and externally has begun to mushroom within retailing in Greece – as in supermarket chains with nationwide coverage. Retailers recognise that when operating in fiercely competitive national and global environments, marketing can create sources of competitive advantage and effectiveness, even prior to being in the market place.

Keywords Internal Marketing, Market Orientation, Organisational Performance, Retailing, Greece

Prokopis K. Theodoridis (corresponding author) Department of Business Administration of Food and Agricultural Enterprises, University of Ioannina, Agrinio, Greece (E-mail: [email protected]). George G. Panigyrakis Department of Business Administration, Athens University of Economics and Business, Athens, Greece.

Received: March 19, 2010 Revised: August 16, 2010 Accepted: August 23, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_2, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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Introduction

Market orientation (MO) has been the central focus of academic research during the last twenty years, reflecting the need for uncovering marketing implementation within a firm and verifying its operationalisation (Ruekert 1992; Webster 1988). Since the early 90’s, several studies have examined the transformation of the concept into a measurable instrument, initially determining the appropriate scales (Narver and Slater 1990; Kohli/Jaworski 1993; Deshpandé/Farley/Webster 1993; Deshpandé/Farley 1998) and then validating the respective measures in different contexts: countries, industries, and types of organisation (Langerak 2003; Cano/Carrillat/Jaramillo 2004; Deshpandé/Farley 2004). Subsequent knowledge on the subject has increased in relation to what constitutes a market-oriented organisation and the respective dimensions/behaviours that one would need to employ for an organisation to be in the market for the market: gathering specific information relative to the environment, competitors and customers; analysing this information and disseminating it within the organisation; creating an effective responsive mechanism through the implementation of a marketing plan in accordance to organisational objectives. The aim is to create a potential differentiation and a competitive advantage (Hunt and Morgan 1995). The result of the adoption and implementation of MO on the actual field has to be a better performance of the organisation in terms of financial and non-financial indicators: profits, sales, market share etc. (Deshpandé/Farley 2004; Cano/Carrillat/Jaramillo 2004). At the same time, research has also underlined the importance of investigating a more comprehensive picture of the organisation in the market and its behaviours, that would contribute in one way or another to MO. Studies have explored and utilised antecedents of MO that enhance, mediate, or moderate the relationship between the MO and a positive result in terms of market performance (Langerak 2003; Cano/Carrillat/Jaramillo 2004). Internal marketing (IM) has been discussed within marketing literature as being the inside-the-firm equivalent of the ‘marketing concept’ in the external market (George 1990; Berry/Parasuraman 1991; Berry 1984). The concept of IM provides the platform of treating the employee as an internal customer and thus trying to satisfy his/her needs and enhance his/her motivation to provide quality customer service which, in turn, creates a satisfied ‘external customer’ (Lings/Greenley, 2001; 2005; Naude/Desai/Murphy 2003; Lings 2004; Gounaris 2006; 2008; Lings/Greenley 2009); at the same time, employee behaviour is envisioned as that of internal customers and suppliers providing quality service to their colleagues, which in turn will again be received by the external customer (George 1990). This creates a provision of service quality to the customer as a result of an internal value chain that has already accumulated the quality in the total offer – product or service – as created through the internal processes of the organisation. In mirroring the external focus of the marketing concept, IM has a twofold existence within the organisation: a culture, i.e. the archetypal code of certain beliefs, leading to the under-

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standing of how things ‘happen’ in the organisation and the behaviours reflecting those beliefs. This behavioural approach of IM has been discussed as contributing positively to the performance of the organisation: an employee with a clear vision and objectives, specific reward and motivational systems, effective informational and feedback mechanisms, supported by his/her colleagues with the provision of quality internal services and interdepartmental coordination, will potentially perform in optimal ways that lead to customer satisfaction, loyalty, repeated sales, increase in the market share and, hopefully, profitability (George 1990). Until today, however, the notion of IM has not been consolidated into a measurable scale and there is a need of more research in this area (Rafiq/Ahmed 2000; Ahmed/Rafiq 2003). Most of the previous work in the area has concentrated either on investigating the relationship between MO and some kind of organisational performance (OP), or alternatively on antecedents of MO in conjunction with their implication in market performance (Langerak 2003; Cano/Carrillat/Jaramillo 2004). The obvious lacuna concerns the examination of the implication of IM – in terms of behavioural schemes within the organisation – both in MO and the performance of the organisation in the market. The aim of the present piece of research is to fill this gap, focusing on the investigation of the impact of IM on the MO of an organisation and on its performance within a retail context. This research provides empirical findings concerning the under-examined triangle between IM, MO and OP, hypothesised and conceptualised for years as a ‘myth’. Even when there has been empirical evidence concerning specific dyadic relationships – with the relationship between MO and business performance dominating the literature – those relationships incorporating IM still call for investigation in more thorough and extensive ways. The first section of this paper discusses the notions of internal marketing, market orientation and OP. The literature review provides the basis for the synthesis of the dimensions of the proposed IM concept in terms of organisational behaviours. Further, market orientation is analysed and determined. The relationships between the ‘mythological triangle’ of IM, MO and OP are discussed and the respective hypotheses are formulated. Next, methodological issues are explained and the results of the study are presented. The last section of the paper provides a discussion of the findings as well as the limitations of the study and propositions for future research.

2.

The Theoretical Background

2.1.

Internal Marketing

Since the 1970’s, Internal Marketing has appeared as a conceptual reflection of the need for creating an internal climate within an organisation by adopting specific behaviours ultimately aiming towards the provision of high service quality to the customer (Berry/Hensel/Burke

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1976). Ever since the first attempts at conceptualising IM, indicative of which is the work of Sasser and Arbeit (1976), Berry (1981), Grönroos (1981), and George (1990), the majority of the work pertaining to IM has remained conceptual (Flipo 1986; Grönroos 1994; Rafiq/Ahmed 1993; Cahill 1995; Foreman/Money 1995; Varey 1995; Varey/Lewis 1999; Rafiq/Ahmed 2000; Bansal/Mendelson/Sharma 2001; Ballantyne 2003; Lings 2004) until recently. Work on IM has as a starting point the concept that IM stresses the importance of marketing internally, within the organisation, focusing on the employee and providing another source of competitive advantage (Sasser/Arbeit 1976; Berry 1984; Berry/Parasuraman 1991). This complementary role of IM to the marketing concept and its implementation is an expression of a holistic management process focusing first internally on the organisation. This integrated process has been discussed within the literature (George 1990) as: effectively developing and maintaining employees both motivated and satisfied (Dunne/Barnes 2000); disseminating within the employees across all hierarchical levels the organisational culture, objectives, behaviours and activities representing a customer and market orientation, regardless of the degree of adoption. We claim that there is also a third way of contributing to the role of IM: ensuring that departments, functions, stores/branches and employees cooperate and behave in a specific manner according to an internal supplier-customer relationship concept (George 1990; Panigyrakis/Theodoridis 2009). These three pillars of the IM concept reflect behavioural aspects which consecutively contribute to external and strategic marketing objectives, as well as to quality, productivity and efficiency (Grönroos 1981; George 1990; MacStravic 1985; Lings 2000; Ahmed/Rafiq/Saad 2003; Lings/Greenley 2001; 2005; Gounaris 2006; 2008). There is extremely limited empirical research in the area providing some evidence of a paradigm of the philosophy, notion and implementation of IM (Foreman/Money 1995; Boshoff/Tait 1996; Caruana/Calleya 1998; Quester/Kelly 1999; Conduit/Mavondo 2001; Lings/Greenley 2001; Ahmed/Rafiq/Saad 2003; Lings 2004; Naude/Desai/Murphy 2003; Lings/Greenley 2005; Gounaris 2006). This lack could most probably be the main reason why the presence of IM awareness within organisations is indeed rare. Inversely, the less we examine the topic, the more the unknown implications of management practices and activities that probably slip undetected by academic examination and theoretical formulations. Nevertheless, the lack of an accepted definition and relevant valid measurements of IM has led to an increased number of attempts by the academia to investigate the concept and its construct (Varey 1995; Rafiq/Ahmed 1993; Ahmed/Rafiq 1995; Rafiq/Ahmed 2000; Lings/Greenley 2005; 2009). The result of the increased number of empirical studies devoted to IM (Lings/Greenley 2001; 2005; Naude/Desai/Murphy 2003; Lings 2004; Gounaris 2006; 2008; Lings/Greenley 2009)

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led to the operationalisation of the concept to a construct, mostly through the adoption of the internal market orientation (IMO) concept: “[…] internal market orientation is about identifying and satisfying the wants and needs of employees as a prerequisite to satisfying the wants and needs of customers […]” (Lings 2004, p. 408). These studies are based partially on the pioneer work of Foreman/Money (1995) – the first internal marketing scale with empirical evidence – with an appropriate and analogous expansion relative to the market orientation concept (Kohli/Jaworski 1990), adapting it internally to the firm (Lings/Greenley 2001; 2005; Naude/Desai/Murphy 2003; Lings 2004; Gounaris 2006; 2008; Lings/Greenley 2009). The most representative and recent papers adopting the concept of IM orientation are the works of Lings (2004), Lings/Greenley (2005; 2009) and Gounaris (2006). Even though Lings/Greenley deviated from their initial attempt (Lings 2000), they found a multidimensional construct within a retail context representing IM orientation as consisting of five dimensions: Informal Information Generation, Formal Face to Face Information Generation, Formal Written Information Generation, Information Dissemination and Responsiveness (Lings and Greenley 2005). They also provide the specific title for the scale (even with some minor differences between the first and the latter works: initially IMOR and then IMO). Gounaris (2006) expanded the IMO scale to make it conceptually more reflective of the notion of market orientation developed by Kohli/Jaworski (1990) within a hotel industry context, building mostly on the work of Lings (2004), Lings/Greenley (2005) (for an analytical discussion of IM scales development in recent years, see Panigyrakis/Theodoridis 2009). Ahmed/Rafiq/Saad (2003) having a different departure basis, focus on the notion of IM mix that could be effectively used to influence employees, so that they are motivated and act with a customer-oriented attitude. This branch of the research adopts the internal market orientation concept with a core notion that the effectiveness of external marketing depends to a great degree on the fact that employees have been satisfied first and have received relative motivation and incentives (Sasser/Arbeit 1976; Berry/Parasuraman 1991; Berry 1984). Clearly, this approach of IM locates its concept and specific management behaviours narrowly within the field of Human Resource Management (Panigyrakis/Theodoridis 2009): behaviours targeting and directing the contact between employees are re-focused on the interactions between customer and employee (Lings/Greenley 2001). IM has to be approached from a broader viewpoint, complementary to the effort of satisfying employees by providing a value to the firm-employee relationship (internal market orientation). IM must also enhance the proper internal environment for providing service quality to the ‘next’ internal customer, an internal customer orientation (George 1990; Dunne/Barnes 2000; Panigyrakis/Theodoridis 2009). It is a concept neglected by the majority of the latest empirical investigations relative to IM (Lings/Greenley 2001; 2005; 2009;

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Naude/Desai/Murphy 2003; Lings 2004; Gounaris 2006). Enhancement of the provision of internal service quality among and within departments, stores, branches and different levels of hierarchy leads to the provision of quality service to the customer (George 1990; Lings/Greenley 2001). This time the conceptual basis for the notion of internal customer orientation (ICO) is the Total Quality Management philosophy, and it operates on the premise that all inside the firm are internal customers and suppliers (Denton 1990; George 1990; Barret 1994; Panigyrakis/Theodoridis 2009). The total offer to the external customer, regardless of whether it concerns a service, a product or a combination of those, is directly influenced by the quality of the internal service. The concept of internal customer and supplier has a wider intra-firm application: this possibly exists within all the various kinds of businesses and not exclusively in service organisations (Gummesson 2000). The notion that everybody in the firm is simultaneously a customer and supplier of services to and from other colleagues or departments is the second critical orientation incorporated in the IM concept (George 1990; Lings 2000; Panigyrakis/Theodoridis 2009). The amalgamation of the two major internal orientations – IMO and ICO – integrates the conceptual approach of IM, filling the gap of examining the concept only partially. Apart from the internal customer orientation and its behavioural representation within the organisation, it is important to discriminate between aspects of the literature devoted to the notion of internal market orientation (Lings/Greenley 2001; 2005; Lings 2004). From this perspective, a crucial element is the need of gathering and analysing information relative to employees (Sasser/Arbeit 1976; Lings/Greenley 2001; 2005; Lings 2004; Gounaris 2006) in order to investigate their desires, satisfaction level and various factors affecting the object of their work (Lings 2000; Lings/Greenley 2001; 2005). Information also has to be relative to the external environment in terms of creating a form of intelligence on the competitors’ personnel, potential pool of employees and relative legislative job subjects (Lings 2000; 2004; Lings/Greenley 2001; 2005). Moreover, organisations have to operate in a transparent way and to be able to openly share with their employees organisational objectives, performance and financial situation (Dessler 1999; Pfeffer/Veiga 1999; Bansal/Mendelson/Sharma 2001). The more one excludes information from the internal stakeholder, the greater the possibility of leading to ineffective decisions and drawbacks (Pfeffer 1995; 1998). Shared information operates as an effective feedback mechanism for the employees in order to evaluate their performance and decision-making (Robbins/Langton 1999; Slater/Narver 1994; Bansal/Mendelson/Sharma 2001). Therefore, two-way effective communication between middle managers, top management and employees provides appropriate feedback to employees, thus improving their job performance (Conduit/Mavondo 2001; George 1990; Grönroos 1990). IM also requires a reactive behaviour towards employee-related information in terms of job design, rewards and other forms of motivation of great importance to employees, training, recruitment, top management support, and other management activities, in order to sup-

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port effectively the market orientation of the firm (Berry/Parasuraman 1991; Lings 2004; Lings/Greenley 2001). These targeted internal behaviours relative to reward and wage systems determine to a certain degree the level of the improvement of the work of each employee. Reward and motivation schemes and systems are crucial elements of employee behaviour (Lawler/Rhode 1976; Anderson/Champers 1985), enhancing the adoption of new behaviours and attitudes geared towards the firm’s market orientation (Ruekert 1992; Hauser/Simester/Wernerfelt 1996). Moreover, Varey (1995) gives an emphasis on the social aspect of IM and claims that it is presented within the concept of managerial consideration. This refers to the degree in which managers/supervisors direct effectively a work climate by offering psychological support, friendship, help, mutual trust and respect (Johnston et al. 1990). The middle hierarchical levels operate as a link between employee and organisation and a positive behaviour towards employees could create better attitudes towards the firm (Katz/Kahn 1978). These organisational behaviours are the transformation of the IM concept into activities, exchanges and relationships, incorporating both the conceptual forms of the internal market and internal customer orientations, i.e. combining marketing, human resources and total quality management philosophies and respective aspects together to support and enhance an external orientation towards the market and fulfil organisational objectives.

2.2.

Market Orientation

It is widely known that market orientation has been developed as one of main bases of the management philosophy reflecting marketing concept (Levitt 1960; Ruekert 1992; Webster 1988). During the late 80’s, the Marketing Science Institute initiated research into the conceptualization and measurement of market orientation (MO), underscoring the importance of exploring the successful implementation of the marketing concept (Deshpandé/Farley 2004). Since then, market orientation has become one of the most studied constructs in the field of marketing (Elg 2007; Lagerak 2003, Cano/Carrillat/Jaramillo 2004). The concept of MO can be approached from two main perspectives: as an organisational culture and as behaviour (Dreher 1994; Homburg/Pflesser 2000). MO as a culture is defined as a set of archetypal concepts leading to the understanding of how things ‘happen’ in the organisation (Deshpandé/Webster 1989). In turn, the behavioural perspective concerns the organisational implementation of the said culture through the right strategy, structure, process and activities (Dreher 1994). Narver/Slater (1990) adopt a cultural approach to MO and operationalise it incorporating three components: - customer orientation, the sufficient understanding of target buyers so as to be able to create superior value for them diachronically

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- competitor orientation, understanding the short-term strengths and weaknesses and the long-term capabilities of both current and potential competitors - interfunctional coordination, the coordinated utilization of company resources for creating superior value for target customers. Having in mind the behavioural approach of MO, Kohli/Jaworski (1990) define it as “organisation-wide generation of market intelligence pertaining to current and future customer needs, dissemination of intelligence across departments, and organisation wide responsiveness to it” (p. 6). The focal point of this approach is the emphasis on the market through an internal coordination of the various functions and departments on the basis of information management – gathering, analysing, disseminating and reacting – relative to the environment, competitors, and customers. Both research groups developed and validated measurement constructs representing their theoretical approach to MO (Kohli/Jaworski 1990; Kohli/Jaworski 1993). Research devoted to the examination of MO within the retail industry – especially during the 80’s and 90’s – has mainly focused on operational marketing activities and practices (Greenley/Shipley 1992) and departmental marketing roles (Piercy/Alexander 1988), while it is mostly descriptive in nature. Piercy/Alexander (1988) found that the majority of retailers were ‘marketing oriented’. Ten years later in the same context (UK), Liu/Davies (1997) provide a more precise picture of the adoption of MO within the retail industry, even though their work is to a great degree descriptive and the construct they adopt is only partially examined. Further, MO within retailing has been investigated in relation of specific organisational characteristics that affect it and potential barriers that could be arise when trying to implement it (Harris 2000; Harris/Piercy 1999). Authors also underscore the significance of MO in retailing as probably having a substantial impact on competitiveness and performance. The study of Soehadi/Hart/Tagg (2001) clearly demonstrates the results of the adoption of MO by Indonesian retailers. It has been mentioned that retailing is an especially complex business setting relative to manufacturing, thus the examination of MO needs a more thorough and analytical procedure (Elg 2007). Even when this differentiation of retailing potentially calls for a modified measurement of MO, empirical attempts still adopt the two most usable measurements of MO (Harris/Piercy 1999; Liu/Davies 1997), showing that a MO perspective is relevant for retailing (Elg 2007). Our study following the logic of the work of Panigyrakis/Theodoridis (2007) adopts the same behavioural approach of Kohli/Jaworski (1993), seeing MO as applicable and appropriate to a retail setting.

Theodoridis, P.K.; Panigyrakis, G.G.

2.3.

41

Organisational Performance

It is certain that the way of ensuring an organisation adopts strategies leading to the achievement of goals and objectives is the monitoring of various performance measurements. Most performance measurements which have been heavily used in empirical research focus on the achievement of a number of key financial ratios, such as return on investment, return on equity, return on sales, etc. (Capon/Farley/Hoeing 1990; Dawson 2005; Reynolds et al. 2005). These financial indicators represent the success of the economic targets of the organisation. These models have been criticised as failing to capture all the dimensions of an organisation’s performance, as well as the degree to which the organisation adapts to the environment in comparison to its success (Brignall/Ballantine 1996). The missing part of an organisation’s performance picture is compensated for by measures which indicate/follow an indirect route to the financial performance: market share, degree of product or service quality, customer loyalty and customer satisfaction, which could be treated as non-financial indicators (Venkatraman/Ramanujam 1986). It is known that the appropriate types of indicators which could be used in measuring retail performance have not been determined conclusively (Ailawadi/Borin/Faris 1995; Dawson 2005; Reynolds et al. 2005). Moreover, the choice of collecting objective measures could stumble upon differences in accounting practices, plus the refusal to provide this kind of data as it contains socially sensitive material (Ailawadi/Borin/Faris 1995). This in turn affects the degree of adoption of objective financial performance measures in empirical studies. In order to overcome the problems, researchers adopt subjective measures of financial and nonfinancial indicators, i.e. asking the perception of managers regarding performance indicators in order to compare it with that of their competitors (Dess/Robinson 1984). Nevertheless, the more common financial indicators used in retail literature are gross margin, rates of return (Bradley/Taylor 1992; Dobson 2005; Reynolds et al. 2005) and sales revenue and growth (Doyle/Hooley 1992; Dobson 2005; Greenley 1995; Hooley et al. 1992; Reynolds et al. 2005). Meanwhile, the relative set of indicators in the non-financial category are: market share (for example: Croni/Skinner 1984; Hooley/Lynch/Shepherd 1990; Doyle/Hooley 1992; Deng/Dart 1994; Liu/Davies 1997), labour and space productivity (Cronin/Skinner 1984; Ingene 1982; 1984; Dobson 2005; Reynolds et al. 2005) and stock turn (Dawson/Shaw 1989). The adoption of subjective measures indicating retail performance when the study is conducted within a single context (supermarket chains) decreases the level of potential restrictions, as the structure and the degree of competition is common to all the participating retailers (Harris 2001). The aim of measuring OP is to capture the most holistic view of performance regardless of categorisations. Our study adopts the use of both financial and nonfinancial indicators, as they offer a broad treatment of OP and an opportunity to purify the

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relationship between financial and operational aspects of performance under examination (Venkatraman/Ramanujam 1986).

3.

The Triangle: Internal Marketing, Market Orientation and Organisational Performance

3.1.

Internal Marketing and Organisational Performance

Even as the empirical evidence relative to the IM concept has increased, in contrast to the initial conceptual discussion which took place within the last thirty years, the notional and conceptual differences among literature have created limitations to the exploration of the impact of IM on OP. Since the specific relationship has been discussed through different approaches (Lings 2000; Ahmed/Rafiq/Saad 2003; Lings/Greenley 2005; 2009; Gounaris 2006; Panigyrakis/Theododrids 2009), yet relatively few in number, restricting the capacity for generalisation on the respective findings, it seems logical for this research to aim in bridging this particular gap. The investigation of the relationship between IM and OP in the literature has been characterized as a navigation with several paths and different departure points. Firstly, one can distinguish the literature on the basis of the degree to which it adopts a concept of IM and its ‘closeness’ to the marketing philosophy and its implementation. These works are the latest empirical investigations that have been already mentioned above and they are very few (Lings 2000; Lings/Greenley 2005; 2009; Gounaris 2006; Panigyrakis/Theododrids 2009). Secondly, a great number of works are approaches of the specific relationship from three main different pathways within the management philosophy and concepts: services, human resource, and total quality. Regardless of the approach, in the majority of cases there is a common characteristic: the attempt at investigating a behavioural aspect of the management relative to the employees and its implication with a certain aspect of OP. The aim always is to find ways of tracing the influence of management implementation upon different kinds of financial and/or non-financial performances. In service literature for example, internal organisational behaviours that could be characterised as the cutting edge of the IM concept have improved service quality (Pfau/Detzel/Geller 1991), decreased the rate of personnel turnover (Gummesson 1997), created customer conscious employees (Grönroos 1981), positive affected customer satisfaction (Heskett et al. 1994, Nagel/Cilliers 1990) as well as business performance (Capon/Farley/Hoeing 1990; Caruana/Pitt 1997). In human resource management literature, human resource practices have been found to positively affect productivity (Ichniowski/Shaw/Prennushi 1995), as well as firm profits and financial performance (Russell/Terborg/Powers 1985; Terpstra/Rozell 1993; Huselid 1995). All these attempts solve only

Theodoridis, P.K.; Panigyrakis, G.G.

43

part of the puzzle, as they examine separated or isolated dimensions of notions adjacent or belonging to IM and their implication on some kind or other of OP indicators. Although the empirical findings relative to the IM concept and notion and its impact on OP are extremely rare and still not enough to provide findings that could be widely generalised, they indeed indicate a positive implication of IM or some of its related dimensions within indicators of OP. Gounaris (2008), adopting the notion of internal market orientation in a hotel context, found positive influences of IM practices on employee satisfaction that could contribute to customer satisfaction and potentially to the overall performance of the firm. Tortosa/Moliner/Sanchez (2009), using the construct of Lings/Greenley (2005) – internal market orientation – found that informal generation of information and communication between and within managers and employees (a dimension of the internal market orientation) has a positive impact on employee satisfaction and on the provided service quality to the customer, leading indirectly to customer satisfaction, i.e., a non-financial indicator of performance. The missing part of the puzzle is the direct impact of IM on organisational performance, at least from the marketing point of view, which is a clear hypothesis of our research.

3.2.

Market Orientation and Organisational Performance

Market orientation emphasises the creation of superior value for the customer, as a result of combining efforts of individuals and departments within the organisation aiming at a higher performance (Deshpandé/Farley 1998; Matsuno/Mentzer 2000; Slater/Narver 2000). MO emerged as a significant antecedent of performance contributing to long-term success (Deshpandé/Farley 1998; Cano/Carrillat/Jaramillo 2004). A market-oriented organisation monitors continuously customers’ needs and emerging opportunities, anticipates competitor moves, explores environmental changes in an attempt to adapt the organisational offering accordingly in order to satisfy customers, while fulfilling its objectives in terms of sales, market share and profits (Kohli/Jaworski 1990; Narver/Slater 1990). The role of MO as an antecedent to organisation performance has been extensively investigated in various contexts (Deshpandé/Farley 2004; Cano/Carrillat/Jaramillo 2004). Most findings indicate a positive relationship between MO and business performance (Deshpandé/Farley 1998; Matsuno/Mentzer 2000; Slater/Narver 2000) even though some studies suggest a negative or non-significant relationship. Langerak (2003) examining 51 studies of MO with a direct link to OP found 18 of them originating in the USA, 13 in Europe, eleven in Asia Pacific, four in the Middle East and Africa and four were cross-country investigations. 26 studies reported positive effects of MO on measurements of business performance, twelve non-significant effects, 2 negative effects, and 10 reported mixed effects. The majority of studies, however, reported the effect of MO on multiple indicators of business performance. Furthermore, in a meta-analytical study, Cano/Carrillat/Jaramillo (2004) found

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58 empirical examinations of the MO construct and its effect on OP – with 42 of them examining the relationship through subjective measurements of financial performance – originating in 23 countries among the five continents. Findings indicated that OP was higher for service market-oriented firms than for manufacturing ones (Cano/Carrillat/Jaramillo 2004). These findings are consistent with the argument that the relationship between MO and performance will be more robust for a service organisation than for a manufacturing one, as service organisations have more customer interactions and potentially leverage more on their MO strategies than manufacturing organisations (Gray/Hooley 2002; Singh 2000). Despite these findings, other research has produced mixed results concerning the relationship between MO and performance (Noble/Sinha/Kumar 2002), ranging from a positive direct relationship (Ruekert 1992; Slater/Narver 1994) to a not-direct link (Diamantopoulos/Hart 1993; Han/Kim/Srivastava 1998; Siguaw/Simpson/Baker 1998). Retail market-oriented organisations are capable of creating better value for their customers as they are more likely to incorporate into their offer the needs and preferences of their clientele (Day 1994; Day/Wensley 1998). The findings of the study of Liu and Davies (1997) in a UK retail context are parallel to those of previous research and provide an explanation of how MO retailers reach higher performance. Moreover, Soehadi/Hart/Tagg (2001) found that MO positively affects retail business performance in an Indonesian context. Rogers et al. (2005), investigating the process and evolution of the internationalisation of a retailer, found that the higher the level of market-oriented behaviour in a competitive environment, the higher the level of retailer performance. Moreover, Harris/Ogbonna (2001) and Panagyrakis/Theodoridis (2007) report a positive link between MO and OP. Piercy/Harris/Lane (2002) conclude that employees in retail market-oriented firms are aware of service and quality importance, influencing the performance of the organisation (Rogers et al. 2005). On the other hand, Harris (2001) reports no effect of MO on organisational performance, leading to the conclusion that the overall issue of the predictive power of MO is, after twenty years of extensive research, still an open question (Langerak 2003; Haugland/Myrtveit/Nygaard 2007). The study of the relationship between MO and performance in various industries and countries is very much an on-going research field (Deshpandé/Farley 2004). While the stream of literature devoted to the relationship between MO and OP has tremendously increased in the last two decades, concerning the retail industry studies relative to manufacturing or even to the general service sector are still few in number (Cano/Carrillat/Jaramillo 2004; Langereak 2003; Elg 2007). The empirical evidence of the specific relationship especially within a retail context is inconclusive, requiring further studies to enhance our knowledge (Noble/Sinha/Kumar 2002).

Theodoridis, P.K.; Panigyrakis, G.G.

3.3.

45

Internal Marketing, Market Orientation and Organisational Performance

There is an ongoing and rather incomplete discussion within the literature of the last twenty years relative to the adoption of internal marketing behaviours within the organisation and the creation of employees better informed and motivated to cope with the appropriate response of the firm to its market (Rafiq/Ahmed 1993). This consequently will probably lead to a positive impact on the market orientation of the organisation and its performance (Grönroos 1982; Gummesson 1987; Berry/Parasuraman 1991; Gummesson 1987; George 1990; Piercy/Morgan 1991; Piercy 1995; Harris/Piercy 1999; Harris 2002; Naude/Desai/Murphy 2003). As George (1990) suggests, these internal behaviours must be operating effectively before the organisation can be successful in achieving goals regarding its external markets. It has been established that creating market-oriented organisations requires a balanced internal and external focus (Piercy 1995). However, there is a lack of empirical evidence to support the view that that IM influences directly market orientation and the performance of the organisation (Conduit/Mavondo 2001). Moreover, although a literature review identifies several antecedents of MO (Bansal/Mendelson/Sharma 2001; Langerak 2003), IM has not been investigated as of them, even it is a common view among scholars that IM will enable employees to behave in a more market-oriented manner and that it affects positively organisation performance (Grönroos 1985; Gummesson 1987; Harris/Piercy 1999). The scarcity of systematic research on the implication of IM in OP either directly or by enhancing market orientation – as a mediate variable – calls for a more analytical investigation of the specific relationships (Ballantyne 2003). Figure 1: The Mythological Triangle

In a retail context, Lings/Greenley (2005) investigating an IM construct, claim that IM has positive implications for some employee behaviours, although they do not investigate the effect of IM on the MO of the firm. In a later study, the authors indeed report a positive impact

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of IM on MO and an indirect link to OP (Lings/Greenley 2009). They suggest that managerial behaviours relative to the needs and wants of the employees create a motivated type of employee, resulting both in a positive effect on customer satisfaction and in profitability, and in enhanced MO for the organisation (Lings/Greenley 2009). Lings/Greenley (2009), as in the previous studies, adopt the construct of internal market orientation, yet exclude the concept of the internal customer- internal supplier from being represented in their IM measurements. Barosso et al. (2005) suggest that an important issue for the management is the coordination of internal activities and behaviours in order to create value for the customer, i.e. the development of an effective internal and external orientation responding to the market and fulfilling organisational objectives. There is probably a more complex relationship between MO and performance than the one assumed up to now in literature, where effects are mediated by important intervening variables (Piercy/Harris/Lane 2002). Our research has hypothesised that, in a retail setting, two major sets of behavioural reflections of respective marketing core concepts – IM and MO – interact: IM positively enhances MO, and at the same time both of them positively influence OP, creating an effective triangle that represents the dual focus of marketing in starting internally from the employee and expanding externally to the customer and competitor. Thus, we claim that MO operates as a mediator variable between the IM and the performance of the retail organisation (see Figure 1).

4.

Methodology

The sample of the present study constituted of supermarket chains with nationwide coverage in Greece. The subject unit of the sample was the Branch manager, as he/she is to some degree independent and impacts on employees. The role of the branch manager is critical, as managerial behaviour and actions have the potential to influence employee behaviour. This, in turn, could probably affect customers’ perceptions of the retail offer they receive (Hartline/Ferell 1996). Twenty-five branch managers and marketing executives were selected for in-depth interviews, to ensure no potential problems would arise due to the wording and/or the translation of specific questionnaire items into Greek. Some items were adapted and some excluded. In-depth interviews specified the set of the proposed items and pre-tested the questionnaire. Respondents were asked to evaluate the phrasing and relevance of the questions to the specific business context being investigated. Before the distribution of the questionnaire, it was given to thirty-two branch managers and marketing executives for approval. Questionnaires were then sent to 1,288 Branch Managers. The final response rate was 265 (20.5%), out of which 252 were deemed usable.

Theodoridis, P.K.; Panigyrakis, G.G.

47

Internal Marketing construct is measured by: 1) the Internal Customer Orientation (ICO) dimension, represented by the scale used by Conduit/Mavondo (2001), here in adapted form, 2) the work of Lings/Greenley (2001), the source of Group Interaction, Collegial Interaction, Formal Interaction (adapted) and External Environment that represents the need of information (internal and external) of employees and employment subjects, and effective internal twoway communication between and within the hierarchy of the organisation. The crucial aspect of feedback within the organisation and from employees is represented by the homonym variable ‘Feedback’ adapted from the “Internal Communication” variable of Conduit/Mavondo (2001), 3) the notion of managerial consideration, measured by adopting constructs from the work of Lings/Greenley (2001), specifically the Wage Flexibility and Job Flexibility, 4) the degree of the responsiveness of the firm towards its employees, measured by the Responsiveness variable of the MARKOR scale (Kohli/Jaworski 1993) which was adapted in terms of meaning and wording to represent responsiveness to internal customer and in the context of a retail organisation (five out of nine initial items) and was renamed in Internal Procedures and Policies, 5) the scale of Jaworski/Kohli (1993) named in its initial form Reward System Orientation, adapted in order to capture the concept of reward systems and motivation incentives, titled Reward Systems. Questions excluded referred to a different research and business context. The IM construct incorporated 10 variables/dimensions and 46 items (Panigyrakis/Theodoridis 2009): 1) Internal Customer Orientation, 2) Group Interaction, 3) Collegial Interaction, 4) Formal Interaction, 5) External Environment, 6) Feedback, 7) Internal Procedures and Policies, 8) Reward Systems, 9) Wage Flexibility and 10) Job Flexibility. All the items were measured using a seven-point Likert scale ranging from 1= “I strongly disagree” to 7= “I strongly agree”. In order to measure the Market Orientation construct, the 20-item MARKOR instrument developed by Kohli/Jaworski (1993) was adopted and extensively adapted for the specific business context. All the items were measured using a seven-point Likert scale ranging from 1= “I strongly disagree” to 7= “I strongly agree”. Organisational Performance was measured with subjective and indirect measures (Dess/Robinson 1984; Conant/Smart/Solano-Mendez 1993; Liu/Davies 1997; Narver/Slater 1990; van Egeren/O’ Connor 1998) appropriate for a retail context. Those consisted of financial indicators – Total Sales, Growth Rate of Sales (Doyle/Hooley 1992; Hooley/Lynch/Jobber 1992; Greenley 1995; Slater/Narver 1994b), Gross Margin (Ingene 1984; O’Riordan 1993) – and non-financial indicators – Market Share (Buzzell/Gale/Sultan 1975; Cronin/Skinner 1984; Deng/Dart 1994; Hooley/Lynch/Shepherd 1990; Liu/Davies 1997), Space Productivity (Cronin/Skinner 1984; Goodman 1985; Ingene 1982; 1984) and Stock Age (Daswon/Shaw 1989). All the performance items were measured using a seven-point Likert

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scale ranging from 1= “much worse” to 7= “much better” , asking respondents to determine their performance in comparison to their major competitor for the last three years.

Purifying the measurements Confirmatory factor analysis (CFA), employing structural equation modelling analysis using AMOS 6.0, was used to investigate the IM scale. In brief, three CFA models were estimated and later compared to each other, after the latent variables and indicators which were not statistically significant were excluded from further analysis: Model 1 – where covariation among items is best explained by five factors which are allowed to correlate, Model 2 – where covariation among items is presented by three factors and Model 3 – where items are represented by a single factor model. A generation model strategy was followed (Joreskog/Sorbom 1993) and all three models were accordingly revised. Table 1: Statistics of Internal Marketing Models Models

1

2

3

Number of factors

5

3

1

87.334

102.337

87.444

34

41

27

0.944 / 0.891 / 0.486

0.935 / 0.896 / 0.581

0.925 / 0.875 / 0.555

NFI

0.932

0.89

0.89

CFI

0.957

0.93

0.92

0.576 - 0.592

0.664 - 0.693

0.667 - 0.690

X² Degrees of freedom GFI /AGFI/PGFI

PNFI - PCFI RMSEA

0.079

0.077

0.094

Composite reliability

0.82/0.87/0.84/0.73/0.66

0.82/0.51/0.96

0.85

Variance extracted

0.69/0.77/0.72/0.50/0.50

0.69/0.34/0.80

0.40

Table 2: Internal Marketing Model 1: Estimates and Standardised Values Indicator

Latent Variable

Estimates1

FORMAL_IN_1

<--

Formal_INT

1**

FORMAL_IN_2

<--

Formal_INT

1.015

S.E.

Critical Ratio

Loadings2

0.087

11.632

0.871

0.067

12.551

0.819

0.797

REWARD_1

<--

Reward Systems

1

REWARD_2

<--

Reward Systems

0.846

INTEPROCED_1

<--

INT_Procedures

1

INTEPROCED_2

<--

INT_Procedures

1.407

0.212

6.64

0.740

1.724

0.248

6.948

0.843

0.081

14.237

0.883

0.095

7.369

0.565

INTEPROCED_4

<--

INT_Procedures

FEEDBACK_1

<--

Feedback

1

FEEDBACK_2

<--

Feedback

1.149

IMAREL_2

<--

ICO

1

IMAREL_5

<--

ICO

0.702

Note: 1 Unstandardised values; 2 standardised values; ** p < 0.001.

0.887 0.483

0.877 0.826

Theodoridis, P.K.; Panigyrakis, G.G.

