Journal of enterprise information management Vol. 18, No. 3, A multi-enterprise view of business activities

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13/05/2005

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ISBN 1-84544-128-1

ISSN 1741-0398

Volume 18 Number 3 2005

Journal of

Enterprise Information Management formerly Logistics Information Management: An International Journal

A multi-enterprise view of business activities Guest Editor: Cengiz Kahraman

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Journal of Enterprise Information Management

ISSN 1741-0398 Volume 18 Number 3 2005

A multi-enterprise view of business activities Guest Editor Cengiz Kahraman

Access this journal online _________________________

271

Editorial advisory board __________________________

272

Guest editorial ___________________________________

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Multi-attribute information technology project selection using fuzzy axiomatic design

¨ ztays¸i Osman Kulak, Cengiz Kahraman, Bas¸ar O and Mehmet Tanyas¸ ____________________________________________

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A study of enterprise human resource competence appraisement Xiaohong Liu, Da Ruan and Yang Xu _____________________________

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Outsourcing logistics activities in Turkey E. Aktas and F. Ulengin_________________________________________

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Supplier selection and management strategies and manufacturing flexibility Nelson Oly Ndubisi, Muhamad Jantan, Loo Cha Hing and Mat Salleh Ayub _______________________________________________

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CONTENTS

CONTENTS continued

The role of logistics in linking operations and marketing and influences on business performance Bu¨lent Sezen __________________________________________________

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Addressing uncertainty and inequality in nuclear policy E. Laes, W. D’haeseleer and R. Weiler _____________________________

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EDITORIAL REVIEW BOARD

Professor Majed Al-Mashari King Saud University, Saudi Arabia

Dr Mohan Kumaraswamy The University of Hong Kong, Hong Kong

Dr Frank Bannister Trinity College, Dublin, Ireland

Dr Ben Light University of Salford, UK

Professor Andy Bytheway Cape Technikon, Cape Town, South Africa

Professor Juan Llopis University of Alicante, Spain

Professor Steven I-Jy Chien New Jersey Institute of Technology, USA

Dr Jihad S. Nader American University in Dubai, United Arab Emirates Professor Shan Ling Pan National University of Singapore, Singapore Professor Ryan R. Peterson Instituto de Empresa, Spain

Professor Gail Corbitt California State University, USA Professor Wendy Currie Warwick University, UK Professor Tom Davenport Babson College, USA Professor Dr I. Atilla Dicle Yeditepe University, Turkey Dr Tony Elliman Brunel University, UK Professor Jerry Fjermestad New Jersey Institute of Technology, USA Dr Gala H. Galal Cairo University, Egypt Dr George M. Giaglis Athens University of Economics and Business, Greece Dr Reyes Gonza´lez University of Alicante, Spain

The Journal of Enterprise Information Management Vol. 18 No. 3, 2005 p. 272 # Emerald Group Publishing Limited 1741-0398

Dr Rob Procter University of Edinburgh, UK Erwin Rausch Didactic Systems, USA Professor Nicholas C. Romano, Jr Oklahoma State University, Tulsa, USA Professor B.S. Sahay Institute of Management Technology, India Professor Joseph Sarkis Clark University, USA Dr Amir Sharif UBS Investment Bank, UK Professor Glenn Stewart Queensland University of Technology, Australia

Professor A. Gunasekaren University of Massachusetts, USA

Professor William Andrew Taylor University of Bradford, Bradford, UK

Professor Ray Hackney The Manchester Metropolitan University, UK

Dr Marinos Themistocleous Brunel University, Middlesex, UK

John F. Hill University of Warwick, UK

Dr David Wainwright Northumbria University, UK

Dr Stephen Jones Conwy County Borough Council, UK

Dr Frithjof Weber Airbus Deutscheland GmbH, Germany

Dr Philip Joyce Swinburne University of Technology, Australia

Dr Edward F. Watson Louisiana State University, USA

Professor Cengiz Kahraman Istanbul Technical University, Turkey

Dr David Whiteley The Manchester Metropolitan University, UK

Guest editorial About the Guest Editor. Cengiz Kahraman is a professor in the Department of Industrial Engineering, Istanbul Technical University (ITU), Turkey. He received his BSc, MSc, and PhD degrees in Industrial Engineering from ITU. He is also a lecturer in the Turkish Air Force Academy. His research areas include Engineering Economics, Statistics, Quality Control, Multi-Criteria Evaluation, and the applications of Fuzzy Sets Theory on these areas. He has published several international journal papers and book chapters. E-mail: [email protected]

Information technology is an important component of effective supply chain management. For many firms, selection of true IT provides a competitive advantage. It is a multi-attribute selection problem since IT solution requires changes in organizational structure, employee job descriptions and behavior. Under incomplete information, since an exact description of many real life physical situations may be virtually impossible, a fuzzy multi-attribute evaluation of IT projects may be useful. The first paper by Kulak et al., “Multi-attribute information technology project selection using fuzzy axiomatic design”, presents the crisp AD approach under complete information and the fuzzy AD approach under incomplete information for IT selection. Managing human resources is a challenge all business professionals face. Human resource management is a staff function whose primary role is to help the organization achieve its goals. Unlike other resources, human being seeks motivation, satisfaction, and security and need an appropriate climate and culture to achieve high performance. Hence, enterprise human resource appraisement should be based on job-relevant criteria, objectively measured, and protected from undue subjectivity and bias. The second paper by Liu et al. presents a competence appraisement model of human resource in an enterprise.. The results obtained in the paper provide a foundation to establish relatively reasonable and efficient enterprise appraisement system of human resource. Outsourcing is a flexible management tool of the individual enterprise. It is a self-reinforcing process as the existence of excellent services creates the change for further outsourcing. The causes of outsourcing processes can be counted as market pressure and supply of excellent services. The third paper of this special issue is on ¨ lengin present an empirical outsourcing logistics activities in Turkey. Aktas¸ and U research study to determine the types of logistics activities which Turkish companies prefer for outsourcing, and the factors that affect the selection and evaluation criteria for Third Party Logistics firms. Supplier selection is a multi-attribute decision-making problem. The nature of this decision usually is complex and unstructured. The objective is to identify suppliers with the highest potential for meeting a firm’s needs consistently and at an acceptable cost. In their paper, Ndubisi et al. examine the impact of supplier selection and management strategies on manufacturing flexibility (such as product flexibility,

Guest editorial

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launch flexibility, and volume flexibility). Details of the findings, theoretical and practical implications, and the research limitation are discussed. Overall business performance achieved, when there exists an effective coordination between the functions can be well above the performance achieved when the tasks are performed individually. In his paper, Sezen explores the individual and joint effects of operations, marketing, and logistics functions on the level of business performance. The implications of the paper are: (1) coordination between operations and logistics functions in the specific sample is the most prominent issue for achievement of high performance; and (2) logistics function carries an important role in linking the two most important functions of a company, namely, operations and marketing functions. Finally, Laes et al. focuses on the justification of technological choices and options in the context of nuclear energy policy. They draw the attention to the link between the way a certain (energy) policy problem is defined, and the way the framework for political decision making is set up in response to the problem. They make use of a scheme derived from policy sciences, mapping out policy problems in two dimensions: the (lack of) certainty concerning the kinds of knowledge a problem may require, and the (lack of) consensus on relevant values (i.e. “the common good”, “basic rights”, etc.). I hope that the papers in this issue of JEIM will be useful for both theorists and practitioners.

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Multi-attribute information technology project selection using fuzzy axiomatic design Osman Kulak, Cengiz Kahraman, Bas¸ar O¨ztays¸i and Mehmet Tanyas¸

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Department of Industrial Engineering, Istanbul Technical University, ˙Istanbul, Turkey Abstract Purpose – Significant productivity improvements have been experienced in business by information technology (IT) implementations in latest decades. However, IT project selection is an important problem because a significant part of IT expenditure is wasted and almost half of IT projects realize no net benefits. Since axiomatic design (AD) has the characteristics of multi-attribute evaluation, it is proposed for multi-attribute comparison of information technology systems (ITS). Design/methodology/approach – The comparison of ITS is made for the cases of both complete and incomplete information. The crisp AD approach for complete information and the fuzzy AD approach for incomplete information are developed. The numerical applications of both crisp and fuzzy AD approaches in the comparison of ITS are also given. Findings – The AD approach takes into account the design range of each criterion, determined by the designer. Thus, the alternative providing the design ranges is selected in AD approach while the alternative meeting the criteria at their best levels is selected in many other methods. This opportunity is not possible when many other existing methods such as AHP, fuzzy AHP, and scoring models are used. The AD approach also differs from many other existing methods from the point of the rejection of an alternative when it does not meet the design range of any criterion. Research limitations/implications – For future research, it is suggested that researchers study weighted crisp and fuzzy AD approaches. Originality/value – This paper is the first which develops the fuzzy AD approach and uses it in the comparison of ITS. Keywords Communication technologies, Fuzzy control Paper type Research paper

1. Introduction In today’s increasingly competitive business climate, information technology (IT) plays a major role in the success of companies. In latest decades, significant productivity improvements have been experienced in business by IT implementations. IT implementations are widely considered as the main cause of these increases. IT implementations’ advantages can be summarized as operation speed, data and data generation consistency and widely distribution and accessibility of information. IT can be defined as “both computer and telecommunications technology for the collection, storage, retrieval, reproduction, processing, diffusion and transmission of information” (Bosworth and Triplett, 2000; Brynjolfsson and Hitt, 2000). IT encompasses hardware, software and the skills of IT personnel. IT-related reorganization or reengineering of communication and decision processes, operations

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including new product or service development based on IT, are also considered as IT investments necessary for the effective use of IT. Recognition of the potential impact of IT on strategic power of companies and increasing levels of IT expenditure have made the evaluation, justification and control of IT investments a critically important issue. Major barriers, identified by a range of studies, occur in how IT investments are evaluated and controlled (Strassman, 1997). Milis and Mercken (2003) define five different parties involved, each with their own objectives and expectations. One of these parties is parent organization that is the owner of the project and is represented by the management. It is the main benefactor of the investment. Management is primarily interested in the gains generated by the project. Another party is the users: the people who will operate the new technology to achieve benefits. Their objective is usually to obtain the best (not optimum) product, at any price. The third party is defined as project team which are the people who implement the new technology. Project managers are focused on short-term criteria set by the sponsor because these will be used to judge them. Other two parties are supporters and stakeholders. Supporters are a heterogeneous group of people that supply resources or services needed for the implementation of the technology. Supporters also focus on short-term criteria since the distance to the general management is further than to the project team in most cases. Stakeholders are the groups whose lives or environment are affected by the investment, but receive neither direct benefits from it nor have direct influence on it. This group is composed of many different subgroups with their own goals and objectives. In this complex decision structure, there have been many different techniques used to evaluate and select IT projects. These techniques can be classified into four major classifications: economic, strategic, analytic, and integrated approaches. While, economic approaches generally use quantitative financial measurements to evaluate IT investments, strategic approaches consider the project’s strategic alliances with corporate strategies. On the other hand, in analytic approaches, analytic formulations, scoring technique, and fuzzy logic are used to evaluate IT projects. IT investment techniques are represented in Figure 1, with their respective literature sources. The importance of IT selection bring forth the academics’ concern about the selection techniques. One of the recent studies is Stewart and Mohamed (2002)’s that proposes a framework that is based on the multi-criteria utility theory (MCUT). Kahraman (2002) uses fuzzy regression analysis to forecast the sale levels of IT in Turkey. Stewart and Mohamed (2003)’s other study uses balanced scorecard (BSC) as a framework to evaluate IT projects in construction sector. Another recent study is Milis and Mercken (2003)’s that discusses the evaluation techniques used to justify capital investments in IT projects. Also there are some studies that focus on the benefits side of IT (Swierczek and Shrestha, 2003). There are various perspectives and criteria in the process of IT selection. In this study they are classified into five basic criteria. These are Technical and organizational risk (TOR). This criterion covers the basic technical and organizational risks that are, technical support and suitability uncertainty, infrastructure requirements. Also organization’s lack of resource commitment and project’s compatibility with current systems are defined in this criterion.

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Figure 1. IT investment techniques and references

Return on investment (ROI). This criterion is not only the financial ratio (ROI) but also general benefits of the projects which are represented in this criterion. Project’s effect on market share and corporate profitability is evaluated in this criterion. Basically it is the created customer and business value compared with the initial and maintenance costs. User satisfaction (US). This is one of the key success factors of a project to be finalized and realized as planned. So the satisfaction of all user levels is a major criterion. This criterion is basically composed of the concepts of, user friendliness, use education and user support. Operational agility (OA). This is another criterion that stands for the projects operational performance. Operational performance can be detailed as, fast response time and quality of the output. Since information is the core point in IT projects, information security is another side of the performance. Strategic competitiveness (SC). This criterion is the effect of the project on organizational competitiveness, which can be considered as the level of alliance of the project with corporate competitive strategies. This contains enhanced organizational image and ability to attract more customers. The ultimate goal of axiomatic design (AD) is to establish a scientific basis for design and to improve design activities by providing the designer with a theoretical foundation based on logical and rational thought processes and tools (Suh, 2001). In accomplishing this goal, the AD provides a systematic search process through the design space to minimize the random search process and determine the best design solution among many alternatives. Many AD applications in designing products, systems, organizations and software have appeared in the literature in the last ten years. AD theory and principles have been introduced first time by Suh (1990). Kim et al. (1991) applied AD principles on software design. AD principles have also been used in the design of quality systems (Suh, 1995) and general system design (Suh, 1995, 1997). Suh et al. (1998) provided a

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manufacturing system design using AD principles. AD principles have also been applied in designing flexible manufacturing systems (Babic, 1999). Kulak et al. (2002) provide a framework and a road map for the design of cellular manufacturing systems using AD principles. Other applications of AD include process and product development (Suh, 2001), structural design in civil engineering structures (Albano and Suh, 1992) and environmental problem solving (Wallace and Suh, 1993). These studies have convincingly shown the applicability and benefits of AD in solving industrial problems. For a long time, it has been recognized that an exact description of many real life physical situations may be virtually impossible. This is due to the high degree of imprecision involved in real world situations. Zadeh (1965, 1968) in his seminal papers proposed fuzzy set theory as the means for quantifying the inherent fuzziness that is present in ill-posed problems. Fuzziness is a type of imprecision which may be associated with sets in which there are no sharp transition from membership to non-membership. Fuzzy logic is basically a multi-valued logic that allows intermediate values to be defined between conventional evaluations like yes/no, true/false, black/white, etc. By using fuzzy logic, notions like rather warm or pretty cold can be formulated mathematically and processed by computers. In this way an attempt is made to apply a more human-like way of thinking in the programming of computers. A major contribution of fuzzy set theory is its capability of representing vague knowledge. Very often in MADM problems data are imprecise and fuzzy. For instance, what is the value of the jth alternative in terms of an environmental impact criterion? A decision maker may encounter difficulty in quantifying such linguistic statements so they can be used in deterministic decision-making. In this paper, as the first time, crisp multi-attribute AD approach and then a fuzzy multi-attribute AD approach to justify ITS are proposed. First, principles of AD and a numeric application of crisp AD approach are given. Second, fuzzy sets and fuzzy AD approach with a numerical application are given. Finally, the comparison of both approaches is made in the conclusion section. 2. Principles of AD The most important concept in AD is the existence of the design axioms. The first design axiom is known as the independence axiom and the second axiom is known as the information axiom. The axioms are stated as follows (Suh, 1990): (1) The independence axiom: Maintain the independence of functional requirements (2) The information axiom: Minimize the information content The independence axiom states that the independence of functional requirements (FRs) must always be maintained, where FRs are defined as the minimum set of independent requirements that characterizes the design goals (Suh, 1990). In the real world, engineers tend to tackle a complex problem by decomposing it into sub-problems and attempting to maintain independent solutions for these smaller problems. This calls for an effective method that provides guidelines for the decomposition of complex problems and independent mappings between problems and solutions. The information axiom states that among those designs that satisfy the independence axiom, the design that has the smallest information content is the best

design (Suh, 2001). Information is defined in terms of the information content, I, that is related in its simplest form to the probability of satisfying the given FRs. Information content Ii for a given FRi is defined as follows:
 1 I i ¼ log2 ð1Þ pi where pi is the probability of achieving the functional requirement FRi and log is either the logarithm in base 2 (with the unit of bits). This definition of information follows the definition of Shannon, although there are operational differences. Because there are n FRs, the total information content is the sum of all these probabilities. If I approaches infinity, the system will never work. When all probabilities are one, the information content is zero, and conversely, the information required is infinite when one or more probabilities are equal to zero (Suh, 1995). In any design situation, the probability of success is given by what designer wishes to achieve in terms of tolerance (i.e. design range) and what the system is capable of delivering (i.e. system range). As shown in Figure 2, the overlap between the designer-specified “design range” and the system capability range “system range” is the region where the acceptable solution exists. Therefore, in the case of uniform probability distribution function pi may be written as
 Common range pi ¼ ð2Þ System range Therefore, the information content is equal to
 System range I i ¼ log2 Common range

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ð3Þ

The probability of achieving FRi in the design range may be expressed, if FRi is a continuous random variable, as

Figure 2. Design range, system range, common range and probability density function of a FR

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pi ¼

Z

dr u

ps ðFRÞ dFR

ð4Þ

dr 1

280

Where ps(FR) is the system pdf (probability density function) for FR. Equation (4) gives the probability of success by integrating the system pdf over the entire design range. (i.e. the lower bound of design range, dr 1, to the upper bound of the design range, dr u). In Figure 3, the area of the common range (Acr) is equal to the probability of success P (Suh, 1990). Therefore, the information content is equal to
 1 I ¼ log2 ð5Þ Acr The information content in equation (1) is a kind of entropy that measures uncertainty. There are some other measures of information in terms of uncertainty. Prior to the theory of fuzzy sets, two principal measures of uncertainty were recognized. One of them, proposed by Hartley (1928), is based solely on the classical set theory. The other, introduced by Shannon (1948), is formulated in terms of probability theory. Both of these measures pertain to some aspects of ambiguity, as opposed to vagueness or fuzziness. Both Hartley and Shannon introduced their measures for the purpose of measuring information in terms of uncertainty. Therefore, these measures are often referred to as measures of information. The measure invented by Shannon is referred to as the Shannon entropy. The Shannon entropy, which is a measure of uncertainty and information formulated in terms of probability theory, is expressed by the function X pðxÞ log2 pðxÞ ð6Þ H ðpðxÞ=x [ XÞ ¼ 2 x[X

where ðpðxÞ=x [ XÞ is a probability distribution on a finite set X.

Figure 3. Design range, system range, common range and probability density function of a FR

Suh’s entropy in AD does not require that the total of probabilities is equal to 1.0 while Shannon entropy does. Because of this property, Shannon entropy should not be used as an entropy measure while evaluating independent functional requirements in AD. In the following, a numeric application of crisp AD approach to justify ITS is given. The application includes information content in equation (1).

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3. A numerical application of crisp AD approach An international bank in Turkey, wants to renew its IT system to satisfy its customer needs. The bank must decide to select the most appropriate one among the different alternative IT systems. There are various perspectives and criteria in the IT projects selection. Therefore the decision makers in the bank grouped them into five basic criteria. These are technical and organizational risk, return on investment, user satisfaction and strategic competitiveness. With respect to the decision makers, the functional requirements that should be satisfied by a IT are given below. Since FRROI is a monetary criterion, it is a different criterion from the others. The other criteria are graded between 1 and 20. This grading is arranged to show that the interval 17-20 is excellent, 13-16 is very good, 9-12 is good, 5-8 is fair and 1-4 is poor. For example while “17 to 20” indicates a low risk (excellent) for technical and organizational criterion, “1 to 4” indicates a high risk (poor) for the same criterion. . FRROI¼ ROI must be over 7 percent (in the range of 7-10 percent); . FRTOR¼ TOR must be over 9 (in the range of 9-20); . FRUS¼ US must be over 13 (in the range of 13-20); . FROA¼ OA must be in the range of 12-16; . FRSC¼ SC must be over 15 (in the range of 15-20). Alternative IT projects’ return on investment and performance scores evaluated by the experts with respect to certain criteria, are given in Table I. The data given in the Table I are arranged to include the minimum and maximum performance values supplied by the IT system. The data in Table I, related to return on investment reflects only the minimum and maximum rates (percent). Using these design and system ranges, the information content for each FR in each IT project may be computed using equations (3) and (5). A sample calculation to obtain the information contents of TOR is presented below (Figure 4).

IT projects IT-A IT-B IT-C IT-D

Return on investment (percent)

Technical and organizational risk

User satisfaction

Operational agility

Strategic competitiveness

6-8 8-9 4-5 8-10

8-12 7-10 12-17 18-20

8-14 13-18 9-14 10-14

11-13 12-16 9-14 14-18

12-18 15-17 12-16 19-20

Table I. The system range data for IT projects

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Figure 4. Design and system ranges of TOR for IT-A

For IT-A: I IT – A ¼ log2



 12 2 8 4 ¼ log2 ¼ 0:415 12 2 9 3

The information contents for the other criteria with respect to the alternatives are given in Table II. As the system with minimum information content is the best one, IT-B is selected. 4. Fuzzy AD approach The fuzzy data can be linguistic terms, fuzzy sets, or fuzzy numbers. If the fuzzy data are linguistic terms, they are transformed into fuzzy numbers first. Then all the fuzzy numbers (or fuzzy sets) are assigned crisp scores. The following numerical approximation systems are proposed to systematically convert linguistic terms to their corresponding fuzzy numbers. The system contains five conversion scales (Figures 5 and 6). In the fuzzy case, we have incomplete information about the system and design ranges. The system and design range for a certain criterion will be expressed by using “over a number”, “around a number” or “between two numbers”. These kind of expressions can be represented by triangular or trapezoidal fuzzy numbers. We now have a function of triangular or trapezoidal fuzzy number whereas we have a probability density function in the crisp case. So, the common area is the intersection IT projects

Table II. Suh’s information content for IT projects

IT-A IT-B IT-C IT-D

IROI

ITOR

IUS

IOA

ISC

P Ii

1.000 0.000 Infinite 0.000

0.415 1.585 0.000 0.000

2.585 0.000 2.322 2.000

1.000 0.000 1.322 1.000

1.000 0.000 2.000 0.000

6.000 1.585a Infinite 3.000

Note: aThe result of alternative with minimum information content

area of triangular or trapezoidal fuzzy numbers. The common area between design range and system range is shown in Figure 7. Therefore, information content is equal to;
I ¼ log2

TFN of system design Common area

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 ð7Þ

283

Figure 5. The numerical approximation system for intangible factors

Figure 6. The numerical approximation system for tangible factors

Figure 7. The common area of system and design ranges

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5. A numerical application of fuzzy AD The same company in Section 3 has the following fuzzy functional requirements: . FRROI¼ ROI must be around 7 percent: (7, 10, 10 percent); . FRTOR¼ TOR must be over 9: (9, 20, 20); . FRUS¼ US must be over 13: (13, 20, 20); . FROA¼ OA must be around 14: (12, 14, 16); . FRSC¼ SC must be over 15: (15, 20, 20). The experts produce the system range data and use the linguistic expressions as in Table III. The conversation scales for the intangibles TOR, US, OA and SC are given in Figure 8 while the ones for the tangible ROI is given in Figure 9. In Figure 9 it is assumed that the most possible value for the criterion ROI is 10 percent. In order to obtain the information content for TOR a sample calculation is given in the following (Figure 10). For IT-A: Common area ¼ ð14 2 9Þ* 0:357=2 ¼ 0:893 System area ¼ ð14 2 8Þ* 1=2 ¼ 3

Table III. The system range data for IT projects

Figure 8. TFNs for intangible factors

IT Projects

Return on investment (percent)

Technical and organizational risk

User satisfaction

Operational agility

Strategic competitiveness

IT-A IT-B IT-C IT-D

High Very high Low Very high

Good Fair Very good Excellent

Good Very good Good Good

Good Very good Good Very good

Very good Very good Very good Excellent

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Figure 9. TFNs for tangible factors

Figure 10. Design and system ranges of TOR in case of fuzziness

IT projects IT-A IT-B IT-C IT-D

IROI

IDTOR

IUS

IOA

ISC

P Ii

1.152 0.000 Infinite 0.000

1.748 6.381 0.365 0.000

5.907 2.466 5.907 5.907

2.907 0.907 2.907 2.907

2.414 2.414 2.414 0.000

14.128 12.168 Infinite 8.814a

Note: aResult of alternative with minimum information content

Table IV. The information content for IT projects

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I TOR ¼ log2

System area Common area




¼ log2

3 0:893

 ¼ 1:748

The information contents for the other criteria with respect to the alternatives are given in Table IV. The alternative with minimum information content is IT-D. The rankings obtained by using the crisp and fuzzy approaches are different. This is result of that the variables in fuzzy approach are not composed of sharp defined values as in crisp approach. The information contents of IT-B and IT-D are very near to each other in the crisp case. This ranking changes to the favor of IT-B in the fuzzy case, because soft sets are used. 6. Conclusions In most of the real-world problems, some of the decision data can be precisely assessed while others cannot. Real numbers are used to represent data which can be precisely measured. For those data which cannot be precisely assessed, fuzzy sets can be used to denote them. The use of fuzzy set theory allows us to incorporate unquantifiable information, incomplete information, no obtainable information and partially ignorant facts into the decision model. When decision data are precisely known, they should not be forced into a fuzzy format in the decision analysis. Crisp MADM methods solve problems in which all decision data are assumed to be known and must be represented by crisp numbers. The methods are to effectively aggregate performance scores. Fuzzy MADM methods have difficulty in judging the preferred alternatives because all aggregated scores are fuzzy data. We propose crisp multi-attribute AD approach when all decision data are known whereas we propose fuzzy multi-attribute AD approach when unquantifiable or incomplete information exists. For the future research, we suggest researchers to study weighted crisp and fuzzy AD approaches. References Albano, L.D. and Suh, N.P. (1992), “Axiomatic approach to structural design”, Research in Engineering Design, Vol. 4 No. 3, pp. 171-83. Babic, B. (1999), “Axiomatic design of flexible manufacturing systems”, International Journal of Production Research, Vol. 37 No. 5, pp. 1159-73. Bosworth, B.P. and Triplett, J.E. (2000), “What’s new about the new economy? IT, economic growth and productivity”, Working Paper, Economics Studies Program, Brookings Institution, Washington, DC, December. Brynjolfsson, E. and Hitt, L.M. (2000), “Beyond computation: Information technology, organizational transformation and business performance”, Journal of Economic Perspectives, Vol. 144, pp. 23-48. Hartley, R.V.L. (1928), “Transmission of information?”, Bell System Technical Journal, Vol. 7, pp. 535-63. Kahraman, C. (2002), “Forecasting the sale levels of information technology using fuzzy regression analysis: the case of Turkey”, International Journal of Technology Management, Vol. 24 Nos. 2-3, pp. 330-9. Kim, S.J., Suh, N.P. and Kim, S. (1991), “Design of software systems based on AD”, Annals of CIRP, Vol. 40, pp. 165-70. Kulak, O., Durmus¸oglu, M.B. and Tu¨fekci, S. (2002), “A complete cellular manafacturing system design methodology based on a axiomatic design principles”, Proceedings of the

30th International Conference on Computers & Industrial Engineering, 28 June-2 July, Tinos Island, pp. 491-6. Milis, K. and Mercken, R. (2003), “The use of the balanced scorecard for the evaluation of information and communication technology projects”, International Journal of Project Management. Shannon, C.E. (1948), “The mathematical theory of communication”, The Bell System Technical Journal, Vol. 27, pp. 379-423, 623-656. Stewart, R.A. and Mohamed, S. (2002), “IT/IS projects selection using multi-criteria utulity theory”, Logistics Information Management, Vol. 15 No. 4, pp. 254-70. Stewart, R.A. and Mohamed, S. (2003), “Evaluating the value IT adds to the process of project information management in construction”, Automation in Construction, Vol. 12, pp. 407-17. Strassman, P.A. (1997), The Squandered Computer: Evaluating the Business Alignment of Information Technologies, Information Economics Press, New Cannan, CT. Suh, N.P. (1990), The Principles of Design, Oxford University Press, New York, NY. Suh, N.P. (1995), “Design and operation of large systems”, Annals of CIRP, Vol. 14 No. 3, pp. 203-13. Suh, N.P. (1997), “Design of systems”, Annals of CIRP, Vol. 46 No. 1, pp. 75-80. Suh, N.P. (2001), Axiomatic Design: Advances and Applications, Oxford University Press, New York, NY. Suh, N.P., Cochran, D.S. and Paulo, C.L. (1998), “Manufacturing system design”, CIRP Annals, Vol. 47 No. 2, pp. 627-39. Swierczek, F.W. and Shrestha, P.K. (2003), “Information technology and productivity: a comparison of Japanese and Asia-Pacific banks”, Journal of High Technology Management Research, Vol. 14, pp. 269-88. Wallace, D.R. and Suh, N.P. (1993), “Information-based design for environmental problem solving”, Annals of CIRP, Vol. 42 No. 1, pp. 175-80. Zadeh, L.A. (1965), “Fuzzy sets”, Information Control, Vol. 8, pp. 338-53. Zadeh, L.A. (1968), “Probability measures of fuzzy events”, J. Math. Anal. Appl., Vol. 23, pp. 421-7.

