E-supply Chain 9781845442774, 9781845441159

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05/04/2005

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ISBN 1-84544-115-X

ISSN 1359-8546

Volume 10 Number 2 2005

Supply Chain Management An International Journal

E-supply chain Guest Editors: Khalid S. Soliman and Brian D. Janz

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Supply Chain Management: An International Journal Volume 10, Number 2, 2005 ISSN 1359-8546

E-supply chain Guest Editors: Khalid S. Soliman and Brian D. Janz

Contents 74

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Guest editorial

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From supply-chain management to value network advocacy: implications for e-supply chains Susan A. Sherer

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An integrated framework for e-supply networks analysis Antonio C. Caputo, Federica Cucchiella, Luciano Fratocchi and Pacifico Marcello Pelagagge

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Strategic decisions in supply-chain intelligence using knowledge management: an analytic-networkprocess framework Mahesh S. Raisinghani and Laura L. Meade

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Successful use of e-procurement in supply chains Thomas Puschmann and Rainer Alt

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Future impacts of RFID on e-supply chains in grocery retailing Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Determinants of business-to-business e-commerce implementation and performance: a structural model Damien Power

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The electronic supply chain (e-supply chain) refers to the utilization of electronic, information-based technologies – specifically the internet – to integrate and coordinate traditionally dispersed buyers and suppliers, and to better manage both upstream and downstream product and servicerelated channels. E-supply chain has increasingly become a focal interest to businesses and supply chain managers since significant improvements in this technology-enabled integration now make the comprehensive management of supply chains a reality. The purpose of this special issue on e-supply chain is to develop a broad understanding of the issues pertaining to the use of these emerging information technologies and their impact on supply chain management. After a vigorous review process, we have selected six papers. The selected articles provide an in-depth understanding of critical issues involved in e-supply chain, and we hope will generate the kind of dialogue necessary to furthering our understanding in this important arena. The special issue begins with a paper that focuses on supply chain management and the notion of value network advocacy. In her paper, “From supply chain management to value network advocacy: implications for e-supply chains”, Sherer highlights the historical roots and the traditional terms used to describe supply chain management to show how their meanings have led to specific types of information systems to support supply chain management. The paper introduces the concept of value network advocacy that can guide e-supply chain development to support a more integrated customer-focused notion of flexible networks that provide value. Caputo, Cucchiella, Fratocchi, and Pelagagge in “An integrated framework for e-supply networks analysis,” provide a framework for analyzing relationships among economic actors in e-supply networks interconnected through the internet. The framework identifies four sets of organizational structures, managerial criteria and critical activities – each one coherent with specific environmental contexts. Two papers discussed organization performance in e-supply chains. In “Determinants of business to business e-commerce implementation and performance: a structural model,” Power stresses that the evidence indicates that the adoption and use of emerging technologies such as the internet is not subject to the same restrictions and impediments traditionally associated with established technologies. Moreover, organizations will find emerging internet-based technologies easier to implement and use, but that this will not necessarily mean that they will improve performance as a result. Performance, however, will be determined by effective strategy formulation, a clear understanding and knowledge of the technologies, appropriate application, and prudent change management. Raisinghani and Meade in their paper “Strategic decisions in supply chain intelligence using knowledge management: an analytic network process framework,” investigate the linkage between organization performance criteria and the dimensions of agility, e-supply chain drivers and knowledge management. The paper addresses the need for strategic decision making tools to assist management in determining which knowledge management construct is most beneficial in the development of an agile supply chain. On the role of information technology and the internet on procurement, Puschmann and Alt in, “Successful use of e-procurement in supply chains,” explores electronic procurement (e-procurement) systems and their contribution to the management of indirect goods supply chains. The study finds that there is a need for an overall

Guest editorial About the Guest Editors Khalid S. Soliman is Assistant Professor of Management Information Systems at Hofstra University. Dr Soliman has worked and consulted in the past 18 years for several national and international corporations. His research and consulting interest include electronic commerce, electronic services, cycle time reduction, interorganizational information systems, and strategic use of information technology to transform organizations and governments. Dr Soliman has published more than 28 articles in refereed journal as well as national and international conference proceedings. His research has appeared in Business Process Management Journal, Communications of the AIS, Information & Management, Information Systems Management, International Journal for Educational Management, Logistics Information Management, and Journal of Management Systems. He also served as a guest editor for special issue of Business Process Management Journal and Supply Chain Management: An International Journal. Brian D. Janz is an Associate Director for the FedEx Center for Supply Chain Management in the FedEx Institute of Technology and Associate Professor of MIS at the Fogelman College of Business and Economics at The University of Memphis. In addition, he is the co-founder of the University’s Center for Managing Emerging Technology. Dr Janz’s research interests focus on how information technologies affect organizational strategy, design, and knowledge worker behavior. Specifically, he is interested in the effects that knowledge management and information technologies have on organizational supply chain management and process cycle times, systems development, and overall business intelligence. His most recent research is focusing on RFID technologies in the healthcare industry. His research has been published in book chapters as well as many academic and practitioner journals including MIS Quarterly, Decision Science, Journal of MIS, Personnel Psychology, Journal of Database Management, Journal of Information Technology Management, Information and Management, Journal of Global IT Management, Cycle Time Research, Journal of Strategic Performance Measurement, and the Journal of Education for MIS. In addition, Dr Janz serves on the editorial review boards of numerous journals. Dr Janz has over 20 years of experience in the information systems field working for The University of Minnesota, IBM, Honeywell, and General Motors, as well as consulting with several Fortune 500 companies and governmental agencies. He is sought out by these organizations to conduct consulting projects, educational and leadership programs, as well as to deliver keynote speeches. In the past year, he was named a Research Fellow to the FedEx Institute of Technology, and was nominated for a Palmer Professorship for Service in the Fogelman College and nominated for the University of Memphis’s Distinguished Teaching Award. Currently, he serves on the IT Steering Committee for the City of Memphis, is a member of the Executive Board of the Memphis-Area Technology Council, and is an external advisor to Denver Health, Colorado’s largest safety-net hospital, as they embark on a total hospital reengineering effort. Dr Janz received his Bachelor’s degree in electrical engineering from The University of Minnesota and an MBA in strategic management and a PhD in MIS from the Carlson School of Management at the University of Minnesota.

Supply Chain Management: An International Journal 10/2 [2005] 75 –76 q Emerald Group Publishing Limited [ISSN 1359-8546]

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future applied research on RFID implementation. Research areas include research using modeling techniques, RFID implementation and the impact of RFID on daily operational issues. With the RFID arena being closely watched by all industries, we believe the authors have made a worthy contribution in helping advance the needed academic conversation related to this promising supply chain technology. Khalid S. Soliman and Brian D. Janz

procurement strategy, an alignment of various e-procurement solutions along the procurement process, and the need for integrated system architectures. Finally Prater, Frazier, and Reyes examine market drivers that are leading to radio frequency identification (RFID) implementation along supply chains in the grocery industry. In their paper, “Future impacts of RFID on e-supply chains in grocery retailing,” they provide a theoretical framework for

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From supply-chain management to value network advocacy: implications for e-supply chains Susan A. Sherer College of Business and Economics, Lehigh University, Bethlehem, Pennsylvania, USA Abstract Purpose – To introduce a broader concept for supply-chain management (SCM), the notion of value network advocacy. Design/methodology/approach – The historical roots and the traditional terms used to describe SCM are explored to show how their meanings have led to specific types of information systems to support SCM. The limitations of these systems are demonstrated with case studies. Then the concept of value network advocacy is introduced to address these limitations, and implications of this term are explored. Findings – The term SCM has its historical roots in the control of fulfillment activities that support the linear physical flow of goods from suppliers to manufacturers to distributors to retailers. Consequently many information systems (IS) applications that support the supply chain have a similar focus. These systems often separate supply from demand management and focus on linear information flows. Often they are implemented without reengineering business processes. A broader concept, value network advocacy, better describes the needs of business today. It is suggested that adoption of this concept in organizations will be limited not by technology, but by lack of trust mechanisms and metrics. Practical implications – The adoption of the broader concept of value network advocacy will enable companies to focus more on developing adaptive networks that support customer needs. Originality/value – The paper introduces the concept of value network advocacy which can guide e-supply chain development to support a more integrated customer-focused notion of flexible networks that provide value. Keywords Supply chain management, Value analysis, Customer relations Paper type Viewpoint

still have low involvement of both customers and suppliers in supply chain processes (Sahay, 2003). The term SCM has its roots in efforts to improve logistics and materials management. The historical roots of the term may have limited companies’ abilities to fully recognize advantages that could be obtained by streamlining and improving the entire process of meeting customer needs. We need to move beyond simply managing supply through a chain of suppliers, manufacturers, distributors, and retailers. The focus on managing fulfillment in a linear fashion has led to the development of information systems supply chain applications that have primarily supported sequential information flow (e.g. EDI, VMI), and have managed demand information in CRM applications separate from supply chain applications. Moreover, the implementation of these applications has often occurred without process change, assuming that the software will directly support existing physical processes. Often companies think information technology alone will solve their supply chain problems (InformationWeek, 2003). Today we need to focus on advocating value for customers in networks of firms that must respond to individualized and changing needs. The technology is evolving to accomplish this task. However, its implementation will be stalled if trust mechanisms and metrics are not developed to support this new focus on value network advocacy. We begin with a discussion of the history of SCM, followed by its implications for the language of SCM. This is followed by a discussion of the consequences of this language and focus. We then suggest a new broader term for SCM, value

Introduction Companies today increasingly recognize that improved management of supply chains can be a source of competitive advantage. As a result, many have reorganized purchasing and logistics functions into supply-chain management (SCM) organizations. They have invested heavily in software to manage the information flows in the supply chain. From 1999 to 2002, vendors sold more than $15 billion in SCM software licenses. And this does not include the cost of installation and maintenance contracts (Kanakamedala et al., 2003). Yet it has been suggested that supply chains are not necessarily any better today than they were when the concept of SCM evolved 20 years ago. Of respondents to a Booz Allen Hamilton SCM survey, 45 percent reported that their solution failed to meet expectations (InformationWeek, 2003). A Forrester Research survey found that more than half of the companies interviewed had SCM systems that failed to meet their expectations (Mazur, 2003). Another recent survey reported that a majority of Indian companies The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm

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From supply-chain management to value network advocacy

Supply Chain Management: An International Journal

Susan A. Sherer

Volume 10 · Number 2 · 2005 · 77 –83

network advocacy, and describe some of the requirements for its adoption.

meaning of the complete term. In either case we find that the term’s historical meaning is not as relevant to the needs of business today. The term “supply” as used in “supply chain management” is an adjective that describes a type of management; altered from its original use as a noun or a verb. As a verb, it means “to provide for or satisfy needs and wishes” and as a noun, supply means “the act of filling a want or need” (MerriamWebster, 1973). These definitions presume that there is someone who determines needs and wishes. This is the ultimate consumer in an extended supply chain; however it is often interpreted as the immediate customer. This definition assumes that “supply” reacts to needs that are known and determinant. We suggest that usage of the term “supply” often separates fulfillment from need. As the term has evolved, supply chain managers have focused primarily on fulfillment. The determination of need is often the separate discipline of marketing. Today customers’ needs change frequently and the adaptability of supply chains becomes a critical problem. There is a great need to connect the “supply chain” discipline with the “marketing” discipline. Yet the name is constrained to a focus on fulfillment. In academic fields, while some institutions have combined marketing and supply chain groups, these are often considered to be separate functions. In business organizations, marketing and supply chain often report to separate directors. The term “chain” refers to “a series of usually metal links or rings connected to or fitted into one another and used for various purposes, a series of links used or worn as an ornament, a series of things linked, connected, or associated together” (Merriam-Webster, 1973). A chain typically implies linear, sequential relationships from one link to the next. There are two problems with this term. First, not all goods flow sequentially. Some supply chains involve concurrent material flow. For example, Dell’s monitors ship concurrently with its computers. Second, the information flow, which is often what is managed for competitive advantage in a supply chain, does not always flow sequentially. In fact, information that is shared with many nodes at once can result in faster, more accurate, and nimble supply chains. When the term was coined, sequential information processing existed due to information systems limitations. But these limitations no longer exist. The name implies focus on a model that is not adaptable to real time change. The third term “management” is defined as “the act or act of managing control, direction; judicious use of a means to accomplish an ends” (Merriam-Webster, 1973). Management refers to the process of getting activities completed efficiently and effectively with and through people. It includes the functions of planning, organizing, leading, and controlling (Robbins and Colter, 1996). Thus, SCM refers to the process of completing fulfillment functions efficiently and effectively. Together the synergistic term defines a new field of endeavor. The term “supply chain management” was coined by Keith Oliver, a Booz Allen Hamilton executive in 1982 (InformationWeek, 2003). The original meaning of the term was the “management of a chain of supply as though it were a single entity, not a group of disparate functions”, and was coined to address the suboptimal deployment of inventory and capacity caused by inherent conflicts among functional groups within a company (Laseter and Oliver, 2003). Supply chain is a term “now commonly used internationally –

History of SCM Prior to the 1980s, most organizations worked fairly independent of their suppliers. Purchasing managers rarely viewed suppliers as value-added partners. Often neglected, purchasing was not perceived as important to mainstream business problems. The birth of SCM as an initiative that integrated external partners was found in the textile industry’s quick response program and the grocery industry’s efficient consumer response initiatives (Lummus and Vokurka, 1999). In 1992 the efficient consumer response working group developed a set of best practices that led to continuous replenishment inventory. Point of purchase transactions were sent to the manufacturer so that they could keep the retailer replenished and balanced. Probably the most publicized efforts in SCM were those of Wal-Mart. Because of its sheer size, the number of suppliers, and the demonstrated improvements, many companies were pushed into supply chain integration with Wal-Mart. In 1983, with bar codes printed on most goods, Wal-Mart introduced checkout scanners in all its stores. They updated inventory numbers for individual items at the point of sale and enabled headquarters to more easily aggregate sales and inventory data at its centralized IT department. In 1987 Wal-Mart completed a two-year satellite communications network installation that sent data from all stores to headquarters, providing real-time inventory data. And in 1990, the retailer implemented a collaborative planning, forecasting and replenishment process that brought suppliers and distributors together to build a combined planning calendar (Johnson, 2002). By the mid to late 1990s, the importance of SCM was widely recognized. The Supply-Chain Council (SCC), organized in 1996 by Pittiglio Rabin Todd & McGrath (PRTM) and AMR Research, with 69 voluntary member companies (www.supplychain.org), now includes 1,000 corporate members world-wide in a broad cross-section of industries, including manufacturers, services, distributors, and retailers. By the late 1990s academic institutions also began to recognize the significance of SCM. In 1997 Michigan Sate University consolidated their Marketing and Logistics Administration Department with many of their operations and purchasing professors into a new department called Marketing and Supply Chain Management. In 1998 Arizona State University established a Supply Chain Management Department by merging purchasing, operations and logistics faculty, along with some others (Larson and Rogers, 1998). Journals focusing on SCM were introduced in 1997 including Supply Chain Management: An International Journal and the Supply Chain Management Review while journals in other disciplines, such as Interfaces and the Journal of Marketing Theory and Practice put out special issue calls for papers.

Language of SCM The history of SCM can be understood by analyzing the language of the field. We can look at the meaning of the term “supply chain management” by analyzing the definitions of its individual component terms or by looking at the synergistic 78

From supply-chain management to value network advocacy

Supply Chain Management: An International Journal

Susan A. Sherer

Volume 10 · Number 2 · 2005 · 77 –83

encompasses every effort involved in producing and delivering a final product or service, from the supplier’s supplier to the customer’s customer” (SCC, 2005). APICS defines supply chain as: the processes from the initial raw materials to the ultimate consumption of the finished product linking across supplier-user companies; and the functions within and outside a company that enable the value chain to make products and provide services to the customer (Cox et al., 1995). The nature and the direction of the linkages is unclear in this definition. Most of the applications that have traditionally been developed have supported a linear linkage of firms. Since the late 1990s leading companies have placed greater emphasis on cost reduction and innovation at the supplier end of the chain rather than the customer end (Laseter and Oliver, 2003). Thus, the synergistic term, just like the separate component terms, has not conveyed an emphasis on a web of connections between partners and customers, particularly for information sharing, nor has it focused on customer needs. Another set of common terms in the supply chain language are upstream and downstream partners in the supply chain. These terms reflect the continuous nature of the physical supply process, using a flow, rather than link analogy. Streams run from a source to a sink; upstream refers to the source of the stream while downstream is in the direction of the flow of the stream. The use of the term stream derives from the linear perception of the supply chain, from one link to another as a stream flows from one direction to another. Upstream partners refer to suppliers; downstream partners to customers. Adopters of the supply chain language focus on the flow from source (suppliers) to sink (customers). The focus is on the physical flow of goods. However, the flow that provides competitive advantage is often the information flow, not the physical flow. Information flows from the customer first, the customer is the source. If value is to be added, then the customer must want or desire the goods or materials. Thus, the customer should truly be the information source. Tompkins and Jernigan (1997) reflect the focus on flow from the customers in suggesting that the misnomer SCM be replaced by the term demand flow management. Should customers not be the upstream partners? The terms SCM, upstream suppliers, and downstream customers reflect the concept of a passive customer who receives the flow of goods and services. In an environment of stable customer demands, these terms might be appropriate. When Ford produced all black model-Ts, the focus on where to find the best suppliers was the best focus. But today the focus first needs to be on the demand drivers. Information flows from the customer backwards. Thus, the idea that the supplier is the source (upstream) may lead to poor behaviors. Meanwhile, while the usage of the term SCM was in its infancy in 1985, Michael Porter introduced another term – the value chain. The value chain as popularized by Porter focused internal to an organization on the series of interdependent activities that bring a product or service to the customer. While this notion is driven more by what it takes to satisfy the customer than the notion of a supply chain, which was popularized to improve fulfillment, the concept was applied internal to a company, as it was assumed that competitive advantage came from improvements in internal operations. It was not until the mid-1990s that the notion of an extended value chain was first introduced. The notion was enhanced by technology that enabled inter-organizational

communication and collaboration. By this time, the usage of the term SCM had been established, with its emphasis on the physical supply chain. As demonstrated by the early examples cited above, SCM initiatives focused primarily upon managing linear fulfillment functions. Some authors combined the two concepts, referring to SCM as “the systematic effort to provide integrated management to the supply value chain in order to meet customer needs and expectations, from suppliers of raw materials through manufacturing and on to end-customers” (Stein and Voehl, 1998, p. 263). Other authors considered two separate terms: supply chain and demand management. Others used the term interchangeably. We argue that emphasis on value may result in more appropriate behaviors for managing today’s supply chains.

History of information systems support for supply chains In order to complete SCM functions efficiently, numerous information systems have been developed to support SCM activities, both planning and execution. Various Information systems applications that were developed to support the supply chain are summarized in Figure 1. Each supports different aspects of planning or executing activities related to fulfillment. The earliest information systems, predating a “language” for SCM primarily supported individual functions such as purchasing departments. Often these systems were custom developed to meet the needs of the individual organizations. Since there was not much inter-organizational coordination between departments in a company or with suppliers/ customers, the systems could be developed to match internal departmental processing requirements. Interorganizational coordination was accomplished by some early adopters with the use of EDI systems. These systems were examples of “standardization”, which involves the establishment of routines or rules that constrain actions of each unit into paths consistent with others in the relationship (Thompson, 1967). EDI standards had to be agreed upon, adopted, and adhered to in order to coordinate the actions of the individual parties. Figure 1 IT investments in the supply chain

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From supply-chain management to value network advocacy

Supply Chain Management: An International Journal

Susan A. Sherer

Volume 10 · Number 2 · 2005 · 77 –83

As coordination with supply chain partners became more significant in the 1980s and the term “supply chain management” was coined, the systems evolved to reflect the capabilities of the technology as well as the language of SCM. The language emphasized a focus on effective fulfillment and linear chains. Many of the systems that evolved focused on managing execution of fulfillment rather than demand reaction, e.g. warehouse and transportation management execution systems. Customer focused systems were developed separately from fulfillment systems. Systems that supported planning, such as advanced planning and optimization, supported “coordination by plan”, which involved established schedules for interdependent units by which actions could be governed (Thompson, 1967). Systems such as vendor managed inventory or advanced planning and optimization were best suited for linear relationships between two partners who could plan together, or one partner whose plan was used to drive the actions of a second partner in the chain, as was the case with Wal-Mart. Customer needs were primarily addressed by a separate class of information systems applications, customer relationship management applications (CRM). Only recently have companies turned to the integration of customer relationship management systems with SCM systems in order to incorporate customer input. However, the term customer relationship management itself is a misnomer. CRM infers that customers can be managed. Customers can be served, listened to and valued, but they can’t always be controlled. While relationships with customers can be managed somewhat, customer needs may not always be controllable. What may be controllable is the adaptability of the network to adjust to changing needs. In a recent survey of 196 executives, enterprise resource planning systems topped the list of supply chain system investments at 71 percent, followed by inventory and warehouse management (54 percent), order management (40 percent), supply chain execution systems (37 percent), advanced planning systems (31 percent), and marketplaces and exchanges (26 percent) (InformationWeek, 2003). Most of these applications reflect a focus on fulfillment, involving coordination by plan, which works best when coordinating a linear chain of relationships between partners. Today applications such as electronic hubs can enable “coordination by mutual adjustment”, which transmits new information during the process of action (Thompson, 1967). This type of coordination is more applicable to situations which are more variable and unpredictable. These can reflect the networked nature of supply chains, rather than the linear nature. Yet these electronic hubs have not been strongly adopted. We suggest reasons for the slow adoption below.

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implementation of IS applications without process change; assuming software supports the physical supply chain in place.

We provide some examples here. Sequential vs network information flow Supply chain applications were developed in two areas: supply chain planning and execution (Kalakota and Robinson, 2001). The applications were developed based upon the concept that information flow, like physical flow, is sequential, as shown in Figure 2. As organizations implemented EDI and VMI, information was shared in a linear fashion between organizations. However, this linear sharing of information can lead to mis-information and longer lead times. An excellent example of the problems that can result from sequential flow of information was the 2001 Cisco write off of $2.2 billion for components it ordered but did not use (Kaila, 2002). To lock in supplies of scarce components, Cisco ordered large quantities well in advance, based upon demand projections from the company’s sales force. However, many of their forecasts were artificially inflated because many Cisco customers also ordered similar equipment from Cisco’s competitors, knowing that they would ultimately just purchase from whoever could deliver first. Bloated demand forecasts led to double and triple orders. Furthermore, each of Cisco’s contract manufacturers such as Celestica, Flextronics, and Solectron competed to fill the same order and to gain an edge, they often tried to lock up supplies of scare components. Cisco’s supply chain system did not show that the spike in demand for these components represented overlapping orders. Because communication was taking place sequentially from one tier to another, Cisco lacked visibility to demand information at the component level. To alleviate this problem, Cisco installed an eHub, which enables network rather than sequential communication. By providing visibility to the entire customer and supplier network, Cisco can react quicker to change. Demand vs supply systems The SCM systems presume demand is given. While many supply chain planning systems currently incorporate more sophisticated demand planning modules, they are generally not linked directly to customer responsive applications. The information systems application that has been developed to gauge customer demand is the customer relationship management system. CRM applications attempt to understand customer behaviors. However, often these systems are not directly linked to the supply chain. Moreover, SCM systems are focused on reducing costs Figure 2 Physical and information flow in the supply chain

Consequences of the narrow focus on SCM Several of the initiatives associated with the development and implementation of SCM information systems applications have been limiting. While we do not suggest that language alone led to these issues, we advocate that a broader notion of the concept may have led to development of different types of applications. Key issues are as follows: . information systems (IS) applications that support sequential rather than network flow of information; . separate IS applications for customer demand analysis and supply analysis; and 80

From supply-chain management to value network advocacy

Supply Chain Management: An International Journal

Susan A. Sherer

Volume 10 · Number 2 · 2005 · 77 –83

whereas customer relationship management systems are focused on enhancing revenue. The missing link between supply and demand systems can lead to excess inventory, additional costs, and/or unsatisfied customers. For example, in the mid-1990s, Volvo had an excessive inventory of green cars mid year. Sales and marketing managers aggressively began offering special deals, discounts, and rebates to their distributors in order to reduce this inventory. When green cars began to sell, the supply chain planning managers thought that customers finally liked these cars, not recognizing that they were responding to the promotions, so they began to produce even more. By the end of the year Volvo was left with a huge inventory of green cars (Lee, 2001). Other disconnects between supply and demand management occur because trade promotions, personalized needs and configurations are not tied directly into supply chain planning and execution systems. The latter simply assume demand is given and work to meet these needs.

responding to changes as they occur. Managers focus on control and providing direction. Managers cannot control the changes, only the responses to the changes. Information systems applications should support capabilities to react to customer changes, rather than controlling fulfillment to meet planned customer needs.

Implications of value network advocacy In some cases, the broader term we suggest has been paralleled by changes in the way SCM is now perceived in many companies. Many changes have resulted from the recent technology, for example the internet allows networked flow of information compared to the linear flow of EDI. Other changes have resulted as organizations recognized the need for change and re-organized their marketing and supply groups to work together. Cross industry initiatives such as RosettaNet are helping to promote open standards and sharing, reducing the lack of standardization that had plagued interorganizational information sharing in the past. Information systems have evolved to link supply and demand in a networked fashion, enabling companies to link customer demand directly to their networked supply chains. Systems such as Cisco’s e-hub private exchange enable contract manufacturers and suppliers to see demands in real time and react accordingly. Industry consortia marketplaces such as Covisint link suppliers to demand changes, if information is adequately provided. Information technology will soon no longer be an impediment to the flow of networked information through hubs that link supply and demand information. However, moving from managing supply to advocating customer value requires a new level of trust and the development of new metrics:

Software implementation without process change A common problem with many software implementations is the installation of software without reengineering the company business processes. Since the concept of SCM has been focused on fulfillment, often separate from the responsibility of marketing, opportunities for process redesign have been overlooked. For example, a computer networking company implemented SCM forecasting software while ignoring their real problem which was a sales incentive program that encouraged overproduction. While the software accurately recognized overproduction, the system was not heeded because when sales were high, a customer could always be found for the excess quantities – and profits were high. So while the software indicated that demand was falling, management and sales failed to heed the alert. Raw materials began to increase and a large write off ensued (Kanakamedala et al., 2003).

Most companies deploying supply chain technology are only getting a small fraction of the benefits which are promised . . . What’s holding back the promising results is something very simple but very difficult to secure . . . Trust. It is NOT that people don’t trust the systems. It is not that people don’t trust the technology. They trust it. In fact, they KNOW it will work – and that’s what people are afraid of . . . What people don’t trust is each other. Particularly, customers and vendors – because when your supply chain is integrated, and when your customers know your resources, and your resources’ resources, that information gives customers tremendous power and control (Duris, 2002).