49

After the examination of the appropriate statistics (see Table 1), composite reliabilities and variance-extracted values (Hair et al. 1998; Fornell/Larcker 1981), the post-hoc analysis (Bentler/Chou 1987; Bollen 1989; MacCallum 1986) indicated that Model 1 (five factors) was better than the other models in terms of reliability (see Table 1 and Figure 2). The IM construct consisted of five dimensions: Formal Interaction (FORMAL), Reward Systems (REWARD), Feedback (FEEDBACK), Internal Procedures (INT_PROC) and Internal Customer Orientation (ICO) (see Table 2) (Appendix A). Figure 2: Internal Marketing – The Construct (Model 1) .64 form_1

FORMAL_IN_1

.80

.76 form_2

FORMAL_IN_2

rwd_1

REWARD_1

rwd_2

REWARD_2

inprcd_1

INTEPROCED_1

Formal_INT

.87

.79

.67 .89 Reward Systems

.67 .82 .23 .55 inprcd_2

INTEPROCED_2 .71

inprcd_4

.45 .48 .74

.59 INT_Procedures

INTEPROCED_4

.88

.49 Fdback

.78 .88 fdk_2

.65

.49

FEEDBACK_1

.46

.50

.84

.77 fdk_1

.48

FEEDBACK_2

.72 .68

imrel_2

.83

IMAREL_2

ICO .32 imrel_5

.57

IMAREL_5

Note: Formal_INT = Formal Interaction; INT-Procedures = Internal Procedures; Fdback = Feedback, ICO = Internal Customer Orientation; form_1…imrel_5 = error terms.

Formal Interaction represents the need for gathering and analysing information relative to employees. Supermarket chains investigate employee attitudes by considering reward systems and compensation. At the same time, they are concerned about employee participation in decisions and actions regarding the supermarket branch. The Reward System seems to concern only the top and middle management (head office branch managers). There is no evidence of rewarding the ‘first line’, even though it is focusing on customer satisfaction. In contrast, re-

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tailers respond to changes in labour issues and to employee complaints (Internal Procedures & Policies). Employees receive feedback from Branch managers on their job performance and they know how their performance is being appraised (Feedback). Moreover, one could find the diffusion of the notion that everybody within the firm is an internal customer and supplier and the aim is to provide quality service to other colleagues, branches or departments (Internal Customer Orientation) (see Appendix A). All these aspects represent the concept of IM within the supermarket chains, indicating an exploratory route. The CFA procedure was followed also for the construct of MARKOR. Three CFA models were analysed and later compared to each other: Model 1 – where covariation among items is best explained by three factors allowed to correlate, based on the original MARKOR scale of Intelligence Generation, Intelligence Dissemination and Responsiveness (Jaworski/Kohli 1993), Model 2 – where covariation among items is presented by two factors, and Model 3 – where items are represented by a single factor model, i.e. a one-dimensional model. All three models were revised during post hoc analysis (MacCallum 1986). The examination of ǻx² – where the three competing models were nested, (Bentler/Chou 1987; Bollen 1989; Hair et al. 1998) – and all the available statistics reveal that the differences between models are major and Model 1 with the three factors fits the specific data set better than the other two models (see Tables 3 and 4; see Figure 3). Supermarket chains in Greece are indeed market-oriented. Table 3: Market Orientation: Statistics for the Competitive Models (N=252) Models

1

2

3

Number of latent variables

3

2

1

214,278

468,689

491,733

42

43

44

Models 1 & 2

Models 1 & 3

254,411

277,455

Ȥ² Degrees of freedom Comparison by ǻX

2

ǻ X2 ǻ of Degrees of freedom Statistical significance (Values of Ȥ² for df 1 & 2)

1

2

Yes

Yes

(10.83 p<0,001)

(13.82 p<0,001)

GFI

0.876

0.732

0.704

AGFI

0.805

0.589

0.555

NFI

0.82

0.607

0.587

CFI

0.848

0.625

0.606

TLI

0.801

0.521

0.507

IFI

0.85

0.629

0.61

RMSEA

0.128

0.199

0.201

Composite reliability

0.83/0.83/0.73

0.72/0.75

0.84

Variance extracted

0.71/0.53/0.32

0.38/0.34

0.33

Theodoridis, P.K.; Panigyrakis, G.G.

51

Table 4: MARKOR – Model 1: Estimates and standardised values (loadings) Indicator

Latent Variable

Estimates

S.E.

Critical Ratio

1

1

Loadings

INTELGEN_1

<--

INT_GENERATION

0.838

INTELGEN_4

<--

INT_GENERATION

1.055**

0.093

11382

0.852

INTELDIS_1

<--

INT_DISSEMINATION

1.019**

0.096

10.612

0.692

INTELDIS_2

<--

INT_DISSEMINATION

1.207**

0.095

12.719

0.918

INTELDIS_3

<--

INT_DISSEMINATION

1

RESPONSE_2

<--

RESPONSE

0.645**

0.075

8.624

0.529

RESPONSE_3

<--

RESPONSE

0.578**

0.065

8.929

RESPONSE_4

<--

RESPONSE

1

RESPONSE_5

<--

RESPONSE

0.903**

0.113

7.995

0.526

RESPONSE_6

<--

RESPONSE

0.653**

0.087

7.474

0.470

RESPONSE_8

<--

RESPONSE

0.795**

0.106

7.503

0.482

0.742 0.541 0.817

1

Note: Standardised values; ** p < 0.001.

Figure 3: Market Orientation – The Construct MARKOR (Model 1)

Note: INT_GENERATION = Intelligence Generation; INT_DISSEMINATION = Intelligence Dissemination; Note: INT_GENERATION = Intelligence Generation; INT_DISSEMINATION = Intelligence Dissemination; RESPONSE = Responsiveness; er_1… er_17 = error terms. RESPONSE = Responsiveness; er_1… er_17 = error terms.

In the case of OP, we compare only two different models: Model 1, with two correlated factors, Financial Performance and Non Financial Performance and Model 2, with a single factor, OP. Statistics strongly indicated that Model 1 fits better the specific data, as it provides

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evidence of convergent and discriminant validity as well as composite reliability (see Tables 5 and 6). Table 5: Statistics of Organisational Performance Models Model

1

2

Number of Factors

2

1

Chi Square

19.450*

113.053

Degrees of Freedom

8

9

NFI

0.983

0.901

CFI

0.990

0.908

PNFI/PCFI

0.524/0,528

0.541/0.545

RMSEA

0.076

0.215

Composite Reliability

0.88/0.82

-

Variance Extracted

0.90/0.75

-

Note: * Significant at p < 0.013.

Table 6: Organisational Performance Model 1: Estimates and Standardised Values Indicator

Latent Variable

Estimates1

S.E.

Critical Ratio

Loadings2

SALES

<--

F_PERFORMANCE

1

SALES_GROWTH

<--

F_PERFORMANCE

1.011**

0.054

18.791

0.906

0.851

1.04**

0.063

16.516

0.847

GROSS MARGIN

<--

F_PERFORMANCE

MARKET SHARE

<--

NF_PERFORMANCE

1

SPACE PROD

<--

NF_PERFORMANCE

0.949**

0.048

19.648

0.888

STOCK

<--

NF_PERFORMANCE

0.843**

0.058

14.611

0.757

1

0.900

2

Note: Unstandardised values; standardised values; ** p < 0.001.

5.

Findings

After the methodological procedure indicating the adoption of the best models for the specific data, the relationship between IM, MO and OP was examined. These dimensions, which represented combinations of weighted composite values, were converted into weighted summary scales for each composite value, or factor scores. It was revealed that IM has a positive significant effect both on MO and on OP, while in turn MO has a positive impact on OP (see Figure 4 and Table 7). The IM clearly mediates the relationship between MO and OP (partial mediation). This is the first empirical evidence in the literature on the direct effect of IM both on MO and OP. Findings are consistent with the claim that creating market-oriented organisations requires a balanced internal and external focus (Piercy 1995). Moreover, the results underline that an important issue for the management is the coordination of internal activities and behaviours in order to create more value for the customer, i.e. the development of an effective internal and external orientation responding to the market and fulfilling organisational objectives (Barosso/Martin/Sanchez del Rio 2005).

Theodoridis, P.K.; Panigyrakis, G.G.

53

Figure 4: The Triangle: Internal Marketing, Market Orientation, and Organisational Performance

Table 7: Internal Marketing, Market Orientation and Organisational Performance Variables

Variables

Estimates

S.E.

Critical Ratio

Loadings1

Direct Effect

1

MO

“

IM

0.528*

0.045

11.643

0.650

0.697

OP

“

MO

0.160*

0.053

3.021

0.230

0.217

“

IM

0.248*

0.043

5.763

0.439

0.466

OP

Indirect Effect

1

0.151

1

Note: Standardised values; * p < 0.05.

The role of IM as revealed in this study fills the lack of empirical evidence in support of the idea that IM influences directly MO and the performance of the organisation (Conduit/Mavondo 2001; Ballantyne 2003) and provides confirmation that IM is a crucial precedent of MO, enabling employees to behave in a more market-oriented manner and positively affecting the organisation performance (Grönroos 1985; Gummesson 1987; Harris/Piercy 1999; Piercy/Morgan 1990). Results are also symptomatic of the work of Lings/Greenley (2009), suggesting that the implementation of the IM concept results both in a positive effect on customer satisfaction and profitability, while it also enhances the MO of the organisation (Lings/Greenley 2009). Thus, on the basis of these findings, the core research hypotheses have been validated.

6.

Discussion and Conclusion

This research aimed to examine the impact of IM and MO on OP within a retail context. Our research provides empirical findings to an under-examined triangle, hypothesised and conceptualised for years as a ‘myth’. Even though there is empirical evidence between specific dyadic relationships of the triangle – with the relationship between MO and OP dominating the relative studies – the relationships incorporating the IM concept have the less empirical sup-

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port in the literature. Therefore significant contributions can be drawn from these results on a theoretical level as well as in terms of implications for retail management. From a theoretical perspective, this study looks more deeply at the positive influence of IM on MO and on OP, showing the need for bridging internal and external marketing focus. First and foremost, the study investigated a synthesis of the IM dimensions, incorporating both the concepts of internal market orientation and internal customer orientation and indicating that the construct of IM, within the retail industry, consists of five dimensions: Formal Interaction, Reward Systems, Feedback, Internal Procedures and Internal Customer Orientation (see Appendix A). Supermarket chains seem to implement an inception of IM as they: a) consider in a recognisable manner the attitudes and needs of employees, b) remunerate diverse management level employees in relation to customer satisfaction and service, c) provide feedback on evaluation methods and employee effectiveness, d) are interested in employees’ needs, grievances and task-related queries, and e) attempt to implement the notion within the firm, using the workforce as in-house suppliers to colleagues. All the dimensions represent organisational behaviours, as the decision process is determined totally by the top management. It is an intelligible representation of a centralised formal retail organisation, as upper levels of hierarchy direct lower levels without reverse routing. Findings are consistent with research indicating that the effectiveness of external marketing depends to a great degree on the fact that employees are satisfied first and have received relative motivation and incentives (Sasser/Arbeit 1976; Berry 1984; George 1990; Berry/Parasuraman 1991; Lings/Greenley 2001; 2005; 2009; Lings 2004; Gounaris 2006; Tortosa/Moliner/Sanchez 2009) through: gathering and analysing information relative to employees (Sasser/Arbeit 1976; George 1990; Lings/Greenley 2001; 2005; Lings 2004; Gounaris 2006) in order to investigate their desires, satisfaction level and various factors affecting their work object (George 1990; Lings 2000; Lings/Greenley 2001; 2005); operating in a transparent way and being able to openly share with their employees organisational objectives, performance and financial situation data (George 1990; Dessler 1999; Pfeffer/Veiga 1999; Bansal/Mendelson/Sharma 2001; Lings/Greenley 2001; 2005), as well as sharing information constructive of an effective feedback mechanism for the employees in order to evaluate their performance and their decision-making and, thus, improving their job performance (Robbins/Langton 1999; Slater/Narver 1994a; Bansal/Mendelson/Sharma 2001; Conduit/Mavondo 2001; Lings/Greenley 2001; 2005); maintaining a responsive behaviour towards employeerelated information to design appropriate reward and motivation schemes and systems that are crucial determinants of employee behaviour (George 1990); disseminating and adopting the notion that everybody within an organisation should see him/herself as a customer of other colleagues, receiving internal service in various forms from them, while simultaneously seeing him/herself also as a supplier to other internal customers, all with the ultimate goal of cre-

Theodoridis, P.K.; Panigyrakis, G.G.

55

ating a quality service experience for consumers (George 1990; Gummesson 1987; Dunne/Barnes 2000; Lings/Greenley 2001). It is crucial to mention the lack of five out the initial ten variables being formulated the IM construct. The dimensions that were found to be non-significant and thus expunged from the construct are symptomatically some of those related to the work of Lings/Greenley (2001): External Environment, Collegial Interaction, Group Interaction, Wage Flexibility and Job Flexibility. The restriction of the construct could be reasonably explained, as a) the different context relative to the study of Lings/Greenley (2001) potentially affects the structure of the dimensions (UK vs. Greece), b) the study is conducted within a single type of retailing (supermarket chains vs. various types of retailing), c) the existence of potential differences in management style needs to be taken into account when analysing IM and organisational behaviours. Some of the core behaviours designed for implementation within a participated organisational context could not be found within a centralised control-based management (Ahmed/Rafiq 2002). Apart from the possible methodological and contextual differences in relation to the source of the specific dimensions, it is important to underline that findings illustrate the absence within retail organisations of a particular widely-implemented management policy concerning job and wage flexibility policies. Branch managers seem to have limited or no responsibility in determining the level of remuneration of their staff in order to adapt to local conditions, as well as in order to provide for a flexible environment for their team of employees in their branch level. Moreover, Group Interaction and Collegial Interaction are not supported by the SEM analysis. This finding indicates probably that both top management and branch management do not fully take advantage of the IM. There is a belief that certain explicit factors (for example, organisational and structural problems, demographics and synthesis of the body of employees, employee turnover ratio) restrict the utilization of the IM concept. Moreover, an indicated important driver for OP, financial and non-financial, is IM as specified by the strength of its relationship to OP. Findings provide credence to past literature that has assumed this relationship as an axiom, and hence, this paper contributes to the academic literature in this area (Grönroos 1981; George 1990; Lings 2001; Ahmed/Rafiq/Saad 2003; Lings/Greenley 2001; 2005; Gounaris 2006). In addition, the marketing role as a specialist function and dominant organisational ethos in retailing in Greece is ascertained. This is due somewhat to both store concentration and augmented competition. Similar characteristics were identified when comparing the MO in retailing with market-oriented manufacturing companies. They both, for example, gather, create and respond to market intelligence, coordinate business activities and have market focus. Retailers appear to recognise the value of facilitating MO within their firms.

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This research also presents empirical evidence of a direct link between MO and OP. Findings indicate anew that the ‘being in the market for the market’ philosophy implemented by supermarket chains in Greece positively affects OP. These results are equivalent to the majority those in previous work on the specific relationship, suggesting a clear positive link between MO and organisational performance (e.g., Baker/Sinkula 1999; Deshpandé/Farley 1998; Harris 2001; Matsuno/Mentzer 2000; Slater/Narver 2000; Cano/Carrillat/Jaramillo 2004), regardless of country context (Deshpandé/Farley/Webster 2000). Findings are consistent with expectations; the notion of MO as an important determinant of firm performance is clearly supported. An evident managerial implication is that MO has an effect on performance and supports a proposition throughout the literature on the necessity to satisfy customers better than competitors. Retail managers need to reconsider their primary business philosophy and become more customer- and competitor- oriented, not only at the corporate level but in branches and various departments thereof. Retailers that are more market-oriented will obtain higher levels of performance, potentially achieving a sustainable competitive advantage. This implies that, on an operational level, the retailer has to react fast and predict the future needs and preferences of its customers. There is a need to enhance the level of knowledge of the customers’ needs and preferences so as to adjust the offer to customer expectations better than the competitors will. In order to do so, MO provides the essential guidelines to follow in the firm at an operational level, increasing the efficiency and effectiveness of its marketing actions. Furthermore, IM was found to have a positive direct impact on MO and the performance of the organisation (Conduit/Mavondo 2001; Ballantyne 2003; Grönroos 1985; Gummesson 1987; Harris/Piercy 1999; Piercy/Morgan 1990), mediating the relationship between MO and OP. It is clear that the path of creating market-oriented organisations requires a balanced route as regards internal and external focus (Piercy 1995). Retail managers have to coordinate specific internal activities and behaviours in accordance to the IM concept in order to create value for the customer, i.e. to develop an effective internal and external orientation responding to the market and fulfilling organisational objectives (Barosso/Martin/Sanchez del Rio 2005). They have also to develop a better understanding of the wants and needs of employees, parallel to the understanding the external market. Retail organisations need to promote and enhance the generation of information about employees, in formal and informal ways. This chain of relationships leads to an increase in the company’s performance, something which establishes the mediating role of IM in the complex relationship between MO and OP. To conclude, supermarket chains appear in Greece to have found the best road to IM intuitively. The principal source of decision-making and implementation of tactics, policies and strategies, whether internal or external, is the head office. A situation of a responsibilityholding culture was found, as there is no evidence of disseminating authority in the decision-

Theodoridis, P.K.; Panigyrakis, G.G.

57

making modus operandi. The role of the Branch manager was found to concern primarily the practicalities of daily store routine. In order to create and maintain long-term relationships, retailers, from a managerial perspective, should combine forces with all personnel, creating an effective value chain by targeting both internal and external recipients, employees and customers (Gummeson 2000). Adopting and implementing an IM concept could achieve a competitive advantage for the retailer. This would be effected through: a) creating a tailored honing of the external and internal product by offering motivational and reward systems, based on the satisfaction of the external customer, to employees, b) getting employees involved by requesting their opinions and then providing positive or negative feedback to facilitate the implementation and adoption of an MO culture and behaviour, and c) developing a collective system of beliefs leading to a customer process orientation for both internal and external relationships. The organisational behaviours, activities, exchanges and relationships reflecting the IM concept incorporate both the conceptual forms of internal market and internal customer orientations, i.e. they combine marketing, human resources and total quality management philosophies to support and enhance an external orientation to the market and to fulfil organisational objectives about achieving a higher level of performance.

Limitations and Further Research It goes without saying that single key informants, post hoc analysis, the single context of a study and, probably, sample size are considerations when examining research limitations. Nevertheless, there is a need of further validation of the IM scale as regards the behavioural aspects of the concept in the firm. Its application in different retail and service settings would be considered inevitable. Ahmed/Rafiq/Saad (2003) call for investigation of the concept in specific service sectors. Context seems to affect the synthesis of the IM construct and probably the differentiation in the stage of implementing or adopting specific behaviours by firms. It is crucial to investigate in a more systematic manner the possibility of casual ordering within the dimensions of IM by trying to reveal any sequence in the applicability of firm behaviours. Another limitation of the study is probably the adoption of subjective performance measures, as managers, when perceiving themselves in relation to customers and competitors, may overstate their performance (Noble/Sinha/Kumar 2002). This is one of the very few studies that have examined the impact of IM and MO on OP in retail organisations. The role of marketing both as a core organisational philosophy and specialist function in retailing in Greece has begun to gain importance. Retailers have recognised that marketing – focusing both internally and externally – can create sources of competitive advantage and therefore effectiveness in the market place, especially when operating in

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fiercely competitive national and global environments. The triangle is no longer mythological. A market-oriented retail organisation applying internal marketing obtains an ameliorated organisational performance.

Appendix A Internal Marketing Construct (IM)1 Internal Marketing – IM

Mean

St. Dev.

4.54

1.51

5.19

1.4

REWARD_1 – Top management is rewarded for achieving customer satisfaction (c)

5.15

1.43

REWARD_2 – Branch Managers are rewarded for achieving customer satisfaction (c)

5.47

1.31

INTEPROCED_1 – It takes us forever to decide how to respond to changes in labour issues (r) (c)

4.3

1.58

INTEPROCED_2 – For one reason or another we tend to ignore changes in our employees needs (r) (c)

4.87

1.45

INTEPROCED_4 – Employees’ complaints fall on deaf ears most of the times (r) (c)

4.83

1.56

FEEDBACK_1 – Employees received feedback from their superiors on their job performance (b)

5.58

1.28

FEEDBACK_2 – Employees are made aware of how their performance is being appraised (b)

5.56

1.46

IMAREL_2 - We constantly seek to increase the value of services we provide to the other departments or branches (b)

5.33

1.34

IMAREL_5 – We charge departments the true value of services we provide (b)

4.52

1.37

Formal Interaction FORMAL_IN_1 – We survey our staff at least once a year to get information about their attitudes towards reward systems and compensation (a) FORMAL_IN_2 – We survey our staff at least once a year to get information about their participation in the decisions and actions of the branch (a) Reward Systems

Internal Procedures & Policies

Feedback

Internal Customer Orientation

1

Note: The questionnaires are available upon request. a = Lings/Greenley (2001); b = Conduit/Mavondo (2001); c = Kohli/Jaworski (1993); (r) = reverse order.

Theodoridis, P.K.; Panigyrakis, G.G.

59

Appendix B The MARKOR Construct Market Orientation Intelligence Generation INTL_GEN-1 – We meet with customers at least once a year to find out what products or services they will need in the future. INTL_GEN-4 – We poll our customers at least once a year to assess the quality of our products and services.

Mean

St. Dev.

5.55

1.46

5.41

1.51

5.32

1.39

5.41

1.23

5.80

1.26

6.00

1.00

5.69

0.88

5.75

1.02

Intelligence Dissemination INTL_DIS-1 – We have interdepartmental meetings at least once a quarter to discuss market trends and developments. INTL_DIS-2 – Market personnel in our organisation spend time discussing customers' future needs with other functional departments. INTL_DIS-3 – When something important happens to the market, the whole organisation knows about it in a short period. Responsiveness RESPON-2 – For one reason or another we tend to ignore changes in our customers' product or service needs. (r) RESPON-3 – We periodically review our product and service offer to ensure that they are in line with what customers want. RESPON-4 – Various departments get together periodically to plan a response to changes taking place in our business environment. RESPON-5 – If a major competitor were to launch an intensive campaign targeted at our customers, we would implement a response immediately. RESPON-6 – The activities of the different departments in this organisation are well coordinated. RESPON-8 – Even if we came up with a great marketing plan, we probably would not be able to implement it in a timely fashion. (r)

5.43

1.40

5.28

1.14

5.01

1.35

Note: (r) = reverse order.

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Information is Useful, but Knowledge is Power! Loyalty Programmes and how they can Benefit Retailers Steve Worthington and Josh Fear

Abstract This paper reports on research carried out in Australia into attitudes and behaviours of consumers who hold and use loyalty cards, issued by major retail groups. In addition to asking which cards were held; how often they were used and what the value of the rewards were that card holders redeemed, the research investigated attitudes towards the privacy of the information gained by the retailer, from both the application for and subsequent use of the loyalty card. Card holder attitudes were also sought as to the aggregation of loyalty card data and its subsequent sale back to the retailers’ suppliers and hence this being an income stream for the retailer who operates the loyalty programme.

Keywords Loyalty Programmes, Information Privacy, Knowledge Value

Steve Worthington (corresponding author) Department of Marketing, Monash University, Melbourne, Australia (Tel: + 61 399 032 754; E-mail: [email protected]). Josh Fear The Australia Institute, Canberra, Australia.

Received: February 24, 2010 Revised: July 21, 2010 Accepted: August 13, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_3, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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1. Introduction Jane is 53 years old and lives with her cat in a northern suburb of Melbourne. She works full time on the other side of town, so she prefers to drive rather than catch public transport. On the weekend Jane likes to do some gardening, and she is also fond of red wine. In fact, she drinks so much that it makes financial sense for her to buy her wine by the carton. Jane’s daughter lives a few kilometres away and has an 18-month-old girl. Jane likes to buy clothes and toys for her granddaughter, even though she has more than enough already. How do we know all these things? Because some time ago Jane applied for a loyalty card at her local supermarket so that she could earn frequent flyer points every time she goes shopping. She now hands over her card whenever she is at the checkout. Although her identity is kept confidential by the supermarket chain, Jane would probably recognise herself from the ‘profile’ that it has built from its database. The supermarket knows that she is a pet owner, because she buys cat food. It knows that she drives to work, because she buys fuel at a petrol station owned by the same retailer. From her regular purchases it also knows that she is a gardener and a wine drinker. From her occasional purchases of baby products, it has even deduced that there is a baby in the family, but that it isn’t hers. Given her age, it has assumed that Jane is a new grandmother. Jane now receives regular communications from the supermarket chain with advertising and promotions that are specially designed to appeal to her. After doing extensive survey and focus group research with people like Jane, the supermarket chain has developed a sophisticated ‘segmentation’ that allows it to target different kinds of customers with different messages. Like Jane, many people who hold a loyalty card do not realise just how valuable their personal information can be, especially when it is aggregated with that of their fellow customers. This paper explores this hidden side of loyalty cards by comparing the reality of such schemes with public perceptions. It begins by providing some background to loyalty programmes in Australia and the possible uses to which loyalty programme data can be put. It then describes the results of survey research with a sample of 832 Australians who participate in retail loyalty programmes. The paper concludes with some observations about how the environment in which loyalty programmes operate can be changed to achieve a better balance between commercial innovation and consumer privacy and autonomy.

What is a Retail Loyalty Programme? The basic idea behind a loyalty programme is to gain a bigger share of customer spending by rewarding individuals for shopping at a particular store or group of stores. The more money a customer spends, the greater the rewards. Sometimes rewards come in the form of discounts

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on products in the store. Other loyalty programmes allow members to accumulate rewards ‘points’, which they can then redeem for a variety of perceptually ‘free’ goods or services. Members of a loyalty programme are usually given a loyalty card – perhaps a simple piece of cardboard (for example indicating how many take-away coffees someone has purchased), but more usually a credit card-style plastic card with a magnetic strip or barcode containing a unique member identification number and perhaps the name of the customer. There is usually no annual fee or payment facility associated with a retail loyalty card; its sole purpose is to monitor transactions in order to reward customers in proportion to their spending. Whenever a purchase is made, information about the purchase (such as the price, product, place of purchase and date) is recorded alongside the member number. Over time, therefore the information about consumer behaviour gathered through loyalty card data can be substantial. Increased customer fidelity is just one benefit of setting up a loyalty programme; in addition, such programmes can generate a wealth of commercially valuable information about purchasing behaviour. In fact, this aspect of a loyalty programme can be just as important for a company as any increase in sales due to customers spending to earn reward points. For this reason, ‘loyalty programme’ is something of a misnomer; a better term would be ‘rewards and information exchange programme’, because that is a more accurate description of the transaction between customer and company. In return for providing information about themselves and their spending patterns, members of a loyalty programme receive rewards in proportion to their spending. The company operating the programme can then use the information that these programmes generate to more accurately target offers to customers, refine their marketing approaches, and potentially to also then sell aggregated information and ‘insights’ about consumer behaviour to their suppliers.

Types of Loyalty Programmes Before continuing, it is worth distinguishing a retail ‘loyalty card’ from other card-based schemes that aim to increase customer loyalty. For the purposes of this paper, a loyalty card refers to a personalised card, issued by a retail outlet or group, which has no payment function and which can be used to track customer purchases at the product level. It is the ability to generate data about specific product purchases that makes loyalty programmes such a potential source of commercially valuable information. There are of course a range of similar schemes which aim to encourage ‘loyalty’, but these do not generate data at the level of specific products. These include: Credit and charge card reward programmes, which are linked to a credit/charge card payment facility. Although such programmes reward fidelity to the card issuer, and garner information about the card holder and their spending behaviour, they usually cannot capture information about

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the types of products purchased – only the place and date of purchase. Some credit/charge card reward programmes are co-branded with airlines, retailers, petrol companies and other multipleoutlet businesses. Frequent flyer programmes, which were the original ‘loyalty’ programmes and are still highly successful in commercial terms. Frequent flyer programmes collect information about an airline’s highest spending customers, and reward those who fly regularly. Rewards can take the form of free flights or upgrades, but over recent years some airline frequent flyer schemes have developed into de-facto currencies which can be redeemed for a wide range of products. In some cases – and somewhat confusingly - other loyalty programmes (including retail loyalty programmes and credit/charge card reward programmes) chose to issue frequent flyer points as rewards. This paper considers only those loyalty programmes which can track purchases at the product level. In Australia, the most prominent loyalty programmes (as defined) are: FlyBuys, which is operated by Loyalty Pacific Pty Ltd. FlyBuys points can be earned at a range of retail outlets many of which are part of the Coles Supermarket Group and the National Australia Bank (NAB) groups. FlyBuys points are offered by: Best Western, Bi-Lo, Budget car rental, Coles, Curves, Jetset, Kmart, Liquorland, NAB, Source MasterCard, Target, and Travel World. There are an estimated 5.5 million members of the FlyBuys scheme, making it the largest in Australia. Everyday Rewards, which is operated by Woolworths Supermarkets. Points can be earned at Woolworths, Big W, BWS and Dick Smith. This loyalty programme was launched in mid 2009, but membership is growing strongly. The Everyday Reward card is believed to have attracted 3.8 million members by September 2009. Myer One, which is operated by Myer Department Stores. Points can be earned at Myer stores only. There are believed to be 3.1 million members, who between them hold 4.4 million cards. Priceline Club Card, which is operated by the Priceline Health and Beauty Group. Points can be earned at Priceline stores only. There are an estimated 2.7 million members. In addition to these popular national loyalty programmes, there are many other programmes in Australia of varying sizes and kinds. For example, there are loyalty programmes associated with retailers of household goods (e.g. Holy Sheet), outdoor equipment stores (e.g. Snowgum), and hotel groups (e.g. Priority Club). Each programme has a different system to earn and redeem points, in line with the kinds of customer behaviour it seeks to promote.

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2. Literature Review In their seminal article on customer loyalty, Dick/Basu (1994) discuss how retailers could manage store loyalty, in the context of both cognitive and affective antecedents being, “critical in the determination of an overall store image and influence the degree of repeat patronage”. Their paper concludes that “loyalty is a complex phenomenon that warrants a more multi-faceted conceptualisation than has been attempted previously”. Furthermore they suggest a “broadening of our view of loyalty to encompass [...] various contingencies, as well as the characteristics of different loyalty targets”. Academics have subsequently endeavoured to broaden their theoretical views on customer loyalty, a recent example being Worthington/Russell-Bennett/Hartel (2010), who propose adding the dimension of emotional loyalty, to the existing dimensions of attitudinal and behavioural loyalty. Others have focused their attention on customer loyalty programmes; O’Malley (1998), offers a critical view of such schemes, concluding that “for many organisations they have become a necessary and costly requirement for doing business” and that whilst loyalty schemes, “may have a valuable role in retail marketing, they can achieve little more than spurious loyalty”. Uncles/Dowling/Hammond (2003), suggest that there are two main aims of customer loyalty programmes. One is to increase sales revenues by raising purchase usage levels, and/or increasing the range of products bought from the supplier. The second more defensive aim, is to build a closer bond between the brand and current customers, in the hope that this will maintain the current customer base. They go on to discuss the challenges that face organisations who have loyalty programmes, but concludes that such programmes “are likely to be in a marketer’s tool kit for a long time yet”. Research into loyalty programmes in retailing also has a long pedigree with Parsingham (1998), noting that such schemes in grocery retailing are hardly a new phenomenon, with the first example of a loyalty scheme based on a usage incentive, being the trading concept of the Co-operative Societies introduced into the UK by the so-called Rochdale Pioneers in 1844. Sopanen (1996), in her review of loyalty schemes in retailing across Europe, claims that whilst many retailers run loyalty schemes, few of them claim that their customers are exclusively loyal to them. Dowling/Uncles (1997), introduced the concept of ‘polygamous loyalty’, where customers are thought to be ‘loyal’ to a limited range of brands/retailers. Further specific research into loyalty schemes in retailing has examined the employee dimension (Smith et al. 2004); the accuracy and ethics of collecting customer data from loyalty schemes (Smith/Sparks 2004), and the strategic role of loyalty schemes (Rowley 2007). The latter suggests that such schemes make a “knowledge-based contribution, to marketing competence and performance” and she uses the UK retailer Tesco, Clubcard loyalty programme as the case study to support this assertion.

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The research reported below builds on this view of loyalty programmes and discusses what information is acquired from customers who participate in retailer loyalty schemes in Australia and how those retailer’s might use such information, following the example of Tesco in the UK. In particular it considers how loyalty schemes participants feel about the use of their personal information, either to ‘profile’ them so that the retailer can better ‘target’ them with offers, or use their personal information in an aggregated form, to then sell on to the retailer’s suppliers as marketing information.

3. How Loyalty Programmes Acquire and Use Information Loyalty card programmes collect and store different types of data about their card holders. This can include: - Information provided by the customer applying for the card (e.g. age, gender, address). - Information about purchases made using the loyalty card at the point of sale (e.g. type and location of retail outlet, type of product, price). - Information about redemptions made using the rewards that the Loyalty programme provides (e.g. type of product redeemed, store at which vouchers are spent). - Responses to any surveys or other information-gathering schemes conducted by the Loyalty programme. Thus some of the kinds of information that such loyalty programmes collect and collate are: Customer demographics – e.g. age and gender. Location – e.g. home address, most visited/highest value store. Products purchased – by category, brand. Frequency of purchase – e.g. every week, last six months. Transaction value – e.g. average basket size, average category purchase. Basket analysis – which product purchases correlate with other characteristics (such as gender/age/cross-promotions). Customer behaviour – response to promotional offers and other marketing.[1] Loyalty programme operators must abide by the provisions of the Australian Privacy Act 1988, which set out how personal information can and cannot be used under the law. For example, personal information cannot be given to any third party organisation. However there is great value embedded in the information that loyalty schemes can deliver and loyalty programme operators use this personal information about their members in various ways. First and foremost, it is used to keep track of points earned and redemptions made, and then to communicate this to members. This provides an ongoing and justifiable reason for such communications to take place.

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Second, personal information is used to send marketing material to members. These two functions – communication and marketing – are in practice often carried out simultaneously. Members might receive brochures or advance notification about an upcoming sale in the same envelope as their quarterly or yearly statement of points earned. Or, since much of this activity is shifting online, they might be notified of offers in an email that also includes their points balance. Consequently, the act of joining a loyalty programme is interpreted as a signal by members to the retailer that they are interested in and willing to receive marketing materials. Having received such ‘consent’ from loyalty programme members, retailers then need to decide which marketing materials to send to whom. A very simple promotion might apply to all members – for example, a 10% discount during a certain period. More complex promotions are targeted, with different materials sent to different members. For example, since women are thought to be more likely than men to respond to an offer on cosmetics, such an offer might be sent to female members but not males. A more sophisticated approach would be to use the repository of personal information to predict which kinds of members are more likely to respond to which promotions. The database might show that certain individuals spend more on a particular class of product or at a particular store; these people would then receive an offer or deal that corresponds to those habits. Or the database might show that women between 35 and 54 are more likely than others to use a discount voucher, so members that meet this criteria would be sent vouchers rather than some other kind of promotion. Given the wealth of information available to retailers through a loyalty scheme, the extent to which promotions can be tailored is limited only by the imagination and budget of retail marketers. A third way that loyalty programme operators can use the personal information supplied by their members is to convert it into commercially valuable ‘insights’ to generate additional revenue. In a hypothetical scenario, a supplier of hair products could ask a loyalty programme operator to ascertain what types of customers typically buy its brand of hair shampoo. Armed with this knowledge, the supplier could devise a promotional campaign giving buyers of its shampoo a half-price offer on its conditioner. This offer would then be sent by the loyalty programme operator to members with the right characteristics. The personal details of members are not passed onto the supplier (because the loyalty card operator disseminates the offer), so privacy laws are not breached. The operator is compensated by the supplier – generating income from the loyalty card scheme – while the supplier benefits from being able to target potential customers with more precision than they would be able to achieve through other kinds of marketing. A fourth way that loyalty card operators can use member information is to sell it in de-identified form – i.e. after removing any markers, such as name and address, which could reveal the identity of individual members. This is already being done in some overseas markets (see the Tesco example below). Anecdotal evidence suggests that this practice does occur in Australia to some de-

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gree, and it is likely to increase as databases mature and marketers realise the commercial value of that information.