Further reading Awad, A.H.-S. and Tang, W.H. (1984), Probability Concepts in Engineering Planning and Design, Volume II – Decision, Risk and Reliability, Wiley, New York, NY. Dugdale, D. (1991), “Is there a correct method of investment appraisal?”, Management Accounting, Vol. 69, pp. 46-50. Fitzgerald, G. (1998), “Evaluating information systems project: a multi-dimensional approach”, Journal of Information Technology, Vol. 14, pp. 17-30. Hochstrasser, B. and Griffiths, C. (1991), Controlling IT Investment: Strategy and Management, Chapman and Hall, London. Irani, Z., Ezingear, J-N. and Grieve, R.J. (1997), “Integrating the costs of a manufacturing IT/IS infrastructure into the investment decision-making process”, Technovation, Vol. 17 Nos. 11-12, pp. 695-706. Kakati, M. and Fhar, U. (1991), “Investment justification of flexible manufacturing systems”, Engineering Costs and Production Economics, Vol. 21, pp. 30-43.

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Kambil, M., Henderson, J.C. and Mohsenzadeh, H. (1993), Strategic Management of Information Technology Investment: An Options Perspective, Chapter 9, Idea Group Publishing, Harrisburg, PA. Kaplan, R. and Norton, D. (1996), “Using the balanced scorecard as a strategic management system”, Harvard Business Review, Vol. 74 No. 1, p. 75. Kennedy, A.J. and Sugden, K. (1986), “Post completion auditing: a source of strategic direction?”, Management Accounting, Vol. 67, pp. 34-7. Liang, G.S. and Wang, M.J.J. (1993), “A fuzzy multi-criteria decision making approach for robot selection”, Robotics & Computer-Integrated Manufacturing, Vol. 10 No. 4, pp. 267-74. Nelson, C.A. (1986), “A scoring model for flexible manufacturing systems project selection”, European Journal of Operations Research, Vol. 24, pp. 346-59. Parker, M., Benson, R. and Trainer, H. (1988), “Information economics: linking business performance to information technology”, Prentice-Hall, Englewood Cliffs, NY. Remenyi, D. and Heafield, A. (1995), “Business process re-engineering: some aspects of how to evaluate and manage the risk exposure”, Proceedings of the 2nd European Conference on Information Technology Investment Evaluation, pp. 161-73. Saaty, T.L. (1990), “How to make a decision: the analytic hierarchy process”, European Journal of Operational Research, Vol. 48, pp. 9-26. Sloggy, J.E. (1984), “How to justify the cost of an FMS”, Tooling and Production, Vol. 50, pp. 72-5. Sullivan, W.G. (1986), “Models Ies can use to include strategic, non-monetary factors in automation decisions”, Industrial Engineering, Vol. 42, pp. 42-50. Suresh, N.C. and Meredith, J.R. (1985), “Justifying multimachine systems: an integrated machine approach”, Journal of Manufacturing Systems, Vol. 4, pp. 117-34. Ward, J.M. (1990), “A portfolio approach to evaluating information systems investments and setting priorities”, Journal of Information Technology, Vol. 5, pp. 222-31. Willcocks, L. and Lester, S. (1996), The Evaluation and Management of Information Systems Investments: From Feasibility to Routine Operations. Investing in Information Systems: Evaluation and Management, Chapman and Hall, London.

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A study of enterprise human resource competence appraisement Xiaohong Liu

Human resource competence appraisement 289

Chengdu University Technology, Chengdu, Sichuan, People’s Republic of China

Da Ruan The Belgian Nuclear Research Centre (SCK·CEN), Mol, Belgium, and

Yang Xu Intelligent Control Development Centre, Southwest Jiaotong University, Chengdu, Sichuan, People’s Republic of China Abstract Purpose – For an enterprise, the competence of human resource is more important than the intellect or the basic quality of human resource. This paper aims to present a competence appraisement model of human resource in an enterprise. Design/methodology/approach – The paper puts forward the appraisement index architecture of enterprise human resource competence on the foundation of adopting the concept and models of competence, and establishes a general model of the enterprise human resource competence appraisement. Findings – The results obtained in this paper provide a foundation to establish a relatively reasonable and efficient enterprise appraisement system of human resources. Originality/value – The research offers information about the enterprise appraisement information processing system of human resources. Keywords Human resourcing, Uncertainty management, Competences Paper type Research paper

1. Introduction Drucker (1954) in the Practice of Management first put forward the concept of human resource, great progress has been made in the theory of human resource management, meanwhile, it plays an important role in guiding the practice of management. Human resource has been considered as a kind of strategic contributors in an enterprise since 1990s. As a consequence, many theories and methods of the strategic management of human resource have been developed. In some degree, the management of human resource becomes the strategic management of human resource. How to treat and determine the value of human resource becomes an important researching content in the strategic management of human resource (Baron, 2003; Dennis et al., 2002; Grabot The authors gratefully acknowledge the support of National Social Science Foundation of China (Grant No. 03CJL004) and the National Natural Science Foundation of China (Grant No. 60474022). The authors would like to thank two anonymous reviewers and Professor C. Kahraman (Guest Editor of this special issue) for their constructive and helpful comments on the earlier version of the paper.

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and Letouzey, 2000; Gunderson, 2001; Hagan, 1996; Jeong, 2002; Kaufman, 2001; Pinker and Larson, 2003; Remus and Timothy, 2002; Wang and Yao, 2003). According to the basic conditions of human resource such as its psychology, interest, knowledge, ability, body and performance and so on, the appraisement of enterprise human resource is the course of estimating and judging the value for human resource (include existing value and latent value), it is used in the choice of future occupation of human resource and job adjustment to offer scientific and objective basis, its purpose is to properly arrange human resource more efficiently. The origin of competence can be traced back to the later 1960s, the idea of competence was put forward by David McClelland who is a psychologist at Harvard university and his team through a plenty of researches. The traditional theoretical model of personnel assessment cannot foresee performance and personal success, and more, it lacks fairness. They discovered the important factors that affect individual’s performance are such as achievement motivation, person occasion understanding, and group team influence and so on. According to McClelland, it is necessary to give up the traditional assessment technique and method, and the researcher should seek a kind of variable that can cause to succeed, and at the same time do not have prejudice, then, to develop a kind of objective method that can describe the identification. Under such background, McClelland has developed the concept of competence as a centre of personnel assessment; its purpose is to face future, performance, objective and operability. McClelland (1973) published the article of Testing for competence rather than for intelligence that provided the birth foundation of the competence theory. Since 1973, McClelland has formally put forward the competence concept, and competence has become an important studying content in the field of theory and application of human resource management. However, the definition of competence is not completely consistent. Professor McClelland defined competence as: it can distinguish in the personal features in specific working post and organization environment. In England, researchers often get working behaviour in touch with competence, and get competence in touch with national professional qualification, management Charter innovation and national standard, has formed the reference duty standard of official and management academic organization, but the definition trends into work out the trade standard and labour relation, and do not care for individual performance. Richard Boyatzis, the consulting adviser of American Micbo company, defined competence as is: in a working or certain condition and the reference standard, the excellent achievement or effective and the individual latent characteristic have relation between cause and effect, it can be motivation, property and ability, self reflection or the image of social role, or is people using the knowledge (Boyatzis, 1982). Wang (2002), from trend in operable angle defined competence as those that can be used to distinguish clearly high performance with ordinary performance, or distinguish the personal characteristic of effective performance with invalid performance. In the definition of competence, some emphasize special quality, others emphasize behaviour, but different definitions have nevertheless the common points: (1) used performance standard as reference; (2) included the viewpoint of relation between cause and effect, and competence has caused individual performance as a main reason;

(3) did not exclude personal latent property or behaviour, and the behaviour of personal was the reflection of competence, competence was the combination of different layer surface of special quality and behaviour; (4) behaviour was not competence, and was its expression form, not all behaviours was the expression of competence, competence was in which stabilized, described, foreseen of high performance that is a part of behaviour. In this paper, the definition of competence strangely depends on the content of a practical circumstance. For facing the professional development of enterprise human resource appraisement, its essence is in specifying working post and ambient conditions, human resource can obtain high performance’s factor’s optimization combination such as body, interest, knowledge, ability and the personal psychology and so on. Professional development is the basic view of the modern enterprise management of human resource. It is also one of the norms of an enterprise appraisement of human resource. Essentially, there are some inner connections between professional development and human resource competence appraisement, which can only realize professional development really through competence appraisement. This paper puts forward the appraisement index architecture of enterprise human resource competence on the foundation of adopting the concept and models of competence, and establishes a general model of the enterprise human resource competence appraisement. 2. The concept of the enterprise human resource appraisement of professional development The human resource appraisement is the outcome of human resource management theory and practice developing certain stage. The enterprise human resource appraisement belongs to the field of enterprise human resource relative value measurement. Human resource program, personnel examination and human resource appraisement will be the three basic works of modern enterprise human resource management. 2.1 The concept of professional development The systematic ideology from the professional development point of view in human resource management originated from Schein (1978), published Career Dynamics: Matching Individual and Organizational Needs. Schein divided occupation into inner-professional and external professional, the inner-professional is the road of experience in the course of human resource pursuing a kind of professional, this is the human resource own occupation, and the human resource tries to make the work and other needs such as safe guarantee, social contact, respect, realize personal value and so on, family duty and individual relax to reach balance. External professional is the occupation for organization (such as enterprise), and it expresses the organization with great efforts to offer a development road that is following, perceiving, feasible for the human resource. External professional is relative inner-professional objective existence. The professional development’s key essence is the reasonable combination of inner-professional and external professional, and the needs of personal and organization both sides get to satisfy, is benefited each other. The professional development’s basic model is shown in Figure 1. Figure 1 shows that the goal between personal and organization is different. If the goal of one side is satisfied only and the purpose of another side is given up, it cannot

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Figure 1. Viewpoint of professional development: basic model

form effective professional development obviously. Essentially, professional development course is both personal and organization’s benefit reasonable biggest melt, i.e. realizing one side’s purpose does not harm another side’s purpose, this seems in the Pareto optimum model of welfare economics. It is very important that professional development for the human resource marketing of flowing and two-way selecting, it is a basic guarantee to realize the reasonable disposition of human resource and raises human resource using efficiency. 2.2 The concept of the enterprise human resource appraisement of professional development Though the thought of the human resource appraisement has come long time ago, it is restricted into two aspects: one is not having operability, i.e. do not solve the problem how to realize cost and value measuring method, the other is considering organization benefit only and ignoring personal benefit, i.e. have no idea of professional

development. Because of the above-mentioned reasons, the enterprise human resource appraisement has not formed yet a more systematic theoretical system so far. Along with the fast development of information technology, the enterprise survival and development’s environmental have been greatly changed, the virtual marketing (mainly based on computer network and internet) becomes a new space of enterprise survival and development, the demand of individuation is the customer’s major feature in virtual market, the individuation of human resource management is also becoming a direction of the modern enterprise human resource management (Liu et al., 2002). Because of the changing of enterprise survival and development’s environmental, it is necessary for enterprise to build a human resource appraisement system of professional development. The enterprise human resource appraisement of professional development is a process that is enterprise according to human resource’s basic conditions such as psychology, interest, knowledge, ability, body, performance and so on to estimate and judge the value for human resource (include existing value and latent value), it is used in the choice of future occupation of human resource and job adjustment to offer scientific and objective basis, its essence is coming true between the needs of the individual and enterprise, its core is accomplishing person’s value maximum on the foundation of knowing individual, its method belongs to the field of enterprise human resource relative value measured.

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3. Competence model It is positive meaning that the concept of competence to raise human resource efficiency. In the application research of competence, researchers have established some related models of competence. Actually, the model of competence is applying the thought of competence in the course of human resource appraisement, it selects high performance according to specific working post and ambient conditions. The section introduces three competence models: iceberg model, general model and manager person competence model. 3.1 Competence iceberg model Competence iceberg model is shown in Figure 2. The model divides competence into two parts, one is the upside water surface that includes mainly knowledge and skill, and the other is the below water surface that includes mainly viewpoint of value, self image, character/personality, self-force/social motivation and so on. Comparatively, the feature of upside water surface is more than the feature of below water surface obvious,

Figure 2. The iceberg model of competence

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outstanding and easy to measure, but what decides the successful opportunity of a person really is the feature of below water surface, because of those factors hidden below water surface, they are easily neglected and hard to be measured relatively. Figure 2 has been regarded as a basic model of competence. Kanungo and Misra (1992) thought that ability did not be equal to competence, ability showed in obvious behaviour, and showed by the competence intellectual and perception campaign under complex unconventional task and changeful ambient conditions. Parry (1998) thought that the difference of competence and ability still lied in the level of vague generalization, ability more task centre melt and specify more to melt, and competence was more universal and general. Knowledge has dual character, one is objective, another is it can be grasped, but knowledge is not competence. Relation between knowledge and competence is: competence is in the course of grasping knowledge in formed and developed, if left study and train, competence cannot develop. On the other hand, certain competence is prerequisite to grasp knowledge (such as learning ability); competence restricts to grasp depth and the speed of knowledge. Wang (2002) described the iceberg model that contains better dialectics thought and embodies the relationship between internal cause and external cause would be useful in appraising an individual. However, for enterprise human resource appraisement, the iceberg model did not offer reality the method of application, and in the enterprise human resource appraisement of professional development need to consider the benefit of personal and enterprise. Enterprise needs selecting in current and future time, the iceberg model emphasized the factors of the below water surface that cannot be perceived directly (this is called internal cause), and knowledge and skill belong to evidently partial (this is called external cause), and the iceberg model did not give the conversion relation between the internal cause and the external cause method, besides, the model did not give quantification examination knowledge and skill. In a word, the iceberg model can be used to explain the competence produce reason, but it cannot be used to design an appraisement index. 3.2 The competence general model of Boyatzis Boyatzis (1982), the consulting adviser of American Micbo Company, had put forward specially a general model of competence. Boyatzis thought the competence is to make manager obtain outstanding achievement of those behaviours. He investigated 20 organizations and 20,000 managers, and attempted to find these general competence models. Boyatzis put forward a general model of competence that included 21 kinds of competent feature, they are as follows: (1) correct self-appraisement; (2) generalities; (3) notice close relation; (4) emphasize result; (5) develop other person; (6) judge ability; (7) effective location; (8) logicality thought problem; (9) group team management;

(10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21)

memory; objectivity; attitude positive; initiative; self-confident; self-control; professional knowledge; sense of responsibility; willpower with meet ability; express ability orally; good at use the strength of the masses; and good at to utilize can use resource.

3.3 The competence model for manager Besides the competence general model of Boyatzis, some scholars have still put forward other competence model, though these competence models are not completely identical, they pay attention to skill and knowledge. As shown in Table I the section cites a manager competence model according to the behaviour of manager high performance. 4. Basic hypothesis To construct the enterprise human resource competence appraisement relatively reasonably, this paper does the following basic hypothesis. (1) There are two type factors that affect competence: according to the viewpoint of optimization combination of the essence of competence that is through the human resource’s basic conditions such as psychology, interest, knowledge, ability, body and so on under specific working post and ambient conditions to obtain high performance, it can be generalized influencing competence two basic factors that are internal environment of person (use Se to show, it includes personal psychology, interest, knowledge, ability and body) and external environment of person (use Oe to show, it includes enterprise sense and human relations). The internal environment of person is the foundation that forms the competent force of person, and the interact result of the factors of internal environment of person and the factors of external environment determines the difference in degree of competence. (2) The three layers of competence appraisement: static appraisement, dynamic appraisement and competence appraisement. As for internal environment of person appraisement, it belongs to the static appraisement. Integrating internal environment with external environment appraisement belongs to dynamic appraisement in competence appraisement model. Appraisement of efficient achievement which gives rise to dynamic appraisement belongs to competence appraisement. The high performance is the result of internal environment of person, external environment of person and subjective effort interacting each

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296 Persuasion Professionalism Professional knowledge Problem is solved and analysed Link up orally It is written to link up Entrepreneur property Commercial consciousness Innovation Lead takes action Strategy Person occasion sensitivity Flexibility Recover force Table I. The appraisement index of the competence model for manager

Self encourages

Encourage and authorize other person in order to reach organization goal Organize and arrange incident, campaign and resource; establish and put forward time and specification Show goal consciousness and standard consciousness; to guarantee quality and production standard is suitable do not lose strength to spare Affect, persuade or move other person, let it agree, accept or change behaviour Know technical or professional working method, and grasp technical knowledge continuously Analysis problem decomposes some, based on related information, make the judgement of system and reason For individual with organization can spoken language understand, fluent, it is absorbing Writing is clear and succinct, offers adaptive grammar, style and language for reader Understand and apply commercial and financial principle; there are cost profit sight, market-in concept and increament idea Found the method input work of new and rich imagination; definite fresh method shows that query traditional desire Display at any time preparation decision, begin the action of positive and original wound Demonstrate rich foresight outstanding insight and the overall view for thing It is sensitive to move efficiently mutual with other person; respect other person, cooperate happily Success meets the change of demand and environment Is being baffled and still maintain effective working behaviour under pressure; maintenance is sober, calm, palm control self Self promises, goes forward with great efforts to goal; show that enthusiastic and professional promise is

other, because the subjective effort of person is a variable that is expressed in the working, if the result of combining of internal environment of person and external environment of person is much better, the level of the will be much higher, therefore the factor of subjectively effort of person is assumed to be decided by the factors of internal environment of person and external environment of person. The factor of subjective effort of person is assumed as a constant one in the high performance appraisement. The relation of the result of dynamic appraisement and the high performance is nonlinear; therefore, this paper uses the S-curve to express the relation. (3) The basic index system of competence appraisement is shown in Table II. This index system is the index of static appraisement when not combining with the

External environment (Oe)

Psychological (Se1)

Internal environment (Se)

Working habit

Viewpoint of value

Manage system

Work condition

Work time Work efficiency

Encouragement goal

Lead style

It is injustice in executing

It is difficult to execute

Soft condition

Excess intimate Drift apart excess Hard condition

Movement reaction

Special ability Basic condition

Body (Se5) Human relations

General ability

Professional knowledge

General knowledge

Interest strength

Interest kind

Risk attitude

Nature feature

Subclass indexes

Ability (Se4)

Knowledge (Se3)

Interest (Se2)

Father indexes

Factor type For the nature of different type can use Carter special character theoretical measure Risk attitude is affected by factor, and it has stability in certain period Person has various types of interest, and we can get its result through testing It is different in the strength of person’s interest and we can get its result through testing General knowledge has universal meaning in working, and we can get its result through testing Professional knowledge that is demanded in special working, and we can get its result through checking certificates or testing It includes person’s occasion ability, learning ability and meeting ability, and its result is difficult to be gotten It is special ability of different fields that are difficult to be gotten It is healthy condition that can be gotten through testing It is the reaction speed for outside that can be gotten through observing The relation among colleague in work is too intimate to affect work Lack the basic affection between colleague The material equipment of necessity lacks with facility It is not enough of information in work and it is not reasonable in the information campaigns Management system is inconsistent with the actual condition of enterprise internal and external environment Management system has not uniform measure in conducted course, and it is obvious unfair It is different for a person to adapt the leading style such as the dictatorship, democracy and pass unchecked Encourage and restrain are transfer and guide the two of personal enthusiasm aspect Self restrains and organizes the balanced problem of restraint Working efficiency is too rapid to adapt

Explanations

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Table II. The basic index system of the competence appraisement

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factors of external environment of person, and the index belongs to the index of dynamic appraisement when combining with the factors of external environment, if the result of dynamic appraisement is according to competence requirement; the index belongs to the index of competence appraisement. (4) Competence appraisement result: because there is a great deal of fuzzy information in the course of human resource appraisement, this paper uses the principle of the biggest subordinate degree of fuzzy comprehensive opinion to determine the result of appraisement. Set up the language of appraisement as qualified completely, qualified, qualified basically, not quite qualified and do not be qualified, and uses P1, P2, P3, P4 and P5 to express the language of appraisement, the set of the language of appraisement is P ¼ {P 1 ; P 2 ; P 3 ; P 4 ; P 5 }; which has only qualified completely, qualified is according to the competence requirement. There is an appraisement subclass that belongs to the competence: P e ¼ {P 1 ; P 2 }.

5. The architecture of enterprise appraisement index of human resource based on competence The appraisement index system is necessary for all appraisement system. Appraisement index system provides a guideline for supervisor to appraise appraisement object, it is a key factor for appraisement system whether is objective and reasonable, and it is a main method to cut down artificial error factor in the course of appraisement. A series of researches have been carried out about the basic quality of person and personnel examination and human being has gotten a series of research accomplishment in this field. In the process of social development, information technology, especially since 1993 internet commercialized, virtual market makes the consumer’s individuation getting regression gradually, at the same time, today the people are realizing that the degree of resource rare is more exigent than ever. This makes the study of enterprise appraisement of human resource of professional development to be an important direction. Now, the result of study combining the professional development with competence is very few, however, the study of combining the professional development with competence is very meaningful because it can objectively solve the problem that is faced with in the current enterprise appraisement of human resource. The enterprise appraisement of human resource follows the logic relation of goal-norm-index, that is to say, the enterprise appraisement of human resource is guided by a certain goal, formed with some norm layer, and every norm layer is divided into a few specific index systems. There are certain limitations of existing personnel examination architecture model in the appraisement of human resource, as the theory of measure the predisposition of person, the model adopt the split and completely aspect scanning appraisement pattern. Therefore, this paper puts forward a kind of architecture model that suits the enterprise appraisement of human resource.

5.1 Existing enterprise personnel check architecture model The existing architecture of enterprise personnel examination is shown in Figure 3.

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Figure 3. The architecture of existing enterprise personnel examination

The architecture model shown in Figure 3 belongs to the logic relation goal-norm-index and split and completely aspect scanning appraisement pattern, the method of calculating the appraisement result is shown in Figure 4. Peng (2002) analyzed basic features and shortcomings of a model for scanning split and full aspects that is a type of methods to measure diathesis of a person. He thought that there are three following basic features. (1) Especially emphasize index split independence, that is to say, the low correlation between indexes is necessary. (2) The viewpoints of overall analysis, that is to say especially notice the integrity of system, and make every index to be considered in the process of appraisement. (3) Establish standard reference system correspondingly, it is very beneficial for the post that determines general principle hold a post qualification condition. Peng considered this pattern had two defects in an actual operation. (1) This pattern did not represent the regularity that person quality structural state is a reaction stimulated by environment. (2) This pattern’s distinguish degree in function of practice is low.

Figure 4. Split and completely aspect scanning appraisement pattern

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There are three aspects that are not suitable for oriented vocational development of enterprise appraisement of human resource in current model of personnel appraisement system. First, in a norm-layer, we do not take time into consideration. Time is an essential factor to realize the purpose of enterprise and individual aim. Some objects are to be realized in current, others will be realized in the future. But the future is uncertain time conception. It needs to be determined by the condition of enterprise and individual. Second, the appraisement of human resource need consider the adaptability between the value of utility and environment. Finally, the utility of human resource is not embodied, especially, under the circumstance of dynamic human resource, enterprise and employee are legally to select each other, and the individual makes decision by the value of utility of human resource, i.e. without considering the factor of professional development. 5.2 The appraisement architecture of enterprise human resource based on competence The appraisement architecture model of enterprise human resource based on competence put forward in this paper is shown in Figure 5. Both the enterprise and the individual can appraise according to the architecture shown in Figure 5, and then measure the value of human resource and make decision according to their principles, respectively. 6. The appraisement model of enterprise human resource based on competence without time factor 6.1 Establishing model Let set A, B, C, and P be the interior environment factor, the outer environment factor, the subjective effort, and competence appraisement comment set of person,

Figure 5. The appraisement architecture model of enterprise human resource based on competence

respectively, P ¼ {P 1 ; P 2 ; P 3 ; P 4 ; P 5 }; then the appraise course enterprise human resource based on competence is: P ¼ f ðA; B; CÞ:

ð1Þ

In equation (1), for the analytical convenience, let C ¼ 1 according to basic assumption; if only appraise A, then it is static appraisement; A £ B implies appraise A under the condition B, and it is dynamic appraisement; when P is the subclass of the appraisement comment set P e ¼ {P 1 ; P 2 }; then P e ¼ f ðA; BÞ is competence appraisement. If the appraisement result of static appraisement is represented with appraisement comment very high, high, normal, low and very low, then because the interior environment of person is the foundation that forms the competence of person, the appraisement result of static appraisement determined, based on the biggest membership degree principle, as low and low very much can be considered as unfit the competence requirement, refuse. Compared with the basic assumption which only have qualified completely and qualified as satisfying competence requirement, the appraisement result of static environment includes very high, high and normal. Obviously the selection range of appraisement results of static appraisement is relative wide than that of competence appraisement. This is because there is the phenomenon called unified reaction when person is in the interactive course with the outer environment, and when unified reaction arises, the person whose appraisement result of static appraisement in general may satisfy the competence requirement. But because the role unified reaction is limited, the probability of the person whose appraisement result of static appraisement is low or very low to be satisfying the competence requirement is very small, and according to the thought of probability theory, it is nearly impossible that small probability incident appears in one experiment. Dynamic appraisement is an appraisement result that considers the factor of the outer environment effecting the interior environment of person. According to the basic index of competence appraisement shown in Table I, we then analyze the influence of the outer environment on the interior environment of person, and the result is shown in Table III. Explanation: “þ ,” “þ þ ” and “þ þ þ ” express having certain influence and influence obviously and influence notably, respectively. The interior environment of person is influenced by the outer environment differently. According to the number of the interior environment influenced notably by the outer environment, we can get through Table II: the leading styles and the encourage goals in viewpoint of value are two, the leading style the psychological factor of human resource, and the encourage goal influences notably the interest of human resource; additionally, human relations influence notably the nature feature of psychological factor. In the interior environment of person, both the interest and psychology of person are influenced notably by the outer environment, while the ability and knowledge of person are influenced notably by the interest and the psychology of person and body is the foundation of competence. In competence appraisement, referring to the iceberg model, divide the appraisement indices into two kinds of indices: dominance and recessive indices, where dominance indices include body, ability and the knowledge of person and these are the three essential factors of the concept of human resource; recessive indices include interest and the psychology of person. Dominance index quantity the degree of

Human resource competence appraisement 301

Table III. The influence of the outer environment on the interior environment of person

Psychology (Se1) Nature feature Risk attitude Interest (Se2) Interest kind Interest strength Knowledge (Se3) General knowledge Professional knowledge Ability (Se4) General ability Special ability Body (Se5) Basic condition Movement reaction þþ þ þ þ þ þ

þ þþ þ þ þ þ þ þ þ

Human relations

þ þ

þ

þ

þ

þþ

þþ þ þ

þþ þ

Outside environment Manage system Carry out Carry out difference injustice

þ þ

þ

þ

þ þ

þ þþ þ þþ

þþ þ þþ þ

þ þ

Viewpoint of value Lead Encourage style goal

þ

þþ

þ

þ þ

Working habit Work Work time efficiency

302

Interior environment

Working condition Hard Soft condition condition

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the value of the utility of human resource, and recessive index influences and decides the exertion of the value of the utility of human resource. We take the assumption that when the dominance index takes certain value, the recessive index will decide the appraisement result of the value of the utility of human resource (competence size). The above-mentioned viewpoint is different from the existing personnel measure and appraisement. In the existing personnel measure and appraisement, the basic conditions such as body, interest, knowledge, ability are taken as independent index systems, and for the treatment of final appraisement result, adopt generally the method of weighted means. According to common knowledge, along with the raise of the level (represented as the membership degree of psychology and interest adapting the outer environment) of the interest and psychology of a person (based on the product of the two) adapting the outer environment, the role that the person can exert in work also raises to a higher level, i.e. the competence level prompts. But the role that person can exert in work is limited, when the role of person reaches certain level, the speed to rise more will be very slow, and tends to a limiting value eventually. Therefore, the competence model of person can be constructed with the curve of correction index. Figure 6 shows the comparison of the competence appraisement model (denoted as A) and the traditional appraisement model (denoted as D). In a traditional appraisement model: Qi ¼ ð1 2 lÞ

m X j¼1

r ij aij þ l

n X

wik uik

Human resource competence appraisement 303

ð2Þ

k¼1

In equation (2), Qi expresses the membership degree of the appraising result subordinating to the ith appraise comment, aij and uik are the degrees that the jth dominance index and the kth recessive index are subordinating to the ith appraisement comment, respectively; rij, wik, l and ð1 2 lÞ are the weights of the jth dominance

Figure 6. The comparison of the competence appraisement model and the traditional appraisement model

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index, the k recessive index, all recessive indices and all dominance indices, respectively, and 0 # l # 1; m X

r ij ¼ 1;

j¼1

304

n X

wik ¼ 1:

k¼1

According to the biggest membership degree principle, the appraise result in traditional appraisement model is finally determined as: Qk ¼ max{Q1 ; Q2 ; . . . ; Qr }

ð3Þ

According to equation (3), the appraisement result belongs to the kth appraisement comment relatively. There is, in a competence appraisement, an appraisement result synthetic general model that is constructed as:

Pi ¼

n Y 9 pik 8 m m X X > > > k¼1 > > ðr ij aij Þ ðwik uik Þ> > >1 2 ! > > = < n Y j¼1 k¼1 " #n 1 2 bi p i ¼ 1 2 m > > X > > i¼1 > > > > 1 þ ðr ij aij Þ > > ; :

ð4Þ

j¼1

In equation (4), pi expresses the degree that the appraisement result is subordinate to the ith appraisement comment; aij and uik are the degrees that the jth dominance index and the kth recessive index are subordinates to the ith appraisement comment, respectively. Sort uik descendent by the satisfactory degree for recessive indices, i.e. the satisfactory degree of uði21Þk is better than that of uik, and stipulate pik ¼ max{u1k ; u2k ; . . . ; uik }; rij is the weight of the jth dominance index, and m X

r ij ¼ 1;

j¼1

n is the relevant coefficient of appraising working post, n $ 1; and the higher the coordinate requirement of the working post, the bigger n. For the case of decision, management, technical and schoolwork post, n can take values 5, 3, 2, and 1, respectively. Explanation of equation (4): (1) The bigger the appraisement result value with respect to dominance indices, the bigger the result of m X

r ij aij ;

j¼1

and the higher the competence of latent explanation, i.e. with the same recessive index, the competence appraisement result is relatively better. Since equation (4) is actually a monotonous increasing function, it satisfies the above-mentioned condition.