A broader concept: value network advocacy The focus of information systems to support efforts in the customer fulfillment process should be on value, not supply. Organizations need to focus efforts on what adds value to the customer. While supply chain applications focus on supplying customer demand, they are not necessarily focused on what this demand is and how it changes over time. What is it that customers truly want? How do their needs change over time? This is what is needed and this should be the focus of applications and initiatives. Today we should be focusing on networks, not linear chains or flows. This applies to the physical process and even more so, the movement and sharing of information. Information has become the key driver of advantage. Information hubs should be the basis of communication Information technology today can support this move. We need organizations that center around customer advocacy, employing people who are advocates for adding value for the customer and information systems to support these advocates. These advocates must be responsive to change. While management assumes control, advocates act in favor of others, in this case the customer and the participating companies. Thus, advocates work in favor of others,

Of senior IT managers, 75 percent cite lack of trust as the number-one barrier to electronic collaboration (Paul, 2003). Boeing is facing this problem with its implementation of a product data management system. While technology no longer limits the ability of partners to concurrently work on designs, trust is an issue “because the [supplier] could build the same part for your competitor,” says Griffin, VP and CIO. “Once you say, build me the world’s best overhead arch beam, they could turn around and sell that to Airbus.” No one has come up with a satisfactory solution to that conundrum yet, despite vendor claims to the contrary, says Griffin, adding, “We need to work some stuff out” (Paul, 2003). Online marketplace use has been hampered by lack of trust. Originally billed as a tool for streamlining the automotive supply chain, Covisint’s image has changed and is being shunned by some suppliers, because they are the tool for reverse auctions and market testing against the incumbent supplier. Some suppliers have refused to participate in Covisint while others say they are just more careful when they suspect a bidding event is merely a market test because 81

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Volume 10 · Number 2 · 2005 · 77 –83

Conclusions

they know it is a product currently being made by another supplier. Suppliers felt that 80 percent of reverse auctions were market tests (Hannon, 2003). We need ways to incorporate trust into network systems so that they will be used. This requires first that specific codes of standards be established. The Original Equipment Suppliers Organization (OESA) created a code of conduct for OEMs and tier one automobile suppliers to use in conducting reverse auctions but so far it has not received much backing from automotive OEMs (Hannon, 2003). Once codes of conduct are established, information systems can keep information on credibility of participants that can lead to trust. Trust is a multi-dimensional construct, involving both cognition, individual beliefs about peer reliability, competence, honesty, and reputation; and affect, grounded in reciprocated interpersonal care and concern (McAllister, 1995). Information systems can provide support for cognition based trust by providing information about the past performance of participants. This is the approach taken by online marketplaces such as E-bay. Online feedback mechanisms have evolved as a technology for building trust (Dellarocas, 2003). Affect based trust will only occur over time as companies interact with each other. Trust, not technology, will be a major factor in moving companies to adopt information systems applications that support value network advocacy. We also need new metrics today for the ability to provide customer value. These metrics need to account for value in the entire network and then apportion this value to individual participants in a way that is acceptable to all. Most companies have internal performance metrics, e.g. profitability, revenue, inventory turns, order-to-cash cycle time. Sometimes supply chain partners may use different metrics. “You may promise your customers a better order fill rate, but can you be sure your suppliers can get the needed materials to you to complete the order? And what your suppliers actually send you may be far removed from what you promised to send to your customers? You and your suppliers may be using different measures altogether” (Keebler et al., 1999). New metrics that focus on objectives of all business partners are required. We also need a way to apportion the value of achieving the overall goals to the individual participants in the network. But even if partners could use the same metrics, most of the metrics today focus on either efficiency (cost and time), or output (quality, delivery performance, or synchronization). Value network advocacy requires new metrics of customer agility, the co-opting of customers in the exploration and exploitation of opportunities for innovation and competitive action (Sambamurthy et al., 2003) in the value network. All parts of the value network need to be linked to adaptability to customer value and individual portions of the value network must be measured in terms of their contribution to customer agility. What is needed to drive advocacy in a value network are metrics for consumer driven value that translate into measures of individual company performance. Customers may be interested in low cost, high quality, and/or responsiveness of service. Actions should be not just around fulfilling demand, but responding to changing customer value. We need to recognize and measure what this is and how this translates to value for each of the participants in the network.

We have argued that the history of SCM has been matched by the development of information technology applications that support the language that has been used to describe the field. Additionally, we have suggested that a broader notion of the language, moving from emphasis on SCM to value network advocacy more accurately reflects the future needs of companies. However, we suggest that information technology applications that match this notion will not be widely adopted because of deficiencies in trust mechanisms and metrics. We have suggested that information systems that support the supply chain have matched the evolution of the concept of SCM. The emphasis of the language of SCM has been on effective fulfillment through linear relationships in the supply chain. The information technology applications that have evolved have supported coordination in fulfillment, in a sequential fashion that reflects this linear emphasis. We suggest that this has limited their usefulness because they did not fully reflected the network nature of coordination and have not integrated customer needs and changes effectively. Today however the technologies exist to support a broader concept: the value network advocacy. Will this notion take hold? The technologies are available, yet we see slow progress in their adoption. We suggest that there are two reasons for this: lack of trust; and inter-organizational customer agility focused metrics. We advocate not only the adoption of a new language for SCM, but also research in these areas. Only then will we see movement to a new concept that more accurately reflects the requirements of organizations today.

References Cox, J.F., Blackstone, J.H. and Spencer, M.S. (Eds) (1995), APICS Dictionary, 8th ed., American Production and Inventory Control Society, Falls Church, VA. Dellarocas, C. (2003), “The digitization of word of mouth: promise and challenges of online feedback mechanisms”, Management Science, Vol. 40 No. 10, pp. 1407-24. Duris, R. (2002), “A matter of trust”, Frontline Solutions, Vol. 3 No. 13, p. 50. Hannon, D. (2003), “The automotive buy – suppliers: friend or foe?”, Purchasing, Vol. 132 No. 2, pp. 25-9. InformationWeek (2003), “Supply chain management still a work in progress”, InformationWeek, May 23. Johnson, A.H. (2002), “35 years of IT leadership: a new supply chain forged”, Computerworld, Vol. 36 No. 40, pp. 38-9. Kaila, P. (2002), “Inside Cisco’s $2 billion blunder”, Business, Vol. 3 No. 3, p. 88. Kalakota, R. and Robinson, M. (2001), e-Business 2.0, Addison-Wesley, Reading, MA. Kanakamedala, K., Ramsdell, G. and Srivatsan, V. (2003), “Getting supply chain software right”, McKinsey Quarterly, No. 1. Keebler, J., Manrodt, K., Durtsche, D. and Ledyard, D.M. (1999), Keeping Score: Measuring the Business Value of Logistics in the Supply Chain, Council of Logistics Management, Oak Brook, IL. Larson, P.D. and Rogers, D.S. (1998), “Supply chain management: definition, growth and approaches”, Journal of Marketing Theory and Practice, Vol. 6 No. 4, pp. 1-5. 82

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Laseter, T. and Oliver, K. (2003), “When will supply chain management grow up?”, Strategy þ Business, No. 32, pp. 20-5. Lee, H.L. (2001), “Ultimate enterprise value creation using demand-based management”, paper presented at Stanford Global Supply Chain Management Forum, Stanford, CA. Lummus, R.R. and Vokurka, R.J. (1999), “Defining supply chain management: a historical perspective and practical guidelines”, Industrial Management & Data Systems, Vol. 99 No. 1, pp. 11-17. McAllister, D. (1995), “Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations”, Academy of Management Journal, Vol. 38 No. 1, pp. 24-59. Mazur, L. (2003), “Marketing loses clout if a supply chain is flawed”, Marketing, Vol. 16, p. 16. Merriam-Webster (1973), Webster’s New Collegiate Dictionary, G. and C. Merriam Company, Springfield, MA. Paul, L.G. (2003), “Suspicious minds: collaboration among trading partners can unlock great value. Mistrust is a

barrier. Here are six ways to build confidence”, CIO, Vol. 16 No. 7, pp. 74-82. Robbins, S. and Colter, M. (1996), Management, PrenticeHall, New York, NY. Sahay, B.S. (2003), “Supply chain collaboration: the key to value creation”, Work Study, Vol. 52 No. 2, pp. 76-83. Sambamurthy, V., Bharadwaj, A. and Grover, V. (2003), “Shaping agility through digital options: reconceptualizing the role of information technology in contemporary firms”, MIS Quarterly, Vol. 27 No. 2, pp. 237-63. Stein, M. and Voehl, F. (1998), Macrologistics Management, St Lucie Press, Boca Raton, FL. Supply-Chain Council (2005), available at: www. supply-chain.org Thompson, J.D. (1967), Organizations in Action: Social Science Bases of Administrative Theory, McGraw-Hill, New York, NY. Tompkins, J. and Jernigan, B. (1997), Goose Chase: Capturing the Energy of Change in Logistics, Tompkins Associates, Raleigh, NC.

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An integrated framework for e-supply networks analysis Antonio C. Caputo, Federica Cucchiella, Luciano Fratocchi and Pacifico Marcello Pelagagge Faculty of Engineering, University of L’Aquila, L’Aquila, Italy Abstract Purpose – The purpose of the present paper is to provide a comprehensive framework for analyzing relationships among economic actors interconnected through internet and constituting e-supply networks (e-SNs). Design/methodology/approach – At first the main factors characterizing e-SN pattern are identified (organizational structures, managerial criteria and critical activities), then two separate procedures are adopted for developing an integrated reference framework. The first based on the analysis of correlations among variables influencing the factors under investigation; the second based on the analysis of different types of physical and immaterial flows among actors involved in the e-SN. On the basis of such evidence an integrated global framework is proposed, which is then used to classify and describe some relevant literature-based case studies. Findings – On the basis of two newly introduced variables, namely the internal integration degree and the decision-making concentration degree, the framework identifies four sets of organizational structures, managerial criteria and critical activities, each one coherent with specific environmental contexts. Research limitations/implications – The framework is restricted to describing and classifying different typologies of e-SN. Practical implications – The framework may be useful for assessing if the typology of organizational structure, managerial criteria and critical activities adopted for the management of a specific e-SN, is coherent with e-SN business environment. It may also provide useful guidelines for managers and practitioners involved in e-SN design. Originality/value – The paper provides an original integrated framework to classify e-SNs. Keywords Supply chain management, Organizational structures, Competences Paper type Research paper

the patterns of existing e-SNs and verify the coherence between the influencing factors. The paper is organized as follows. In the first paragraph factors that mainly characterize e-SNs are briefly resumed and interdependencies among them are identified and analysed to highlight existing relationships. On the basis of such evidences, in the second paragraph, an integrated global framework is proposed. The framework identifies four sets of organizational structures, managerial criteria and critical activities, each one coherent with specific environmental contexts. In the last part of the paper, the framework is thus applied to describe, analyse and classify some literature-based case studies. Concluding remarks and implications for further research are finally presented.

Introduction The importance of supply chain management for the competitiveness of industrial and services enterprises has been demonstrated by several authors (i.e. Lambert et al., 1996; Cooper et al., 1997; Beamon, 1998; Nøkkentved, 2000; Tapscott et al., 2000; Baldi and Borgman, 2001; Zheng et al., 2001). Such a criticality is even more relevant in the case of enterprises adopting e-business strategies, that is, are involved in e-supply networks (e-SNs). Within those networks, partners resort to internet technologies and/or electronic data interchange (EDI) to buy, sell, distribute products or services and cash flows (William et al., 2002). Despite the huge number of works on this subject (i.e. Cravens et al., 1996; Lamming et al., 2000; Cox et al., 2001; Harland et al., 2001; Zheng et al., 2001), an integrated approach for analysing relationships among actors interconnected through internet is not yet available. In order to contribute towards the solution of such problem, based on the preliminary analysis conducted by Cucchiella et al. (2002), a comprehensive framework is proposed to classify

Description of factors characterizing e-SNs and their relative consistency Factors affecting e-SNs In a previous work (Cucchiella et al., 2002), the following three main criteria were identified as characterizing e-SNs: 1 structures adopted to organize the relationships among the actors of the network (Tapscott et al., 2000); 2 criteria adopted to manage such relationships (Nøkkentved 2000); and 3 activities to be developed for coordinating the relationships (Zheng et al. 2001).

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With respect to the first element, different literature contributions focus the attention on the organizational structures adopted to coordinate relationships among actors of supply networks (SNs) or e-SNs (i.e. Cravens et al., 1996;

Supply Chain Management: An International Journal 10/2 (2005) 84– 95 q Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/13598540510589160]

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Volume 10 · Number 2 · 2005 · 84 –95

Ernst and Kamrad, 2000). Among them, Tapscott et al. (2000) propose the concept of b-web, that is a distinct system of suppliers, distributors, commerce services providers, infrastructure providers, and customers that use the internet for the primary business communications and transactions. Authors under investigation define five types of b-webs based on the level of product/service value integration (VI) and control type (CT) – which may be hierarchical or selforganizing – adopted to manage relationships among embedded actors: 1 agora; 2 aggregation; 3 value chain; 4 alliance; and 5 distributive network.

the flow of goods and services from original sources to end customers”. Such a definition is an evolution of the concept of b-web adopted by Tapscott et al. (2000), given the inclusion of lateral links, reverse loops and two-way exchanges. Zheng et al. (2001) identify four e-SNs based on two variables: leading firm degree of influence (LFI) and supply network dynamism (ND) (Figure 3). Analysis on factors consistency As earlier shown, and more deeply examined in Cucchiella et al. (2002), each criterion adopted to classify an e-SNs depends on two influencing variables that, in turn, are affected by some dependence parameters (Table I). However, such variables are not independent as a set of interdependence relationships may be established among them. In the following such correlations are determined according to two distinct procedures.

Since the distributive network is not relevant to this paper, the four b-webs organizational structures may be correlated with VI and CT as shown in Figure 1. With respect to managerial criteria, Nøkkentved (2000), extending the previous work of Ferrari (2000), states that such criterion may be defined on the basis of two variables, market fragmentation (MF) and product/process complexity (PPC). Consequently, six types of e-SNs may be identified (Figure 2): 1 auction house; 2 independent trading exchanges (ITEs); 3 vendor trading exchanges (VTEs); 4 consortium trading exchanges (CTEs); 5 private trading exchanges (PTEs); and 6 collaborative community exchanges (CCEs).

Interdependencies of influencing variables: a dependence parameters analysis In this section interdependencies among influencing variables will be analysed based on dependence parameters. To reach such an objective, it is useful to subdivide the investigated variables in two different sets. The first one is composed by CT, LFI and MF while the second VI, PPC and ND. With respect to the first set (CT, LFI and MF), it is evident that CT and LFI are both related to the presence of a leading actor and to its role in the decision-making process. More specifically, a high value of CT is possible in the case of presence of a leader, high level value offered to consumer and large enterprise dimension. However, these dependence parameters imply also a high leading firm influence that, according Zheng et al. (2001), is due to a high level contribution offered to value creation, large enterprise dimensions, high profits and sales volumes, high number of enterprises controlled by the leader, detention of critical resources and asset. At the same time, according the resource-dependency theory (Pfeffer and Salancik, 1978), CT depends on the industry concentration, that is the MF. For example, in the

Finally, several authors (i.e. Harland, 1996; Lamming et al., 2000) analysed the critical activities that have to be developed in an e-SN according the specific business environment in which it is embedded (Biemans, 1995; Johnsen et al., 2000). Such critical activities are assumed as a proxy of competencies to be owned by the central firm. Here we refer to the critical activities indicated by Zheng et al. (2001), who propose the concept of e-SN as “a set of inter-connected SCs, embedding Figure 1 The organizational structures

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Volume 10 · Number 2 · 2005 · 84 –95

Figure 2 Managerial criteria

Figure 3 Critical activities

activities are closely interconnected. More specifically, it is possible to define four combinations of such factors that result homogenous and consistent with specific environmental features (Table II).

case of a high number of suppliers, distributors and consumers is necessary to manage the network through a hierarchical control. This CT is needed in the case of a high number of actors. As a consequence, a strict interdependence among the three variables under investigation seems to exists. At the same time, it must be noted that there is no correlation among the dependence parameters related to these variables and those influencing the other three (VI, PPC, ND). On the contrary, parameters impacting on these last three variables appear strictly interdependent. For instance, the value of offered benefits (which impacts on VI) is tightly connected with the product customisation degree (which influences PPC) and to product variety (affecting ND). At the same time, the greater the product customisation degree (which has an effect on PPC), the greater the cost of switching supplier (which influences ND). Besides, the market dynamism (which impacts on PPC) is directly correlated to the innovation frequency (which has an effect on ND) and inversely to the market maturity (which affects ND). Insofar, the other three variables under investigation (VI, PPC and ND) are strictly connected and all refer to the type of relationships established among actors embedded in the e-SN. Based on earlier discussion, it may be stated that organizational structures, managerial criteria and key

Interdependencies of influencing variables: a flow-based analysis Interdependences among influencing variables may be identified and discussed also adopting a flow-based approach, that is analysing the content of exchange relationships among actors operating within the e-SN. Nevertheless, this analysis may be conducted only with respect to organizational structures and managerial criteria, being impossible to define flows connected to key activities. According to the managerial literature, flows taking place among actors embedded in a network may regard either material elements (for instance, goods, parts) or immaterial ones (such as, money, know how, patents information). However, there is not always a perfect correlation between material and immaterial flows. For instance, in a business-toconsumer (B2C) context, distributors generally prefer to have their own stocks, therefore the material flow is as follows: Manufacturer ) Distributor ) Customer: On the contrary, in a business-to-business (B2B) context distributors generally act as mere intermediates, as a consequence the material flow becomes: Manufacturer ) Customer: However, in both cases the immaterial flow is the same: 86

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Table I Variables and parameters describing e-SN patterns Factor

Influencing variables

Dependence parameters

Organizational structures

Value integration

Value of offered benefit Number of phases affected within the industry Number of operator types Leader presence-absence Level value offered to consumers Enterprise dimensions Degree of product customisation Durability-perishability of the good Market stability-volatility Supplier’s number Distributor’s number Consumer’s number Products variety Production volumes Supply-switching cost Innovation frequency Market maturity level Level contribution offered to value creation Enterprise dimensions Produced profits Sales volumes Number of enterprises controlled by the leader Detention or lack of critical resources Detention or lack of critical asset

Type of control

Managerial criteria

Product/process complexity

Market fragmentation

Critical activities

Network dynamism

Leading firm influence

Table II Combination of factors influencing supply chain performance Organizational structures

Managerial criteria

Key activities

1. 2. 3. 4.

Auction house ITE, VTE PTE, CCE, CTE PTE, CCE

Motivating, risk and benefit sharing, equipment integration, information processing Partner selection, decision making, equipment integration, information processing Partner selection, decision making, human resource integration, knowledge capture Motivating, risk and benefit sharing, human resource integration, knowledge capture

Agora Aggregation Value chain Alliance

Manufacturer , Distributor , Customer:Immaterial flows may regard transfer of data, information and knowledge (Davenport and Prusak, 1998). Data are unbiased elements related to events, while information is an elaboration of data aimed to define a specific meaning. Finally, knowledge is a mix of structured experiences, values, contextual information and intuitions based on experience, resulting from elaboration of information (Nonaka and Takeuchi, 1995). The nature of the flows among actors involved in the network can be schematised on the basis of a two digits code. The first, of binary type, is related to the presence/absence (respectively 0 and 1) of material flows. The second represents the presence/absence of immaterial flow and their nature. More specifically, the code will assume the value 0 in the case of no immaterial flows, 1 in the case of data exchange, 2 for information interchange and 3 for knowledge transfer. Above defined flows may be then analysed with respect to the three basic components of an e-SN: suppliers, central actors/manufacturers and customers (Lochamy and Smith, 2000). More specifically, the latter may be classified as intermediary customers, if they transform or resell purchased goods/services; or final customers if they use/consume goods/

services. In the alliance such two types of actors coincide, while in agora, aggregation and value chain, there is a coincidence between the central actor and intermediary customers. Based on such assumption, each organizational structure and managerial criterion may be schematised by a 3  3 flows matrix that, for each type of actor, defines the content of possible material and immaterial flows. Hence, flows related to the four combinations earlier identified (agora-auction house, aggregation-ITE/VTE, value chain-PTE/CCE/CTE and alliance-PTE/CCE) will be analysed and related flows matrix defined and compared: 1 Combination 1: agora-auction house. In virtual auctions, all actors reciprocally exchange information while goods transit directly from suppliers to consumers. Being both Agora and Auction House based on such a type of negotiation model, their flows matrix will result identical (Tables III and IV). 2 Combination 2: aggregation-ITE/VTE. As abovementioned, the Aggregation model may be used both in B2B and in B2C markets. In the first case, the central actor gathers information about consumers’ preferences and expectations, transferring them to suppliers. The 87

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Table III Flows in the agora Cent. Act. Inter. Cons.

Supp. Supp. Cent. Act. Inter. Cons. Final cons.

0

2

1

2

0

2

0

2

Final cons. 1 0

2 2

Table IV Flows in the auction house Supp. Supp. Cent. Act. Cons.

0 1

Cent. Act. 2 2

Cons.

0

2

0

2

1 0

3 2 2

latter use such information to identify a customized proposal for final customers. Hence, knowledge transfers take place between supplier and final users. At the same time, material flows take place directly between suppliers and final consumers (Table V). When aggregation is used in B2C contexts, the central actor needs to organize its own warehouses, owing to the huge number of potential customers and their geographical dispersion. Therefore, the material flow is organized in two-steps: firstly goods are transferred from suppliers to the central actor and then from the latter to the final customers. At the same time, as in the B2B context, the leading firm exchanges knowledge with suppliers. Contrary to the industrial markets, however, knowledge is also transferred between the leading company and the final customers, being impossible a direct exchange between suppliers and clients (Table VI). As mentioned above, also the ITE model may be used in the two contexts, B2B and B2C. In case of industrial markets, the leading firm manages only the transfer of simple information between buyers and suppliers but does

Table VII Flows in ITE (B2B) Supp. Supp. Cent. Act. Cons.

Supp. Cent. Act. Final cons. Inter. Cons.

0 1

Cent. Act. 2 3

0

2

0

2

Supp. Cent. Act. Inter. Cons. Final cons.

Supp. Cent. Act. Cons.

0

2

0

2

1 0

3 2

Cent. Act.

1

1

3

1

3

3

Cons. 1

3

Final cons. Inter. Cons. 1 0

Table IX Flows in VTE

3 2

Supp. Supp. Cent. Act. Cons.

Cent. Act.

1

Final cons.

1

3

1

3

3

Cons. 1

1

Cent. Act. Inter. Cons.

Supp.

3

3 1

2 3

Cons.

3

Table X Flows in value chain

Cent. Act. Inter. Cons. 1

1

0 1

Supp.

Table VI Flows in aggregation (B2C type) Supp.

Cent. Act.

Table VIII Flows in ITE (B2C)

Table V Flows in aggregation (B2B type) Supp.

not take part in the physical flow. Consequently, knowledge exchange will occur directly among suppliers and buyers (Table VII). On the contrary, in the case of B2C market, the presence of warehouses at the central actor level implies a two-steps material flows. At the same time, suppliers have a very limited knowledge with respect to customers needs, therefore it must be transferred by the central actor (Table VIII). Based on such considerations, ITE and aggregation are characterized by the same material and immaterial flows, as expected. Since the VTE is a B2B version of ITE, its flows will be the same of ITE in industrial markets (Table IX). Combination 3: value chain-PTE/CTE/CCE. As earlier pointed out, in the Value Chain the central actor allocates the different phases of value creation to actors on the basis of their competencies. Consequently, among such actors there are both material and knowledge flows (Table X). Similarly, in the PTE the leader, on the basis of owned power, constitutes a private club and assigns the different phases of value creation to participants (Table XI). In the CTE the leading company acts as a coordinator of different actors involved in the e-SN. Therefore, a knowledge interchange takes place with both buyers and sellers, but also between them. On the contrary, goods are directly transferred from supplier to customers, since the central actor is a mere orchestra director (Table XII).

Supp. Cent. Act. Inter. Cons. Final cons.

3

3

88

1 1

Final cons.

3

3

1 1

3

3

An integrated framework for e-supply networks analysis

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Volume 10 · Number 2 · 2005 · 84 –95

The proposed integrated framework

Table XI Flows in PTE Supp. Supp. Cent. Act. Cons.

Cent. Act. 1

1

Cons.

In the previous section, four possible combinations of organizational structures, managerial criteria and key activities were identified. Components of each combination result are homogeneous with respect to the type of relationships among actors. Therefore, they may be adopted in specific environmental contexts. As earlier stated, strong correlations between two sets of variables, which influence factors characterizing e-SNs, have been found. The first one is based on the presence and the possible role of the leading company, with respect to the decision-making process; while the second on the type of relationships established among various actors. Based on such results, it seems possible to identify two new macro-variables characterizing the environment in which the e-SN takes place: the decision-making concentration degree (Figure 4) and the internal integration degree (Figure 5). More specifically, CT, LFI, and MF are positively correlated to the decision-making concentration degree. As a consequence, the latter will results higher if CT is hierarchybased, the market highly concentrated and the leading firm extremely influencing. Also VI, ND and PPC are positively correlated with the internal integration degree. As a result, the latter will be higher if the offered value is relevant, the product/process complex and the network environment variable over the time. Summing up, the two new macro variables may be set at two levels (high and low) depending on the value of parameters shown below. Parameters affecting degree of decision-making concentration are: 1 High degree of decision-making concentration: . presence of a leader; . high size of leader enterprise; . high number of enterprises controlled by leader; . high contribution of leader to value creation; . high profits created by leader enterprise; . presence of leader critical asset and resource; and . high number of channel players within the industry and single category (supplier, producers, distributors). 2 Low degree of decision-making concentration: . absence of a leader; . low size of leader enterprise; . low number of enterprises controlled by leader; . low contribution of leader to value creation; . low profits created by leader enterprise; . absence of leader critical asset and resource; and . low number of channel players within the industry and single category (supplier, producers, distributors).

3

3

Table XII CTE flows Supp. Supp. Cent. Act. Cons.

4

0 1

Cent. Act. 3 3

0

3

0

3

Cons. 1 0

3 3

The CCE has a flows structure similar to the CTE, since the only difference lies in the type of involved actors. More specifically, while in the latter they are generally competitors, in the former they belong to the same vertical industrial environment (Table XIII). Combination 4: alliance-PTE/CCE. As previously highlighted, in the alliance model the central actor does not play any hierarchical role, being each actor totally independent. Consequently firms involved in the e-SN will be characterized by significant knowledge flows, while material transfers will take place directly among customers and suppliers (Table XIV). Based on such considerations, it results that this model has a flows structure totally consistent with those of PTE and CCE (respectively, Tables XI and XIII).

To sum up, both the adopted methodologies confirm the possibility of defining four sets of organisational structures, managerial criteria and key activities which results consistent with each other and with specific environmental conditions. In the next section, an integrated framework will be presented in order to define in which conditions the four sets are more usefully adopted.

Table XIII CCE flows Supp. Supp. Cent. Act. Cons.

0 1

Cent. Act. 3 3

0

3

0

3

Cons. 1 0

3 3

Parameters affecting degree of internal integration are: 1 High degree of internal integration: . high value of benefit offered; . high number of phases effected inside the network; . high number of operators types inside the network; . high perishability of the good; . low production volumes; . high degree of product customisation; . high product variety; . high innovation frequency; . low supply switching cost; and . high market maturity level.

Table XIV Alliance flows Supp. Supp. Cent. Act. Final cons. Inter. Cons.

0 1

Cent. Act. 3 3

0

3

0

3

Final cons. Inter. Cons. 1 0

3 3

89

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Volume 10 · Number 2 · 2005 · 84 –95

Figure 4 Decisional concentration level and its components

Figure 5 Internal integration level and its components

2

structures with reference to the environment in which they interact and operate. In order to verify the possibility of using in such a manner the proposed framework, it was applied to twelve relevant case studies cited in Tapscott et al. (2000), Nøkkentved (2000) and Zheng et al. (2001) to verify whether they fit in the proposed framework, thus validating the underlying conceptual model. However, information directly given by cited authors (Table XV last column) do not allow to thoroughly classify each examined company with respect to all three adopted factors. They only enable to associate them to one or two factors, thus preventing from readily applying the model. Therefore, for each case study supplementary information were also searched in literature and world wide web, as shown in Table XV, in order to enable the model utilization. Therefore to evaluate the coherence also with the other one/ two factors the following procedure was adopted: . selection of the reference model quadrant to which the case study belongs on the basis of identified factor(s); . determination, according to the model, of values of the remaining unknown factor(s); and . verification of the congruence between the value(s) assumed by factor(s) characterising the examined case

Low degree of internal integration: . low value of benefit offered; . low number of phases effected inside the network; . low number of operators types inside the network; . low perishability of the good; . high production volumes; . low degree of product customisation; . low product variety; . low innovation frequency; . high supply switching cost; and . low market maturity level.