4. The Tesco Example The UK retailer, Tesco, provides a telling example of how loyalty programmes can make use of customer data (Humby/Hunt/Phillips 2004). Launched in 1995, the Tesco Clubcard is said to be the world’s most successful retail loyalty scheme. It has a participation rate of over 80% and has been extended to Tesco’s operations in Ireland, Poland and Korea. Every quarter Tesco mails out 13.5 million pieces of Clubcard promotions to British households, with 7.5 million variations in the coupons, deals, discounts and other deals sent to customers. The response rate is very high, 20 per cent of customers make use of coupons sent to them, compared to an industry average of 0.5 per cent. The high participation rate is due to the fact that coupon offers are targeted to each customer, based on their known previous purchase patterns. For example, Tesco can use its customer data to promote products that are likely to appeal to parents of students leaving home for university for the first time – such as bedding, towels or cooking equipment – at the start of the academic year. It can then use the data gleaned through this process to provide offers on products that are likely to appeal to these same parents as their offspring return home in the lead-up to Christmas – products such as computer software, DVDs or alcohol. The Clubcard scheme costs Tesco an estimated 0.8% of the value of its sales, but it recovers these costs by generating additional revenue through ‘partnerships’ with suppliers. Tesco offers its suppliers access to aggregated (i.e. de-identified) data relating to customer behaviour. Having access to information about the shopping habits of 13 million households in the UK, Tesco’s data is valuable for suppliers, who can use it to better understand the purchasing decisions of potential customers. By working with their suppliers and sharing information in this way, Tesco claims that it is ‘creating a more collaborative partnership by placing the customer at the centre of the decision-making process’.[2] Tesco also organises its suppliers around certain ‘category captains’, who are responsible for ensuring that the correct products are developed, stocked and merchandised for each category of product. The information derived from the Clubcard scheme enables Tesco to increase sales in other ways, such as through in-store advertising, differential pricing and better merchandising. Its massive database of customer habits also helps to identify opportunities for Tesco to increase its share of customer spending outside its stores. For example, Tesco has now become a provider of financial services, offering insurance policies, credit cards and other loans to consumers.[3] In Australia, some retailers are also moving into financial services. The David Jones Department Store group has recently launched a credit card through American Express, while the Woolworths Everyday Money credit card is operated in partnership with HSBC.[4]

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5. Loyalty Card Survey In order to better understand how loyalty programmes are perceived in Australia, The Australia Institute, in collaboration with the Department of Marketing at Monash University, commissioned an online survey of 1,000 people in July 2009. The survey sample was representative of the adult Australian population by age, gender and state/territory, and respondents were sourced from an independent online panel provider.[5] Respondents were drawn from the Valued Opinions Panel, which is owned and managed by the Australian arm of Research Now. It is a research-only panel (i.e. panel lists are not used to carry out any non-research activities, such as marketing) recruited from a wide variety of sources to avoid any bias associated with limited-source recruitment. Panel members are individually rewarded for their participation in a survey at a level that helps to ensure reliable levels of response and considered answers to the questions, but not so high as to attract ‘professional’ respondents. In the case of this survey, the incentive for participation was AUD 2.00 per respondent. The survey questionnaire is reproduced at Appendix A, and additional tables of survey results are available at Appendix B. Four in five survey respondents (83%) reported having at least one loyalty card; this figure is probably higher than for the population as a whole because of the nature of the survey sample.[6] The most common card was FlyBuys, held by a majority of those surveyed (59%). Around half (48%) said they had a Woolworths Everyday Rewards card, while about a quarter said they had a Myer One card or a Priceline Clubcard (25% and 23%). A few respondents (11%) said they had another type of loyalty card;[7] these included cards issued by Franklins, Dymocks, various pharmacy chains, local coffee shops and the Qantas and Virgin Blue airline frequently flyer programmes. When looking at the average number of loyalty cards held by respondents of different kinds (up to a maximum of five in this survey), it is possible to see distinct differences between men and women and between people of various ages (see Figure 1). Women held an average of 2.02 loyalty cards, while for men this was only 1.29. Average numbers of loyalty cards increase more or less consistently with increases in age. Whereas 18-24 year olds had only 1.55 cards, those over 60 reported having 1.76 cards. The frequency with which loyalty cards are used depends on which type of card it is – that is, how often people are shopping at a particular store. Cards associated with supermarkets are used very often, 67% of respondents with a FlyBuys card, and 73% of those with a Woolworths Everyday Rewards card, reported using it at least once a week. By contrast, only 6% of Myer One card holders and 7% of those with a Priceline Club card used it at least once a week. Nevertheless, very few of those with a loyalty card said they never used it – less than 5% in all cases.

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Figure 1: Average Number of Loyalty Cards 1.0

Male

1.2

1.4

1.6

1.8

25-34 years

2.02

1.55 1.60

35-44 years 45-54 years 55-64 years

1.72 1.61 1.70

65 years or older

All

2.2

1.29

Female

18-24 years

2.0

1.76

1.66

Note: n = 1,000. Question: ‘Do you have any of the following ‘loyalty’ cards?’ (maximum of 5, including ‘other’). Includes those who said they had no loyalty cards.

The great majority of loyalty card holders said they still carry their cards with them. Indeed, 93% of those with a FlyBuys or Woolworths Everyday Rewards card said they always or usually carried their card with them. Most respondents also said that in hindsight it was worth joining their loyalty card scheme. Around two in three loyalty card holders surveyed (70%) said they had redeemed awards or points from a loyalty card scheme.[8] By far the most common type of redemption was for vouchers to spend at a particular store or group of stores; 76% of respondents who had redeemed points had received this kind of reward. Around 14% had redeemed points for electronic goods, while 12% had made redemptions for airline flights or holidays. One in four (24%) said they had made another kind of redemption, most commonly discounts on fuel. Other kinds of redemptions included movie tickets, restaurant meals and even cash. Respondents were asked to estimate the dollar value of any redemption made through their loyalty card schemes in the previous 12 months. The mean value of redemptions was AUD 113.[9] Three in four of those who had made a redemption (73%) estimated its value at AUD 100 or less, while just under half (46%) made redemptions worth AUD 50 or less.

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A minority of survey respondents said they had opted out of receiving marketing materials from their loyalty card schemes – between 15 and 20% for each card type. Those who had opted out almost invariably did this when they were joining the scheme, by ticking a box on the application form; there were very few who had made a request by phone or in writing after they had joined. The survey asked which aspect of a loyalty card scheme was most important to respondents – keeping their personal information confidential or getting more rewards (see Figure 2). Around half of respondents (49%) said privacy was more important, while 45% preferred getting more rewards (with another 7% not sure about this question). Figure 2: Privacy vs. Rewards by Gender and Age 0%

20%

40%

60%

80%

Male

Female

18-24 years

25-34 years

35-44 years

45-54 years

55-64 years

65 years or older

Privacy is more important Rewards are more important

All

Note: n = 832. Question: ‘In your view, which of these aspects of a loyalty card scheme is most important?’

Women were slightly more concerned about privacy compared to men. However, there were major differences in attitudes to privacy across the age spectrum. People aged between 18 and 24

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years were much more likely to regard rewards (63%) as more important than privacy (28%). Respondents aged between 35 and 44 years were divided roughly evenly between preferring privacy (50%) and preferring rewards (48%). Among the oldest age group (65 years and over) there was an overwhelming preference for privacy (58%) over rewards (35%). In other words, concerns about privacy are associated with increasing age, and to a smaller extent with women. This finding is notable, given than women and older people tend to have more loyalty cards on average than men and younger people. Figure 3: Awareness of and Concern about Use of Personal Information 0%

20%

40%

60%

80%

To track what products you buy

To track where you buy products

To contact you with offers and promotions based on your purchasing behaviour

To compare your purchasing behaviour with others

Aware

Concerned

To 'profile' you as a particular type of customer

To be combined with data on other people and sold to third parties in de-identified form

Note: n = 832. Questions: ‘When you originally signed up for a loyalty card, were you aware that your personal information could be used in the following ways?’ ‘Would it worry you if your loyalty card scheme was using your personal information in the following ways?’

Respondents were asked whether they were aware that their personal information could be used in various ways when they originally signed up for a loyalty card (see Figure 3). A majority said that they were aware that their information could be used to track what products they buy (56%), to track where they buy products (61%), and to contact them with offers and promotions based on their purchasing behaviour (69%). Less than half said that they were aware that personal information could be used to compare their purchasing behaviour with

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others (44%) and to ‘profile’ them as a particular type of customer (46%). Only a quarter (28%) reported being aware that their information could be combined with data on other people and sold to third parties in de-identified form. As well as measuring awareness, the survey also tested levels of concern about the various ways that loyalty card schemes can use personal information. Roughly one-third of respondents (between 30 and 41%) said they would be concerned if their personal information was used in these kinds of ways. The exception was if their de-identified information was combined with others and sold on; a large majority (71%) expressed concern about such a situation. Figure 4: Concern about Use of Personal Information 0%

20%

40%

60%

80%

To track what products you buy

Privacy is more important Rewards are more important To track where you buy products

To contact you with offers and promotions based on your purchasing behaviour

To compare your purchasing behaviour with others

To 'profile' you as a particular type of customer

To be combined with data on other people and sold to third parties in de-identified form

Note: n = 832. Questions: ‘In your view, which of these aspects of a loyalty card scheme is most important?’ ‘Would it worry you if your loyalty card scheme was using your personal information in the following ways?’

Concern about how data is used was stronger among respondents who indicated that keeping their personal information confidential was more important than getting more rewards (see Figure 4). Four in five of these respondents (79%) said that they would be concerned if their information was sold to third parties in de-identified form, compared with 63% of those who

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said that rewards were more important than privacy. Around half of respondents who said privacy was a priority (48%) also expressed concern about their information being used to ‘profile’ them. The minority of respondents who said they did not have any loyalty cards (17% of the survey sample) were asked why this was so. Although many (38%) said there was no particular reason or that they just weren’t interested, a sizeable proportion (30%) said that they wouldn’t get enough in return for using loyalty cards. Fourteen per cent said they had never got around to joining a loyalty card scheme, while 13% said that they had had loyalty cards in the past but got rid of them. Only a small proportion (2%) cited privacy concerns as the reason for not having any loyalty cards.

6. Conclusions Loyalty cards are already a widespread feature of the retail environment in Australia, with the most popular loyalty programmes now having millions of members. The largest programme, FlyBuys, has more than 5 million members, and membership of the Woolworths Everyday Rewards scheme, which was launched relatively recently, is growing very quickly. According to our survey, women are much more likely to have a loyalty card than men, and membership of loyalty programmes is more common among older rather than younger people. The majority of survey respondents with a loyalty card reported using them regularly and carrying them around in their purse or wallet. Around two in three people surveyed said that in hindsight it was worthwhile joining the loyalty card programme, while around 20% said it was not worthwhile. Despite such indications of general satisfaction with the big loyalty programmes in Australia, it is likely that these schemes have a large number of ‘lapsed’ members – that is, people who applied for a card and perhaps used it for a time but no longer do so. There is no publicly available information from loyalty programme operators on the proportion of members which are ‘active’ or ‘lapsed’. However, our survey results show that the most common reason for not joining loyalty schemes is not getting enough in return; only a small proportion of people cite privacy reasons. Survey findings also suggest that most members of loyalty programmes are aware that their information can be used to track what products they buy, to track where they shop, and to contact them with offers and promotions. There is relatively little concern about loyalty programme operators using information in these ways. Fewer people are aware that their personal information can be used to compare their purchasing decisions with others and to ‘profile’ them, and around one in three respondents said they would be concerned if this occurred.

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Very few people were aware that their information could be combined with data on other people and sold to third parties in de-identified form, but a large majority (71%) said they would be concerned if this took place. Concerns about privacy are strongest amongst women and among older people, the very demographic groups that are most likely to be members of loyalty programmes. 70% of loyalty card holders said they had redeemed awards or points from a loyalty card scheme. By far the most common type of redemption was for vouchers to spend at a particular store or group of stores; three in four respondents who had redeemed points had received this kind of reward. Other kinds of redemptions included electronic goods, airline flights or holidays, and discounts on fuel. The financial value of redemptions allows us to put a dollar value on the benefit to a typical loyalty programme member for actively participating in a loyalty programme (by regularly presenting their card at the point of sale). At a normal level of retail spending, someone can expect to receive around AUD 113 worth of rewards points per year.

Economic Implications The costs of running a loyalty scheme can be substantial when spread across millions of members. For instance, it has been estimated that the cost to Woolworths of purchasing Qantas frequent flyer points accrued through its Everyday Rewards scheme will be between AUD 60 and AUD 80 million per year and “lift the cost of customer loyalty by 0.4c to 3c for every dollar spent by customers” (Mitchell 2009, p. 9). There are a number of ways that retailers can recoup these costs. The first and most obvious is to raise prices. If a retailer with a loyalty programme did this, it would mean that members of the loyalty programme, who receive benefits in the form of reward points, are being crosssubsidised by customers who are not members, and therefore do not receive any rewards. In such a case, it would cost someone who is not a member of a loyalty program AUD 113 per year in forgone benefits to shop at a retail outlet that offers a loyalty programme. Another way to recover the costs of running a loyalty programme is to generate more revenue by increasing sales volumes. This is the ostensible purpose of a ‘loyalty’ scheme – to encourage people to spend their money at one store rather than another, so as to earn reward points. But an even more effective way to increase sales is to turn the purchasing data from a loyalty programme into commercially valuable information. Such information might be used to refine the range of products sold to match customer habits, or to develop offers or deals targeted at particular types of shoppers. For example, it has been reported that Woolworths uses postcode data from its Everyday Rewards members to evaluate possible locations for new supermarkets and petrol outlets (Mitchell 2009, p. 9).

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In addition, programme operators can partially offset the cost of their loyalty programme by aggregating member data and selling this in de-identified form to suppliers or other corporate entities. The UK retailer Tesco provides a telling example of how this can be done; its customer database is based on the behaviour of the 13 million households that hold a Tesco Clubcard. Information on who buys which products, when and where they buy them and how much they spend can be seen at the level of individual products. This information can help manufacturers and suppliers to understand the purchasing decisions and habits of customers and to design products and marketing campaigns accordingly. The information that suppliers purchase from Tesco is aggregated, so there are no breaches of privacy law. By ‘collaborating’ with the retailer in this way, partners also strive to reach or retain a position as a preferred supplier, further strengthening Tesco’s market power. There is a lack of awareness in Australia about the potential for loyalty programme data to be aggregated and subsequently sold on to third parties. Selling data or ‘insights’ in this way can generate income for loyalty programme operators, and loyalty card holders are probably undervaluing the information that they provide, both at the time they apply for and in their ongoing use of a loyalty card. There is a strong case for loyalty card operators to recognise the true value of such information, both by revealing more fully the ways that data is used and by expanding the financial value of rewards provided to customers. Supporting the need for better recognition of the value of customer information is the prospect of rewards ‘points’ being devalued over time. For example, the financial value of points accrued through credit card reward programmes have been declining for some years. In 2003 an average spend of AUD 12,400 p.a. was required to earn a AUD 100 shopping voucher. By 2009 the average spend required was AUD 17,000 – a much higher rate of ‘inflation’ than the consumer price index (Payment Systems Board 2009). Unless consumers are vigilant, there is no barrier to loyalty programme points being subject to inflation of a similar kind Retailers and other loyalty program providers can be prone to effectively ‘devaluing’ their loyalty points, by increasing the number of points required to redeem a particular value, as the example above demonstrates. Hence customers of retailers who use loyalty programs need to be aware of the potential for such ‘devaluations’ and to, where appropriate redeem their points with some regularity.

Recommendations With loyalty card programmes now having a very strong presence in the Australian retail sector, the fact that many consumers remain unaware of how programme operators can use their personal information is a concern. Rather than merely abiding by the Privacy Act, retailers should seek to gain truly informed consent from their loyalty programme members before using their information to ‘profile’ or ‘segment’ them or to pass de-identified information

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onto other third parties. Describing how customer information could be used in a statement of privacy policy will not automatically translate into consumer understanding. Retailers should therefore improve the ways that they disclose and explain, in plain English, what they do with the information contained in their customer databases. For their part, consumers should be mindful of the value of the information they provide to retailers every time they hand over their loyalty card. In some cases this information will be worth much more to the loyalty programme operator than the dollar value of any redemptions or rewards they might receive. As loyalty schemes mature over time, the commercial value of such information will increase, yet rewards points are often subject to devaluation over time – meaning that customers need to spend more and more to ‘earn’ the same amount of rewards. Finally, consumers who are not members of a loyalty programme need to be cognisant of the possibility that they are subsidising loyalty programme members through their purchases. Retailers need to cover the costs of their loyalty programmes – which can be considerable – and if they cannot do so in full by attracting more customers, then they may raise prices.

Appendix A Survey Questionnaire The survey contained the following questions, as well as a series of demographic questions. Q1. Do you have any of the following ‘loyalty’ cards? - FlyBuys – skip to Q3 - Woolworths Everyday Rewards – skip to Q3 - Myer One – skip to Q3 - Priceline Clubcard – skip to Q3 - Other loyalty card (please specify) – skip to Q3 - None of these Q2. Is there a particular reason why you don’t have any loyalty cards? - I have privacy concerns – skip to demographic questions - I’ve had them in the past but got rid of them/stopped using them – skip to demographic questions - I never got around to joining a loyalty card scheme – skip to demographic questions - I wouldn’t get enough in return for using them – skip to demographic questions - Other reason – skip to demographic questions - No particular reason/just not interested – skip to demographic questions Q3. How often do you use these cards? (asked in a grid; only the cards selected in Q1) - Every day

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At least once a week At least once a month At least once every six months Less than once every six months Never Not sure

Q4. Have you asked not to receive information about offers and promotions from these loyalty schemes? (asked for each card type) - Yes – by ticking a box on the application form - Yes – by making a request by phone - Yes – by making a request in writing - No Q5. Have you ever redeemed any awards or points from these loyalty schemes? - Yes - No – skip to Q8 - Not sure – skip to Q8 Q6. What kind of redemptions did you make? [multiple response] - Airline flights/holidays - Vouchers to spend at a particular store/group of stores - Hotel rooms - Rental cars - Electronic goods - Other (please specify) Q7. Please estimate the dollar value of any redemption you made through loyalty card schemes in the last 12 months. Q8. In your view, which of these aspects of a loyalty card scheme is most important? - Keeping my personal information confidential - Getting more rewards - Not sure Q9. When you originally signed up for a loyalty card, were you aware that your personal information could be used in the following ways? - To track what products you buy - To track where you buy products - To contact you with offers and promotions based on your purchasing behaviour - To compare your purchasing behaviour with others

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- To ‘profile’ you as a particular type of customer - To be combined with data on other people and sold to third parties in de-identified form Q10. Would it worry you if your loyalty card scheme was using your personal information in the following ways? [yes/no] - To track what products you buy - To track where you buy products - To contact you with offers and promotions based on your purchasing behaviour - To compare your purchasing behaviour with others - To ‘profile’ you as a particular type of customer - To be combined with data on other people and sold to third parties in de-identified form Q11. Do you still carry these cards with you? (asked for each card type) - Always - Usually - Sometimes - Rarely - Never - Not sure Q12. In hindsight, was it worthwhile joining this scheme? (asked for each card type) - Yes - No - Not sure

Appendix B Additional Survey Results Table B1: Which loyalty cards do you have? n

%

FlyBuys

586

58.6

Woolworths Everyday Rewards

479

47.9

Myer One

253

25.3

Priceline Clubcard

234

23.4

Other

109

10.9

One or more loyalty cards

832

83.2

No loyalty cards

168

16.8

1,000

100

Total

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Table B2: How often do you use your loyalty card? FlyBuys Every day

Woolworths ER

Myer One

Priceline Clubcard

7.5%

6.5%

-

-

At least once a week

59.7%

66.2%

6.3%

7.3%

At least once a month

23.5%

19.8%

37.5%

41.0%

At least once every 6 months

5.3%

3.3%

36.0%

34.6%

Less than once every 6 months

1.9%

1.7%

14.6%

12.8%

Never

1.5%

1.5%

4.3%

3.8%

Not sure

0.5%

1.0%

1.2%

0.4%

Total

100%

100%

100%

100%

Note: Base = 586 (FlyBuys), 479 (Woolworths ER), 253 (Myer One), 234 (Priceline Clubcard).

Table B3: Do you still carry your loyalty card(s)? FlyBuys

Woolworths ER

Myer One

Priceline Clubcard

Always

80.0%

78.3%

67.6%

67.5%

Usually

13.1%

14.8%

17.4%

15.4%

Sometimes

2.9%

4.0%

9.1%

6.8%

Rarely

2.0%

1.7%

4.0%

5.6%

Never

1.9%

1.0%

1.6%

4.3%

-

0.2%

0.4%

0.4%

100%

100%

100%

100%

Not sure Total

Note: Base = 586 (FlyBuys), 479 (Woolworths ER), 253 (Myer One), 234 (Priceline Clubcard).

Table B4: In hindsight, was it worthwhile joining this scheme? FlyBuys

Woolworths ER

Myer One

Priceline Clubcard

Yes

65.0%

62.8%

58.5%

59.4%

No

19.8%

15.4%

22.5%

21.8%

Not sure

15.2%

21.7%

19.0%

18.8%

Total

100%

100%

100%

100%

Note: Base = 586 (FlyBuys), 479 (Woolworths ER), 253 (Myer One), 234 (Priceline Clubcard).

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Table B5: Types of redemptions n

%

Vouchers to spend at a particular store/group of stores

441

76.3

Electronic goods

83

14.4

Airline flights/holidays

71

12.3

Hotel rooms

45

7.8

Rental cars

6

1.0

138

23.9

Other

Note: Base = 578. Includes only respondents who said they had redeemed awards or points from a loyalty card scheme. Because the question about types of redemptions was multiple response, percentages add up to more than 100 %.

Table B6: Have you opted out of receiving marketing materials? FlyBuys

Woolworths ER

Myer One

Priceline Clubcard

16.4%

18.4%

17.4%

14.1%

Yes – by making request by phone

1.5%

1.0%

2.4%

0.9%

Yes – by making a request in writing

0.2%

-

-

-

No

81.9%

80.6%

79.8%

85.0%

Total

100%

100%

100%

100%

Yes – by ticking a box on the application form

Note: Base = 586 (FlyBuys), 479 (Woolworths ER), 253 (Myer One), 234 (Priceline Clubcard).

Table B7: Is there a particular reason why you don’t have any loyalty cards?1 No particular reason/just not interested

n

%

64

38.1

I wouldn’t get enough in return for using them

50

29.8

I never got around to joining a loyalty card scheme

24

14.3

I’ve had them in the past but got rid of them/stopped using them

21

12.5

I have privacy concerns

4

2.4

Other reason

5

3.0

168

100

Total

Note: 1 Includes only respondents who reported having no loyalty cards.

Notes [1]

This information was derived from a variety of loyalty programme providers, both from publicly available information and personal discussions by the authors.

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[2]

Dunnhumby 2009. Case studies – Tesco. http://www.dunnhumby.com/uk/our-clientscase-studies accessed 26 November 2009.

[3]

See www.tescofinance.com/personal/finance/home.jsp.

[4]

See http://www.everydaymoneycard.com.au/Numbers/ and http://www.davidjones. americanexpress.com/dsmlive/dsm/int/au/en/davidjones/davidjonescard/davidjonesam excard.do?vgnextoid=0fca417db755a110VgnVCM200000cff4ad94RCRD, accessed November 15, 2010.

[5]

Further details about the survey methodology are available in the Appendix A.

[6]

Respondents were sourced from an online panel of people who had agreed in advance to answer surveys. The high proportion of respondents with one or more loyalty cards is likely to be due to an overrepresentation of loyalty card holders among the online panel community (because there is an intuitive similarity between joining a loyalty card scheme and joining an online survey panel). Although this makes it difficult to draw conclusions about the incidence of card ownership across the population, other survey results (which focus almost exclusively on people who have loyalty cards) remain statistically reliable.

[7]

This proportion would in all likelihood have been higher if additional cards had been presented in the survey.

[8]

This figure applies to any redemption made from the loyalty card schemes referred to in the survey.

[9]

In order to account for the value of points accrued but not redeemed in the last 12 months, all respondents with a loyalty card have been included in calculating an average redemption amount. Respondents who said they had not made a redemption in the last 12 months were assigned a value of AUD 0. If high-value redemptions (greater than AUD 1,000) are excluded from analysis, the average redemption amount was AUD 79.

[10]

There are other parallels between loyalty programmes and credit card rewards programmes. The Reserve Bank recently intervened in the market for payment cards to promote more efficient and transparent payments system. There was a concern that consumers who paid by credit card were being cross-subsidised by consumers who paid by other payment mechanisms, such as cash, cheque or debit card. There was also a concern that those credit card holders whose cards had a rewards programme, were being cross–subsidised by those credit card holders who chose not to carry and use such cards. This would be similar to way shoppers who do not have a loyalty card.

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References Dick, A.; Basu, K. (1994): Customer loyalty: towards an integrated conceptual framework, in: Journal of the Academy of Marketing Science, Vol. 22, No. 2, pp. 99-113. Dowling, G.; Uncles, M. (1997): Do customer loyalty programs really work?, in: Sloan Management Review, Vol. 38, No. 4, pp. 71-83. Humby, C.; Hunt, T.; Phillips, T. (2004): Scoring points: how Tesco is winning customer loyalty, London. Mitchell, S. (2009): Woolies out to woo unfaithful shoppers, in: Australian Financial Review, April 26, p. 9. O’Malley, L. (1998): Can loyalty schemes really build loyalty?, in: Marketing Intelligence and Planning, Vol. 16, No. 1, pp. 47-55. Passingham, J. (1998): Grocery retailing and the loyalty card, in: Journal of the Market Research Society, Vol. 40, No. 1, pp. 55-63. Payment Systems Board (2009): Annual report, Reserve Bank of Australia, http://www.rba.gov.au/PublicationsAndResearch/PSBAnnualReports/2009/Pdf/2009-psbann-report.pdf, accessed November 12, 2010. Rowley, J. (2007): Reconceptualising the strategic role of loyalty schemes, in: Journal of Consumer Marketing, Vol. 26, No. 6, pp. 366-374. Smith, A.; Sparks, L.; Hart, S.; Tzokas, N. (2004): Delivering customer loyalty schemes in retailing: exploring the employee dimension, in: International Journal of Retail and Distribution Management, Vol. 32, No. 4, pp. 190-204. Smith, A.; Sparks, L. (2004): All about Eve?, in: Journal of Marketing Management, Vol. 20, No. 3-4, pp. 363-386. Sopanen, S. (1996): Customer loyalty schemes in retailing across Europe, Templeton College, Oxford University. Uncles, M.; Dowling, G.; Hammond, K. (2003): Customer loyalty and customer loyalty programs, in: Journal of Consumer Marketing, Vol. 20, No. 4, pp. 294-316. Worthington, S.; Russell-Bennett, R.; Hartel, C. (2010): A tri-dimensional approach for auditing brand loyalty, in: The Journal of Brand Management, Vol. 17, No. 4, pp. 243-253.

Modelling the Impact of 3D Authenticity and 3D Telepresence on Behavioural Intention for an Online Retailer Raed Algharabat and Charles Dennis

Abstract This study aims to investigate the effects of three dimensional (3D) product authenticity and 3D product telepresence on consumers’ behavioural intention. Particularly, we define and operationalise 3D authenticity based on the psychological state in which virtual objects presented in 3D in a computer-mediated environment are perceived as actual objects. However, to define and operationalise 3D telepresence, we follow the existing literature which emphasises on the transportation state to define consumers’ virtual experience. Moreover, we investigate the effects of control and animated colours on the creation of 3D product authenticity and 3D product telepresence constructs, which in turn impact behavioural intention. A hypothetical retailer website presents a variety of laptops which allow participants to control the content and form of the 3D flash. We find that defining and operationalising virtual experience based on the 3D product authenticity concept is significantly associated with behavioural intention in comparison to the 3D telepresence construct.

Keywords Virtual Experience, 3D Telepresence, 3D Authenticity, Control, Animated Colours, Behavioural Intention

Raed Algharabat (corresponding author) Marketing Department, University of Jordan, Amman, Jordan. (E-mail: [email protected]). Charles Dennis Marketing Department, Brunel University, London, UK.

Received: March 13, 2010 Revised: July 21, 2010 Accepted: August 13, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_4, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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Introduction

A three-dimensional (3D) virtual model enhances users’ virtual, experiential and instrumental experiences (Algharabat/Dennis 2010). A 3D presentation enables consumers to interact with products, enriches their learning processes, and creates a sense of being in a simulated real world (Klein 2003; Li et al. 2001; 2002; 2003). Steuer (1992, p. 78) defines virtual reality (VR) as “a real or simulated environment in which a perceiver experiences telepresence”. In contrast, virtual experience (VE) derives from VR and can be defined as “psychological and emotional states that consumers undergo while interacting with a 3D environment” (Li et al. 2001, p. 14). Despite widespread discussions and various definitions of VE, we notice that previous scholars, within the online retail context, consider the notions of 3D telepresence as virtual substitutes for actual experience with the products. However, the telepresence and presence constructs are not necessarily wholly appropriate concepts for marketers since they represent a process of being mentally transported into other areas or being immersed into an illusion environment (Algharabat/Dennis 2010). Such notions may not be particularly helpful for marketers and website designers who are concerned with 3D product visualisation of real products. This study aims to compare the impact of 3D product authenticity construct and 3D product telepresence on behavioural intention. We use Algharabat/Dennis’ (2010) theory of 3D product authenticity and 3D telepresence theory (Kim/Biocca 1997) to compare their impact on users’ behavioural intention. To compare the impact of 3D telepresence and 3D authenticity on behavioural intention, we first discuss the notion of 3D telepresence then draw on Algharabat/Dennis’ (2010) theory of 3D product authenticity.

2.

Theoretical Background

2.1.

Telepresence and 3D Telepresence

VR terminologies enter the vocabulary with the emergence of immersive virtual reality (IVR) devices, such as head-mounted display, which allow users to interact with virtual environments and to visualise different objects (Suh/Lee 2005). As a result, the notions of telepresence emerge. Notwithstanding, previous literature in the IVR area has provided readers with different classifications and conceptualisations of VR experience. For example, Steuer’s (1992, p. 76) definition of VR focuses on human experience, not technological hardware, and differentiates between two types of VE; presence and telepresence. Whereas presence refers to “the experience of one’s physical environment; it refers not to one’s surroundings as they exist in the physical world, but to the perception of those surroundings as mediated by both automatic and controlled mental processes”, telepresence is “the experience of presence in an environment by means of a communication medium”. However, Biocca (1992) defines telepresence as users’ ability to be, psychologically, transported into another area. To

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extend prior literature, Lombard/Ditton (1997) identify six taxonomies of VE: social richness, realism, transportation, immersion, social actor within medium and medium as social actor. Online retail literature introduces the non-immersive virtual reality (NIVR) environment, which allows users to interact with e-retailers websites and products using 3D product visualisations in desktop or laptop computers (Suh/Lee 2005). Furthermore, e-retailing literature defines and operationalises VE based on three elements; interactivity and vividness of the 3D product visualisation, and the notion of telepresence. Notwithstanding, Lombard/Ditton’s (1997) classification of VE, only two types are identified in the e-retailing area. The first is VE as telepresence, or the illusion of being in a place far from the physical body (based on Biocca 1997; Heeter 1992). This conceptualisation of VE relates to transporting a user, self, or place, to another place. The second form is VE as a social telepresence, such that other beings exist in the VR world with whom users can interact (e.g., avatars). Authors such as Heeter (1992) and Lombard/Ditton (1997) empirically test this concept, and McGoldrick and colleagues (2008) emphasise the avatar’s role in enhancing virtual personal shopper capabilities. Despite widespread discussions and various definitions of telepresence (Lee 2004; Li et al. 2001), we notice that previous scholars, within the online retail context, consider the notion of telepresence as a virtual substitute for actual experience with the products. Thus previous marketing literature has focused on defining and conceptualising telepresence virtual experience based on websites’ adverts or 3D virtual models (see Table 1). For example, to measure cyberspace telepresence, Shih (1998) proposes a conceptual framework, and posits that the vividness of the information (operationalised as multi-sensory information, i.e. breadth and depth) that a consumer receives in cyberspace and the interactivity of the cyberspace technology (operationalised as control, speed, and feedback) provide the main antecedents of telepresence (i.e., being there). In turn, Coyle/Thorson (2001) focus on videocassette movies and investigate the effects of progressive levels of interactivity (number of choices and presence of a clickable image) and vividness (audio and animation) of web marketing sites to measure participants’ telepresence (i.e., being there). Klein (2003) employs a simple technology such as Authorware © 3.0 and 4.0 to examine and measure the effects of telepresence (i.e., being transported into another area) on consumer responses. Moreover, Klein (2003) finds that interactivity (user control) and media richness (breadth of sense channels) emerge as the main antecedents of consumers’ telepresence, with significant positive influences on telepresence creation. Fortin/Dholakia’s (2005) empirical research reveals the direct and indirect impacts of interactivity (degree of control, response time) and vividness (breadth and depth of the message, colours, graphics, quality and resolution) on social telepresence. High levels of interactivity and vividness have significant impacts on perceived social telepresence. Hopkins et al. (2004) investigate websites’ telepresence and consider vividness (but not inter-

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activity) as the main determinant of telepresence virtual experience. On the other hand, other scholars (e.g., Li et al. 2001; 2002; 2003; Fiore et al. 2005; Suh/Chang 2006; Yang/Wu 2009) define and measure VE based on the 3D telepresence notion. Such scholars investigate the role of 3D virtual models to enhance users’ 3D telepresence experience. However, we claim that using the notions of 3D telepresence or presence and their definitions, to measure 3D virtual experience are not necessarily wholly appropriate concepts for marketers and website designers. Because (i) these notions represent a process of being mentally transported into other areas or being immersed into an illusion environment, such notions often reflect negative meanings such as immersion, delusion and transportation (Lee 2004); (ii) presence and telepresence measurement scales, were originally built upon external devices, such as headmounted display, which are not used in the online retailers’ 3D virtual model; and (iii) the lack of agreement upon the antecedents of telepresence and presence (interactivity and vividness) constructs often complicates measuring the 3D product visualisation VE. Table 1: Previous Research on Online VR Using 3D Telepresence Virtual Experience Measurement Conceptual

Study

Sample

Stimuli

Shih (1998)

Conceptual paper

N/A

Coyle/Thorson (2001)

Students

Transportation into another place; being there

Li et al. (2001)

Student

Videocassette movies Blues music CDs Women’s golf clothing and equipment Hot sauces 3D products: bed, ring, watch, laptop computer

Li et al. (2002)

Students

3D/2D: bed, ring, watch, laptop advertisements

Li et al. (2003)

Students

Klein (2003)

Non-students

Hopkins et al. (2004)

Students

3D/2D product type: wristwatch, bedding material and laptops Authorware © 3.0 and 4.0 Study = 1, Wine Study = 2, Face cream Website for the National Arbor Day Foundation

Presence: based on physical engagement, naturalness, and negative effects Telepresence and virtual affordance

Fiore et al. (2005a)

Students

Clothing (3D virtual model)

Suh/Chang (2006)

Students

Video-clip Multiple-pictures VR 3D

Yang/Wu (2009)

Students and nonstudents

My Virtual Model An advanced IIT website

2.2.

Illusion and immersion

Telepresence: transporting into another area Telepresence: being transported into another area Telepresence: being there Telepresence: transported into another area

TM

Telepresence: transported into another area

Virtual Experience Antecedents Vividness (breadth and depth) and interactivity (speed and control) Vividness (breadth and depth) and interactivity (speed and control) Virtual experience is vivid, involving, active, affective psychological states Interactivity and media richness Interactivity and media richness User control and media richness (full-motion video and audio) Media richness Interactivity (modifying the content) and visual vividness User control and media richness Interactivity and vividness

3D Authenticity

Algharabat/Dennis (2010) bridge the above gaps. They notice that none of the previous definitions of telepresence or presence that use 3D virtual models realistically taps consumers’

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virtual experiences. The authors posit that a 3D virtual experience should be an authentic representation of the direct (offline) experience. Furthermore, they propose a new notion that relates to the simulation of online products and virtual experience, namely, the authenticity of the 3D product visualisation. The authors assert that telepresence and presence are not particularly well suited to the online retail context, because they reflect illusion and transportation to other places. In contrast, the concept of 3D authenticity of the product visualisation implies the ability to simulate the product virtual experience in bricks-and-clicks contexts. Algharabat/Dennis (2010, p. 101) define the authenticity of the 3D product, in a computermediated environment, as: a psychological state in which virtual objects presented in 3D in a computer-mediated environment are perceived as actual objects. Furthermore, the authors identify users’ ability to control the content and form of the 3D flash (interactivity) and their ability to see the products with their chosen colours (vividness) as the main antecedents of 3D authenticity.

3.

Conceptual Framework

3.1.

3D Telepresence and 3D Authenticity Antecedents

Figure 1 explains the main constructs and their relationships. We use the control construct to represent interactivity in an online retail context. Algharabat/Dennis (2010) define control as “users’ abilities to choose the content and form of the 3D virtual model, particularly, their ability to rotate, zoom in or out on the product, and to click on any part of the 3D virtual model to get instant information about it, and the ability of the 3D virtual model to respond to participants’ orders properly”. Previous scholars (Coyle/Thorson 2001; Klein 2003; Shih 1998) posit that user control has a positive impact on the creation of 3D telepresence. Moreover, Algharabat and Dennis [1] (2010) posit that control has a positive impact on the creation of a realistic 3D product visualisation. We hypothesise that: H1a: A high level of perceived control of 3D product visualisation increases 3D telepresence. H1b: A high level of perceived control of 3D product visualisation increases 3D authenticity. Some 3D product visualisations, in the online retailer, require visual and auditory channels for facilitating consumers’ vividness; others manifestly need only visual aspects. We focus on one aspect of vividness, namely, breadth, while holding depth constant. Specifically, we focus on one aspect of vividness breadth, namely, animated colours. Animated coloured pictorial images used in this study to represent consumers’ ability to see 3D products in their colours (animated skins) just as they would see them in person. High-quality online animated colours may enhance consumers’ perception of the 3D telepresence (e.g., Fortin/Dholakia 2005; Klein

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2003; Shih 1998; Schlosser 2003). Moreover, consumers’ ability to change the animation (colours) of the 3D product might help them sense authenticity over the product, and it might lead to a true virtual experience, according to research on online shopping (Algharabat/Dennis 2010; Klein 2003). Therefore: H2a:

A high level of 3D animated colours increases 3D telepresence.