(2) When ;uik ¼ 0; there is no competence, that is P i ¼ 0: (3) When n X

r ij aij ¼

j¼1

m X

Human resource competence appraisement

wik uik ¼ 1;

k¼1

both the outer environment and the interior environment of person reach the biggest membership degree, and now the membership degree of competence subordinating to “qualified very much” should be 1. (4) When n Y

pik ¼ 1;

k¼1

all the recessive indices reach optimum state, and now Pi is determined by the dominance appraisement index score and the appraisement post requirement together. (5) The requirement for recessive indices is affected apparently by the outer environment, i.e. the competence will seriously drop if not fit the environment any more. For the factors of the inside environment of person that are not affected apparently by outside environment, put them aside. So when appraising a person or a working post, it needs to order and classify recessive indices combined with an actual condition. For different cases, the significance that the recessive indices affected by the outer environment is not identical. In a competence appraisement model, the final appraise result can also be determined according to the biggest membership degree principle in the same way: P k ¼ max{P 1 ; P 2 ; . . . ; P r }

ð5Þ

According to equations (4) and (5) the appraisement result belongs to the kth appraisement comment relatively. 6.2 Application of competence appraisement model Appraise the dominance indices (knowledge, ability and body) in the interior environment of a person (or many persons) according to “the basic index system of the competence appraisement of Table I”. Set the appraisement comments as “very good (very high)”, “good (high)”, “general (normal)”, “bad (low)”, “very bad (very low)”, i.e. the appraisement comment set V ¼ {V 1 ; V 2 ; V 3 ; V 4 ; V 5 }; and according to the static appraisement result composition method, the single factor appraisement matrix can be obtained as follows:
 ð6Þ Q ¼ 0:3 0:8 0:4 0 0 To establish membership functions for its recessive indices from the viewpoint of psychology and interest, make satisfy very much takes value 1, not satisfy at all takes value 0, and the corresponding membership function value according to satisfactory

305

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level is shown in Figure 7. See Xu et al. (2004) for the research work in the aspect of satisfaction degree. The recessive index psychology includes nature feature and risk attitude, the index interest includes interest kind and interest strength, expressed as ui1, ui2, ui3 and ui4. Appraise recessive indices according to appraisement comments: “satisfy very much”, “satisfy”, “general”, “do not satisfy” and “do not satisfy very much.” Suppose the single factor appraisement matrix of recessive indices 1 0 0:3 0:6 0:2 0 0 C B B 0:9 0:1 0 0 0C C B ð7Þ R¼B C; B 0 0:3 0:6 0:2 0 C A @ 0 0:2 0:6 0:3 0 and 0 Ru ¼ @ 0:25

4 X

u1k

0:25

4 X

k¼1

u2k

0:25

k¼1

4 X

u3k

0:25

k¼1

4 X

u4k

0:25

k¼1

4 X k¼1

1 u5k A;

then
Ru ¼ 0:3

0:3

0:35

 0 :

0:125

ð8Þ

Note 0 Rp ¼ @

4 Y

p1k

k¼1

4 Y k¼1

p2k

4 Y

p3k

k¼1

4 Y

p4k

k¼1

4 Y k¼1

1 p5k A;

then
Rp ¼ 0

Figure 7. The membership function of recessive indices based on the degree of satisfaction

0:0324 0:1944

0:1944

 0 :1944 :

ð9Þ

Assuming what to be appraised is technical post, set n ¼ 2; then
 P ¼ 0 0:0459 0:1480 0 0

ð10Þ

According to the biggest membership degree principle, the competence appraisement result of this person is determined as “relative general”. If let: 1 0 1 0 0 0 0 C B B1 0 0 0 0C C B R0 ¼ B ð11Þ C B1 0 0 0 0C A @ 1 0 0 0 0
R0p ¼ 1

1

1

 1 :

1

ð12Þ

Similarly let n ¼ 2; then:
P 0 ¼ 0:586

0:691

0:490

0

 0 :

ð13Þ

According to the biggest membership degree principle, the competence appraisement result of this person is “relative good (high)”. But since the membership degree of the recessive indices subordinating to “satisfy very much” are all 1, the membership degree of the appraisement result of this person subordinating to “very good (high)” is higher apparently than that obtained by the static method. For this person, if the last result (6) of the static appraisement changes showed as type (14): Q0 ¼ ð 0:4

0:8

0:4

0

0Þ

ð14Þ

and the calculation result according to type (4) under the same condition is shown as type (15):
 P 00 ¼ 0:694 0:691 0:490 0 0 : ð15Þ According to the biggest membership degree principle, the competence appraisement result of this person is “very good (high)”. If 1 0 0 0 0 0 1 C B B0 0 0 0 1C C B 00 R ¼B ð16Þ C; B0 0 0 0 1C A @ 0 0 0 0 1 then no matter what the static appraisement result is and what value n takes, there is
 P 00 ¼ 0 0 0 0 a ð17Þ where a [ ½0; 1
:

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308

According to the biggest membership degree principle, the competence appraisement result of this person is “very bad (low)”. This implies that when a person do not satisfy the outer environment completely, the competence of this person is “very bad (low)”. 7. Composition calculation of enterprise human resource appraisement result based on the competence with time factor In the appraisement of enterprise human resource based on competence, we should consider the time discrepancy in the aspect of use of different types of human resource. For instance, some human resources are important for enterprise now, but their role in future may not be quite good through forecast; while some other human resources may not be very important for enterprise by now, but they can do great contribution for enterprise in the future that can be foreseen. In fact it is exactly based on this kind of consideration for a lot of enterprises to carry out the strategy of reserving talents for developing needs. Therefore, in the appraisement of enterprise human resource, it needs to consider the time factor. The appraisement general model of enterprise human resource without time factor based on competence that analyzed above is the foundation of the appraisement of enterprise human resource with time factor. On this basis, the appraisement model of enterprise human resource with time factor is put forward in this section. In general, the value used for the different types of human resource is fluctuation, which is shown in Figure 8. There are three types of human resource according to the relative importance of human resource’s factors of strength, knowledge and ability, the human resources. They are defined as physical type, knowledge type and ability type of human resource, respectively. For different types of post (such as decision, management, technical and schoolwork post), there exist some differences, such as the property contents of human resource, understanding time and so on. Figure 9 shows the time discrepancy needed for different types of post investigation human resource. When considering human resource with time factor, equation (1) becomes: P ¼ f ðA; B; C; tÞ:

ð18Þ

In equation (18), t is the using (working) time of human resource in the enterprise, t [ ½0; T
where T is the biggest using (working) time of human resource in the

Figure 8. The fluctuation of different types of human resource

enterprise, whose value can be determined according to experiences or the average social statistical result. With the same assumption as that of the appraisement general model of enterprise human resource without time factor based on competence, let C ¼ 1: From theoretical point of view, if the time variable is continuous, equation (18) can be expressed as: Z T PðtÞ dt: ð19Þ P¼

Human resource competence appraisement 309

0

In equation (19), P(t) expresses the appraisement result of enterprise human resource at t, and Z T 0

expresses the composition of the appraisement result from time 0 to T. For the appraisement result showing in numeric value, equation (19) can be expressed as: P ¼ t0 Pð0Þ þ t1 Pð1Þ þ · · · þ tn PðnÞ ¼

n X

ti PðiÞ

ð20Þ

i¼0

In equation (20), n X

ti ¼ 1;

i¼0

and i expresses the ith appraisement time. If t0 . 0:5; then the appraisement is current-dominant, if t0 , 0:5; then the appraisement is future-dominant, if t0 ¼ 0:5 then the appraisement has both the current and the future in consideration. In the course of enterprise human resource appraisement, natural language is concerned with the appraisement information. Let X ¼ {pi }ði [ {0; 1; . . . ; T}Þ be the limited and ordered language terminology on the interval [0, 1], where pi is a language variable, and the number of linguistic variables is odd, if X has the following features: (1) Order character: if i $ j; then pi $ pj : (2) Inverse operation: if j ¼ T 2 i; then negðpi Þ ¼ pj :

Figure 9. The investigation time of different type post

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310

(3) Maximum operation: if pi $ pj ; then maxðpi ; pj Þ ¼ pi : (4) Minimum operation: if pi $ pj ; then minðpi ; pj Þ ¼ pj : Then the composition of language value appraisement can be carried out by using the LOWA operators, the research work in the aspect of LOWA can be obtained in Herrera et al. (1995, 1996, 1997) and Herrera and Herrera-Viedma (2000), and equation (18) can be expressed as: P ¼ C{tk ; pk ; k ¼ 1; 2; . . . ; n} ð21Þ ¼ t0 ^Pð0Þ%ð1 2 t0 Þ^C{bh ; ph ; h ¼ 2; . . . ; n} where,

bh ¼

th : n X ti i¼2

when n ¼ 2; P is defined as: P ¼ t0 ^Pð0Þ%ð1 2 t0 Þ^Pð1Þ ¼ t0 ^pi %ð1 2 t0 Þ^pj ¼ pk

ð22Þ

where k ¼ min{T; i ¼ roundðw1ðj 2 iÞÞ}; j $ i: About the weight, it can be determined by the expert consulting or by other special methods. 8. The design of process of enterprise appraisement index of human resource based on competence According to the thought of competence, in the construction of enterprise appraisement index system of human resource, the staffs who can obtain high performance and be fit for specific position and circumstance is selected by applying the aim that appraisement index and assessment technique will realize. It is necessary for an enterprise to select the staffs that are the fittest for the given position and circumstance by the thought of competence. Meanwhile, as for competence, we take the basic condition of staff into consideration, so the staff we selected by the thought of competence is also fit for his utility, that is to say, the enterprise and the individual all reach at the maximum profit, which is consistent with the thought of oriented professional development. It is an important link for the study of enterprise appraisement of human resource to design the appraisement index. Whether the design of appraisement index is scientific and reasonable or not has direct influences on the utility of appraisement result. This section is devoted to the method and steps of the enterprise appraisement index design of human resource. 8.1 The factors of appraisement index Every personnel examination should have its own measure index, only by which can we make personnel examined, supervisor, examination method and the result of examination compatible. Hence, a complete appraisement index of personnel examination should include three aspects: measure factors, measure sign and measure scale. The appraisement index of personnel examination is by the form of

measure factors, measure sign and measure scale to turn the measure object into the content of appraisement index or the factors, and the appraisement standard into measure sign and measure scale, furthermore, makes the measure object and the appraisement standard together with each other to compare and assess. Example 1 (Wang, 2002), charming and inspiring force to measure comment index, as shown in Table IV.

Human resource competence appraisement 311

8.2 Absolute and relative appraisement Absolute appraisement is a distance or appraisement which supervisor uses the same appraisement standard to compare different personnel examined. Relative appraisement is a distance or appraisement which supervisor compares different personnel examined with each other and according to the result compared the standard with character of personnel examined to order. If relative appraisement is performed according to the same standard of appraisement, the result of relative appraisement can indicate the difference between different appraisement objects. On the contrary, if it does not according to the same standard of appraisement, the result of relative appraisement cannot indicate the difference between different appraisement objects. Absolute appraisement and relative appraisement have different factors in the appraisement index. In an absolute appraisement, the reference standard is given, take the score of an examination as an example, if we consider that the score is 60, then the score is qualified for our requirement and the score is considered strict with reference standard. There is no strict reference standard in relative appraisement, for example, there are three students A, B and C, their credits of the same curriculum are 50, 40, and 30, respectively, if we stratify them into two levels: A is better than B, B is better than C, in fact, if we appraise them by the standard absolute appraisement (score 60), the result is that they are nonconformity. In addition, there are incomparable problems in relative appraisement, that is to say, if we appraise object according to different appraisement object and appraisement standard, then we will get lost the comparison, for instance, in 1,000 m running competition, if we let different ages of boys and girls take part in the same item, the result we obtain will get lost the comparison, such as, A: a 13-year old boy finished the competition in 6 minutes, and B: a 9-year old girl finished in 7 minutes, we cannot tell who is better than other. Obviously, absolute appraisement will be more objective than the relative appraisement, but relative appraisement based on the reference standard can select the human resource who not only according to the appraisement criterion but relative much better also from the numerous candidate.

Measure factor Measure content

Measure scale

Influence

Proficient General Very bad Proficient General Very bad

1 Good at persuading, good at earning support 2 Can adjust appearance in order to attract audience 3 Can use complex means in order to indirectly influence the public opinion 4 Can plan eye-catching incident in order to explain the main points of problem

Proficient General Very bad Proficient General Very bad

Table IV. Influence measure comment index design example

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312

8.3 Principle of construction of appraisement index Whether an appraisement index is reasonable or not depends on the quality of enterprise appraisement of human resource directly. The principle is the same to the construction of enterprise appraisement of human resource and personnel examination index. Mainly, there are five general principles. (1) The appraisement purpose and object should be defined. (2) The design of appraisement contents should be reasonable, and the appraisement factors of appraisement index should be consistent with appraisement sign and scale. (3) The terms used in appraisement should be easy to understand without vagueness. (4) The appraisement sign should be quantified, try to avoid discrepancy due to the standard of subjective judgement and make every essential factor easy to operate and objectivism. (5) The system of appraisement index is required relative independence and unities, different appraisement factors should keep relative independent, and the appraisement index of the same appraisement factor should also keep

Figure 10. The design process of enterprise appraisement of human resource

relative independent, the permutation of difference of appraisement factors should reflect the purpose of appraisement which is expected. 8.4 The enterprise appraisement index design process of human resource The enterprise appraisement index design process of human resource is shown in Figure 10. 9. Conclusion The enterprise appraisement of human resource is significant not only of enterprise but also of staff, at the same time, this is also a complex systematic project. It is an important research direction for management theory and especially for human resource management to develop appraisement of human resource reasonable and scientifically. In this paper, a model of enterprise appraisement of human resource based on competence is given. The results obtained in this paper provide a foundation to establish relatively reasonable and efficient enterprise appraisement system of human resource. Moreover, in order to build facing professional development of enterprise appraisement theory of human resource, this paper has entered more thorough research in the aspect of the enterprise human resource competence appraisement, and established the model of enterprise human resource competence appraisement, index system, application and design method. Therefore, these research accomplishments have offered necessity to further study the enterprise appraisement information processing system of human resource. References Baron, R.A. (2003), “Human resource management and entrepreneurship: some reciprocal benefits of closer links”, Human Resource Management Review, Vol. 13 No. 2, pp. 253-6. Boyatzis, R.E. (1982), The Competent Manager, A Model for Effective Performance, McBer and Company, Boston, MA. Dennis, B.A., Debra, A.L. and Charlie, M. (2002), “Using job satisfaction and pride as internal-marketing tools”, The Cornell Hotel and Restaurant Administration Quarterly, Vol. 43 No. 2, pp. 87-96. Drucker, P.F. (1954), The Practice of Management, Harper & Brothers, New York, NY, p. 264. Grabot, B. and Letouzey, A. (2000), “Short-term manpower management in manufacturing systems: new requirements and DSS prototyping”, Computers in Industry, Vol. 43 No. 1, pp. 11-29. Gunderson, M. (2001), “Economics of personnel and human resource management”, Human Resource Management Review, Vol. 11 No. 4, pp. 431-52. Hagan, C.M. (1996), “The core competence organization: implications for human resource practices”, Human Resource Management Review, Vol. 6 No. 2, pp. 147-64. Herrera, F. and Herrera-Viedma, E. (2000), “Linguistic decision analysis: steps for solving decision problems under linguistic information”, Fuzzy Sets and Systems, Vol. 115 No. 1, pp. 67-82. Herrera, F., Herrera-Viedma, E. and Verdegay, J.L. (1995), “A sequential selection process in group decision making with a linguistic assessment approach”, Information Sciences, Vol. 85 No. 4, pp. 223-39.

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Herrera, F., Herrera-Viedma, E. and Verdegay, J.L. (1996), “A model of consensus in group decision making under linguistic assessments”, Fuzzy Sets and Systems, Vol. 78 No. 1, pp. 73-87. Herrera, F., Herrera-Viedma, E. and Verdegay, J.L. (1997), “Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making”, International Journal of Approximate Reasoning, Vol. 16 Nos. 3/4, pp. 309-34. Jeong, B. (2002), “Measurement of human capital input across countries: a method based on the labourer’s income”, Journal of Development Economics, Vol. 67 No. 2, pp. 333-49. Kanungo, R. and Misra, S. (1992), “Managerial resourcefulness: a reconceptualization of management skills”, Human Relations, Vol. 45 No. 12, pp. 1311-32. Kaufman, B.E. (2001), “Human resources and industrial relations: commonalities and differences”, Human Resource Management Review, Vol. 11 No. 4, pp. 339-74. Liu, X.H., Xu, Y. and Liu, X.M. (2002), “Human resource systematic management in virtual enterprise”, Reform of Economic System, Vol. 20 No. 3, pp. 49-52 (in Chinese). McClelland, D.C. (1973), “Testing for competence rather than for intelligence”, American Psychologist, Vol. 28, pp. 1-4. Parry, S. (1998), “Just what is a competency? (And why should you care?)”, Minneapolis. Training, Vol. 35 No. 6, pp. 58-64. Peng, Z.L. (2002), “Enterprise manager appraises system with encourage machine made research – theory”, Model and Method, Huaxia press, Beijing. Pinker, E.J. and Larson, R.C. (2003), “Optimizing the use of contingent labour when demand is uncertain”, European Journal of Operational Research, Vol. 144 No. 1, pp. 39-55. Remus, I. and Timothy, A. (2002), “Judge, understanding the dynamic relationships among personality, mood, and job satisfaction: a field experience sampling study”, Organizational Behavior and Human Decision Processes, Vol. 89 No. 2, pp. 1119-39. Schein, E.H. (1978), Career Dynamics: Matching Individual and Organizational Needs, Addison-Wesley Publishing Company, Reading, MA. Wang, L. (2002), Practical Personnel Measure (in Chinese), Economic Scientific Press, Beijing. Wang, Y. and Yao, Y.D. (2003), “Sources of China’s economic growth 1952-1999: incorporating human capital accumulation”, China Economic Review, Vol. 14 No. 1, pp. 32-52. Xu, Y., Zeng, X. and Ruan, D. (2004), “A comprehensive evaluation system based on complex uncertain information”, Journal of Donghua University of China, Vol. 21 No. 3, pp. 30-4. Further reading Frederick, E.S. (1985), Human Resource Management, 2nd ed., Reston publishing company, Inc., New York, NY. Liu, X.H., Xu, Y. and Chen, S.W. (2004), “A kind of information processing method in linguistic-value appraisement of enterprise human resource”, Journal of Donghua University of China, Vol. 21 No. 3, pp. 35-9. (Xiaohong Liu was born in 1970, and received the BS degree in environmental engineering and the Master degree in management science and engineering from Nanchang Aviation Industry Institute and Sichuan University, People’s Republic of China, in 1991 and 2000, respectively. He is an Associate Professor at Chengdu University of Technology and a PhD researcher at the Intelligent Control Development Centre, Southwest Jiaotong University, People’s Republic of

China. His focusing research is on human resource management and its information processing, theory and application of fuzzy control and intelligent control. He has published over 20 papers. Da Ruan received a BSc Degree in Applied Mathematics from Fudan University, Shanghai in 1983, a Certificate in Management from Leuven University, Belgium in 1990 and a PhD Degree in Mathematics from Gent University, Belgium in 1990. He was a Teaching Research Assistant at Fudan University from 1983-1986, a PhD Researcher at Gent University from 1987-1990, a Post-Doctoral Researcher at the Belgian Nuclear Research Centre (SCK·CEN) from 1991-1993 and since 1994 has been a senior researcher and FLINS Project Leader at SCK·CEN. He was a guest research scientist at the OECD Halden Reactor Project (HRP), Norway from April 2001 to September 2002. He is a principal investigator for the research project on intelligent control for nuclear reactors at SCK·CEN and for the research project on computational intelligent systems for feedwater flow measurements at HRP. His major research interests lie in the areas of mathematical modelling, computational intelligence methods, uncertainty analysis and information/sensor fusion, decision support systems and soft computing applications to information management, robotic systems, nuclear power plants, and safety related engineering fields. Yang Xu received the BS degree in mathematics and the PhD degree in management engineering from Southwest Jiaotong University, People’s Republic of China , in 1981 and 1996, respectively. He is currently a Full Professor with South-West Jiaotong University, Chengdu, Sichuan, China. His focusing research is on applied mathematics, logic algebra, algebraic logic, uncertainty inference, theory and application of fuzzy control and intelligent control, uncertainty game and decision-making, and intelligent computer. He has published over 280 papers, and he has edited and published 8 books. He has been the Director or a Main Researcher on 33 projects of academic research and applications.)

Human resource competence appraisement 315

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Outsourcing logistics activities in Turkey

316

Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

E. Aktas and F. Ulengin

Abstract Purpose – This research aims to determine the current situation of outsourcing logistics activities in Turkey, a country which has a great potential for logistics activities among the surrounding continents because of its geographical location. Design/methodology/approach – Survey analysis was conducted with 250 of the top 500 Turkish firms specified by the Istanbul Chamber of Commerce for the year 2001. These firms are selected based on the firms’ total sales volume, profitability, and other financial performance indicators. The responses were evaluated statistically using SPSS software. Factor and cluster analyses were utilized to determine the behavior of respondents against their logistics service providers and to categorize the respondents. Findings – The focus of the part of the survey is basically in the following areas: logistics functions outsourced by Turkish firms; the extent to which logistics functions in general and transportation functions in particular are outsourced by Turkish firms; and the criteria used to select and evaluate the performance of the outsourcing firms. The performance of the first three outsourcing firms currently used by Turkish firms. Originality/value – This study shows that the power of third party logistics (3PL) firms in Turkey is underestimated. The firms that outsource their logistics activities in Turkey are 95 percent foreign capitalized. Turkish businessmen think that they should do their business themselves and they are not aware of the benefits of outsourcing logistics activities. In fact, in selecting the transportation carrier, they consider different criteria but the general tendency is either to select the carrier that has a good reputation and/or the one which is easy to collaborate with. Keywords Outsourcing, Logistics, Transportation Paper type Research paper

The Journal of Enterprise Information Management Vol. 18 No. 3, 2005 pp. 316-329 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410390510591996

Introduction Logistics is that part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements (www.clm1.org). Owing to the globalization of sources, manufacturing and production, distribution companies in recent years have been adopting the logistics management view to guide their business operations. The adoption of logistics concepts has increasingly forced such companies to focus on their core business and, at the same time, to outsource their transport and other logistics activities. This has resulted in an increasing demand for logistics services that has generated, in past decades, the creation of a worldwide growing market in which specialized service providers, which are called third party logistics (3PL) providers, operate. Recently, it has been highlighted that successful logistics management depends more and more on the performance of the 3PLs. Accordingly, they can play a key integrative role in logistics functions by the management of information flows connected with the entire delivery of goods. This has

created an increasing need to support customers’ logistics requirements through the effective use of information and computer technologies. Bendor-Samuel (1998) asserts that outsourcing provides a certain power that is not available within an organization’s internal departments. This power can have many dimensions: economies of scale, process expertise, access to capital, access to expensive technology, etc. Another possible benefit is that outsourcing provides companies with greater capacity for flexibility, especially in the purchase of rapidly developing new technologies, fashion goods, or the myriad components of complex systems (Carlson, 1989; Harrison, 1994). One of the advantages of using 3PL results from economies of scale (merits from large truck fleets, warehouses, etc.) and economies of scope, which encourage firms to increase net value by reducing costs. The effects of these economies depend on the type of 3PL provider (e.g. IT-equipped, marketing-based, non-asset-based, etc.) Competent 3PL providers possess high coordination ability, enabling them to find reliable partners or sub-contractors, and to efficiently manage the inter-firm flow of goods. Such ability can be developed through experienced 3PLs. Likewise, by outsourcing logistics activities, firms can save on capital investments, and thus reduce financial risks. Investment on logistics assets, such as physical distribution centers or information networks, usually needs large and lump sum costs, which involves financial risks. Furthermore, the 3PL provider can spread these risks by outsourcing to sub-contractors. In developed countries, transport carriers and logistics service providers are expanding their services into various areas that traditionally belonged to their customers upstream as well as downstream. This outsourcing trend is a huge challenge for operators but is also a great opportunity for enlarging their base for business activities. To be able to carry out these new services effectively, significant requirements are put on development for appropriate processes, capability of collaborating and use of advanced information technology. On the other hand, as the world becomes more globally integrated and the boundaries between countries and cultures disappear, many developing countries, including Turkey, are turning into attractive centers for international firms because of their geographical locations, low working fees and high potential for market extensions. However, a previous study shows that in Turkey, outsourcing is still solely based on transportation (Ulengin and Ulengin, 2003). As can be seen from this research, many Turkish firms understand logistics services as taking the transportation order from the manufacturer and delivering the goods to destination points, without thinking about the warehouse design, the optimum location of the warehouse or of inventory management. Such ways of thinking are concerned only with one side of the subject and reduce logistics services to a narrow transportation perspective. The main focus of this particular paper is to analyze the current as well as the future state of Turkish firms in terms of their use of transport carriers and 3PL providers.