Based on such evidencies, an integrated reference framework may be developed, using the two new macro variables (Figure 6). In each of the four quadrants, are indicated the combination of organizational structure, managerial criteria and critical activities more consistent with the specific business environment.

Integrated framework verification and application The proposed reference framework lends itself to be best utilized as an analysis and classification tool of e-SN Figure 6 The integrated global model

90

91

PlasticsNet

Peapod

Ariba

MSA Metalsite

Priceline

eBay

Mp3.com

Sun Microsystems

Linux

Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000) Tapscott (2000)

et al.

et al. Nøkkentved (2000)

Nøkkentved (2000), Davis (1999)

1. Aggregation 2. ITE

1. Aggregation 2. VTE 1. Aggregation

et al.

Mahadevan (2002), Nøkkentved (2000) Bhambri (2001)

1. Agora

1. Agora 2. Auction house 1. Agora

et al. Nøkkentved (2000)

Nøkkentved (2000)

et al. et al.

Tapscott et al. (2000)

et al. Nøkkentved (2000)

1. Alliance 2. CCE 1. Alliance

Nøkkentved (2000)

et al. Nøkkentved (2000)

Classification case studies

Kraemer and Dedrick (2002) 1. Value chain Tapscott et al. (2000) Zheng (2001) 1. Upper right quadrant framework critical activities 1. CTE

Leading firm influence

Critical activities

2. Alliance

Bailey (2001)

Zheng (2001)

Network dynamism

et al.

Nøkkentved (2000)

Mahadevan (2002)

Mahadevan (2002), Bailey (2001), Nøkkentved (2000)

Barratt and Rosdahl (2002), Lichtenthal and Eliaz (2003) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000) Tapscott et al. (2000)

Kraemer and Dedrick (2002)

Covisint

Tapscott et al. (2000)

Market fragmentation

Ali-Yrkko¨ (2001), Mahadevan (2002)

Tapscott et al. (2000)

Prod/proc. complexity

Managerial criteria

Nokia

Cisco Systems

Organizational structures Type of Value integration control

Table XV Available information on chosen case studies and their classification

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Antonio C. Caputo et al. Volume 10 · Number 2 · 2005 · 84 –95

An integrated framework for e-supply networks analysis

Supply Chain Management: An International Journal

Antonio C. Caputo et al.

Volume 10 · Number 2 · 2005 · 84 –95

studies, according to the value(s) of the respective influencing variables, and the values given by the model for the same factors.

Manufacturing Connection Online. The same technological platform also enables CMs to constantly monitor Cisco’s inventory levels, in order to continuously update producing plans. Tapscott et al. (2000) identify Cisco as a value chain, because of its high level of value integration (high offered benefit) and its hierarchical control (presence of leader). Based on such considerations, it has to be verified the consistency of Cisco business model with other two elements of the upper right quadrant: CCE, CTE or PTE managerial criteria and a set of four critical activities (partner selection, decision making, human resources integration, knowledge capture). With respect to the consistency with one of the managerial criteria (CCE/CTE/PTE), it has to be pointed out that Cisco is a typical example of PTE. Two main reasons can explain such an assumption. First of all, Cisco is able to dramatically reduce operating costs and to rapidly satisfy the needs of customers through the application of the internet technologies both to procurement and production. Second, Cisco holds highly qualified industry-specific competences and a strong trademark. These elements allow the firm to outsource noncore activities and easily create value for the whole business web. With respect to the consistency with the set of critical activities, it is crucial the leader high degree of influence over its partners and the high network dynamism (because of the relevant innovation frequency in the ICT industry). More specifically, Cisco carefully selects skilled actors which are able to successfully implement technological innovations. As a consequence, the Cisco ability to integrate partners and to promote knowledge capture becomes critical (Table XVI).

For space limitations the application of such procedure to case studies is shown only for four cases. Cisco Systems Cisco Systems (www.cisco.com) is a leading firm in the manufacturing of high-tech products like networking equipment, router and telecommunication software. According to its business model, Cisco concentrates on innovation as its core activity, while manufacturing and customer service are outsourced through long-term partnerships (Kraemer and Dedrick, 2002; Tapscott et al., 2000). As a consequence, Cisco has built up a supply chain – called Ecosystem – where very skilled partners are linked together by internet technologies (Kraemer and Dedrick, 2002). More specifically, Cisco coordinates different actors through both, its deep competences in the information and communication technology (ICT) and its strong trademark (Kraemer and Dedrick, 2002; Tapscott et al., 2000). This assumes more relevance because of the high level of fragmentation of the industry under investigation (Mahadevan, 2002). Another element qualifying the Cisco business model is the high degree of product customisation. An useful example is shown by the newly established Internet Business Solutions Group that provides the implementation of a global networked business model, that is developed on the needs of consumers and permits the use of advanced technological solutions in the e-commerce, customer-care, supply-chain management, e-learning and web foundation (Kraemer and Dedrick, 2002). Interactions among internal and external actors are online managed through many internet infrastructures: Cisco Connection Online, Manufacturing Connection Online, Cisco Employee Connection (Kraemer and Dedrick, 2002). The functionality of such applications will be now explained taking into account the traditional order cycle. Registered customers interested in acquiring Cisco products and/or services may use the “Marketplace” option. The same also allows the configuration of acquired goods. Moreover, both clients and business partners may collect technical information and download updated software through “Technical assistance” and “Software library” function. At the same time, they can access to commercial and administrative information (e.g. prices lists and state of the orders) using the Customer Service option. At the same time, the Internetworking Product Center automatically routes orders to Cisco or its suppliers depending on the demanded products. This system allows all actors to collect in real time information about products availability and delivery times. In the case of direct orders management by Cisco, an extranet platform (Cisco Supplier Connection, CSC) informs suppliers and contracts manufacturers (CMs) of possible deviations between received orders and scheduled production plans. In this way, suppliers can adjust their scheduling to the market needs. Finally, CSC enables, through “New product introduction” and “Autotest” functions, to continuously share information about products and to automatically verify them. On the other hand, when suppliers directly manage orders, they can directly ship products to customers through the

Linux Linux is an open-source operating system created in the 1990s as a Microsoft Windows competitor. This software – freely downloadable on the internet – is developed by the contributions of different users (Tapscott et al., 2000). More specifically, users at the global scale may propose and realise improvements for the initial version, in order to increase its capabilities and adapt it to new and differentiated needs (Tapscott et al., 2000). Originally, all contributes were managed by the Linux’s creator, Linus Torvald. Latterly, these contributes have been routed into a web site (www. linux.org) in order to better provide assistance to all who want to use Linux. As a consequence, this operating system has become the result of collaboration between different actors who strongly contribute to realise a highly complex high-tech product. Concluding, the role played by the internet technologies in order to create and spread relational capital useful for the value creation becomes extremely relevant. Linux is presented by Tapscott et al. (2000) as an alliance, because of its high level of value integration and the selforganizing control. More specifically, they classify Linux as a design collaborative alliance. Based on such a classification, it has to be verified the consistency of Linux with the other two elements of the lower right quadrant: CCE or PTE managerial criteria and a set of four critical activities (motivating, risk and benefit sharing, human resource integration and knowledge capture). The consistency with a managerial criterion (CCE/PTE), derives from the high product complexity and the low level of market fragmentation. More specifically, considering the 92

An integrated framework for e-supply networks analysis

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Antonio C. Caputo et al.

Volume 10 · Number 2 · 2005 · 84 –95

Table XVI Cisco Systems dependence parameters Factor

Influencing variables

Dependence parameters value

Factor value

Internal integration level

Value integration Product/process complexity Network dynamism Type of control Market fragmentation Focal firm influence

High offered benefit value High degree of product customisation High innovation frequency Presence of a leader High number of suppliers Presence of critical assets and resources

High

Decisional concentration level

strong collaboration among the network actors, Linux is a CCE. In fact, they modify the operating system in order to increase both its efficiency and correspondence to the needs of the users. As a consequence, all actors strongly contribute to the value creation. With respect to the coherence with the set of four critical activities, some supporting elements can be found in the business model of Linux. The first activity (motivating) is confirmed by the partners’ efforts to modify and improve the software, giving consumers the possibility to share the benefits of a continuous technological development. Therefore, all of them can equally benefit from the functionality of the software. Moreover, it has to be underlined the relevance of the role assumed by the web site in two activities: human resource integration and knowledge capture. Users can freely and in real time interact, strengthening and capitalizing their knowledge and competences, in order to achieve high standards of product efficiency (Table XVII).

High

that Priceline is characterised by the absence of an high consumer benefit, low efforts to create value, customised products/services and low switching costs (items are purchased in auctions potentially available to a wide range of buyers). With respect to critical activities, a great importance has to be given to the commercial risk and benefit sharing. The intermediator gains the difference between the price due to the supplier for the purchased service/product and the price imposed to the customer (MIT, 2001; Zhang, 2001). Therefore, the benefit sharing becomes quite evident. At the same time, the number of information processed by Priceline in order to manage data about suppliers, customers, different kind of goods and services and transactions are quite huge. Therefore, this activity becomes crucial for the creation of a sustainable competitive advantage. Finally, also partners’ motivation is extremely relevant, because of the high number of actors and the absence of a leader (Table XVIII). Peapod Peapod (www.peapod.com) is a B2C e-marketplace where registered customers can buy different types of groceries. Clients can access an online catalogue – linked to supermarkets of the Peapod’s network – order products and receive them directly at home (Mendelson, 2001; Tapscott et al., 2000; Pine et al., 1995). As a consequence, Peapod has to select supermarkets – typically a highly fragmented sector (Bhambri, 2001), and process information about both products and consumers (Tapscott et al., 2000). Since its establishment, this activity has been managed in two different ways (Levi and Levi, 1999). More specifically, initially a pull strategy has been adopted that implies the absolute lack of warehouses. Received the order from a customer, Peapod took products by the supermarkets closest to him/her and delivered groceries at his/her home. Such a business model, however, led to an high level of stock out rates (8-10 per cent) making the service offered quite ineffective. As a consequence, Peapod decided to build its own distribution centres where to pick up groceries. In this way, Peapod added a push strategy to the previous pull strategy, decreasing stock out rates to 2 per cent.

Priceline Priceline (www.priceline.com) is a “virtual plaza” where everyone can buy standardised goods and services (airline tickets, vacations, travels), fixing the maximum price he accepts. In other words, transactions are based on the reverse auction mechanism, which allows customers to make an offer and suppliers to accept or deny it (MIT, 2001; Eisner and Belmount, 1999). The internet site is managed by an independent intermediator not involved in production and/ or distribution of available services/goods. Priceline is defined by Tapscott et al. (2000) as an Agora, because of its self-organizing control (leader absence) and low value integration degree (commodity products). As a consequence, it has to be verified the consistency with the other two elements in the lower left quadrant: managerial criterion (auction house) and critical activities (motivating, risk and benefit sharing, equipment integration and information processing). As already stated, Tapscott et al. (2000) and Nøkkentved (2000) affirm there are a lot of close connections between agora and auction house models. With this respect, it is evident Table XVII Linux dependence parameters Factor

Influencing variables

Dependence parameters value

Factor value

Internal integration level

Value integration Product/process complexity Network dynamism Type of control Market fragmentation Focal firm influence

High offered benefit value High products obsolescence High innovation frequency Absence of a leader Low number of suppliers Absence of critical resources

High

Decisional concentration level

93

Low

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Volume 10 · Number 2 · 2005 · 84 –95

Table XVIII Priceline dependence parameters Factor

Influencing variables

Dependence parameters value

Factor value

Internal integration level

Value integration Product/process complexity Network dynamism Type of control Market fragmentation Focal firm influence

Low offered benefit value Low degree of product customisation Low switching costs Absence of a leader High number of suppliers Low contribution level offered to value creation

Low

Decisional concentration level

Low

coherent with those actually adopted. This result should not be considered a failure of the reference model, being the latter developed in order to classify orthodox e-SNs basing on the chosen criteria. However, specific circumstances may require alternative e-SN structures, while, on the other side, a proper management policy may make even unorthodox e-SNs efficient ed effective.

Peapod is presented by Tapscott et al. (2000) as an example of aggregation because of its hierarchical control, due to the presence of a leader, and its low value integration level. As a consequence, it is necessary to verify the consistency of Peapod business model with the other two features of the upper left quadrant: the ITE or VTE managerial organization and the set of critical activities (partner selection, decision making, equipment integration, information processing). With respect to the managerial criterion, it may be initially stated that Peapod is consistent with both ITE and VTE because of the high market fragmentation level, Bhambri (2001), and the low product complexity. More specifically, however, Peapod is an ITE because it operates in a B2C context where the warehouses ownership allows to increase the level of service offered to consumers and reduce constantly transportation and delivery costs (Chopra and Van Mieghem, 2000; Levi and Levi, 1999). With respect to the consistency with critical activities, it has to be pointed out the importance of suppliers’ selection, because of the sector fragmentation. Moreover, equipment integration and warehouses management are crucial in order to reach a high level of effectiveness in the offered service level. Finally, information processing is relevant because of the wide range of data about products and clients it has to manage (Table XIX). In the previous section the evaluation methodology presented has been applied to test the consistency and capabilities of the integrated reference framework on the basis of some relevant case studies. As a matter of fact the procedure has been applied to twelve case studies (although only four have been presented here owing to space limitations) and for all of them the usability of the proposed framework for e-SNs description and classification was confirmed. Nevertheless, the model it is not intended to represent an exhaustive schematization framework of any existing e-SNs. Indeed some network, such as SAP, has been identified in which the more appropriate set of organizational structure, managerial criteria and critical activities suggested by the framework it is not

Conclusions In spite of the huge number of research works on SN management, a lack was identified with respect to the definition of suitable integrated global frameworks for analysis of relationships among economic actors embedded in a e-SN. Therefore, in this paper a theory-based framework has been developed to classify e-SNs and verify their consistency with the business context in which they operate, on the basis of factors describing e-SNs patterns. Consistency among these factors has been evaluated in order to define four set of factors which are coherent with specific environment contexts. As a result, two macro-variables were identified, the internal integration degree and the decision-making concentration degree. According to them, the proper sets of the three factors have been defined. The results confirm that the proposed framework may also provide useful guidelines for managers and practitioners involved in e-SN design.

References Ali-Yrkko¨, J. (2001), Nokia’s Network – Gaining Competitiveness from Co-operation, Taloustieto Oy, Helsinki. Bailey, D. (2001), “Antitrust implications of B2Bs: Covisint – a competitive collaboration?”, available at: www.ftc.gov/ opp/ecommerce/comments/baileycovisint.pdf Baldi, S. and Borgman, H.P. (2001), “Consortium-based B2B e-marketplaces: a case study in the automotive industry”, 14th Electronic Commerce Conference, Bled, 25-26 June.

Table XIX Peapod dependence parameters Factor

Influencing variables

Dependence parameters value

Factor value

Internal integration level

Value integration Product/process complexity Network dynamism Type of control Market fragmentation Focal firm influence

Low number of operator types Low degree of product customisation High market maturity level Presence of a leader High number of suppliers and consumers Presence of critical assets

Low

Decisional concentration level

94

High

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Barratt, M. and Rosdahl, K. (2002), “Exploring business-tobusiness market sites”, European Journal of Purchasing & Supply Chain Management, Vol. 8, pp. 111-22. Beamon, B.M. (1998), “Supply chain design and analysis: models and methods”, International Journal of Production Economics, Vol. 55, pp. 281-94. Bhambri, A. (2001), “B2B in the food industry: what is the best marketplace model?”, available at: www.industrysearch. com.au/features/b2bfood.asp Biemans, W.G. (1995), “Internal and external networks in product development: a case for integration”, in Bruce, M. and Biemans, W.G. (Eds), Product Development: Meeting the Challenge of the Design-Marketing Interface, John Wiley, New York, NY, pp. 137-59. Chopra, S. and Van Mieghem, J.A. (2000), “Which e-business is right for your supply chain?”, Supply Chain Management Review, July/August, pp. 32-40. Cooper, M.C., Lambert, D.M. and Pagh, J.D. (1997), “Supply chain management: more than a new name for logistics”, The International Journal of Logistics Management, Vol. 8 No. 1, pp. 1-14. Cox, A., Chicksand, L. and Irelan, P. (2001), “E-supply applications: the inappropriateness of certain internet solutions for SMEs”, 10th International Annual Conference of International Purchasing and Supply Education and Research Association, Jo¨nko¨ping, 8-11 April. Cravens, D.W., Piercy, N.F. and Shipp, S.H. (1996), “New organisational forms for competing in highly dynamic environments: the network paradigm”, British Journal of Management, Vol. 7, pp. 203-18. Cucchiella, F., Fratocchi, L., Pelagagge, P.M. and Scacchia, F. (2002), “Analysis of factors affecting e-supply chain performance”, Journal of International Technology and Information Management, Vol. 11 No. 2, pp. 51-62. Davenport, T. and Prusak, L. (1998), Working Knowledge, Harvard Business School Press, Boston, MA. Davis, J. (1999), “PlasticsNet: the trading post. Taking on a 92 billion-pound gorilla – one buyer at a time”, Business 2.0, No. 1, September. Eisner, A.B. and Belmount, N. (1999), Priceline.com and Online Airline Ticket Business, Lubin School of Business, Pace University, Pleasantville, NJ. Ernst, R. and Kamrad, B. (2000), “Evaluation of supply chain structures through modularisation and postponement”, European Journal of Operational Research, Vol. 124, pp. 495-510. Ferrari, R. (2000), “Get your supply chain processes ready for trading exchanges”, Report on Supply Chain Management, AMR Research, Boston, MA, pp. 3-24. Harland, C.M. (1996), “Supply chain management: relationships, chains, and networks”, British Journal of Management, Vol. 7, pp. S63-S80. Harland, C.M., Knight, L.A. and Sutton, R.Y. (2001), “Information for supply interventions: sector, network and organization opportunities from network and organization opportunities from e-commerce”, 10th International Annual Conference of International Purchasing and Supply Education and Research Association, Jo¨nko¨ping, 8-11 April. Johnsen, T.E., Wynstra, F., Zheng, J., Harland, C. and Lamming, R.C. (2000), “Networking activities in supply networks”, Journal of Strategic Marketing, Vol. 8 No. 2, pp. 161-81.

Kraemer, K.L. and Dedrick, J. (2002), “Strategic use of the internet and e-commerce: Cisco Systems”, Journal of Strategic Information Systems, Vol. 11, pp. 5-29. Lambert, D.M., Emmelhainz, M.A. and Garden, J.T. (1996), “Developing and implementing supply chain partnerships”, The International Journal of Logistics Management, Vol. 7 No. 2, pp. 1-17. Lamming, R., Johnsen, T., Zheng, J. and Harland, C. (2000), “An initial classification of supply networks”, International Journal of Operations & Production Management, Vol. 20 No. 6, pp. 675-91. Levi, D.S. and Levi, E.S. (1999), The Effect of E-business on Supply Chain Strategy in Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies, McGraw-Hill, New York, NY. Lichtenthal, J.D. and Eliaz, S. (2003), “Internet integration in business marketing tactics”, Industrial Marketing Management, Vol. 32, pp. 3-13. Lochamy, D. and Smith, W. (2000), “Target costing for supply chain management: criteria and selection”, Industrial Management & Data Systems, Vol. 100 No. 5, pp. 847-68. Mahadevan, B. (2002), “Emerging market mechanisms in business-to-business e-commerce: a framework”, paper presented at International Conference for e-Business, e-Education, e-Science, and e-Medicine on the Internet, Rome. Mendelson, H. (2001), “Webvan: the new and improved milkman”, Graduate School of Business, Stanford University, Stanford, CA, available at: www.gsb.stanford. edu/cebc/pdfs/EC-31_Webvan.pdf MIT (2001), “eBusiness case examples”, MIT eBusiness Process Repository, available at: http://process.mit.edu/eph/ Directory.asp Nøkkentved, C. (2000), Collaborative Processes in E-supply Network, Center for Applied Management Studies, Copenhagen. Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company, Oxford University Press, New York, NY. Pfeffer, J. and Salancik, G. (1978), The External Control of Organizations: A Resource Dependence Perspective, Harper & Row, New York, NY. Pine, B.J., Peppers, D. and Rogers, M. (1995), “Do you want to keep your customers forever? How Peapod is customizing the virtual supermarket”, Harvard Business Review, March/ April, pp. 103-14. Tapscott, D., Ticoll, D. and Lowy, A. (2000), Digital Capital: Harnessing the Power of Business Webs, Harvard Business School Press, Boston, MA. William, L.R., Esper, T.E. and Ozment, J. (2002), “The electronic supply chain: its impact on the current and future structure of strategic alliances, partnership and logistics leadership”, International Journal of Physical Distribution & Logistics Management, Vol. 32 No. 8, pp. 703-19. Zhang, J. (2001), “Priceline.com accounting tricks? Net vs gross revenue”, available at: www.public.iastate.edu/ , chrisz/Academic%20Projects/acct598/Priceline.pdf Zheng, J., Johnsen, T.E., Harland, C.M. and Lamming, R.C. (2001), “A taxonomy of supply networks”, 10th International Annual Conference of International Purchasing and Supply Education and Research Association, Jo¨nko¨ping, 8-11 April.

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Determinants of business-to-business e-commerce implementation and performance: a structural model Damien Power Department of Management, Faculty of Economics and Commerce, The University of Melbourne, Parkville, Australia Abstract Purpose – Seeks to test the relative importance of various drivers of information-technology-related performance, and compare these drivers in the context of using established and emerging technologies. Established technologies include those generally promoted as the European Article Numbering (EAN) system (electronic data interchange (EDI), barcoding, etc.), while the emerging ones are based on the use of the internet. Design/methodology/approach – A survey was designed based on previous research and a series of case studies conducted within the membership of EAN Australia. The method of analysis employed was structural equation modelling based on data collected from 553 members of the EAN organisation in Australia. Findings – Use of technology enabling business-to-business (B2B) e-commerce was found to provide a potential source of performance improvement, but such improvement is shown to be more a function of the process by which strategy is formulated, and organisational capability, than of the technologies per se. The adoption and use of emerging technologies (such as the internet) are not subject to the same restrictions and impediments traditionally associated with established technologies. Therefore, organisations will find emerging internet-based technologies easier to implement and to use, but this will not necessarily mean that they will improve performance as a result. Performance will still be determined by effective strategy formulation, a clear understanding and knowledge of the technologies, appropriate application, and prudent change management. Research limitations/implications – This research has been conducted in Australia, and restricted to the membership of the EAN organisation. This membership is largely representative of the fast-moving consumer goods (FMCG) industry. Whether such results would be consistent in other countries and industries would need to be verified through further research. Originality/value – Develops and tests an integrated model linking strategy formulation, knowledge, capability, use of technology and performance. Provides valuable insight into why and how technology implementations can be configured for success. Keywords Electronic commerce, Management strategy, Supply chain management, Communication technologies, Performance measures Paper type Research paper

objectives, and the extent to which implementation has been promoted across the supply chain.

Introduction Many organisations are increasingly faced with the problem of having to manage not just internal operations and functions, but a broader range of relationships with trading partners. This need also has led many to look at implementing technological solutions to enable this process. Such implementations often promise much, but evidence suggests that realising the benefits of investment in this area has not always been easy. This paper endeavours to provide some insight into the nature of this problem by examining the relationship between such implementations, organisational performance and a number of proposed determinants of technology-based outcomes. These determinants include strategy development processes, organisational capability, knowledge of the technologies, content of plans and

Background Literature review The potential for information technology (IT) to alter the way supply chain partners interact, and to enable true integration is perhaps summed up by Christopher when he says: The use of information technology to share data between buyers and suppliers is, in effect, creating a virtual supply chain. Virtual supply chains are information-based rather than inventory-based (Christopher, 2000, p. 38).

Perhaps the most compelling illustration of the extent of the opportunity presented by advances in IT comes from Gagliardi (1996). He cites a number of reports to highlight the levels of information inefficiency (and opportunity) in supply chains generally. He uses the following examples: a Gartner Group report that found that 75 per cent of data consists of re-entry information from another computer; an A.T. Kearney study estimated that average supply chain management costs are 10.1 per cent of a company’s sales, while a Fortune magazine survey estimated this figure to be

The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm

Supply Chain Management: An International Journal 10/2 (2005) 96– 113 q Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/13598540510589179]

The author would like to thank EAN Australia for providing both cash and in-kind support for the conduct of this research.

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Business-to-business e-commerce implementation and performance

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10.5 per cent; the A.T. Kearney study also found that the cost breakdown was 19 per cent administration, 29 per cent inventory, 22 per cent warehousing and 30 per cent transportation. Unfortunately, although the vision is seductive, evidence suggests that the reality of adoption and use of long established technologies (such as electronic data interchange (EDI), barcoding, etc.) for the management of supply chains falls short of the expectation. EDI implementation has been identified in the literature as being both costly and complex to implement (Barua and Lee, 1997; Cash and Konsynski, 1985; Ramamurthy et al., 1999; Rassameethes and Kurokawa, 2000; Power, 2002). A 1998 Deloitte Consulting study (Modern Materials Handling, 1998) of 200 manufacturing firms in the USA found that only 33 per cent believed their supply chain management capabilities to be better than average for their industry. Only 1 per cent rated their performance in this area as world class. This survey also found that 80 per cent had embarked on a major supply-chain initiative, and 75 per cent were significantly increasing spending on technology to support these programs. The survey identified the most important issue for these companies as managing the flow of information, but also found potential problems for companies in managing that flow. Many companies reported having EDI capability, but in general were not using EDI for a large proportion of transactions. Respondents also indicated that they saw EDI channels being replaced by the internet in the near future, although it was not clear how they saw this impacting on information management between partners. These findings are supported by a survey in the USA by Tompkins and Associates (IIE Solutions, 1999) that found 86 per cent of respondents felt their supply chain techniques were not aligned with marketplace demands, and 53 per cent were not satisfied with their return on investment from these initiatives. A study of 57 suppliers to the US auto industry (Jayaram et al., 2000) found that the potential for deployment of IT to have a significant impact on time-based performance is greatly enhanced by the application of other complementary methods such as concurrent engineering, process improvement and standardisation. These results perhaps point to why so many organisations report dissatisfaction in this area, given that the deployment of IT will need to be associated with a process improvement program before real gains can be expected to be realised. These results are supported by other research on the business benefits of EDI adoption (Lee and Clark, 1999; Ramamurthy et al., 1999). The Ramamurthy et al. study in particular found that extensive diffusion of EDI between partners can create significant benefits, but that the extent of diffusion was dependant on an array of internal and external factors. These included competitive pressure, customer support, internal support, compatibility, resource intensity and benefits potential of EDI. Recent Australian research in this area further reinforces these findings, where similar barriers to adoption have been identified, and evidence found to suggest that in many cases these barriers are only overcome through significant pressure being applied by trading partners (Power and Sohal, 2002). The strategic implications of supply chain management and business-to-business (B2B) e-commerce has also attracted some research attention. Gilmour and Hines (2000) interviewed managers in 17 companies in Australia and the UK and found three factors that had a significant impact on

the extent to which capabilities in managing supply chains would be applied strategically. These included the historical relationships between trading partners, position of power in the channel and the nature of the logistics task. Gilmour (1999) conducted a study of nine companies to assess how they add value by managing the supply chain strategically. Using a combination of surveys and in-depth workshops, he concluded that cost reduction and containment (as strategic objectives for logistics operations) were not sufficient to sustain competitive advantage. Adding value through logistics was a more effective strategy, in particular through improving organisational capabilities in the areas of IT and areas such as teamwork, performance measurement and alignment of organisational culture. Malhotra and Grover (1998) identify two types of survey research: exploratory and explanatory. Exploratory research can be characterised as descriptive in nature, starts without a model, and seeks to clarify issues for further research. Explanatory research is usually focused on finding causal relationships between variables. Models that have been developed from theory would typically be tested in this type of research. It is interesting to note that out of a total of 85 survey research related papers identified during the review of the literature for this research, 63 (74 per cent) fell into the exploratory category, while 22 (26 per cent) could be categorised as explanatory (the majority of these being simulation models). Bakos and Treacy (1986) developed an early model hypothesising the relationship between IT and corporate strategy in the mid-1980s. They proposed a causal relationship where competitive advantage was determined by a combination of bargaining power and comparative efficiency. They theorised that the use of IT for developing innovative products could affect comparative efficiency (through reduced operating costs) or bargaining power (by promoting differentiation and customer switching costs). The changing nature of technology, and its subsequent alteration of these relationships, is emphasised by Porter (2001). In discussing the impact of the internet on competitive advantage, he states that operating efficiencies will be improved by internet technologies, but that the improvement will not be sustainable in the long term. This is due to the open nature of internet technologies, and the normative effect this could have. This same effect, according to Porter, will reduce the ability of companies to differentiate their offerings, and will also reduce switching costs. This example serves to illustrate the effect such rapid changes in technology can have on the development and testing of theory in the area of supply chain management and B2B ecommerce. It may also partially explain the low percentage of explanatory (or causal) models in the literature. Significance of this study This research is situated in the context of limited adoption and satisfaction with established technologies, evidence of opportunities for improved competitive advantage through their application, and the emergence of open and cheap internet-based applications. The lack of models developed to try to explain the dynamics (within organisations) of the relationship between availability and opportunities presented by established technologies on one hand, and their limited historical adoption on the other, represents a significant gap in the literature. Given the emergence of cheaper and more freely available alternative technologies (e.g. internet based) 97

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an opportunity also exists to test for their potential impact on such a model. This research is aimed at developing a model to fill this gap, and as a result provides insights into some important relationships, as well as a platform from which subsequent research can be conducted.

suppliers. Hicks identifies the goal of strategic supply chain planning as being “. . . to arrive at the most efficient, highly profitable supply chain system that serves customers in a market” (Hicks, 1999, p. 26). As such, he states that these types of decisions are characterised by high expenditures and significant risk. He identifies two separate paradigms for supply chain improvement, centred around IT and logistics. Although it is desirable to model the behaviour of a supply chain in order to make informed planning decisions, the issue of dynamic competitive environments makes this an activity that is at best difficult, and at worst perilous. It is also apparent that for organisations to develop a competence in the management and integration of supply chains, logistics and supply chain management need to be given a higher level of strategic importance (Meade, 1998; Philip and Pedersen, 1997). As such, links have recently been identified between more effective integration strategy development and performance (Rosenzweig et al., 2003; Vickery et al., 2003). The importance of a strategic outlook is captured in H2: H2. The strategic “mindset” of an organisation is a significant determinant of the extent of implementation.