H2b: A high level of 3D animated colours increases 3D authenticity. Figure 1: Conceptual Framework

3.2.

The Effects of 3D Authenticity and 3D Telepresence on Behavioural Intention

The role of 3D product visualisation in enhancing behavioural intentions appears well supported. For example, Klein (2003) posits a positive relationship between telepresence and consumers’ attitudes. Hopkins et al. (2004) find a significant impact of perceived telepresence on attitude towards the advertisement and brand. On the other hand, we claim that the relationship between 3D authenticity and behavioural intention might be stronger than the relationship between 3D telepresence and behavioural intention. Such claim comes to the surface after our careful looking at the previous relationships between 3D telepresence and behavioural intention. For example, Suh/Chang (2006) posit a non-significant relationship between the two constructs. However, Fiore et al. (2005) assert a positive relationship between 3D telepresence and behavioural intention (standardised path coefficient = 0.14*). H3a:

The relationship between 3D authenticity and behavioural intention is positive.

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H3b: The relationship between 3D telepresence and behavioural intention is positive.

4.

Method and Sample

4.1.

Method

We designed a hypothetical retailer’s website with one stimulus for this study. The stimulus was illustrated on 3D product visualisation site that allowed participants to view the focal product, laptops, from different angles; they also could rotate the product and zoom it in or out. The 3D stimulus is intended to help consumers to imagine the product in appropriate and relevant ways and thus enhance their virtual experiences (Li et al. 2001). The website we created for this study was not previously known to users, nor did users have any knowledge of the fictitious brands on it. Thus, we eliminated any impact of previous experiences or attitudes (Fiore et al. 2005). The site offers a wide variety of laptops, similar to those that many college-aged women and men currently buy and use. Therefore, site provides a suitable context for the present sample. In designing this interface, we consider a comprehensive site to visualise an electronic online retailer to surpass actual experience. To determine the appropriate time exposure to an online stimulus, we followed Zajonc’s (2001) study and set a time limit of five minutes to navigate our stimulus. After viewing the stimulus for this time, the subjects completed a questionnaire. To check the common method bias, we followed the Harman's single-factor test, confirmatory factor analysis (CFA), and multitrait-multimethod (MTMM, Podsakoff et al. 2003) techniques. Results show that common method variance is not of great concern and thus is unlikely to confound the interpretations of our results. See Appendix. Participants were informed that this study pertained to consumers’ evaluations of an electronic retailer’s website. The questionnaire contained five-point Likert-type scales, anchored by “strongly disagree” and “strongly agree”. To measure the perceived control construct, we developed a three-item scale that centres on users’ ability to rotate and zoom in or out the virtual model based on McMillan/Hwang’s (2002) and Song/Zinkhan’s (2008) studies. To measure animated colours, we developed a three-item animated colour scale based on Fiore and colleagues (2005), Klein’s (2003) and Steuer’s (1992) studies. The items tap how closely the simulated sensory information reflects the real product. For 3D telepresence, we used a modified version of Kim/Biocca’s (1997) scale that has been used by the majority of previous scholars (e.g., Klein 2003; Li et al. 2002) in the marketing filed to measure users’ virtual experience based on their feelings of being transported into another area when using a rich media such as 3D, video or TV. This scale measures users departure and arrival once using a 3D flash on an online retailer.

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To measure 3D authenticity, we used Algharabat/Dennis’ (2010) scale. To measure behavioural intention, we used a modified version of Fiore et al.’s (2005) scale.

4.2.

Sample

Student samples have often been used in online shopping research (e.g., Li et al. 2002; 2003; Fiore et al. 2005; Kim et al. 2007; Balabanis/Reynolds 2001). This is justifiable as students are computer-literate, and have few problems in using new technology. Students also are likely consumers of electrical goods (Jahng et al. 2000). We used a sample of 400 students for the data collection. The sample was gender balanced, consisting of 47% women and 53% men, and 90% of the sample ranged from 18 to 30 years of age. Approximately 94% reported having had prior online shopping experience. We conducted a non-response bias test (Armstrong/Overton 1977) to confirm the generalisation of our results via comparing the late responses with the early responses. Results show no significant difference between respondents (p > 0.05). As a result, non-response bias was considered not to be a serious limitation in this study.

5.

Results

5.1.

Measurement Model

We evaluated the measurement and structural equation models using AMOS 16. The measurement model includes 18 indicators, and we provide its results in Table 2, including the standardised factor loading, standard error (SE), t-values, average variance extracted, and composite reliability for each construct. The standardised factor loadings (Ȝ) are all greater than .60. The composite reliabilities for perceived control (.86), animated colours (.74), 3D authenticity (.85), 3D telepresence (.85), and behavioural intention (.89), all are acceptable (Hair et al. 2006). Moreover, average variance extracted by each construct exceeds the minimum value recommended by Hair et al. (2006), (i.e., equals or exceeds .5), indicating convergent validity. The square roots of the average variance extracted by each construct exceed the correlation between them (Table 3), demonstrating discriminant validity. Thus, our instrument had satisfactory construct validity (Anderson/Gerbing 1988; Fornell/Larcker 1981).

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Table 2: Measurement Model Results for Hypothetical Model Construct Indicator

Standardised Factor Loading ( Ȝ)

SE

Ș1 (Perceived control) After surfing the 3D sites: - I felt I could control the laptop movements - I felt it was easy to rotate the laptop the way I wanted - I felt that I had a lot of control over the content of the laptop’s options (i.e. angles and information)

0.967 0.638 0.830

¯ 0.089 0.067

0.731

¯

0.663

0.083

10.216

0.698

0.104

9.951

0.759 0.764

¯ 0.080

13.816

0.780

0.082

14.342

0.759

0.084

13.136

0.782

¯

0.834

0.058

17.309

0.784

0.062

15.539

0.700

0.062

13.998

0.849

¯

0.854

0.048

20.173

0.797 0.688

0.060 0.049

18.169 14.678

Ș2 (Animated colours) After surfing the 3D sites: - Multicolour in the 3D laptop let me easily visualize what the actual laptop is like - It provided me with accurate visual information about the laptops - Colours brightness of the 3D laptop let me visualize how the real laptop might look Ș3 (3D Authenticity) After surfing the 3D sites: - 3D let me see the laptop as if it was a real one - 3D let me feel like I am dealing with a salesman who is responding to my orders - 3D let me feel like if I am holding a real laptop and rotating it (i.e. virtual affordance) - 3D creates a product experience similar to the one I would have when shopping in a store Ș4 (3D Telepresence) After surfing the 3D sites: - I forgot about my immediate surrounding when I was navigating through 3D sites - While I was on the 3D sites, I sometimes forgot that I was in the middle of an experiment - While I was on the 3D sites, my body was in the room, but my mind was inside the world created by Brunel site - While I was on this site, the world generated by Brunel (3D) was more real or present for me compared to the ‘real world’ Ș7 (Behavioural intention) After surfing the 3D sites: - After seeing the web site, how likely is it that you would buy a laptop from this online store - I would be willing to purchase a laptop through this online store - I intend to buy a laptop from this online store - I would be willing to recommend this online retailer to my friends

tValue

Average Variance Extracted

Composite Reliability

0.68

0.86

0.50

0.74

0.59

0.85

0.61

0.85

0.68

0.89

7.479 10.800

Table 3: Discriminant Validity Construct

Animated Colours

Perceived Control

3D Authenticity

3D Telepresence

Animated colours

0.82

Perceived control

0.513(**)

3D authenticity

0.657(**)

0.480(**)

0.77

3D telepresence

0.313(**)

0.231(**)

0.523(**)

0.78

Behavioural intention

0.273(**)

0.153(**)

0.362(**)

0.171(**)

Behavioural Intention

0.71

0.82

Note: ** p < 0.01. The figures under the diagonal are the Pearson (R) correlations between the variables. Diagonal elements are square roots of average variance extracted.

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Structural Equation Model

The adequacy of the hypotheses was assessed by using comparative fit index (CFI), goodness of fit index (GFI) and root mean square error of approximation (RMSEA). The results of structural equation modelling obtained for the proposed conceptual model revealed a chisquare of 438.746 (df = 113), CFI of .901, GFI of .90 and RMSEA of .08, indicating a good model fit (Byrne 2001; Hair et al. 2006). Figure 2 shows that perceived control and animated colours had significant positive effects on 3D authenticity (H1a: CR = 4.422; H1b: CR= 8.844). Moreover, as hypothesised, perceived control and animated colours had positive effects on 3D telepresence (H2a: CR = 7.419; H2b: CR = 2.077). However, 3D authenticity had a positive impact on behavioural intention (H3a: CR = 7.991), with a non significant impact of 3D telepresence on behavioural intention (H3b: CR = -.645).

5.3.

Test of the Hypotheses

Behavioural intention was predicted by 3D telepresence (standardised path coefficient, ȕ = -.04, p > .05) and 3D authenticity (standardised path coefficient, ȕ = .40, p < .001), and these constructs together explained 24% of the behavioural intention (coefficient of determination, R2 = 0.24). As a result, hypothesis H3a was supported. However, H3b was not supported. 3D authenticity was predicted by perceived control (ȕ = 0.35, p < .001) and animated colours (ȕ = 0.69, p < .001). These constructs explained 60% of the 3D authenticity construct (R2 = 0.60). As a result, hypotheses H1a and H2a were supported. Finally, 3D telepresence was predicted by perceived control (ȕ = 0.15, p < .05) and animated colours (ȕ = 0.36, p < .001). These constructs explained 15% of the 3D telepresence construct (R2 = 0.15). As a result, hypotheses H1b and H2b were supported (see Figure 2). To demonstrate the significantly greater influence of 3D authenticity compared to 3D telepresence on behavioural intention, we alternately constrain and release these paths. Table 4 compares the chi-square and CFI differences between the above two constructs, demonstrating that 3D authenticity has significantly more impact than 3D telepresence on behavioural intention. Table 4: Comparison Between the Effects of 3D Authenticity and 3D Telepresence Constructs on Behavioural Intention when Constraining and Releasing them 2

2

Ȥ when Constraining 3D Authenticity and Releasing 3D Telepresence

CFI when Constraining 3D Authenticity and Releasing 3D Telepresence

Ȥ when Constraining 3D Telepresence and Releasing 3D Authenticity

CFI when Constraining 3D Telepresence and Releasing 3D Authenticity

¨Ȥ

2

¨ CFI

p

675.082

0.871

536.990

0.900

130.092

0.019

Sig.

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Figure 2: Structural Path Coefficients and R for the Effects of Perceived Control, Animated Colours on 3D Authenticity and 3D Telepresence and their Impact on Behavioural Intention

6.

Discussion, Conclusions and Implications

This study aims to investigate the effects of authentic 3D product visualisation and 3D telepresence virtual experiences on consumers’ behavioural intention. Particularly, we define and operationalise VE based on perceived control and animated colours. Moreover, we investigate the effects of perceived control and animated colours on the creation of 3D authenticity and 3D telepresence constructs, which in turn impact consumers’ behavioural intention. The emergence of the notion of 3D authenticity makes it easier for marketers and practitioners, interested in using 3D to simulate real products in the online retail context, to use and apply this notion to measure consumers’ virtual experience. Previous scholarly literature (e.g., Coyle/Thorson 2001; Klein 2003; Li et al. 2002; 2003) has defined and operationalised VE based on the notion of 3D telepresence to explain consumers’ virtual experience in the bricksand-clicks context. The telepresence theory (originally) has been evolved and established in the immersive virtual reality environment, and marketing scholars have adopted this theory and used the same measurement scale that scholars from the IVR field have used to measure consumers’ VE. However, having such a scale within the online retail context may confuse marketers and users because what measures a TV telepresence, for example, might not be applicable to the 3D computer context. Furthermore, the 3D telepresence scale centred on

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products that do not usually exist (Lombard/Ditton 1997). Results support previous research which posits that perceived control and animated colours are the main determinants of 3D telepresence. However, our results reveal that using the 3D telepresence notion and its scale to measure virtual experience did not impact users’ behavioural intention regarding the online retailer. Instead, our 3D authenticity construct refers to the ability to imagine a virtual object as real. Our results support Algharabat/Dennis’ (2010) study which revised previous definitions of telepresence and presence and argued that none of the previous definitions could be used to tap the concept of using virtual environments to reflect the consumer virtual experience. Furthermore, our results demonstrate that 3D authenticity is more relevant than 3D telepresence for marketers concerned with using 3D to enhance behavioural intention within the online retailer context. The negative relationship between 3D telepresence and behavioural intention can be explained by the nature of the 3D telepresence measurement scale. In other words, after surfing the 3D flash, participants believed that neither they forgotten their immediate surrounding, nor they were being transported into another place. Participants believed that the notion of 3D telepresence is related to an unauthentic product, and as a result they would not be enthusiastic to buy an unauthentic product.

6.1.

Theoretical Implications

Our results reveal a significant relationship between 3D authenticity and behavioural intention, compared with a non-significant one between 3D telepresence and behavioural intention, indicating that 3D authenticity has more influence on behavioural intention in comparison to 3D telepresence. We followed Algharabat/Dennis (2010) and narrowed the operationalisations of 3D authenticity antecedents to perceived control and animated colours to reflect a real authentic VE. In line with other online retail researchers who investigated the influence of using 3D product visualisation on VE (Li et al. 2001; 2002; 2003), we find that marketers should focus on specific aspects of interactivity and vividness (rather than on the abstract constructs) when defining 3D virtual experience. For example, when it comes to 3D virtual models, we prefer focusing on the narrowest, most relevant aspects of interactivity (i.e., perceived control). Whereas Heeter (2000, p. 75) describes interactivity as “an overused and under defined concept”, we posit that perceived control represents a useful construct for 3D models in the online retail context. Moreover, in support of previous research (Ariely 2000; Coyle/Thorson 2001) we narrow our conceptualisation of perceived control to consumers’ ability to control the content and form of the 3D flashes. In other words, users’ ability to zoom in or out, rotate and get more information about the product enhances their perceptions of the authenticity of the 3D products. Furthermore, whereas prior research defines vividness according to sensory breadth and depth, we argue that research might benefit from a tighter focus on specific aspects of

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vividness through illustration, such as we have applied here. This result is in accordance with Pimentel/Teixeira’s (1994) study that asserts visual stimuli are the main sensory cues in producing virtual experiences.

6.2.

Managerial Implications

In a highly competitive environment e-retailers need to find ways of attracting and retaining customers (Khakimdjanova/Park 2005; Mummalaneni 2005). A website with an authentic 3D is an important stimulus that would help e-retailers to find success and it often helps them to enhance the e-shopping environment (Khakimdjanova/Park 2005; Park et al. 2008). E-retailers should pay more attention to 3D authenticity antecedents, i.e., perceived control and colour when designing their 3D virtual models. Including real colours and flashes that consumers can control easily will lead to more authentic online VE. Further, retail website designers can contribute to enhancing consumers’ virtual experience by improving users’ perception of the authenticity of the 3D. To achieve this, website developers should consider the importance of the perceived control and animated colours constructs. The empirical results of this research reflect the importance of participants’ ability to easily zoom in or out a laptop, and rotate it (control construct). In addition, participants’ ability to change the laptop colours (animated colours) considered another important aspect to enhance users’ perception of the 3D authenticity. Website developers should take advantage of the technological advancement and keep developing and updating the online retailers’ 3D flashes. Otherwise if all the competitors, on the same industry, use the same 3D flashes then the animation will not attract the consumers’ attention (Fasolo et al. 2006). It should be accepted that developing 3D flashes is not a money-free issue. Nevertheless, many companies have already claimed to have improved their sales as a result of designing and using 3D flashes. For example, J.C. Penny, eBags and Wal-Mart claimed that their online sales have increased 10% to 50% after using rich media such as 3D flashes (Demery 2003). Demery (2006) posits that the numbers of companies who are investing in 3D virtual models is increasing steadily because these companies are seeing the potential of the technology for selling more products. Nantel (2004) asserts that consumers shopping online for clothing are 26% more likely to purchase from the sites that have 3D virtual model than from sites that have not. Fiore (2008) posits that media richness is an important way to differentiate retailers. Wagner (2000) posits that online retailers with 3D product visualisations may reap benefits that extend beyond sales. For example, 3D increases site stickiness: users will spend more time on the online retailer, which leads to more opportunities to learn more about the products, interact with them, build trust and confidence. Finally, according to the Social Issues Research Centre (SIRC, as cited in Herrod 2007) study it is expected that by 2020 virtual commerce (v-commerce) will replace e-commerce and the development of 3D virtual models (such as 3D virtual shopping malls) will be leading the whole industry by 2020.

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Limitations and Further Studies

Although the generalisability of the results is limited by the student sample, and cannot be generalised to all online consumer groups, we argue that students represent the shoppers of tomorrow, computer literate, have few problems using new technology, and are likely consumers of electrical goods (Balabanis/Reynolds 2001), thus this research has prescient value. Second, since this study has focused only on laptops, which we considered to be products that are associated with more search or experience, it is unclear to what extent the results can be generalised and applied to other online products. Further research should consider whether adding auditory cues to the 3D flashes influence behavioural intentions. Further research should consider whether 3D authenticity, experiential and instrumental constructs have direct effects on behavioural intentions. We recommend research efforts to extend the generalisability of our findings to other contexts and samples since we designed and collected the data using a mock up retail website.

Appendix

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Notes [1]

We used H1b and H2b to control our new model. Algharabat/Dennis (2010) have tested theses relationships and found them significant.

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Integrated Retail Channels in Multichannel Retailing: Do Linkages between Retail Channels Impact Customer Loyalty? Hanna Schramm-Klein

Abstract Many retail companies have used multiple retail formats simultaneously for a long time, but the topic has gained importance with the introduction of new channels of distribution such as the internet or mobile devices (e.g., smartphones). The term ‘multichannel retailing’ is therefore simply a new way of describing what is really an ‘old’ phenomenon, but one that has become increasingly relevant and topical. Though multichannel retailing is of great importance in retail practice and has already received considerable attention from researchers, there is still no consensus on whether retailers should integrate or separate their retail channels. Therefore, with this study, we address this topic and show, based on an empirical study, that the integration of consumer-related functions and processes between the channels of multichannel systems has positive effects on customer loyalty.

Keywords Retailing, Consumer Behaviour, Multichannel Retailing, Channels of Distribution, Customer Loyalty

Hanna Schramm-Klein Chair for Marketing, University of Siegen, Germany (Tel: +49 271 740 4380; E-mail: [email protected]).

Received: May 26, 2010 Revised: August 25, 2010 Accepted: September 3, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_5, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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Introduction

Multichannel retailing has grown tremendously during the last decade, mainly because of the introduction of new types of retail channels due to technological innovations such as the internet and mobile shopping channels. In retailing research, the general topic of multichannel retailing has attracted increasing attention, and there are numerous recent studies that analyse consumer behaviour in a multichannel environment (Konus/Verhoef/Neslin 2008; McGoldrick/Collins 2007; Neslin/Shankar 2009; Kyoung-Nan/Jain 2009). While there is a tendency to integrate retail channels in retail practice, e.g., by using the same retail brand between the channels, there is no consensus on whether it is actually favourable for retailers to link the processes between the channels of a multichannel system. One of the main arguments against channel integration brought up by retailers is that channel integration costs retailers money because most customers do not typically use integrated functions; if the majority of customers used these functions, this shift would result in a large financial burden for retailers. However, one can observe that consumers switch channels during their shopping processes and are accustomed to using several channels while completing a purchase (Rangaswamy/van Bruggen 2005). Therefore, channel integration might be a prerequisite to keeping customers within a company during their purchasing processes. Prior studies on multichannel retailing relate mainly to the importance of specific channels in a multichannel system and suggest, for example, migration possibilities (Ansari/Mela/Neslin 2008). Most of the studies relate to multichannel systems, which are characterised by various channels offering interrelated merchandise assortments or an overlapping merchandise mix (Nicholson/Clarke/Blakemore 2002), and most of the studies show that multichannel customers seem to be more profitable in terms of customer profitability (Venkatesan/ Kumar/Ravishanker 2007). The main problem under review in previous research is the issue of constructing a profitable multichannel structure, i.e., which types and what number of retail channels a retailer should provide in the retail channel portfolio. Apart from this issue of a profitable multichannel structure, retailers are confronted with the problem of to what extent and in which areas alternative channels should be cross integrated. Because previous retail research cannot yet provide an answer to this issue, this study addresses this problem. As research has shown, channel coordination is important to increasing customer value (Neslin et al. 2006), but there is still no commonly agreed upon notion concerning which functions of retail channels should be integrated and to what extent linkages should be established between the diverse channels of the multichannel retail portfolio. As this topic is of tremendous importance to retail practice, this study aims to fill this gap in the literature. The following study details the investigation into the impact of multichannel retail systems on consumer behaviour. We use a customer-centric approach and analyse whether the

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integration of distribution channels in retail channel portfolios has a positive effect on customer loyalty.

2.

Conceptual Background and Hypotheses

When retailers use several retail channels as part of their distribution policy, there is a basic choice of either combining or separating the alternative retail channels (Chavez/Leiter/Kiely 2000). If companies follow the strategy of separating alternative channels, interaction between channels is avoided. The processes and functions will not appear to be cross-channel linked from the perspective of the consumer (although this does not exclude the integration of backend processes). The channels may belong to the same owner, but this is often not signalled (e.g., the channels are branded differently). In contrast, an integration strategy instead links channels. Integration aims to build a holistic, total system concept with the expectation that an integrated system will bring the consumer particular benefits (Gulati/Garino 2000). When an integration strategy is implemented, a uniform customer model is applied, and there is close reconciliation between marketing mix instruments. It is important that the processes and functions being integrated are consumer orientated, as customers’ perceptions of the way the system is structured relate to consumer behaviour. Therefore, at issue is not the degree of integration undertaken by a firm, but rather the customer’s perceptions of the extent of integration and how the channels communicate. When shopping formats are used in isolation, the benefits of the individual channels can only be experienced separately. In multichannel systems, the separate services of alternative business and operation types are aggregated. If these services are strictly separate, the benefit to the consumer is the sum of the spectrum of benefits resulting from the extended variety of options for the buying process within a retailer. However, if the consumer is also able to combine certain areas of the individual buying processes, i.e., if they are aware that certain functions have been organised cross-channel by the retailer, then the result is the opportunity to carry out the buying process over a variety of channels. Cross-channel function integration is related to communication between the various channels. Integration may therefore avoid conflict between the channels or within the channels. When irritation and increasing complexity are avoided, this, in turn, is associated with a positive effect on consumer reaction. It is therefore assumed that functional integration has a positive influence on the use of the channels in multichannel systems. As integration is associated with more use, by implication, consumer loyalty to the multichannel system is also improved. When the focus is on the perception of a retail channel portfolio, there are two important dimensions. First, there is the individual evaluation of all the independently functioning channels in a retail channel system; second, there is the evaluation of the integration of the chan-

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nels in the sense of a cross-channel relationship. The perception of retail channels involves consumers assessing the retail performance of each channel. In addition to the straightforward representation of the collected or stored information, cost and benefits or gratification are important to an evaluation of multichannel systems (Mukherjee/Hoyer 2001). Approaches examining the way an assessment is formed are frequently based on exchange theories, cost/benefit models or uses and gratification approaches (Lin 1999; Stafford/Stafford/Schkade 2004). The evaluation processes for assessing alternative retail channels compare the expected total benefit of a retail channel, for example, basic benefits (e.g., provision with goods), personal benefits (e.g., enjoyment, comfort) and social benefits (e.g., appraisal from others) with expected expenditure associated with a retail channel, that is, monetary expenditure (e.g., product price, information, travel, and transport costs) and non-monetary expenditure (e.g., time, physical, and psychological effort). Various dimensions have become apparent and various suggestions have been made regarding the question of which attributes define the important characteristics of a retail channel and are thus used to form an evaluation. In the majority of studies into shopping outlet evaluation (e.g., Fisk 1961; Lindquist 1974; Palmer 2000; OdekerkenSchroder et al. 2001), evaluation is seen as the result of a multi-attribute model and a function of the salient features of a shopping outlet, which the consumer has evaluated and compared (Bloemer/de Ruyter 1998). The attributes that thereby come into consideration correspond with the consumers’ perceptions of the elements of the retail marketing mix instruments used in the individual retail channels (see Pan/Zinkhan 2006 for a meta-analysis). When considering the integrated, overall connection between channels, the primary concern is not individual retail channels and their specific characteristics, but rather, the opportunity presented to the customer to use the different retail channels in combination (in the sense of cross-use in the shopping process). Evaluation of the total retail channel system in the context of multiple retail channel systems has a cross-channel dimension; that is, it involves a crosschannel perspective. The aspects relating to channel interaction are the main focus of interest. These are aspects relating to the consumers’ perceptions of the value-added benefit to an individual from a multichannel retail system when there is cross-channel functioning. In the context of evaluating channel interaction in a multichannel system, the compatibility of the integration, effectiveness of the integration and complementariness of the channels are aspects of consumer perception that are particularly important. Closely related to the evaluation of channel interaction in multichannel systems is the consideration of consumer synergy created by the use of such systems. If consumers are aware that synergy effects can result from using the retail channels in combination, a positive evaluation of the integrated function can be expected. Retail channels may be seen as the package of retail options available for a consumer to use in specific shopping situations. Therefore, the better the channels complement one another and

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integrate with one another, the better their combined functioning. Evaluation of their integrated functioning is therefore related to the actual smoothness of the combined use of the alternative channels or how smooth it is perceived to be by consumers. Consequently, cost/benefit analysis, i.e., how much effort is associated with the use of combined retail channels or how much effort is perceived to be involved by the consumer, is important. Expended effort is therefore another factor affecting the feasibility of using retail channels in combination. The specialisation of a channel, that is, how the consumer benefits from an alternative channel, is not in this case related to the individual processes taking place during shopping, but to the response of alternative retail channels to different consumer need situations and structures. For example, internet shopping is likely to be preferred if consumer convenience is uppermost in a specific consumer scenario; however, if certain stimuli or experiences are being sought, then retail stores may be preferable. Consumers benefit when a firm can offer an expanded benefit spectrum. The combined use of retail channel systems in multichannel systems means the retail channels can be used in a more individual-based way than when the channels are used separately. As such, cross-channel use of multichannel systems effectively offers more uses and new uses of retail channels than one-channel systems (Mathwick/Malhotra/Rigdon 2002; Mathwick/Malhotra/Rigdon 2001). Integration of channels eases cross-channel movement of consumers in a multichannel system and provides further stimulus for such cross-channel movement. It can therefore be assumed that integration is correlated to greater use and results in reinforced repurchase and repeat use behaviour. The positive correlation is not likely to be a direct correlation, but rather an indirect relationship. Therefore, a thorough cognitive understanding of the perception of integration is required (Steenkamp 1990) to apply the benefits of channel integration. Therefore, in this study, consumer attitude towards a multichannel system is included as a mediator variable, mediating between the perceived integration grade and the reaction of the consumer. Consumer perception of channel integration is improved particularly by orientation information, integrated branding and integrated communication. Better consumer perception of channel integration has a positive effect on attitude as increased retailer visibility means the retailer is then recognised in alternative channel environments. This perception eases orientation and enhances trust (Davis/Buchanan-Oliver/Brodie 2000). Consumer awareness that alternative shopping formats are integrated also leads to a positive consumer attitude relationship, as integration enables synergy effects to be created. Related to this concept is the interplay between consumer perceptions of similarities between the alternative channels. If a retailer’s alternative shopping formats are similar, particularly regarding merchandise mix, price structuring, design and communication policy, then swapping between the channels in a multichannel system is comparatively easy for an individual. Integration of channel functions therefore has a positive effect on the consumer’s attitude towards the overall multichannel system. Attitudes are generally defined as overall, subjective, emotional and cognitive judg-

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ments regarding an object that are acquired and modified through learning processes and thus tend to remain stable over time (Dick/Basu 1994; Ajzen/Fishbein 1980). However, in this study, we focus specifically on consumer attitude towards the total retail channel portfolio provided by a retailer. Attitude towards a multichannel system refers to enduring views that are stored in memory, unlike an evaluation, which is more short-term oriented. Summing up these ideas, we propose the following: H 1:

The higher the degree of the perceived integration of the retail channels is, the more positive the consumer attitude towards the multichannel system will be.

Additionally, the perception of the retail channels and the multichannel system as a whole is important in attitude formation. The more positive the evaluation of multichannel retailers’ channels and of their interaction is, the more the system is perceived to be beneficial to the consumer. When an evaluation is positive, the utility and the benefits of a system to the consumer dominate and have a positive effect on attitude towards a retail channel system (Yoo/Donthu/Lee 2000). The greater the benefits are perceived to be, the greater the conviction that a multichannel system is suited to their buying needs and the more pronounced the advantages of the system will be perceived to be (Eastlick/Lotz 1999). A positive attitude is associated with the notion that a multichannel system provides specific benefits to the consumer that cannot be provided by a one-channel system (de Ruyter/Wetzels/Kleijnen 2001). However, consumer attitude towards the multichannel system represents a more holistic view and a more abstract level than the evaluation of the multichannel system. It is affected by a large number of other factors (Steenkamp 1990). In addition to the effect of the evaluation of each of the single channels, the evaluation of the interaction of the channels is particularly relevant. Consumer awareness of the spectrum of alternatives, the spectrum of uses and the resulting consumer synergy has a positive effect on their attitude towards a multichannel system and enhances consumer trust. The effect of the direction of usage perception (which is strongly cognitive), leads to the assumption that evaluation has a positive effect on attitude and trust. A positive evaluation of the multichannel system also means that consumers are confident that the retail company is able to fulfil their specific needs, and consumers can realise benefits in purchase situations. This sense of competence helps reducing perceived risk and provides confidence (Selnes 1998). We therefore propose the following: H 2:

The more positive the evaluation of the multichannel system is, the more positive consumer attitude towards the multichannel system will be.

H 3:

The more positive the evaluation of the multichannel system is, the higher consumer trust towards the multichannel system will be.

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In terms of the relationship between trust and consumer attitude towards the multichannel system, we assume that trust acts as an important antecedent that is of high importance in attitude formation. Trust is conceptualised as the degree of confidence in the exchange partner’s integrity and reliability that is associated with attributes like consistency, honesty, fairness, responsibility or benevolence (Morgan/Hunt 1994; Moorman/Zaltman/Deshpande 1992). Trust reduces customers’ perceived risk associated with purchase decisions. In multichannel systems, each format is characterised by specific risk perceptions. In retail stores, for example, the tangible environment and physical presence of merchandise, sales assistants and other customers contribute to risk reduction. Consumers can inspect products and quality, check availability and build up personal relationships to sales people. These abilities contribute to the building up of consumers’ trust (Ganesan/Hess 1997; Sirdeshmukh/Singh/Sabol 2002). In internet shopping, the lack of this physical presence is the cause for specific risk dimensions. Consumers do not have the ability to check merchandise before buying; risk therefore stems partly from the time lag between buying and actually receiving goods. Other specific risk dimensions refer to cost dimensions in remote ordering (e.g., postage and packing), productrelated risk dimensions (e.g., financial risk, functional risk, and social risk) or risk dimensions related to the retail company (e.g., dealer-related risk and source risk). Online shopping is especially associated with higher perceived risk (Gupta/Su/Walter 2004). The specific risk dimensions in online shopping situations refer to the buyer-seller relationship, the internet as a ‘risky’ medium or legal insecurity in Internet situations (Van den Poel/Leunis 1999; McCorkle 1990; Wood 2001). In addition to trust dimensions related to each single channel, in the context of this study, an important dimension of trust refers to the overall retail channel system and the retail company, respectively. Trust in this understanding is focused on the operation of the retail channel system in a holistic view. It is influenced by single-channelrelated trust, and interdependence between these channels is an important factor of influence (Sirdeshmukh/Singh/Sabol 2002). Trust is associated with a positive assumption related to likeability for the retail company. Trusting consumers are convinced that the company will act in a reliable manner and will refrain from opportunistic behaviour. This trust leads to a positive attitude and a long-term orientation (de Ruyter/Wetzels/Kleijnen 2001). Therefore, we postulate the following: H 4:

There is a positive effect of consumer trust on consumer attitude towards a multichannel system.

One of the important goals in multichannel customer management is to increase customer loyalty (Neslin/Shankar 2009). Loyalty is understood to be a long-term attachment to a firm (Dick/Basu 1994). Theoretical foundations with which to examine loyalty formation are found in cognitive dissonance theory, learning theory and risk theory (Sheth/Parvatiyar 1995). Components or facets of customer loyalty are considered to be repurchase, recommendation

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and supplementary purchases (Mittal/Kumar/Tsiros 1999). Loyalty in terms of the multichannel system is also observed, not only in the repurchase or re-use of a channel, recommendation and supplementary purchasing/use in one single channel but also in the use of other channels in that multichannel system (as a specific dimension of supplementary purchase/use). When other channels are used, it means a customer is using the same retailer for additional shopping or in other need situations. Furthermore, loyalty may be shown by a consumer staying with a company during the shopping process while using a combination of retail channels, for example, to collect information from an internet shopping site that is later used for shopping in stationary outlets of the same retailer (which also eliminates “free riding” behaviour). If there is a positive attitude towards a multichannel system, it may be assumed that consumers are building a long-term positive orientation towards that retail business. Trust is also associated with this long-term orientation in consumers’ relationships to the retail company. It is a means that contributes to cost reductions as it reduces perceived risk. Dick/Basu (1994) emphasise the significance of a positive attitude in loyalty formation and understand it as an antecedent to or a prerequisite for loyalty formation. Trust is also associated with a positive contribution to customer retention (Sirdeshmukh/Singh/Sabol 2002). These assumed relationships can be transferred into loyalty behaviour towards a retailer. A number of empirical studies have demonstrated that there is a correlation between trust and a positive attitude towards and loyalty to that retailer (e.g. Lessig 1973; Steenkamp/Wedel 1991; Macintosh/Lockshin 1997; Sirdeshmukh/Singh/Sabol 2002). We therefore propose the following hypotheses: H 5:

The more positive the attitude towards a multichannel system, the greater the extent of consumer loyalty.

H 6:

The higher the level of trust in a multichannel system, the greater the extent of consumer loyalty.

3.

Research Design

An empirical survey using an online consumer questionnaire was carried out in Germany using a standardised questionnaire. Eight German retailers were selected as questionnaire stimuli. Each had a multichannel system covering retail outlets, traditional catalogues and internet shops. The retailers were selected on the basis of the general visibility of their online shops and the market importance of the retailer (based on a study of the German “Lebensmittel Zeitung”, the leading industry magazine). A variety of sectors (apparel, books, groceries, and cosmetics) were covered, and care was taken to ensure that multichannel systems with a range of differing characteristics were chosen so that a wide spectrum of multichannel systems was represented. 981 consumers filled out the questionnaire. After the elimination of incomplete data records, 786 cases were used in the analysis below. The sample mirrored the demo-

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graphic distribution of online buyers or users of online shops in Germany (GfK-Web*Scope). In the sample, women had a representation of 42.7%. The average age of those interviewed was M = 32.4 (SD = 11.3) years.

4.

Measurement Scales

Integration grade of the channels. Channel integration was conceptualised as a formative construct. There are two different dimensions to the integration of the functions of multichannel system channels. First, there is the integration of goods processes (supply and return processes between the retailer and the customer). This dimension of integration relates to the coordination of physical goods processes between the catalogue, internet shop and stores (2 indicators). As a second dimension, the integration of information and orientation processes was regarded (3 indicators). Evaluation. The evaluation of the channels of the multichannel system and the dimension of the evaluation of the integration of the channels within the multichannel system were isolated and investigated separately. As dimensions of the retail mix, merchandise selection, the price/value relationship, customer advice, information, the design of the shopping environment, general services, the accessibility of the channels, and opening times were regarded (see Pan/Zinkhan 2006), and the perception of these channel characteristics was collected for each single channel separately. The overall perception of the multichannel retailing system was conceptualised as a formative construct based on these perceptions by calculating an index (the weighted average of channel evaluations). Table 1: Operationalisation of the Evaluation of Channel Integration Dimension

Indicator “Integration”

Indicator “Importance”

Goods processes catalogue – outlet

Collection/return to stationary outlets of goods ordered from catalogue outlets

Option to collect/return catalogue goods from/to stationary outlets

Goods processes internet-shop – outlet

Collection/return to stationary outlets of goods ordered over the internet

Option to collect/return internet goods from/to stationary outlets

Product information

Product information about all channels available in all channels

Option of getting product information about all channels in all channels

Price information

Price information about all channels available in all channels

Option of getting price information about all channels in all channels

Orientation information

Orientation information about all channels via visibility of assortment and services

Option of orientation in all channels

Recommendation

Pointers to alternative channels in all channels

Option of finding recommendation about other channels

Integration customer card

Bonus points for customer card holders in all channels

Option to collect customer card bonus points in all channels

Due to the formative nature and the complexity of the construct and the difficulty of collecting direct evaluations of integration processes in a multichannel system, we conceptualised the evaluation of the integration of the channels using the adequacy-importance model. The

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two-component perspective of this model (see Table 1) uses separate data, measuring first, the perception of inter-channel integration of functions within the channels of a multichannel system (“objective impression”, expression value Ai) and second, the evaluation of the importance of the integration of such functions (“importance of attribute”, weighting factor Gi). The evaluation of integration was calculated by the mean of all weighting factors multiplied by their corresponding expression values (Eastlick/Feinberg 1999). Attitude. The attitude towards the multichannel system reflects the individual advantageousness to the consumer of that retail channel system in its entirety. We thus used a reflective measurement approach. It is a global judgment (Parasuraman/Zeithaml/Berry 1988) about a retailer as a whole. This perspective is fundamental to the holistic, intercorrelated view (“gestalt view”). It captures the global assessment of the multichannel system by customers (Keaveney/Hunt 1992). Consumer’s likeability was chosen as an indicator of the affective component of attitude (Dick/Basu 1994; Keller 1998). The appreciation of a multichannel system, i.e., the judgment of whether the system serves to satisfy the consumer’s needs, was used to measure the cognitive component of attitude (Dick/Basu 1994; de Ruyter/Wetzels/Kleijnen 2001). The measurement model shows a high level of internal consistency with regard to the average variance extracted (AVE) of .57 and the composite reliability of .73. Trust. Selnes (1998) considers the one-dimensional global trust-assessment as the most reliable way to measure trust. Following this view, in this analysis, trust was measured as the direct assessment of consumers’ trust relating to each individual channel and the multichannel system as a whole (Sirdeshmukh/Singh/Sabol 2002). Though one might argue that this could imply a formative structure on trust towards the multichannel system, we argue that these trust dimensions reflect consumers’ trust towards the multichannel system as a whole, and thus, we conceptualised trust using the reflective approach. In terms of internal consistency, the measurement model produces acceptable results with an AVE of .58 and a composite reliability of .89. Loyalty. Consumer loyalty to the multichannel system was measured by applying a reflective approach. We collected loyalty towards each individual channel of the multichannel systems. The data collected were based on the intentional behaviour of consumers so that nonintentional or coincidental repeat purchases were excluded from loyalty, and the redundancy of usage behaviour was avoided. The intention to recommend a channel to family and friends was used as the indicator of loyalty. This is generally considered to be an appropriate indicator of loyalty (Andreassen/Lanseng 1997; Chaudhuri 1999). This measurement model for loyalty shows a high level of internal consistency (an AVE of .66 and a composite reliability of .85).