Literature review The operational structure of many companies in the face of globalization demonstrates that long-term cooperation agreements between buyers and sellers are increasingly

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common. These benefits have inspired production companies to establish strategic relationships with external third-party service providers (3PL). There has been considerable interest worldwide in the last few years in the growth of 3PL providers. These firms typically provide some of the following services: warehousing operations, freight payments, carrier selection and rate negotiation. In addition, 3PL firms may develop information systems and manage inventory and customer order fulfillment (Golop and Reagan, 2001; Boyson et al., 1999). Several recent studies have addressed the issue of growth in the 3PL market in detail. A study by Murphy and Poist (1998) provides a review and synthesis of research on this topic. Their study suggests that while current use is fairly low, the majority of users of 3PL services will increase such use in the near future. Traditionally, 3PL services are provided by the organization of the shipper (Lieb and Randall, 1996). The next step in the evolution is that freight transport and forwarding firms, which handle logistics operations on behalf and on credit of the shipper, can be called on as the 3PL providers of the first generation (Berglund et al., 1999). The fourth party logistics (4PL) provider integrates the logistics services provided to the shipper as part of a partnership, managing and optimizing the whole supply chain (network), including both operational and strategic levels (Magill, 2000). Bade and Mueller (1999) define the 4PL firm as the Supply Chain Integrator (SCI), managing the firm’s own resources, skills and knowledge, as well as its technologies, combining them with sub-suppliers for delivering the holistic supply chain customers. Recent studies performed in Europe in the same period report that market growth has not been as rapid as predicted in earlier studies (Virum, 1993). Parker (1999) and Stone (2000) report that while European users of 3PL services are satisfied with services received, they have not, in general, increased their use of such services during the last few years. However, many have increased the breadth of services purchased beyond warehousing and transportation. Skjott-Larsen’s (2000) evolution model for 3PL logistics companies consists of the integration rate with the customer’s business and the specialization of assets. Schary and Skjott-Larsen (2001) claim that logistics services in Europe have shifted, first from the market transaction to the outsourcing of freight transport and warehousing, and then to 3PL and 4PL companies. Today, in the USA, manufacturing is the industry sector most likely to outsource, with durable goods accounting for 39 percent of all activity, and nondurable goods accounting for 25 percent (Zhu et al., 2001). In addition, with a global outsourcing market estimated at £188 billion in 1998, and with annual growth rates of 15 percent (Coombs and Battaglia, 1998), the distinction between economic activities in different sectors has become blurred (McCarthy and Anagnostou, 2003). Although outsourcing is undertaken by many organizations to control or reduce costs, there is some evidence that it does not decrease costs as expected, and in some cases, actually increases costs. For instance, when an item is outsourced, the assumption is that the supplier’s costs and required contribution is less than and will continue to be less than the cost of internal provision. A survey based on 1,000 managers worldwide by the PA Consulting Group (PACG) revealed that only 5 percent of organizations gained high levels of economic benefit from outsourcing (PA Consulting Group (PACG), 1996) and that 39 percent of organizations admitted “mediocre” economic benefit. It is necessary but not easy to establish a reliable and

cost-effective partnership between the firm and the 3PL provider. In order to establish a reliable partnership, efforts should be made in two stages; 3PL provider selection and contract signing. First, in the stage of selecting a new partner, it is important to select the 3PL provider which has the ability to provide better services. To do this, complex selection procedures are necessary to identify their ability. However, the complex selection procedures may involve additional transaction costs. Second, it is important to establish a system to maintain their reliable partnership once the 3PL partner is selected; information sharing and apparent risk sharing between parties is always required. This would also involve additional transaction costs. Constructing a risk sharing scheme between the firm and the 3PL provider is critical in establishing reliable partnerships. As can be seen from a survey of the literature, past studies on outsourcing and supply chains generally provide information about developed countries. There are very few studies based on developing countries’ current supply chain and logistics activities (Sohail and Sohal, 2003, Ulengin and Ulengin, 2003). Sohail and Sohal (2003) examine 3PL services in Malaysia and indicate that a number of operating units in many Malaysian firms utilize the services of logistics providers, and have being doing so for several years. Ulengin and Ulengin attempt to provide a perspective for the current status of logistics activities in Turkey. In this research, the cluster analysis conducted shows that it is possible to categorize Turkish firms as “modern” or “traditional” firms; “modern” firms outsource their logistics activities more than “traditional” firms. In traditional firms, logistics comes fourth in terms of importance, after manufacturing, marketing, and purchasing, while it is second for modern firms, coming just after sales. The above-mentioned study also demonstrated that outsourcing is generally understood as transportation. That is why this paper analyzes the current state as well as the future of general outsourcing activities in Turkish firms in more detail, but is especially focused on the outsourcing of transportation activities.

Methodology A survey analysis was conducted with 250 of the top 500 Turkish firms specified by the Istanbul Chamber of Commerce for the year 2001. The Istanbul Chamber of Commerce lists and evaluates 500 firms every year, based on the firms’ total sales volume, profitability, and other financial performance indicators. Questionnaires were sent by fax to the respondent group, which was composed not only of large scale firms but also of those which have continuous growth. A total of 48 questionnaires were returned, representing a 19.2 percent response rate. The questionnaires were based on those proposed by Lambert and Stock (1999) but changes were made to adopt them to Turkish firms. This paper only takes into account the outsourcing part of a large survey that also investigates the current status of all the logistics functions conducted by the firms. The focus of the part of the survey analyzed in this study is basically in the following areas: . logistics functions outsourced by Turkish firms; . the extent to which logistics functions in general and transportation functions in particular are outsourced by Turkish firms;

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.

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the criteria used to select and evaluate the performance of the outsourcing firms; and the performance of the first three outsourcing firms currently used by Turkish firms.

The responses were evaluated statistically using SPSS software. Factor and cluster analyses were utilized to determine the behavior of respondents against their logistics service providers and to categorize the respondents. Research findings General characteristics of the firms The respondent firms were mainly from the food and beverage sector (20.1 percent), followed by textile (16.7 percent), automotive (12.5 percent), chemistry-plastics (12.5 percent), and iron-steel (0.08 percent) industries. The main customers of the surveyed firms were “other firms” (52.1 percent). The number of employees employed by the firms was between 500 and 999 (42.1 percent) in the main. More than half of the respondents were small and middle-scale firms and did not have a partnership with foreign firms (54.2 percent). Annual gross incomes were generally less than $200 million (85.7). The average annual sales volume of the respondent firms was $1.8 million, and the average number of years in business was 28. Gross sales had increased by 20 percent in the last five years, which showed us that despite the economic crisis, the rate of sales have increased in Turkey. Average annual transportation costs were about $1.6 million. A summary of the general characteristics of the firms is given in Table I. Table I shows the percentage of respondents in each employee number group and the number of respondents that outsource their logistics activities in each employee group. The scale of the firms affects the existence of the logistics department (corr. 0.078, sig. 0.000). There is no significant relationship between outsourcing decision and the scale of the firm (corr. 0.021, sig. 0.905). However, the outsourcing level shows a significant difference according to the existence of a logistics department (corr. 0.137, sig. 0.000). In Table II, the respondents are grouped with respect to their employee number. The average years in business for the respondents is also exhibited here according to the percentage of respondents and number of respondents that outsource their logistics activities in each employee number group.

Employee number

Table I. Employee numbers and number of respondents outsourcing

,100 100-249 250-499 500-999 1,000-2,499 2,500 and over

Percentage of respondents

Number of respondents outsourcing

2.6 2.6 18.4 42.1 18.4 15.8

1 1 7 14 7 5

Table III represents the number of employees in the logistics department with respect to total employee number. In the third column, the percentage of respondents is given and in the fourth column the number of respondents outsourcing is given. In Table IV, the average sales volume of the respondents is evaluated with respect to employee numbers and the number of respondents outsourcing and the percentage of the respondents are also given. Table V shows the average endorsement value of the respondents with respect to their employee numbers. Also, the number of respondents outsourcing and the

Employee number ,100 100-249 250-499 500-999 1,000-2,499 2,500 and over

Employee number

Years in business

Percentage of respondents

Number of respondents outsourcing

1 40 25.4 31.1 46.1 32.2

0.03 0.03 0.19 0.42 0.19 0.14

1 1 7 14 7 5

Number of employees in logistics department

Percentage of respondents

Number of respondents outsourcing

– – 8 16 68 88

0.05 – 0.2 0.4 0.2 0.15

1 – 4 7 4 3

,100 100-249 250-499 500-999 1,000-2,499 2,500 and over

Employee number ,100 100-249 250-499 500-999 1,000-2,499 2,500 and over

Employee number ,100 100-249 250-499 500-999 1,000-2,499 2,500 and over

Sales volume

Percentage of respondents

Number of repondents outsourcing

25£ 106 21£ 106 51£ 106 59£ 106 68£ 108 20£ 107

0.04 0.04 0.22 0.33 0.26 0.11

1 1 6 9 7 3

Endorsement

Percentage of respondents

Number of repondents outsourcing

25£ 106 21£ 106 66£ 106 79£ 106 17£ 107 18£ 107

0.04 0.04 0.26 0.33 0.22 0.11

1 1 7 8 6 3

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Table II. Average years in business

Table III. Number of employees in logistics department

Table IV. Average sales volume

Table V. Average endorsement

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percentage of respondents answering the endorsement question is given by grouping them according to employee numbers. General outsourcing perspective in Turkish firms In a majority (47 percent) of the respondent firms, purchasing, supply, inventory management, order fulfilling, customer services, production scheduling and negotiations with salespersons are accepted as in-house logistics activities. In a three-year time period, these firms do not consider outsourcing the logistics activities mentioned above. Similarly, warehousing activities are held by the firm itself in 76 percent of the firms. Only 24 percent outsource warehousing to other logistics firms and 23.5 percent of the respondents intend to outsource their logistics activities within a three-year time period. Nearly 93.5 percent of the respondents outsource their transportation activities. It can be seen that Turkish firms in particular outsource transportation activities and the direct participation of manufacturer firms in transportation is expected to decrease visibly within a three-year time period. Therefore the current 3PLs, in fact, play the role of freight transporters. Outsourcing in transportation activities As can be seen from the general perspective, transportation has a dominant role in outsourcing activities. That is why a more detailed analysis regarding transportation outsourcing is provided in this study. Fifty-four percent of Turkish firms choose to work with a 3PL firm in their transportation activities from supplier to manufacturer and 60 percent use a 3PL for the transportation from manufacturer to customer. From supplier to manufacturer (88.52 percent) and from manufacturer to customer (88.87 percent), the materials and goods are mainly transported by motor vehicles. The average value of the transported goods is about $100,000. The fact that the motor vehicles are preferred to other means of transportation is not a surprising result if today’s circumstances are taken into account. By the end of 2001, the number of firms that had licenses from the Ministry of Transportation for international highway transportation was 892, their fleet having a total capacity of 711,000 tones (www.mfa. gov.tr/Turkce/grupe/ues-7/Uluskarayolutasima.htm). Factors affecting the satisfaction from the 3PL providers in transportation Factor analysis is conducted in order to understand the real factors underlying the selection of the carriers. A factor is a mother-concept which gives a summary of a subgroup of indicators that largely measure the same (see Hair et al., 1992 for details of factor analysis). As can be seen in Table VI, the factor analysis shows that it is possible to represent all 31 selection criteria with seven factors. The values given in the table correspond to factor loadings. Factor 1 is composed of: “the ability of the carrier to deliver damage-free goods”; “advance notice of transit delays if possible”; “shipment security”; “the ability of the carrier to customize its services to meet specific and/or unique needs to handle emergency shipment”; “length of promised transit times” and; “the ability to adhere to special shipping instructions”. In fact all these criteria are specifically related to the reliability of the carrier. That is why Factor 1 is named as “Reliability of the carrier”.

Factor definitions

Ability of carrier to deliver damage-free goods If possible, advance notice of transit delays (e.g. weather, equipment S2_17 breakdown etc.) S2_18 Shipment security Ability of carrier to customize its services to meet specific and/or S2_25 unique needs to handle emergency S2_16 Length of promised transit times (from pick up to delivery) S2_27 Ability of carrier to adhere to special shipping instructions S2_4 On time deliveries S2_5 Prompt action on complaints related to carrier’s service S2_8 Electronic communication during transportation S2_6 Electronic (on-line terminal) interface for pick up S2_14 Carrier’s general attitude toward problems/complains S2_7 Electronic (on-line terminal) interface for tracing S2_24 Carrier’s financial condition S2_23 Carrier’s reputation S2_22 Cleanliness of carrier’s equipment S2_31 Low frequency of split shipment S2_26 Ability of carrier to handle hazardous material S2_15 Willingness to negotiate rates S2_28 Carrier has satisfactory insurance coverage S2_12 Assistance from carrier in handling loss and damage claims S2_3 Provides same day delivery S2_11 Cash discounts for early payment or prepayment S2_20 Quality of drivers S2_21 Accuracy of response to tracing inquiry S2_9 Single point of contact with carrier to resolve operations problems S2_10 Rate structure simple and easy to understand S2_30 Accurate billing S2_1 Carrier’s delivery history without loss/damage S2_13 Bar coding to facilitate training Extraction method: principal component analysis Rotation method: varimax with Kaiser normalization

S2_29

Factors

0.65 0.63 0.58

0.74 0.70

0.81

1

0.79 0.78 0.74 0.72 0.64 0.61

2

0.81 0.75 0.74

3

0.78 0.74 0.63 0.56 0.48

4

0.80 0.65 0.62 0.49

5

0.79 0.74 0.41

6

0.87 0.55

7

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Table VI. Factor loadings for transportation criteria

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Factor 2 is composed of: “on time deliveries”; “prompt action on complaints related to carrier’s service”; “electronic (online terminal) interface for tracing”; “electronic (online terminal) interface for pickup”; “carrier’s general attitude towards problems/complaints” and; “electronic interface for billing”. As can be seen, the criteria under this factor are concerned with the prompt response of the carrier. Therefore Factor 2 is named as “Prompt response in the delivery cycle”. Factor 3 includes “carrier’s financial condition”, “carrier’s reputation” and “cleanliness of carrier’s equipment”. Owing to their common characteristic, this factor is labeled as “Prestige of the carrier”. Factor 4 comprises: “low frequency of split shipments”; “the ability to handle hazardous material”; “willingness to negotiate rates”; “satisfactory insurance coverage of the carrier” and; “assistance from carrier in handling loss and damage claims”. Factor 4 is named “Financial opportunities and flexibility to customer inquiries”. Factor 5 includes: “provides same day delivery”; “cash discounts for early payment or prepayment”; “quality of drivers” and; “accuracy of response to tracing inquiries”. This factor is labeled as “Reliability and quality of operations management and delivery cycle” Factor 6 comprises: “a single point of contact with the carrier to resolve operations problems”; “rate structure simple and easy to understand” and; “accurate billing”, and is accordingly labeled “Easiness to collaborate”. Finally, Factor 7 includes: “carrier’s delivery history without loss/damage” and “bar-coding to facilitate tracing” and is accordingly named “Accurate order receipt and follow up”.

Cluster analysis for the respondent firms In order to classify the firms according to their common characteristics, a cluster analysis was conducted. A cluster analysis is a multivariate data analysis technique used in grouping objects according to the characteristics they possess. If the classification is successful, the objects within clusters will have similar characteristics and there will be important differences between clusters. In this study, Hierarchical Agglomerative Clustering was used. In this method, each object starts out as its own cluster. In subsequent steps, the two closest clusters are combined to form a new cluster, thus reducing the number of clusters in each step. Wards Method is selected as the agglomeration procedure because this clustering procedure minimizes the within-cluster sum of squares at each stage. It attempts to combine clusters with a small number of observations and form clusters which tend to have the same number of objects. The distance between objects is measured via a squared Euclidean distance measure. (For more information about cluster analysis, one may consult Hair, 1995). In this study, the programs are clustered according to the similarity of importance that they attach to the seven factors revealed in the previous step. The analysis of the dendrogram and ANOVA used to test the significance of the differences between the group means finally resulted in four significant clusters. The categories common in the programs assigned to each cluster were specified and a title was given according to these common categories. The firms that are grouped in the same cluster, together with the mean and standard deviation of each cluster, are given in Figure 1. Figure 1 shows more clearly the configuration of the factors within each cluster.

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Figure 1. Configuration of the factors within each Cluster

When these results are interpreted together with the ANOVA test results (Table VII), it can be seen that the clusters do not have significant differences in terms of their Factor 1 and Factor 7 values. However, there are significant differences among the clusters in terms of other factors. The firms in Cluster 1 especially give importance to prestige and to ease of collaboration with carriers in their carrier’s selection process. Factors Reliability of carrier Prompt response in delivery cycle Carrier prestige Financial opportunities flexibility in customer inquiry Honesty and quality of operations management and delivery cycle Ease of collaboration Accurate order receipt and follow up

Mean square

Sig.

Between groups Within groups Between groups Within groups Between groups Within groups

0.446 1.038 5.153 0.717 2.247 0.915

0.733

Between groups Within groups

4.611 0.754

0.001

Between groups Within groups Between groups Within groups Between groups Within groups

6.578 0.62 7.375 0.565 0.582 1.029

0.000

0.000 0.046

0.000 0.641

Table VII. ANOVA results

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These firms are not overly concerned with the financial opportunities and flexibility that can be offered by the carrier. They give also less importance to “Honesty and quality of operations management and delivery cycle”. In fact, these firms prefer an easy way of selecting the carrier and assuming that the prestige of the firms is the primary indicator of its success, they prefer to select any carrier that has a good reputation in the market.. They are risk averse. The firms in this cluster have spent in average of 34.4 years in business, with the employee number of the firms varying between 500 and 2500. The average annual sales volume of these firms is $57 million, with sales growth over the past five years at 27.5 percent. The firms have a mean endorsement value of $75,195,455 and mainly serve international markets. All respondents in this cluster have a logistics department and an average of 25 employees work in this department. Therefore, they are globally oriented, large scale firms and have understood the importance of coordinating logistics activities through a separate department. The firms in Cluster 2, on the other hand, especially emphasize the financial opportunities and ease of collaboration in their selection of carrier. They prefer simplicity in their activities with the carriers. The firms in this cluster have an average of 27.1 years in business, with the employee number varying between 500 and 1,000. The average annual sales volume for these firms is $58,707,518.5, with sales growth for the past five years at 30.1 percent. The firms have a mean endorsement value of $65,060,305. They serve to both national and international markets but give a higher priority to national markets. Seventy-eight percent of the respondents in this cluster have a logistics department and an average of ten employees work in this logistics department. Therefore, these firms are relatively smaller scale when compared to those of Cluster 1 and they are more dometic market-oriented. The firms in Cluster 3 give importance to “Prompt response” and “Honesty and quality of operations management and delivery cycle”, followed by “Accurate order receipt and follow up”. However, they do not give too much emphasis to ease of collaboration. They can be accepted as being in the mainstream. These firms have an average of 29.6 years in business, with the employee number of the firms varying between 1,000 and 2,500. the average annual sales volume for these firms is $242,515,355. Sales growth over the past five years is 5.4 percent. The firms have a mean endorsement value of $17,695,2000. They mainly serve international markets, and the international markets have a higher priority than national markets. Seventy-six percent of the respondents in this cluster have a logistics department and an average of 39 employees work in this logistics department. Thus, the firms in this cluster when compared to the other clusters have the largest scale in terms of sales volume. Finally the firms in Cluster 4 believe that “Reliability of the carrier”, “Prompt response in the delivery cycle”, “Prestige of the carrier” and “Honesty and quality of operations management and delivery cycle” are not important in carrier selection. They accept that “financial opportunities and flexibility to customer inquiry” and “ease of collaboration” have a low level of importance in carrier’s selection. They are “easy going”. The firms in cluster 4 have an average of 30.7 years in business and the number of employees in the firms varies between 250 and 1,000. Average annual sales volume for

these firms is $55,777,777.8, with sales growth for the past five years at 23.1 percent. The firms have a mean endorsement value of $52,222,222.2. They serve both international and national markets, but they give a higher priority to national markets. All respondents in this cluster have a logistics department and an average of 35 employees work in this logistics department.

Outsourcing logistics activities

Satisfaction from the 3PLs in transportation In this survey respondents are asked to evaluate in a 1-7 scale the first three 3PL firms that they outsource their transportation activities to, in terms of their satisfaction in a 1-7 Likert scale. As can be seen from Table VIII, the respondents of our questionnaire are satisfied with their first and second 3PL firms but they are not satisfied with the third 3PL firm. One possible reason for this is that the second and third 3PL firms are used in cases of emergencies and in unplanned situations. The most outsourced 3PL firm is recommended without doubt while others are not. The satisfaction level from the third most used 3PL firm is significantly different from the first and second. The respondents do not recommend them to other manufacturers.

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Conclusions and further suggestions Outsourcing activities have become one of the most important organizational functions in the 21st century. An efficient supply chain management requires optimization of the product’s movement from raw material to finished good for customers. This optimization results in a need for professional experts in coordinating logistics services. It is profitable to outsource logistics activities because they are non-value adding but they can not be eliminated and 3PL firms will perform the logistics in the right way. Besides this, a unit requiring resource allocation is eliminated by outsourcing. In developed countries, firms no longer undertake all the operations in the supply chain because they focus on their core business, which means outsourcing logistics activities in the first place, followed by other organizational functions. However, this study shows that the power of 3PL firms in Turkey is underestimated; outsourcing is accepted as synonymous with using a carrier for transportation. The firms that outsource their logistics activities in Turkey are 95 percent foreign capitalized. Turkish businessmen still think that they should do their business themselves and they are not aware of the benefits of outsourcing logistics activities. In fact, in selecting the transportation carrier, they consider different criteria but the general tendency is either to select the carrier that has a good reputation and/or the one which is easy to collaborate with. Initially, in the USA, 3PL firms were mostly used for transportation activities (Holcomb et al., 1998). 3PL firms performed those tasks which were not basic and which were monotonous and required investments (Sink and Langley, 1997). In the 3PL firms 1st-2nd 1st-3rd 2nd-3rd

Correlation

t-test sig. (two-tailed)

0.267 0.455 0.430

0.312 0.011 0.045

Table VIII. Satisfaction from current 3PLs

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past, 3PL firms were expected to cover routine logistics functions but now they are supposed to function in information systems, inventory management and customer order fulfilling, tasks which in fact require deep strategic knowledge and specialization (Boyson et al., 1999). It can be said that the trend of outsourcing in Turkish firms is similar to that of US and European firms (Schary and Skjott-Larsen, 2001). The difference is that these firms are at different stages of development, and it can be said that Turkish firms are at the initial stage. However, their level of commitment to the utilization of 3PLs is not discouraging. Turkish firms should be encouraged to work with a few number of 3PL firms and sustain complete integration among them. Their outsourcing should not solely be based on transportation but also on other logistics activities, such as warehousing. However, the use of outsourcing for logistics activities other than transportation requires extreme information sharing and can only be successful when a collaboration based on mutual confidence can be settled. The firms should see the 3PL firm as their own logistics department. Performance evaluation must be held on a regular basis with feedbacks. With this philosophy; the firms should improve their relations with the 3PLs and force them to catch up with modern technologies. The conducted survey contains useful information, to the logistics executives considering outsourcing as well as to the 3PL service providers who are considering relationships with firms planning to enter into the Turkish market. In fact, Turkey is at the epicenter of transport corridors connecting Europe to the Caucasus and Asia, as well as to the Middle East. This is important not only for Turkey’s foreign trade relations and economic development but also for regional and interregional economic cooperation. In the aftermath of the cold war, Turkey has moved from the periphery of Europe to the edge of a new political and economic reality called Eurasia. This region, broadly defined as including Central Asia, the Caucasus and the Black Sea countries, attracts increasing attention not only because it constitutes one of the world’s most potentially important energy-producing regions, but because it is also a crucial trade and transport corridor linking East and West. While there is still a high percentage of firms which have not outsourced their logistics activities, the conducted survey shows that 3PL services in Turkey have potential for further development and the vision of developing Turkey into a logistics hub in the region will further enhance the use of the 3PLs in the years to come. References Bade, D. and Mueller, J. (1999), “New for the millennium: 4PL trademark”, Transportation and Distribution, Vol. 40 No. 2, pp. 78-81. Berglund, M., van Laarhoven, P., Sharman, G. and Wandel, S. (1999), “Third-party logistics: is there a future?”, The International Journal of Logistics Management, Vol. 10 No. 1, pp. 59-70. Boyson, S., Corsi, T. and Dresner, M. (1999), “Managing effective third party logistics relationship: what does it take”, Journal of Business Logistics, Vol. 21 No. 1, pp. 73-100. Carlson, B. (1989), “Flexibility and theory of the organization”, International Journal of Industrial Organization, Vol. 7 No. 1, pp. 189-203. Coombs, R. and Battaglia, P. (1998), “Outsourcing of business services and the boundaries of the firm”, CRIC, Working Paper 5, The University of Manchester, Manchester.

Golop and Reagan (2001), “Impact of information technology on personal travel and commercial vehicle operations: research challenges and opportunities”, Transportation Research Part C: Emerging Technologies, Vol. 9 No. 2, pp. 87-121. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1992), Multivariate Data Analysis With Readings, 4th ed., Prentice-Hall International, Englewood Cliffs, NJ. Harrison, B.T. (1994), Lean and Mean: The Changing Landscape of Corporate Power in the Age of Flexibility, Basic Books, New York, NY. Holcomb, M.C., Manrodt, K.B. and Thompson, R.H. (1998), “The changing environment of transportation and logistics: a profile of the top us purchases”, paper presented at the 8th World conference on Transport Research, Antwerp, 12-17 July. Lambert, D. and Stock, J.R. (1999), Strategic Logistics Management, Irwin McGraw-Hill, Boston, MA. Lieb, R. and Randall, H. (1996), “A comparison of the use of the third party logistics services by large American manufacturers, 1991-1996”, Proceedings of the Council of Logistics Management, Orlando, FL, pp. 431-52. McCarthy, I. and Anagnostou, A. (2003), “The impact of outsourcing on the transaction costs and boundaries of manufacturing”, International Journal of Production Economics, Vol. 88 No. 1, pp. 61-71. Magill, P. (2000), Outsourcing Logistics: The Transition to 4th Party Partnerships in Europe, KPMG, Financial Times Retail and Consumer. Murphy, P.R. and Poist, R.F. (1998), “Third-party logistics usage: an assessment of propositions based on previous research”, Transportation Journal, Vol. 37, pp. 26-35. Parker, J.G. (1999), “European 3PL study”, Traffic World, Vol. 258, pp. 21-5. Schary, P. and Skjott-Larsen, T. (2001), Managing the Global Supply Chain, Copenhagen Business School Press, Copenhagen. Sink, H.L. and Langley, J.C. Jr (1997), “A managerial framework for the acquisition of third party logistics services”, Journal of Business Logistics, Vol. 18 No. 2, pp. 163-89. Skjott-Larsen, T. (2000), “Third party logistics – from an interorganizational point of view”, International Journal of Physical Distribution and Logistics Management, Vol. 30 No. 2, pp. 112-27. Stone, M.A. (2000), “European extension of third party logistics service providers the UK experience”, paper presented at the 3rd International Conference on Logistics, RIRL 2000, Trois-Rivieres, 9-11 May. Sohail, M.S. and Sohal, A.S. (2003), “The use of third party logistics services: a Malaysian perspective”, Technovation, Vol. 23 No. 5, pp. 401-8. Ulengin, F. and Ulengin, B. (2003), “Impact of internet on supply chain activities: the case of Turkey”, paper presented at The International Logistics Congress 2003, Istanbul 30 June-1 July. Virum, H. (1993), “Third party logistics development in Europe”, Logistics and Transportation Review, Vol. 29 No. 4, pp. 355-70. Further reading Press, S.J. (1972), Applied Multivariate Analysis, Holt, Rinehart and Winston, Inc., Chicago, IL.