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Hypothesis development Knowledge of the technologies Although the early research in this field examined the dynamics of the industrial “system” of the supply chain (Forrester, 1958, 1961), analysis at that time (and subsequently) points to the behaviour of the system being determined by the decisions made at the individual organisational level (Forrester, 1958, 1961, 1968; Sterman, 1989; Holweg and Bicheno, 2000). Recent studies indicate that better decision making can be linked to better understanding of system capabilities, leading to more effective VMI strategies (Disney and Towill, 2003a, b), as well as more effective forecasting (Djonckheere et al., 2004). Supply chain management means the focus of management must go beyond that of the individual enterprise, but the ability of the enterprise to see the opportunities, and turn them into value adding processes could well be largely dependent on internal resources and their deployment. It follows, therefore, that in order to be able to implement business-to-business (B2B) e-commerce enabling technologies, individual organisations need to have some understanding of the implications, as well as the range of options available. The implication can be drawn that levels of understanding of the technologies, their applications, and their benefits would be related to the quality of such decisions. There is an emergent body of literature that seeks to link understanding of the benefits to extent of implementation (Handfield et al., 2000; Stevens, 1990; Truman, 2000), and the literature also provides theoretical models of what constitutes an extensive implementation (EAN Australia, 1998; Mussellman, 1997). The importance of knowledge of the technologies is captured in H1. This hypothesis tests the proposition that those organisations with higher levels of understanding of these issues will be more likely to implement B2B enabling technologies more extensively: H1. The extent of implementation will be significantly determined by: (a) the level of understanding of the range of options; (b) potential benefits; and (c) the range of applications available for implementation.

This hypothesis tests the proposition that the propensity for an organisation to extend implementation beyond it’s own operational boundaries will be strongly related to, and perhaps largely determined by, the strategic “mindset” that characterises the organisation. This is not a theme that is covered empirically to any great extent in the literature, and represents a gap that this study seeks to fill. “Mindset” in this context relates to two separate areas of an organisation’s strategic outlook that are captured in the following subhypotheses: H2a. The content of an organisation’s strategic objectives and plans will be a significant determinant of extent of implementation. This hypothesis tests the proposition that organisations articulating their strategic objectives and plans relating to supply chain management will be likely to reflect this in the extent of implementation. The relationship between strategic intent and extent of implementation of these technologies is not one that is widely reflected in the literature. There is, however, an extensive body of the strategic management literature covering the argument for and against deliberately articulating strategy to enable effective implementation (i.e. of that strategy) (Mintzberg, 1987, 1991; Mintzberg and Waters, 1985; Ansoff, 1965, 1972, 1991; Ansoff et al., 1974). More recent research in the context of applying technologies to the management of supply chains indicates that the internet is being used to aid supply chain strategic planning (Lancioni et al., 2003). If it is accepted that the implementation and use of B2B technologies is inherently strategic, then it is worthwhile testing for a relationship between the extent of planning and articulation, and extent of implementation: H2b. The process by which an organisation formulates it’s strategic logic will be a significant determinant of extent of implementation.

Strategic importance of B2B-enabling technologies The strategic nature of supply chain management methods is a common theme in the literature (Bovel and Martha, 2000; Hicks, 1999; Fein and Jap, 1999; Kaufman et al., 2000; Lummus and Vokurka, 1999; Magretta and Dell, 1998; Magretta and Fung, 1998; Porter, 2001; Sislian and Satir, 2000; Stock et al., 1998). Porter (2001), in analysing the potential for emerging technologies to alter competitive environments, sees a major opportunity for organisations to differentiate themselves on the basis of a distinctive value chain. In fact, he states that this may be one of the few ways in which companies can develop a sustainable competitive advantage using these technologies, as the overall effect of their adoption will be to intensify competition, lower barriers to entry and increase bargaining power of both buyers and

The theme of environmental and technological change driving the need for the use of B2B e-commerce technologies in the management of the supply chain is a common one in the literature (Ballou et al., 2000; Bensaou and Earl, 1998; 98

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Porter, 2001; Zhang and Sharifi, 2000; Wilding, 1998; Westhead et al., 2000; Rao, 1999; Salvador et al., 2001; Rudberg and Olhager, 2003). Against a background of such environmental turbulence, extensive implementation becomes even more problematic for organisations. On the one hand there is an apparent imperative to implement, and on the other the nature of such an environment can significantly influence the integrity of decision processes. Action uninformed by effective environmental scanning processes will be fraught with risk. This hypothesis captures the proposition that extent of implementation will be characterised by effective processes for strategic logic formulation that are designed to mitigate these risks.

appears strong on rhetoric, but weak on weight of real evidence. Some authors provide empirical evidence to support the proposition that significant benefits come as a result of implementing a range of supply chain management practices and technologies (Crum and Allen, 1997; Fernie, 1995; Handfield et al., 2000; Lancioni, 2000; Monczka et al., 1998; Narasimhan and Jayaram, 1998; Shin et al., 2000; Tan et al., 1999). There are, however, a number of studies that are at best cautionary in relating the ease and certainty of realising these benefits (Min and Galle, 1999; McCutcheon and Stuart, 1999; New, 1996; Stuart and McCutcheon, 1996; Stuart, 1997; Whipple and Frankel, 2000). It is also apparent that nearly all of these studies are focused on the correlation between supplier relationships and business benefits. Another point of interest to emerge from the literature review is that of 236 documents scanned during the review process (using content analysis and the NVivo text analysis program), only 7 (3 per cent) were found to mention performance measurement. Of these, only four related directly to methods for the measurement of supply chain performance (Beamon and Ware, 2001; Holmberg, 1999; Tarr, 1998; Walker, 2001). The testing for relationships between perceived business outcomes and the extent of implementation of supply chain management practices and B2B e-commerce technologies is therefore captured in the following hypothesis: H5. Extent of implementation will be a significant determinant of perceived business benefits.

Capability to implement B2B technologies Another common theme in the literature is that of the need for supply chain processes to be reengineered, and the strategic nature of this task (Mabert and Venkataramanan, 1998; Ruetterer and Kotzab, 2000; Tan et al., 1998). Having the intent to implement is one thing, putting it into practice is another. The need to focus on processes when implementing e-commerce applications is highlighted by Froehlich et al. (1999, p. 473): E-commerce places new demands not only on delivery technology, but on the way that business processes are designed. At present, technology is forcing organisations to embark on e-commerce before they have built a coherent model of the business processes they need.

The appropriateness of legacy business processes has also been identified as a potential impediment to implementation. An Andersen Consulting report (Anderson Consulting, 1994) has identified inaccurate data, existing systems infrastructure and entrenched business practices as the major barriers to implementation of advanced technologies and innovative management approaches. The literature is also thin in providing empirical evidence on successful investment profiles, although there is much talk of the importance of Return on Investment as a metric for success. Some articles address the issue of where money could (or should) be spent, but few provide empirically based guidelines in support (Jutla et al., 1999a; Frye, 1997; El Sawy et al., 1999; Masella and Rangone, 2000; Waller et al., 1999). This is a significant gap as it follows that if organisations are to reengineer processes in order to implement extensively, they also need to decide where to invest. Choices for investment can cover issues as diverse as software and hardware choice, use of consultants, training, process reengineering and outsourcing. The importance of investment decisions is highlighted by the inherently complex nature of the implementations process (Pant et al., 2003). The following hypotheses are designed to test for the effect of the combination of the ability to reengineer existing business processes, and the choice of an appropriate investment strategy, on extent of implementation and performance: H3. Capability to implement will be a significant determinant of extent of implementation. H4. Capability to implement will be a significant determinant of extent of performance.

The influence of emerging technologies The rapid development of communications infrastructure and technological change is rated by many authors as having the potential to move supply chain management into its next phase of integration. Projections of the potential impact of technology include: the development of “directory enabled networks” that will enable smarter, more interactive search and relationship management capabilities (Cohen and Jordan, 2000); extensive use of extranets, sub contracting and networked enterprises to promote “mass customisation” (Magretta and Dell, 1998; Magretta and Fung, 1998); more rapid and extensive adoption of EDI technologies through the use of the internet and the development of XML/EDI standards (Puttre, 1997; Johnston and Mak, 2000); moves toward collaborative design platforms as product life cycles shorten and customer intelligence becomes more accessible (Say, 2000); reengineering of cross organisational processes into task specific work flows (Seybold, 1999); and a fundamental shift in power to the consumer changing the nature of relationships with customers, and the way companies compete (Slywotzky et al., 2000). This perception is further highlighted by content analysis of 236 articles used in this review of the literature using the NVivo software package. In this case 133 (56 per cent) of these articles addressed themes related to the emergence, adoption, use and proposed impact of the internet for the extension of supply chain management capabilities. At the same time, many are recognising the fact that effective use of internetbased solutions and methods can be highly situational (Garcia-Dastugue and Lambert, 2003). The findings that emerge from the previous five hypotheses need to be examined in light of the use and availability of new technologies to determine whether they still remain valid.

Relationship between extent of implementation and performance The literature promotes heavily the business benefits that will accrue to organisations as a result of extended implementation. This is one area of the literature that 99

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H6.

analysis to be carried out on a subset of the full database, and to reduce the proportion of missing data for some constructs. AMOS, the structural equation modelling (SEM) package developed for use with the SPSS statistical analysis program, along with SPSS, was used for the analysis.

Characteristics identified for the adoption and use of existing technologies (H1-H5) will still hold true for emerging technologies such as the internet.

Method

Structural model development

Background A survey instrument was designed for the testing of these hypotheses using data gathered from a review of current literature combined with two separate sets of case studies (a total of 15 cases). These cases were conducted in two phases. The first comprised five companies, one being a major retailer, the other four being suppliers to that retailer. The second set covered ten EAN Australia member companies. The focus of these case studies was on developing a clearer view of levels of knowledge of the EAN (European Article Numbering) system, processes in place in these organisations determining levels of implementation, perceived benefits derived from implementation, and impediments to further adoption.

Background Survey items generally employed five-point Likert scales with the range being “not at all” to “a very large extent”, or “not important” to “extremely important” depending on the nature of the question (where different dimensions were used they are detailed in the tables below). Factor analysis was employed on a subset of the data to extract underlying constructs or factors from the data set. As a result 15 separate factors were extracted (comprised of 116 individual survey items). These were subsequently reduced to factor variables for use as variables in the structural model. In some cases two factors were combined to produce a single variable (where the theory justified this) to promote model simplicity. Six dimensions comprise the basic model.

Survey sample The sample for the conduct of this research has been drawn from the membership of EAN Australia. EAN Australia is the organisation that administers, validates and issues EAN standard barcodes to Australian companies. As well as promoting the use of these barcodes, EAN promote a system for the adoption and implementation of electronic commerce and supply chain management. This uses a combination of EAN-numbering, barcoding and EDI-type technologies to link the flow of physical goods with the flow of information through a supply chain.

Basic model components Capability In the model this dimension is an unobserved variable comprising two factor variables. These comprise three separate factors, namely strategic reengineering (variable in model “streeng” comprising seven survey items – alpha 0.8114), infrastructure spending (comprising four survey items – alpha 0.6867) and technology spending (comprising two survey items – alpha 0.7088) combined (variable in model “investprof”): 1 Strategic reengineering (five-point Likert scale, “not at all” to “to a very large extent”): . extent of involvement during the planning and implementation of the EAN system of senior management; . the EAN system has become an integral part of the organisation’s continuous improvement process; . the strategic importance of implementation is understood within our organisation; . implementation of the EAN system is a response by our organisation to a rapidly changing business environment; . EAN system implementation will improve organisational innovation; . we implemented the EAN system at a time of generally good business performance; and . implementation has been the result of senior management driving change. 2 Infrastructure spending (six-point scale, “0 per cent” to “100 per cent”): . approximate percentage of total expenditure allocated to other capital equipment; . approximate percentage of total expenditure allocated to process re-engineering; . approximate percentage of total expenditure allocated to consultants; and . approximate percentage of total expenditure allocated to training/employee development. 3 Technology spending (six-point scale, “0 per cent” to “100 per cent”):

Elements of the EAN system Standard numbering and barcoding The use of standard numbering allows unique worldwide identification of products, shipments, organisations, locations and a range of variable data such as batch identification, useby dates, etc. The barcodes allow these numbers to be read by a scanner and input into a computer enabling automated data capture. EDI EDI is direct computer-to-computer exchange between trading partners of agreed and structured business documents such as purchase orders, invoices, consignment notes, remittance advice and customs documents. The combination of EAN numbering, barcode scanning and EDI enable organisations to link the physical movement of goods to the electronic data related to those goods. Thus the potential is created for business-to-business electronic commerce, and the capability produced for inventory, logistical and sales information to be widely understood across the entire supply chain. Survey administration and data segmentation The survey was administered to 3,356 managers in EAN member organisations responsible for the use of the EAN system. There were 553 responses received, indicating an estimated response rate of 16.5 per cent. The sample size was reduced to 335 companies for the confirmatory analysis using the structural model. This was done to allow the initial factor 100

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approximate percentage of total expenditure allocated to computer related hardware; and approximate percentage of total expenditure allocated to computer software.

the importance placed by your organisation on reviewing competitor’s access to and cost of raw materials; . the importance placed by your organisation on reviewing competitor’s relative cost position; . the importance placed by your organisation on reviewing competitor’s processes in bringing new products to market; . the importance placed by your organisation on reviewing competitor’s human resource practices and policies; and . the importance placed by your organisation on reviewing competitor’s planning and investment justification processes. Benchmarking (five-point scale, “0” to “9 þ ”): . estimated number of different sites visited for the purpose of benchmarking during a calendar year senior management; . estimated number of different sites visited for the purpose of benchmarking during a calendar year middle management; . estimated number of different sites visited for the purpose of benchmarking during a calendar year frontline management; and . estimated number of different sites visited for the purpose of benchmarking during a calendar year general staff. Stakeholder involvement (five-point Likert scale, “not at all” to “to a very large extent”): . extent of involvement during the planning and implementation of the EAN system of middle management; . extent of involvement during the planning and implementation of the EAN system of front-line management; . extent of involvement during the planning and implementation of the EAN system of general staff; . when we develop our plans, policies and objectives we incorporate customer requirements, supplier capabilities and the needs of other stakeholders; . senior managers actively encourage change and implement a culture of trust, involvement and commitment in moving toward implementing ISCM; . champion(s) of change are effectively used to drive change in this organisation; . at this organisation we pro-actively pursue continuous improvement rather than reacting to crisis/fire fighting; . ideas from production operators are actively used in assisting management; . our company has effective “top-down” and “bottomup” communication processes; . we know our customer’s current and future requirements (both in terms of volume and product characteristics); and . these customer requirements are effectively communicated and understood throughout the workforce. .

The ability to reengineer processes was judged to be indicative of the organisation’s capability to implement their supply chain management strategy. Capability is also characterised in the model by the investment profile of an organisation. This construct was felt to be of importance for representing the propensity for an organisation to invest in the necessary infrastructure (human and human process based) to support effective implementation. 3 Process In the model this dimension is an unobserved variable comprising three factor variables. These are comprised of four separate factors, namely challenging cognitive frameworks using external resources (variable in model “ccframeext” comprising 11 survey items – alpha 0.8596), environmental scanning (variable in model “envscan” comprising nine survey items – alpha 0.9344), benchmarking (comprising four survey items – alpha 0.8687) and stakeholder involvement (comprising 11 survey items – alpha 0.8614) combined to create the construct challenging cognitive frameworks using internal resources (variable in model “ccframeint”): 1 Challenging cognitive frameworks using external resources (five-point Likert scale, “not at all” to “to a very large extent”): . the following have been a valuable source of advice or assistance customers or clients; . the following have been a valuable source of advice or assistance suppliers; . the following have been a valuable source of advice or assistance competitors; . the following have been a valuable source of advice or assistance international or overseas firms; . the following have been a valuable source of advice or assistance other Australian firms; . the following have been a valuable source of advice or assistance industry associations; . the following have been a valuable source of advice or assistance management consultants; . the following have been a valuable source of advice or assistance university or business schools; . the following have been a valuable source of advice or assistance conferences; . the following have been a valuable source of advice or assistance exhibitions; and . the following have been a valuable source of advice or assistance media. 2 Environmental scanning (five-point Likert scale, “not important” to “extremely important”): . the importance placed by your organisation on reviewing market share of competitors; . the importance placed by your organisation on reviewing competitor’s processing technologies; . the importance placed by your organisation on reviewing competitor’s quality assurance procedures; . the importance placed by your organisation on reviewing competitor’s product range;

4

The three factors making up the unobserved variable “process” draw on the Sanchez and Heene (1997) model. In order to provide a context for the initial examination of different organisational approaches to strategy development, 101

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a model of the organisation as an open system facing an uncertain future was used (Sanchez, 1997; Sanchez and Heene, 1997). In this model the requirement for flexibility and adaptability in the face of an uncertain and changing environment places pressure on the rationale for achieving organisational goals (the organisation’s strategic logic). The formulation of that logic in this model is enabled by three dimensions. The first of these dimensions is challenging cognitive frameworks, and it captures the need for companies to question basic business assumptions in order to remain flexible. The second element of the Sanchez and Heene (1997) model captures the need for organisations to scan their environment in order to be as aware as possible of impending change, and how that change could affect competitive positioning. The exploratory and initial case studies provided some evidence that these issues were important for firms in determining strategies for implementation of the EAN system. Benchmarking is the third dimension of the Sanchez and Heene model, and it covers the gathering of information on “best practices” from within (as well as beyond) a firms industry. Both sets of cases provided some evidence for this practice being an integral part of formulating effective implementation strategies. It was also identified through the review of the literature and the conduct of the cases that the Sanchez and Heene model could be expanded to incorporate the potential input from a broader range of stakeholders. One theme to emerge from both the literature and the cases was that extended involvement of suppliers, customers and employees was important for the development of effective supply chain management strategies (Cachon and Lariviere, 1999; Cachon and Fisher, 2000; Bensaou, 1999; Bensaou and Anderson, 1999; Bensaou and Venkatraman, 1995; Cox, 2000; Masella and Rangone, 2000; McCutcheon and Stuart, 1999; Maltz and Srivastava, 1997; Stuart, 1997; Stuart and McCutcheon, 1996). The involvement of these stakeholder groups was incorporated in the model with benchmarking to create the construct challenging cognitive frameworks using internal resources. The combination of these two factors attempts to capture the idea from the Sanchez and Heene (Sanchez and Heene, 1997; Sanchez, 1997) model of challenging cognitive frameworks from within as well as from external means, and extends the concept of benchmarking to a broader one of organisation wide stakeholder involvement.

we understand the potential benefits for our organisation from implementing integrated supply chain management techniques; . we understand the extent to which implementation affects the day to day running of our business; . all relevant staff have participated in information sessions/training programs; . the difference between a “reactive”, “tactical” and “strategic” implementation is understood in our organisation; . we understand the technical issues relevant to implementing integrated supply chain management techniques; . our organisation has a good understanding of the full range of strategic options for implementation; . our organisation has a good understanding of the full range of technological options for implementation; and . our organisation has a good understanding of why implementation is important for the business. Understanding of the potential benefits of the EAN system (five-point Likert scale, “not at all” to “to a very large extent”): . use of the EAN system can lead to improved stock management; . use of the EAN system can lead to improved customer service levels; . use of the EAN system can lead to improved quality and timeliness of business information; . use of the EAN system can lead to improved application, understanding and use of electronic commerce; and . use of the EAN system can lead to improved ability of the organisation to be flexible and adjust to rapid change. Understanding of a full implementation of the EAN system (fivepoint Likert scale, “Not at all” to “To a very large extent”): . “full” implementation of the EAN system means applying EAN product numbers and barcodes to all WIP and outward goods; . “full” implementation of the EAN system means scanning and capturing data using EAN numbers and barcodes for use in all functional areas of the business; . “full” implementation of the EAN system means applying EAN product numbers and barcodes to all incoming items, WIP and outward goods; . “full” implementation of the EAN system means outsourcing application of product numbers and barcodes to a third party; and . “full” implementation of the EAN system means proactively encouraging all suppliers to apply and scan EAN barcodes. .

2

3

Knowledge In the model this dimension is an unobserved variable comprising two factor variables. These comprise three separate factors, namely knowledge of implications and options for implementation of the EAN system (variable in the model “know1” comprising ten survey items – alpha 0.9474), understanding of potential benefits of the EAN system (comprising five survey items – alpha 0.8824) and understanding of a “full implementation” of the EAN system (comprising five survey items – alpha 0.8341) combined (variable in the model “know2”): 1 Knowledge of implications/options for implementation of EAN system (five-point Likert scale, “not at all” to “to a very large extent”): . we have a good understanding of the full implications of implementation for our business; . B2B e-commerce opportunities are understood in our organisation;

The first of the three elements covering this issue relates to the implications of implementation, and options available to companies. The second aspect of knowledge covered here revolves around the potential benefits to be had from implementation. The third aspect covers the issue of levels of understanding of what a complete or extended implementation of the EAN system means. These final two factors were combined in the model to reflect a high degree of covariance evident between them during model testing, 102

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indicating some degree of overlap between the two constructs in the context of the model.

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Content In the model this dimension is a factor variable made up of 15 individual observed variables (alpha 0.9336) covering the stated plans, objectives and expectations of the implementation strategy (five-point Likert scale, “not at all” to “to a very large extent”): . our objective was to better manage our own internal processes only; . our objective was to better manage our complete supply chain; . our objective was to use implementation as a catalyst for change; . our objective was to extend implementation to our own suppliers; . we expected to gain tangible benefits for our business from implementation; . we expected real cost savings for our business from implementation; . we expected to gain major productivity improvements from implementation; . we expected implementation to lead to further application of electronic commerce in our company; . we expected implementation to lead to further application of electronic commerce across our entire supply chain; . we expected implementation to fundamentally alter business operations; . implementation has been carefully planned and costed; . implementation is part of a long term strategic plan; . implementation has followed development of a detailed business case and project plan; and . implementation followed a critical evaluation of our supply chain and processes.

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.

there has been cross functional involvement in the implementation process; suppliers have been involved in implementation; implementation is critical to the competitiveness of our organisation; and implementation is seen to be a strategic opportunity for our organisation.

Each respondent was then categorised as being “strategic”, “tactical” or “reactive” based on the mean scores of these variables. As a result of this classification process each case was coded within this variable as being either: 1 ¼ “reactive”; 2 ¼ “tactical”; or 3 ¼ “strategic”. This variable was then used in the model to represent the extent of implementation construct. Performance This dimension of the model is made up of one factor variable. As a result of the initial factor analysis of 17 variables from the survey, two factors were extracted and named operational outcomes (comprising 13 survey items – alpha 0.9700) and bottom-line outcomes (comprising four survey items – alpha 0.8540): 1 Operational outcomes (five-point Likert scale, “not important” to “extremely important”): . contribution of the EAN system implementation to reduced finished goods inventory; . contribution of the EAN system implementation to reduced WIP inventory; . contribution of the EAN system implementation to reduced raw materials/components inventory; . contribution of the EAN system implementation to improved product traceability; . contribution of the EAN system implementation to improved stock accuracy; . contribution of the EAN system implementation to reduced time required for annual stock takes; . contribution of the EAN system implementation to increased productivity; . contribution of the EAN system implementation to improved product quality; . contribution of the EAN system implementation to increased flexibility; . contribution of the EAN system implementation to reduced cycle times; . contribution of the EAN system implementation to improved cash flow; . contribution of the EAN system implementation to reduction in claims; and . contribution of the EAN system implementation to reduced costs. 2 Bottom-line outcomes (five-point Likert scale, “not important” to “extremely important”): . contribution of the EAN system to: Improved customer satisfaction; . contribution of the EAN system to: Improved service quality; . contribution of the EAN system to: Increased sales; and . contribution of the EAN system to: Increased net profit.

Extent of implementation In the model this dimension is a variable measuring the degree to which implementation has been extended beyond the enterprise to include customers and suppliers. The literature also proposes a formal model for implementation based around three approaches: “strategic” (actively promote use of the EAN system with multiple supply chain partners), “tactical” (use some aspects of the system internally and to a limited extent with trading partners); and “Reactive” (apply barcodes to outgoing goods only) (Mussellman, 1997; EAN Australia, 1998). The respondents were categorised on the extent of use of the techniques and technologies, breadth of integration, and degree of extension of the techniques across their wider supply chain. Nine items reflecting the extent to which the EAN system had been adopted were used to classify respondents into different groups (five-point Likert scale, “not at all” to “to a very large extent”): . we receive extra information from customers (e.g. better forecast demand) as a result of implementation; . we have used implementation as an opportunity to extend the use of some techniques to internal processes; . we have extended implementation throughout the organisation and it’s supply chains; . implementation applies to finished goods as well as to internal processes; . implementation applies to finished goods, internal processes and incoming goods from suppliers;

These were combined to form a single factor variable capturing perceived contribution of the technologies to 103

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organisational performance. Content analysis of 46 articles relating to research on B2B e-commerce and supply chain management (conducted as part of the literature review) revealed that 25 (54 per cent) covered the issue of business benefits. Most common business benefits cited include: ability to connect to multiple suppliers and customers; reductions in cycle times; reductions in inventory; improved speed and quality of communication; reductions in costs; and reductions in overheads through elimination of non-value adding activities. This element of the model covers many of these areas, and draws on the evidence of the case studies in covering both operational and bottom line (or profit/revenue) related issues.