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All reflective indicators (attitude, trust and loyalty) were assessed for discriminant validity using Fornell/Larcker’s (1981) criterion. The square root of the average variance extracted for each reflective construct was higher than the correlation between that construct and any other construct. The discriminant validity was satisfactory with respect to all of the relevant variables. In the case of formative measurement models (channel evaluation, the perception of channel integration, and the evaluation of channel integration), substantial collinearity among indicators would affect the stability of indicator coefficients because they are based on linear equation systems. In our study, none of the indicators revealed multicollinearity problems (none of the variance inflation factors exceeded 2.77). To test for external validity, we assessed nomological validity for all constructs by including additional items in the survey that captured consumers’ satisfaction with the multichannel system and consumers’ purchasing behaviours in the multichannel system. According to the theoretical discussion, the formative constructs should be related positively to these constructs. To test this, we estimated bivariate correlations between the formative constructs and the additional items. All correlations were positive and significant (range from .24** to .45**). Because the constructs behave as expected with respect to some other construct to which they are theoretically related (Churchill 1995), we assume that nomological validity is satisfactory with respect to all the relevant variables.

5.

Results and Implications

The hypotheses that we have postulated between the perceived integration grade, between the channels of the multichannel retailing system, the evaluation of the channels and of the channel integration, attitude, trust and consumer loyalty were analysed with structural equation modelling (see Figure 1) using AMOS. The global fit measures show a good fit of the model: all exceed the recommended minimum values (Bagozzi/Yi 1988). The path coefficients correspond to the formulated hypotheses. The standardised path coefficients are shown in Figure 1. We can show that if consumers perceive that channels are integrated, there is a positive effect on their attitude towards the multichannel retailing system as a whole (H 1), with the integration of goods processes having a slightly higher impact than the integration of information processes. We thus can confirm hypothesis 1. Even though channel integration is of significant importance, the general evaluation of the multichannel system is of primary importance for attitude formation (H2) and for trust formation (H3). While the evaluation of channel integration is of high relevance in terms of its influence on consumers’ attitudes towards the multichannel system (H2), there is no impact on trust. We therefore can confirm hypothesis 2, but only find partial support for hypothesis 3. Trust shows significantly positive impact on attitude. We thus can confirm hypothesis 4. Both trust and attitude show a high positive influence

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on consumer loyalty towards the multichannel retailing system. Therefore, hypothesis 5 and hypothesis 6 can be confirmed. Figure 1: Path Analysis Integration Goods Processes

.223* Trust

Integration Information

.192*

.265** .470**

.421**

Loyalty .658**

Evaluation of Channels

.540** .055 n.s. .353*

SMC: .58

Attitude

Evaluation of Channel Integration

GFI: .943 NFI: .956 CFI: .967 AGFI: .912 RMSEA: .060

** p d .01 * p d .05 n.s. not significant

In sum, only the relationship between the evaluation of channel integration and trust does not show a significant effect. All other relationships are significant. The explanatory power of the model is comparatively high, represented by the share of variance (.58) explained for loyalty by the model (which is shown as SMC in Figure 1), especially when taking into account that the model only formulates selected relationships and that attitude, trust and loyalty are influenced by a large number of other factors not considered here.

6.

Summary and Implications

The results of our study thus show that linkages between channels are highly relevant to a multichannel system. This result indicates that integrated retail channel systems may be superior to separate systems as channel integration shows a positive impact on customer loyalty. Additionally, consumers’ evaluations of the retail channel system are of high importance. In this context, the impact of the evaluation of channels is greater (and the correlation greater) than the impact from the evaluation of the coordination and the perceived degree of integration of the channels. The analysis shows that the impact of channel integration is triggered mostly by affecting consumer attitudes because consumers’ evaluations of channel integration do not significantly affect trust towards the distribution channel system. This indicates the high relevance of cognitive processes in the context of integration effects. Channel integration eases orientation and intensifies potential existing cross-channel synergies, which will also lead to a more differentiated use of the retailer’s whole multichannel system according to cus-

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tomers’ preferences and needs in purchase processes. Therefore, in contrast to brand or product-centric approaches, a retailer should increase the perception and evaluation of channel integration by using the proposed customer-centric approach providing, for example, orientation information, integrated branding and integrated communication (Reinartz/Krafft/Hoyer 2004). Furthermore, our results indicate that a well-integrated multichannel strategy could also enable customer migration into more efficient retail channels that will increase long-term customer profitability (Ansari/Mela/Neslin 2008; Thomas/Sullivan 2005; Wolk/Ebling 2010). The results also indicate that the attributes relating to the individual channels have the most important effect on attitude and trust. Reasons for this could be that use of multichannel systems has been characterised so far by the channels being used separately by the customer, not to their full capacity and not to the full extent of the potential combination capacity. This results from the fact that, although the internet is pivotal to all multichannel systems in this study, it is still a comparatively ‘new’ marketing channel. Not only consumers but also retailers have less experience with the internet (in comparison to the experience they have with more traditional retail channels), and the full potential of (customer-orientated) system integration has not been reached. The number of integrated channel systems is therefore limited; they are relatively new and consumer use is still correspondingly low. This information shows a need for retail practice action in a variety of areas, e.g., in the quantity of available retail channels from a company and in the quality of their integration regarding optimisation of transactions for customers. It would therefore be advisable not only to intensify the combination options of channels but also to optimise the ’smoothness’ of crosschannel activities for the customer. In terms of communication policy, it would thus be advisable to emphasise the potential of the use spectrum available to the consumer in a multichannel system concept as a use and service package rather than to concentrate on the benefit of separate channels’ usage. The implications for further research are closely related to the limitations of our study. We only analysed multichannel systems, combining their internet shops with retail stores and traditional catalogue channels. The findings therefore relate to the specific importance of the observed channels, and in particular to the specific importance of internet channels within the context of a combined application of alternative channels in retail. This study also only investigated multichannel systems that, as a minimum requirement, had begun to implement integration and did not include strictly separated systems.

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Appendix Table A1: Measurement Scales Constructs

Indicator

Integration goods processes

- Collection/return of goods from/to stationary outlets of goods ordered from a catalogue - Collection/return of goods from/to stationary outlets of goods ordered over the Internet

Integration information processes

- Product information about all channels in all channels - Price information about all channels in all channels - Orientation to all channels through visibility/acquaintance with assortment and services

Evaluation of channels

- Evaluation of outlets - Evaluation of catalogues - Evaluation of Internet shops

Attitude

- Likeability of retailer - Appreciation

Loyalty

- Recommendation intention (outlets/catalogues/Internet shops)

Trust

- Trust in retail format (retail outlets/catalogues/Internet shops) - Trust in company

Table A2: Results of Confirmatory Factor Analysis Constructs with Indicators

Standardised Factor Loadings

SMC 1 (min. 0.4)

Catalogue goods

1.00

1.00

Internet goods

0.83

0.69

Product information

0.74

0.55

Price information

0.75

0.56

Orientation information

0.67

0.44

Evaluation of outlets

0.59

0.35

Evaluation of catalogues

0.79

0.62

Evaluation of internet

0.82

0.67

Sympathy

0.90

0.80

Appreciation

0.67

0.42

Trust in outlets

0.89

0.79

Trust in catalog

0.82

0.67

Trust in internet shop

0.84

0.71

Trust in company

0.71

0.50

Recommendation outlet

0.92

0.84

Recommendation catalogue

0.74

0.55

Recommendation internet

0.77

0.59

Integration goods processes

Integration info. processes

Evaluation of channels

Attitude

Trust

Loyalty

1

Composite Reliability (min. 0.5)1

Average Variance Explained (min. 0.5)1

0.92

0.85

0.76

0.52

0.77

0.53

0.73

0.57

0.89

0.58

0.84

0.64

Note: Bagozzi/Yi 1988; Bagozzi/Baumgartner 1994; Boomsma/Hoogland 2001.

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The Retail Industry in Spain Maria Puelles, José Antonio Puelles and Susana Romero

Abstract In this report we present an overview of the current situation of the retail sector in Spain. It begins with a review of the most relevant features that shape the commercial activity, as the influence of density and population growth, autonomous communities, policy issues and tourism. Afterwards, the general structure of the retail industry (food and nonfood separately) is characterised, with a detailed description of the key actors. Particular attention has been paid to highlight the most significant data on its activities and strategies, pointing out the consequences, for both sectors, of the important growth of store brands. Finally, we present the main conclusions on the topic, as well as a brief look to the future prospects of the retail sector in Spain.

Keywords Spain, Retail Market, Internationalisation, Department Stores, Hypermarkets, Fashion Retailing

Maria Puelles (corresponding author) Department of Marketing and Market Research, Universidad Complutense de Madrid (E-mail: [email protected]). José Antonio Puelles Department of Marketing and Market Research at Universidad Complutense de Madrid. Susana Romero Department of Economics at Universidad Rey Juan Carlos of Madrid.

Received: March 9, 2010 Revised: July 27, 2010 Accepted: August 16, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_6, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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1.

European Retail Research Vol. 24, Issue II, pp. 129-166

Overview on Spain

Spain’s particular geography, with numerous mountain ranges and vast plateaus and being surrounded by sea along most of its perimeter, has conditioned to a very large extent its geographical, industrial and commercial growth. In addition to its geography, Spain’s political and regional structure is perhaps the most relevant and prominent feature in explaining the particularities in Spain in terms of development. Figure 1: Population Growth in Spain (1594-2009, in Thousand)

Source: INE (2009a).

Population growth in Spain was more or less sustained and remained constant until 2006 when it began to level off (see Figure 1). However, the average population density of 91.4 people per square kilometer in 2008 is lower than that of most other western European countries and is unevenly distributed across Spain, as can be seen in Table 2. Nonetheless, more than four million new inhabitants from abroad immigrated in the last ten years, which also boosted consumption and economic growth in general. So growth of the population was primarily due to the inclusion of adult foreigners. Another feature of the population in recent years is the upward trend in one-person households. These features or trends in the Spanish population pyramid present considerable challenges to the retail industry since immigration has recently affected Spain far more than other EU countries. The inclusion of foreigners gives rise to a new segment of consumers with specific requirements and a strong tendency to consume, thereby offsetting their lower level of earnings.

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Figure 2: Population Density in Spain (2009)

Barcelone

Madrid

Balearic Islands

Canary Islands

Source: Alarcos Research Group (2009).

Throughout history, Spain’s population has remained concentrated primarily in two areas: - The coastal areas and nearby valleys are the most densely populated and home to the main towns and metropolitan areas (except for Madrid), e.g. Barcelona, whose area of influence covers the whole of the coast of Catalonia, Valencia, Alicante-Elche-Murcia-Cartagena, Seville-Cádiz-Málaga-Granada, Bilbao-Guipúzcoa-Santander, Asturias, La Coruña-Vigo, Palma de Mallorca, etc. - Madrid is a densely populated area and the capital is the largest city in Spain. It is the third largest municipality in the European Union (surpassed only by London and Berlin) and it has the third largest metropolitan area in the European Union (outdone only by Paris and London), which includes towns such as Móstoles, Alcalá de Henares, Fuenlabrada, Alcorcón, Leganés and Getafe, all of which have a population of over 100,000. Madrid is so densely populated because it is the capital of the country and its influence reaches as far as the provinces of Toledo and Guadalajara, making it a vast metropolitan area. However, the whole inland area is suffering from problems relating to depopulation, noteworthy exceptions being Zaragoza, Cordoba, and Valladolid. Table 1 shows the most densely populated cities in Spain.

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Table 1: Most Populated Cities in Spain as a Percentage of the Total Population (2009) Madrid

6,386,932

% of the Total Population 13.7

Barcelona

5,487,935

11.7

Valencia

2,575,362

5.5

Alicante

1,917,012

4.1

Seville

1,900,224

4.1

Malaga

1,593,068

3.4

Murcia

1,446,520

3.1

Cadiz

1,230,594

2.6

Vizcaya

1,152,658

2.5

La Coruña

1,145,488

2.5

Most populated cities, total

24,835,793

53.1

Spain, total

46,745,807

100

City

Population

Source: INE (2009a).

45% of Spain’s population lives in the seven most populated provinces, while only 8% of the total population lives in the fifteen less populated areas (excluding Ceuta and Melilla). None of the 22 less-populated provinces are on the coast. However, with the exception of Madrid, Seville and Zaragoza, all the 15 most populated provinces have access to the sea.

2.

Socio-economic Indicators of the Industry and the Retail Sector

Spain has a service-based economy with the service industry accounting for approximately 67% of GDP, followed by industry with 29%. Agriculture represents just 4% despite Spain being renowned in the EU as one of the most competitive agricultural producers. Within the service industry, the tourist sector is the cornerstone of the Spanish economy. In recent years, the number of visitors has grown by 5% each year and according to data from the Ministry of Trade and Tourism this growth is expected to be sustained for the next ten years, reaching 75 million tourists in 2020. After France, Spain receives the largest number of tourist in the world and is surpassed only by the USA with respect to revenue generated from this industry. Table 2 shows that four autonomous communities (Andalusia, Catalonia, the Community of Valencia, and Castilla y León) receive more than 50% of these visitors – Andalusia being the community that receives the most, (17%), followed by Catalonia (13.5%), the Community of Valencia (10.5%), and Castilla y León (9.8%). When compared to 2008 this market share basically remained stable, with no changes in the ranking with respect to 2009.

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Table 2: Market Share of Visits Received per Autonomous Community (2009) Ranking

Autonomous Community

Level of Concentration

Ranking

Autonomous Community

Level of Concentration

1

Andalusia

17.0%

10

Extremadura

2.9%

2

Catalonia

13.5%

11

Asturias

2.6%

3

Community of Valencia

10.5%

12

Murcia

2.2%

4

Castilla y León

9.8%

13

Basque Country

2.1%

5

Castilla-La Mancha

7.0%

14

Cantabria

1.9%

6

Madrid

6.3%

15

Navarre

1.8%

7

Galicia

5.0%

16

Balearic Islands

1.6%

8

Aragon

4.2%

17

La Rioja

0.9%

9

Canary Island

3.1%

18

Ceuta and Melilla

0.1%

Source: IET (2010).

Spain receives the most tourists from the UK, Germany and France. In Figure 3 we can see that for the loyalty, measured as the number of times a tourist has been before, it is noteworthy that 85% of them had already visited Spain. Also, 45% of tourists said they had visited Spain previously more than ten occasions. Figure 3: Tourists’ Loyalty to Spain (Number of Previous Visits by Country of Origin)

Source: IET (2010).

Key Indicators and Developments in the Retail Sector Although tourism is spread throughout Spain, the biggest influx is concentrated in certain areas such as Catalonia, the Balearic Islands, the Canary Islands, Andalusia and the Community of Valencia. From the above population distribution map, it can be observed (see Table 3)

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that the most densely populated areas coincide to a great extent with the areas that attract most tourism, which also gives rise to a significant increase in the development of retail activity associated with this demand. Table 3: Retail Density per Autonomous Community; Number of Retail Outlets per 1,000 Inhabitants Autonomous Community

2000

2006

2007

2008

Ceuta and Melilla

19.37

18.08

17.58

17.18

Galicia

14.99

15.39

15.56

15.35

Balearic Islands

18.51

16.66

16.08

15.18

Canary Islands

16.36

15.34

15.43

15.10

Extremadura

12.81

15.08

15.22

15.01

Andalusia

14.87

15.07

15.13

14.81

Basque Country

14.55

14.01

13.84

14.37

La Rioja

17.14

14.66

14.68

14.37

Community of Valencia

15.99

14.69

14.68

14.23

Castilla y León

15.11

14.27

14.24

13.98

Spain, total

15.24

14.31

14.31

13.98

Asturias

15.85

14.36

14.24

13.91

Catalonia

17.29

14.14

14.16

13.77

Castilla-La Mancha

15.18

14.07

13.99

13.58

Cantabria

15.03

13.81

13.78

13.44

Murcia

14.69

13.40

13.61

13.37

Navarre

13.19

13.41

13.39

12.90

Aragon

13.78

13.05

12.96

12.63

Madrid

13.16

12.57

12.50

12.06

Source: ICE (2008).

The industry breakdown established by the Spanish National Institute of Statistics (INE) defines retail in Spain as a part of the service industry. According to the CNAE-2009 classification [1], which substitutes that of 1993, it is allocated to Section G which includes divisions 45, 46 and 47. In 2007, the retail industry accounted for 15.43% of GAV (Gross Added Value) at basic prices for the Services sector and 10.39% of the total GAV for Spain, ranking it the second most important industry in the Spanish economy after tourism. The revenue from the marketservice sector was down 3.2% in 2008 with respect to 2007. Employment in the retail industry also fell by 2.9% in 2008 compared with an increase of 2.1% in 2007. According to data from the Labour Force Survey (EPA), active employees in the industry accounted for 16% of the total Spanish economy in 2008. With respect to household consumption, the annual average expenditure was EUR 32,001 in 2007. Average spending on household consumption was down 0.1% in 2008 in comparison to 2007, totalling EUR 31,953. If the effect of inflation is eliminated, the variation stands at

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-4.1% (INE 2009b). Table 4 shows the evolution and the changes of annual spending per household. Table 4: Evolution and Distribution of Average Household Spending (EUR) Total 1. Food and non-alcoholic beveages 2. Alcoholic beverages and tobacco

1998

2000

2004

2008

17,730 3,321

19,862 3,536

23,340 4,002

31,953 4,647

455

474

523

617

3. Clothes and footwear

1,274

1,484

1,558

1,958

4. Housing, water, electricity and fuel

5,289

6,003

7,443

8,707

830

978

1,051

1,662

5. Furniture, equipment and other housing expenses 6. Health 7. Transport 8. Communication 9. Leisure, entertainment and culture 10. Education 11. Hotels, bars and restaurants 12. Other goods and services

415

422

519

1,024

2,082

2,269

2,442

4,362

335

388

608

971

1,031

1,190

1,431

2,201

236

244

248

295

1,568

1,752

2,073

3,069

889

1,116

1,436

2,440

Source: INE (2009b).

An analysis of the data for this ten-year period show that the largest increase in spending related to housing, water, electricity and fuel, transport, leisure and hotels, and bars and restaurants while the lowest related to alcoholic beverages, tobacco and education. However, this trend has changed in the current crisis as it has in other countries. In general, there is a downward trend in all items but one of the most relevant figures for Spanish retail is the reduction in spending on food and drink outside the home, which fell by 6.6% in one single year (from July 2008 until July 2009) according to the MARM Dossier on Food Consumption in Spain (MARM 2009). With respect to the immediate future, Fundación de Cajas de Ahorros (FUNCAS 2010) has forecasted the trends in household consumption for 2011 (see Table 5) which indicate that it will continue to fall across the board. Table 5: Economic Forecasts for Spain, 2010-2011 DATA OBSERVED 1996-2007 2008 (average) Final household consumption

3.8

-0.6

PROJECTION

CHANGES in FORECAST

2009

2010

2011

2010

2011

-0.5

0.7

0.6

0.6

-0.6

Source: FUNCAS (2010).

Moreover, the smaller size of one-person households implies a fall in demand in terms of quantity of products consumed but also reduces the importance played by price in purchase decisions, which comes second to factors such as comfort and convenience. Last but not least, the ageing population will imply a reduction in the quantity of food consumed but also to the purchasing of products with greater added value and a stronger tendency to purchase them at

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local stores. This market will also demand specific products based on its needs such as personal, leisure, tourist and transport products, home delivery services and all manner of similar facilities (information, till assistance, proper and legible labelling, etc.). With regard to purchasing habits, Spanish consumers use multiple formats, making their choices based on the type of product sought. In terms of fresh food, they still lean towards traditional stores but prefer larger distributors for packaged items. However, they divide their trips between various formats (hypermarkets, supermarkets, discount stores, etc.). When choosing products, quality is the most highly-valued attribute, followed by price, which has become more important in the latter stage of the crisis and has fostered the development of store brands as part of the choice on offer at stores [2] In addition to these stores, the retail range includes market stalls, wholesale purchasing, convenience stores, vending services and the internet. Yánez (2009) summarises some of the most significant trends observed in the Spanish fast moving consumer goods (FMCG) market that can be used as a reference for decision making in this area, as follows: - More products will be targeted at smaller segments. - Consumers will be aware that the future is uncertain and, consequently, will try to save money, looking for special offers, and will be less interested in buying items to stand out from the crowd and more interested in their own well-being. - The changes in the socio-cultural structure will also be important for marketing. The age group over 65 will continue to grow as a percentage of the population, will give rise to a revolution in the tourist, real estate, healthcare and leisure sectors and even the education sector; the markets will to a large extent have to adapt to the tendencies of these older customers. - Housework will be shared much more and the male will play a more active role; the idea of being at home, even while working, will gain more currency in the face of an uncertain future and job instability. - At the same time, since Spain is an established consumer society, concerns for health, security, leisure and the personal search for the meaning of existence will continue to grow. Therefore, great expectations will be placed on products for personal use, with priority given to information services and protective products, and new needs will also arise in the field of amusement and impulse purchases. - Customers will have even less time to shop and, therefore, speed and convenience will be their priority. Their purchasing preferences will tend towards simplified offers at economical prices excluding coupons and discounts, all the while demanding fast, efficient and personalised service and punctual delivery.

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- In view of the large variety of ranges, consumers will want expert ‘agents’ to give them advice and information so that they are able to make quick purchasing decisions. - Companies should help their customers to manage pressure from an increasingly complex world through regular home deliveries of basic products: detergent, food, paper, etc. - Increased demand for home delivery emerges, particularly at weekends. - Increase in family budgets for products are aimed at guaranteeing family stability, such as employment insurance, insurance for legal costs and for care of the elderly. As noted in the introduction, one of the main impacts of regional political development is the adaptation of general Spanish legislation to each community. Retail density, defined as the number of retail establishments per 1,000 inhabitants, makes it possible to observe the differences between the retail models of the various autonomous communities. Table 3 reflects the retail density per autonomous community in 2008, in descending order. It can also be observed that in 2008 there were 13.98 retail premises per 1,000 inhabitants in Spain. The autonomous communities with the highest retail density were Ceuta and Melilla (17.18), Galicia (15.35) and the Balearic Islands (15.18) while Madrid (12.06), Aragon (12.63) and Navarre (12.90) have the lowest density. As already noted in most of the autonomous communities, there is a downward trend in retail density throughout Spain due to the sharp increase in the population and a decrease in the growth or retail outlets, as can be seen in Table 7. The trends in 2008 and 2009 and the forecasts for 2010 follow the same line, with a significant decrease in the number of stores (mainly traditional) that have been forced to close as a result of the recent economic crisis. Table 6: Retail Density Indicators in Spain (1992-2007) Number of stores Sales (in million EUR) Employees Inhabitants (in million)

2007

2006

2004

2002

2000

1992

646,804

636,451

639,714

628,065

607,848

582,885

215,041

206,834

183,464

161,064

141,367

88,933

1,879,890

1,830,116

1,737,941

1,621,438

1,507,862

1,361,340

45.201

44.709

43.198

41.838

40.500

39.138

114,390

113,017

105,564

99,334

93,753

65,328

Sales per inhabitant (EUR)

4,757

4,626

4,247

3,850

3,491

2,272

Inhabitants per store

69.88

70.25

67.52

66.61

66.63

67.15

2.91

2.88

2.71

2.58

2.48

2.34

Productivity (sales per employee)

Size (employees per store)

Source: ICE (2008).

The basic legislation governing opening hours in Spain is Law 1/2004, of December 21, on shop opening hours. This Law establishes the principle of freedom for retailers to decide the days and times of their commercial activity within the law and the legislation issued by the autonomous communities. Due to the unique nature of the autonomous communities in Spain, it is important to note that the law allows them to set the weekly limit of opening and closing

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hours for stores for the total number of working days. The autonomous communities may also establish the number of Sundays and public holidays authorised for trading and the maximum opening hours on the dates permitted (subject to basic provisions of the Law). Table 7 summarises the number of store opening days per autonomous community in 2010. Table 7: Number of Store Opening Days per Autonomous Community Autonomous Community

Number of Public Holidays and Sundays on which Retailers are Allowed to Open

Andalusia

8

Aragon

8

Balearic Islands

8

Canary Islands

9

Cantabria

8

Castilla la Mancha

8

Castilla y León

8

Catalonia

8

Community of Valencia

8

Extremadura

8

Galicia

8

Navarre

8

Madrid

22

Murcia

10

Asturias

8

La Rioja

8

Ceuta

12

Melilla

8

Source: MITYC (2010).

Logically, these differences affect trading capacity and retail trends in Spain. By way of example, the Autonomous Community of Madrid, which since 2009 has increased the number of opening days, is becoming a highly attractive hub for both Spanish and tourist trade since it is making itself accessible in terms of shop opening days and hours. In any case, the public is generally satisfied (Institut Cerdá 2005) with these opening hours and considers them sufficient (86.8%) as do retailers (75.6%). Purchases are spread throughout the week but are more common on Thursdays, Fridays and Saturdays. In short, although the overall trends in the retail and consumer sector can be observed in every Spanish autonomous community, each one is extremely influenced by the features of their government. Considerable differences can be found in their policies, which are reflected in the organisational structure of their retail industry. This data is particularly important for companies that wish to set up or open new stores and for making decisions about the location and size of points of sale and employee management.

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Structure of the Retail Trade

The Spanish retail industry is characterised by a large number of retailers and traditional shops. Retail is one of the most dynamic activities in the Spanish economy, evidenced by the over 620,000 retail outlets. This retail scenario has changed considerably in recent years in accordance with the new requirements and changes already mentioned in terms of population and demand. The adjustments have focused to a large extent on the change in the traditional sales system with a move towards self-service, specialisation and new sales approaches (stores and retail formats) that can satisfy all manner of consumers and purchasing methods. For comparison purposes with other EU countries, the main indicators for the retail sector are included in Table 8. It can be observed that the retail sector in Spain has an extremely high value in all respects, rivalling other more advanced European countries such as Germany and France. Table 8: Main Indicators of the Retail Sector in Different European Countries (2006) Average Cost per Employee (Thousands of EUR)

Cost of Employees (Millions of EUR)

Productivity/ Employee (Thousands of EUR / Employee)

328,226

23.5

6,747

27.9

298,742

27.3

5,759

34.9

789

360,147

8.3

2,062

10.4

65,855

9,106

1,776,317

28.9

47,037

37.1

76,133

4,763

2,768,348

20.7

50,508

27.5

52,110

8,353

1,860

518,699

16.3

4,070

16.1

Hungary

21,436

2,384

538

331,650

6.4

1,710

7.2

Italy

286,262

43,675

6,061

1,846,070

24.5

22,873

23.7

Country

Turnover (Millions of EUR)

Value Added Tax (Millions of EUR)

Gross Investment (Millions of EUR)

Number of Employees (Units)

Austria

46,374

9,159

1,016

Belgium

66,185

10,428

2,316

Czech Rep.

26,488

3,753

France

381,994

Germany

380,171

Greece

Luxembourg

7,036

943

78

20,215

30.9

566

46.7

Netherlands

81,675

17,236

1,980

750,935

15.7

10,295

23.0

Poland

62,922

9,362

1,764

1,242,234

5.2

3,711

7.5

Portugal

38,136

5,900

1,785

438,380

9.4

3,929

13.5

Romania

18,221

2,041

1,506

501,198

2.4

1,125

4.1

Slovakia

7,086

1,036

382

86,008

6.3

534

12.0

Slovenia

6,712

1,108

525

52,860

14.8

721

21.0

Spain

206,834

42,362

6,744

1,777,463

18.9

23,916

23.8

Sweden United Kingdom European Union (total)

53,467

9,721

1,033

282,066

31.3

7,484

34.5

409,100

87,116

14,764

2,952,639

19.1

52,858

29.5

272,271,831

418,397

60,962

17,472,300

18.7

259,716

24.0

Source: ICE (2008).

In the last few months of 2008 and in 2009, the Spanish economy and the economies of other countries had to contend with a dramatically adverse economic climate, sparking a reduction in household spending on consumption. However, this situation acted as a driver for retail

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groups who had to find strategies to boost sales. Some of these strategies included cost cutting, strict control of the supply chain and prices, renegotiation with suppliers, an increased range of store brands, the tendency to reduce the sales area of stores, the closure of less profitable stores and an increase in the commitment to and promotion of internet sales. In any case, in an industry whose turnover is close to EUR 250,000 million, billings of retailers in Spain fell by 12% in 2009. This represents a fall in revenue of almost EUR 30,000 million according to data from the Spanish Retailing Federation (February 2010). In 2010, 40,000 local outlets were closed in the Spanish market, representing 6% of the approximately 650,000 existing retail operators and a loss of 5% of jobs in the industry, affecting 90,000 of the 1.8 million retail employees. According to the same association, the food industry (both in terms of manufactured and perishable goods) recorded the best performance with dips of only 2% – 6% while the retail furniture and decoration sector was the most affected with a downturn of 35% as a result of its close ties with the construction industry. Textile and footwear retail fell slightly less (5% – 15%) and the textile industry offset a considerable loss through sales although it also lost between 10% to 20% on personal items and 15% to 25% in the case of homeware. However, we also noted that certain Spanish players developed commercial strategies in 2009 that put them in very strong positions worldwide. For example, the Mercadona chain moved up eight places to 38 in the retail industry world ranking (based on retail sales for the previous year), three places above El Corte Inglés, which was down one place to 41 according to the 2010 edition of Deloitte Global Powers of Retailing 2008. Inditex, the most renowned Spanish company in international retail circles, jumped from 65 in the prior year to 54, ahead of Gap (55) and H&M (60). The Eroski Group also moved up from 90 to 76. We will now review the most relevant events and data explaining the current situation and structure of retail in Spain. Certain fundamental events have given rise to significant changes in demand and, consequently, the structure of retail in Spain in the last twenty years. One such event is Spain’s full membership of the EU, and another, the change in the type and demand of Spanish households, which is also influenced by the substantial increase in the foreign population resulting from immigration. Spain’s accession to the EU in 1986 opened it up to the European markets and brought more global lifestyles and behaviour to the Spanish. The expansion of the major retail groups, mainly from France and Germany, was boosted from that moment onwards, together with their particular retail formats (see Table 9). The Carrefour and Auchan groups set up hypermarkets throughout Spain, starting with the most populated autonomous communities and cities and the most important tourist hubs. The roll-out of these large groups sped up the transition from a retail structure based primarily on traditional trade to a new structure based on self-service.

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Table 9: Origin and Year of Arrival of the Main Distributors in Spain Name

Year of Arrival

Country of Origin

Pryca shopping centres

1973

France

Continente shopping centres

1976

France

Makro

1976

Netherlands

Alcampo

1979

France

Dia (Group)

1983

France

Unigro Group

1988

Netherlands

Itm Ibérica

1988

France

Comptoirs Modernes

1989

France

Leclerc

1990

France

Dairy Farm

1991

Hong Kong

Booker Cemasce C&C

1992

United Kingdom

Punto Cash

1993

France

Lidl Autoservicios Descuento

1994

Germany

Penny Market

1995

Germany

Tengelmann

1995

Germany

Royal Ahold

1996

Netherlands

Leader Price

1997

France

Source: Cuesta (2006).

At present, retail distribution in Spain is characterised by the functioning of two systems side by side (Cuesta 2006). On the one hand, there is the system based on traditional retail, made up of numerous small stores with old-fashioned and inefficient retail equipment, acting independently, with a low level of training, a family-based employee structure and financial difficulties, etc. Consequently, it is difficult for this system to survive which results in the progressive closure of this type of stores and a drastic decline of its market share. On the other hand, there is the system based on the introduction of new retail formats using the self-service system formed by large retail organisations with great purchasing power. These organisations are increasingly concentrated and are constantly innovating in sales and management techniques and, in general, they are ready to adapt to changes in the conditions of their environment. Such an unbalanced dual system within retail causes constant cannibalisation of traditional retail by the network of large organisations based on self-service sales. Table 10 details the purchases made by Spanish consumers by store type. Noteworthy is the progress made by supermarkets in recent years (46.1% of the market share in 2008). They have steadily increased their market share to the detriment chiefly of specialised retail, which now only has a market share of 28%.

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Table 10: Market Share for Food and Beverage Retailing Food and Beverage Retailing

Market share

Specialised stores

28.2

Supermarkets

46.1

Hypermarkets

16.8

Cooperative stores

0.4

Street markets

1.3

Door-to-door selling

0.8

Self consumption

2.6

Other commercial types

3.9

Source: ICE (2008).

Consequently, the companies leading the Spanish retail ranking basically operate hypermarkets and supermarkets (see Figure 4). Figure 4: Evolution of the Retail Structure in Spain (from 1994 to 2008)

Source: Adapted from ICE (2008).

Therefore, the retail industry in Spain has an oligopolistic structure with a very small number of large groups dominating the most significant formats (hypermarket, supermarket and discount stores), where there is intense competition between the same and different formats. After making these general observations, we consider that it is important to analyse the general structure of the industry at this point in terms of the most notable FMCGs in order to better explain their particular characteristics.

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143

Players and Trends in Different Retail Sectors

The main retailers present in Spain focus their development on the food industry (see Table 11) except for El Corte Inglés, a general retailer, and Inditex (which includes the Zara brand) which is part of the fashion industry. Therefore, we will examine these large groups separately. A major development is also taking place among large nonfood specialists, which often are associated to the main food groups – such is the case of the Bricor brand that focuses on DIY and gardening and is a member of the El Corte Inglés Group, and the Auchan group brands (Mouliez family): Leroy Merlin, Aki, Décathlon, Jardiland and the recently eliminated brand Boulanger (replaced by Worten). Table 11: Main Retail Industry Companies in Spain (2008) Company

Sales (Millions of EUR)

El Corte Inglés

17,362

Mercadona

15,379

Inditex

10,407

Centros Comerciales Carrefour

9,581

Eroski

9,013

DIA

4,232

Alcampo (Auchan Group)

3,901

Hipercor

3,088

Lidl Supermercados

2,000

Dinosol Supermercados

1,690

Makro Autoservicio Mayorista

1,390

Source: Esade sectorial flash (2010).

4.1.