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Nelson Oly Ndubisi School of Business and Economics, Monash University, Malaysia, Selangor, Malaysia

Muhamad Jantan and Loo Cha Hing University of Science Malaysia, Malaysia

Mat Salleh Ayub University of Malaysia Sabah, Sabah, Malaysia Abstract Purpose – It is a general belief that using the right strategy for supplier selection and management will ensure the right suppliers who will adequately support the manufacturer to be flexible enough to meet customers’ needs are engaged. Yet, there is little empirical evidence to support this view, especially in Malaysia. This paper attempts to fill this need by examining the impact of supplier selection and management strategies on manufacturing flexibility (such as product flexibility, launch flexibility, and volume flexibility). Design/methodology/approach – The population for this study consists of manufacturing firms in the semi-conductor industry in Malaysia listed in the Penang Development Corporation’s directory. Questionnaire was used and each of the 120 companies listed in the sampling frame was sent a copy, out of which 100 copies were collected back. However, only 92 copies were usable. Data were analysed using the multiple regression model. Findings – It was found that the selection of supplier based on technology is important for the manufacturer whose focus is on product and launch flexibility. However, quality becomes strategically important when the manufacturer is focusing on volume flexibility. Inventory management and technology roadmap are very important supplier management strategies with robust influence on all three forms of manufacturing flexibilities, namely product flexibility, launch flexibility, and volume flexibility. In sum, the manufacturer needs to understand clearly which flexibility of its operation is required, and then adopt a working supplier selection and management strategy. Originality/value – This research is new and beneficial to manufacturers and suppliers in the semi-conductor sector. Keywords Supply chain management, Suppliers, Malaysia Paper type Research paper

The Journal of Enterprise Information Management Vol. 18 No. 3, 2005 pp. 330-349 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410390510592003

Introduction Supply chain management (SCM) is a popular topic today. Firms are using effective SCM to support their multiple manufacturing goals such as flexibility, cost, quality and delivery (Wacker, 1996). In today’s competitive and uncertain environment, the flexibility of supply chain is crucial in satisfying customers’ changing needs. A number of operation’s innovative strategies such as agile manufacturing, lean manufacturing, synchronous manufacturing, product customization and time-based competition were introduced to improve the flexibility of the manufacturer. However, improvement

solely on the manufacturer’s capability is not enough to address the needs of the flexible supply chain. Upstream activities of the supply chain will play a vital role in determining the flexibility of the chain. Manufacturers have utilized supplier strengths and technologies to support new product development efforts (Morgan and Monczka, 1995) and have drastically reduced supply bases to a handful of certified suppliers (Inman and Hubler, 1992). Most of the recent literatures on SCM focus on manufacturers’ attempts to integrate processes and form alliances with suppliers to more efficiently and effectively manage the purchasing and supply function. Carter et al. (2000) forecast that supplier selection will increasingly be based on strategic contribution to the supply chain and will extend beyond first-tier suppliers. Early involvement of suppliers in product design, for instance, allows manufacturers to develop alternative solutions; to select the best and most affordable components, materials, and technologies; and to receive help in design assessment. Supplier involvement in product and process design and continuous improvement activities has been shown to have a positive impact on competitive advantage and performance (Vonderembse and Tracey, 1999). In general, SCM seeks to improve the performance through elimination of waste and better leveraging of internal and external supplier capabilities and technologies (Morgan and Monczka, 1996). Since the supplier selection and management is very important in the SCM, a related question that arises in this context is, which supplier selection and management strategies should be pursued by the manufacturer to enhance its flexibility? There is little empirical evidence to validate this view and these linkages of the relationship have not been well explored and understood. Few studies have examined alternative ways of attaining flexibility objectives (Narasimhan and Dass, 1999). One of the possibilities is to study the emphasis of the manufacturer’s supplier selection and management strategy and their contribution towards its flexibility. This study is an attempt to fill this gap. Literature As time to market continues to compress due to customers changing demands, manufacturers are responding with a complementary reduction in product lifecycles (Signal, 1999). In order to meet this variability of demand, the manufacturer needs to incorporate flexible supply chain in their operations that are scalable and adaptable to achieve shorter order fulfillment lead-time. Watts et al. (1990) emphasized that an organization’s ability to produce a quality product at a reasonable cost and in a timely manner is heavily influenced by its suppliers’ capabilities. A key dimension in supply chain performance is flexibility. Flexibility is one of the important objectives in operation strategy model (Schroeder, 2000) and is often seen as a reaction to environmental uncertainty (Suarey et al., 1991; Gerwin, 1993). Flexibility is described as the ability of a manufacturing system to cope with environmental uncertainties (Barad and Sipper, 1988). Although there are many ways to characterize supply chain flexibility, for example, manufacturing flexibility and marketing flexibility (Vickery et al., 1999), this research focuses on manufacturing flexibility, which can be further categorized into product flexibility, launch flexibility and volume flexibility. In general, flexibility reflects an organization’s ability to effectively adapt or respond to changes that add value in the customer’s eyes (Upton, 1995).

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Manufacturing flexibility Manufacturing flexibility refers to the quickness and ease with which plants can respond to the changes in market conditions. Thus, the concept of flexibility is essentially a measure of the efficiency of the process of change. It derives from the efficiency of the production system not in making products, but in changing either the number or types of product made. Manufacturing flexibility is affected by “upstream” uncertainties such as supplier defaults on delivery and performance, machine breakdowns, rejects, variable task times; as well as “downstream” uncertainties due to demand volatility and changes in product mix, price, and competition action (Zelenovic, 1982; Gupta and Goyal, 1989). A dominant feature of the academic literature is the use of taxonomies of flexibility, which classify different types of manufacturing flexibility (Narasimhan and Dass, 1999). For the purpose of this research, three types of flexibilities are investigated, namely product flexibility, launch flexibility and volume flexibility. There has been emphasis on the increasing importance of product flexibility. Product flexibility is a value-adding attribute that is immediately visible to the customer and requires the effective collaboration of the internal and external functional players, including marketing, product design and development, engineering and suppliers. Vickery et al. (1999) reported that product flexibility was significantly related to financial and marketing performance. Since product flexibility is so important in determining financial and marketing performance, it is vital to understand its antecedents. Examples of such salient antecedents which have not been addressed by prior studies are supplier selection and supplier management. Volume flexibility directly impacts customers’ perceptions by preventing out-of-stock conditions for products that are suddenly in high demand. Volume flexibility requires close coordination between the manufacturer and its suppliers, especially in the face of increasing demand. Empirical study has indicated that volume flexibility and launch flexibility are key responses to marketing practice uncertainty and product uncertainty, respectively (Vickery et al., 1999). As the product life cycles dramatically decrease, increasing strategic emphasis is being placed on bringing many new products to market as quickly as possible since it provides companies a real competitive advantage. Launch flexibility brings the following advantages. (1) Pioneering performance advantage, where early market entry is related to higher market share or profitability (Robinson et al., 1992). (2) Quality image perception advantage, where the early entrant has the first opportunity to build and nurture a long-term relationship with the buyer and search costs would induce the buyer to remain with the early entrant (Hauser and Wernerfelt, 1990). (3) Innovation leadership advantage, where technology superiority is perceived by customer; scale and experience economy advantages, where early entrant can gain production efficiencies from early buildups of experience and size advantages (Lieberman and Montgomery, 1988). Supplier-manufacturer relationship There is no gainsaying that the relationship between supplier and manufacturer is an important one. The relationship can be best explained by using agency theory. So far,

agency theory is used to guide the transportation user and provider in evaluating outsourcing relationships (Logan, 2000), and attempts to describe the relationship using the metaphor of a contract (Jensen and Meckling, 1976). Agency theory centers around two parties, a principal (manufacturer) and an agent (supplier) who collaborate with each other to achieve certain outcomes. This theory is concerned with resolving two problems that can occur in agency relationships. The first agency problem arises when (1) the desires or goals of the principal and agent conflict, and (2) it is difficult or expensive (agency cost) for the principal to verify what the agent is actually doing. The general agency costs include the costs of structuring, monitoring, and bonding a set of contracts among agents and principals with conflicting interests. The second problem of risk sharing arises when the principal and agent have different attitudes toward risk. The principal and the agent may prefer different actions because of the different risk preferences (Eisenhardt, 1989). In order to achieve a “win-win” situation, both the manufacturer and its supplier need to compromise and come to a set of common interest for them to get involved in the partnership. By having this partnership, they can grow faster in terms of business and technology, and outperform their competitors to gain more benefit for both sides. In the current competitive environment, suppliers are important resources for manufacturers. Suppliers have a large and direct impact on the cost, quality, technology, and time-to-market of new products (Handfield et al., 1999). In many industries, the management of suppliers can account for as much as 60 and 80 percent of manufacturing cost (Asmus and Griffin, 1993). The management of supplier relationship is a vital task for manufacturers as it can contribute to both competitiveness and profitability of a company (Lemke et al., 2000). As highlighted by Christopher and Martin (1997), effective supplier management can take costs out of the supply chain. Supplier selection strategy Supplier selection strategy is the strategy adopted by the manufacturer, to evaluate and select suppliers, which fulfills the requirements of the manufacturer. To build more effective relationship with suppliers, organizations are using supplier selection criteria to strengthen the selection process. It is indicated that the supplier selection criteria is changing with the new challenge to select suppliers who can add long-term value to the manufacturer (Lemke et al., 2000). Based on the empirical data collected from 170 purchasing managers and members of the National Association of Purchasing Management, Dickson (1966) identified quality, cost and delivery performance history as the three most important criteria in supplier selection. According to a review of 74 articles discussing supplier selection criteria, quality was perceived to be the most important, followed by delivery performance and cost (Weber and Current, 1991). The selection of suppliers is critical for several reasons. First, the trend toward “just-in-time” manufacturing practices has resulted in a supply base reduction (Pearson and Ellram, 1995). Second, due to resource scarcity, there is a need for greater interaction between the buyer and the supplier. Third, many firms involve

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their suppliers early in the planning process so that they are able to deliver superior value to their customers (Trent and Monczka, 1998). In order to release products quickly, supplier selection occurs at the front end of the program, long before the specifications are laid out. Sun System involves supplier by reviewing their technology roadmaps to determine what technology is emerging that Sun may be able to use in future products (Teague, 1997). By bringing the market-leading technologies into the design process at an early stage, suppliers can help the manufacturer in reducing the lead-time and improve the product’s performance. Supplier also can assist manufacturers in understanding the adoption of new technologies that can improve their product, launch and volume flexibility. The supplier selection strategy in terms of technology, quality, cost and delivery performance are important strategies in overcoming the “upstream” uncertainties, such as supplier defaults on delivery and performance, high cost production, and quality rejects; as well as “downstream” uncertainties due to demand volatility and changes in product mix, price, and competition action, which requires flexibility in the manufacturing processes. Supplier management strategy Supplier management strategy is the strategy used by the manufacturer to improve its supplier’s performance and capabilities to meet the manufacturer’s short-term and/or long-term supply needs. Supplier management is concerned with organizing the optimal flow of high-quality, value-for-money materials or components to manufacturing company from a suitable set of innovative suppliers (Goffin et al., 1997). This strategy allows the manufacturer to bridge the gaps, after the supplier selection process, between its suppliers’ capabilities and its own expectation. It is impossible to find the supplier who matches 100 percent the needs of the manufacturer in the initial selection process. Effective supplier management can take costs out of the supply chain. By involving suppliers in product development activities and continuous improvement efforts, suppliers learn about customer requirements, culture, and decision-making patterns, which help them to be more efficient in meeting the manufacturer’s expectation (Cocks, 1996; Epatko, 1994; Leenders, 1994; Minahan, 1996; Morgan and Monczka, 1996; Towler, 1996). These strategies help organizations enhance communication, share knowledge, improve decision-making, and upgrade supplier and manufacturer’s performance. Vonderembse and Tracey (1999) found that although both the supplier selection criteria and the supplier involvement are positively correlated with manufacturing performance, the supplier involvement in product design activities and continuous improvement efforts is much lower than the use of supplier selection criteria. Early supplier involvement has an even greater benefit, a shortening of design cycle time, which means faster launch flexibility. However, there is lack of literature, which relates directly this strategy and the manufacturing flexibility. In the automobile industry, especially for Japanese companies, supplier management in terms of lean manufacturing (technology), JIT delivery and inventory management had proved to help address the needs for supply chain flexibility (Liker and Yen-Chun, 2000). According to Clark and Fujimoto (1989),

supplier involvement and strong supplier partnerships account for almost 33 percent of the man-hour advantage, and the four to five month lead-time advantage enjoyed by the Japanese auto companies over US car makers. The partnerships are particularly critical in JIT environment where there is little inventory to cushion production, scheduling and usage problems. Establishment of technology and quality roadmap is believed to be one of the important activities in supplier management. BMW published a supplier partnership manual and held seminars for suppliers to present their “Road Map to Quality”, which helped BMW to be 20 percent above the industry average in several quality-performance categories. This manual clearly delineates supplier responsibilities and expectations and is geared toward improving alignment between the corporate cultures (Handfield, 2000). Such road maps are becoming increasingly common to spur manufacturer and supplier organizational alignment. They attempt to show companies where they are today and project where they should be in the short-, medium- and long-terms. By involving supplier in the early stage of design, having clear quality and technology roadmap, and proper inventory management program, the manufacturer is more ready to combat the war of uncertainty in its supply chain. Figure 1 shows the schema of the research constructs. The paper theorizes that supplier selection strategies (e.g. technology, quality, cost and delivery performance), and supplier management strategies (such as supplier early involvement, quality roadmap, technology roadmap, and inventory management) are directly associated with product flexibility, volume flexibility, and launch flexibility. More precisely, the model proposes supplier selection and supplier management strategies as predictors of manufacturing flexibility. From the above, two broad hypotheses are derived: (1) There is a significant positive relationship between supplier selection strategies namely, technology, quality, cost, and delivery performance and manufacturing flexibility such as product flexibility, volume flexibility, and launch flexibility. (2) There is a significant positive relationship between supplier management strategies for example, supplier early involvement, quality roadmap, technology roadmap, and inventory management in one hand and product flexibility, volume flexibility, and launch flexibility in another hand.

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Figure 1. Constructs schema

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Methodology The population for this study consists of the manufacturing firms in the semi-conductor business located in northern Malaysia state of Penang. It is important to highlight that Penang is the seat of semi-conductor industry in Malaysia and south-east Asia by extension. All the firms (both local and foreign) in this line of business operating in Malaysia have situated in Penang. The sampling frame is drawn from companies listed in the factory directory published by Penang Development Corporation (PDC). Based on the information from the sampling frame, the manufacturers are from different countries of origin (namely America, Germany, Japan, Malaysia, Taiwan, and UK), and they are involved in semiconductor, computer and computer peripherals, telecommunications, electrical products and instruments industries. The unit of analysis for this study is the business unit with manufacturing activities (represented by the purchasing director or manager), and as such a purposive sampling method (non-probabilistic) is used. This method is more appropriate than the random sampling method because only specific targets that have manufacturing activities are in the best position to provide the desired information for this study. The design of the questionnaire is derived from the issues and questions raised in the literature. The questions were taken directly from the past questionnaires with few modifications made to the model requirements (Narasimhan and Dass, 1999; Khaw, 1999; Jantan et al., 2003a). Few academicians with expertise in this area were approached before developing the questionnaire, in addition to personal interviews conducted with practitioners who have vast experiences in supplier selection and management field as well as supply SCM. Their suggestions were incorporated in the questionnaire and pre-tested. The pre-test was conducted on three purchasing managers to ensure that issues of concern are correctly addressed and also to ensure the clarity and validity of the questions raised. Changes were made based on their feedback to produce the final version. The final version has four major sections, which contain 46 items. The first section (section A) consists of 11 general questions pertaining to the individual and organization profile. The following sections (section B, C and D) consist of questions, which measure each item on a 6-point Likert scale anchored by 1 (strongly disagree) and 6 (strongly agree). Section B has 13 questions regarding supplier selection strategy and section C has 12 questions on supplier management strategy taken from Khaw (1999) and Jantan et al. (2003a). The last section, section D contains 10 questions on manufacturing flexibility from Narasimhan and Dass (1999). A copy of the questionnaire was sent to each of the 120 companies listed in the sampling frame, out of which 100 copies were collected back. However, only 92 copies were usable, which indicates a response rate of approximately 77 percent. The flawed 8 copies were either incomplete or filled up by non-targeted respondents, which may not have related experience in this survey. Results Respondent and company profiles. The summary of the organizational background, namely size of the company in terms of employee, years of establishment in Malaysia, supplier base, and material cost structure are shown. Among the survey organization, the majority (41.3 percent) are American companies, followed by Japanese firms

(27.2 percent), Malaysian firms (18.5 percent), Taiwanese firms (5.4 percent), and others (including the German and UK firms) recorded 7.6 percent. A total of 78.3 percent of the organizations have more than 500 employees, and 71.7 percent has been established in Malaysia for more than ten years. The majority of the organizations deal with a huge supplier base, for instance, 71.7 percent of the organization have more than 200 suppliers. There is wide spread of material cost among the organization. About 24 percent of organization have material cost of less than 50 percent, 19.6 percent have between 51 and 60 percent and 27.2 percent have between 61 and 70 percent and . 70 percent each. There is no significant dominance of material cost structure among the surveyed organization. The summary of the profiles of the respondents and the organizations are presented below. Among the 92 respondents, 57.6 percent is female. The majority of the respondents (72.8 percent) are college or university graduates. All 92 respondents belong to the procurement division/department of the firms, 40.2 percent are in senior management position, while the rest are in middle management level. Majority of the respondents (52.2 percent) have total working experience in procurement or SCM field for at least six years, 63.0 percent of the respondents is attached to the current position between 1 and 5 years. In all, respondents are competent and qualified to furnish reliable information for the research. Reliability of measurement. In order to ensure the reliability of the measures, the multiple statements dealing with supplier selection, supplier management and manufacturing flexibility variables were assessed for reliability using Cronbach’s a. Table I gives a summary for all the variables in the analysis. The reliability a ranges from 0.5161 to 0.8172. Only one variable (i.e. inventory management) shows Cronbach a value less than 0.6 recommended by Hair et al. (1998). However, the alpha value of 0.52 for inventory management may not be critical because it is only a very slight weakness, moreover, there are previous researches that have used variables with much less coefficient alpha values. For example, Alexandris et al. (2002) have used a variable with a problematic scale yielding coefficient alpha of 0.29. No.

Variables

1.

Supplier selection Technology Quality Cost Delivery Supplier management Supplier involvement Quality roadmap Technology roadmap Inventory management Manufacturing flexibility Product flexibility Launch flexibility Volume flexibility

2.

3.

Questions

Cronbach’s a

B1-B3 B4-B6 B7-B9 B10-B12

0.6169 0.7767 0.6487 0.7894

C1-C3 C4-C6 C7-C9 C10-C12

0.8037 0.8157 0.8172 0.5161

D1-D4 D5-D7 D8-D10

0.7479 0.8098 0.6468

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Table I. Cronbach’s a value for variables

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Table II. Description of the composite variables

The descriptive characteristics of the composite variables listed are all tapped on a six-point scale ranging from strongly disagree (1) to strongly agree (6). The summary of the descriptive statistics is shown in Table II. It can be seen that the mean for all dimensions are well above the mid point (3) of the anchors. Supplier involvement and volume flexibility have lower mean values as compared to other variables. This indicates that the level of supplier involvement and volume flexibility is not as high as the level of other dimensions. The rest of the variables have mean values of at least four. The supplier selection dimensions have mean values between 4.7 and 5.2, which indicate that all these variables are very important in supplier selection. Among them, delivery mean value is the highest, 5.13, which show that most of the manufacturers have consistence opinion in delivery performance measure compared to the other variables in the questionnaire. Quality roadmap has the highest mean value, 4.83 among all the supplier management variables, followed by inventory management with mean value of 4.43. The product and launch flexibility have mean value around 4.1. In conclusion, manufacturers view all the variables as important elements of the construct, however, supplier selection strategy has received more emphasis than supplier management. Mean differences. Differences in manufacturing flexibilities, supplier selection strategies and supplier management strategies were tested using one-way ANOVA to find out whether there are any differences across country of the origin, supplier base, and material cost. The results show that only launch flexibility exhibits significant differences in the category of country of origin at 5 percent significance level. Manufacturing firms from Japan and United States are significantly higher in launch flexibility as compared to rest. There are no significant differences with respect to supplier base and material cost. At 5 percent significance level, supplier selection based on technology strategy demonstrates significant mean differences for country of origin and supplier base categories. European, United States, Malaysian and Japanese firms put more emphasis on technology when selecting suppliers compared with Taiwanese firms. There is no significant difference in supplier selection strategies based on material cost. There is also no significant difference in supplier management strategies based on country of origin, supplier base, and material cost. Variables

Mean

Standard deviation

Technology Quality Cost Delivery Supplier involvement Quality roadmap Technology roadmap Inventory management Product flexibility Launch flexibility Volume flexibility

4.6884 4.7971 4.8152 5.1304 3.6304 4.8333 4.1812 4.4275 4.1793 4.1486 3.6304

0.6645 0.7671 0.6673 0.6366 1.0581 0.8523 0.8901 0.8185 0.8307 0.9289 0.7990

Testing for associations Supplier selection strategy and product flexibility. The regression analysis results shown in Table III show that supplier selection strategies based on technology, quality, and delivery performance contribute significantly ðF ¼ 3:304; p ¼ 0:004Þ and predict 16.1 percent variation in product flexibility. Detail results show that there is significant relationship between technology ðt ¼ 2:717; p ¼ 0:008Þ and product flexibility. There is no significant relationship between quality ðp ¼ 0:647Þ; cost ðp ¼ 0:431Þ and delivery ðp ¼ 0:632Þ considerations and product flexibility. When product flexibility is the focus, technological consideration is the only significant criteria in choosing suppliers. At 5 percent significance level, only supplier selection based on technology has significant impact on product flexibility. Supplier selection strategy and launch flexibility. The results of the regression analysis (see Table IV) show that supplier technology consideration, quality consideration, cost consideration, and delivery consideration contribute significantly ðF ¼ 2:788; p ¼ 0:031Þ and predict 11.4 percent variation in launch flexibility. Detail results show that only technology is significantly associated ðt ¼ 2:331; p ¼ 0:022Þ with launch flexibility. There is no significant relationship between quality ðp ¼ 0:728Þ; cost ðp ¼ 0:796Þ and delivery ðp ¼ 0:681Þ considerations and launch flexibility. Again, technological consideration appears as the only significant criterion emphasized when selecting suppliers to attain flexibility in product launch. Supplier selection strategy and volume flexibility. The regression analysis results shown in Table V show that supplier selection strategies based on technology, quality, and delivery performance contribute significantly ðF ¼ 6:894; p ¼ 0:000Þ and predict 25 percent variation in volume flexibility. Moreover, results show that there is significant relationship between quality ðt ¼ 3:519; p ¼ 0:001Þ and volume flexibility. There is no significant relationship between technology ðp ¼ 0:713Þ; cost ðp ¼ 0:204Þ and delivery ðp ¼ 0:411Þ considerations and volume flexibility. A plausible R 0.401 Variables Technology Quality Cost Delivery

R 0.337 Variables Technology Quality Cost Delivery

R2

F

Sig. F

0.161 b 0.326 0.058 0.083 0.056

3.304 t 2.717 0.460 0.791 0.480

0.004 Sig. 0.008 0.647 0.431 0.632

R2

F

Sig. F

0.114 b 0.286 0.045 0.028 0.049

2.788 t 2.331 0.350 0.259 0.413

0.031 Sig. 0.022 0.728 0.796 0.681

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Durbin-Watson 1.926 Tolerance 0.678 0.604 0.881 0.712

VIF 1.474 1.656 1.135 1.405

Table III. Selection strategy and product flexibility

VIF 1.474 1.648 1.147 1.411

Table IV. Selection strategy and launch flexibility

Durbin-Watson 2.131 Tolerance 0.678 0.607 0.872 0.709

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explanation for this result is the need to marry quality and quantity. In many instances, there has been a compromise of quality when quantity (volume or mass production) is the focus of the organization. This being the case, organizations, which are faced with the need for mass production, and are particularly concerned about quality standards being compromised, will take steps to ensure that suppliers who are known for high quality inputs are selected. By taking this proactive step of choosing superior quality suppliers, outputs (even though massive) often turn out to maintain acceptable quality standards. It has been reported in prior studies that there is a significant relationship between the quality of inputs and the quality of outputs. The term “gabbage in-gabbage out” (GIGO) has been used very often (even in the high-tech industry) to describe the poor quality of outputs resulting from poor quality of inputs. Summarily, it is found that launch and product flexibility are positively associated with technology-based selection strategy, whilst volume flexibility is positively associated with quality criterion. In other words, when volume flexibility is the manufacturer’s concern, there is the tendency to choose suppliers with known quality record so as to prevent compromising output quality. Moreover, when product or launch flexibilities are the focus, suppliers with cutting edge technologies are preferred. This is because such high-tech suppliers (as compared to low or no-tech suppliers) are more likely to significantly contribute to or facilitate the manufacturer’s quest for creating more innovative products or customized products within the shortest possible time frame – the key benefits of product and launch flexibilities. Supplier management strategy and product flexibility. The results of the regression analysis (Table VI) show that supplier management strategies namely, supplier involvement, quality roadmap, technology roadmap, and inventory management contribute significantly ðF ¼ 5:772; p ¼ 0:000Þ and predict 21.2 percent variation in product flexibility. Detail results show that there is significant relationship between technology roadmap ðt ¼ 2:312; p ¼ 0:023Þ; inventory management ðt ¼ 2:248; R2

F

Sig. F

0.245 b 20.043 0.434 0.129 0.093

6.894 T 2 0.369 3.519 1.281 0.826

0.000 Sig. 0.713 0.001 0.204 0.411

R

Table V. Selection strategy and volume flexibility

0.495 Variables Technology Quality Cost Delivery

R

Table VI. Supplier management and product flexibility

0.460 Variables Supplier involvement Quality roadmap Technology roadmap Inventory management

R2

F

Sig. F

0.212 b 20.203 0.171 0.283 0.224

5.772 t 2 1.861 1.486 2.312 2.248

0.000 Sig. 0.066 0.141 0.023 0.027

Durbin-Watson 1.785 Tolerance 0.668 0.584 0.882 0.705

VIF 1.497 1.713 1.134 1.419

Durbin-Watson 2.151 Tolerance 0.774 0.689 0.614 0.921

VIF 1.292 1.451 1.629 1.086

p ¼ 0:027Þ on one hand, and product flexibility in the other hand. There is no significant relationship between early supplier involvement ðp ¼ 0:066Þ; quality roadmap ðp ¼ 0:141Þ and product flexibility. Supplier management strategy and launch flexibility. The results of the regression analysis in Table VII show that supplier management strategies namely supplier involvement, quality roadmap, technology roadmap, and inventory management contribute significantly ðF ¼ 11:265; p ¼ 0:000Þ and predict 24.1 percent variation in launch flexibility. Detail results show that there is significant relationship between technology roadmap ðt ¼ 2:188; p ¼ 0:031Þ; inventory management ðt ¼ 3:458; p ¼ 0:001Þ; and launch flexibility. There is no significant relationship between early supplier involvement ðp ¼ 0:172Þ; quality roadmap ðp ¼ 0:187Þ and launch flexibility. Supplier management strategy and volume flexibility. The results of the regression analysis (refer to Table VIII) show that supplier involvement, quality roadmap, technology roadmap, and inventory management contribute significantly ðF ¼ 15:485; p ¼ 0:000Þ and predict 41.6 percent variation in volume flexibility. Moreover, there is significant relationship between technology roadmap ðt ¼ 2:616; p ¼ 0:010Þ; inventory management ðt ¼ 5:165; p ¼ 0:000Þ on one hand, and volume flexibility on the other hand. There is no significant relationship between early supplier involvement ðp ¼ 0:771Þ; quality roadmap ðp ¼ 0:190Þ and product flexibility.

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Discussion This study is at an exploratory stage in which the researchers are interested in understanding, what type of supplier selection and management strategies should be adopted by the manufacturer, when focusing on different types of manufacturing flexibilities such as product, launch, or volume flexibility.