Justification of the relationships in the model Process as a determinant of capability This relationship draws on the proposition that organisations use a number of methods for determining environmental conditions to formulate supply chain management strategies in dynamic environments. The case studies further provided evidence that the companies that used methods such as benchmarking, the development of a culture for questioning business assumptions (defined in the model as stakeholder involvement), and environmental scanning indicated higher levels of organisational capability for implementation and change. There was some indication that an external focus of this nature enhanced the capability of the organisation to manage the change and implement the appropriate technologies.

Model for testing H6 In order to test H6 the model was modified by replacing the variable “extent of implementation” with another variable titled “extent of implementation of internet-based technologies”. This variable captured the extent of use of the internet for B2B transactions with customers and suppliers based on answers to four questions covering current usage (five-point Likert scale, “not at all” to “to a very large extent”): 1 Indicate the extent of usage of the internet for purchasing. 2 Indicate the extent of usage of the internet for customer service. 3 Indicate the extent of usage of the internet for e-mail. 4 Indicate the extent of usage of the internet for order fulfilment.

Process as a determinant of knowledge This relationship proposes that the process by which supply chain management strategy is formulated will have an effect on the general level of knowledge of supply chain management practices (i.e. the EAN system) within the organisation. Both sets of case studies provided evidence that organisations with extended implementations had used some or all of the elements of the “process” construct (benchmarking, assessment of competitor actions, use of consultants and/or internal resources to challenge business assumptions, etc.) to improve their understanding of the potential benefits, technological options, etc. available to them. The logical extension of this view is that the better informed stakeholders are of the technological options and benefits, the more capable they will be of making better decisions (i.e. challenging cognitive frameworks from within).

Conceptual model Figure 1 has a pictorial representation of the model, expressed as a path diagram (the direction of the arrows indicates theoretical causal relationships). This model proposes that “process” is a determinant of both “knowledge” and “capability”. It further indicates that “capability” is also determined by “knowledge”. “Knowledge” determines the “content” of the implementation strategy, which further is a determinant of “extent of implementation”. “Capability” is a determinant of “extent of implementation” and “performance”. “Extent of implementation” is also indicated to be a determining factor for “performance”.

Knowledge as a determinant of capability This path proposes that “knowledge” of the EAN system (and supply chain options/technologies/benefits) will determine the “capability” of an organisation to implement effectively. Again, both sets of case studies provided evidence to suggest that as understanding grew, so did the capability of the organisation to select appropriate technologies and effectively manage change. Knowledge as a determinant of content This relationship indicates that the level of knowledge of the EAN system (and supply chain management options/ technologies/benefits) will affect the planning processes, stated objectives and expectations of the organisation. Both sets of cases again indicated that this could be the case, with organisations having more knowledge indicating a more proactive approach to planning and articulating objectives.

Figure 1 Conceptual model

Content as a determinant of extent of implementation This path proposes that the planning processes, stated objectives and expectations of the organisation will have an effect on the extent of implementation of the EAN system across the supply chain. Again, the case studies provided some indication that organisations that were more proactive in their planning for implementation were more likely to implement more extensively. Some of these companies also appeared to have a more focused set of objectives and expectations. Capability as a determinant of extent of implementation This relationship indicates that extent of implementation of the EAN system will be also determined by the capability of the organisation to reengineer processes and select 104

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Volume 10 · Number 2 · 2005 · 96 –113

appropriate technologies. Both sets of cases also provided evidence of capability to implement being an important factor, both as an impediment (companies identifying a limited capability to implement) or an enabler (i.e. for those companies at a higher level of implementation).

minimum of 10 respondents per parameter. The x2 ¼ 28:113 with 11 degrees of freedom at a significance of 0.000. This statistic, however, can be sensitive to larger sample sizes, with those greater than 200 being vulnerable to over estimation of significant differences (Hair et al., 1998). In this case the sample size of 334 indicates that this result could be unreliable, and points to the need to use alternative measures of absolute fit. The goodness-of-fit index (GFI) at 0.978 is quite high and provides some confidence in the plausibility of the measurement model. At the same time the root mean square residual (RMSR) of 0.029 is low enough to provide further confidence in the absolute goodness of fit. The root mean squared error of approximation (RMSEA) provides a measure of the expected goodness of fit for the model if it were approximated for the population, and at 0.068 is found to be within the recommended range of 0.05 and 0.08. Both the Tucker Lewis index (TLI) and the normed fit index (NFI) are found to be well above the recommended level of 0.90 at 0.948 and 0.956 respectively, providing further support for the acceptance of the measurement model. The adjusted GFI (AGFI) is also well above the recommended level of 0.90 at 0.945. As such, there is a high degree of confidence provided in the parsimony of the model.

Capability as a determinant of performance This relationship follows from the arguments used for the path from “capability” to “extent of implementation”. The relationship between “capability” and “performance” implies that the level of capability required to implement results in it acting as a potential barrier to adoption (i.e. to extended implementation). Otherwise it would be difficult to explain the restricted levels of adoption in the light of a high level of perceived benefit. Extent of implementation as a determinant of performance This final path captures the proposition that more extensive implementation of the EAN system leads to more business benefits. The extent of potential benefits are highlighted in the literature (see above), and there is an underlying theme that these benefits accrue to organisations that implement more extensively. On the other hand, evidence from the case studies indicated that some companies derived significant benefits with limited implementations. This path provides a means of testing the nature of the relationship between “extent” of “implementation and performance”.

Overall model fit and integrity of the paths proposed The path parameters of the overall model are represented in Figure 3. The following goodness of Fit criteria were recorded for the full model: GFI, 0.948; AGFI, 0.905; RMSR, 0.035; RMSEA, 0.077; TLI, 0.940; NFI, 0.942; x2, 89.570; df, 30; Sig., 0.000; n, 335; x2/df, 2.986. The ratio of distinct parameters to be estimated to the size of the sample (335=25 ¼ 13:4) exceeds the recommended minimum of 10 respondents per parameter. The x ¼ 89:570 with 30 degrees of freedom at a significance of 0.000. As with the measurement model, the sample size of 335 indicates that this result could be unreliable, and points to the need to use alternative measures of absolute fit. The GFI at 0.948 is relatively high and provides further confidence in the plausibility of the overall model, particularly given its complexity. The RMSR of 0.035 is also low, and provides further confidence in the absolute goodness of fit. The RMSEA at 0.077 is found to be within the recommended

Analysis and findings Confirmatory factor analysis In order to test the integrity of the measurement model confirmatory factor analysis (CFA) was carried out (see Figure 2). The following goodness-of-fit criteria were recorded for this model: GFI, 0.978; AGFI, 0.945; RMSR, 0.029; RMSEA, 0.068; TLI, 0.948; NFI, 0.956; x2, 28.113; df, 11; Sig., 0.003; n, 334; x2/df, 2.556 (the sample size for the measurement model – 334 – is different from that used in the overall model – 335.This is due to the elimination of a multivariate outlier exceeding the recommended Mahalonobis distance from the measurement model). The ratio of distinct parameters to be estimated to the size of the sample (334=17 ¼ 19:6) exceeds the recommended Figure 2 Confirmatory factor analysis – measurement model

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Figure 3 Overall SEM path model for full dataset

Discussion

range of 0.05 and 0.08. Both the TL) and the NFI are found to be well above the recommended level of 0.90 at 0.940 and 0.942. The AGFI is also above the recommended level of 0.90 at 0.905.

H1 The structural model expresses the relationship between “knowledge” (as captured by the three constructs used above) and “extent of implementation” as being an indirect one comprising two paths. The first of these is via “capability”, indicating that the extent of knowledge of the EAN system

Analysis of direct and indirect effects Table I details the standardized direct and indirect effects measured. Table I Direct and indirect effects IV

DV

Process

Capability Content Extent of implementation Notes:

denotes significance at p , 0:05,





Indirect





Knowledge Capability Content Extent of implementation Performance Capability Content Extent of implementation Performance Extent of implementation Performance Extent of implementation Performance Performance

Knowledge




Direct 0.80 0.37






0.54 0.71

0.77

0.67



0.67

0.88

0.58

0.49

0.83

0.87



20.16

denotes significance at p , 0:01

106

2 0.130 0.03 2 0.004

Total 0.80

0.90

0.71

0.77

0.67

0.67

0.88

0.58

0.49

0.83

0.74

0.03 20.004 20.16

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Supply Chain Management: An International Journal

Damien Power

Volume 10 · Number 2 · 2005 · 96 –113

will be a determinant of capability to implement, thus ultimately affecting the extent of implementation. The second is via “content”, indicating that levels of “knowledge” will be a determinant of the content of an organisation’s strategic objectives and plans when implementing, and thus influence extent of implementation. A strong and highly significant (0.58 at p , 0:01) indirect effect is recorded between the “knowledge” construct and “extent of implementation” via these paths. In the context of this model this provides evidence to the effect that the null hypothesis should be rejected, and that the extent of implementation is not only positively associated with: the level of understanding of the range of options; potential benefits; and the range of applications available for implementation, but that it is determined by these factors to a significant extent.

The direct effect on “capability” recorded here is moderately strong and significant (0.37 at p , 0:01). The second is via an indirect effect on “capability” via the “knowledge” construct. In this case the proposition is that the process of EAN system strategy formulation determines the level of “knowledge”, which in turn increases “capability” to implement. The direct effect on “knowledge” observed is very strong and significant (0.80 at p , 0:01), while the indirect effect on “capability” recorded is strong and significant (0.57 at p , 0:01). The indirect effect on each of the two constructs making up “capability” (strategic reengineering and investment profile) via these two paths is strong and significant in both cases (0.69 at p , 0:01 and 0.54 at p , 0:01 respectively). The subsequent direct effect of “capability” on “extent of implementation” is also very strong and significant (0.83 at p , 0:01). The third path is via “knowledge” and “content” with the direct effect of “knowledge” on “content” being very strong (0.88 at p , 0:01), and there being no significant effect recorded between “content” and “extent of implementation” (as described in relation to H2a above). The relationships described in the model provide significant further evidence for the proposition that the “process” construct plays an important role in determining the extent to which organisations implement the EAN system. In the context of the Sanchez and Heene (1997) model, these relationships indicate a focus on the use of the elements of the “process” construct to promote effective resource deployment in order to enable the organisation to:

H2 Each sub-hypothesis will be discussed in turn, and the “umbrella” hypothesis proposed above will then be examined in light of the structural model. H2a There was no significant causal path found linking “content to extent of implementation”. At the same time, however, a strong and significant correlation was recorded between these two variables (0.645 at p , 0:01). This is indicative of the fact that perhaps content of strategic objectives and plans is associated with extent of implementation by way of its association with other factors such as the construct “knowledge”. The indirect effect of “knowledge on extent of implementation”, through the effect it has on both “capability” and “content”, is both strong and significant (0.58 at p , 0:01). In this sense, “content” could be seen as a hygiene factor in terms of its effect on the extent to which companies implement the EAN system. As a result of higher levels of “knowledge” of the EAN system, companies are more likely to formulate specific objectives and expectations, and at the same time formulate strategic plans for implementation. The indications are, however, that this process has little or no impact on the extent to which they implement, but is rather the outcome of the other factors preceding it in the model (i.e. “process” of strategy formulation and “knowledge” of the EAN system). This does not mean to say that the formulation of objectives and plans is not important, but rather that the plans and objectives of themselves will have little impact on extent of implementation. It was apparent from some of the cases that the planning process (and by extension the development of objectives and expectations) was “evolutionary” rather than “revolutionary”. The finding that the “content” construct has little or no impact on “extent of implementation”, and that it appears to be heavily determined by growth in “knowledge”, provides some further evidence to support this. This finding provides support for the null hypothesis being accepted.

. . . build up qualitatively new stocks of resources in anticipation of environmental changes in the future (Sanchez and Heene, 1997, p. 34).

In this case, not only is “process” (the means by which an organisation formulates its strategic logic) significantly associated with “extent of implementation”, but it could also be said to be (within the constraints of the model proposed) a significant determinant. As such it would appear to provide evidence for rejection of the null hypothesis. Further discussion of H2 in light of sub-hypotheses and the structural model The literature emphasises the strategic nature of supply chain management initiatives, and the results observed for the two sub-hypotheses confirm this. The findings indicate that the “process” of formulating an organisation’s strategic logic will be a strong determinant of both the level of “knowledge” of the EAN system, and the “capability” to implement it. At the same time, “knowledge” has a strong effect on the “content” of plans, objectives and expectations from implementation, but this “content” has little or no impact on “extent of implementation”. This is despite the fact that “content” is strongly associated with “extent of implementation”, indicating that of the two sets of relationships hypothesised (i.e. “process” with “extent” and “content” with “extent”), “process” is the determining factor. “Content”, on the other hand, can be perhaps seen as a requirement rather than a determinant. In this sense it can be important to define “extent of implementation”, but will not determine what actually happens. If the strategic “mindset” of an organisation can be expressed in terms of these two constructs, this analysis provides significant evidence to support the proposition that “process” will be the more likely determinant of implementation, while the “content” construct represents a blueprint of why and how implementation may be achieved.

H2b The standardised total effect of “process” on “extent of implementation” is found to be both strong and highly significant (0.77 at p , 0:01). This effect is delivered via three separate paths. The first of these is by way of having a direct effect on the “capability” of the organisation to implement, and as such reflects the need for organisations to be able to deploy resources to meet changing environmental conditions. 107

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H3 and H4 “Capability” is observed to be a significant and strong determinant of “extent of implementation” (0.832 at p , 0:01), and as such further confirms the importance of the ability to both strategically reengineer business processes as a determinant of extended implementation, and the significance of appropriate investment profiles. “Capability” is also observed to be a strong and significant determinant of “performance” (0.872 at p , 0:01), in this case again pointing to the importance of being able to manage change effectively, and at the same time maintaining an appropriate and balanced investment profile to ensure performance improvement. The implementation of B2B e-commerce methodologies within (and between) organisations will have repercussions across many different parts of the organisation. One inevitable outcome will be that many of the procedures, rules and activities that have underpinned operations will either need to be changed, or will need to be accommodated within the implementation. This is a complicated and challenging prospect for even the most adept and sophisticated organisations. Put this in the context of many interacting organisations within complex supply chains, and it would not be unreasonable to expect that the degree of difficulty will be increased by a substantial factor. In this sense, it is not hard to see why capability to implement would be an important and significant determinant of both extent of implementation, and ultimately improved organisational performance. The evidence from the model indicates that the null hypothesis can be rejected for both H3 and H4.

common determinants. In practical terms, this could be interpreted to mean that extensive implementation unsupported by a valid strategic formulation process, sufficient knowledge of technologies, applications and benefits, and the capability to implement, will not be sufficient to guarantee improved performance. The importance of “capability”, “process” and “knowledge” in the model is consistent with the low adoption rates of established technologies (such as EDI), despite many benefits being proposed. Many organisations find it difficult to be able to combine these three factors and produce a coordinated and coherent implementation strategy (Moller, 2000a, b). In this sense the relationship between these three factors and both “performance” and “extent of implementation” represents an impediment to extended adoption. The spotlight, therefore, moves from the EAN system per se (and the technologies), and onto the organisation itself. In essence this result points to both the potential benefits of the technology (in this case the EAN system), and to the inherent limitations of these established technologies. Such technology is, after all, simply a set of tools and applications. The implications go beyond the individual enterprise, and to the heart to improving the operations of supply chains through the application of ebusiness enabling technologies. In terms of Forrester’s (1958, 1961) model of industrial dynamics based on information feedback systems, delays in the system (the supply chain) can be amplified depending on the policy responses of individual trading partners. As such, the application of improved IT will provide a potential source of improvement, but cannot be expected to act as a technological panacea eradicating all sources of inefficiency. The solution appears far more likely to originate within the individual organisations, with the efficiency and effectiveness of the supply chain more a function of the sum total of capabilities of the trading partners. As such, the assessment of the evidence indicates that the null hypothesis should be accepted.

H5 The structural model expresses the relationship between “extent of implementation” and “performance” (as captured by the two factor variables “operational outcomes” and “bottom-line outcomes”) as being a direct one, with “extent of implementation” determining “performance”. In the context of the model the path from “extent of implementation” to “performance” is weak and not significant. On the other hand, there is a strong and significant correlation recorded between these two variables (0.590 at p , 0:01), indicating that although the two variables are highly associated, “extent of implementation” does not have a determining effect on “performance”. In this model, the true determinants of “performance” are “capability” (directly), and “process” and “knowledge” (indirectly). The direct effect of “capability” on “performance” is very strong and significant (0.87 at p , 0:01), while the indirect effects of “process” and “knowledge” are also strong and significant (0.67 at p , 0:01 and 0.49 at p , 0:01 respectively). “Capability” is also observed to have a very strong determining effect on “extent of implementation” (0.83 at p , 0:01), while “process” and “knowledge” are also strong and significant indirect determinants (0.77 at p , 0:01 and 0.58 at p , 0:01 respectively). It is these shared relationships that perhaps provide some of the explanation of the relationship between “extent” of “implementation and performance”. Companies that report extensive implementation of the EAN system also appear to report higher levels of performance, but it would appear to be a mistake to conclude that one will automatically lead to the other, or that in fact one determines the other. The nature of the relationship (in this model) is a function of the sharing of

H6 When the variable created is substituted into the structural model under the new observed variable name of “Extent of implementation of B2B using the web”, the most obvious effect on the model is to weaken the relationship between “capability” and the new “extent of implementation” construct. Figure 4 shows a comparison between the two models with the major path values detailed. The path from “capability” to “extent of implementation” in the “established technologies” model is both strong and significant, and as discussed earlier in this paper represents the need for organisations to have the necessary levels of infrastructure and ability in order to implement extensively. For the “internet technologies” model, however, this relationship no longer holds. In fact, the relationship is not just weakened, but it is both very weak and no longer significant. This effect captures the ease with which organisations are now able to start using the internet-based solutions, and supports the proposition that the adoption of internet technologies will perhaps not be subject to many of the impediments of other technologies (such as EDI). What is also important to note is that the path from “capability” to “performance” is still strong and significant, while (as with the established technologies) that from extent of implementation of B2B using the web is weak and non-significant. The implication is that though many more organisations will find 108

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Damien Power

Volume 10 · Number 2 · 2005 · 96 –113

Figure 4 Comparison of structural models for extent of implementation of established and emerging technologies

performance”. At the same time, “knowledge” has a strong effect on the “content” of plans, objectives and expectations from implementation, but this “content” has little or no direct impact on “extent of implementation”. This is despite the fact that “content” is strongly associated with “extent of implementation”, indicating that of the three sets of relationships hypothesised (i.e. “process” with “extent”, “capability” with “extent”, and “content” with “extent”), “process” and “capability” are the determining factors. The structural model provides evidence that “process” and “capability” represent the ability to implement, while “content” represents a blueprint of how this may be achieved. The nature of the relationship between “extent of implementation” and “performance” further highlights the importance of “process”, “knowledge” and “capability” for determining outcomes. In this case, “extent of implementation” is found not to be a driver of “performance”, but rather a relative through a shared set of antecedents (“process”, “knowledge” and “capability”). As such, the application of IT will provide a potential source of improvement, but cannot be expected to act as a panacea for inappropriate supply chain practices. The evidence also indicates that the adoption and use of emerging technologies (such as the internet) is not subject to the same restrictions and impediments traditionally associated with established technologies. This apparent change in the ease with which companies can access and use the technology was also found, however, not necessarily to be interpreted as enabling (of itself) substantial improvement in the efficiency and effectiveness of either individual companies, or (by

the new technologies easier to implement, they will still be faced with the same need for significant levels of “capability” in order to extract benefit through improved performance. This finding provides further support for the proposition that the internet does not of itself offer a “technological silver bullet”, and has some support in the recent literature (Goodman, 2000; Puttre, 1997; Barber, 1997; Jutla et al., 1999a, b). These results indicate that many of the same characteristics identified for the adoption and use of existing technologies will not hold true for emerging technologies such as the internet. As such, in this case the null hypothesis could be rejected. It is, however, important to note that some critical characteristics for improving performance through the use of these enabling technologies appear unchanged. Irrespective of the technology being adopted, it’s ease of use, simplicity of operation, or basis in open and easily transferable standards, the need for organisations to have sound processes for strategy formulation and implementation appears to remain undiminished.

Conclusions General The literature emphasises the strategic nature of supply chain management initiatives, and the results observed provide some confirmation of this. The “process” of formulating an organisation’s strategic logic will be a strong determinant of both the level of “knowledge” of the EAN system, and the “capability” to implement it. “Capability” is seen to be a strong determinant of both “extent” of “implementation and 109

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Damien Power

Volume 10 · Number 2 · 2005 · 96 –113

extension) supply chains generally. Comparisons using the structural model indicated that emerging technologies lower the burden of “capability” for implementation, but not for “performance”. The practical implication of this finding is that organisations will find the technology easier to implement and to use, but that this will not necessarily mean that they will improve performance as a result. The model suggests that “performance” will still be a function of the intangible drivers represented by the “process”, “capability” and “knowledge” constructs. Companies may find that it is easier to become active in the use of the technology, but that they may be disappointed if they expect that significant business benefits will be realised as a result. These will be determined by effective strategy formulation, a clear understanding and knowledge of the technologies, appropriate application, and prudent change management. Michael Porter captures the gist of this issue when he states:

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The great paradox of the internet is that its very benefits – making information widely available, reducing the difficulty of purchasing, marketing and distribution, allowing buyers and sellers to find and transact business with one another more easily – also make it more difficult for companies to capture those benefits as profits (Porter, 2001, p. 66).

Limitations and future research directions This research has been conducted in Australia, and restricted to the membership of the EAN organisation. This membership is largely representative of the fast-moving consumer goods (FMCG) industry. Whether such results would be consistent in other countries and industries would need to be verified through further research. It would be particularly useful to conduct a multi-country and/or multiindustry comparison to test the influence of moderating factors such as national culture and industry characteristics. In this study the importance of strategy formulation processes combined with the capability of the organisation to implement and manage change were found to have a significant influence on technology related outcomes. It would be useful as a follow-up project to test some specific theories in the strategic management literature. In particular, the resource based view of the firm could be incorporated into a similar model to test for the influence this theoretical perspective could have on determining technology choice and potential outcomes.

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Strategic decisions in supply-chain intelligence using knowledge management: an analytic-network-process framework Mahesh S. Raisinghani Texas Woman’s University, School of Management, Denton, Texas, USA, and

Laura L. Meade M.J. Neeley School of Business, Texas Christian University, Fort Worth, Texas, USA Abstract Purpose – To investigate the linkage between organization performance criteria and the dimensions of agility, e-supply-chain drivers and knowledge management. Design/methodology/approach – The analytic network process is applied as the research methodology in the context of executive decisions that include qualitative and quantitative attributes. The decision model is presented, along with a case study with an e-supply chain of a global telecommunications company. Findings – The study develops a framework for measuring the relative importance of a particular dimension based on the application of theoretical concepts from the information systems and management science literature to the digital, knowledge economy. Since contextual factors play a critical role in the design of effective knowledge-management (KM) systems, technical and process solutions need to be customized to fit the organization performance criteria, dimensions of agility and supply chain drivers. Research limitations/implications – The model presented is dependent on the perceptual weightings provided by the decision-maker and the generalizability of findings based on our model to other organizations may be limited. Practical implications – This paper addresses the need for a strategic decision-making tool to assist management in determining which knowledge management construct is most beneficial in the development of an agile supply chain. Originality/value – This paper fulfils an identified information need and offers practical help in a dynamic and competitive environment by providing a decision model that assists in determining which construct of KM is most important based on an organization’s performance criteria, dimensions of agility and supply-chain drivers. Keywords Supply chain management, Knowledge management, Organizational performance Paper type Research paper

more holistic, systemic approach to knowledge. It is not simply a “tool” or “resource” so much as a social construct. It is a reciprocal, interdependent process of learning arising from knowledge transfer (KT) and information flow and communication – a socio-technical perspective that amalgamates the “dualism” of people and technology[1]. During his keynote speech at the Information Resources Management Association’s (IRMA) annual 1998 international conference in Boston, MA, Dr N. Venkatraman from Massachusetts Institute[1] of Technology’s Sloan School of Management discussed how companies manage their knowledge assets and how organizations moved from the industrial economy to the knowledge economy. This development led to a shift in the business environment and introduced the new concepts from the knowledge economy as illustrated by the knowledge cycle in Figure 1. The key is to synthesize the intellectual capital from the tacit and explicit knowledge base of the human mind and the information augmentation provided by applied technologies such as data mining and intelligent software agents. This study focuses on investigating the linkage between the various dimensions of agility, supply chain costs and KM by using the analytic network process in a global telecommunications organization. The overarching strategic organization

We now know that the source of wealth is something specifically human: knowledge. If we apply knowledge to tasks we already know how to do, we call it productivity. If we apply knowledge to tasks that are new and different, we call it innovation. Only knowledge allows us to achieve those two goals (Peter F. Drucker).

Introduction In a knowledge-based industrial economy, logistics play an increasingly important strategic role for organizations that strive to keep pace with market changes and supply chain integration. Knowledge management (KM) has been a major topic for management academicians and practitioners alike in the 1990s. A growing number of studies have called for a The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm

Supply Chain Management: An International Journal 10/2 (2005) 114– 121 q Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/13598540510589188]

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Figure 1 The knowledge cycle

the theoretical framework. In the following section, we outline the research methodology based on the analytic network process and describe each step in the process used for making optimal decisions. A case study is then presented which utilizes the framework for a global e-supply chain. The final section presents some future research directions and concludes the paper.