El Corte Inglés as Dominant Retailer in Spain

El Corte Inglés, which started out as a department store, is the only operator of this format in Spain (see Table 12). It now offers various store types as detailed in the following Table 13. The table shows that in 2008 its profitability decreased by 3.5% as a knock-on effect of the crisis but that the decrease was unevenly spread across the various formats and business areas. The company’s strategic development is focused almost exclusively in Spain, although it opened its first store in Portugal in 2001. According to the company’s own information, the El Corte Inglés Group has implemented a diversification strategy away from their first department store format, together with a specialisation policy which has resulted in the creation of several sales formats. Each one of the chains responds to the demands of a certain market segment: - El Corte Inglés is the Group’s main business line and the format with the greatest reach since it follows the department store model which includes all types of products and services, from fashion and accessories to sports and cultural products and consumer electron-

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ics. With respect to department stores, ‘El Corte Inglés’ has always been a point of reference for consumers in Spain and a must-see tourist attraction for foreigners. Its profile and product range target a medium-high socio-economic level, partly explaining the decline in sales during periods of crisis. The department store’s supermarket also has the same profile and its product range is considered by consumers to be high quality at medium-high prices. Consequently, it has suffered the same setbacks as the store that houses it despite the launch of a new ‘lowest price’ private brand known as ‘Aliada’, which probably mitigated losses in 2008 and 2009. Store brands are dealt with in greater detail in a specific section due to their relevance to the Spanish retail scenario. - The hypermarket chain Hipercor is also characterised by a wide product range under the premise of good value for money. The hypermarkets of El Corte Inglés group operate under the ‘Hipercor’ brand and are located in their own shopping centres, offering a range of food and textile products, accessories, leisure items, toys, computers, etc. similar to that of the group’s department stores but aimed at a slightly lower socio-economic level. The decline in sales is most likely due to the change in consumer habits towards local stores. Furthermore, the supermarket and convenience store formats are becoming increasingly more attractive to Spanish consumers to the detriment of hypermarkets (which lost 7.7% in comparison to the prior year). Table 12: El Corte Inglés: Turnover by Retail Sector %/Total Company

Retail Sector

55.7 17.8 0.3

Do-it-yourself (Bricor)

13.3

Travel agency (Viajes El Corte Inglés)

2.3

Change in %

2008

2007

Department stores (El Corte Inglés)

9,667.26

10,136.73

-4.6

Hypermarkets (Hipercor)

3,088.67

3,346.83

-7.7

48,41

34,84

39.0

2,306.01

2,243.53

2.8

Supermarkets (Supercor)

407.73

403.09

1.2

2.3

Convenience stores (Opencor)

407.63

400.31

1.8

1.0

Textile (Sfera)

170.83

144.61

18.1

0.5

Optician (Optica 2000)

80.82

82.87

-2.5

5.5

I.C.T’s (Investrónica, Telecor)

954.22

946.62

0.8

0.8

Insurance company (Seguros El Corte Inglés)

142.91

124.27

15.0

0.5

Other business

88.04

126.61

-30.5

100

Total company

17,362.3

17,990,31

-3.5

Source: El Corte Inglés annual report (2008).

The other formats fall within the framework of a specialisation policy which allows them to be at the forefront of their respective industries, whether travel, computers, telephony, insurance, convenience stores, supermarkets, opticians, fashion or DIY. - For example, the Sfera brand (designed to rival Zara, the Inditex group’s star player) seems to have obtained good results in spite of the economic situation. Its product range is centred on affordable clothing and accessories, dominated by own brands and similar to its

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main competitor. These stores are usually situated outside the main brand’s shopping centres in locations which are home to the various Inditex Group brands which we will consider later. - Bricor is a large retail outlet specialising in DIY and gardening which opened at the end of 2006. It also seems successful in the Spanish market, as evidenced by the increase in its sales figures during its first two years of business.

4.2.

Textile and Fashion Retailing

2009 was not a good year for the textile market in Spain. The financial crisis which continued in 2010, also gave rise to the fall in household consumption in this industry, affecting all companies irrespective of their size. Sales during the sales season, which began on June 21, 2010 in Madrid (Madrid is the first city to begin its sales season as it is a tourist attraction for consumers from Spain and other European countries), are expected to drop by around 30% with respect to 2009. According to the industry forecast, the figure will be the same in other important cities such as Barcelona and Valencia. The price war has also been to the detriment of companies, who have seen their profit margins plummet. In any case, Spain continues to be a very attractive country for the major international textile retail groups, who announced their intention to enter the industry in the main cities such as Madrid and Barcelona, pitting themselves against the Inditex Group. El Corte Ingles is one of Spain’s leading fashion and textile retailers. As mentioned previously, its product range is aimed at a mid-high socio-economic level, with a significant presence of national brands and some store brands. This somewhat limits its potential to expand during periods of recession like at present. The Carrefour Group is another one of the leading textile retailers in Spain, which in this case includes homeware. Spanish consumers regard Carrefour’s clothing as low quality and low price and, therefore, demand is mainly focused on essential items (t-shirts, pyjamas, socks, etc.) while homeware presents a completely different picture and is highly regarded for its good quality for money and innovation. Mango, the second largest Spanish fashion exporter, has nowadays 1,431 shops in 100 countries, and wishes to open 150 more in 2010. This fashion group reached in 2009 a sales volume of 1,480 million EUR, 2.8% more than in 2008. The 78% of the turnover of the company came from the sales to foreign markets, whereas the Spanish market supposed the 22% remaining. Mango has targeted China in 2010 as their following ‘great bet’, since they expects to inaugurate 59 points of sale in the country. The turnover of Mango across Internet was 11.7 million EUR in 2009 and could increase in 2010 with the incorporation of the shoppers from China and Russia. Nowadays, the sales online come from Europe, The United States, Canada, Japan, Turkey, and Korea.

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The Inditex Group as Major Global Player from Spain The Inditex Group has various brands with specific features targeted at different demographic segments, and also categories other than personal apparel. It is considered one of the most powerful groups in the world in its business area and has 4,530 stores in 73 countries. It also has over 100 companies related to various activities making up the textile design, manufacture and distribution business. According to experts and the company itself, the secret of its success is the right mix between innovation and flexibility. In any case, the flagship of fashion in Spain is Zara, the Inditex group company known in major countries worldwide. The first Zara store opened in 1975 in La Coruña (Spain), where the Group began operating and which is still home to the company’s central services. Its stores, which are always found in privileged locations, are present in over 400 cities throughout Europe, America, Asia and Africa. Table 13 shows the development Inditex sales. Inditex has expanded rapidly throughout the world and is currently present in 74 countries. Its performance has always been positive, even during the recent crisis, Table 13: Inditex Group Sales Figures Financial year Revenue (millions of EUR)

2009

2008

2007

11,084

10,407

9,435

Net profit (millions of EUR)

1,314

1,253

1,250

Number of stores

4,607

4,264

3,691

Number of countries Share of international sales Employees

74

73

68

68%

66%

62.5%

92,301

89,112

79,517

Source: Inditex (2010).

Inditex’s store formats and brands comprise Zara, Pull and Bear, Massimo Dutti, Bershka, Stradivarius, Oysho, Zara Home, Uterqüe and Tempe (see Table 14). Each of the brands is directed at a specific segment of the population but they all have the same original characteristics in common: record adaptability to the fashion trends of each country, city and even specific area and excellent value for money. ‘Uterqüe’, which first opened in 2008, is the Inditex Group’s new sales format. Its focus is on accessories, fashion articles and clothing which are more select and of higher quality and price than its other stores in general. The collection, designed in full by Uterqüe’s creative team, combines the style of the latest fashion trends with the exclusiveness of its product. According to the company, the Inditex business model is characterised by a high degree of vertical integration compared to other models developed by our international competitors. It covers all phases of the fashion process: design, manufacture, logistics and distribution to its own managed stores. It has a flexible structure and a strong customer focus in all its business

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areas. The key to this model is the ability to adapt the offer to customer desires in the shortest time possible. For Inditex, time is the main factor to be considered, above and beyond production costs. Vertical integration enables the company to shorten turnaround times and achieve greater flexibility, reducing stock to a minimum and diminishing fashion risk to the greatest possible extent. Using this strategy, in 2009, Inditex became the number one fashion group worldwide snatching the lead held until then by the US company The GAP (see Table 15). Zara is the market leader in Spain. Table 14: Number of Inditex Stores in the World (April 2010) Brand

Number of Stores

Zara

1,422

Zara Kids

209

Pull and Bear

640

Massimo Dutti

507

Bershka

665

Stradivarius

533

Oysho

402

Zara Home

263

Uterqüe

64

Total

4,705

Source: Inditex (2010).

Table 15: 10 Top Fashion Retail Companies Around the World Company

Origin Country

Turnover (Millions of EUR)

The TJX Company1

US

13,100

Kohl’s Corporation2

US

11,300

Inditex GAP

3 4

Hennes & Mauritz (H&M) Limited Brands5 Nordstrom6

Spain

10,407

US

10,020

Sweden

9,320

US

6,240

US

5,910

Japan

5,270

Ross Stores8

US

4,470

Next9

UK

4,060

Fast Retailing7

1

Note: The TJX Companies, Inc. is the leading off-price retailer of apparel and home fashions in the United States and worldwide. 2 Kohl's Corporation is an American department store chain. Based on 2008 revenue, Kohl's was the 24th-largest retailer in the United States. 3 The Gap, Inc. the largest specialty apparel retailer in the US. 4 H & M Hennes & Mauritz AB (operating as H&M) is a Swedish clothing company, known for its fast fashion clothing offerings. 5 Limited Brands (formerly known as The Limited, Inc.) is an American apparel company. One of its best-known brands is Victoria’s Secret. 6 Nordstrom, Inc. is an upscale bridge department store chain in the United States. 7 Fast Retailing Co., Ltd. is a Japanese retail holding company. In addition to its primary subsidiary Uniqlo, it owns several other brands, including Aspesi, Comptoir des Cotonniers, Foot Park, Princess Tam-Tam and National Standard. 8 Ross Stores, Inc. is a chain of American off-price department stores, operating under the name Ross Dress for Less. It is the nation's third largest off-price retailer. 9 Next plc is one of the United Kingdom's largest clothing retailers. Source: Adapted from Expansión (2010).

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As previously stated, Zara is the Inditex Group’s most well-known brand worldwide. Tourists and foreigners who know Spain cite it as one of Spain’s seven greatest contributions to the world (alongside Pablo Picasso, Don Quijote, sherry, Pedro Almodóvar and the Spanish language). On its own, it is an enormous tourist attraction in all cities and especially in more commercially developed areas such as Madrid, Barcelona and Valencia. When the Spanish fashion brand Zara opened its doors in London it was likened to a fairy tale. When it arrived in Switzerland, fashion experts said that the company was like a tornado in the ‘prêt-a-porter’ world. Wherever it lands, it achieves astronomical sales figures. Currently, it is present in 51 of the largest cities in Spain, 76 in France, 7 in Switzerland, 45 in Germany, 50 in the UK and in 14 US states (6 in New York City and 2 in San Francisco) and in numerous Asian, Middle Eastern and even African countries. Regarding the Zara strategy, Kumar (2005) wrote in the Businessworld magazine: Zara sourced around half its garments from third parties in low-cost manufacturing locations like Asia. These were basic collection items or wardrobe ‘staples,’ with minimum fashion content such as T-shirts, lingerie and woollens, and where there was a clear cost advantage. Externally manufactured items were shipped to Zara's distribution centre. The other half of Zara’s garments, those that were more fashion-dependent, was manufactured in-house, in nearby Zara factories. Zara is a fashion imitator. It focused its attention on understanding the fashion items that its customers wanted and then delivering them, rather than on promoting predicted season’s trends via fashion shows and similar channels of influence, which the fashion industry traditionally used. A team of 200 young, talented yet unknown designers created designs, based on the latest fashions from the catwalk and other fashion hotspots, which were easily adaptable to the mass market. In this way, Zara became adept at picking up up-to-the-minute trends and churning them out to stores around the world in a matter of weeks. With regard to the future, the Zara chain will begin selling its products online during the 2010 autumn-winter season. Initially, internet sales will begin in Spain, France, Germany, the UK, Italy and Portugal and will gradually be introduced in all the markets in which Zara is present. In this connection, the deputy chairman of Inditex, Pablo Isla, described this launch as “a significant strategic step within the framework of the Inditex Group’s daily quest to offer the best service to its customers throughout the world”.

4.3.

Food Retailing

As mentioned previously, the main retail groups in Spain base their activity on the sales of food. In Table 16 we show the 20 top food retail companies by selling surface in 2008. Supermarkets generate in 2008 the 46.1% of home food sales; corner shops got 27.7% and hypermarkets, the most notable of which are Carrefour, Alcampo, Eroski, and Hipercor, gen-

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erate the 16.8% (ICE 2008). Overall, in 2008 organised retail in Spain billed a total of EUR 76,790 million. 62.49% of this figure corresponds to the turnover of the five main groups (see Table 19): Carrefour (19.46%, inc (18.60%), the Eroski Group (11.74%, including Eroski, Vegalsa and Caprabo), the Auchan Group (6.46%, including Alcampo and Sabeco), and the El Corte Inglés Group (6.23%, including only the divisions with a food base, i.e. El Corte Inglés supermarkets, Hipercor, Supercor, Opencor, and Gespevesa). Table 16: Top 20 Food Retail Companies by Floor Space in 2008 No.

Company

Surface (sqm)

Country Share sqm (%)

No. of Own Stores

No. of Franchises

1

Mercadona, S.A.

1,584,426

13.25

1,210

-

2

C.C. Carrefour

1,523,179

12.74

269

8

3

Eroski Group

1,076,519

9.01

653

416

4

Dia, S.A.

941,444

7.88

1,972

824

5

Alcampo, S.A. (Auchan)

497,187

4.16

50

-

6

Lidl Sup., S.A.

384,000

3.21

480

-

7

Consum, S. Coop.

367,283

3.07

426

138

8

Dinosol Sup., S.L.

366,248

3.06

427

-

9

Hipercor, S.A.

358,257

3.00

36

-

10

Coviran

323,431

2.71

2,350

-

11

Caprabo Group

292,772

2.45

359

-

12

Gadisa

244,950

2.05

204

191

13

El Arbol Group

210,110

1.76

341

130

14

Aldi Sup., S.L.

185,500

1.55

195

-

15

Sup. Sabeco, S.A.

166,213

1.39

126

-

16

Alimerka, S.A.

141,779

1.19

170

-

17

Supercor, S.A.

141,150

1.18

82

18

Ahorramas, S.A.

133,057

1.11

193

-

19

Dist. Froiz, S.A.

129,250

1.08

180

50

20

Hnos. Martin, S.A.

127,773

1.07

116

-

Source: Alimarket (2009a).

Table 17: Evolution of Market Share of the Main Food Retail Groups in Spain 2002-2008 (in %) 2002

2003

2004

2005

2006

2007

2008

Carrefour Group1

22.0

22.1

22.4

21.7

22.4

23.2

19.46

Mercadona, S.A.

12.8

14.6

16.3

17.8

18.7

19.6

18.60

8.2

8.3

7.4

7.3

7.5

10.1

11.74

Auchan Group3

5.7

6.0

6.1

5.8

5.8

5.8

6.46

CR4 (4-top market share)

48.7

51.0

52.2

52.6

54.4

58.7

56.26

Eroski Group

2

Note: 1 Carrefour group: Centros Comerciales Carrefour, S.A.+ Día, S.A. (includes Plus Supermarkets since 2007). 2 Eroski group: Eroski (supermarkets) + Eroski (hypermarkets) + Caprabo, S.A. (since 2007). 3 Auchan Group: Alcampo, S.A. + Sabeco supermarkets, S.A. Source: ICE (2008).

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Shopping Behaviour An analysis of the purchasing behaviour of Spanish consumers reveals, in line with the general ideas presented at the start of this article and the analysis of the data in Table 18 that purchases made at traditional stores are decreasing sharply, to the advantage of supermarkets, and there is a slight downward trend in hypermarkets. The reason may lie in the proximity of supermarkets and their greater adaptation to the specific needs and requirements of each area in which they are located. Experts also flagged traditional store opening hours as a reason why they are ceasing to be feasible. In any case, the large-format supermarkets (with sales floors of between 1,000 and 2,499 square meters) have reaped the greatest benefits. Although, the growth of the supermarkets is evident, in the table 19 we can see that, for packed food, only the format from 1,000-2,499 sqm is the one that really has showed an important advance, whereas small and medium supermarkets have been losing sales. Table 18: Food Market Share by Home Sales (% Sales Value) 1995

1999

2001

2003

2004

2007

2008

Total food (packed and fresh food) Corner shops

1

35.6

31.5

31.3

30.1

30.0

28.0

27.7

Supermarkets2

35.5

39.9

42.2

42.4

43.8

45.6

46.1

Hypermarkets

16.8

17.0

18.3

17.6

17.0

16.9

16.8

Other3

12.1

11.6

8.2

9.9

9.2

9.5

9.4

Total

100

100

100

100

100

100

100

Packed food (without fresh food) 1

24.1

14.7

14.8

13.9

13.4

11.6

11.4

Supermarkets2

44.0

52.8

53.6

54.3

55.9

57.1

58.1

Hypermarkets

24.3

25.3

24.8

24.1

23.7

22.9

22.7

7.6

7.2

6.8

7.7

7.0

8.4

7.8

100

100

100

100

100

100

100

Corner shops

Other

3

Total

Note: 1 ‘Corner shops’ includes grocer's shops, bakeries, butcher’s shops, fish markets, frozen food shops and markets. 2 ‘Supermarkets’ includes discount stores and self-service. 3 ‘Other’ includes self-consumption, street markets and other different stores. Source: MARM (2009).

Table 19: Market Share Performance by Store for Packed Food (%) Store Type

1994

1996

1998

2000

2001

2002

2003

2004

2005

2006

2007

Corner shops

13.0

10.8

9.0

7.4

6.5

5.9

5.5

5.1

4.8

4.4

4.3

4.2

Self service up to 100 sqm Small supermarkets 100399 sqm Medium-size supermarkets 400-999 sqm Supermarkets 1,000-2,499 sqm Hypermarkets 2,500 sqm or over

12.0

9.6

8.8

7.7

6.8

6.4

5.9

5.6

5.3

4.8

4.3

4.2

19.0

20.3

20.9

20.8

20.2

19.8

18.5

17.6

17.3

16.4

15.8

15.2

15.0

14.9

16.7

19.6

20.7

21.9

22.1

21.5

21.1

20.8

20.8

20.2

10.0

11.6

12.9

15.5

17.6

20.3

23.3

26.2

28.3

31.2

33.2

35.4

31.0

32.7

31.6

29.0

28.2

25.7

24.6

23.9

23.2

22.5

21.5

20.9

Source: Nielsen (2009).

2008

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However, an analysis of the data furnished by the Spanish Ministry of Industry, Tourism and Trade regarding the price changes by sales format confirms that the hypermarket format is responding best to the crisis and to the new price-focused demands and trends of consumers. In view of their importance, Table 20 includes the latest results of retailers’ prices in Spain in the food and household goods sectors. This information, from the Retail Price Observatory of the Spanish Ministry of Industry, Tourism and Trade shows the main players in the industry. Table 20: Food Retail Prices Observatory for Spain Company

Total Food

Packaged Food (Standard Shopping Basket)

Standard Economic

Aldi Specialised stores Dia Lidl Supply markets Mercadona Alimerka Carrefour M.A.S. Alcampo Sup. Piedra Gadis Carrefour express Galerias Primero Supersol Froiz E. Leclerc El Jamon Maxi-Dia Caprabo Sabeco Eroski Eroski Center El Arbol Ahorramas Dia Market Condis Sup. Consum Sup. Consum basic Lupa Coviran Hiper dino Super BM Supercor Sorli Discau Hipercor El Corte Ingles

[no data] [no data] [no data] [no data] [no data] 100 101 102 103 103 104 104 104 105 105 105 105 105 106 106 107 108 108 108 108 108 108 110 110 111 111 111 112 113 114 118 120

[no data] [no data] [no data] [no data] [no data] 106 105 102 107 100 109 107 106 111 110 106 106 109 107 106 108 104 106 106 106 107 108 107 107 109 112 108 107 108 115 109 109

[no data] [no data] [no data] [no data] [no data] 38.23% 32.16% 38.56% 37.53% 36.78% 33.86% 36.32% 37.24% 34.95% 35.92% 34.08% 33.87% 36.12% 39.75% 36.58% 38.08% 38.67% 37.45% 33.51% 33.62% 36.47% 31.32% 38.97% 38.62% 31.68% 34.94% 33.59% 33.94% 28.79% 30.33% 31.32% 31.11%

vs.

Packaged Food (Economic Shopping Basket) 102 [no data] 105 104 [no data] 105 114 100 107 101 115 109 107 115 112 112 112 111 103 107 107 102 106 113 113 109 118 105 105 119 117 115 113 123 128 120 120

Household Goods (Standard Shopping Basket) [no data] 113 [no data] [no data] [no data] 106 109 109 112 106 110 107 112 111 115 109 107 110 106 108 112 109 114 112 108 108 107 107 108 113 113 100 110 112 123 114 117

Source: MICYT (2009).

To calculate the relative indices, the store (format, city or brand) with the lowest weighted average price is given an index of 100 and other stores are then referenced on the basis thereof. Consequently, all the relative indices are equal to or greater than 100. In order to understand

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this information, it must be noted that the concept of a ‘standard shopping basket’ contains the most common national-brand products. The ‘budget shopping basket’ contains the same products as the standard shopping basket but at a lower price regardless of whether they are national or private brands. It can be seen that the lowest-priced brands in the standard shopping basket (variety of the usual household consumption products) are Mercadona, Alimerka, Carrefour, MAS, and Alcampo while the most expensive brands correspond to the various divisions of the El Corte Inglés food group. For the first time, hypermarkets have become the most economical outlet for the budget shopping basket as far as packaged food is concerned. They also hold this position for packaged food, fruit, vegetables, and fish in the standard shopping basket. In Table 21 we note the main trends in food and household goods based on the previous study (Price Observatory), which we also discuss below. The role of the recent economic crisis in the general lowering of prices in all the sales formats is noteworthy. Hypermarkets are trying to recover their leadership based on this strategy, with more effectiveness than the other formats. The explanation for this can be found in their greater capacity to employ price as a tool thanks to an even more intensive use of their store brands. As a result of this strategy, the difference between the cost of the ‘economic basket’ and the ‘standard basket’ has widened to a minimum of 35%, and by up to 37% in hypermarkets. Table 21: Conclusions from the Price Observatory – 4th quarter 2009 Conclusion General results

Results by format: standard food purchase basket

Results by format: Economic food basket Results by format – food: standard vs. economic basket

Important trend towards food price decreases in 2009. Change in 4th quarter 2009, with food price increases in all commercial formats except for hypermarkets, observed in all references. Household goods prices decrease in 4th quarter, except for traditional shops, in which the opposite trend was observed. By store type, the price gap widens, being 3% at the moment. In 2009 results, all formats have reduced prices. The biggest decrease is seen in hypermarkets (-2.3%) and the smallest in large supermarkets (-1.1%) Hypermarkets are positioned as the cheapest format, and small supermarkets as the most expensive. In the last quarter, only hypermarkets decrease prices compared to the previous quarter. Compared to the previous quarter, all the other formats have increased prices in a similar proportion (between +0.2% and +0.6%). In 2009 results, all formats have reduced prices. Hypermarkets are the cheapest format, and small supermarkets (109) are the most expensive. Compared to the last quarter, all formats except for hypermarkets have increased prices, especially the medium-sized supermarkets. Minimum difference between the standard and the economic basket is 35%, following the rule: the larger the surface, the larger the difference. Hypermarkets present the highest difference among baskets (37%).

Source: MITYC (2009).

In view of the results of this analysis, we would like to underline the particular behaviour of supermarkets in the face of the crisis and the decline in their sales compared with the hypermarket format though the supermarkets are growing more than the supermarkets. Store brands play a considerable role in this hypermarket drive as observed by the variation in the standard shopping basket compared to the budget shopping basket. Therefore, the following section

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will deal with the analysis of store brands in the food industry and in large nonfood retail outlets (category killers) since we consider store brands to be one of the most relevant factors for the present and future of FMCGs not only in Spain but in the rest of Europe and other countries with more developed economies.

Importance of Store Brands Having analysed the scenario of FMCGs in the food industry and the trends reflected by the Price Observatory, we will now focus on one of the most important strategic elements that has most helped its growth: store brands. Store brands are the result of growth and concentration in the area of FMCG retail, as is the case in other European countries (Cliquet 2009; Reynolds 2009; Morschett 2009). In Spain, those products have had a constant growth from its origin supported by the retail concentration (Puelles 1986; 1991; 1992; 1995; Román/Recio/Puelles 1993; Serra/Puelles 1993; Serra/Puelles 1994; Puelles/Puelles 2003; 2004; 2008; 2009). First of all, it is interesting to note that all of the world’s top ranked countries in terms of private label are European because despite the importance of the US private-brand market, it is at present less than half of the leading European countries. Table 22 includes the top countries by store brand share, based on the source we consider most reliable for this purpose, PLMA, which brings together the leading private-brand manufacturers in the world. Table 22: Top Countries by Store Brand Share Country

Ranking

% Store Brand Share

2008

2009

2010

2008

2009

Switzerland

1

1

1

53

54

2010 53

United Kingdom

2

2

2

43

48

47

Belgium

3

3

6

42

40

38

Germany

4

4

5

39

40

41

Spain

5

5

4

35

39

42

Austria

15

6

7

21

37

38

Slovakia

7

7

3

34

37

44

France

6

8

8

34

34

35

Portugal

9

9

10

27

34

34

Czech Republic

11

12

9

25

28

35

Finland

12

10

11

25

28

29

Denmark

10

10

12

27

28

28

Source: PLMA (2010).

The drop in disposable income due to the recession and the increased uncertainty resulting from the rise in unemployment rates in Spain (almost 20%) led to a change in spending habits. In response to this situation, consumers are trying to reduce the total cost of the shopping basket as much as possible. The effect of this trend is that consumers are becoming less sensitive to brand

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names (IRI 2010) and more conscious of price, which has become the decisive factor in many categories and overrides other factors such as brand, variety and format, etc. According to an article published in Cinco Días on December 13, 2009, almost nine out of ten consumers (88.6%) consider that store-brand products are beneficial when shopping while 4.2% consider that they are negative, based on the latest report from the Public Opinion Polls (IOP) of Simple Lógica. However, there are also significant differences in the aforementioned consideration depending on the age, level of education and the place of residence of those surveyed. The consumer groups which value store brands most highly are aged between 25 and 44, have a secondary (93%) or university education (95%) and reside in the autonomous communities of Catalonia (93%) or Madrid (92%). The success of the MDD in commodities has led the distributors to extend their offer and brands to consumer durables categories (Caplliure/Miquel/Mollá 2010); this one is one of the most important trends of growths of the store brands in Spain at the moment. Conversely, those with a worse opinion of these brands include the over 55’s (although this figure does not exceed 6.4%), with primary or a lower level of education (81.3%) and residing in autonomous communities such as Andalusia (83.9%) and Galicia (84.8%). According to this same study and as we mentioned previously, the consumption of store brands is growing according to the research of the GUIA-MDD group of Universidad Complutense de Madrid[3]. 51.6% of consumers surveyed state that they use some or many store brands in their homes. Of this figure, 16.2% say that they use a lot of store brands at home and 35.4% indicate that they use some, compared to 10.2% who state that they use few and 7.9% that state they do not buy them at all. A closer look at the role of store brands in Spain in the current economic situation confirms that they come out on top (Abril 2009). According to various sources including Infoscan (IRI 2009), the proportion of store brands as a percentage of total food sales began to increase considerably from the last quarter of 2007, achieving a maximum of over 38% in value in the second quarter of 2009. In Spain, the market share of store brands currently stands at around 50%, meaning that at present half of all food products purchased in Spain are store brands. With regard the current economic crisis, store brand strategies have been very pro-active. In fact, retailers started their price reductions with their store brands and they strongly communicated that to the consumer to help them in view of the current economic circumstances. Some of them have launched even more economical lines such as ‘Carrefour Discount’. We can see this trend in Figure 5 which represents the market share of store brands in the last seventeen years in Spain. We can observe that market share growth during recession is asymmetric (Puelles/Abril 2010). The data obtained by the research group GUIA-MDD [3] of Universidad Complutense de Madrid in December 2009 seem to confirm these observations on the trend and improvement in the perception of store brands in Spain due to the crisis. The results of this research show not only the

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increasing demand for store brands but also other interesting conclusions are particularly noteworthy: - The purchase and consumption of store brands is on the increase and there is a greater predisposition towards this trend, although to a lesser extent in some concrete categories of products like cosmetics, wines, and ‘jamón serrano’ (Muñoz/Cotes 2010). - The quality of store brands is perceived in a better light, probably as a result of increased use (Mendez/Oubiña/Rubio 2009). - The price and quality of store brands in Spain are valued highly by consumers although they consider that the packaging could be improved. - The association between the quality of store brands and the store image is significant, particularly in brands with the same name as the store. As a result, the major retail players in Spain have continued to push their own brands forward in recent years, mainly in 2008 and 2009, as can be seen in Figures 5 and 6. Figure 5: Evolution of Store Brands’ Market Share in Spain (from 1991 to 2008)

Source: Adapted from Nielsen (2008); Abril/Boehm (2009); Puelles/Abril (2010).

Figure 6 reflects and supports the data obtained by Puelles and Abril (2010) on the growth of store brands during recession. This growth is broken down, by format, in the following Figure 7 where it can be noted that although hypermarkets are promoting their brands by offering better prices (as can be seen in the data from the Price Observatory of the Spanish Ministry of Industry, Tourism and Trade), consumers continue to opt for the supermarket format, especially the large-scale supermarket format (1001 to 2500 square kilometer).

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Figure 6: Store Brands Share in Value, Hypermarkets and Supermarkets (from 2003 to 2009)

Source: Adapted from IRI (2009).

Figure 7: Store Brands Share of Sales (%), Hypermarkets and Supermarkets (2009)

Source: Adapted from IRI (2009).

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As a final conclusion about Store brands, in general, the tendency is one of constant growth in the market share of store brands in comparison to national brands.

4.4.

The Category Killers

Large retail outlets are those with selling space of above 2,500 square meters. The opening of a large retail outlet is subject to obtaining two licences, one from the Spanish state and another from the autonomous community in which it is located (LOCE 1996 [4]), which to a certain extent has limited expansion. However, in 2010 certain autonomous communities (first and foremost, Madrid) are expected to eliminate the second licence, assigning the municipal councils the capacity to permit openings, provided that the project complies with the “public interest” required by the European Directive. We expect that this will promote the development of this type of business. As indicated in the introduction to this section, the nonfood specialist retailers entered Spain on the back of large European retail groups such as the Auchan Group which opened its DIY store Leroy Merlin (initially L&M) in Spain’s main cities in 1989. The retail format referred to in this article, large nonfood specialised retail outlets, has shown significant progress in the last few years with respect to the number of brands present and the number of new establishments opened for each brand, not only in Spain but also in the rest of Europe and the USA, although this growth slowed in 2008 and 2009. Based on this data, it is interesting to study its peculiarities and strategies in depth in order to determine the factors behind its current success and to attempt to predict how it will perform in the future. In any case, the large nonfood retail outlet concept is well entrenched in Spain and is continuously evolving and growing both in Spain (Puelles 2004a; 2004b; 2006; Puelles/Manzano 2009) and in the rest of the European Union and the USA. Its main competitors are small specialised retail outlets, hypermarkets and department stores, together with internet sales. Although their initial objective was to be leaders in depth of line, these outlets are consolidating their position as specialists in the group of consumers within their scope of action, focusing on a non-professional buyer and excluding the most specialised items and those whose quality and/or margin is too low. The importance they place on the different categories and subcategories in each sector depends largely on their profitability, as in other formats. On the other hand, their status as ‘category killers’ seems to assume that they would have, along with the wide range of the lines they work with lower prices than the competition for their product range in general. In reality, lower prices can be obtained in other formats such as hypermarkets with even greater differences if we add to the price of the item certain elements which are often not included in the products of the large nonfood retail outlets or the price of which is higher, such as transport, installation, extension of warranties, financing, etc. One of the most notable characteristics of this type of establishment is the enormous difficulty the consumer

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(Fernandez 2008; Puelles 2006) has in comparing prices between different brands since they do not tend to coincide except in very specific categories such as toys.

Main Players Table 23 shows the growth, in number of stores, from 2004 to 2006 of certain of the most important brands in Spain. Table 23: Main Category Killers in Spain Company Menaje del Hogar Urende

First Store in Spain (Year) --

Spain

No. of Stores 2009 47

1969

Spain

30

Country of Origin

Main Product Category Electrical & household goods Electrical & household goods

Ikea

1981

Sweden

11

Furniture & decoration

Leroy Merlin

1989

France

47

DIY

Toys’R’Us (& Babies’R’Us)

1991

U.S.

52

Toys

Décathlon

1992

France

76

Sports

Fnac

1993

France

19

Leisure, books.

Media Markt

1999

Germany

52

Electronics

Saturn

2005

Germany

9

Electronics

Bricor

2006

Spain

2

DIY

Source: own compilation from different company corporate websites.

As mentioned above, this format is sometimes the result of the large food retailers diversifying into categories other than food which are attractive and have sufficiently promising margins to be treated and commercialised independently, as in the case of Alcampo, Décathlon, Boulanger, Kiabi and Norauto, which belong to the Mulliez Family Association, together with other brands grouped together in Spain under the Adeo Group (Leroy Merlin, Bricocenter, Aki, Weldom, Dompro and Bricoman). Table 24: Media Markt Development in Spain Year

No. of New Stores

1999

1

7

2000

3

44

2001

5

145

2002

4

300

2003

5

2004

4

638 852

2005

6

1,021

2006

9

1,421

2007

4

1,790

2008

5

1,809

2009

6

1,758

Source: Media Markt corporate website (2010); Alimarket (2009).

Turnover (in Million EUR)

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The Media Markt and Saturn brands also belong to another large food group, the Metro Group. Media Markt is of German origin and is Europe’s largest consumer electronics retailer. It specialises in information technology, home appliances, audiovisual equipment and CDs. The first store opened 1979 in Munich. Today, it is owned by MediaSaturn Holding, part of the Metro Group, which also owns the rival chain, Saturn. Due to its rapid expansion in Spain, some key figures shall be displayed (Table 24). Saturn, a sister company of the same group, began its expansion into Spain less than five years ago and, therefore, its presence in Spain is less than that of Media Markt. Furthermore, consumers do not seem to notice significant differences between their offerings which justify preferring one brand over the other. However, both companies are currently leading this industry in sales. Toys ’R’ Us Iberia is a consolidated company with revenue of EUR 316.8 million in 2008, the same year in which it increased its sale of toys in Spain by 4.3%. Currently, it has 52 stores in Spain. In 1993, FNAC, owned by the French group PPR, arrived in Spain and opened its first store in Madrid. Currently, it has 19 stores in Spain. The PPR Group's activity in the retail sector is comprised of the Printemps, Redcats, FNAC, Conforama and CFAO brands. Leroy Merlin, which arrived in Spain in 1989, leads the DIY sector and has decoration and gardening sections. Together with Ikea and Décathlon, it is one of the groups that has developed its store brands the most. The group to which it belongs also owns the Aki brand with smaller stores and a more limited product range. In the home appliance and consumer electronics sector there are also two Spanish brands: Menaje del Hogar and Urende. Currently, Menaje del Hogar, with 47 stores (between large nonfood retail outlets and medium-sized specialised retail outlets), forms part of the Kesa Electricals Group (the third largest specialised retailer of home appliances in Europe) which owns the Darty, Comet, BCC, Vanden Borre and Datart brands and which is present in nine European countries. Urende, on the other hand, has 30 stores in Spain. Store brands are used unevenly, although increasingly, in two very different ways. There are establishments which exclusively or at least dominantly sell store brands which may or may not coincide with the retail brand, such as Ikea and Décathlon. However, in other sectors such as the home appliance sector, store brands are not so evident although there are national brand products which are made by manufacturers to be sold exclusively by these nonfood retailers. We could say that this is an example of a private brand use which is extended but not evident. One of the attractions of these stores for Spanish consumers is price, followed by variety and breadth of the offering. In order to consolidate the image of reasonable pricing, two main strategies are used, everyday low price advertising and the inclusion of more and more store brands in the selection. Changes in the use of store brands are taking place in the large non-

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food retail sector which we consider very significant and analyse in detail. One of the most noteworthy is the emergence of lowest price brands at the same establishments that had already consolidated their private brand, leading to a second class of private brand and following the path of the large food retailers (Puelles/Puelles 2003). Without a doubt the significant appeal and growth of this format seem to be based on pillars which, although different from those that first brought them about, are just as valid. They include: - A less extensive offering which is more focused on the preferences of the type of consumer within their scope of action. - A greater number of categories which supplement the original main category so that the consumer perceives the visit to be more convenient and rewarding. - The availability of the selected item is usually guaranteed by a large stock in the store or warehouse. The buyer perceives this as a necessary reward for the effort of the trip. - Greater concentration of large nonfood specialised retail outlets and concentrations together with leisure and fashion centres to offer an alternative way to spend weekends and holidays. In addition, they extend opening hours to coincide with the aforementioned leisure and fashion centres. - Improvement of merchandising in order to convert the visit to the store into a pleasurable experience and encourage a greater volume of impulse purchases. - Available space is used efficiently to adapt to the seasonality of the sales of the various subcategories which comprise the product range; in some cases with very sophisticated and innovative merchandising techniques. - Continual, highly attractive special offers which act as a magnet for consumers and consolidate the image (Manzano 2009) of everyday low-price establishments (we stress that the nature of this strategy is more perceived than real). - A wide range of additional services, from those purely linked to the product such as transport, installation and financing, etc., which, although they are not free in the majority of brands, are beginning to be included as part of certain products as a way of differentiating the brands. There are also other services which promote the DIY leisure and training side such as catalogues, courses, talks, advisory services, daycares, gyms, massages, etc., which are also paid but they make the visit to the large nonfood retail outlet into an experience in and of itself. - Excellent customer loyalty programmes which grant access to additional guarantees, ease of purchase, discounts, privileged information and additional services at a lower cost or even free. - Extended and adjusted opening hours to adapt them to the time of purchase of the types of products in which large nonfood retail outlets specialise.