R 0.584 Variables Supplier involvement Quality roadmap Technology roadmap Inventory management

R 0.645 Variables Supplier involvement Quality roadmap Technology roadmap Inventory management

R2

F

Sig. F

0.341 b 0.136 0.139 0.243 0.312

11.265 t 1.377 1.329 2.188 3.458

0.000 Sig. 0.172 0.187 0.031 0.001

R2

F

Sig. F

0.416 b 0.026 0.131 0.274 0.438

15.485 t 0.277 1.321 2.616 5.165

0.000 Sig. 0.782 0.190 0.010 0.000

Durbin-Watson 2.136 Tolerance 0.771 0.687 0.612 0.932

VIF 1.296 1.455 1.633 1.074

Table VII. Supplier management and launch flexibility

Durbin-Watson 1.753 Tolerance 0.771 0.687 0.612 0.932

VIF 1.296 1.455 1.633 1.074

Table VIII. Supplier management and volume flexibility

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Mean differences With respect to organization profile, it is found that there is significant differences in launch flexibility for firms from different countries of origin. Manufacturing firms from Japan and United States have significantly higher launch flexibility as compared to the rest. This may be due to great support from R&D centers from their parent companies for both Japan and United States, which gives them good launch flexibility. It is also found that the supplier selection based on technology has significant differences among firms of different countries of origin The European, United States, Malaysian and Japanese firms put more emphasis on technology when selecting supplier compared to Taiwanese firms. This may be explained by the corporate culture of European, American and Japanese companies who have their own R&D activities for new product introduction, which needs to stress a lot on the technology sourcing. Taiwanese companies are well known for the strategy of imitating and modifying products, which does not call for a lot of own R&D activities. The imitating strategy of Taiwanese firms do not always stress on new technology, but tap on the existing technologies. Supplier selection strategy and manufacturing flexibility The research finding is that manufacturers who concentrate on product and launch flexibility tends to select supplier based on technology in comparison with quality, cost and delivery performance. To achieve a wider range of product and be able to deliver fast enough to the market is crucial nowadays as the competition is so intense. Only firms with advanced technology as its competitive edge can overcome stiff competition by introducing wide range of products to meet the different market segments and able to deliver quickly to the hands of customer before any of its competitors can do so. By selecting supplier with leading edge technology, the manufacturer can leverage on its competency to introduce more products and enjoy the first mover advantages. For example, according to Design News article, Sun Microsystems involves key suppliers in the design of new workstations, networking systems and supercomputers to shrink cycle time in view of some of product platform to around 18-36 months. Sun taps on the latest and greatest technology of its supplier to allow Sun to continuously introduce more new product quickly ahead of its competitors. However, the scenario changes when the manufacturer’s focus is on volume flexibility. It is found that selection of supplier base on quality is more important compared to technology, cost and delivery performance. Volume flexibility is more related to advanced manufacturing technologies such as efficiency of equipment and resource utilization. If equipment is running at high efficiency and good resources are in place, the quality problem is going to be minimal. Therefore, it is important to select the supplier based on quality when the manufacturing activities are high volume in nature to avoid any supplier quality problem in the materials or parts supply, which might affect output quality. Based on the findings, it is salient for the manufacturer to understand and be well aware of, which types of manufacturing flexibility it would like to focus. Different manufacturing flexibility requires different emphasis on the supplier selection strategy and supplier management strategy. For example, if the operation is more focussed on launch flexibility, the manufacturer should emphasize heavily on technology as its supplier selection strategy to reap the first mover advantages.

As more companies move toward globalization, pressure to disperse product value creation chain in a way that will yield lowest possible cost, by tapping on the location economies globally will be intensified. The result will be a regional focus operation such as R&D center (which is more related to product and launch flexibility) being located in one region (for instance, United States), and manufacturing operation (which is related to volume flexibility) being located in Southeast Asia region.

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343 Supplier management and manufacturing flexibility An effective supplier management system can result in optimal inventory levels and, in multiplant operations, optimal production capacity, both of which can maximize the use of working capital. A supplier management system may also result in better (more dependable) delivery service to the manufacturer; when production occurs at different locations, manufacturers are able to determine quickly the most economical source for a particular plant. As manufacturers expand into international markets and source these markets from multinational production facilities, they are increasingly confronted with cost variables that make it imperative to employ a total systems approach to the management of the supply process to achieve efficient operation. The striking consistency of technology roadmap and inventory management in determining all the three manufacturing flexibilities (i.e. product, launch, and volume) is worth noting. Proper inventory management enables manufacturers to guard against stock-out and excess stock situations, either of which could result in an increase in cost of production. Inventory management can also help to control the quality of inputs as well as the quantity that goes into any production process. A good inventory management will ensure that the right quantity and quality of inputs are sourced, held or timely delivered, and excellently combined in the production process in order to enhance product innovation capability, launch flexibility, and volume adaptation. When product innovation is the concern of the manufacturer, its consummation will depend partly on the inventory management ability (e.g. ease of sourcing the right materials in the right quantity), and partly on few other factors that are beyond the scope of this research. This is also the case when launch and volume flexibilities are the focus. The ability of the manufacturer to send a particular innovation timely to the market and to juggle with the ups and downs (volatility) of market demand will depend to some extent on his ability to acquire needed inputs and to produce within the time-to-market window. The extent of complexity of the innovation (Jantan et al., 2003b) will contribute strongly in determining the criticality of inventory management, as well as the extent of supplier support (see also Ndubisi and Richardson, 2002; Ndubisi and Jantan, 2003) the manufacturer may require. Technology roadmap is another important determinant of product, launch, and volume flexibilities. By helping suppliers to create a technology roadmap, or using suppliers with a technology roadmap that is suitable to the manufacturer’s need, both partners will maximize efficiency. A technology roadmap that is up-to-date, useful, and usable, will enable the supplier to adequately support the manufacturer’s effort to be more innovative than competitors, to have a shorter time-to-market cycle, and also to commercialize such innovations in other to reap the early mover advantages and economies of scale. Typically, an innovation has the following characteristics: relative advantage (the perceived marginal value of the new product relative to the old); compatibility (its compatibility with acceptable behavior, previous technology, etc.);

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complexity (the degree of complexity associated with product use); trialability (the degree of economic and/or social risk associated with product use); and observability (the ease with which the product benefits can be communicated) (Cateora and Graham, 2002), therefore any manufacturer’s ability to turn out an innovative product earlier than competitors, will depend among other factors, the extent to which he can integrate the operations of the supplier to his, the continuous upgrade by the supplier of his technology in other to align with those of the manufacturer, and the swiftness to which the supplier can respond to future technological changes resulting from the manufacturer’s technology shift. These are all important irrespective of which flexibility or combinations that the manufacturer is keen to pursue. Surprisingly supplier involvement and quality roadmap have no significant association with manufacturing flexibility. Although respondents reported high mean for supplier involvement and quality roadmap, none of these factors predicted product flexibility, launch flexibility, or volume flexibility. With respect to quality roadmap’s non-influence, it may be that since quality is not a determinant selection factor (except for volume flexibility), the salience of quality roadmap in supplier management has diminished. But in the case of volume flexibility, it could be that manufacturers having considered quality in selecting suppliers may not emphasize it in supplier management, plausibly because of a supposition that suppliers will maintain quality expectations. Supplier involvement is not a salient factor in supplier management among respondents in view of the paraded benefits of this strategy. For example, Solar Turbines, Inc., a division of Caterpillar, describes how customers are integrated into the production process this way: The Customer is involved as a vital member of the Project Team from initial inquiry to final acceptance. The customer works with and issues project specifications to our. . . Sales Engineer, who maintains initial customer contact, prompts analysis of customer needs, submits a comprehensive proposal to the customer, monitors execution of the order, and submits the order to the assigned. . . Application Engineer, who is responsible for. . . works closely with Engineering and control systems. . . who works closely with Project Manager. The Project Manager handles all aspects of the order, maintains liaison with the Customer,. . . (Cateora and Graham, 2002).

There is no doubt that Solar Turbines, Inc., and Caterpillar are successful global firms, which success the firms have attributed to their close working relationship with customers. Implications of the findings The findings suggest several theoretical and managerial implications. Theoretically, the research helps to explain the causal chain linking supplier selection and supplier management strategies with manufacturing flexibility. The study shows that technology is the only element of supplier selection strategy that significantly predicts product flexibility and launch flexibility, while quality is the only predictor of volume flexibility. With respect to supplier management, technology roadmap and inventory management are robust predictors of the three manufacturing flexibility namely product, launch, and volume flexibility. The results theoretically imply that after selecting the right suppliers, it is needful to present them the technology roadmap or

plans of the manufacturer and to establish a proper inventory management program if manufacturing flexibility is desired. On the practical front, the study provides an avenue to explore the strategic decision in supplier selection strategy and supplier management strategy with respect to different types of manufacturing flexibilities. Different types of manufacturing flexibilities require different driver in supplier selection and supplier management. There is no one single formula that applies to all situations. For example, the manufacturer who is focusing on launch flexibility need to emphasize more on technology in supplier selection, inventory management and technology roadmap in supplier management. Manufacturers that focus on product flexibility may need to emphasize more on technology in supplier selection and technology roadmap as well as inventory management in supplier management. Manufacturers whose focus is on volume flexibility may need to emphasize on quality in supplier selection in order to continue to deliver quality products to customers. The manufacturer needs to identify its own types of flexibility before any strategic decision can be made for supplier selection and management. In the past, the manufacturer may need to concentrate on various types of flexibility under one roof. With the current trend toward globalization, differentiation on flexibility is becoming more obvious as global companies are dispersing their product value creation chain in different locations to lower down the cost and increase the product quality. In some firms, products are designed in America or Europe and manufactured in Asia, and then sold in other markets or even brought back to the designer nations. In other cases manufacturers locate activities where optimal flexibilities could be consummated, for example, US operation may focus on product and launch flexibility and Asia operation focuses on volume flexibility. Many Australian firms have towed this path in the last two decades. These firms design the products in Australia, manufacture in China, and ship them back to the Aussie market. Limitation of the study A few limitations are identified and recognized while conducting this research, albeit, the research is considered successful in meeting its objectives. The study is limited by scope. First, the study is focused on the manufacturing firms in the northern region of Peninsular Malaysia, which may subject it to regional clustering bias. Nevertheless, since Penang is the seat of semi-conductor and other high-tech industries in Malaysia and South-east Asia by extension, the choice is second to none. Second, up to 81.5 percent of the responding companies is foreign-owned, which may hinder the generalizability of the findings especially in the local setting. However, this same factor also contributes to the strength of the research and gives it an international outlook and flavor, because it involves companies and managers of different nationalities, background, and culture. Nevertheless, the weaknesses must be kept in view while interpreting and applying the results. Suggestion for future research There is limited literature on the roles of supplier selection strategy and supplier management strategy in determining manufacturing flexibility. The advancement of telecommunication technology, globalization, stiff competition and movement towards free market economy has heightened the importance of supply chain flexibility. There

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is need to investigate manufacturing flexibility further especially in other sectors. In addition, there are other types of manufacturing flexibility such as material flexibility, equipment flexibility, program flexibility and market flexibility that is not covered and explored in this study. Future research may take up this challenge. To complete the entire supply chain, the manufacturer must ensure its downstream supply chain such as manufacturer flexibility, distribution channel and logistic, are robust enough to satisfy the customers apart from the upstream activities addressed in this study. Future research may address these downstream activities. Lastly, there is a suspicion that supplier management strategies could have some moderating effect on the relationship between supplier selection strategies and manufacturing flexibilities. Future research in this area should explore this moderator effect. Also replicating the current study in other industries in other nations is suggested. Such future research should include larger sample size to increase the external validity and the generalizability of the findings. Conclusion Based on the study, the selection of supplier based on technology is important for the manufacturer focus on product and launch flexibility. However, quality becomes strategically important when the manufacturer is focusing on volume flexibility. Inventory management and technology roadmap are very important supplier management strategies with robust influence on all three forms of manufacturing flexibilities, namely product flexibility, launch flexibility, and volume flexibility. Lastly, the study has shown that there is no single formula that can fit all situations. It depends on the performance measures, business nature, business environment and other market factors that the manufacturer needs to deal with. The manufacturer needs to understand clearly which flexibility of its operation is required, and then adopt a working supplier selection and management strategy. References Alexandris, K., Dimitriadis, N. and Markata, D. (2002), “Can perceptions of service quality predict behavioral intentions? An exploratory study in the hotel sector in Greece”, Managing Service Quality, Vol. 12 No. 4, pp. 224-31. Asmus, D. and Griffin, J. (1997), “Harnessing the power of your suppliers”, The Mckinsey Quarterly, Vol. 3, pp. 63-78. Barad, M. and Sipper, D. (1988), “Flexibility in manufacturing systems: definitions and perti-net modeling”, International Journal of Production Research, Vol. 26 No. 2, pp. 237-48. Carter, P.I., Carter, J.R., Monczka, R.M., Slaight, T.H. and Swan, A.J. (2000), “The future of purchasing and supply: a ten-year forecast”, The Journal of Supply Chain Management, Vol. 36 No. 1, pp. 14-26. Cateora, P.R. and Graham, J.L. (2002), International Marketing, 11th ed., McGraw-Hill, New York, NY. Christopher, M. and Martin (1997), Marketing Logistics, Butterworth-Heinemann, Oxford. Clark, K.B. and Fujimoto, T. (1989), “Lead time in automobile product development explaining the Japanese advantage”, Journal of Engineering and Technology Management, Vol. 6 No. 1, pp. 25-59. Cocks, P. (1996), “Partnership in pursuit of lean supply”, Purchasing & Supply Management, pp. 32-3.

Dickson, G.W. (1966), “An analysis of vendor selection systems and decisions”, The Journal of Supply Chain Management-Supplier Performance, Vol. 2 No. 1, pp. 5-17. Eisenhardt, K.M. (1989), “Agency theory: an assessment and review”, Academy of Management Review, Vol. 14 No. 1, pp. 57-74. Epatko, E. (1994), “Supplier can help meet customer desires”, Purchasing, Vol. 117 No. 8, pp. 9-11. Gerwin, D. (1993), “Manufacturing flexibility: a strategic perspective”, Management Science, Vol. 39 No. 4, pp. 395-410. Goffin, K., Szwejczewski, M. and New, C. (1997), “Managing suppliers: when fewer can mean more”, International Journal of Physical Distributions & Logistics Management, Vol. 27 No. 7, pp. 422-36. Gupta, Y.P. and Goyal, S. (1989), “Flexibility of manufacturing systems: concepts and measurements”, European Journal of Operational Research, Vol. 43, pp. 119-35. Hair, J.F. JR, Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, 5th ed., Prentice-Hall Inc., Upper Saddle River, NJ. Handfield, R.B., Ragatz, G.L., Petersen, K.J. and Monczka, R.M. (1999), “Involving suppliers in new product development”, California Management Review, Vol. 42 No. 1, pp. 59-82. Handfield, R.B. et al. (2000), “Avoid the pitfalls in supplier development”, Sloan Management Review, Winter, pp. 37-49. Hauser, J.R. and Wernerfelt, B. (1990), “An evaluation cost model of consideration sets”, Journal of Consumer Research, Vol. 16, pp. 393-408. Inman, R.A. and Hubler, J.H. (1992), “Certify the process, not just the product”, Production and Inventory Management Journal, Vol. 33 No. 4, pp. 11-14. Jantan, M., Ndubisi, N.O. and Loo, C.H. (2003a), “Can supply chain management strategies predict manufacturing flexibility”, Asian Academy of Management Proceeding, Vol. 1, pp. 247-64. Jantan, M., Ndubisi, N.O. and Ong, B.Y. (2003b), “The viability of e-commerce as an alternative distribution channel”, Logistic Information Management, Vol. 16 No. 6, pp. 427-39. Jensen, M. and Meckling, W. (1976), “Theory of the firm: managerial behavior, agency costs and ownership structure”, Journal of Financial Economics, Vol. 3, pp. 305-60. Khaw, P.L. (1999), “The impact of intra-firm sourcing strategy and inter-firm sourcing strategy on supplies quality, delivery and cost”, MBA Thesis, School of Management, University of Science Malaysia. Leenders, M.R. (1994), “Adapting purchasing to supply chain management”, International Journal of Physical Distribution & Logistics Management, Vol. 24 No. 1, pp. 40-2. Lemke, F., Goffin, K. and Szwejczewski, M. (2000), “Supplier base management: experiences from the UK and Germany”, The International Journal of Logistics Management, Vol. 11 No. 2, pp. 45-58. Lieberman, M.B. and Montgomery, D.B. (1988), “First-mover advantages”, Strategic Management Journal, Vol. 9, pp. 41-58. Liker, J.K. and Yen-Chun, Wu (2000), “Japanese automakers, U.S. suppliers and supply-chain superiority”, Sloan Management Review, pp. 81-93, Fall. Logan, M.S. (2000), “Using agency theory to design successful outsourcing relationships”, The International Journal of Logistics Management, Vol. 11 No. 2, pp. 21-32. Minahan, T. (1996), “Buyers take a lead role in setting corporate strategies”, Purchasing, Vol. 120 No. 7, p. 31. Morgan, J. and Monczka, R.M. (1995), “Alliances for new products”, Purchasing, pp. 103-9.

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Morgan, J. and Monzcka, R.M. (1996), “Supplier integration: a new level of supply chain management”, Purchasing, pp. 110-13.

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Ndubisi, N.O. and Jantan, M. (2003), “Evaluating IS usage in small and medium-sized firms using the technology acceptance model”, Logistics Information Management, Vol. 16 No. 6, pp. 440-50.

Narasimhan, R. and Dass, A. (1999), “An empirical investigation of the contribution of strategic sourcing to manufacturing flexibilities and performance”, Decision Sciences, Vol. 30 No. 3, pp. 683-718.

Ndubisi, N.O. and Richardson, S. (2002), “Facilitators for the use of DSS in SMBs: suggestions for redefinition of marketing strategy”, Cyberscape, Vol. 1, pp. 128-57. Pearson, J.N. and Ellram, L.M. (1995), “Supplier selection and evaluation in small versus large electronics firms”, Journal of Small Business Management, Vol. 33 No. 4, pp. 53-65. Robinson, W.T., Fornel, C. and Sullivan, M.W. (1992), “Are market pioneers intrinsically stronger than later entrants?”, Strategic Management Journal, Vol. 13, pp. 609-24. Schroeder, R.G. (2000), Operations Management, Contemporary Concepts and Cases, McGraw-Hill, Irwin, New York, NY. Signal (1999), “Signal upside production flexibility: tactics and strategies”, The Performance Measurement Group, LLC, Vol. 1 No. 1. Suarey, F., Cusumano, M.A. and Fine, C.H. (1991), Flexibility and Performance: A Literature Critique and Strategic Framework, Sloan School, MIT, Cambridge, MA. Teague, P.E. (1997), “Suppliers: the competitive edge in design”, Design News, Vol. 52 No. 9, pp. SD5-S15, Boston. Towler, B. (1996), “Communication and the supply chain – how?”, Purchasing & Supply Management, pp. 26-7, February. Trent, R.J. and Monczka, R.M. (1998), “Purchasing and supply management: trends and changes throughout the 1990s”, The Journal of Supply Chain Management, Vol. 34 No. 2, pp. 2-11. Upton, D.M. (1995), “What really makes factories flexible?”, Harvard Business Review, July/August, pp. 74-84. Vickery, S., Calantone, R. and Droge, C. (1999), “Supply chain flexibility: an empirical study”, The Journal of Supply Chain Management, pp. 16-25. Vonderembse, M.A. and Tracey, M. (1999), “The impact of supplier selection criteria and supplier involvement on manufacturing performance”, The Journal of Supply Chain Management, pp. 33-9. Wacker, J.G. (1996), “A theoretical model of manufacturing lead times and their relationship to a manufacturing goal hierarchy”, Decision Sciences, Vol. 27 No. 3, pp. 483-517. Watts, C.A., Kim, K.Y. and Hahn, C.K. (1990), “The supplier development program: a conceptual model”, Journal of Purchasing and Materials Management, pp. 2-7, Spring. Weber, C.A. and Current, J.R. (1991), “Vendor selection criteria and methods”, European Journal of Operational Research, Vol. 50, pp. 2-18. Zelenovic, D.M. (1982), “Flexibility: a condition for effective production systems”, International Journal of Production Research, Vol. 20 No. 3, pp. 319-37. (Nelson Oly Ndubisi (PhD) is the head of Postgraduate Studies at the Labuan International Campus of the University of Malaysia Sabah, Malaysia. Dr Ndubisi has published articles in a number of prestigious journals. He holds two prestigious research awards. His research interests

and post-graduate supervision are in the area of technology marketing, electronic transactions, services and relationship marketing and entrepreneurship. Muhamad Jantan (PhD) is the director of the Centre for Policy Research at the University of Science Malaysia. Dr Jantan is professor of operations strategy. He has published a number of articles in the area of operations management, an area he has also supervised a number of post-graduate research. His research interests are in the field of operations strategy and operations management. Cha Hing Loo (PhD) was formerly a postgraduate student in the School of Management, University of Science Malaysia, Malaysia. Cha Hing’s research interest is in the area of and supplier relationship management. Mat Salleh Ayub (PhD) is currently a doctoral student. He was formerly the coordinator of the entrepreneurship program at the School of Business and Economics, University of Malaysia Sabah, Malaysia. His research interests are in the area of entrepreneurship and marketing.)

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The role of logistics in linking operations and marketing and influences on business performance Bu¨lent Sezen Gebze Institute of Technology, Faculty of Business Administration, Cayirova Fabrikalar Yolu, Gebze, Kocaeli, Turkey Abstract Purpose – This study explores the individual and joint effects of operations, marketing, and logistics functions on the level of business performance. The main purpose is to test whether the business performance achieved when logistics function is in complete coordination with operations and marketing functions is superior to the performance when the functions operate in a less coordinated manner. Design/methodology/approach – Study hypotheses regarding the links between coordinated and non-coordinated performances and overall business performance are evaluated through a survey of automobile manufacturers in northwest Turkey. Separate regression analyses are conducted to test the hypotheses. Findings – It is shown that overall business performance achieved when there exists an effective coordination between the functions can be well above the performance achieved when the tasks are performed individually. Specifically, results from regression analyses performed to test the validations of study hypotheses indicate two important implications: coordination between operations and logistics functions in the specific sample is the most prominent issue for achievement of high performance; and logistics function carries an important role in linking the two most important functions of a company namely, operations and marketing. Originality/value – This study adds some value to the current literature such that it empirically shows the links between coordinated and non-coordinated functional performances and overall business performance, and eventually raises the importance of logistics function in a manufacturing-oriented business environment. Keywords Logistics, Marketing, Business performance, Turkey Paper type Research paper

The Journal of Enterprise Information Management Vol. 18 No. 3, 2005 pp. 350-356 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410390510592012

Introduction Success of a business firm is largely dependent on achieving an effective coordination and integration among individual units of the organization. A great deal of literature related with this issue of coordination between parts of an organization is attributed to two major business functions: operations and marketing (Ellinger et al., 2000; Morash et al., 1996). There are several factors that may prevent an accordant operation between these two functions. For example, while marketing department’s aim is to increase sales through price cuts and promotions, the goal of operations department can be to achieve a higher level of quality in products, thereby increasing the cost (and price) of the product. Certainly, such differences will result in severe contradictions between the actions taken by each department. The most prominent connection between operations and marketing is logistics. The tasks of the logistics function usually necessitate close interactions with both

operations and marketing functions. Supporting this distinguishing role of logistics, several past studies emphasized the importance of logistics and the relationships between these three functions (Emerson and Grimm, 1996; Gattorna et al., 1991; Morash et al., 1996). The aim of this study is to test whether the level of business performance achieved when logistics function is in complete coordination with operations and marketing functions is higher than the level of performance when the three functions operate separately, and to measure the relative importance of logistics function in integrating the other functions. Based on these objectives, major activities of a business organization are divided into the following categories: . activities purely related with the operations function; . activities purely related with the marketing function; . activities purely related with the logistics function; . activities related with both operations and logistics functions; and . activities related with both marketing and logistics functions. A survey questionnaire, including items specifically measuring a business firm’s performances on these five different activity categories and a general business performance scale, was developed and applied on the managers of automobile manufacturers located in northwest Turkey. Logistics, marketing, and operations departments and their activities Correspondents of the logistics unit are external and internal customers, distributors, and suppliers. Some major tasks of the logistics include moving, storing, and recording raw materials/work in process/products, ensuring an efficient flow in marketing channels, cost minimization in the entire processing of orders, and thereby, increasing the profitability in general (Gattorna et al., 1991). Logistics performance can be evaluated by considering logistics costs, customer satisfaction, product availability in the market, conforming to the promised delivery dates and quantities, flexibility in all logistics activities, and efficiency in inventory management. The responsibilities of the marketing unit are to determine target consumers, understand their thinking and life styles, and guide in how the company resources will be used in order to meet those requirements of the customers. There are several issues that are related both with the marketing and logistics functions. For example, packaging is such an issue. Coloring and labeling a package are marketing related concerns, whereas unit size of the package and easy handling are some of the issues that should be considered by both departments. Therefore, a cooperative work is needed between the marketing and the logistics people for making such decisions. Operations unit is responsible for manufacturing the required quantity of products, in the quality and time demanded by customers by using materials, equipments and human resources in the minimum possible cost. Operations function should always be in close interaction with other units of the organization in order to be able to employ company resources in an efficient manner. For example, for acquisition of materials and equipments, it should work together with people in finance department; whereas, for order shipments, material handling, and inventory policies, it should communicate with the logistics unit.

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The effects of individual versus coordinated performances of the functions on business performance and hypotheses The effects of marketing and logistics Lack of coordination between the marketing and the logistics departments may result in weak cooperation and lower overall business performance. Voorhees et al. (1988) assert that packaging, customer services, and order transactions are major areas of possible disagreements between the two functions. Johnson and Borger (1997) list some important complaints about logistics and emphasize the fact that marketing managers do not completely understand what the real meaning of logistics function is. On the positive side, a well-coordinated, harmonic relationship between marketing and logistics is reported to create higher satisfaction levels for both sides (Lynagh and Poist, 1984). Similarly, Murphy and Poist (1996), Ellinger et al. (2000), Voorhees et al. (1988) and Emerson and Grimm (1996) show that cooperatively managed marketing-logistics activities increases satisfaction, reduces faults in delivery, and provides efficiency in price and service policies. Since this cooperation and higher satisfaction of individual units is expected to provide a suitable base for higher levels of business performance (Murphy and Poist, 1996), their best influence on overall business performance should be observed when the marketing and logistics units work together on the tasks that they have joint responsibilities for.

H1a.

There is a positive relationship between the cooperative performance of marketing-logistics activities and the overall business performance.

H1b. The effect of cooperative performance of marketing-logistics activities on the overall business performance is greater than the effects of their individual, non-coordinated performances on the overall business performance. The effects of operations and logistics Since operations and logistics units should exchange information regarding such issues as demand forecast, material handling, and customer services, coordination in their joint activities becomes an especially important concern (Gattorna et al., 1991). Logistics is also crucial for the operations personnel’s interactions with other departments. Edwards and Lucas (1990) and Morash et al. (1996) show that effective cooperation between operations and logistics increases the effectiveness in distribution and customer services, reduces supply related costs, and provides an easier control of demand changes. Therefore, the best influence of operations and logistics functions on overall business performance should be expected when they work together on the tasks that should be performed by both. H2a.

There is a positive relationship between the cooperative performance of operations-logistics activities and the overall business performance.

H2b. The effect of cooperative performance of operations-logistics activities on the overall business performance is greater than the effects of their individual, non-coordinated performances on the overall business performance.

Method A survey study of automobile manufacturers was conducted in the northwest part (Marmara and Ege regions) of Turkey for testing the hypotheses developed. The firms that operate the three functions (operations, marketing, and logistics) in three separate departments are selected among all the manufacturers in this sector. This selection procedure yields a total of 142 automobile manufacturing firms in the specific region. Sixty-eight of these manufacturing firms are located in the Marmara region – which is also the region of the research team. The top managers of these companies accepted face-to-face interviews for completing the questionnaires. The remaining firms (74) were contacted via mail. Only 17 responses were received from these mail surveys. Thus, the total size of the sample that is used for analyses is 85, which is more than half of the total sampling frame of 142.