Research constructs and theoretical framework The concept of KM concerns the creation of structures that combine the most advanced elements of technological resources and the indispensable input of human response and decision-making. Duhon (1998) defines KM as “a combination of technology supporting a strategy for sharing and using both the brainpower resident within an organization’s employees and internal and external information found in ‘information containers’”. The goal of KM is to simultaneously manage data, information, and explicit knowledge while leveraging the information resident in people’s heads through a combination of technology and management practices (Duhon, 1998). Documentum’s (a document management company; www. documentum.com/) vice president Larry Warnock describes KM as the “utilization of intellectual capital”. Intellectual capital, or knowledge, is the source of innovation that ultimately allows companies to focus on their individual customer. Documentum uses a term called “knowledge-chain management” to define the way knowledge is created, shared, and leveraged in context of a business process. The supply chain is the business process by which materials and information move through an organization to deliver the ultimate product to a customer. KM as operationalized in this paper “caters to the critical issues of organizational adoption, survival, and competence in the face of increasingly discontinuous environmental change. Essentially it embodies an organizational process that seeks synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings” (Malhotra, 2000). This definition not only recognizes the discontinuous environment but also the importance of both techno-centric and socio-centric approaches. The traditional view of KM primarily relies on the prepackaged or “taken for granted” interpretation of the knowledge. Such knowledge is generally static and does not encourage the generation of multiple and contradictory viewpoints in a highly dynamic and everchanging environment. Beijerse (1999) identifies the following demands on organizations in a knowledge-based economy: . an increasing complexity of products and processes; . a growing reservoir of relevant knowledge, both technical and non-technical; . increasing competition in an economy with shorter product life cycles, in which case learning processes have to be quicker; . an increased focus on the core competencies of the firm which have to be coordinated, but letting go of less relevant tasks; and . companies will increasingly have the work done by a flexible/changing workforce, which makes holding on to knowledge and transferring knowledge all the more difficult.

performance criteria of cost, time, flexibility and quality serve as drivers for this study. The internet and e-business have directly impacted supply chain management. With the increasing growth of businessto-business and business-to-consumer avenues the traditional supply chain has been expanded. Business-to- business via ecommerce will reach $5.7 trillion by the end of 2004 or 29 percent of the dollar value of commercial transactions (Bermudez et al., 2000). Supply chain solutions participants need to leverage their understanding of the physical process combined with the latest technology solutions to provide the necessary visibility and connectivity in the supply chain. The e-supply chain uses internet-based computing and communications to execute both front-end and back-end business processes. It has emerged as a key enabler in supply chain integration (Lee and Whang, 2001). The e-supply chain needs to be able to meet customer’s needs as efficiently and effectively as possible. Furthermore, as the internet continues to become a major player in supply chain planning, the enterprise will need increasingly agile practices to rapidly evaluate new business opportunities and identify the e-supply chain that offers that greatest potential (Sadeh et al., 2003) This paper provides a decision model which assists in determining which construct of KM is most important based on an organization’s performance criteria, dimensions of agility and supply chain drivers. The main issue with KM is determining how executives get the insight they need to run their business and how they formalize that insight. Making use of diverse and changing resources has two main objectives. One, in order to substantially benefit from the available technology, the decision maker should be able to efficiently locate and access the needed information/resources in a timely manner. So to begin with there is the goal of providing the library of information and materials, or “knowledge”. This array of knowledge is by no means static, so maintenance of the system, involving reorganization procedures and continual development of information sources, is necessary. The other essential objective relies more on the human capabilities of analysis and decision-making. The knowledge base must be combined with the ability to effectively and efficiently filter the tremendous amount of data and information so that what is left is truly meaningful packets of knowledge. Software and machines can accomplish this to a point, but the human input and control in the system is the critical component. This, too, should be a continuous and ongoing process. The intent here is not to examine the technical aspects, but to consider the cognitive process needed to develop a useful framework in which to manage our store of knowledge. The paper is organized as follows: the first section describes the key constructs used to build our framework and illustrates 115

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Next we describe the supply chain taxonomy. A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request. The supply chain not only includes the manufacturer and suppliers, but also transporters, warehouses, retailers, and customers themselves (Fawcett and Clinton, 1997; Simchi-Levi et al., 2000). Some of the functions included in the supply chain are new product development, marketing, operations, distribution, finance, and customer service. If the supply chain process is looked at from a cycle view, all supply chain processes can be broken down into the following four process cycles: customer order cycle, replenishment cycle, manufacturing cycle and procurement cycle (Coleman et al., 2000). The analytic network process (ANP) is capable of taking into consideration multiple dimensions of information into the analysis, a powerful and necessary characteristic for any strategic decision. Figure 2 developed by the authors as part of the analytic network process (ANP) illustrates the KM and supply chain initiatives research model, and serves as the framework for our research study. The overall question being posed in this paper is “what dimension of KM is most important in developing an agile e-supply chain?” The factors that impact this decision are based on organizational performance criteria, dimensions of agility, and dimensions of costs in the supply chain. The organizational-performance criteria are straightforward and consist of traditional strategic organizational metrics such as time, quality, cost, and flexibility (Kleindorfer and Partovi, 1990; Sarkis, 1998). The following sections will describe each the other three dimensions in the model in greater detail.

efficiently and with agility. In order to be agile; able to respond to unanticipated change, the supply chain must seek to address four main principles: cooperate to enhance competitiveness; enrich the customer; master change and uncertainty; and leverage the impact of people and information (Goldman et al., 1995). Cooperate to enhance competitiveness The specific benefits of this cooperation include both interand intra-enterprise benefits as follows: . decrease of product development costs, time to market, and risk; . ethic of trust is built and maintained in order for cooperation to succeed; . acceleration of technology transfer and an increase in resource availability; and . able to focus on the processes which human and technological resources are best suited. In order to maximize the potential of this principle, the enterprise needs to utilize existing resources regardless of location in order to bring the product to the consumes as cost effectively and rapidly as possible. Enrich the customer The products of the enterprise need to be viewed by the customer as solutions to a problem. Building long-term stable relationships are based on selling solutions that involve products, information, and services. A relationship between producer and customer will evolve as changes in the environment occur. Products will be able to be designed by the end user, as well as upgraded and reconfigured rather than replaced.

Dimensions of agility In order to maintain that the strategy selected relates to the desire to be an agile supply chain, the dimensions of agility are paramount. Due to the pace at which business is conducted the supply chain needs to be able to respond quickly,

Master change and uncertainty The supply chain needs to be organized so that it can thrive on change and uncertainty. The structure needs to be flexible to allow for rapid reconfiguration of human and physical

Figure 2 The supply chain and KM dimensions model

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resources. The following are ways in which to create an environment that embraces change: . maintain a skilled workforce; . give workers the resources and the authority to respond to changing market opportunities; . the structure needs to support the linkage of necessary resources within the enterprise as well as between enterprises; and . foster an entrepreneurial company culture.

.

.

systematic problem solving – requires a mindset, disciplined in both reductionism and holistic thinking, attentive to details, and willing to push beyond the obvious to assess underlying causes; and learning from past experiences – reviews a company’s successes and failures, assessing them systematically, and transferring and recording the “lessons learned” in a way that will be of maximum benefit to the organization.

Two important points regarding knowledge acquisition and creation; first, information, whether it is acquired from an external or an internal source is subject to perceptual filters (norms, values, and procedures) that influence what information the organization listens to and ultimately accepts. Second, knowledge acquisition and creation systemically is guided by a firm’s core competency strategy. For organizations to meet their strategic objectives, knowledge acquired from multiple sources must selforganize around the firm’s key business processes and knowledge domains modeled in a firm’s value chain (Morse, 2000). The principal enabling technologies are data mining, pattern matching, automatic inference, concurrent engineering, process analysis, just-in-time learning and business research (Alavi and Leidner, 2001; Nissen et al., 2000).

Leveraging the impact of people and information Finally, the mechanism, which utilizes cooperative relationships to enrich the customer, is based on the dimension of leveraging the impact of people and information. People and information are the agile enterprise’s most valued resources. Motivation in employees can be enhanced by distributing decision-making authority. An agile enterprise sells its ability to convert the knowledge, skills, and information embodied in its personnel into solutions for individual customers. Dimensions of costs in supply chain management If an enterprise is to exploit the advantages of setting up the supply chain to its full potential, an understanding of the key differences between using the internet and other channels for the flow of information, products, and funds must be attained. Four drivers of the supply chain performance are critical to determining a supply chain’s responsiveness and efficiency. These drivers are: inventory; transportation; facilities; and information (Chopra and Meindl, 2001). Inventory includes all raw materials, work in process and finished goods. Transportation is the moving of inventory from point to point in the supply chain and can encompass various modes. Facilities are the places in the supply chain network where inventory is stored, assembled, or fabricated. Finally, information is the data and analysis regarding inventory, transportation, facilities, and customers throughout the supply chain (Cotey, 2000; Fawcett and Clinton, 1997; Malhotra, 2000).

Knowledge storage and retrieval In order to store and later to retrieve knowledge, an organization must first determine what is important to retain and how best to retain it. Semantic and episodic knowledge about customers, projects, competition, and industry should be structured and stored so the system can find and deliver it quickly and correctly. When structuring knowledge, it is important to consider how the information will be retrieved by different groups of people. Functional and effective knowledge storage systems allow categorization around learning needs, work objectives, user expertise, use of the knowledge, and location (where the information is stored). However, knowledge is not always present in its optimal form, is not available when needed, and is not present where the work activity is carried out. Additionally, knowledge content is often not complete, not current, and not uniform. Some of the key enabling technologies are multimedia databases, query languages, text index, search engines, data mining and storage servers/advanced computer storage technology and document management technology that allow knowledge of an organization’s past, often dispersed among a variety of retention facilities, to be effectively stored and made accessible (Alavi and Leidner, 2001).

Dimensions of KM KM focuses on understanding how knowledge is acquired, created, stored and utilized within an organization. Organizational KM processes that are grounded in the sociology of knowledge and based on the view of organizations as social collectives and “knowledge systems” are as follows: creation; storage/retrieval; transfer; and application (Holzner and Marx, 1979; Pentland, 1995; Morse, 2000; Alavi and Leidner, 2001). Learning occurs when individuals create new knowledge by combining explicit knowledge accessed from KM systems, with their prior knowledge, normally in tacit form. These four processes enable end-users, while interacting with their KM system, to generate and share knowledge.

KT Alavi and Leidner (2001) have conceptualized KT/flows in terms of five elements: perceived value of the source unit’s knowledge; motivational disposition of the source (i.e. their willingness to share knowledge); existence and richness of transmission channels; motivational disposition of the receiving unit (i.e. their willingness to acquire knowledge from the source); and the absorptive capacity (i.e. ability to acquire, assimilate, and use knowledge) of the receiving unit. KT from an intra and/or inter-firm perspective involves the mechanical, electronic, and interpersonal movement of information and knowledge both intentionally/formally and unintentionally/informally. Organizations intentionally

Knowledge creation Organizational knowledge creation is generative, where knowledge is actively constructed from information previously stored and new information drawn from the environment. Organizations create new knowledge through social and collaborative processes: . action learning – involves working on problems, focusing on the learning acquired, and actually implementing solutions; 117

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transfer knowledge by written communications, training, internal conferences, internal publications (i.e. within the firm and/or within the supply chain), job rotation and job transfer, and mentoring. Organizations unintentionally transfer knowledge as a function of unplanned human interaction, i.e. job rotation, stories and myths, task forces, and informal networks. The various levels at which transfer occurs are transfer of knowledge between individuals, from individuals to explicit sources, from individuals to groups/SCM partners, between/across groups/SCM partners, and from the group/ SCM partner/s to the organization (Alavi and Leidner, 2001). Workflow systems, groupware, database, GDSS, video teleconferencing, electronic bulletin boards, discussion forums, knowledge directories, list -servers, and graphics applications are some of the key enabling technologies.

directions of the arcs signify dependence. Arcs emanate from a controlling attribute to other attributes that may influence it. The ANP approach is capable of handling interdependence among elements by obtaining the composite weights through the development of a “super-matrix”. The interdependence in this model is between the dimension of costs in SCM and the dimensions of KM. Overall, there are six major steps in the ANP process and these six steps will be discussed in conjunction with the case study in the following section: 1 develop a decision network hierarchy showing the relationships among decision factors (Figure 2); 2 elicit pair-wise comparisons among the factors influencing the decision; 3 calculate relative-importance-weight vectors of the factors; 4 form a super-matrix (i.e. a two-dimensional matrix composed from the relative-importance-weight vectors) and normalize this super-matrix, so that the numbers in every column sum to one; 5 calculate converged (“stable”) weights from the normalized super-matrix; and 6 determine overall weightings of decision criteria.

Knowledge application Dramatic advances in communications and transportation, has speeded the flow and production of goods and/or services, created increasing demand for these products, and eased the task of managing globally dispersed assets. These factors have all combined to create highly- competitive global markets in which change is rapid and companies need to be quick and flexible, but able to retain benefits of both economies of scale and scope. The non-linear, radical and discontinuous changes in the competitive landscape require continual updates to the best practices archived in the knowledge database. How global organizations become aware of their intellectual resources (knowledge) and what programs they implement in order to apply and/or distribute this knowledge, to increase competitiveness, have become a key component in understanding how global companies can leverage their knowledge generating capabilities in creating new opportunities in global markets. Effective KM application promotes an integrated approach to identifying, managing, and sharing all of an enterprise’s information assets. Automatic inference expert systems, rule-based/case-based expert systems, workflow systems, workflow automation systems are the key enabling technologies for knowledge integration and application. Next we describe the research methodology and framework used in this study.

Application of the framework and a case study The framework presented in the paper was tested with a global telecommunications company, with particular emphasis on their global e-supply chain operations. ANP can be used with a single decision maker; however, to increase the validity two independent decision makers were questioned. The case study was conducted with a company that is a world leader in mobile communications and a leading supplier of mobile phones and fixed broadband and IP networks. This company has leveraged the mobility of the internet and has used it to their benefit. The two decision makers were questioned separately and their responses normalized. The following sections are the result of these interviews. The overall objective of the framework is to determine which KM construct is most influential in the current e-supply chain. Knowing this information enables management to ascertain if the supply chain is positioned appropriately to meet its strategic objectives.

Research methodology: the analytic network process

Steps 2 and 3: pair-wise comparisons and relativeimportance-weight vectors Eliciting preferences of various criteria and dimensions requires a series of pair-wise comparisons where the decision maker will compare two components at a time with respect to a “control” criterion. In ANP, pair-wise comparisons of the elements in each level are conducted with respect to their relative importance towards their control criterion (Pentland, 1995). An example of the pair-wise comparison matrix is shown in Table I. The decision maker is asked a series of comparison questions and the weightings are then obtained. For this matrix, an example question for the decision maker is: “In terms of inventory costs what is the relative importance of each dimensions of knowledge management?” The dimensions of knowledge management are KC (knowledge creation), KS (knowledge storage/ retrieval), KT (knowledge transfer) and KA (knowledge application).

The research methodology used in this paper is an intuitive approach utilizing quantitative, qualitative, tangible and intangible factors pertaining to the decision of which KM construct is the most important for a given enterprise’s esupply chain, based on their organization’s performance criteria, the dimensions of agility and the supply chain drivers. The ANP is a general form of the analytic hierarchy process (AHP) (Saaty, 1996) for decision structuring and decision analysis that was first introduced by Saaty (Holzner and Marx, 1979) (see Meade and Sarkis (1999) for an example application and brief review of other ANP research). ANP allows for a set of complex issues that have an impact on an overall objective to be compared with the importance of each issue relative to its impact on the solution of the problem. As is depicted in Figure 2, the network structure of ANP is defined graphically with two-way arrows (or arcs), which represent interdependencies among clusters or groupings, or if within the same level of analysis, a looped arc. The 118

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the relative importance weight for each KM construct. The construct with the highest value will be the “most important” based on the decision makers’ criteria and strategy selected. Therefore, based on the type of strategy being pursued by the enterprise and the importance of their supply chain drivers, the dominant KM construct can be determined. This can then be compared to the overall KM strategy such as codification vs. personalization, and if necessary, the appropriate corrective action taken to align the intent with the implementation of KM strategy. The selection of the dominant KM factor is determined by the greatest value for the relative importance weight each alternative. In this case we have four alternative KM factors. The Relative importance weight, Ri is defined by:

Table I Pair-wise comparison matrix for inventory costs and dimensions of knowledge management and relative importance weights

Inventory costs

KC

KS

KT

KA

GMean

Importance weights (Evector)

KC KS KT KA

1.00 0.25 3.00 3.00

4.00 1.00 5.00 1.00

0.33 0.20 1.00 3.00

0.33 1.00 0.33 1.00

0.816 0.473 1.495 1.732 4.517

0.181 0.105 0.331 0.383 1.000

Super-matrix ANP uses the formation of a super-matrix to allow for the resolution of the effects of the interdependence that exists between the elements of the system. The super-matrix is a partitioned matrix, where each sub-matrix is composed of a set of relationships between two levels in the graphical model.

Ri ¼

XXX PC w SC4w AD4xw KM i4xw ; w

x

i

where: PC ¼ performance criteria (cost, time, flexibility, and quality of the e-supply chain); SC ¼ e – supply chain costs (information, inventory, facility and transportation); AD ¼ agile dimension of the e-supply chain; and KM ¼ dimensions of KM. The calculations give the following results: KC ¼ 0:26; KS ¼ 0:132; KT ¼ 0:441; KA ¼ 0:328 Based on these results, it appears KT is the dimension of KM that has the most impact on the e-supply chain at the case company. Knowing this result the company is able to make decisions that support KT and channel resources and time into ensuring its success.

Super-matrix formation and final relative importance weight calculation ANP uses the formation of a super-matrix to allow for the resolution of the effects of the interdependence that exists between the clusters within the decision network hierarchy. The super-matrix is a partitioned matrix, where each submatrix is composed of a set of relationships between two clusters in the graphical model. In our model the interdependence exits between the dimensions of costs in supply chain management and the dimensions of KM. Table II shows the super-matrix before convergence.

Conclusion

Calculate converged weights The next step with the super-matrix evaluation is to determine the final relative importance weights of each of the alternatives. To complete this step and help guarantee convergence, the columns of the super-matrix must be “column stochastic”. That is, the weights of each column for the super-matrix need to sum to 1. For convergence to a final set of weights, we raise the normalized (column stochastic) super-matrix to a large power until stabilization of the weights occurs (see Table III).

This paper has addressed the need for a strategic decision making tool to assist management in determining which KM construct is most beneficial in the development of an agile supply chain. Obviously the end result will differ based on the responses of the decision maker. The ANP process of eliciting information and showing the various relationships requires that management be familiar with the issue and to think of the problem in systemic and inter-relational terms. The actual process of going through the decision will help management learn of the various issues related to strategic decisions. The process and model are valuable knowledge and learning tools, not just a mechanism to support a final decision. The model is also flexible enough to incorporate additional criteria with little difficulty, as required by the dynamic and competitive environment and organizational structure.

Calculate relative importance weight for each KM construct The sixth and last step in the ANP process is to take the final results of the converged super-matrix and the eigenvector values from the earlier pair-wise comparisons and calculate Table II The super-matrix before convergence Super-matrix Inform. Inv. costs Facility Transport KC KS KT KA

Inform.

Inv. costs

Facility

Transport

KC

KS

KT

KA

0 0 0 0 0.250 0.093 0.432 0.222

0 0 0 0 0.181 0.105 0.331 0.383

0 0 0 0 0.196 0.093 0.426 0.285

0 0 0 0 0.219 0.171 0.268 0.342

0.654 0.187 0.036 0.123 0 0 0 0

0.688 0.145 0.033 0.135 0 0 0 0

0.181 0.105 0.331 0.383 0 0 0 0

0.648 0.237 0.031 0.084 0 0 0 0

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Table III The super-matrix after convergence Super-matrix Inform. Inv. costs Facility Transport KC KS KT KA

Inform.

Inv. costs

Facility

Transport

KC

KS

KT

KA

0 0 0 0 0.224 0.114 0.380 0.283

0 0 0 0 0.224 0.114 0.380 0.283

0 0 0 0 0.224 0.114 0.380 0.283

0 0 0 0 0.224 0.114 0.380 0.283

0.477 0.165 0.146 0.212 0 0 0 0

0.477 0.165 0.146 0.212 0 0 0 0

0.477 0.165 0.146 0.212 0 0 0 0

0.477 0.165 0.146 0.212 0 0 0 0

structures that combine the most advanced elements of technological resources and the indispensable input of human response and decision-making. The challenge of managing these complex structures has tremendous potential from either the practical, productive viewpoint or the human growth perspective. In a way, the development of a “knowledge entity” seems to be much like the education of a human being. Both have growing, changing, and unpredictable potential for innovation, each in their own way. Since contextual factors play a critical role in the design of effective KM systems, technical and process solutions need to be customized to fit the organization performance criteria, dimensions of agility and supply chain drivers.

There are some limitations of the model that we have presented. One is the knowledge of the decision maker. The decision-maker provides the values for the pair-wise comparisons and therefore, the model is very dependent on the perceptual weightings provided by the decision-maker. Using several decision makers from the same organization and averaging their responses can mitigate this risk. The decisionmaker set needs to include someone in the organization who understands the strategic level of the logistics process and the implications for their company. Hence in this study, we collected data from two decision-makers from the same organization independently. Second, KM is not just a technology project. KM relies on organizational structures and culture to meet its goals. Therefore, there is a very heavy dependency on the specific organization or at least the specific type of organization, where the KM initiative is being implemented. Thus the generalizability of findings based on our model to other organizations may be limited; however, the methodology is transferable.

Note 1 Source: e-mail communication from Dr Elayne Coakes, Westminster Business School, London.

Future research References

The significance of this study is the development of metrics for measuring the relative importance of a particular dimension based on the application of theoretical concepts from the information systems and management science literature to the modern knowledge economy. It embraces a multidisciplinary and interdisciplinary perspective on the challenge of KM in the context of supply chain strategy by drawing upon perspectives from the domains of strategy, information systems, management science, organizational behavior and organizational development. Future research might focus on how organizations share stories of their practice, field, or interest area. Using narrative inquiry, micro-perspective questions such as “tell me a story about how a client was successful with a KM initiative” can lead to revealing narratives that recount the practices, cultural norms, political obstacles, and other perspectives for how organizations are struggling with KM-related problems. At the macro-perspective level, the subjects can be asked to share their perspectives of the changing business landscape, including shifts in market trends, economic principles, and social context. People need to connect with other people; to hear the “ring of truth” that has been proven to guide decision-making and learning more reliably and more commonly than traditional IT-approaches to KM. This study is intended to raise the level of intellectual curiosity about the link between KM and global supply chain drivers in the digital economy. The concept of KM in the context of an agile supply chain suggests the creation of

Alavi, M. and Leidner, D.E. (2001), “Knowledge management and knowledge management systems: conceptual foundations and research issues”, MIS Quarterly Review, Vol. 25 No. 1, pp. 107-36. Beijerse, R.P. (1999), “Questions in knowledge management: defining and conceptualizing a phenomenon”, Journal of Knowledge Management, Vol. 3 No. 2. Bermudez, J., Kraus, B., O’Brien, D., Parker, B. and Lapide, L. (2000), The Issue: Is B2B Commerce Hype or Revolution?, AMR special report on e-commerce, AMR Research, Inc., Boston, MA. Chopra, S. and Meindl, P. (2001), Supply Chain Management: Strategy, Planning, and Operation, Prentice-Hall, Englewood Cliffs, NJ. Coleman, P., Barret, B. and Austrian, B. (2000), E-Logistics: The Back Office of the New Economy, Bank of America Securities equity research report, Bank of America Securities, New York, NY. Cotey, D.R. (2000), “Knowledge enterprises and the future of e-business”, Handbook of Business Strategy, January/ February, pp. 127-38. Duhon, B. (1998), “It’s all in our heads”, Inform, Vol. 12 No. 8, pp. 8-13. Fawcett, S.E. and Clinton, S. (1997), “Enhancing logistics to improve the competitiveness of manufacturing organizations: a triad perspective, logistics in manufacturing”, Transportation Journal, pp. 18-28. 120

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Goldman, S.L., Nagel, R. and Oreuss, K. (1995), Agile Competitors and Virtual Organizations, Van Nostrand Reinhold, New York, NY. Holzner, B. and Marx, J. (1979), The Knowledge Application: The Knowledge System in Society, Allyn & Bacon, Boston, MA. Kleindorfer, P.R. and Partovi, F.Y. (1990), “Integrating manufacturing strategy and technology choice”, European Journal of Operational Research, Vol. 47, pp. 214-24. Lee, H.L. and Whang, S. (2001), “E-business and supply chain integration”, Proceedings of Stanford Global Supply Chain Management Forum, November, pp. 1-22. Malhotra, Y. (2000), “Deciphering the knowledge management hype”, available at: www.brint.com Meade, L. and Sarkis, J. (1999), “Analyzing organizational project alternatives for agile manufacturing processes: an analytical network approach”, International Journal of Production Research, Vol. 37, pp. 241-61. Morse, R. (2000), “Knowledge management systems: using technology to enhance organizational learning”, International Resources and Management Association Conference, Anchorage, AK.

Nissen, M., Kamel, M. and Sengupta, K. (2000), “Integrated analysis and design of knowledge systems”, Information Resources Management Journal, pp. 24-43. Pentland, B.T. (1995), “Information systems and organizational learning: the social epistemology of organizational knowledge systems”, Accounting, Management and Information Technologies, Vol. 5 No. 1, pp. 1-21. Saaty, T.L. (1996), Decision Making with Dependence and Feedback: The Analytic Network Process, RWS Publications, Pittsburgh, PA. Sadeh, N., Hildum, D.W. and Kjenstad, D. (2003), “Agentbased e-supply chain decision support”, Journal of Organizational Computing and Electronic Commerce, Vol. 13 No. 3/4, pp. 225-42. Sarkis, J. (1998), “Evaluating environmentally conscious business practices”, European Journal of Operational Research, Vol. 107, pp. 159-74. Simchi-Levi, D., Kaminsky, P. and Simchi-Levi, E. (2000), Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies, Irwin McGraw-Hill Companies Inc., Boston, MA.

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Successful use of e-procurement in supply chains Thomas Puschmann The Information Management Group (IMG AG), St Gallen, Switzerland, and

Rainer Alt Institute of Information Management, University of St Gallen, St Gallen, Switzerland Abstract Purpose – Electronic support of internal supply chains for direct or production goods has been a major element during the implementation of enterprise resource planning (ERP) systems that has taken place since the late 1980s. However, supply chains to indirect material suppliers were not usually included due to low transaction volumes, low product values and low strategic importance of these goods. Dedicated information systems for streamlining indirect goods supply chains have emerged since the late 1990s and subsequently have faced a broad diffusion in practice. The concept of these e-procurement solutions has also been described broadly in the literature. However, studies on how companies use these e-procurement solutions and what factors are critical to their implementation are only emerging. This research aims to explore the introduction of e-procurement systems and their contribution to the management of indirect goods supply chain. Design/methodology/approach – Chooses a two-part qualitative approach. First, summarizes the results of a benchmarking study that was conducted by a consortium of 12 multinational companies. During the benchmarking process 120 questionnaires were distributed, ten phone-based interviews were conducted, and finally five successful practice companies were selected and analyzed in detail. Second, draws together the success factors identified in the benchmarking study and maps them against the successful practice companies. Findings – Although e-procurement has substantially streamlined the procurement and coordination processes for indirect goods, many companies operate multiple e-procurement solutions. For integrated procurement solutions, the paper recognizes the need of an overall procurement strategy and organization, an alignment of various e-procurement solutions along the procurement process and the need for integrated system architectures. Companies also have to realize that a no standardized e-procurement solutions exists and that important success factors are “non-technical” in nature. Originality/value – This paper presents a first step towards a systematic analysis of factors that may guide companies in the implementation of eprocurement solutions. Besides providing a direct contribution to the project work in companies it may stimulate further research in e-procurement success factors. Keywords Procurement, Communication technologies, Supply chain management, Benchmarking, Critical success factors Paper type Research paper

been redesigning their relationships with business partners for indirect procurement. Direct procurement addresses all components and raw materials that are used in the manufacturing process of a finished product, such as sheet metal, semiconductors, and petrochemicals (Lamming, 1995), whereas indirect procurement relates to products and services for maintenance, repair and operations (MRO) and focuses on products and services that are neither part of the end product nor resold directly (Zenz, 1994). Traditionally, ERP systems have been applied to products with high transaction volumes and direct implications for value-adding processes. As a consequence, we still find paper-prone and labor-intensive processes for indirect procurement that harbor large inefficiencies. The diffusion of e-procurement systems in the late 1990s has created the potential for reorganizing the MRO supply chains. Compared to ERP, these systems were considerably

Introduction Evolution of e-procurement As a major part of supply chain management (Leenders and Fearon, 1997; Monczka et al., 1997), supply chains in procurement are traditionally supported by information technology. With the implementation of enterprise resource planning (ERP) or manufacturing resource planning (MRP) systems in the 1980s electronic data interchange (EDI) connections with suppliers were established. For example, close partnerships have been forged with direct material suppliers through the automation of delivery schedules by linking a company’s materials management system with supplier systems. Since the mid-1990s companies have also The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm

This research was conducted as part of the Competence Center Business Networking at the Institute of Information Management (IWI-HSG) in collaboration with the Transfer Center for Technology Management (TECTEM) at the Institute of Technology Management, University of St Gallen. The authors would like to thank the staff from TECTEM, in particular Mr Urs Frehner, for their cooperation and for the suggestions for revisions of the manuscript from two anonymous reviewers.