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- Reintroduction into cities in smaller formats in order to maintain those customers who think it is difficult or not worthwhile to travel to the outskirts where large nonfood specialised retail outlets are traditionally located. Opening smaller stores in strategic locations for the use and enjoyment of the categories in which they specialise. - In specific cases and with the introduction of new brands (Brico Dépot, Tobogán, etc.), there has been a return to low prices in general for the entire product range and a broadening of the depth of the line to include products for both professionals and beginners. The result is a return to the roots of these formats without abandoning current policies. In short, the aim is to expand the market with new consumer segments. - Store brands are becoming more and more relevant and prominent, both explicitly and in concealed form, and with such success for some brands that they becomes the market reference rather than the national brands, as is the case with Ikea and Décathlon. - Development of store brands in the format of a lowest price brands in order to address segments which are more sensitive to price. - Creation of large nonfood retail outlets by manufacturer cooperatives as in the case of the French ironmongers who founded brands like Master Pro and Brico Pro in order to compete with other large nonfood specialised retail outlets. The first store opened in 1991 and they currently have 354 outlets throughout France. Now that the strengths of these large nonfood specialised retail outlets have been pointed out, we would also like to emphasise that the greatest weaknesses of the nonfood retail outlets may be that they focus on very seasonal categories and on maintaining the image of ‘perceived low’ prices. With respect to the latter, if the current trend of evaluating and comparing prices before buying continues, these formats will face difficulties, at least at medium term, in maintaining their positioning as everyday low price establishments (more perceived than real), which is one of the greatest attractions for consumers. However, strengthening other qualities which are perceived as appealing, such as adapting the product range to the characteristics of the consumers they serve, improved services and the creation of a pleasant environment which encourage and justify the trip, both inside the store and through the joining of large nonfood specialised retail outlets with fashion and leisure, will probably allow them to continue their trajectory and expansion. In addition, the creation of new brands directed at groups who are more sensitive to price may help to maintain, and even grow, their share of the market.

5.

General Conclusions on the Retail of FMCGs in Spain

In accordance with the information presented throughout this report, the retail industry in Spain is of vital importance to the economy of our country. Spain’s unique geographic and political characteristics have created a very uneven distribution of population and, therefore,

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of business, resulting most notably in certain areas where both these factors combine. With respect to the future development of the industry, the expansion of existing companies and the possible entry of new competitors, these factors take on increased significance. The varied legislation governing retail makes it advisable to consider this factor as a possible incentive or deterrent for the development of certain sales formats. Spain is traditionally a tourist country, the destination of many visitors from Europe and other continents, which has promoted the entrance and growth of the international retailers which have been able to provide support for and a response to the increasingly varied demand (Spanish, foreign/tourist) in Spain. There are areas which particularly attract tourism from certain European countries such as the Canary and Balearic Islands where there are even towns in which the majority of registered inhabitants are German. This has encouraged the development of businesses created specifically to meet the needs of these groups. The retail structure based on traditional business which existed until relatively recently underwent rapid change after Spain joined the EU and large international retail groups in all sectors were developed. Spanish consumers have adapted very well to the new formats and sales offerings, which has contributed to the expansion of these groups. However, the retail industry, along with numerous other businesses, has been hard hit by the economic crisis, and many mainly small businesses have had to shut their doors. Tourism is a small exception since Spain offers a cultural alternative with sun and beach that is more affordable than other international destinations, although the length of stay and the average spending per tourist have decreased considerably. In the context of the economic crisis, the outlook is still not very encouraging regarding the stimulus for consumer spending in 2011. However, retailers are making great efforts to reactivate it, as in the case of food businesses which considerably lowered their prices in 2008 and 2009 due to a large extent to the development of their store brands. The development of these store brands is very significant in Spain, with a market share of almost 40%, and consumers are getting used to buy these products as they were national brands. Furthermore, a substantial improvement in the perception and acceptance of this type of product by consumers has been detected, which could be a possible way to increase sales of certain categories such as ecological products. Lastly, we would like to draw attention to the flexibility of the retail structure and Spanish consumers with respect to their adaptation to new trends and challenges, demonstrated by their ability to change in recent years and their confidence in the reactivation of consumer spending in the short term once the crisis has remitted, based on past consumer trends in Spain.

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Notes [1]

CNAE-2009 is the National Classification of Economic Activities resulting from the international revision process known as Operation 2007 and has been compiled according to the conditions set out in the Regulation approving NACE Rev.2. The objective of this classification is to establish a hierarchical group of economic activities that may be used to: 1) Promote the implementation of national statistics that may be differentiated according to the activities established. 2) Classify statistical units and entities according to the economic activity carried on.

[2]

Due to their importance, we have included the link to the studies conducted by the Spanish government on consumer habits in Spain: http://www.mapa.es/es/ alimentacion/pags/consumo/resumen.htm and http://www.mapa.es/es/alimentacion /pags/consumo/observatorio/informes_anuales.htm.

[3]

GUIA-MDD: Academic Research Group on Store Brands. Group of the Universidad Complutense de Madrid working since 1990 in research on the evolution of this trend in Spain and Europe. Since 2008, researchers from several Spanish and foreign Universities have joined the group.

[4]

Spanish Retail Law 7/1996, of 15 January.

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Puelles, J.A.; Puelles, M. (2003): Marcas de distribuidor más de 30 años de un proceso dinámico, competitivo e imparable, in: Revista Distribución y Consumo Mayo, pp. 55-71. Puelles, J.A.; Puelles, M. (2004): Marcas de distribuidor, in: Diez de Castro, E. (ed.): Distribución commercial, 3rd ed., City Madrid, pp. 101-129. Puelles, J.A.; Puelles, M. (2008): Marcas de distribuidor (MDD), 100 Ideas clave. Iniciativas empresariales más novedosas a nivel mundial, in: Revista Distribución y Consumo, No. 100, pp. 241-256. Puelles, J.A.; Puelles, M. (2009): Evolución, situación actual y perspectivas de las MDD en España, in: Revista Distribución y Consumo, No. 107, pp. 7-20. Puelles, M. & Abril, C. (2010): Store brands in current economic crisis. 9th. International Conference Marketing Trends Venice, January 21-23, 2010. Puelles, M. (2004a): Grandes especialistas no alimentarios, colección estudios Vol. 78, Ministerio de industria Turismo y Comercio Dirección General de Política Comercial, Madrid. Puelles, M. (2004b): Los grandes especialista no alimentarios, in: Revista Distribución y consumo, No. 78, pp. 15-21. Puelles, M. (2006): Competencia y nuevas estrategias en el sector de la distribución especializada no alimentaria, in: Distribución y consumo, No. 100, pp. 5-23. Puelles, M.; Manzano, R. (2009): Actualidad de las marcas de distribuidor en las grandes superficies especializadas no alimentarias, in: Distribución y Consumo, No. 108, pp. 38-45. Pull and Bear (2010): http://www.pullbear.com/, accessed January 13, 2010. Reynolds, J. (2009): Investigación de marcas de distribuidor Evolución y situación actual en el Reino Unido, in: Revista Distribución y Consumo, No. 107, pp. 29-37. Román, V.; Recio, M & Puelles, J.A. (1993): Análisis de la distribución comercial en la CEE.- situación y perspectivas., Revista de Dirección, Organización y Administración de Empresas, Junio-Septiembre 1993, pp. 12-22. Serra T. & Puelles, J. A. (1993): Análisis de las marcas de la distribución en el mercado de la alimentación. Temas actuales de marketing, V encuentro de profesores universitarios de marketing; Sevilla, Octubre 1993, pp. 103-117. Stradivarius (2010): Stradivas, http://www.stradivas.com/, accessed January 13, 2010. Uterqüe Spain (2010): Uterqüe Spain, http://www.uterque.es/, accessed January 13, 2010. Worten Spain (2010): Worten Spain, http://www.worten.es/, accessed January 14, 2010. Yanez, M. (2009): Trends in consumer goods market in Spain. http://marketingconsumidor. blogspot.com/2009/06/tendencias-del-cosumidor-gustos-habitos.html, accessed December 20, 2009. Zara (2010): Zara, http://www.zara.com/, accessed January 13, 2010. Zara Home (2010): Zara home, http://www.zarahome.com/, accessed January 13, 2010.

Retailing in Italy - Players, Strategies and Trends Cristina Ziliani, Edoardo Fornari, Sebastiano Grandi, Maria Grazia Cardinali, Daniele Fornari, Francesca Negri and Davide Pellegrini [1]

Abstract Retailing in Italy is characterised by slowness in modernisation and internationalisation compared to the other European countries. The main reasons are restrictive regulations, especially governing the opening of large stores, and small firm size. This paper introduces the main players in the Italian food and nonfood retail market. The first part focuses on current developments in grocery market structure, strategic retail banner positioning and store format performance, at national and local level. Competition in nonfood retailing is also analysed, emphasising the key role played by international chains. The second part of the paper focuses on three major trends. The first is the growth of private labels. The second is the spread of loyalty programmes and the increasing use of loyalty card databases in planning and implementing micro-marketing strategies. The third and last trend concerns shopping behaviour, where there are changes in shopper profiles and needs.

Keywords Grocery Retailing, Italy, Market Concentration, Store Format Innovation, Private Label, Loyalty Programmes, Shopping Behaviour Changes

Cristina Ziliani (corresponding author), Dipartimento di Economia, Sezione Marketing, University of Parma, Parma, Italy (Tel: +39 521 032 012; E-mail: [email protected]). Edoardo Fornari, Dipartimento di Economia, Sezione Marketing, University of Parma. Sebastiano Grandi, Dipartimento di Economia, Sezione Marketing, University of Parma. Maria Grazia Cardinali, Dipartimento di Economia, Sezione Marketing, University of Parma. Daniele Fornari, Dipartimento di Economia, Sezione Marketing, University of Parma. Francesca Negri, Dipartimento di Economia, Sezione Marketing, University of Parma. Davide Pellegrini, Dipartimento di Economia, Sezione Marketing, University of Parma.

Received: March 25, 2010 Revised: July 15, 2010 Accepted: June 30, 2010

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D. Morschett, et al. (eds.), European Retail Research, DOI 10.1007/978-3-8349-6147-1_7, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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Introduction

The extremely discontinuous and complex nature of the macroeconomic scenario of today makes it important to analyse the changing structure and trends of the retail market. In Italy, as elsewhere, the retail revolution has modified equilibria and roles of retailers in all value chains and thus brought about a need for a ‘systematic’ perspective in market analysis. The structure and dynamics of the channel relationships and marketing policies are closely influenced by the operating environment as well as the different stages of the marketing channel, which means that functional and sectoral approaches are inadequate to interpret the growing complexity and discontinuity of the marketing processes. Today, interdisciplinary skills are required in order to gain a complete, integrated and interactive view of the phenomena conditioning company marketing policy. This work therefore focuses on the main trends on the Italian retail market: - The first trend is the slowing in the growth rate of modern distribution, which is occurring overall and at varying rates. There has been a fall in the number of new store openings, and many companies are modernising existing outlets rather than opening new ones. - The second trend is a change in models of consumption, with consumer demand increasing for services rather than for products. - The third trend is a re-shaping of competition among different strategic groups with widespread recourse to buying groups by multinational firms and the increasing instability of these groups. - The fourth trend is the development of different sales channels in both food and nonfood distribution. The dynamics of this development are characterised by the success of convenience stores and category killers, by the maturity of the hypermarket business model and by the ‘search for new identity’ by discount outlets. - The fifth trend regards innovative store brand strategies where there is increased fragmentation and differentiation of the store brand lines, often strengthened by promotion and communication as well as traditional marketing levers. - The sixth trend is the paradigm shift in retail pricing policy, which is increasingly blurring the distinction between short and long term pricing policies and emphasising ‘value for money’ positioning. - The seventh trend is the increasing use of loyalty card data in customer segmentation and micro-marketing.

2.

Retail Market Structure

The modernisation of retail tends to occur gradually and at different rates across different countries (Lugli 2009). The process is gradual; the irreversible structural configuration brought about by the Commercial Revolution was consolidated gradually over the years. It is

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also transversal in that it tends to appear in similar ways across different countries and distribution sectors, albeit at different times. This indicates the existence of a ‘life cycle’ characterised by stages where the indicators show different values. The indicators under examination here are modern trade, types of sales channels, the degree of commercial concentration of sales and procurement, the competitive positioning of strategic groups and the level of presence of international retail brands. The indicators show that modernisation of the retail system has reached a phase of progressive maturity in Italy, as in other countries. A comparison of Fast Moving Consumer Goods (FMCG) sales in modern distribution (hypermarkets, supermarkets and self-service superettes) and traditional distribution (traditional and specialised stores) shows that modern distribution now accounts for nearly 80% of sales (see Table 1). Table 1: The Importance of Modern Distribution in the FMCG Market Year

Modern Distribution Market Share of Number Grocery Market of Stores

Traditional Distribution Market Share of Number Grocery Market of Stores

1970

17.0

402

83.0

406,850

1980

26.0

1,526

74.0

357,475

1990

54.0

4,425

46.0

298,090

2000

65.4

7,253

34.6

212,520

2009

76.5

9,449

23.5

67,050

Source: Authors’ elaborations on several data sources.

Traditional distribution outlets in the food sector have undergone a significant selection process, and the number of sales points has fallen from over 400,000 in 1970 to the current 67,050. Traditional and small specialised outlets, mainly family-run, are playing an increasingly marginal role. The Italian distribution market is also characterised by ongoing modification in the market positions of different sales channels. There has been a significant reduction in the number of mixed, small food sales points and mini markets (100-200 sqm) and an increase in the number of superstores, supermarkets, discounts, and drugstores (see Table 2). Superstores, discount and convenience stores have registered particularly positive growth performances in recent years, thanks to specialised grocery chains opening sales points directly and through franchising. But the low presence of hypermarkets in Italy compared with the main European countries appears to be the result of two groups of factors: legal restrictions and local variations. As regards legislation, commercial law in Italy is particularly restrictive on large stores, although it was recently liberalised. As for local factors, the Italian population tends to be distributed over small and medium towns rather than big metropolitan areas, and it is thus more difficult to identify consumer areas large enough to warrant the presence of a hypermarket. Generally speaking, there is great variety in the local distribution of retail for-

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mats. In Northwestern Italy, hypermarkets and superstores enjoy leadership and a market share of 40%, while in the South their presence is marginal and their market share is just 15%. Table 2: Market Position of Different Store Formats (2009) Number of Stores

Store Number Trend versus 2008

Market Share (%)

Hypermarket

401

+12

16.4

-0.2

Superstore

387

+26

8.8

+0.4

Supermarket

8,661

+265

40.3

+0.4

Convenience Store

6,898

+70

11.0

-0.2

Discount

3,848

+305

10.1

+0.6 +0.1

Store Formats [2]

Drug store

Market Share Trend versus 2008 (%)

2,196

+132

2.2

Mini/Micro Store

12,540

-403

5.1

-0.5

Food/Mixed Store

41,568

-1,215

4.9

-0.4

Total

76,499

-808

100.0

-

Source: Authors’ elaborations on IRI – Information Resources data.

However, just as in the main European markets, a significant slowdown in hypermarket growth rate is currently being seen in Italy. The phenomenon appears to be due to structural constraints on one hand, and marketing factors on the other. From the opening years of the 21st century, hypermarkets in Italy have recorded a gradual but constant reduction in levels of productivity and performance, and some researchers are talking about ‘maturity’ of the model. Development dynamics of distribution formats in Italy can be summarised in a matrix of the trends of average sales per sales point on one axis and the trends of the number of stores on the other (see Figure 1). Figure 1: Channel Development Trends (2009 versus 2008) 

+8

SUPERSTORE DRUG

+6

SUPERMARKET

+4

Trend of average turnover per +2 store

DISCOUNT

SUPERETTE

0 Ͳ2

HYPERMARKET MINIͲMARKET

Ͳ4 Ͳ4

Ͳ2

0

+2

+4

+6

+8

Trend in number of stores

Note: The bubbles’ size reflects the market share of each store format in Italy. Source: Authors’ elaborations on data from IRI – Information Resources.

+10

+12

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The matrix shows clearly how hypermarkets and mini-markets have recorded a decrease in the level of sales per sales point against an increase in the number of stores. The decrease in the growth of hypermarkets appears to be linked to the following variables: - population ageing, which favours the development of convenience stores - a fall in average family size and consequent diminishing spending on food - increasing competition among nonfood category killers - a change in the composition of food consumption, with fresh products, mainly purchased in small/medium stores gaining a larger share - gradual convergence of promotion and price policies between different sales channels, which reduces hypermarket appeal against supermarkets - decline in the efficacy of promotions and consequent attraction ability of large sales points - new organisation models increasingly characterised by centralised decision-making, which penalises peripheral levels of motivation and professionalism and therefore commercial performance. Modernisation of distribution systems and the development of new distribution formats appears to be favoured by increasing concentration of distribution. In fact, in the five years 2004-2009, market shares of the top ten modern trade operators with C5 and C10 indexes of concentration were consistently higher than 50% and 75% (see Table 3). These high shares, although they are related to the modern component of food retail, have seen the Italian market at least partly narrow the gap with more developed markets such as the UK, Germany, Spain, and France. Table 3: The Level of Concentration of Italian Retail Market (% over Total Modern Grocery Distribution (MGD)) Concentration Index

2004

2009

C1

17.4

15.5

C3

37.0

36.5

C5

53.2

54.1

C10

76.3

78.3

Source: Authors’ elaborations on IRI – Information Resources data.

An analysis of the different markets on the basis of the retail concentration indexes reveals that Italy still records an absence of leadership, with no leading retailer having a market share of 20%. But it also reveals that retail operator concentration levels are very close to those of other countries. Concentration is increasing, but it is important to remember that the Italian distribution market is characterised by the strong presence of buying groups. The high number of buying groups appears to be the result of two main reasons. The first is their ability and flexibility in formulating marketing policies for different local areas still

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strongly characterised by big differences in consumption/purchase models and companies’ competitive behaviour. The second has to do with national and regional regulations on commerce, which are restrictive and conservative. This makes the opening of a new hypermarket extremely complex and limits the development of chains. Buying groups now have a market share above 43%, showing a growth of nearly four percentage points against a reduction of the weight of Italian and international chains (Table 4). This trend is even more significant given that the chain store market share includes sales at Consumer Co-operative stores, which are characterised by a business model similar to chain stores, although there are significant differences with commercial chains from the point of view of regulations. Table 4: The Weight of Strategic Groups in Italian Retail Market (% of total MGD) Strategic Groups

2004

2009

Chains + co-operative groups

55.2

52.8

Buying groups

39.9

43.5

Other (independent)

4.9

3.7

100.0

100.0

MGD Total

Source: Authors’ elaborations on IRI – Information Resources data.

The high number of buying and co-operative groups on the Italian market has also reduced growth opportunities for international distributors. The internationalisation of the Italian grocery retailing market is characterised by two features. The first is that all distributors of Italian origin have shown a reluctant approach; instead of new geographical contexts they prefer to focus development on the Italian market (Treadgold 2000; Dawson 2004). The following factors have dictated this choice: - Until 2000, slow modernisation of the retail system encouraged investment in ‘internal’ development, and top companies obtained significant growth rates both in absolute terms (increase in trade and sales points) and relative terms (increase in the market shares). - International expansion of distribution normally occurs ‘one way’, from the economically more developed towards less developed countries (Dawson 2001). Most of the geographically and culturally close country-markets feeding into Italy have a more highly evolved retail system, which thus means they are a threat to competition rather than a business opportunity. - The business model of Italian retail is often difficult to export as it has a complex organisational structure and firms are often grouped into trade associations. The second characteristic of internationalisation of the Italian retail market is that it is one of the markets with the biggest investment opportunities for multinational retailers [3], albeit from the competition point of view. But there is still today a very low number of multina-

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tional retailers and they constitute a minority. The only international groups which have developed a significant presence to date are the two French firms Carrefour and Auchan, and their market shares of supermarket distribution, lower than 20%, have been stable over the last five years (see Table 5). The factors limiting the development of international groups and thus potential investments are of three types. The first factors are ‘environmental’ difficulties such as the inefficiency and lack of infrastructure (transports, logistics, etc.) as well as national and local regulations which often make the process of opening a new sales point too ‘bureaucratic’ and expensive. In distribution, large chains gain advantage from scale economies once critical mass is achieved, but in Italy regulations tend to place a brake on the process of internationalisation before this point is reached. Table 5: The Market Share of International Groups in Italy (% MGD) Groups

2004

2009

International groups

19.6

19.5

National/regional/local groups

80.4

80.5

MGD Total

100.0

100.0

Source: Authors’ elaborations on IRI – Information Resources data.

The second factor is that international groups, in order to standardise supply more efficiently, tend to export those sales point formats which are the most strongly consolidated in their own market. For French retailers, this type of store is the hypermarket, but hypermarkets have proven unsuitable for the Italian market. The third factor is the typical supermarket development model based on direct investment, with the acquisition of control capital of pre-existing chains and/or the opening of new selfowned sales points. The model is expensive in terms of initial investment, but it is based on the assumption that direct control over the market guarantees medium term opportunities for successfully repeating a formula which has proven successful in the home country. Currently the attempt to repeat the strategic and operational logic of the French domestic market is clashing with complex consumption models, strongly differentiated in the different local areas of Italy. The differentiated structure of competition too makes it less effective to apply standardized business logic. In general, the complexity of the Italian market leads to strong differentiation of retailer’s commercial performance. This variability in particular concerns the indicator of the sales level per square meter of sales space, and as Table 6 shows there is a big gap between average store productivity and productivity of the best chains.

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Table 6: Productivity of Sales in Retail Channels (Sales per sqm, EUR, 2009) Productivity (all retailers average)

Store Formats

Productivity (best retailers average)

Hypermarket

5,060

7,100

Supermarket

4,950

9,370

Convenience Store-Superette

6,050

10,300

MGD Average

4,995

8,160

Source: CERMES (2009).

The average market value oscillates at around EUR 5,000 per square meter in hypermarkets/ supermarkets and around EUR 6,000 per square meter in convenience stores, but for the best retailers or well-known chains, levels are much higher in all sales formats.

3.

Main Food Retailer Profiles

The main peculiarity of the Italian grocery trade is that it has the lowest level of market concentration in the EU, with the top five players, exclusively Italian and French retailers, capturing more than 50 percent of the FMCG market in MGD (Table 7). Table 7: Top 5 Italian Grocery Retailers (2010) Number of Stores

Total Sales Area (sqm)

Grocery Banner Sales (EUR Million)

Coop

1,348

1,535,818

11,423

15.5

Conad

2,518

1,042,403

6,608

11.2

Carrefour

1,608

1,338,836

6,469

9.8

Auchan

1,596

1,805,925

7,505

9.7

151

528,500

5,150

7.9

7,221

6,251,482

37,155

54.1

Top 5 Retailers

Esselunga Top 5 Total

Market Share of MGD (%)

Source: Authors’ elaborations on Planet Retail and IRI – Information Resources data (2010).

This is largely due to the importance of the buying groups and independent actors, which are more firmly rooted in the Italian market than anywhere else in Western Europe. Like cooperatives in other southern European countries, Coop and Conad are very strong, and there is no sign that their market positions are eroding. In order to strengthen their competitiveness against modern, mostly foreign-owned companies, a number of locals have looked for foreign partners with whom they can combine their activities in Italy. Partnerships include matches such as Leclerc/Conad and Carrefour/Gruppo GS. Italy continues to be marked by a clear North-South wealth division, with the North having higher income levels and consequently higher retail concentration. Italy continues to be a classic supermarket country, despite the fact that traditional retailing is in decline as everywhere in the EU. Many hypermarkets are underperforming. This section briefly describes the six main players in FMCG retailing in Italy: Auchan, Carrefour, Conad, Coop, Esselunga, and Selex.

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Auchan

Corporate Profile The French retailer Auchan has extensive expertise in the Italian market due to its former tieup with Rinascente. It has 16,000 employees, 75% of whom are shareholders. Auchan is now focusing on an aggressive pricing strategy in Italy, with the accent shifting from promotional to permanently low prices in its hypermarkets. As well as hosting substantial nonfood sections inside its hypermarkets, Auchan is also introducing Over The Counter (OTC) pharmaceuticals at discounts of up to 30%, mobile phone services with a local partner, Wind, jewellery and optician departments to its stores. Thanks to an agreement with Italcogim Energie, it is also diversifying its range to include sales of gas and electricity. In e-commerce, Auchan has introduced the AuchanDrive concept, whereby customers order products online and pick them up in five minutes at a dedicated outlet situated beside a hypermarket. The first online delivery outlet was introduced in Turin. The Auchan Group has also diversified with its fast food chain, Flunch. Formats Like Carrefour, Auchan has a strong focus on hypermarkets (54 stores) and supermarkets, with an extensive network of Sma and Simply Market supermarkets. Auchan is currently aiming to convert all Sma outlets to Simply Markets, a discount supermarket with an EDLP policy. This format has been exported to France, Spain and Poland. The Sma banner comprises the formats Punto Sma, (between 300 and 500 sqm), Sma (between 600 and 2,500 sqm), Sma Superstore (2,000 to 3,000 sqm) and Cityper (superstores of around 3,000 sqm). Private Label Strategy Auchan has built up a range of 4,000 Auchan-branded products in Italy, 95% of which are manufactured in the country and supplied by 366 companies. In the private label (PL) portfolio Auchan offers three main lines: standard (e.g.: Auchan, Sma Auchan, Simply), economy (e.g.: Budget Booster) and premium (e.g.: I sapori delle Regioni, Filiera controllata, Bio Sma Auchan). PL penetration is still fairly low. Loyalty Cards In March 2010, the group announced the launch of an Italian version of the Nectar programme in partnership with Groupe Aeroplan. Customers can now collect points at Auchanowned Simply Sma stores and 725 other franchises of Punto Sma, Simply, Ipersimply, Sma, Cityper and Auchan hypermarkets. The scheme is further discussed in Section 7. Auchan of-

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fers a private payment card, Auchan Mastercard Accord, operated by its fully-owned subsidiary Banque Accord Italia.

3.2.

Carrefour

Corporate Profile The Italian division of Carrefour is strongly focused on hypermarkets and supermarkets. Currently looking for a multi-format single brand strategy in Italy, Carrefour is rebranding its convenience stores GS as Carrefour Market, and the Dì Per Dì convenience stores are to be converted into Carrefour Express. In the past, Carrefour followed specific strategies for its three formats (hypermarket, supermarket and convenience stores), but since 2009, it has applied the same marketing policy to each format. Carrefour has put diversification into practice by introducing nonfood products and services. In 2005 it developed a full range of financial services (CSF, Carrefour Servizi Finanziari) where the main item is customized consumer credit. In June 2007, it launched a new virtual mobile operator in Italy, UNOMobile, which uses the Vodafone network. Since the liberalisation of pharmaceuticals sales in September 2006, some Carrefour stores have also sold OTC drugs in a special area under the supervision of qualified pharmacists. Formats Carrefour’s multi-format presence includes hypermarkets, supermarkets and cash & carries. Stores are mainly concentrated in the northern half of Italy. Carrefour runs about 20 cash & carry stores: DocksMarket and GrossIper. Private Label Strategy With the launch of Carrefour’s multi-format single brand strategy, 2,400 own-branded products have been regrouped under the Carrefour brand and are offered in all hypermarkets, supermarkets and neighbourhood stores. Product ranges are food (InForma health food and organic food), nonfood, clothing (Tex), a standard range (Carrefour), a premium range (First Line) and a value range. Loyalty Cards In 2008 Carrefour extended its SpesAmica card from the supermarket and neighbourhood networks to its entire Italian network, in order to consolidate its loyalty scheme. SpesAmica offers exclusive promotions and price reductions through Smile point collection. Carrefour shoppers can choose a more advanced loyalty card, Pass Card (in Carrefour hypermarkets) or

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Carta SpesAmica Pass: a loyalty card that functions as payment card at the same time. See also Section 7.

3.3.

Conad

Corporate Profile Conad is an Italian co-operative set up in Bologna in 1962 as a purchasing network for retailer co-operatives and independents. It operates through eight large co-operative buying groups and distribution centers: Nordiconad, Conad Centro Nord, Commercianti Indipendenti Associati, Conad del Tirreno, Pac2000A, Conad Adriatico, Sicilconad Mercurio and Conad Sicilia. In May 2001 Conad signed an alliance with Leclerc, which gave 60% control to Conad. The Conad National Consortium offers its members a range of services such as trade marketing studies, financial services, technical support, quality control and PL management. Conad has diversified its range with the introduction of pharmaceuticals, fuels, and optics. It also runs a fast food corner, Pastameal Points, in partnership with Barilla. On a European level, Conad is a buying alliance “Coopernic”, together with French Leclerc, Swiss Coop, and Belgian Colruyt. Formats The core business of Conad system are supermarkets. Conad runs E.Leclerc Conad Ipermercati hypermarkets, Conad supermarkets and neighbourhood stores, Margherita neighbourhood stores and a new concept of superdiscount (Todis). It is also currently testing a vending machine format, Shop 24. Private Label Strategy Conad has several different kinds of private labels. There is Conad il Biologico (organic pasta, jams, fruit juices, oil, rice, coffee, mozzarella, etc), Conad Kids (for children aged 6-10, based on healthy and balanced nutrition), Conad Percorso Qualità (fruit and vegetables, poultry, meat, fish produced according to Conad Quality Cycle guidelines), Sapori&Dintorni Conad (regional delicatessen food lines), Eco+ (value), and several others. It operates a ban on all Genetically Modified organisms (GM) and synthetic chemicals in Conad own labels. Loyalty Cards Its “Carta Insieme” loyalty card, available since 1998 and gradually being extended to all Conad outlets, is one of the most widely-distributed cards in the Italian retail network. There were over 5 million cardholders in August 2009 and it was used in 65% of store transactions.

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Coop

Corporate Profile The market leader in Italian MGD is Coop, running stores all over the country, with over 6 million members. Coop Italia is the food buying and marketing company for the entire Coop group, which consists of nine large co-operatives (Coop Adriatica, Coop Centro Italia, Coop Consumatori Nordest, Coop Estense, Coop Liguria, Coop Lombardia, Novacoop, Unicoop Firenze, Unicoop Tirreno). In addition to these there are 14 medium and about 105 small cooperatives. All the co-operatives belong to one of three associations responsible for coordination, representation and promotion: Centrale Adriatica, Consorzio NordOvest and Consorzio Tirrenico. In terms of ownership, it is a typically Italian hybrid group with a mixture of company-owned and associated independent stores. Quality of service, social commitment, protection of consumer interests and environmental safeguards are all important issues for Coop. Beside food, it is involved in a wide range of business activities, including financial services, mobile phones (Coop Voce, with Telecom Italia Mobile), consumer electronics, DIY (Brico Io), and OTC pharmaceuticals in dedicated corners with PL drugs (e.g.: “Coop acetylsalicylic acid and ascorbic acid”, at 40-50% lower than the average market price of aspirin). Like Esselunga, Coop has developed a self-service scanning system using special mobile readers as well as self-service checkouts. Formats Operations in Italy are strongly based on hypermarkets, supermarkets and neighborhood stores, which account for more than 95% of sales. The approximately 90 hypermarkets are mostly located in shopping centres. Coop also has over 300 discount stores, branded “Dico, The Italian discount”. Private Label Strategy The Coop private label range consist of more than 2,000 items: Coop (standard line, food and nonfood), Bio-Logici, Crescendo (baby articles), Eco-Logici (ecological private label products from the European Community), Essere (toiletries, health and cosmetic articles), Fior Fiore (local specialities), Senza Glutine (gluten-free products), Solidal (fair trade products), Soluzioni (ready-to-serve meals) and Smiling Euro, a value PL which is not immediately identified as a Coop label.

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Loyalty Cards Over 6 million membership cards Socio Coop are active. Members can take part in various initiatives, as well as collect points.

3.5.

Esselunga

Corporate Profile Founded in 1957, Esselunga is a private Italian company owned by its Chairman Bernardo Caprotti and his family through Supermarkets Italiani S.p.A. Key success factors are store location, product range, PL quality, competitive price policy and communication. Esselunga is a pure supermarket operator, but supports its bricks and mortar business with small scale on-line shopping. Formats Esselunga is specialised in superstore and supermarket format, and the 140 sales points are located in the Centre-North of Italy. Private Label Strategy Today, Esselunga offers PL brands in all price segments. Ranges include Esselunga (the first private label, launched at the end of the 1970s), Esselunga Bio, Eco Label (ecological products), Esselunga Top (premium PL), “I Pronti in Tavola” and “Fatti da noi” (ready to eat), Naturama (fresh food range), Fidel (value). Loyalty Cards Fidaty Card advantages are mainly in shopping and point collection. Over 90% of sales are made to consumers carrying the card. Esselunga also offers “Fìdaty Oro” cards and “CartaSi Fìdaty Oro plus”, credit cards which allow customers to pay for their shopping and collect points faster than the Fidaty Card transactions.

3.6.

Selex

Corporate Profile Selex is one of the biggest associations of independent retailers in the Italian grocery trade, with annual sales of over EUR 8.2 billion in 2008. Consisting of 24 retailer and wholesaler members over the whole country, its key business areas include international buying for group

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members, product range expansion, logistics optimisation, national marketing activities and private label purchase. Formats In 2009, Selex ran 3,247 outlets with a total sales area of 1,944,518 sqm including almost all store types: hypermarkets (IperFamila and Famila), superstores, large and medium supermarkets, neighbourhood stores (A&O), soft and hard discount stores (Sú) as well as cash & carry outlets. Private Label Strategy Private label strategy focuses on product segmentation, with the aim of building a complete range in terms of choice and price. Selex offers the following PLs: Premium brand (Bio Selex, I prodotti della natura, Selex, Selex Più), its own retail brand (Selex), brands with imaginative names (Conviene, Vale, Jollina, Atmosfera e Benessere, Bontà del pasticcere), Cash & carry PL (Su, Vanto). There are also PLs for hotels-restaurants-catering. Loyalty Cards In March 2009, Selex had approximately 3.5 million active loyalty card holders. It was thus able to optimise planning of promotions and operate effective Customer Relationship Management (CRM), and collaborate profitably with manufacturers. Selex offers the following loyalty cards: Selex Card, A&O, Pan, Famila and Club Famila, which is a loyalty and credit card, run in co-operation with BankAmericard. During the 1980s, buying alliances among buying groups and independent retailers (also known in Italy as “Supercentrals”) were established under a joint head office in order to match the buying power and to combine purchasing, logistics and service activities. Probably, the main difference between Supercentrals in Italy and in other European countries is the high rate of mobility among their members, which gives rise to continuous new entries and disappearances of Supercentrals (Fornari 2009). This is due to the fact that they are usually set up as purchasing centres without any strategic marketing orientation. The following Supercentrals are currently active in Italy: Centrale Italiana (Coop Italia, Sigma, Despar Sevizi, Il Gigante), ESD (Selex and Acqua e Sapone), SICON (Conad, Gruppo Rewe, Interdis), CSA (Carrefour, Sun and Agorà), and Sisa-Finiper-Coralis.

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Clustering Local Italian Markets

There are several reasons for the prevalence of multi-channel distribution in Italy, as discussed in Section 2. They include: - Geography and demography. The population is widely dispersed all over the country, and there are few high density metropolitan agglomerates. - Local tradition and habits, which reduce the advantages of format standardisation. - High number of small family companies and family-owned stores, which may belong to voluntary and co-operative chains. - National and local urban planning regulations which protect historic town centres and limit the growth of large retail outlets. So there is a low level of standardisation in types of outlet, and the multi-channel nature of retail implies affiliation policies and development by mergers and acquisition. So far, most Italian grocery stores are small in size (under 400 sqm); but big stores have a large market share (see Table 8).[4] In fact, for stores larger than 1,000 sqm, market share is almost 50% of total. This figure is lower than the European average but is consistent with the total number of stores per inhabitant, which is about 2.8 stores per 1,000 inhabitants compared with 0.6 in France and the UK, and 0.8 in Germany. Table 8: Numbers and Market Share of Modern Store Formats by Size (sqm) Size - Square Metres

Number of Stores

Market Share (%)

400-800

4,930

27.0

800-1,200

1,579

17.6

1,200-1,600

859

13.6

1,600-2,500

588

14.7

2,500-4,500

352

18.0

Over 4,500

120

9.1

8,428

100.0

Total

Source: Authors’ elaborations based on data from Nielsen (2009).

Of course, the multichannel situation has significant consequences on efficiency and effectiveness. First, it weakens supply chain efficiency, secondly, given that product ranges are many and various, it influences bargaining power and vertical relationships. But in spite of all this, sales figures per square metre in Italy are not excessively low compared to European ones; annual supermarket turnover per sqm reaches an average of EUR 5,000. The figures are clearly influenced by local profiles. Productivity is lowest in rural areas and is markedly influenced by the asymmetric national income distribution. In order to map local differences for the development of retail strategy, it is useful to perform an in-depth geo-marketing analysis.