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Measures The measures of the questionnaire are developed based on the previous works that specifically investigated the relationships between logistics, operations, and marketing functions (Edwards and Lucas, 1990; Gattorna et al., 1991; Morash et al., 1996; Murphy and Poist, 1996). The first draft of the questionnaire is pre-tested and verified on 13 firms that are located in or near Istanbul. The questionnaire consisted of six sections. The first two sections measure the firm’s individual performances in logistics and operations functions, respectively. They are based on the scales of Gattorna et al. (1991) and Chow et al. (1994). The third section is related to the marketing performance of a firm, and it is adapted from Murphy and Poist’s (1996) study of relationships between operations, marketing and logistics. The fourth and fifth sections measure the firms’ cooperative performances of marketing-logistics and operations-logistics activities. These scales are specifically developed for the purposes of this study, and they ask respondents the level of “coordination performance” in activities that should be performed together. The final section measures the firm’s overall business performance (Fawcett and Clinton, 1996). All items are measured using five-point Likert-type scales (1-absolutely disagree; 5-absolutely agree). Table I represents descriptive statistics for all the study variables. Reliability tests indicate that all of the constructs have reliability coefficients (Cronbach’s a) greater than 0.60, and all variables are unidimensional, i.e. they load on to single factors. Mean

SD

4.31 4.04 4.08 3.96 4.06 4.02

0.52 0.65 0.59 0.60 0.59 0.53

LP LP OP MP L £ O L £ M BP

OP

MP

L £ O

L £ M

BP

– 0.44** 0.40** 0.37** 0.36** 0.19

– 0.26* – 0.34** 0.41** – 0.28* 0.42** 0.75** – 0.31** 0.34** 0.45** 0.39** – Notes: Significant at *0.05 level (two-sided); ** 0.01 level (two-sided); LP: logistics performance; OP: operations performance; MP: marketing performance; L £ O: logistics-operations coordination performance; L £ M: logistics-marketing coordination performance; and BP: overall business performance

Table I. Means, standard deviations, and Pearson correlations of variables

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Analysis and results Regression analyses are performed in order to test the validations of hypotheses developed in this study. Business performance is selected as the dependent variable in all regressions, and the average values of individual items have been calculated for all the six constructs before conducting regression analyses. In the first regression analysis, logistics performance, marketing performance, and logistics-marketing coordination performance are selected as independent variables. Table II shows the results of this regression including standardized b coefficients and their significance levels. While individual logistics performance has no significant effect on business performance, its coordination performance along with marketing is significantly influential on overall performance ðb ¼ 0:26Þ, and this coordination effect is higher than that of individual marketing performance ðb ¼ 0:21Þ, providing support for H1a and H1b. In the next regression analysis, the independent variables are logistics performance, operations performance, and logistics-operations coordination performance. Table III shows the results of this regression model. Again, individual performance of logistics has no significant effect on overall performance, whereas its coordinated performance with operations seem to be highly important for overall performance ðb ¼ 0:35Þ, and this coordination effect is higher than that of individual operations performance ðb ¼ 0:14Þ, providing support for H2a and H2b. In the last regression analysis, all the performance scales, except for overall business performance (the dependent variable) are selected as independent variables. This final regression model (Table IV) represents a full picture of all variables. The R 2 value shows that all the predictor variables represent 27 percent of the variance observed in overall business performance. As can be seen from Table IV, logistics-operations coordination performance (b ¼ 0:24; p , 0:05), logistics-marketing coordination performance (b ¼ 0:09; p , 0:05), and marketing performance alone (b ¼ 0:50; p , 0:05) have significant effects on overall performance at 0.05 level, providing support for H1a and H2a.

Independent variable Table II. The effects of logistics, marketing, and their coordination on business performance

Logistics-marketing coordination performance Marketing performance Logistics performance

Significance ( p)

0.26** 0.21* 0.01

0.005 0.023 0.496

Notes: Significant at *0.05 level (two-sided); ** 0.01 level (two-sided); R 2 ¼ 0:20; and F ¼ 6:3

Independent variable Table III. The effects of logistics, operations, and their coordination on business performance

b

Logistics-operations coordination performance Operations performance Logistics performance

b

Significance ( p)

0.35** 0.14** 0.04

0.000 0.006 0.368

Notes:**Significant at 0.01 level (two-sided); R 2 ¼ 0:24; and F ¼ 7:5

Discussion and managerial implications For this specific sample, when evaluated together with all other variables, individual logistics performance seems to be non-significant for the overall business performance. However, this finding should not be misinterpreted. Instead of considering the individual effect of logistics, we should consider its indirect effects through the coordination achieved between logistics and operations and logistics and marketing. We can see from Table I that logistics performance variable has high correlations with almost all other variables. Based on the regression results and these correlations, we can conclude that the indirect, rather than the direct, influences of logistics performance through its interactions with other functions can be more clearly observed in the specific sample. From the managerial standpoint, coordinating and managing logistics function together with other major functions will have positive implications for the overall business performance. Another important result of the study is that logistics-operations coordination performance has been found to be the most influential factor on the overall business performance. The coordination between these two important functions will also have major advantages in terms of procurement, just in time production, cost reductions, and fast delivery. The answer to the question of “why logistics-operations coordination is more important than the logistics-marketing coordination” most probably lays in the manufacturing orientation of the specific sample, the automobile manufacturers. Most of the recent research studies concentrate on excellence in functional areas. However, success in one or two functional areas may not be sufficient for being successful in all other functions. Competitive advantage and improved system performance can be achieved only through effective coordination and communication between all functions (Morash et al., 1996). Although operations, marketing, and logistics functions by themselves are all important factors for business performance, this study shows that their coordinated working toward problem solving is the most important factor for the existing and future performances of the organizations.

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Conclusion Results of a survey conducted in the automobile manufacturing industry in northwest Turkey show that business performance achieved through effective functional coordination is higher than the performance achieved when the tasks are performed individually. In line with previous work on the subject of coordination between logistics, operations and marketing functions, this study proves that the overall business performance will be significantly improved through the way in which the logistics function is effectively integrated with both upstream operational function and

Independent variable Logistics performance Operations performance Marketing performance Logistics-operations coordination performance Logistics-marketing coordination performance

b

2 0.10 0.13 0.17* 0.24* 0.09* Notes: *Significant at 0.05 level (two-sided); R 2 ¼ 0:27; and F ¼ 5:3

Significance ( p) 0.203 0.070 0.050 0.039 0.026

Table IV. Effects of all variables on overall business performance

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downstream marketing function in the supply chain. Two important findings of the empirical study are: . coordination between operations and logistics functions in the specific sample is the most prominent issue for achievement of high performance, and . logistics function carries an important role in linking the two most important functions of a company, operations and marketing. An extension to this study could be to implement the similar empirical context into other manufacturing industries.

References Chow, G., Heaver, T.D. and Henriksson, L.E. (1994), “Logistics performance: definition and measurement”, International Journal of Physical Distribution & Logistics Management, Vol. 24 No. 1, pp. 17-28. Edwards, L. and Lucas, R. (1990), “Integrated logistics systems with distribution resource planning”, Logistics Information Management, Vol. 3 No. 4, pp. 21-36. Ellinger, A.E., Daugherty, P.J. and Keller, S.B. (2000), “The relationship between marketing/logistics interdepartmental integration and performance in U.S. manufacturing firms: an empirical study”, Journal of Business Logistics, Vol. 21, pp. 1-22. Emerson, C.J. and Grimm, C.M. (1996), “Logistics and marketing components of customer service: an empirical test of the Mentzer, Gomes and Krapfel model”, International Journal of Physical Distribution & Logistics Management, Vol. 26, pp. 29-42. Fawcett, S.E. and Clinton, S.R. (1996), “Enhancing logistics performance to improve the competitiveness of manufacturing organizations”, Production and Inventory Management Journal, Vol. 37 No. 1, pp. 40-6. Gattorna, J., Day, A. and Hargreaves, J. (1991), “Effective logistics management”, Logistics Information Management, Vol. 4 No. 2, pp. 14-28. Johnson, J.C. and Borger, D.L. (1997), “Physical distribution: has it reach maturity?”, International Journal of Physical Distribution & Materials Management, Vol. 7 No. 5, pp. 283-93. Lynagh, P.M. and Poist, R.F. (1984), “Assigning organizational responsibility for interface activities: an analysis of PD and marketing manager preferences”, International Journal of Physical Distribution & Materials Management, Vol. 16 No. 6, pp. 34-46. Morash, E.A., Dro¨ge, C. and Vickery, S. (1996), “Boundary-spanning interfaces between logistics, production, marketing and new product development”, International Journal of Physical Distribution & Logistics Management, Vol. 26 No. 8, pp. 43-62. Murphy, P.R. and Poist, R.F. (1996), “Comparative views of logistics and marketing practitioners regarding inter-functional co-ordination”, International Journal of Physical Distribution & Logistics Management, Vol. 26 No. 8, pp. 15-28. Voorhees, R.D., Teas, R.K., Allen, B.J. and Dinklie, E.T. (1988), “Changes in the marketing-logistics relationship”, Journal of Business Logistics, Vol. 9 No. 1, pp. 34-50.

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Addressing uncertainty and inequality in nuclear policy

Uncertainty and inequality in nuclear policy

E. Laes Belgian Nuclear Research Centre (SCKzCEN), Boeretang, Mol, Belgium

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W. D’haeseleer Energy Institute (KULeuven), University of Leuven, Heverlee, Belgium, and

R. Weiler CABME (Centre for Agrarian Bio- en Environmental Ethics) (KULeuven), University of Leuven, Heverlee, Belgium Abstract Purpose – This paper analyses the justification of technological choices and options in the context of nuclear energy policy. We argue that “society” increasingly demands a justification with regard to the level of uncertainty and inequality a certain technological choice induces. We aim to demonstrate that policy makers in fact do address these issues, but depending on how they define the problem, this is done in a more explicit (overt) or implicit (covert) way. Design/methodology/approach – First, the changing context with regard to the justification of technological choices is briefly sketched. We draw the attention to the link between the way a certain (energy) policy problem is defined, and the way the framework for political decision-making is set up in response to the problem. In order to clarify this observation, we make use of a scheme derived from policy sciences, mapping out policy problems in two dimensions: the (lack of) certainty concerning the kinds of knowledge a problem may require, and the (lack of) consensus on relevant values (i.e. “the common good”, “basic rights”, etc.). Each type of policy problem requires a distinct solution strategy. A so-called Type III-error occurs when the wrong problem is solved by employing a strategy which does not apply to the problem at hand. In that case, political theory predicts strategic behavior in order to actively suppress or blur value differences. The Belgian decision to phase out nuclear power is used as a case study to illustrate some of the theoretical implications of the scheme. Findings – Several Type III-errors could be demonstrated in the case of the Belgian phase out. In this case, social learning was severely hampered by different methodological approaches; lack of data; different perceptions of relevant time scales; different framing of the problem; institutional barriers; lack of communication; strategic use of scientific assessments by different stakeholders; and insufficient knowledge of scientific assessments. Originality/value – The paper aims to broaden the debate on energy policy outside the boundaries of institutional decision-making. We conclude with some practical recommendations for future energy policy, regarding problem structuring, defining possible options, goal and strategy formulation and monitoring of choices. Keywords Decision making, Nuclear energy industry, Risk assessment, Sustainable development Paper type Research paper

1. Introduction The acceptance of sustainable development as a guiding principle for policy-making has provided a stimulus for rethinking the justification of technological choices and options. In a first part of this paper, we examine this changing context and the implications for technology assessment (TA) and technology policy. The resulting theoretical framework allows one to both describe how policy makers, analysts, policy

The Journal of Enterprise Information Management Vol. 18 No. 3, 2005 pp. 357-376 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410390510592021

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advisors, etc. justify (technology) choices under the umbrella of sustainable development, and arrive at normative conclusions about possibilities for improvement. As a case study, we take a look at the justification given for the nuclear phase out in Belgium, based on official policy documents and interviews with members of the Belgian Federal Council on Sustainable Development. We conclude with some recommendations.

358 2. Theoretical background 2.1 Uncertainty and inequality The long-standing practice and theory development in TA and policy makes it hard to consider conceptual issues in a few lines. After all, TA has been studied from very diverse points of view, including (but not limited to) policy analysis, systems analysis, the sociology of scientific knowledge, and communication theory. Despite the difficulties of generalization, two (mutually intertwined) issues in TA and policy stand out in this very large and equally diverse body of scientific thought: uncertainty and inequality. The issue of uncertainty is widely seen as a key characteristic of modern science and technology. In fact, it is the main driving force behind different policy movements such as the acceptance of the precautionary principle as a guideline for environmental and health policy on a national and international level, and behind new developments in TA practices. In order to make a justified (technological) choice, policy makers ideally have to anticipate and reduce the uncertainties linked to this choice, or at least clearly state the limits of “state-of-the-art” knowledge. On the other hand, the issue of inequality reflects the fact that resources and opportunities to influence the decision-making process (starting from defining or structuring the problem definition to implementing solutions) are not the same for everyone. Additionally, those who take decisions may or may not be those who in the end become affected. Again, on this issue, there is a long tradition of reflection, mainly with regard to participation. For our purposes, it suffices to characterize both issues further based on an analytical distinction (in an ideal-typical sense) in three dimensions: a cognitive, normative and a pragmatic dimension (Klu¨ver et al., 2000). Hence, this leads to the following scheme. 2.1.1 Uncertainty . Cognitive uncertainty. With knowledge production accelerating, cognitive uncertainty may be generated as the understanding of phenomena becomes even more complex, and at the same time, principal limits of knowledge emerge. This is often called the “problem of expertise”: policy makers are often faced with a lack of uncontested factual knowledge. . Normative uncertainty. Scientific developments might raise new questions and problems for which ethical principles or existing standards or norms are not applicable. Alternatively, it might be unclear which values are at stake for different social actors or the public at large. . Pragmatic uncertainty. Results from the difficulties encountered in policy-making processes to reach conclusions and, under the above-mentioned conditions of cognitive and normative uncertainty, to implement decisions in a

turbulent social environment. Not only the consequences of developments, but also the reactions of social actors and the possible interactions with other policy fields can be very uncertain. 2.1.2 Inequality. . Cognitive inequality. reflecting different social actors’ perspectives or knowledge of technological and scientific issues. . Normative inequality. reflecting the plurality of (possibly conflicting) norms and values. . Pragmatic inequality. Reflecting the unequal distribution of institutional or informal influence on decision-making processes shaping the technology in question, as well as the unequal distribution of resources that enable actors to take part in such processes. These problems are often summarized in the phrase that “technology policy has to function in a complex world”. By simply reversing the polarity of the problems encountered, it becomes very easy to draw a picture of an ideal policy-making process (including its cognitive base), as is done in some theories of participatory democracy. Technology policy should then take into account all relevant disciplinary insights, the full spectrum of points of view, a most complete set of options, etc. The claim is made that in this way, technology policy will achieve a higher degree of legitimacy and functionality. This point of view is often criticized as being an utopian to be of any use in practical circumstances, which are, after all, characterized by multiple tensions, such as limited time, resources, or power play between political actors. It is a foregone conclusion that in reality, no (technology) policy-making process can meet all of these criteria at once. But in our view this does not detract from the usefulness of the general overview of issues presented above, for two reasons. The first is that policy makers, when justifying technological choices, implicitly or explicitly have to make choices when addressing these problems, e.g. regarding the knowledge base; acceptable levels of uncertainty; or whom to include or exclude in the policy-making process, at which stages, and how. The second reason is that while the “ideal” picture may not be achievable or even desirable in all circumstances, it might be in some. This point will be discussed further in the following section. 2.2 Structured vs unstructured policy problems One line of reasoning in policy sciences links the content of policy problems to methods of political decision-making. In other words, authors from this school (Grin, 1997; Hisschemo¨ller, 1993) claim that different approaches to decision-making and knowledge production are justified in light of different conceptions of the problem at hand. The fact that policy problems are political constructs is generally recognized in policy sciences; however, much less attention is given to how these problems are constructed or defined. In other words, much attention is given to the strategies deployed to solve problematic situations, rather than to the logically preceding phase of problem structuring. Furthermore, these authors argue that the “real” power lies with the one who is able to impose his/her definition of the problem at hand, because together with the problem definition, the available scope for solution finding is “smuggled” furtively into the decision-making process.

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Table I. Structured vs unstructured problems in TA and policy

Four types of problems can be mapped out in two dimensions. One dimension refers to (the lack of) certainty concerning the kinds of knowledge a problem may require. The other refers to the (lack of) consensus on relevant value perspectives (i.e. the common good, basic rights, etc.). A problem is termed structured when there is a high degree of consensus and certainty. A problem is referred to as moderately structured (ends) when there is a consensus on relevant values and uncertainty or dissent on what kind of knowledge is relevant. A problem is called moderately structured (means) when there is a consensus on what kind of knowledge is relevant, but ongoing dissent with regard to the values at stake. A problem is called unstructured when there is neither consensus nor certainty. Table I gives a schematic representation. Next, the claim is made that these different types of problems require different strategies for finding solutions. All of these strategies are compatible with the basic idea of the democratic constitutional state, but promote (fundamentally) different conceptions of democratic method or practice[1] to address the issue of uncertainty and inequality raised in Section 2.1. Broadly speaking, structured problems require solutions according to standard procedures involving quantifying technical methods. Unstructured problems require methods for clarifying or finding the problem itself. These methods focus on social and political interaction, rather than on quantifying techniques in order to reveal the assumptions of policy actors holding divergent views. Some measure of problem structuring is needed in these cases, implying awareness-raising of a problem by means of confronting, evaluating and integrating as much (potentially) contradictory information as possible. Two types of policy strategy (policy as a rule, policy as accommodation) are encountered in nuclear or energy policy and will be detailed further[2]. In the last section of this paper, we will offer some thoughts on policy as social learning in the context of the future of nuclear energy in Belgium. Lastly, the chain of argumentation is completed by the concept of the so-called “Type III-error”[3]. A Type III-error occurs when the wrong problem is solved by employing a method that does not apply to the problem at hand. For instance, when policy as rule is applied to a problem which implies a political choice regarding the values at stake, political differences of opinion need to be actively suppressed or blurred. After all, a structured problem implies a large consensus on the technical nature of the problem at hand. The crux is thus to demonstrate or identify the mechanisms by which certain interests or points of view are marginalized. Before

Dissent on small facts

Dissent on large facts

Dissent on small values Structured problem Little need for additional TA Policy as rule

Moderately structured problem (ends) Use TA to clarify facts and causal connections Policy as negotiation

Dissent on large values Moderately structured problem (means) Interactive form of TA could be useful (with explicit consideration of value perspectives) Policy as accommodation

Unstructured problem Use interactive forms of TA Policy as social learning

proceeding with the intended examination of the policy development cycle for the Belgian nuclear phase out, two remarks seem to be in place here. Firstly, the scheme represents not merely an academic interest; it has been tested empirically. The four types of problems correspond to empirical observations of TA practices and policy approaches, which makes it a suitable candidate for our purposes. Secondly, the scheme should not be used as a technical instrument for an objective approach of the policy problem at hand (i.e. we encounter policy problem x, so we should apply approach y). One should always keep in mind that policy problems are social and political constructs. Whether or not there is a consensus about the values at stake or about relevant knowledge is always an (inter)subjective affair. The classificatory scheme should rather be regarded as a methodological aid for empirical observation and as a guideline for a substantiated problem choice. Furthermore, its main value does not lie in providing new and directly “usable” knowledge for policy-making. Rather, it points to the “white spots” and the uncertainties in the information on a policy problem because alternative problem approaches, and the corresponding policy strategies, are made visible. All of these strategies are characterized by a certain approach to knowledge production and utilization, by patterns of interaction and inclusion/exclusion mechanisms. The aim of the scheme is thus to make the one-sidedness of certain approaches more visible, without however giving a decisive answer on the “correct” interpretation. A justified problem choice always remains a (partly) normative choice, be it from the part of a policy analyst, an observer, a policy maker or other stakeholders. Taking together these two remarks, it can be said that the value of the classificatory scheme lies in a more adequate description of democratic methods (not only solution-oriented but also problem-oriented) and in suggesting possibilities for improvement. In the following sections, we aim to reconstruct the process of justification underlying the parliamentary decision to phase out nuclear power in Belgium, and we will also confront the official justification with some alternative points of view. We will try to demonstrate some so-called Type III-errors and in the concluding remarks suggest some possible improvements. The reconstruction is based on a variety of sources, including scientific literature, official policy documents, positions papers, leaflets, etc. Furthermore, our analysis is guided by in-depth interviews with members of the Belgian Council for Sustainable Development (FRDO/CFDD) (Laes and Meskens, 2002). 3. The phase-out decision in a historical perspective One might argue that in Belgium, as in many other industrialized countries, the energy sector has been shaped in the past (roughly before 1990) by the dominant importance accorded to strategic issues and competitiveness: the energy supply was diversified in order to minimize the geopolitical risks of dependence on oil-exporting countries and measures were provided to guarantee a secure and continuous supply of energy at a reasonably competitive price for all concerned. The post-war “social pact” formed the core of energy policy: representatives of both employers and employees recognized the need for a growing economic output in order to maximize welfare, and direct state intervention was encouraged. Historically, the bargaining process among the interested parties has led to a low priority for measures to promote a rational use of

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energy (because this interest was not directly advocated, or even implicitly opposed). This situation is now changing quite drastically, as a result of the ongoing liberalization of the energy sector in Europe and the higher importance of environmental issues on the political agenda, most notably the Rio Declaration (UNCED, 1992) and the Kyoto Protocol (UNFCCC, 1997). In this context of profound change, the nuclear phase out was first announced in the Government policy statement of 7 June 1999 (at the beginning of the legislature of the previous government), together with the intention to comply with the Kyoto agreements[4]. The phase-out scenario means that the Belgian nuclear power plants would effectively be taken out of service in the period 2015-2025 (after 40 years of operation), whereas Belgium now provides for close to 60 percent of its electricity needs by nuclear power generation. A strategic analysis of the Belgian electricity generation system was first commissioned in April 1999 by the predecessor of the State Secretary of Energy and Sustainable Development of the Belgian government 1999-2003. A group of experts (the AMPERE Commission) was appointed to contribute to this analysis (AMPERE Commission, 2000). Its mandate was to analyze the global context with regard to the economy and energy, to estimate the long-term electricity demand (set by the commission towards the year 2020), and to evaluate potential energy technologies with regard to their economical, ecological and social impacts. A few months later, the new government (a coalition of liberal, socialist and green parties) came into office, and the state secretary of Energy and Sustainable Development modified the assignment of the AMPERE Commission according to the new orientations in energy policy. Hence, the commission was asked to take into account the scenario to phase out nuclear power plants (while paying particular attention to an evaluation of the costs of radioactive waste management and dismantling of existing power plants), the Kyoto agreements (signed by Belgium on 29 April 1998), and the best international practice concerning demand-side management (DSM). In October 2000, the commission presented its results. It recommended keeping open the nuclear option by maintaining its nuclear expertise through a continuing participation in national and international research on new nuclear reactor types (AMPERE Commission, 2000, Executive Summary, p. 83). Publication of the AMPERE report was followed by a peer review by experts of international renown (Bourdeau et al., 2001). Although the AMPERE Commission does not explicitly position[5] its activities under the perspective of sustainable development, the report remains a focal point in the discussion, as it is the only recent prospective analysis for the Belgian electricity sector (albeit without taking into account the aspects of liberalization). All participants in the debate, be it proponents or opponents of the nuclear option, have felt obliged to refer to the AMPERE report. In the Federal Plan for Sustainable Development (2000-2004)[6] (ICDO, 2000), the nuclear phase out was also briefly referred to. The government engaged itself to draft a justification of this choice. This justification would elaborate on the following elements: the planetary impact of a widespread use of nuclear power generation, a long-term vision on nuclear energy, the integration of the dismantling of nuclear power plants in a global strategy to reduce CO2 emissions and to change consumption habits, and the

scientific uncertainties surrounding nuclear energy. However, the promised note was never published. 4. Justification of the nuclear phase out as a well-structured problem 4.1 The nuclear phase-out law in a nutshell The phase-out law (published in the Belgian law gazette on 8 February 2003) was the culmination of the political decision-making process. Earlier, a preliminary draft of this law was discussed by the Council of Ministers before being presented to parliament. The main interest of this draft lies in its explanatory annex: in fact, this is the only available official document giving some indications on the rationale behind the government’s initiative and the parliamentary decision (Parl. DOC 50 1910/001)[7]. Apparently, the government was not willing to organize a large societal debate on the issue, as an emergency treatment of the proposal of law by the parliament was demanded [8]. In Appendix, an overview is presented of the policy development cycle, with the relevant policy questions and the corresponding answers taken from the above-mentioned official documents. Some selected issues from this table will be developed further in order to demonstrate how in this case the policy problem was transformed in a tractable technical form. For a more thorough discussion of the phase-out law, we refer to Michiels (2003) and D’haeseleer (2003). 4.2 Recasting the problem in a technical mould Technical approaches to policy problems are supported by certain policy claims: . the problem can be circumscribed within the limits of one or a few academic disciplines (most notably engineering and economics); . within these academic disciplines, there is a general consensus on the applicable methods (or new methods are developed within the disciplinary limits); . experts are easily recognizable based on academic qualifications; . participation by other actors (non-specialists) is very limited; . transparency is very limited; . decisions are preferably taken by one political body (which appears as a “monolithical block”, e.g. “the legislator”); and . the problem is tractable within the mandate of recognized bureaucratic institutions (the hierarchy of existing institutions is respected). Furthermore, a technical approach can only function properly within the limits of given policy goals. Let us start with the policy goals directly related to nuclear policy. First of all, it is remarkable that the real motives of the nuclear phase out are hardly discussed. No explication of the motives is found in the explanatory annex of the proposal of law (Parl. DOC 50 1910/001), and, as mentioned earlier, the announced explicatory note in the Federal Plan for Sustainable Development was never published. It is clear that the legislator wants to phase out the existing nuclear power plants for electricity production[9], and that new power plants cannot be built. This decision only applies to nuclear fission technology, not to nuclear fusion. However, in response to one of the hearings organized in the course of the policy development cycle[10] (and also in some interviews in newspapers), the State Secretary specified that the phase out is justified because of:

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.

.

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the risk of catastrophic accidents, which are admittedly very low, but, in the words of the State Secretary, entirely unmanageable in a densely-populated country such as Belgium; proliferation risks, where the greatest area of concern is the fabrication of a so-called “dirty bomb” (spreading radioactive material with a conventional explosion); and the risks posed by the management of nuclear waste, and, most notably, irreducible uncertainties linked to the management of high-level waste over very large time spans.

Earlier on, we mentioned the fact that in a technical conception of policy-making, goal setting could not be discussed. As a matter of fact, this is not entirely true. This approach may also be applied in goal setting, but for this, the goals in question have to be transformed into technical standards. The transformation of the concept of “risk” into a technical issue serves as an excellent example here. In view of practical applications in the policy sphere, risk was defined as the probability of an adverse event multiplied by its (quantitative) consequences (e.g. number of casualties, number of injured, etc.). As a consequence, according to a certain (technical) interpretation, different risky activities become comparable on an equal basis. One might also be tempted to set technical standards to the societal acceptability of risky activities, e.g. a risk of 102 6 per year (i.e. one casualty in a million years of activity) is often proposed as a general “acceptable risk ceiling” for society. Why this little excursion into risk theory? We want to make the point that by interpreting the goals of the phase-out law as the State Secretary did (i.e. catastrophic risk, proliferation risk, and long-term risks of high-level radioactive waste), these goals are clearly set beyond the limits of a technical risk discourse. The goals are said to be “ethical”, meaning, in this case, beyond (a strictly technical) discussion. After all, how can one reasonably calculate the risk that someone will construct a “dirty bomb” in the years to come? And is it not true that the consequences of a serious reactor accident are “incalculable” (true, the probability is very low; so, in mathematical terms, the problem is the unstable mathematical case of “zero £ infinity”)? But while the goals of the phase-out law are effectively placed beyond the limits of a technical debate, the means are not. And then, in light of reaching these goals (and the broader goals of energy policy, cf. infra), many questions can be raised regarding the efficiency and effectivity of phasing out nuclear power plants once they have reached a 40-year lifetime. For instance, why is the operational life span limited to 40 years? In the United States, life extensions have already been granted by the US Nuclear Regulatory Commission (NRC) to a number of nuclear power plants for an additional 20 years of operation beyond the current 40 year license (Hashemian, 2002). In the Belgian context, detailed calculations (subject to the boundary condition of safety rules) would indicate whether this is a conceivable option from a socio-economic point of view. However, the opportunity to stage a debate on this issue was not taken, contrary to France for instance, where a recent report (Bataille and Birraux, 2003) thoroughly analyzes lifetime extensions and comes to quite favorable conclusions. Furthermore, regarding proliferation and safety, should we infer from the rationale of the phase-out law that the reigning international and national safety and proliferation regime (conventions, laws, etc.) are considered to be insufficient as a

guarantee? If safety is the issue, will further research into passively safe reactors be encouraged? These are all reasonably conceivable questions in light of the above-mentioned goals which simply have not been addressed in the policy-making process. Regarding the broader goals of energy policy, it is fair to say that these can generally be summarized as guaranteeing a secure and reliable energy supply, with a high level of safety, with minimal impact on the environment, providing large opportunities for a qualitative employment and leading to acceptable prices for both industrial and private consumers. In the explanatory annex to the law, and in the parliamentary hearing, an attempt is made to show that all of these objectives can be reconciled with the objective of phasing out nuclear power. Only for the issue of energy security explicit (but nevertheless still non-binding) provisions are made: this has to be monitored by the Commission for the Regulation of Electricity and Gas markets (CREG) on a yearly basis (starting from 2015) and can be invoked by the government as a cause of “force majeure”[11]. Of course, one of the issues which has drawn a great deal of attention is the compatibility of the phase out with the (post-)Kyoto commitments. Let us take this as just one example for the question of justification. In this discussion, the justification of the law relies on the CO2 emission results of a purely hypothetical and exemplary reduction scenario of electricity demand developed by the AMPERE Commission. In fact, this commission points out that between a high-growth scenario and a low-growth scenario, 17 Mton of CO2 could be avoided. But these are purely theoretical figures, i.e. there is no certainty that either the high or the low-growth scenario is more “real” (actually, recent increases in electricity consumption were of the order of magnitude of 2-3 percent per year). First, the explanatory annex gives no details about how this reduction of 3 percent per year could be reached. Second, it will already be necessary to advocate a low-growth scenario to be able to reach the (post-)Kyoto reduction with nuclear power still present. No matter how it is explained, an overnight nuclear phase out will result in an increase of CO2 emissions of about 16-17 Mton. This is not to say that government should not take active measures to promote the rational use of energy pending more detailed analysis of the reduction potential. We only point out that the justification given in the proposal of law is, at best, based on shaky foundations. The justification given in the policy documents quite frequently quotes the conclusions of the AMPERE Commission, and thus gives the appearance of relying heavily on expert opinion. However, it is often unclear whether this is really the case. For instance, when the explanatory annex to the law announces the government’s intention to “keep open the nuclear option”, it is not certain that this means quite the same as the AMPERE Commission’s recommendation to “keep open the nuclear option”. The consequences of the phase-out law can also be dealt with within the mandates of existing institutions; no additional institutional structures need to be created. Regarding broad participation, we already mentioned the fact that the government demanded an emergency treatment of the proposal of law, a fact which inspired some members of parliament to criticisms of “dogmatism” and a “lack of respect for the parliament” (Parl. DOC 50 1910/004, p. 10). This being said, participation in the drafting of the Federal Plan for Sustainable Development was encouraged (although it did not result in the promised explanatory note as mentioned earlier).