Supply Chain Management: An International Journal 10/2 (2005) 122– 133 q Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/13598540510589197]

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Figure 1 Effects of e-procurement

less expensive and more flexible due to increased standardization on a technical level. More or less all studies on e-procurement report large efficiencies regarding process and procurement costs (Gebauer and Segev, 1998). The main idea of e-procurement is to include the end-user (requester) in the procurement process via an electronic multi-vendor catalog and to close the process gaps (e.g. re-entry of data) in the supply chain for indirect goods (Neef, 2001). A third phase of development in e-procurement has also been observable with the integration of electronic markets (emarkets) in the supply chain since the end of the 1990s (Poirier and Bauer, 2000). These e-markets evolved alongside the early system vendors like Ariba, Commerce One or SAP and support the outsourcing of operational procurement functions, offering tools for auctions and requests for quotations. However, the following evolution of e-markets has led to a substantial consolidation and many now focus on outsourced solutions for catalogs and auctions. To summarize, these three development stages form the basis for the term e-procurement in this paper. According to (Dolmetsch et al., 2000), e-procurement deals with the management of supply chains in the procurement of indirect goods that is based on Internet information systems and also e-markets.

companies were planning to implement e-procurement systems at that time. Other studies show similar proportions for other countries (for the USA, for example, Industrial Distribution, 2001; The Institute of Management and Administration, 2000). A study by Wyld (2004) reports that currently almost half of all American companies use eprocurement systems. Although the adoption of e-procurement has rapidly increased in recent years, companies face different challenges associated with the advent and use of eprocurement. One is that most companies only apply single e-procurement functions. The analysis by Wyld (2004) shows that in the USA only 30 percent of the companies surveyed use e-procurement systems for requests for quotations, online auctions (25 percent) or e-markets (33 percent). A second challenge is that, despite the overwhelming evidence which shows the advantages of e-procurement systems, proprietary systems such as EDI continue to persist, and have to be included in a company’s overall e-procurement infrastructure. To do so, companies need to know the critical success factors in implementing e-procurement strategies, processes and systems. From an academic perspective, some initial contributions to success factor research exist. An analogy with the natural sciences shows that causal links between actions and their successful effects as the main goal. In the social sciences, the deterministic claim of the empirical success factor research approach very often cannot contribute clear results (e.g. Eyholzer and Hunziker, 2000; Industrial Distribution, 2001; The Institute of Management and Administration, 2000; Wyld, 2004, Kauffmann and Mohtadi, 2004; Gebauer and Shaw, 2004). Instead of the verification of constant laws, the search for a few parameters (success factors) is therefore proposed (e.g. Boynton and Zmud 1984). This more qualitative research approach identifies success factors from case studies and differs from empirical success factor research that defines strong requirements in terms of validity and reliability. Despite these missing causal effects, there is a belief that research has to strive for recommendations that reduce uncertainty and guide management actions (Tan and Pan, 2002). Because of the difficulties of empirical success factor research, this article chooses a two-part qualitative approach. It summarizes the results of a benchmarking study that was conducted by a consortium of 12 multi-national companies from Germany and Switzerland. During the benchmarking

Benefits of e-procurement The potentials of e-procurement have already been proven in a number of studies (Aberdeen Group, 2001; Eyholzer and Hunziker, 2000; Arthur Andersen Business Consulting, 2001). According to these studies, e-procurement enables companies to decentralize operational procurement processes and centralize strategic procurement processes as a result of the higher supply chain transparency provided by eprocurement systems. Typically, a company’s procurement function is subdivided into strategic and operational processes since activities and priorities in these two areas are entirely different (Kaufmann, 1999; Lamming, 1995). Supplier management, the pooling of purchase requisitions and procurement-oriented product development are tasks that are typically assigned to strategic procurement. Prior to e-procurement, strategic procurement often had to deal with administrative routine work as well, such as individual transactions, converting purchase requests into purchase orders or ensuring the correct allocation of invoices received. Strategic aspects are frequently neglected in the process, with the buyer having little influence over the choice of suppliers and the purchased products. The use of Internet technologies in procurement is aimed at realizing faster and more efficient operational procurement processes which bypass the purchasing department and enable those people to concentrate on more strategic tasks (Giunipero and Sawchuk, 2000; see Figure 1). In e-procurement, requesters directly search for and select products in electronic catalogs which are authorized and negotiated by strategic procurement in advance. Successful use of e-procurement Despite the potentials promised by the vendors of such systems, e-procurement got off to a slow start. A study by (Eyholzer and Hunziker, 2000) shows that only 18 percent of the Swiss companies analyzed used electronic product catalogs, auctions or requests for quotations in procurement in the year 2000. According to this study, however, many 123

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

process that took place between March and September 2000, 120 questionnaires were distributed, ten telephone interviews were conducted, and finally five successful practice companies were selected and analyzed in detail. The article analyzes implemented e-procurement solutions and identifies factors that the companies surveyed cited as important requirements for the successful use of e-procurement systems in their organizations.

Figure 2 Focus of the benchmarking project

Research method Benchmarking method Benchmarking can be defined as the systematic comparison and learning from other companies with the goal of achieving sustainable improvements for a company’s own position (Camp, 1989). Depending on focus, two benchmarking approaches can be distinguished which are not mutually exclusive (Pieske, 1995): 1 Goal of comparison. Quantitative benchmarking is aimed at comparing efficiency on the basis of key performance indicators in order to define a company’s position by applying objective criteria. The goal of qualitative benchmarking, on the other hand, is to deduce reference concepts, methods and models for the design and the transfer of successful practices to one’s own company. 2 Horizon of comparison. Four main types of benchmarking can be differentiated depending on organizational focus. Internal benchmarking studies allow companies to compare best practices on a quantitative, key performance indicator-based approach. External methods such as competitive benchmarking support individual positioning very well but are lacking when it comes to discovering detailed key performance indicators from other industries (Boutellier et al., 1999).

The results of the 52 questionnaires returned were reported to the consortium in the second meeting. Ten responses with the highest scores (regarding the defined criteria) were documented in more detailed case studies based on phone interviews. All cases were reported on an anonymous basis to the consortium members and prioritized during the review meeting. Finally, this assessment process led to the selection of five successful practice companies. Benchmarking partners The review meeting led to the selection of five successful practice companies. These companies presented their solutions during site visits. The five selected companies were: 1 Babcock Borsig AG, headquartered in Oberhausen, Germany, is an international technology group operating in the fields of power engineering and shipbuilding. In keeping with its decentralized company structure, Babcock has a decentralized purchasing organization. Babcock runs a Lotus Notes-based e-procurement system which covers approx. 90 percent of the company’s indirect procurement volume. 2 Bayer AG, headquartered in Leverkusen, Germany, is a multi-national company with core competencies in chemical and pharmaceutical products. Prior to implementing the SAP Business-to-Business eprocurement system, Bayer started a worldwide bundling project for indirect goods in order to achieve horizontal and vertical synergies in procurement. In 2000 the company initiated an e-procurement project with an electronic catalog including some 169,000 articles from 39 suppliers. 3 Cisco Systems, Inc. is a manufacturer of networking equipment and services for the Internet and is headquartered in San Jose, USA. Cisco arranged its procurement in line with the different commodities the company procures (e.g. telecom, IT, training, etc.). In 1996 the company started with the implementation of the Ariba Operating Resource Management System (ORMS). Cisco purchases approx. 60 percent of all indirect products and services from 17 suppliers via the Ariba solution. 4 SAP AG, headquartered in Walldorf, Germany, is the world’s largest supplier of ERP systems. The company introduced a corporate purchasing department in 1999 for the coordination of their international procurement activities. The company announced 14 purchasing managers for each country and each commodity. At the same time, the company implemented the SAP B2B Procurement system with which SAP procures approx. 16,000 items for services and IT.

The consortium benchmarking which was applied for this benchmarking project concentrates on an external, industryindependent comparison of generic concepts and critical success factors. The company consortium consisted of purchasing specialists from twelve German and Swiss companies and was supported by an expert team consisting of the University of St Gallen’s Institute of Information Management and its Benchmarking Center TECTEM. The consortium benchmarking method aims to identify crossindustry successful practices which are selected in a given project procedure. These successful practices are concepts, methods and models that have been proven in one or more companies and lead to a competitive advantage (Boutellier et al., 1999). Qualitative benchmarking requires the definition of objects of comparison to ensure the comparability of the successful practices (Camp, 1989). In the e-procurement benchmarking project, these objects were defined during the first consortium meeting. The objects of comparison were: introduction project, the procurement organization, content and catalog management, supply chain processes and system architecture, as well as operational efficiency (see Figure 2). The benchmarking project encompassed four phases (see Figure 3). During the preparation phase objects of comparison and criteria were defined and discussed in the first consortium meeting (see Table I). This structure was used in the questionnaires that were sent to 120 potential successful practice companies in Europe and North America. 124

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Figure 3 Research method

Table I Defined criteria for successful practices Object of comparison

Defined criteria

Introduction project

Complete implementation of e-procurement system E-procurement in operation . six months Change management system in place Multinational enterprises with large procurement volume High degree of implementation Reorganization project as part of e-procurement project Criteria for the development of a procurement portfolio Company-wide product classification scheme (e.g. UN/SPSC) Use of catalog hosting on the intranet Use of e-procurement standard software Internal integration with ERP systems External integration with e-markets Measurement system for procurement (e.g. balanced scorecard) Use of key performance indicators ROI analysis

Organization

Content and catalog management

Supply chain processes and system architecture

Operational efficiency

5

procurement. Little attention was paid to MRO procurement, and manual, paper-based procedures prevail. Not only are they labor-intensive and harbor a considerable error potential, but many transactions simply bypass the purchasing department and are carried out directly with local suppliers. Especially the large benchmarking companies started eprocurement with organizational concepts on corporate level. Typically, the areas purchasing, IT and financial accounting had to be coordinated in order to define common goals. Successful e-procurement implementations included more than merely a new IT system. The benchmarking project highlights five factors for the implementation of eprocurement in large organizations (see Figure 4): 1 realignment of the purchasing operation; 2 reorganization of the procurement process;

Xerox (Europe) Ltd is headquartered in London, UK, and manufactures copiers, printers, scanners, software as well as providing services. In 1999 the company started a procurement project that focused on the reorganization of its 16 independent country-based procurement organizations through a central commodity board that coordinates procurement on a pan-European level. Besides the procurement of indirect products, Xerox has a strong focus on the procurement of services since this represents the biggest volume in its procurement portfolio.

Results of the benchmarking study Introduction project Many large companies have a similar situation in their indirect procurement supply chain prior to the implementation of e125

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Figure 4 Implementation project

3 4 5

people also raised objections to a lean authorization procedure. Since they have usually spent years performing the task of “authorizing”, they consider it to be an important and meaningful part of their daily work. In the case of a lean procurement process, invoice verification can be simplified as well, only performed at random or replaced by a credit system. Supplier management is another area of organizational change. E-procurement provides the opportunity to establish preferred suppliers in the MRO area as well (Smeltzer, 2001). For this purpose it is necessary to implement supplier management as part of the e-procurement project. As most of the large companies have decentralized procurement structures in place, all of the companies analyzed implemented a central coordination instance in order to have better control over the products and services to be purchased on a company-wide basis. Bayer, for example, conducted a pooling project prior to the implementation of its e-procurement solution in order to bundle volumes on a regional and, where possible, even on a global level.

preparation of catalogs offering the right amount of goodquality content; embracement of suppliers at an early stage; and integration of e-procurement and back-end systems.

The overall introduction of an e-procurement system typically required approximately six months. All benchmarking partners had pilot solutions in place prior to the roll-out of the system. However, addressing non-technical questions took significantly longer. Bayer, for example, needed about a year to form a global commodity coordination board which was necessary to pool volumes of certain products and services. Another year was required to establish centralized master data management, a key element for data quality in the catalog. Organization Prior to the introduction of e-procurement, buyers frequently had to deal with individual transactions. They had to negotiate with suppliers, convert purchase requests into purchase orders, handle queries and ensure the correct allocation of the invoices received. In the operational workload, strategic aspects were neglected and buyers had little influence over the choice of suppliers and the purchased products. Their negotiating power was limited as the purchasing decision was made by the requester or the authorizer and not by the purchasing department. The requester was at the center, with all activities emanating from him or her (see Figure 5). E-procurement brings about important simplifications of the MRO procurement process and reduces this operational workload for buyers by decentralizing the operational procurement process. If the procurement process is to be faster and more convenient, the number of authorization stages must be radically reduced. Babcock Borsig, for example, eliminated its authorization workflow altogether. At Bayer, all employees may authorize their own purchasing operations up to a limit of e1,500. SAP reduced the number of authorization stages from six to one. With the old, paperbased procurement process, numerous authorization stages were necessary and involved, e.g. line and project managers, specialists or the purchasing department. Very often these

Content and catalog management Despite the re-engineering of the procurement process, content management is another key factor for successful eprocurement implementation (Smeltzer, 2001; Poole and Durieux, 1999). Among our successful practice companies, four strategies were observed (see Table II): 1 Intranet catalog. Electronic multi-vendor product catalogs hosted on a company’s own intranet to pool enterprisewide demand and optimize procurement processes. 2 Punchout. A catalog hosted on the supplier’s web site (e.g. Dell) if products are more complex and need to be configured with a product configurator. 3 Auction. Auctions to leverage price reductions through supplier competition. Auctions are suitable for products and services with low complexity and allow comparison among different suppliers. 4 Request for quotation (RFQ). In settings with low frequency of use and high complexity, RFQs are an instrument for inviting suppliers to submit bids based on previously published specifications. 126

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Figure 5 Shift from managing transactions to managing suppliers

Table II Characterization of e-procurement strategies E-procurement strategy Criterion Number of orders Volume per order Number of requestors Number of suppliers Degree of standardization Competition

Intranet catalog High Low High Low High Low

Punchout Medium Low Medium Low Medium Low

Identifying the right e-procurement strategy for each commodity is crucial to the success of a company’s solution and therefore ranks as one of the major challenges. First of all, products and services with a very high degree of coordination effort with the supplier and a very low order frequency are certainly not candidates for e-procurement (Porter, 2001). These products require a high effort for content negotiation. Bayer, for example, conducted an auction for a plant with a value ofe310 million. It took the company three months to specify the product with all the necessary details in order to keep it comparable among the different suppliers. Finally, the auction was conducted with a price reduction of one percent. This confirms that when conducting auctions, price is not the sole determining factor for supplier negotiations (Kenczyk, 2001). Among the decision criteria to consider when bidding and buying engineered custom parts are quality, technical ability, cost, lead time, delivery arrangements and payment terms, to name but a few. These requirements are unique to both the part design and the capability of suppliers. Table II shows the criteria that characterize each single e-procurement strategy. Auctions and requests for quotations are partly complementary strategies used to reduce procurement costs. Where appropriate, companies conduct auctions for certain products and catalog them afterwards. Some companies tried to catalog services as well. In the initial phase of most e-procurement projects, services are not usually included in catalogs. However, the benchmarking study shows signs that bode well for the cataloging of services. Bayer, for example, is establishing a standard directory for maintenance services. With some 800,000 order items a year, this results in a considerable transaction volume. One item within this area, for example, is “lay one meter of cable”. In collaboration with Manpower, a UK-based human resource company, Xerox has already built up a catalog for temporary

Auction Low High Low High High High

Request for quotation Low High Low Medium Medium Medium

staff. Function, level of qualifications, workplace and length of employment can be entered, the price is then shown and the order can be sent to Manpower electronically. Catalog orders for services are usually more detailed than paper-based orders, each item is standardized and listed individually. This makes it possible to draw an exact comparison between the invoices received and the order submitted. The main criterion for services is their degree of standardization. For example, the qualification profile of a new employee is not as standardized as a print job for a marketing brochure. Therefore, Xerox uses the punchout scenario for services with a low degree of standardization and less purchasing frequency. Catalog management deals not with the content itself but with the physical hosting of catalogs (Dolmetsch et al., 2000). In our benchmarking study we found three different strategies (see Figure 6). An initial strategy is the use of catalogs that are hosted on a company’s Intranet. The purchasing company is the owner of the catalog data and changes are typically performed by the purchasing company itself or the supplier. All the successful practices used this form of catalog hosting because the company has better control over changes and the catalog can easily be released after approval by the purchasing department. A second strategy which uses externally hosted catalogs on a supplier’s website is the punchout mechanism. The punchout scenario enables requesters to access external catalogs via their own e-procurement system (Kalakota and Robinson, 2001). Selected products and services can be chosen from the supplier’s electronic product catalog and transferred to the internal e-procurement system with a mouse click. The advantage of this strategy is a streamlined catalog maintenance and procurement process in the same way as the catalog would be hosted on a company’s own 127

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Figure 6 Strategies for catalog management

intranet. The requester sees only those products and services that the purchasing department negotiated. Product configurators from the suppliers that could only be integrated into a company’s own Intranet with a great deal of effort are the main reason for using the punchout scenario. A third strategy for catalog management is the use of external multi-vendor product catalogs that are hosted on electronic marketplaces. This strategy is tightly coupled with a company’s general procurement strategy (Raisch, 2001). Babcock Borsig, Bayer and SAP used this strategy because they initiated their own electronic marketplaces with other partner companies. SAP, for example, introduced its marketplace emaro in order to pool volumes and standardize procurement processes with suppliers. Bayer follows the same strategy. The company launched the marketplace cc-chemplorer in October 2000 with the same 169,000 catalog items that Bayer had formerly held in its own multi-vendor product catalog. The main goal of these marketplaces was to use synergies not only within one company but also across several companies. Although a broad diffusion of these e-markets did not occur and some solutions (e.g. emaro, EC4EC) have disappeared cc-chemplorer appears to operate successfully in the segment of outsourced content and catalog management.

processes. Similarly, implementing an e-procurement system in isolation without considering the entire procurement process and the systems involved will not be sufficient (Deise et al., 2000). As shown in Figure 7, the various eprocurement strategies need to be crafted in a company’s procurement process according to their strengths (Riggs and Robbins, 1998; Hughes et al., 1998; Dolmetsch et al., 2000; Kalakota and Robinson, 2001). Usually, they are complementary and support different parts of a company’s procurement process. At Bayer and Xerox the roll-out of the e-procurement system has been aligned with the SAP R/3 project. The decision in favor of a particular e-procurement system will usually depend on the existing ERP and procurement systems. However, comprehensive studies on system evaluation are not usually performed. Selecting a system tends therefore almost without exception to be a pragmatic decision. Xerox, for example, evaluated e-procurement systems from Ariba, Commerce One, Oracle and SAP, and finally chose the SAP solution because of its integration capability with their existing SAP R/3 system. Another major criterion when selecting an e-procurement system is its technological maturity. Cisco opted for Ariba’s e-procurement system as it provided the best link to the Oracle system at the time and also led in terms of user friendliness. Typically, all eprocurement systems have adapters to allow seamless integration with back-end systems. Cisco’s Ariba system, for example, extracts all user information such as user name, password and IP addresses from the Peoplesoft human resources system. Additional interfaces exist to link in the Oracle financial and material management system. As eprocurement is not targeted exclusively at the optimization of internal processes, integration is also required towards the suppliers and electronic marketplaces. SAP, for example, uses emaro to link with suppliers’ systems for order processing and accounting. However, most of the companies still focused on internal integration whereas the link to electronic marketplaces continues to be a second priority (see Figure 8).

Supply chain processes and system architecture Compared to the internal focus of traditional logistic approaches, SCM emphasizes the management of upstream and downstream relationships and the role of supply chain optimization to increase customer value at less cost (Christopher, 1998; Ross, 1998). Examples of SCM initiatives are just-in-time, zero inventory, efficient consumer response, vendor-managed inventory or continuous replenishment (Kalakota and Whinston, 1997). SCM involves three areas to deal with (Christopher, 1998): order processing activities, physical activities, and order-related financial activities. The experiences of many failed ERP implementations show that the introduction of a new system is only efficient with the redesign of existing business 128

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Figure 7 Supply chain processes and e-procurement strategies

Figure 8 Use of e-procurement systems

The use of standards plays a critical role in e-procurement. Objects to be standardized are catalogs, data and processes. If the catalog data were not organized according to an ordered structure, they would be virtually unusable. For example, Bayer structured and stored its items using the eCl@ss standard (Table III). Like UN/SPSC, eCl@ss is a product classification

system. In addition, it is possible to cover various characteristics of a product with the aid of the list of attributes. Some products differ only marginally in their characteristics. A set of weighing scales, for example, may have a scale from 20-200 g or 101,000 g and show different graduations. However, UN/SPSC does not allow characteristics of this kind to be included. 129

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Table III E-procurement architecture components and standards

Company

E-procurement system

ERP system

Babcock Borsig AG Bayer AG Cisco Systems, Inc. SAP AG Xerox (Europe) Ltd

Lotus Notes SAP B2B 2.0 Ariba Buyer 6.1 SAP B2B 2.0 SAP B2B 2.0

SAP R/3 SAP R/3 Oracle, Peoplesoft HR SAP R/3 SAP R/3

Architecture component Product Catalog classification standard standard BME-Cat Harbinger Ariba Requisite Requisite

BME-Cat eCl@ss UN/SPSC UN/SPSC UN/SPSC

Communication standard

E-market

ASCII XML XML XML XML

EC4EC chemplorer – emaro –

needs to be redesigned. In the successful practices, this redesign focused on: . reduction or elimination of authorization stages; . regulation of exceptions to a limited degree at the beginning; . elimination of paper; . integration of suppliers in the entire process chain; and . consideration of the complete process, from searching for articles through to invoicing.

Operational efficiency According to a study from Intersearch Corp. (1998), approximately 80 percent of all purchasing transactions are spent on indirect products and services. Most Fortune 100 companies have in excess of 40,000 suppliers of indirect goods but purchase less than US$10,000 annually from 80 percent of those suppliers. E-procurement provides an opportunity to consolidate sources and control maverick buying, which can account for dramatic savings. These cost savings are one of the most important motivations for eprocurement. Nearly all of the companies analyzed in the benchmarking study have confirmed operational efficiency. E-procurement benefits fall into two major categories: efficiency and effectiveness (Kalakota and Robinson, 2001). The former includes process, products and inventory savings (see Figure 9), the latter the proactive management of key data, and higher-quality purchasing decisions within organizations. Efficiency improvements are calculated on the basis of the as-is situation prior to the implementation of eprocurement. The more complicated the old paper-based procurement processes, the more authorization stages and exceptions, and therefore the higher the savings will be. To take advantage of these potentials, the procurement process

Many figures relating to the savings potentials in the procurement process have already been published (e.g. Intersearch Corp., 1998; Killen & Associates, 1997). The average process costs per order in the as-is situation at all benchmarking partners lay between US$70-150. The cost reductions in an e-procurement project are on average between 50 percent and 80 percent. This savings potential, averaging US$70 and more per order, forms the basis for most feasibility studies prior to e-procurement projects. The long-term e-procurement users among the benchmarking partners, namely Babcock Borsig and Cisco, confirm these savings potentials. Here, it is important to consider not only the savings in the actual purchasing operation itself but also on the part of users, authorizers, invoice verification and logistics. Cisco highlights the efficiency potential of eprocurement. In view of the company’s growth structures, processes in procurement also have to grow, or be readily adaptable. Purchasing volume has more than doubled within the last two years and is nevertheless still handled by the same number of staff but now using e-procurement.

Figure 9 Savings potential of e-procurement

Summary and outlook Summary of benchmarking results The benchmarking study showed that companies which successfully implemented e-procurement rely on proven concepts regarding introduction, organizational change, content and catalog management, procurement processes and system architecture in order to achieve operational efficiency. The successful practices demonstrate that eprocurement is merely a non-technical issue. The effort undertaken to implement e-procurement as a strategy is mostly spent on organizational aspects and the redesign of procurement processes rather than on technical questions. All successful practices implemented a globally oriented commodity coordination board to agree upon the products purchased via the e-procurement solution. The strong decentralization of the procurement function in large companies was a barrier to achieving synergies from pooling volumes at a corporate level. E-procurement enabled companies 130

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

to gain greater transparency over their procurement portfolio with the availability of more detailed data. The benchmarking project showed that all successful practices have strengths in certain areas. Babcock Borsig, for example, focused on the support of procurement processes in operational and strategic issues with the marketplace EC4EC that not only supported indirect but even direct procurement processes. Bayer, on the other hand, had a strong focus on content management. The company defined a high percentage of its indirect product volume and developed a catalog that also served to build up a new business segment with the marketplace cc-chemplorer. Cisco’s e-procurement solution was characterized by a high degree of integration on a systems level. The young company history provides the advantage of avoiding data redundancies on a global basis. The e-procurement systems are tightly integrated with other operational systems. This allows Cisco a very high degree of transparency and standardization. The same can be said about SAP. Because of the company’s IT focus, it has been using its own electronic marketplace since 1999 for the procurement of PCs from Fujitsu Siemens. The establishment of the emaro marketplace was the next step in this direction. A completely new dimension of e-procurement is provided by Xerox. The company traditionally has a strong focus on the procurement of services and it began very early with the bundling of services in catalogs. All the companies analyzed collected know-how concerning e-markets. But most of them did not plan to substitute their internal catalogs by catalogs hosted on e-markets. In fact, these companies believed that electronic marketplaces complement their existing e-procurement solutions with functionality for strategic procurement issues (e.g. requests for quotations). Other companies used their internal catalogs to found e-markets, as the examples of Babcock Borsig and Bayer show. Table IV summarizes the success factors which were identified in the benchmarking project and maps them against

the successful practice companies. Seven independently named success factors were important in all five companies (1.2, 1.3, 2.1, 2.2, 3.3, 4.2, 5.1). Other factors can be explained by company or project specifics. The use of standards for data interchange, for example, was much more important for Bayer and SAP because these companies used eMarkets to integrate their e-procurement systems with their suppliers. This is the reason why these three companies also had to develop a strategy for the physical hosting of their catalogs. Outlook In most companies, procurement has always been an unnoted function (Kaufmann, 1999). Management’s prime interest was focused on manufacturing and sales. Recently, more and more companies have realized that procurement plays a very important role. In fact, procurement is more significant than sales in terms of its influence on company figures. For example, a case study at Mercedes-Benz identified that a 10 percent increase in turnover had the same effect on the operating result as a reduction in material costs of 0.518 percent, due to the leverage effect of procurement costs (Kalakota and Robinson, 2001). Thus, e-procurement has a strategic function in most organizations as the high diffusion of Wyld (2004) shows. Since many companies have implemented traditional e-procurement systems, new areas of improvement come along: . Collaborative procurement. Collaboration is aimed at a closer interaction between suppliers and customers through the use of Internet technologies such as portals. An example of such collaboration scenarios comes from the automotive industry where manufacturers report their demand and inventory status through supplier portals. These numbers are used by first-tier suppliers to feed their supply chain and production planning systems with realtime data. This form of collaboration means a two-way

Table IV Summary of success factors Object of comparison

Success factor

1. Introduction project

1.1 1.2 1.3 2.1 2.2

2. Organization

3. Content and catalog management

3.1 3.2

4. Supply chain processes & system architecture

3.3 4.1 4.2

5. Operational efficiency

4.3 5.1 5.2

Realignment of the purchasing organization Preparation of catalogs Embracement of suppliers at an early stage Automation of authorization workflow Creation of a central coordination instance for supplier management Identification of the right e-procurement strategy for each commodity Standardization of services for representation in the catalog Strategy for the physical hosting of the catalogs Alignment of e-procurement strategies with the procurement process Integration of the e-procurement system with other relevant systems Use of standards for catalogs and data interchange Redesign of the procurement process in order to gain efficiency improvements Link to the balanced scorecard

131

Babcock Borsig

Bayer

Cisco Systems

SAP

Xerox

U U U U

U U U U

U U U U

U U U

U U U U

U

U

U

U

U

U

U

U

U U U

U

U

U

U

U

U

U U

U

U U

U U

U

U U

U U

U

U U

.