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The following results were obtained through research recently conducted by Selex, a national retail firm, in collaboration with Nielsen and the University of Parma.[5] The research consisted of three phases: a cluster analysis of 8,424 local store attraction areas; a cross analysis of different formats within the clusters; an audit of product ranges sold within the different clusters. - Cluster 1 (Residential Urban) very high ‘house density’ (inhabitants per sqm), high average age, high education level, high service employment and low presence of big modern stores. This type of area is widely spread all over Italy and its presence in the South of Italy shows that the geographical distribution of national incomes cannot be considered the main variable of local differences. Store profile in a Residential Urban area is similar in the North and South of Italy. Usually these areas encourage the development of convenience stores selling a wide range of products with a high component of service (time and use). - Cluster 2 (Commercial Roads) very high density of shops (sqm of modern distribution per 1,000 people), very low housing density; average income and education level, average employment and immigration levels. Commercial roads are more common in the North of Italy, but are also found in the Centre and the South. They feature big store formats with very wide product ranges, from grocery to nonfood. - Cluster 3 (Industrial Countryside) very high percentage of people employed in manufacturing and high presence of immigrants with low education levels. These are countryside areas, so housing and store density is low. The range of products is various and features local products and a wide range of nonfood. This cluster is not present in the South of Italy. - Cluster 4 (Tourism) very high presence of hotel and restaurants. Seasonal activity is frequent and the range of products needs to vary during the year. Nonfood and fresh products are very well represented. - Cluster 5 (Rural Small Villages) shows above average employment in agriculture but a very low overall employment rate. The education level is almost average but incomes are very low, immigration is low, store and house density is below average. This cluster is not present in the North of Italy. - Cluster 6 (Low Income Countryside) lowest rates of employment, education and income. Modern retailers are not common. The range of products includes many local fresh goods. This cluster is not present in the North of Italy. The most significant finding is that the distinction between the North and South of Italy holds true depending on the cluster profile one considers: in fact, clusters 1 (Residential Urban), 2 (Commercial Roads) and 4 (Tourism) are present both in the North and in the South; cluster 3 (Industrial Countryside) is present only in the North and cluster 5 (Rural Small Village) and 6 (Low income countryside) are typical of the South. As it is widely recognised, the local economic and social structure can influence the presence of different store formats and consequently the range of products sold. So, for a modern retailer, geo-marketing analysis opens up

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new opportunities for development strategies and can inform the micro-tuning of local investment.

5.

Nonfood Retailing

Highly specialised small stores continue to play a central role in nonfood sectors, although market share figures show the gradual growth of modern distribution at the expense of traditional shops. Modern distribution has in fact progressively eroded the market share of traditional distribution. Recent figures show that the market-share of traditional stores declined from 66.6% to 46.8% over the 12 years up to 2008 (see Table 9). The erosion of market share of traditional channels is less striking when considering that other channels such as hawkers, open air markets, mail order, door to door, online etc. increased market share by 1.7% share in the same period. Modern distribution (specialised and mass merchandisers) increased over the same period from a market share of 20.1% to 38.2% (see Table 10). It is mainly the specialised chains which account for the growth of modern distribution. Table 9: Evolution of Nonfood Channels (Market Share in %) Nonfood Channel

1996

2004

2005

2006

2007

2008

Hypermarkets and supermarkets

4.1

7.4

7.6

7.6

7.5

7.5

Mass merchandisers

2.5

2.1

2.1

2.1

2.1

2.2

Specialised chains

13.5

22.4

23.4

25.5

26.7

28.5

Traditional trade Other channels (hawkers, door to door, internet, etc.) Total nonfood

66.6

53.9

52.5

50.3

49.1

46.8

13.3

14.2

14.4

14.5

14.6

15.0

100.0

100.0

100.0

100.0

100.0

100.0

Source: Federdistribuzione (2009).

Data on the evolution of the market share of modern trade comes from figures from the Observatory of Nonfood Retailing provided by Indicod-ECR. We believe the Indicod-ECR definition of specialised chains to be more coherent with our aims than other definitions, used elsewhere, which consider any outlet over 1,500 sqm as a specialised store. In fact, modern chain stores even smaller than 1,500 sqm with a specialised assortment develop marketing policies, and producers gradually lose control of the levers of retail mix, particularly price. Table 10: Evolution of Nonfood Channels (Market Share in %) Nonfood Channel

1996

2004

2005

2006

2007

2008

Modern trade

20.1

31.9

33.1

35.2

36.3

38.2

Traditional trade

79.9

68.1

66.9

64.8

63.7

61.8

Total nonfood

100.0

100.0

100.0

100.0

100.0

100.0

Source: Federdistribuzione (2009).

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It is thus crucial to analyse the market share of modern distribution (specialised stores and mass merchandisers), and its evolution in recent years in different sectors. Table 11 shows that the dynamics of growth vary a lot from one sector to another. Traditional retail stores continue to hold a dominant market share in many sectors, but modern retail in Italy has gained market share similar to major European countries in sectors such as consumer electronics (goods appliances, small appliances, telephones) and Edutainment goods, where it accounts for over 50% market share. It is thus very likely that the purchase of many nonfood products will be ‘banalised’, and this process is of great potential for the modernisation process. Table 11: The Market Share of Modern Distribution in the Main Nonfood Sectors (Market Share in %) Nonfood Sectors

2007

2008

Clothing and footwear

44.3

46.6

Consumer electronics

77.1

76.1

Appliances

46.1

47.1

Small electronics

88.8

87.2

Hardware

31.2

39.7

Phone & mobile devices

53.9

55.9

Furniture and furnishings

22.6

22.3

Do-it-yourself

33.7

35.4

Sports equipment

39.6

40.7

Edutainment

61.1

63.8

Source: Indicod-ECR (2009).

In the evolutionary dynamics of modern distribution, there are differences between specialised stores and mass merchandisers (hypermarkets and supermarkets). In all sectors, hypermarkets and supermarkets still play a marginal role in terms of market share and suffer in terms of growth. But as Table 11 shows, growth in the mass merchandiser channel is lower than growth in specialised chains, and in some sectors is even showing a negative trend. The low market share of hypermarkets and supermarkets in many nonfood sectors is partly due to the structural crisis that has hit the hypermarket format, also mentioned in Sections 2 and 3. In other words, hypermarkets and supermarkets in Italy are suffering the effects of the crisis in the format as well as restrictive legislation. Of course, the relative weights of mass merchandisers, hypermarkets and supermarkets are different from sector to sector. Purchase of some shopping goods is now completely banalised and modern distribution has gained market shares close to 30%, which is however far below European benchmark levels. The modernisation of nonfood retailing in Italy is thus being mainly driven by the dynamics of specialised chains (see Table 12).

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Table 12: The Market Share of Modern Distribution in the Main Nonfood Sectors (Market Share in %) Nonfood Sectors

2002

2006

2008

Clothing and footwear

20.4

29.1

35.4

2008 vs. 2002 +15.0

Consumer electronics

27.2

38.5

43.3

+16.1

Electronics

49.2

59.7

61.8

+12.6

Appliances

27.8

34.2

39.9

+12.1

Small electronics

46.6

54.6

58.0

+11.4

Hardware

9.1

21.0

29.5

+20.4

Digital camera & photography

31.1

50.1

53.5

+22.4

Phone & mobile devices

28.5

31.0

32.1

+3.6

Multimedia storage

33.8

43.4

43.7

+9.9

Furniture and furnishings

12.7

14.7

15.7

+3.0

Do-It-Yourself

12.3

25.1

25.7

+13.4

Sports equipment

+7.3

26.9*

32.8

34.2

Perfumery

51.6

45.7

44.9

-6.7

Edutainment

33.2

40.6

44.4

+11.2

1

Optical

18.2

22.9

30.1

+11.9

Textile

13.0

19.7

21.9

+8.9

Toys

34.4

35.5

34.5

+0.1

1

Note: Specialised chains include small specialised stores. Source: Indicod-ECR (2009).

The central role played by specialised chains in recent years is explained by their marketing orientation, specialised range of assortment and store format innovation. Their aggressive pricing policy has also put a brake on further growth of hypermarkets and supermarkets in nonfood sectors. Chain stores have recorded growth rates above 10% in many sectors since 2002. Despite this growth however, market share remains below 50%. Clearly there is still significant potential for modernisation of the distribution system in Italy. Many shopping goods can now be treated as FMCGs and a gradual modernisation of nonfood retailing is predicted in Italy for the near future.

6.

Private Label Development

The level of PL development in a retail market is a key indicator of the level of modernisation. In industrialised countries, PLs are a driver of growth strategies for the best performing retailers (Burt 2000; Ailawadi/Keller 2004). In the FMCG sector, store brands are widely developed all over the world, and the most advanced area is Europe, where the PL accounts for about 20% of total MGD turnover. But as a result of differences in the structure of demand and retail competition, the Italian grocery market is lagging behind. The market structure is relatively behind, due to the survival of many traditional trade firms, low concentration in market shares and the low presence of international players (Mc Goldrick 1984; Lugli 2009)

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(see Tables 1 and 2). In addition, the key role played by buying groups also limits opportunities for retail branding. In fact, the plurality of store banners and deficiencies in coordination between national headquarters and individual stores tend to reduce branding strategies effectiveness (Lugli 1993; Pellegrini 1994). Finally, Italian consumers traditionally have great trust in leading manufacturer brands. As a result, they tend to consider private labels as a second best choice, with a lower positioning in product quality (Ravazzoni 1995; Richardson 1997; Fabris 2004). Despite these significant structural limitations, store brand sales have been very dynamic and their growth rate has been positive during the last 20 years. Market share has doubled since the early 1990s (7%) and today stands at 13.6%. In particular, the annual growth rate in sales was double digit in 2008/2009 and PL now has a total turnover of more than EUR 5.5 billion, gaining 1.5 points of market share since 2007 (see Table 13). Table 13: PL Growth in Italy (Hypermarkets + Supermarkets, FMCG Categories) Year

Turnover (Million €)

CAGR (%)

Market Share (%)

2005

4,057

+4.3

11.8

2006

4,219

+4.0

11.9

2007

4,409

+4.5

12.1

2008

4,985

+13.1

12.7

2009

5,525

+10.8

13.6

Source: IRI – Information Resources (2005-2009).

This data is even more significant if compared to data for other brands. PL development during 2009 was worth about EUR 640 million, more than 40% of total grocery sales growth. The increase in private label market share, concerning 241 product categories out of 320, was homogenous within retailer assortments. It was achieved especially against follower manufacturer brands, which lost more than 6 market share points in 2000-2009. But for the first time, 2009 saw even leading manufacturer brands suffering a reduction in their relative market positioning. This appears to be the direct consequence of PL improvements in real and perceived product quality, and shows that consumers have started to perceive PL brands as credible substitutes for quality manufacturer brands. PL market share in fact tends to be growing in product categories where the following conditions hold (Fornari 2009): - Pricing differentials with leading manufacturer brands are lower than 20%. This is often the case where quality up-grade of products allows retailers to raise selling prices. This evidence conflicts with the traditional theoretical finding that the low PL market share in Italy was linked to low price competitiveness (Cristini 1992). - Concentration in manufacturer brand sales is high. This has two implications. The first is that PLs need to be considered as direct competitors by leading manufacturer brands. The second is that even in monopoly/oligopoly markets, store brands can succeed in overcoming competitive barriers and obtain adequate profit levels (Baden Fuller 1980; Lugli 2003).

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- Annual sales growth rates are double digit. PLs appear to be increasingly capable of exploiting opportunities presented by emerging and dynamic markets. This represents a new trend, because in the past, store brands were found to have difficulty in managing product innovation (Ravazzoni 1995; Berges-Sennou 2004). The strong growth rate of PL appears to be linked to an increase in branding investments by the main Italian grocery retailers. Over the past two decades, few of them adopted clear branding strategy. But a structural decrease in margins and a big increase in shopper mobility between stores revolutionised this attitude and recently even buying groups and smaller chains (both regional and multiregional) have started to consider branding a key driver in differentiation and raising store loyalty levels (Corstjens/Lal 2000). There have thus been several important changes in PL management practices. First, the number of product categories with a presence of store brand products has increased sharply. In the early 2000s these product lines were found in few categories, mainly those characterised by maturity in purchasing trends and stability in intra-brand competition dynamics. But by 2009, market data showed that although there is great variability in retailer management of PL ranges, nearly 100% of FMCG product categories presented at least one PL stock-keeping unit (SKU). This is confirmed by the number of new PL products launched, which was 4,250 in 2009, involving 193 categories out of 320. The average number of PL SKUs for each store was 1,103, up by 7.5% from 2008. A second important change in store brand management is the emergence of segmentation. This new market trend, which has occurred for several years in other European countries, seems to be related to the retailers’ aim of simultaneously satisfying numerous consumer targets and/or numerous consumer needs (Dawson 2004; Cristini 2006; Planet Retail 2009). The multi-branding strategy is based on a ‘house of brands’ approach which implies the development of different lines, each characterised by specific brand name, brand image and brand identity (Aaker 1991). In best practice internationally, PLs are usually segmented into three tiers, corresponding to the three principal pricing/quality levels in retailer assortments. Ranges thus include an entry level line (with low quality and pricing standards and generic or phantom branding, directly comparable to discount products); a standard level line (with medium quality and pricing standards close to leading manufacturer brands, and store banner branding) and a premium level line (with high quality/pricing standards, directly comparable to specialty food stores, and sub or phantom branding). The three-tiered strategy is fairly recent in Italy, and in latest years there has been significant growth in sales of both entry level and premium lines. In 2009 standard level lines accounted for more than 85% of total PL turnover, and market shares of premium and economy lines reached respectively 3.2 and 5.8% (see Table 14).

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Table 14: Growth of Different Private Label Lines (Hypermarkets + Supermarkets, FMCG Categories) 2006 Private Label Lines

Turnover (EUR Million)

2009 Share of Total (%)

Turnover (EUR Million)

Share of Total (%)

Premium

63

1.5

177

3.2

Standard

3,548

84.1

4,713

85.3

Economy

232

5.5

320

5.8

Others (organic, etc.)

376

8.9

315

5.7

4,219

100.0

5,525

100.0

Total private label

Source: IRI – Information Resources (2005-2010).

Focusing on only those product categories where PL is present (68% for entry level lines and 35% for premium lines), the figures are even more significant. In these product categories, these types of line gained market share 12.0% for entry level and 14.5% for premium lines. This shows that both lines have enormous potential for growth and extending their range. The third recent trend in Italian store brand strategies is the huge growth in investment in advertising to support PL positioning. This investment is increasingly made in mass media exposure and packaging. During last two years, the main Italian retailers have invested large amounts in improving technical aspects and restyling graphics of PL products. In the past, packaging strategies had a ‘me too’ orientation tending to imitate leading manufacturer brands. But leader brands vary between different product categories, and the ‘me too’ approach was thus not appropriate for developing a homogeneous brand image over the whole assortment. Following international best practice, Italian retailers have recently adopted a more independent approach to PL packaging, building a brand image for each line valid for all categories of presence with recurrent colours, lettering, images, etc. (Cristini et al. 2007). The last important change in PL is that retailers have become increasingly oriented to specific price promotion activities. Many studies showed that pricing discounts on private label products were not only ineffective, but also dangerous, in economic terms, for retailers (Lugli 1993). It was argued that Hi-Lo pricing strategies on PL were a marketing mistake for three reasons. The first was that the demand curve for this type of product is usually indifferent to price cuts, which consequently generate limited effects in term of incremental sales volumes. The second reason was that purchase trade from co-packers are based on net-net price, with no contribution for promotion. Promotion of PL thus requires significant investment from the retailer. The third reason was that price promotion reduces store profit levels, which conflicts with the original purpose of PL, which was to achieve better margins. But in the period 20062009 the share of sales of PL on promotion in Italian MGD stores increased from 16.8 to 20.7%, which was the consequence of a big reduction in the previous gap compared to manufacturer brands in price promotion effectiveness. This change in orientation to price promo-

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tion is due to several conditions. First of all, there are increasing numbers of categories where PL has become market share leader. This has come about where the PL has a strong brand identity and consumers put them on their ‘shopping list’ in the same way as leading brands. In this situation, price cuts on PL lines could be effective for store acquisition strategies. Secondly, price promotion can help to stimulate purchasing trials of PL in new categories. Temporary price decrease is thus a marketing investment, rather than a reduction in profit levels. Finally, in product categories with intense intra-brand competition, PLs have to compete in order to survive. The rules of the game may include intense and frequent price cuts, and all brands, both manufacturer and retailer, must be involved in price competition. All these changes in store brand strategies have modified Italian consumer approach to PL purchasing. In fact, most recent shopping behaviour studies on FMCG have shown significant improvements in consumer perceptions of PL products. Italian consumers tend to appreciate their lower prices and quality today more than in the past. This increasingly positive attitude has given PL a high level of shopping penetration (more than 70% of households) and a high level of purchasing frequency (10 times a year average per household). In 2009 more than 45% of households increased the volume of PL purchased. Growth in consumer trust of PL means that consumers are increasingly aware of changes on the PL market. In fact, the majority of consumers correctly perceived an increase in price cuts on PLs, a reduction in product quality gap between store brands and leading manufacturer brands, an increase in the number of PL ranges and shelf space. They appear overall to be accustomed to PL product positioning, which is broadly similar among retailers. In fact in 2009 nearly 60% of Italian consumers purchased PL products in other grocery stores as well as their favourite. It therefore appears that Italian consumers today are associating lower risk and at the same time good value for money proposition with PL purchase (Gonzales Mieres et al. 2006; Fornari 2007).

7.

Loyalty programmes and Clubs – the Strategies of Italian Retailers

The Observatory on Loyalty Cards at the University of Parma (www.partnership4loyalty.com) has been monitoring retail loyalty marketing activities across Europe since 1998, with a special focus on Italian grocery retailing. In this section the current status of retail loyalty marketing activity in Italy is outlined and put in perspective with its recent history and the European scenario. Italian consumers have been familiar with loyalty marketing for more than thirty years: Bollini Végé are in fact as old as UK Greenshield Stamps. It was only in the early 1990s, however, that retailers started substituting paper stamps with plastic cards (Ziliani 2008). In the early years of loyalty cards, around 1993-1995, there was typically one pioneer retailer in each country: in the UK it was Tesco, in Italy it was Esselunga, and others displayed a wait-

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and-see attitude. It took approximately five years for an imitation phase to follow. As early as 2000, all 20 top retailers in Italy offered a loyalty card and programme, and penetration among consumers increased rapidly. Today 86% of supermarket shoppers in the country use a loyalty card, and each household owns an average of 2.5 cards (compared with 3.3 cards in the USA and 2.8 in the UK; figures from Planet Retail), while 35% of consumers have three or more cards, according to Nielsen Consumer Panel. In 2009, as shown in Table 15, retail loyalty programmes counted their customers in millions and Coop, Conad and Esselunga customer databases rivalled major European schemes in size. The figures show the number of families using retailer cards for shopping at least once in the period from August 2008 – August 2009 (Figures courtesy of Nielsen). The percentage of sales going through the cards averages 64%, reaching 94% in Esselunga and being as low as 35% in other cases. Table 15: Italian Households Shopping with a Retailer’s Loyalty Card (2008-2009 in Thousand) 6,736 Conad

5,043

Esselunga

4,261

GS

3,590

Selex

3,371

Auchan

2,207

Carrefour

2,112

Sma

2,083

Iper

2,076

Gruppo Pam

2,076

Interdis

1,860

Bennet

1,707

Despar Servizi

1,691

Rewe

1,525

Sisa

1,411

Panorama

884

Crai

545

Source: Nielsen Consumer Panel (2009) – courtesy of Nielsen Company.

‘Pure’ loyalty cards [6] are most common, providing cardholders with the following benefits: - reduced prices and discounts (100% of cases) - point program (100%) - targeted promotions based on customer shopping habits (83%). Payment cards (debit and credit cards, linked to major circuits such as Visa), despite an early, maybe too early, start in the mid 1980s, when customers were still unfamiliar with plastic money, are still infrequent, with only 6% of surveyed card programmes offering debit or

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credit functions. In this area, a recent significant move was the launch of the Lidl Card, the first discount loyalty card in the country, a trial run by the German retailer Lidl with a view to possible international extension. In comparison with the European scenario, Italian loyalty programmes differ for the choice of point redemption options offered, in that they are heavily tilted in favour of gift catalogues (90% compared to 21% across Europe). In other countries, points are most commonly redeemed for discounts on specific products or total grocery bill. But in Italian homes, there are glossy, full-color coffee table gift catalogues offering an average of 90 items from tableware to bed linen, electronics and sports equipment, and an increasing array of vouchers for weekend breaks and other leisure options. In an attempt to be more attractive to customers, loyalty programmes today boast point accrual and redemption partners, the most common being petrol stations, insurance companies, utilities and other services. New programmes are no longer born ‘pure’ like their predecessors ten years ago, but appear in various network forms. The ‘coalition’ model, well known in Europe thanks to the success of Nectar in the UK and Payback in Germany, has only very recently appeared, with major retail group Auchan launching the “Nectar Italia” loyalty scheme at the time of writing of this article. Foreign business models are in fact attempting to colonise the Italian loyalty arena: first came Tesco’s loyalty think tank, DunnHumby, which clenched a deal with Gruppo Pam for the introduction of microtargeting expertise and retail intelligence systems; and today Auchan’s agreement is with the owner of the U.K. Nectar scheme Groupe Aeroplan (cp. Section 3). The aim is to distribute five million cards within a year. All these moves demonstrate that Italian retailers are paying more attention than ever before to their loyalty strategies, striving for differentiation and a tangible return on investment. In Italy, loyalty schemes cost an average 0.7% of turnover (in a 0.4-1% range), more than in France, where the figure is 0.5%, according to industry publication LSA, and more than in other countries. According to our survey of the top 20 companies, loyalty investments have been nibbling at the marketing/advertising budget for some time, mainly at the expense of ‘non loyalty’ advertising and communication activities. In Table 16 the retail advertising/communication budget is broken down into three categories, based on an emerging classification in the industry: “non loyalty mass marketing” – comprising mass TV/press/outdoor advertising, retail circulars and the like; “loyalty mass marketing” – related to programme costs such as catalogue printing, cost of rewards, plastic cards and other materials [7]; and “loyalty micromarketing”, the most innovative part of the loyalty game, where points/discounts are awarded to selected customers/customer groups based on behavioural segmentation enabled by insight from loyalty card usage gathered in retailers’ databases.

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Table 16: Breaking Down Retail Communication Investment Retail Communication Investments

Percentage

Non-loyalty mass marketing

60.0

Loyalty mass marketing

32.0

Loyalty micromarketing

8.0

Total investments

100.0

Source: Observatory on Loyalty Cards at the University of Parma (Survey 2009).

Loyalty marketing accounts for 40% of the marketing budget, of which 32% is scooped up by general catalogue/programme communication and 8% is invested in targeted activities. It is worth noting that at some retailers, micromarketing accounts for as much as 30% of the budget, signalling that a shift is taking place from mass marketing by retailers to a more customer-centric approach. Necessary to targeted marketing is the ability to derive insight from customer data: a skill highly praised by most, but mastered by a few, according to our findings. But Italian retailers are gradually starting to use customer data and derived knowledge, and following the same road taken by Europe’s ‘best in class’, as recorded in a 2004 study by Cuthbertson and Laine of Oxford University. They found that applications of customer data in retail companies included: - assessment of loyalty programme performance, in terms of customer participation, as a basis for programme improvement (loyalty mass marketing decisions) - location analysis and new store opening decisions - customer acquisition and reactivation by means of direct communication - aggregated customer base analysis. Table 17 shows that the same areas of customer data analysis, now consolidated, are today receiving most attention from Italian retailers. Table 17: Use of Customer Data by Italian Retailers Use of Customer Data

Percentage

Loyalty programme management

50.0

Customer base analysis

44.0

Targeted promotions

32.0

New business opportunities

25.0

Range/category management

13.0

Source: Observatory on Loyalty Cards at the University of Parma (Survey 2009).

But only a handful of retailers can as yet be considered masters of customer analysis (22%): the majority have focussed on a single area of application (62%), and laggards have not yet tackled the subject (16%). One good reason for retailers to use data is to get manufacturers involved: suppliers are willing to pay to reach targeted audiences with coupons and product offers, and show interest in co-operating on new product launch evaluation and category man-

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agement. Carrefour is pioneering the outsourcing of such ‘vertical’ co-operation with manufacturers to data analysis bureau Crea. Given the successful experience of Tesco with the same model, and the unquestionable difficulties of going it alone and internally, more retailers will be tempted to adopt this model in the future. Point-based programmes and the ubiquitous gift catalogues may be the most conspicuous loyalty tools used by retailers but they are by no means the one and only. Over the years other forms of continuity promotions have been used and, most notably, a whole range of media for direct communication with customers. Table 18 compares the 2009 situation with findings of a similar survey of 2002. Table 18: Retailers’ Media of Choice for Communication with Customer Base Media

2002

2009

Website

23

94

Direct mailing

77

82

Till receipt printing

18

82

E-mailing

23

50

Customer magazine

45

38

SMS texting

14

35

In-store kiosks

23

33

Self scanning

0

33

Interactive voice response

5

13

Telemarketing

0

7

Source: Observatory on Loyalty Cards at the University of Parma (Surveys 2002 and 2009).

The diversity of media options has increased enormously, and today retailers are keenly pursuing digital channels that allow for more frequent, affordable and personalised communication with 25 million regular Internet users and 50 million cell phone users in the country. There is the potential for closer continuous and ubiquitous contact between consumers and their favourite retailers, and it is up to retailers to show what they have learned from listening to their card-bearing customers and use the channels of communication meaningfully.

8.

New Trends in Shopping Behaviour and Consequences for the Retail Landscape

Marketing management studies tend to focus on consumer behaviour rather than shopping behaviour analysis. But the retail revolution, especially in the FMCG sector, has modified this approach and brought the need to investigate consumer attitude toward stores as well as products/brands..[8] New trends in shopping behaviour by Italian households need to be analysed as they have implications for manufacturers’ and retailers’ marketing strategies.

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The first important trend is multi-channel shopping, which is the tendency to visit many different kinds of stores in order to purchase the same kind of product (Fornari 2009). This phenomenon tends to be more prevalent for commodities than for shopping and specialty products. Differences in shopping behaviour for these two kinds of goods are closely connected to differences in service needs. For commodities, service needs are low because consumers are used to self-service stores and have matured frequent shopping experience, so that they tend to consider almost all different brands as direct substitutes. This justifies the tendency to visit different kinds of stores, both specialised and mass merchandisers, without any distinction. For shopping and specialty goods, however, service needs tend to be higher because purchase occasions are fewer, and consumer expertise consequently lower, and the product worth is much higher. Consumers thus prefer specialised stores to purchase shopping/specialty products because more personal shopping advice can be given. In the FMCG sector, almost all products are commodities, so more and more consumers tend to have a multi-channel shopping approach. In fact in 2009, 26.5% of Italian consumers visited only one favourite store for grocery shopping expeditions. But almost 30% regularly visited four or more different stores (supermarkets, hypermarkets, convenience stores, discounts, etc.) according to Nielsen Consumer Panel. This new attitude towards grocery stores has important consequences for store competition. In particular, it leads to an extension of the frontiers of competition, from intratype/intra-format to inter-type/inter-format (Lugli 2004).[9] The second significant trend in shopping behaviour is the reduction of brand loyalty. A shopping expedition for commodities is widely perceived as a necessary activity, strongly influenced by household purchasing power and not very gratifying. So, in general, consumer attitudes to shopping for commodities tend to be very rational and impersonal with regard both to stores and to brands. This implies a widespread consumer tendency to consider all manufacturer and store brands as equal. But decreasing in brand loyalty levels does not necessarily imply lower levels of brand sensibility. Recent surveys of shopping behaviour showed that consumers tend to chose products by selecting from a basket of two or three favourite brands considered as equal, rather than always searching for the same brand (Fabris 2008). This trend obviously generates an increase in store loyalty against brand loyalty, and if just one of the two or three favourite brands is absent, over 70% of Italian shoppers tend to purchase another one of their usual brands from the same store, rather than waiting for the previous brand to arrive or changing store in order to find it (Fornari et al 2008). The third change in shopping behaviour is purchase polarization on the main three pricing levels in retailer assortments (entry level, mainstream level, premium level). Italian consumers are showing a declining need for range variety at modern grocery stores, which has however increased during recent years. But shopping behaviour tends to be increasingly differentiated. In fact, shoppers’ requirements and their purchasing availability tend to vary a lot for

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different product categories and/or for different shopping expeditions. This has generated a gradual purchase concentration on a limited range of brands, mainly leading manufacturer brands and PL positioned in the mainstream pricing level [10], and at the same time an increase in purchases of both entry level products (especially for basics) and premium level products (especially in high value added categories) (see Table 19). Table 19: Purchase Polarisation on Pricing Levels (Hypermarkets + Supermarkets, FMCG Categories, 2009) Pricing Levels

Turnover Share (%)

CAGR (%)

Premium

17.9

+8.4

Mainstream

77.5

+2.3

4.6

+1.7

100.0

+3.2

Entry level Total FMCG

Source: IRI – Information Resources.

Development in premium level products sales appears to be closely linked to the emerging segmentation of shopping behaviours in the quality food area. This in turn is a result of the spread of new consumer trends like healthy living, rediscovery of past food traditions, environmentalism, ethical shopping, etc. Consolidation of these needs allows retailers to enhance their assortment quality image through offering selected top level ranges of both manufacturer brands and PL. It also increases the uniqueness of retailer’s assortment; the wider the premium assortment, the less intense price competition. The fourth trend in shopping behaviour is a new approach towards retailer pricing policies. Several empirical studies show that Italian consumers tend to have an increasingly speculative attitude towards price promotions, and buy discounted products only, which lowers the crosscategory purchasing effects of price cuts (Grandi 2008). This attitude could well be linked to the rising perception of the weaknesses of price promotions. In fact, significant shares of consumers seem to have understood the ‘portfolio-mix’ management principle followed by retailers; in other words they are aware that price cuts on certain products and brands correspond to price increases on others. And many shoppers have realised that price promotion often leads to the purchase of extra volumes of products, and that only price cuts on leading manufacturer brands and/or fresh foods are really effective. Increasing awareness of retailer pricing strategies and techniques are leading consumers to refine their search for ‘value for money’. There is also a close relationship between the tendency to pay premium prices for added value perceived in a single product/brand. Readiness to pay premium prices is higher when perceived value of products/brands increases, and vice versa. The search for ‘value for money’ is leading consumers to a more rational approach in evaluating both baseline and promotional retailer pricing policies, especially when it is hard to compare different products/brands benefits and advantages objectively.

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Finally, the fifth emerging trend in shopping behaviour is change in service needs. Recent sales dynamics in FMCG in Italy have shown that shopping advice offered by supermarket salespeople has become less important than practical services incorporated in products. This tendency is confirmed, for instance, by an increase in ready meal sales, because these products reduce time and effort in cooking and preparation at home. Furthermore, for fresh foods there has been a decrease in sales from personnel-assisted shelves and an increase in sales from self-service shelves, even though these are characterised by higher average prices. This trend appears to be closely linked to the increasing demand for time-saving products, that allow consumers to skip queues [11], and for functional products. Modern packaging techniques give manufacturers the opportunity to extend shelf-life of products and avoid rejects. New trends emerging in demand will strongly influence both retail landscape and store formats future dynamics. In general, the reduction of personal service needs will drive further development of modern distribution (versus traditional distribution [12]) and an increase in market concentration levels. Nevertheless, in the context of modern distribution, buying groups fit specific shopper needs in different areas (regional food products and brands, local pricing sensibility, etc.) better than chains (see Table 4): this is also proved by the fact that in 2009 international groups (such as Carrefour and Auchan) abandoned the southern regions of Italy (where buying groups are stronger), selling their outlets to local firms and re-focusing their business on the northern regions.[13] Strongly related to these evidences, the Supermarket is going to confirm and strengthen its leadership against others store formats.[14] On the contrary, the rise in consumers’ average age, the consolidation of a ‘value for money’ approach to shopping and the tendency to buy only grocery products (especially fresh foods) in self service stores [15] are reducing development perspectives for Hypermarket and Discount stores. In fact, new opening plans by major retailers are focusing on small/medium size food stores and multi-channel strategies are being replaced by single-channel ones (Fornari 2009).

Notes [1]

This paper is the result of team work by the seven authors. Nevertheless, Part 1 was written by D. Fornari, Part 2 by S. Grandi and D. Fornari, Part 3 by F. Negri, Part 4 by D. Pellegrini, Part 5 by M.G. Cardinali, Part 6 by E. Fornari, Part 7 by C. Ziliani and Part 8 by S. Grandi. The authors are involved in researching and teaching Retail Marketing and Trade Marketing at undergraduate and graduate level at the University of Parma, where degree courses, Masters programmes and postgraduate diplomas covering all areas of retailing have been offered for over 15 years.

[2]

Differently from Nielsen, IRI-Information Resources provides a definition of store formats based not only on store size (in square metres) but also on range structure. In

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particular, hypermarkets are self service, modern trade stores with a 2,500 sqm and more size, and a range composed by grocery and non grocery (house-hold appliances, clothing, etc.) products; superstores are self service, modern trade stores with a 2,500 sqm and more size, and a range composed mainly by grocery products (both food and nonfood); supermarkets are self service, modern trade stores with a 400-2,500 sqm size and a range composed only by grocery products (mainly food); convenience stores are self service, modern trade stores with a 200-400 sqm size and a range composed only by grocery products (mainly fresh foods); discount are self service, modern trade stores with a variable size and a range composed mainly by grocery unbranded products; drug stores are self service, modern trade stores with a variable size and a specialized range composed only by home and personal care products; mini/micro stores are traditional trade stores (with personal service) with a 200 sqm and less size and a range composed only by grocery products (mainly food); food mixed stores are traditional trade stores (with personal service) with a 200 sqm and more size and a range composed mainly by grocery products. [3]

A recent survey of grocery markets by the British IGD institute ranks Italy as one of the top investment opportunities along with the BRIC countries (Brazil, Russia, India, and China). These are markets where there are few competition barriers to access for new entries, and considerable development opportunities for international retailers (IGD Research 2008).

[4]

According to Nielsen there are 8,424 modern stores (over 400 sqm), while according to IRI there are 401 hypermarkets (over 2,500 sqm), 387 superstores (between 1,500 and 2,500 sqm) and 8,661 supermarkets (between 1,500 and 400 sqm). See Table 2.

[5]

The author would like to thank Selex and their Marketing Director, Stefano Gambolò, for the cooperation and support to this work. The following discussion focuses on results of all three steps. The first step was the calculation of the attraction areas for 8,424 stores. An algorithm was used to calculate the range of attraction of the single store. The range was found to be positively influenced by store format/size and negatively influenced by the population density, which reduces mobility. Once the microarea for each store was calculated, 23 variables were gathered. These describe the structure of local demand (socio-economic profile of customers) and local supply (number and typologies of stores and economic structure of the area). These variables were then subject to principal component analysis and 14 variables selected. These were linked to the 8,424 stores, and cluster analysis was performed to yield six new groups. A single cluster consists of a micro-area with profiles that are internally homogeneous but very different from those of other clusters. Cluster analysis was preceded by a factor analysis which related the original 23 variables to seven new expli-

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cation factors weighted through a multi-regression analysis. The cluster analysis is based on a heuristic algorithm that builds groups of stores until the variance within the single cluster is the lowest possible. [6]

According to KPMG classification, pure loyalty cards allow for spending and accruing benefits with only the card-issuing retailers. Other models include: ‘push’ – spending at several retailers, accruing benefits with the card issuing retailer; ‘pull’ – spending at the card-issuing retailer, accruing benefits outside the retailer’s everyday range; ‘purchase’ – spending and accruing benefits across many retailers.

[7]

Excluding the value of points accrued under the programme rules that in Italy generally prescribe 1 point per Euro spent, plus extra points on selected items in store.

[8]

In order to emphasise the importance of shopper marketing management, various researchers have underlined that the time spent by consumers in grocery stores is often longer than time spent watching manufacturer brand advertising in front of the TV. This means that stores are becoming not only shopping places, but also communication media (Holbrook/Hirschman 1982; Haley 1984; Bellenger/Korgaonkar 1980; East 1997).

[9]

In recent years, fierce competition has developed on the Italian FMCG market between modern grocery stores (supermarkets, hypermarkets, convenience stores, discounts, etc.) and Ho.Re.Ca. stores (restaurants, coffee shops, canteens, fast foods, vending machines, etc.). This multi-channel shopping is the result of the trend for consumers to satisfy their eating needs both at home (buying at supermarkets and cooking) and out of the home (buying at Ho.Re.Ca. without cooking) (Cardinali 2005).

[10]

Purchase concentration on limited range of brands in the mainstream pricing level has generated significant decreases in follower brand market shares. These brands often suffer from the lack of clear positioning strategies, and consumers tend to perceive them as ‘me too’ products compared to the leading brands ones (Source: Nielsen Trade Mis, IRI-Information Resources).

[11]

Recent studies have suggested that increasing level of consumer participation in activities traditionally performed by salespeople constitutes ‘prosumerism’ and is closely linked to increased rationality and awareness of grocery purchasing (Lugli 2005).

[12]

Despite the significant selection process occurred from 1970 to nowadays (see Table 1), the number of traditional distribution outlets in Italy is still higher than in other main European countries (Planet Retail 2010). Source: IRI-Information Resources, 2010.

[13]

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[14]

Buying Groups’ store portfolio is focused on Supermarkets and Convenience Stores, which have grown a lot both in outlet number and in market share over recent years (see Table 2).

[15]

Sales performance by nonfood/nongrocery products in Hypermarkets was significantly negative during 2009 (IRI-Information Resources 2009).

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