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Summing up, we believe it is fair to say that an attempt was made to recast the nuclear phase out as a technical or well-structured problem. But this could only be done by leaving a great amount of “white spots” in the justifications given (only a few of which have been hinted at in the preceding section). In the remainder of the text, we will explore some alternate points of view.

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5. Continuing the problem as one of accommodation This position (mainly expressed by representatives of unions during the parliamentary hearings and the interviews we conducted) seems to be caught in a paradox. The position on the future role of nuclear power under the flag of sustainable development was perhaps best phrased by one participant: “As long as there is no real commitment to the development of a vision on long-term alternatives for nuclear power, a phase-out scenario is nonsense. But, if society does not want to consider the phase-out of nuclear energy, the motivation to think about alternatives will also be very weak”. The unions stated that they were not interested in the “pro or contra” discussion about nuclear power; rather, that attention should be given to the institutional embedding of this technology is society. They prefer a real balance between economic, social and environmental development. Of course, there is some discrepancy between different unions in how these rather general objectives should be reached. For instance, the socialist union wanted to link the phase-out decision to a guaranteed investment in measures for rational energy use and the assurance that enough replacement investments will be made (in order to safeguard jobs in the energy sector) at the time of the phase out (2015-2025). The demand was made that these measures should be financed by the owners of the nuclear power plants, since they have in the past enjoyed the benefits of a quick depreciation of their investments within the framework of a protected market (“stranded benefits”). Fear exists that in the future, nuclear power will be “inevitable” if one wants to respect post-Kyoto commitments and still foster economic growth. Rather, acceptance (or rejection) should be based on a democratic debate with the representatives of concerned parties, under conditions of full transparency. For now, according to this perspective, these conditions have not been fulfilled; too much is left in the dark: costs of decommissioning, costs of high-level waste management, but also the real costs of the business-as-usual scenario, etc. – all “great unknowns”. In other words, the unions are mainly concerned with the maintenance of some kind of system of social consultation (as a policy of accommodation), as it existed before the liberalization of the electricity market. This perspective runs the risk that in a liberalized market, the government’s power of intervention could be limited. 6. Recasting the problem as a transition towards “participatory democracy” From a different perspective (mainly environmental non-governmental organizations and some ecology-oriented scientists), citizen participation in decision-making is one of the cornerstones of energy policy. The suitability of the representative democratic model as a reference framework to fundamentally alter patterns of development is implicitly questioned. From this perspective, energy policy problems are fundamentally about economic or technological system dynamics that have evolved separately from the day-to-day life world of ordinary citizens. The assumption is that

the state actively intervenes in the habits and consumption patterns of its citizens. An example is the supposed “naturally increasing” demand for energy. Now, if the state is partly the cause of changes in the individual preferences, then clearly it cannot be deduced from the structure of preferences in the absence of the state that the state is desirable: for the state modifies, one might say, the assumptions from which its desirability can be deduced (here we are talking still within the limited context of energy policy). Thus, by exerting its powers, the state little by little takes away the responsibility of the citizens towards the community. Political apathy is considered to be a direct consequence of this development. The state tends to undermine the conditions which make the alternative to it workable, and in this way makes itself more desirable. It does this by weakening or destroying community. People nowadays are supposed to be uninterested in societal questions and are often not willing to take up responsibilities, as is witnessed by some statements during the interviews: “The link between the act (e.g. consumption leading to domestic waste) and the consequences (e.g. burning of domestic waste in incinerators) is not recognized; all responsibility is delegated to the governing bodies or society at large”. Still according to this viewpoint, a decisive factor in a transition towards a more participatory democratic energy policy will be the scale of technological systems. Small-scale technologies will be an enabling factor for this “local and basic democracy”. One participant gave the example of Denmark, where a large percentage of the taxes are levied by local authorities; thus, the spending of tax money will be much more transparent and interested citizens will enjoy a much larger degree of control. He referred to “the current practice of financing projects from an enormous government budget so that the total costs to society remain obscure”. Similarly, small-scale energy production technologies (solar panels, wind energy, etc.), owned by the consumers themselves, or local communities, will make energy use and its effects more transparent and accessible for debate at a local level. Such participation is difficult to achieve in a national and strategic discussion, the nuclear power question being an example par excellence. It turns out that involving citizens in an abstract, strategic problem concerning the whole of society is very difficult, because an important element for participation is clarity concerning what is at stake. Overall, people are supposed to become involved in decision-making issues only when they think that the issue is in their immediate interest. This perspective is in a certain sense very ambiguous. It stresses the opposition between the social rationality of participation in a community of energy producers and consumers (the “virtual power plant” – an interconnection of many individual small-scale electricity users and producers at the community level, supported by larger, nation-wide grids for emergency back-up) and energy policy guided by the state or pure market approaches. The socially rational energy community is most of all an ideal picture that has to be aspired to in a far-off future, because at present, the necessary conditions for the realization of this ideal picture are not considered to be fulfilled. This observation then produces the peculiar point of view that in order to close the gap between the present and the future, strong elements of the policy as rule are preferred. In order to promote participation in the future, participation in the present should be limited. Thus, governments need to exclude nuclear power based on strong ethical grounds, and rational use of energy and renewable energy must be promoted by

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making full use of a range of policy options open to policy makers under conditions of liberalized markets (e.g. efficiency standards for appliances, public R&D spending, energy taxation, internalization of external costs, etc.). By combining a nuclear phase out with international obligations to lower greenhouse gas emissions (or generally, tightening the limits of “environmental space”), the only conceivable policy option lies in substantially improving the rational use of energy (through a combination of efficiency and sufficiency measures), together with a promotion of renewable energy sources. 7. Wrap up and recommendations Earlier, we have briefly touched upon some results of an enquiry into the science/policy interface in the policy development cycle of a law to phase out nuclear energy in Belgium. Summarizing the more general picture (which we were not able to address fully within the limited context of this paper), social learning in this policy development cycle has been hindered by a number of factors (Laes and Meskens, 2002): . different methodological approaches (bottom-up vs top-down analysis of energy system); . lack of data (to perform the bottom-up analysis); . different perceptions of relevant time scales (or how to link short-term issues with long-term issues); . different framing of the problem (electricity vs energy system); . institutional barriers (e.g. to develop the needed long-term vision); . lack of communication (between political decision makers and scientists, between scientists and stakeholders); . strategic use of scientific assessments by different stakeholders, or . Insufficient knowledge of scientific assessments. We believe the problem can indeed be qualified as “unstructured” and could benefit from a much larger degree of social learning in the distinct phases of the policy development cycle (see Appendix). Therefore, we offer the following lines of thought as suggestions for improvement and at the same time as material for discussion. (1) Problem structuring At the most fundamental level of the discussion lies the assessment whether it is ethically justified to continue the reliance on nuclear power in a sustainable development perspective. This is an essentially political discussion. However, successful consideration of justification entails building shared values and common goals across stakeholders with conflicting views. The promised explanatory government note (see Section 3) could have been an important element in this strategy. The narrative of technological progress no longer guarantees an automatic social consensus. Consequently, the questions that would have to be addressed in this note seem to be going in the right direction: what is at stake here is the fulfillment of overriding sustainability objectives, such as respect for the autonomy of future generations, equity in world development, a safe world environment, etc.

(2) Defining the possible options/assessment of response . Care should be taken in defining the possible options for action. The AMPERE Commission mostly focused on tutorial material about technological options for electricity generation, while it seems that detailed information about strategies for DSM in the whole energy sector might have been more policy relevant. This observation points at the absolute necessity of efficient communication between the policy makers (who define the scientific themes and who select the scientists) and the researchers (who provide the scientific information following the terms of the mandate received). Such a process would have allowed the detection of “white spots” in the scientific knowledge on DSM in an earlier research stage, and in a more timely demand for additional research (not necessarily by the AMPERE Commission, since its task was to provide a synthesis of the existing knowledge). In defining the research questions, we suggest a broader involvement of stakeholders (perhaps in the framework of the FRDO/CFDD). By this procedure, it would be guaranteed that the range of policy options under consideration would be broad enough to address all relevant needs and concerns. . Decision makers should also ensure that all relevant disciplines are included in the option assessment. In particular, framing the risks of nuclear power generation within a purely economical, technical or regulatory paradigm is too narrow from a societal point of view. The issue of trust in regulatory organisms is at least equally important and requires the input of socio-psychological insights on risk perception. . Also, the selection of a timeframe for the assessment of options seems particularly relevant. Being a decision with long-term consequences, the nuclear phase out should be considered in the context of long-term energy scenarios (e.g. horizon 2050). Whilst inevitably involving a high level of uncertainty, these scenarios open up possibilities for policy beyond those shown by purely econometric modeling and thus have the added advantage of making possible a debate on the normative level (“where do we want to go?”). These scenarios should therefore not be regarded as predictions (and have to be complemented by more precise, short-term foresight), but should investigate widely ranging consequences, reflecting a plurality of societal interests and values. As such, they could provide a platform for a better “aggregation” of societal actors. We recommend setting up the structures needed to elaborate and periodically review these scenarios. They could for example be developed by the Federal Planning Bureau (an advisory organism generally regarded with trust), a second AMPERE activity, or a combination of inputs by both groups (with most likely a larger investment of means and time than in the first AMPERE assessment). Interaction with stakeholders represented in the FRDO/CFDD (or any other advisory board deemed necessary) and policy makers should be foreseen at different time intervals to ensure an iterative and converging process before the results are communicated to decision makers for approval. (3) Goal and strategy formulation/making the decision . Expert involvement. Experts of course have to be competent and experienced. Personal involvement in the issues at stake should not be (and generally are not)

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interpreted as a lack of integrity. Policy makers should however ensure that a sufficient plurality of disciplines and societal interests is represented in the expert group (see recommendation 2). Also, in cases where social polarization prevails (such as the nuclear energy controversy), it might be useful to allow the presentation of substantiated minority points of view next to a generally accepted consensus position. Expert commissions should also make sure that their methodologies are sufficiently understood by stakeholders. Role of government. Policy makers in general should be involved in providing the necessary political and financial basis to build the required consultation structures (see recommendations under points 1 and 2). As regards the decision makers: it is evident that political representatives are the ultimate source of legitimacy. However, it is important that the decision can be justified at all times. The considerations that have led to the decision should be made public and should address the concerns of stakeholders and internationally recognized ethical principles. Particularly, the long-term scenarios mentioned under recommendation 2 could serve to structure such reasoning. Role of stakeholders. Participation should at first focus on the “vested interest groups” in energy policy (e.g. unions, utilities, employers’ organizations, administration, non-governmental organizations) and should start from a careful analysis and understanding of the action perspectives, motives and limits of these actors. Involvement of other groups (including broad citizen participation) should not be excluded a priori, but the advantages and inconveniences should be carefully evaluated.

(4) Monitoring The above-mentioned long-term scenarios would be useful as a point of reference for a continuous monitoring of the policy goals (including, but not restricted to energy security). They could give an indication along which path society is evolving, and consequently, which measures have to be taken. Thus, research is continuously alternated with discussions amongst parties involved. In part, the results of these discussions will influence further decision-making (e.g. “why is policy x not meeting its target?”), but they will also lead to problem definitions for further research (e.g. “why is technology y not meeting the desired level of generation capacity?”). The continuous nature of decision-making on issues impacting on the phase out decision (climate policy, liberalization of energy markets, etc.) makes it necessary for the production of knowledge to be similarly organized in a more continuous way too. 8. Summary of findings and conclusions Technology policy in general, and (nuclear) energy policy in particular, has to face up to new challenges posed by an increasingly “complex” environment. Demands for a reduction of scientific uncertainty and political inequality (be it in cognitive, normative or pragmatic terms) need to be addressed. Contemporary policy sciences have drawn the attention towards the intrinsic connection between the way a policy problem is framed and the suggested solution in terms of a policy strategy. All of these strategies are compatible with the basic idea of the democratic constitutional state, but promote (fundamentally) different conceptions of democratic method or practice to address the issue of uncertainty and inequality. For instance, technical approaches to decision-making have the potential to increase the rationality of the decision with

minimal transaction costs (in terms of time, number of persons involved, networking, etc.), but only under the condition that there is sufficient agreement among the involved actors on the technical character of the problem at hand. Powerful actors can still impose a technical solution in turbulent social environments, but only by actively suppressing other values/interests, by blurring the issues and/or by making strategic use of information (often even bordering on manipulation). Our analysis of the policy development cycle in the case of the Belgian decision to phase out nuclear power is a clear illustration of “recasting problems in a technical mould”. Based on an analysis of stakeholder perspectives, we conclude that energy policy in Belgium could benefit from a much greater degree of social learning. In particular, an institutional structure should be set up, involving broad participation by decision makers, experts and stakeholders, for clarifying: (1) Problem structure. What is exactly the problem with the evolution of the energy system? Do we want “absolute” safety regarding catastrophic risks, proliferation and radioactive waste management (Section 4)? Or do we want to mitigate the consequences of liberalization (Section 5)? Or do we want to evolve towards a more decentralized energy structure, in order to promote “socially rational” energy communities (Section 5)? What about our responsibilities to Third World countries? Considering the value differences between stakeholder groups, different desirable long-term end states for the energy system should be allowed for discussion purposes. (2) Goal setting. Problem structuring should result in a clear and transparent list of acceptable goals for energy policy, with minimal acceptable levels for each of them. (3) Definition of options. Should be the result of a clear communication between policy makers and experts, in order to ensure that no relevant policy option is overlooked. Options should be assessed from the point of view of the long-term desirable end-states, in terms of the risks and the potential advantages a particular option in furthering the goals associated with a particular end-state. Options should also be judged on their impact on society, involving other disciplines than engineering or economic approaches (whilst of course still reserving a major role for economic and technical input). (4) Monitoring. Long-term desirable end states should be translated into intermediate goals. These goals should of course be flexible, and allow for a continuing process of deliberation, evaluation and adjustment (e.g. “why is policy x not meeting its target?”). It is our contention that a profound structural change such as the nuclear phase out would require a sustained leadership defending clear-cut goals and procedures for the production of scientific knowledge and the interaction process with stakeholders with respect to sustainable development. Only under these conditions can a sufficient level of trust be built up between the involved players for a concerted action. If not, the discussion runs the risk of getting bogged down in endlessly repetitious arguing, as appears to be the case for the time being.

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Notes 1. Hisschemo¨ller (1993) builds his classificatory scheme on arguments found in political theory. More specifically, he distinguishes the technical approach (based on certain elite theories), the market approach (based on economically rational conceptions of political participation), the distributive justice approach (based on theories which stress the role of the state in protecting vulnerable interests in society) and the public participation approach (based on egalitarian or anarchist political theories). 2. Policy as negotiation is typically encountered in problems of distribution. In that case, policy goals are broadly accepted (and non-negotiable); the issue is to realize these goals within the limits of acceptable costs for society. A necessary condition for policy as negotiation to work properly is that costs and benefits of policy alternatives have to be reasonably well-known. For example, in the context of climate policy, the problem of distributing greenhouse gas reduction efforts for a given overall national reduction target (for Belgium 2 7.5 percent compared to 1990 levels in the period 2008-2012) over different sectors (industry, transport, households, services) is a typical negotiation problem. 3. A Type I-error occurs when both the problem and method are well-defined, but a mistake is made in applying the method (e.g. an error of measurement). A Type II-error occurs when the problem is stated correctly, but a faulty method is applied in solving the problem. 4. The policy statement was confirmed again by the Prime Minister in his declaration of federal policy to the parliament on 9 October 2001. 5. However, the Royal Decree of 25 November 1999, modifying the Royal Decree of 19 April 1999 (which originally installed the AMPERE Commission) observes that the AMPERE Commission “. . . fulfills an assignment for the common interest regarding energy policy, sustainable development and environmental protection . . . ” (our translation). In its review of Belgian energy policy, the International Energy Agency puts the report of the AMPERE Commission under the heading “Belgium and Sustainable Development” (IEA (2001), Energy policies of IEA countries – Belgium 2001 review, OECD, Paris). It is clear that many of the topics covered in the AMPERE report (social and environmental impact of energy technologies, mid-long term planning, etc.) overlap with the areas of interest in a sustainable model of development. 6. The plan was approved by the Council of Ministers on 20 July 2000 and was consolidated by the Royal Decree of 19 September 2000. The excerpt is taken from section 4.1. (”Policies to promote sustainable energy”), § 396. 7. Available on the website of the Belgian Chamber of Deputies ,http://www.dekamer.be. . 8. In accordance with Article 80 of the Constitution. 9. Possible future applications in the field of desalination of sea water or hydrogen production are not prohibited by the law, adding further to the confusion over the motives of the legislator. 10. The hearing of 24 September 2002 organized by the Commission for Trade and Industry, Science Policy, Education, National Scientific and Cultural Institutions, Trades people and Agriculture (Parl. DOC 50 1910/004, p. 187). 11. A juridical notion meaning that the law can be revoked by unforeseeable and compelling circumstances beyond the will of the party invoking the “force majeure”.

References AMPERE Commission (2000), Rapport van de Commissie voor de Analyse van de Productiemiddelen voor Elektriciteit en de Reorie¨ntatie van de Energievectoren (AMPERE) aan de Staatssecretaris voor Energie en Duurzame Ontwikkeling, available at: http://mineco.fgov.be/ampere.htm Bataille, Ch. and Birraux, C. (2003), Rapport sur la dure´e de vie des centrales nucle´aires et les nouveaux types de re´acteurs, Office Parlementaire d’Evaluation des Choix Scientifiques et Technologiques, Paris. Bourdeau, P., Laponche, B., Morrison, R., Mortensen, J. and Savelli, P. (2001), Assessment of the AMPERE Commission report by an international peer review group, available at: http:// mineco.fgov.be/ampere.htm D’haeseleer, W. (2003), “Future electricity generation in Belgium, the nuclear phase out and its GHG consequences”, Physicalia Magazine, pp. 63-75, Nr. 25. Government policy statement (1999), De brug naar de eenentwintigste eeuw – ontwerp van regeerakkoord, (“The bridge to the twenty-first century – a draft coalition agreement,” our translation), 7 July. Grin, J. (1997), “Interactieve Technology Assessment – Een eerste gids voor wie het wagen wil”, Rathenau Instituut, Den Haag. Hashemian, H. (2002), “Optimized maintenance and management of ageing of critical equipment in nuclear power plants”, in Ruan, D. and Fantoni, P.F. (Eds), Power Plant Surveillance and Diagnostics – Applied Research with Artificial Intelligence, Springer, New York, NY, pp. 41-9. Hisschemo¨ller, M. (1993), “De democratie van problemen – De relatie tussen de inhoud van beleidsproblemen en methoden van politieke besluitvorming”, VU Uitgeverij, Amsterdam. Interdepartementale Commissie Duurzame Ontwikkeling (ICDO) (2000), Federaal plan inzake duurzame ontwikkeling 2000-2004, ICDO, Brussel. ¨ Kluver, L., Nentwich, M., Peissl, W., Torgersen, H., Gloede, F., Hennen, L., van Eijndhoven, J., van Est, R., Joss, S., Bellucci, S. and Bu¨tschi, D. (2000), “EUROPTA (European Participatory Technology Assessment) – Participatory Methods in Technology Assessment and Technology Decision Making”, Danish Board of Technology, Copenhagen. Laes, E. and Meskens, G. (2002), Sustainable Development and Nuclear Energy – Analysis of Interviews with Members of the Belgian Federal Council for Sustainable Development, Contract Report R-3682, SCK-CEN, Mol. Michiels, J. (2003), “De wet van 31 januari 2003 houdende de geleidelijke uitstap uit de kernenergie voor industrie¨le elektriciteitsproductie”, Milieu- en Energierecht, Nr. 2, pp. 86-100. United Nations Conference on Environment and Development (UNCED) (1992), Agenda 21 the Rio Declaration on Environment and Development, the Statement of Forest Principles, the United Nations Framework Convention on Climate Change and the United Nations Convention on Biological Diversity, United Nations Conference on Environment and Development. United Nations Framework Convention on Climate Change (UNFCCC) (1997), Kyoto Protocol to the United Nations Framework Convention on Climate Change, United Nations Framework Convention on Climate Change.

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What may happen? How urgent is the problem? What is at stake for whom?

What can be done to mitigate the problem?

Assessment of risks

Assessment of response

Evaluation

Monitoring

Implementation

Goal and strategy formulation

What is the nature of the problem? What are the causes?

Problem structuring

Are the goals likely to be met?

Is there room for new scientific insights?

What is the link with other policy issues? Which policy instruments are most effective? What are side effects? Are the policies really implemented?

How are uncertainties dealt with?

How to enhance co-operation?

Who is involved?

What should be the goals?

Parliament has voted on the proposal of law. Law can only be revoked by the Council of Ministers when security of energy supply is put at risk. Government depends on utilities (to implement technological alternatives), grid operator (to ensure sufficient exchange capacity) and regional governments (rational use of energy, permits for production units, etc.) for the effective implementation of the phase out. Period considered long enough to develop alternatives or to ensure capacity for electricity import. Relevant policy areas include climate and energy policy. Ban on industrial generation of electricity based on nuclear fission. Limited information on possible side effects. No guarantee; very strong political signal could ensure a de facto implementation of the phase out. Dangers to security of energy supply are the only recognized form of a “force majeure”. Nuclear option is kept open; it is unclear which research lines will be favored in the future. Government spending on national nuclear R&D remains high, but mainly in the areas of nuclear safety and waste management. Monitoring of security of supply by the CREG markets.

Not made explicit; supposedly catastrophic risk, proliferation risks and problems of high-level waste management caused by present-day nuclear power generation (also on a global and intergenerational scale). Catastrophic and irreversible damage to society as a whole; urgency of phase out takes precedence over enhanced risks of anthropogenic climate change. No operational solution for the back end of the nuclear fuel cycle. Forty year lifetime is only defended on the basis that enough provisions will be available to dismantle power plants. Phase out of nuclear power. Continuation of R&D at national and European level. Possible negative impacts on security of energy supply, ability to meet international climate change agreements and the preservation of nuclear know how. No adequate assessment of socio-economic costs of the phase-out decision. Prime goal is to phase out nuclear power.

Policy answer

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What are the costs to society? Are there other benefits?

Typical policy question

Table AI.

Function

JEIM 18,3 Appendix A

(Erik Laes is assistant scientific researcher at SCK-CEN (the Belgian Nuclear Research Centre). Currently, he is working on a PhD thesis (working title: “Sustainability and Nuclear Development”) in collaboration with the University of Leuven (K.U. Leuven). He holds degrees in chemical engineering (K.U. Leuven, 1998), environmental sciences (K.U. Leuven, 1999) and philosophy (K.U.Leuven, 1997). William D’haeseleer is Full Professor in the College of Engineering of the University of Leuven (K.U. Leuven), Belgium. He teaches courses in Nuclear-Reactor Physics, Nuclear Reactor Technology, Radiation Shielding, Applied Thermodynamics & Energy Engineering, Thermal Systems & Energy Management, and Renewable Energy, amongst others. His research activities are situated in the areas of Energy Systems, Energy Management and Energy Policy. He heads the division of Energy Conversion & Applied Mechanics and is the Director of the University of Leuven Energy Institute. William D’haeseleer was an active member of the AMPERE Commission and is presently member of the European Commission’s Advisory Group on Energy (AGE). He is Chairman of the Board of Cogen Vlaanderen. William D haeseleer obtained the degrees of University Graduated Electro-Mechanical Engineering, option Energy, and Nuclear Engineering from the K.U. Leuven in 1980 and 1982, respectively. In December 1983, he graduated as Master of Science in Electrical Engineering from the University of Wisconsin-Madison (UW-M), USA. He obtained his Doctoral Degree (PhD) at that same university UW-M in May 1988. From 1988 till 1993, he resided in Germany, where he was a Scientific Staff Member of the NET Team at the Max-Planck-Institut fu¨r Plasmaphysik in Garching-bei-Mu¨nchen. From 1993 till 1996, he was active in the Belgian engineering consulting company Tractebel Engineering, where he was Manager of the Mechanical Design Section, and departmental Research & Development Manager. As of October 1996, he is a faculty member at the K.U. Leuven. He has been a Fulbright Fellow, and in 1989, he has been Visiting Assistant Professor at the Rennselaer Polytechnic Institute in Troy, New York. (Raoul Weiler teaches at the Universite´ Catholique de Louvain-la-Neuve (UCL), University of Antwerp (UIA), and Catholic University of Leuven (KUL), Belgium. His specialty is the relationship between Technology and Society. He also teaches Agriculture and Applied Biological Sciences at the Centre for Ethics on Agriculture, Life Sciences and Environment (CABME). Weiler is the Vice-President of the European Academy of Sciences and Arts, Vienna (A), President of the Brussels-EU Chapter of the Club of Rome, (B), and an Associated Member of The Club of Rome, (D). He is helping to prepare for the CoR the contribution to the Johannesburg Earth Summit meeting in September. Together with the Factor10 Institute, the CoR Chapter is in the process to set up an agency on sustainable development in Europe. Weiler is also the co-author with Anders Wijkman of the Proceedings of activity The Brussels-EU Chapter organized within the European Parliament. Weiler has been the President of the 4th World Filtration Congress (1986, Ostend, Belgium) and several other congresses on technology; Founder and Past-Chairman of the Working Party on Science, Technology and Society within the Technological Institute of the Royal Flemish Engineers Association (K VIV), (1988-2001), Antwerp, (B). His academic background includes Engineer in Chemistry and Agro-Industries (Bio-Engineer), a Doctor in Agriculture Sciences (1966); Catholic University of Leuven (KUL), Belgium. He also was a Postdoctoral Fellow at the University of North Carolina at Chapel Hill, department of Chemistry; Catholic University of America, Washington DC, department of Physics; Universite´ Paris V Department of Physics, Centre National de Recherche Scientifique (CNRS), (Fr), (1966-1970). His industrial career in Germany and Belgium included the Chemical Industry, Department of Applied Physics and Information Technology, research and development of production processes, manager information technology, (1970-1997). Weiler has several scientific publications, patents, proceedings of symposia and congresses as editor, among them on Water Filtration and the 4th World Congress on Filtration and papers on societal aspects and ethics of technology. Since 1993, four books on the theme of philosophy of technology,

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sustainability and global change and a fifth one under preparation on technology assessment. Several contributions in publications of the European Commission. Also: Which European University for the 21st Century? Proceedings and Recommendations, European Academy for Sciences and Arts, Vienna (A), (2000); Sustainability: A vision for a new Technical Society? In: Technology and Ethics. A European Quest for Responsible Engineering (2001), 511-524. Towards a EU Strategy for Sustainable Development, Proceedings of Hearing.)