Successful use of e-procurement in supply chains

Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

Volume 10 · Number 2 · 2005 · 122 –133

Gebauer, J. and Shaw, M.J. (2004), “Success factors and impacts of mobile business applications: results from a mobile e-procurement study”, International Journal of Electronic Commerce, Vol. 8 No. 3, pp. 19-41. Giunipero, L.C. and Sawchuk, C. (2000), E-purchasing Plus: Changing the Way Corporations Buy, JGC Enterprises, Goshen, NY. Hughes, J., Ralf, M. and Michels, B. (1998), Transform Your Supply Chain: Releasing Value in Business, Thomson, London. Industrial Distribution (2001), “E-procurement still slow to take off”, Industrial Distribution, Vol. 90 No. 3, pp. 32-4. (The) Institute of Management and Administration (2000), Supplier Selection and Management Report: Most Purchasing Pros Still at the Starting Gate with E-procurement, The Institute of Management and Administration, IOMA, Inc., New York, NY. Intersearch Corp. (1998), National Purchasing Organisations User Group Survey, Intersearch Corp., Palo Alto, CA. Kalakota, R. and Robinson, M. (2001), E-business 2.0: Roadmap for Success, Addison-Wesley Longman, Boston, MA. Kalakota, R. and Whinston, A.B. (Eds) (1997), Readings in Electronic Commerce, Addison-Wesley, Reading, MA. Kauffmann, R.J. and Mohtadi, H. (2004), “Proprietary and open systems adoption in e-procurement: a risk-augmented transaction cost perspective”, Journal of Management Information Systems, Vol. 21 No. 1, pp. 137-66. Kaufmann, L. (1999), “Purchasing and supply management – a conceptual framework”, in Kaufmann, L. and Hahn, D. (Eds), Handbuch Industrielles Beschaffungsmanagement: Internationale Konzepte – Innovative Instrumente – Aktuelle Praxisbeispiele, Gabler, Wiesbaden, pp. 3-32. Kenczyk, M. (2001), “Reverse auctions are risky models for buying custom parts”, Machine Design, Vol. 73 No. 6, p. 148. Killen & Associates (1997), “Operating resources management: how enterprises can make money by reducing ORM costs”, White Paper, Killen & Associates, Palo Alto, CA. Lamming, R. (1995), Strategic Procurement Management in the 1990s: Concepts and Cases, Earlsgate Press, Stamford, CT. Leenders, M.R. and Fearon, H.E. (1997), Purchasing and Supply Chain Management, McGraw-Hill, Boston, MA. Monczka, R., Trent, R. and Handfield, R. (1997), Purchasing and Supply Chain Management, International Thomson Publishing, Cincinnati, OH. Neef, D. (2001), E-procurement: From Strategy to Implementation, Prentice-Hall, Upper Saddle River, NJ. Pieske, R. (1995), Benchmarking in der Praxis: Erfolgreiches Lernen von Fu¨hrenden Unternehmen, Verlag Moderne Industrie, Landsberg/Lech. Poirier, C.C. and Bauer, M.J. (2000), E-Supply Chain – Using the Internet to Revolutionize Your Business, Berrett-Koehler Publishers, San Francisco, CA. Poole, K.J. and Durieux, P. (1999), Content Management: The Critical Success Factor for E-procurement, Ernst & Young LLP, San Francisco, CA. Porter, M.E. (2001), “Strategy and the internet”, Harvard Business Review, Vol. 79 No. 3, pp. 63-78. Raisch, W.D. (2001), The E-marketplace: Strategies for Success in B2B E-commerce, McGraw-Hill, New York, NY.

interaction between the manufacturer and the supplier without any manual processes. Mobile procurement. Adding mobile access to eprocurement applications is an option that has not yet been widely adopted. Gebauer and Shaw (2004) report a case study in which a field service engineer can create a purchase request for a field repair job. The application provides functionality in three areas: creating purchase requisitions; approving requisitions; and checking the status of requisitions. Mobile procurement enhances existing e-procurement solutions and makes the application independent of the location where it is used. The benefits are high mobility; support for simple activities like tracking, access to ad hoc information, and reachability.

Future research can address these new areas of improvement and analyze in detail the integration of mobile and collaborative procurement functions into existing solutions. The study described in this paper was limited, because it was only a snap-shot. That’s why another topic for further research is the empirical validation of the success factors which were identified in the benchmarking project. A third subject for further research can be the embedding of the success factors into procedure models for the introduction and implementation of e-procurement systems.

References Aberdeen Group (2001), E-procurement: Don’t Believe the Anti-Hype, Aberdeen Group, Boston, MA. Arthur Andersen Business Consulting (2001), E-procurement: Electronic Purchasing in the German Industry – Status and Trend, Arthur Andersen Business Consulting, Stuttgart. Boutellier, R., Baumbach, M. and Bodmer, C. (1999), “Successful practices in after-sales management”, io management, Vol. 68 No. 1/2, pp. 23-7. Boynton, A.C. and Zmud, R.W. (1984), “An assessment of critical success factors”, Sloan Management Review, Vol. 25 No. 4, pp. 17-27. Camp, R. (1989), Benchmarking: The Search for Industry Best Practices that Lead to Superior Performance, ASQC Quality Press, Milwaukee, WI. Christopher, M. (1998), Logistics and Supply Chain Management: Strategies for Reducing Costs and Improving Services, Chapman & Hall, New York, NY. Deise, M.V., Nowikow, C., King, P. and Wright, A. (2000), Executive’s Guide to E-Business: From Tactics to Strategy, John Wiley & Sons, New York, NY. ¨ sterle, H. (2000), Dolmetsch, R., Fleisch, E. and O “Electronic commerce in the procurement of indirect ¨ sterle, H., Fleisch, E. and Alt, R. (Eds), goods”, in O Business Networking: Shaping Collaboration between Enterprises, Springer, Berlin, pp. 193-209. Eyholzer, K. and Hunziker, D. (2000), “The use of the internet in procurement”, in Hansen, H.R., Bichler, M. and Mahrer, H. (Eds), Proceedings of the 8th European Conference of Information Systems, Vienna University of Economics and Business Administration, Vienna, pp. 335-42. Gebauer, J. and Segev, A. (1998), “Assessing internet-based procurement to support the virtual enterprise”, Electronic Journal of Organizational Virtualness, Vol. 2 No. 3, pp. 30-43. 132

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Supply Chain Management: An International Journal

Thomas Puschmann and Rainer Alt

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Riggs, D.A. and Robbins, S.L. (1998), The Executive’s Guide to Supply Management Strategies: Building Supply Chain Thinking into all Business Processes, Amacom, New York, NY. Ross, D.F. (1998), Competing through Supply Chain Management: Creating Market-winning Strategies through Supply Chain Partnerships, Financial Times/Pitman Publishing, London. Smeltzer, L.R. (2001), “How to build an e-procurement strategy”, Supply Chain Management Review, Vol. 5 No. 3, pp. 76-83.

Tan, C.W. and Pan, S.L. (2002), “ERP success: the search for a comprehensive framework”, 8th Americas Conference on Information Systems, Dallas, TX. Wyld, D.C. (2004), “The weather report for the supply chain: a longitudinal analysis of the ISM”, Department of Management, Southeastern Louisiana University, Hammond, LA, available at: www.ism.ws/ismreport/ forrester Zenz, G. (1994), Purchasing and the Management of Materials, John Wiley & Sons, New York, NY.

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Future impacts of RFID on e-supply chains in grocery retailing Edmund Prater and Gregory V. Frazier Department of Information Systems and Operations Management, The University of Texas at Arlington, Arlington, Texas, USA, and

Pedro M. Reyes Hankamer School of Business, Baylor University, Waco, Texas, USA Abstract Purpose – To place the research on radio frequency identification (RFID) usage in supply chains within a specific business and market context; in this case, the grocery industry. Design/methodology/approach – This paper considers RFID research within the context of the grocery industry and outlines the market drivers that affect the way the grocery industry approaches RFID and also specific areas of research on RFID that should be undertaken to better provide the grocery industry with managerial insights into this technology’s application. Findings – Examining market drivers that are leading to RFID implementation in the grocery industry, this paper provides a theoretical framework for future applied research on RFID implementation. Specifically, it develops a research framework that includes research using modeling techniques, RFID implementation and the impact of RFID on daily operational issues. Research limitations/implications – This paper focuses on the market drivers for RFID implementation. While it does address other areas that are related to research in this field, it is limited in its ability to go into detailed discussion of those areas. For example, while technology implementation and innovation diffusion issues are raised, they are detailed research domains of their own which can only be superficially addressed in the context of this paper. Practical implications – The paper provides a detailed framework of research areas that are of direct, practical importance to the grocery industry. This should encourage research into this area, for, as researchers provide insights into these issues, the grocery industry can immediately put the findings into practice. Originality/value – RFID has garnered a great deal of research interest. However, that research has primarily focused on RFID’s impact on general supply chain issues, failing to place the discussion within a specific business domain. This is necessary because the strategic environment of any business impacts on the applicability of any technology. Keywords Supply chain management, Communication technologies, Food industry, Retailing Paper type Research paper

While research has been conducted on RFID, it has tended to focus on the specifics of the technology (Finkenzeller, 1999; Gould, 2000; Niemeyer and Pak, 2003) or its general promise of cost savings (Donovan, 2003; Kunii, 2003). What has been missing is a discussion of the market drivers (i.e. technology pull, or the forces that drive companies to adopt a technology or methodology) that lead various industries to consider RFID. An understanding of the market drivers of an industry is essential in order for practitioners to best implement a new technology, and for researchers to best understand what issues need to be addressed. The primary focus of this paper is to examine market drivers that are leading to RFID implementation in the grocery industry. We focus on the grocery industry because it is a prime candidate for RFID implementation. Over the past decade, grocery retailers have acknowledged that their supply chains are not responsive enough. To deal with this, they have invested millions into new techniques such as automatic replenishment programs (ARPs). Unfortunately, grocery retailers have actually increased average inventory levels and their related costs (Stank and Crum, 1999; Bowersox and Closs, 1999; Brown and Bukovinsky, 2001). RFID provides the opportunity to reverse this trend and truly integrate the grocery supply chain. This paper provides a theoretical framework for applying RF technology in grocery supply chains. It provides a

Introduction Recently, Wal-Mart announced that they would require all of their larger suppliers to implement radio frequency identification (RFID) on every box and pallet shipped to Wal-Mart by 2005 (Boyle, 2003). Much like they did with EDI development, Wal-Mart is beginning to drive the adoption of RFID, which will mean significant changes in the way supply chains are managed. Other key players driving the development and adoption of RFID include the US Department of Defense, Proctor and Gamble, and the European retailer Metro Group (RFID Journal, 2004). However, just as EDI implementation differs depending on the industry, so will RFID since each industry has specific needs and requirements to meet their supply chain objectives. The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm

Supply Chain Management: An International Journal 10/2 (2005) 134– 142 q Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/13598540510589205]

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Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

framework of supply chain management in the grocery industry, and outlines the major operational requirements that any new system must provide. It then discusses how grocery stores can utilize this technology to change the entire method in which they operate their supply chains. We then outline several distinct research streams to provide a framework for future applied research in this area.

In general, the goal of ARPs is that “the system must at any time provide sufficient supplies of goods in demand at the right spot and at competitive prices. These goods are standardized with a limited shelf life, with little opportunities for market segmentation and with a high demand for efficient logistics. Therefore, there has been a shift from pushing goods through the distribution network to a situation where the goods are pulled through the distribution network” (Ciborra, 1995). Thus, goods need to be replenished more frequently with a smaller average order size. This means that “the optimization of replenishment processes has been a focal strategic issue” (Damsgaard and Lyytinen, 2001). In short, the ultimate goal is that, “the right products reach the shelves at the right time and at lower cost and thus boost sales and profits” (Cottrill, 1997). Since the Kurt Salmon Associates report was released, research has shown that many grocery firms have implemented ECR/ARP programs (Daugherty and Myers, 1999). Unfortunately, the results have not been as good as hoped. For example, inventory stockpiles have actually increased since 1992, along with their attendant costs (Stank and Crum, 1999; Brown and Bukovinsky, 2001). Bowersox and Closs (1999) studied nine retail grocery chains that had implemented ECR from 1992-1997. They found that the chains had decreased average inventory turns and increased inventory levels, but net profit margin increased 22 percent and ROA increased 7 percent. The report concluded that the improved profits came from larger volume purchases, which generate increased promotional money at the expense of lower operating efficiency. More recent research (Brown and Bukovinsky, 2001) also found that most ECR adopters’ inventory efficiencies, asset efficiencies, and cash cycles generally deteriorated compared to non-adopters. Some have argued that ECR’s promised savings are limited because retailers and manufacturers refuse to abandon forward buying practices (Partch, 2000). So, we see that the current use of technology is not providing the desired results, and we must look for other options. This is becoming a more pressing issue because market saturation is changing the basis of competition.

Literature review Automatic replenishment programs: failure to deliver The main driver in recent grocery retailing research on supply chain issues is the program of efficient consumer response (ECR) that was initiated in the USA after a key report by Kurt Salmon Associates (1993). The motivation for this report was the declining profitability of the grocery industry in the face of competition with Wal-Mart and other warehouse clubs/superstores. The key finding in the report was that in the early 1990s the grocery supply chain was extremely inefficient. On average it took 104 days for dry grocery products to go from the supplier to the consumer. The main reason for the large amount of held stock was the fragmentation of the supply chain. Specifically, stock was pulled through the supply chain by way of replenishment orders for stores, but inventory was pushed through the warehouse system by trade promotions and forward buying practices. Forward buying emphasizes acquiring larger quantities of products based upon the purchase volumes necessary to get the best discounts from manufacturers. These quantities are stored in the warehouse. However, products are removed from the warehouse and sent to the stores based upon what the stores forecast they can actually sell. This difference, between acquired (pushed) volume at the warehouse and actual sold (pulled) amounts at the stores, causes substantial inventory growth within the warehouses of the supply chain. Forward buying began in the 1970s as a way for manufacturers to use discounting to bypass the price controls implemented by the Nixon administration. Forward buying is a practice on the part of the buyers, who are stocking up, to take advantage of low price offers due to special promotions, quantity discounts, or special pricing discounts. However, in the 1980s, instead of phasing out these programs, they became more heavily used because consumers were hooked on discounting. In fact, grocery manufacturers’ spending on trade promotions from 1981 to 1991 increased from 34 to 50 percent while advertising fell from 43 to 25 percent. Kurt Salmon Associates argued that this inefficiency, if removed, could save around $10 billion (10.8 percent of sales turnover) in the dry grocery chain. In general, the report held that ECR would reduce inventory levels to 61 days. Kurt Salmon Associates argued that “by jointly focusing on the efficiency of the total grocery supply system, rather than the efficiency of individual components, they are reducing total system costs, inventories, and physical assets while improving the consumer’s choice of high quality . . . grocery products” (Kurt Salmon Associates, 1993). ECR is in the same family of programs as continuous replenishment planning (CRP) and vendor managed inventory (VMI). All these programs fall under the umbrella term of automatic replenishment programs (ARPs). The basic structure showing the reliance on reliable information can be seen in Figure 1.

Market leakage and the need for increased product selection During the 1990s grocery store chains grew both in size and in geographic location. On one hand, grocery retailers expanded into suburban and rural areas while the stores themselves grew in size. These expanded stores, called superstores and megamarts, provided shoppers with huge selections, but also with huge sizes (many are over 50,000 square feet). The reason for this growth in size was simple. Retailers had to compete more directly and “differentiate themselves from each other, destroying the consumer’s commodity-like perception of competing stores” (Duke, 1991). This is a direct result of shoppers’ desires. Table I shows that after convenience, shoppers choose a store based on product range/selection, which even exceeds the importance of price. The reason for this can be explained through market leakage analysis (Ohme, 1982), a tool used to identify future directions for growth. Figure 2 shows the key components. There are two key market factors: a company’s share of the market and the leaked market which the company could serve but doesn’t. In the traditional market, a grocer would have its 135

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

Figure 1 A framework of automatic replenishment program relationships

Table I Factors affecting shopper store choice Factor Convenience Product range/selection Low price Quality Cleanliness Friendly staff Handy operating hours Others

level. Thus, one of the key theoretical questions is, to what extent can technology be utilized to reduce inventories, and therefore shelf space for individual products. This would allow a greater variety of products while maintaining high service levels.

Percentage 54 14 13 9 2 1 1 6

Individual product identification and item level supply chain management Item level identification must be the foundation for item level supply chain management. Item level identification, therefore, is only possible if each item has its own identity that can be recognized easily and efficiently within the entire supply chain. Wireless product identification has recently garnered the interest of researchers (Karkkainen and Holmstrom, 2002). The general technology can be viewed as a wireless barcode. Because of its flexibility, this technology provides the technical basis to manage individual items in a supply chain. Figure 3 illustrates the enabling factors this technology provides. First and foremost, no physical contact is needed to interact with the product items, allowing for increased handling efficiencies. Bar-code readers are no longer needed to update inventories, and theoretically, even checkouts could be eliminated. Recent research reports that checkout costs account for approximately 3 percent of retail revenue in supermarkets in the industrialized world (Hennessy, 2000). Currently some supermarkets are experimenting with selfcheckout capabilities. Wireless technologies using electronic payment methods could allow shoppers to walk out of the store without stopping at a checkout station, having their goods scanned automatically and their credit cards charged. This could lead to reducing (and possibly even eliminating) the entire process and cost of customer checkout (Chain Store Age, 1999). Identification of item level products also allows effective customization of products. In e-grocery retailing, wireless product identification can allow new offerings to customers in addition to making it easier to assemble and deliver the order. In the physical store, since products can be identified remotely, inventory could be managed from the distribution center. These capabilities allow for true VMI (Smaros and Holmstrom, 2000). Finally, this effective information sharing also allows for better control of the supply chain. When companies move from focusing on functional requirements to supply chain solutions, visibility of the supply chain increases and allows for

Source: A.C. Nielsen Company Ltd (1989)

own customers (section D). In addition, there would be market segments and customers they choose not to compete for (section E). If they are to gain market share, they must win some of the leaked market while keeping their own customers. Market leakage occurs in three main forms. First, there are customers that were competed for but lost (section C). Second, there are also those customers who are not covered by the distribution channel (i.e. stores not in the area) which are represented by section B. Finally, customers in section A are lost because product models or brands they would like to buy are not offered. In today’s market a company’s strategic choices are more limited. Specifically, section E (customers not competed for at all, such as product categories not carried) is a limited market since competition has grown more acute. Section B is also limited because grocery chains have now expanded into many, if not most market areas (i.e., market saturation). Thus, section A is the segment of the market that is most easily accessible to grocery stores, garnered by expanding the product/model variety carried in a product category. However, grocery stores have finite shelf space, and that shelf space typically is the only inventory storage available to the store. On one hand, they must keep enough product on hand to avoid stockouts, or they will lose more customers (section C). On the other hand, the only way to provide more products and model variety is to limit the amount of shelf space each individual product takes up in the store. If grocery store retailers are to be able to manage these varied demands, they must be able to identify product on an individual item 136

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

Figure 2 Market leakage analysis

Figure 3 The enabling steps of item level supply chain management

and Albertsons (Salmon, 2003) grocery store chains expressed their desires for the benefits that RF technologies can provide. Automating inventory replenishment decisions would result in significant cost savings to the stores, by freeing up time that department managers spend walking the floor

greater control and efficiencies. In the case of grocery stores, store inventory could be managed from the distribution center. This is something that many grocery supply chain managers have wanted for some time. In personal interviews for this research, managers from both Kroger (Carson, 2003) 137

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

checking the shelves to see what is needed. The managers stated that this time would be better spent on in-store customer service activities (Carson, 2003; Salmon, 2003). If the inventory is managed from the distribution center (DC), and updates are available in real-time, then stock-outs should be significantly reduced. According to one report, stock-out situations cause a 3 percent loss of revenue through lost sales, and 53 percent of the time, stockouts result from problems with the store ordering process (Supermarket Business, 1996). In comparison, only 8 percent of stockouts are caused from inventory being delivered, but not shelved. Given the promising benefits of wireless product identification, we believe that RFID provides these benefits and that its costs are near the threshold to be widely used in the grocery industry.

automatically throughout the supply chain. There are various ranges in the frequency for reading the passive or active tags. In general, the data rate is slower with lower frequencies and faster with higher frequencies (Schuster, 2004). The key factor for widespread RF tag usage is cost. In 2000, RF tags cost about US$1 for a single tag. Currently the cost of RF tags is between 15 and 20 cents. When the cost drops to around 5 cents, experts believe that demand will really take off (Donovan, 2003). Since the semiconductor industry has seen a few years of 50 percent drops in average selling prices, it is likely that RF tags will reach this price point in two or three years. In fact, BusinessWeek recently reported that Hitachi has redesigned the antenna for RF tags, and hopes to sell them for as little as four cents each by 2006 (Kunii, 2003). It is further speculated that as the demand for tags increase, so too will the demand for tag readers. The cost of the readers is anticipated to be around US$150 (Schuster, 2004). While we have already identified some general areas of application of wireless technology to the grocery supply chain, there are specific issues that must be addressed when implementing new technology in the grocery industry.

RFID technology: background and explanation RFID is a very compact technology. About as large as a pinhead, RFID tags (or simply RF tags) consist of two main components: an antenna and a chip that contains an electronic product code (EPC). The EPC standard was developed by the Auto-ID Center, a partnership founded in 1999 by five leading research universities (anchored by the Massachusetts Institute of Technology), and nearly 100 leading retailers, consumer products makers, and software companies (Niemeyer and Pak, 2003). RF tags can provide more information than traditional barcodes. For example, not only can an RF tag tell what the product is, but also when and where it was made, where its components came from, and when they might perish. Another benefit is that unlike bar codes, which need line-of-sight scanning to be read, RF tags also act as passive tracking devices, broadcasting a radio frequency when they pass within yards of a special scanner. RFID technology is robust and has been used for some time in harsh manufacturing environments (Gould, 2000; Murray, 2003). Other applications include car toll tags and securityID badges. Recently, firms have been focusing on their use within supply chains (Karkkainen and Holmstrom, 2002). Currently Wal-Mart and Home Depot are among the companies that are conducting tests to determine if the cost savings from increased inventory accuracy are enough to warrant placing RF tags on every item (Bruce, 2002). These investigations, as well as others, suggest that widespread RF tag use is very near. RF tags have been used for several years in Mobil Gasoline’s Speedpassw system, where the customer passes a small key fob within a few feet of the gas pump to turn on the pump and automatically charge their credit card (Ellis and Lambright, 2002). This approach saves time for the customers and lowers costs for the company. With RFID capability, each store can know exactly what its in-stock inventory is in near-real time. In addition, the distribution centers and warehouses will also have access to current store inventory levels, along with demand trend information, through the use of EDI capabilities. The goal of practitioners and researchers for true quick response (Fernie, 1994) should finally be feasible. The tag itself is one of two parts of the RFID technology (and network) – the second being the tag reader (also called scanner). RFID scanners sense the items and can query information about each item. Because the network is always on, real-time information about the item can be traced

The future of the grocery industry and technology constraints As we have pointed out, implementation of ARP techniques has been of limited value because grocery retailers have not changed their forward buying practices. If they are to operate more efficiently, they must adopt technology that will allow them to use their traditional marketing techniques but still decrease costs through reduced inventories. Cohen (2000) outlines how conditions for effective grocery supply chains must change in terms of personnel, communications and inventory reduction, as shown in Table II. Cohen argues that technology must be the integral part of how manufacturers, warehouses, and retailers communicate with each other. Of specific interest to our research is: 1 communication networks will allow flow-through inventory and JIT delivery between manufacturer and retailer; 2 on-hand shelf inventory in the retail store will be linked to the store’s main computer, thus eliminating the use of inaccurate point of sale data; 3 automatic computer reordering will maintain correct inventory levels; and 4 manufacturers will develop modified packing methods and units to minimize the amount of back-stock levels at both the warehouse and retail levels. Issues 1 and 2 are interrelated. The accurate JIT deliveries, envisioned in issue 1, rely on knowing precisely what the onhand shelf inventory is. Currently, point-of-sale data is not accurate partly because store check-out-clerks do not scan accurately. For example, when they see nine cans of assorted soup, instead of scanning each separately, they might scan one can and multiply the cost by nine to save time at check out. Data entry errors and theft also contribute to inaccurate inventory records. Thus, some technique is needed to remove the human error from inventory information, and that seems to be RFID. Issue 3 is easily implemented with current computer capabilities. However, to be effective it must have accurate information on current inventories. This leads to various 138

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

Table II Pathway to the future Current conditions

Future conditions

Tools and techniques that will get us there

Personnel A few highly knowledgeable people: most workers are minimally trained and educated Limited resources of employees due to cutbacks and downsizing “Command and control” management style

Formation of production teams Highly trained personnel and cross-training within organization Management by integration and self-control

Team concept and management Theory Y use of management techniques Behavioral systems engineering Ergonomics and occupational biomechanics Cognitive engineering design Total quality management

Incorporated use of information systems and computers networks to establish rapid communication between retailer, warehouse and supplier to expedite supply requirements, pricing information changes and production problem resolution

Flow process analysis Manufacturing system optimization Operations research Systems management Manufacturing information systems Neural networks Critical path methods/program evaluation and review techniques

Minimum inventory levels on shelf at retail level. Limited or non-existent inventory levels at retailer and warehouse Production scheduling more closely linked to actual requirement of marketplace Manufacturer’s restructured packaging methods for smaller unit quantity per case to help minimize back-stock levels at warehouse and retailer. Improved methods to streamline process and allow for increased unit volume sales

Just-in-time inventory Integrated logistics planning Cost management Engineering economy Regression and analysis of variance Linear and non-linear optimization Production and inventory control Stochastic processes Simulation modeling Dynamic programming Probability applications Production engineering Work measurement Queuing theory Markov chains

Communications Overuse of printed media leading to large waste of paper Delays in ordering stock items due to lack of personnel and lack of feedback to warehouse and manufacturer Delays in price comparison and updates due to long lead times between change and final resolution Inventory reduction Large inventory levels on shelves and in storage at retail level and in warehouse Production difficulty at manufacturer due to excessive or insufficient manufacturing rates

Source: Cohen (2000)

Certain guidelines should be followed when implementing technology within the grocery environment: . Specifically, the system must not prevent the practice of forward buying (since retailers have shown they will not give it up). . In addition, the system must allow for more efficient shelf space utilization, thus allowing for a greater variety of products to be displayed. This will allow grocers to grab some of their leaked market share. . However, this reduced shelf inventory cannot have the negative impact of increasing stockouts. Rather, forecasting must be accurate enough or replenishment must be quick enough so that high service levels are maintained. . Next, the impact of any modified packing methods must improve supply chain performance. . Finally, the system must be able to withstand “shocks” in demand and react quickly. These shocks, while infrequent, do occur. For example, a recent Homeland security alert caused a run on duct tape. Unexpected bad

topics related to issue 4. Namely, once accurate information is available, companies can move from focusing on functional requirements to supply chain solutions, increasing the visibility of the supply chain and allowing for greater control and efficiencies. In the case of grocery stores, store inventory could even be managed from the distribution center. In that case, grocery stores can take advantage of more efficient reordering policies. This might allow for smaller JIT deliveries, which would allow average inventories to be substantially reduced with minimal impact in customer service levels. With more frequent deliveries, stores might also experiment with smaller case pack sizes. Smaller case pack sizes hold the possibility to reduce both store shelf inventories and warehouse inventories. While reducing warehouse inventories decreases costs, reducing average store inventories is important because this allows stores to make more room on the shelves for additional product varieties. This would allow firms to minimize the category A and C market leakage that was discussed earlier while providing customers more choices 139

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

weather can cause a run on milk and bread. The effect of these demand spikes on the reduced in-store inventory must be assessed.

As for entrenched business practices, two key factors were pinpointed in our discussions with grocers. As mentioned earlier, one of the reasons for ARP failures is the desire of grocers to continue with forward buying practices. Research needs to be conducted to see how the use of RFID can be integrated with forward buying if inventories are being managed by the DC. That brings up the second issue that is loss of control by the individual store managers. This is a distinct issue that must be addressed by the grocery chains. However, some corporate supply chain managers believe that it would be easier to implement a system like this because it would be driven by the DC (Carson, 2003; Salmon, 2003). From the view of management, this eases the transition because many store managers are hesitant to learn new technology and operational styles. This is because most managers have moved up the ranks from bag boy. Their focus is instead on customer service and interaction with the customers. Moving ordering decisions to the DC frees up time for store managers to focus on what they would rather do: interact with the customers. This is the traditional view held in process innovation research by Zmud (1984). It is also suggested, by the latest research in innovation, that the best way to implement a disruptive process innovation of this type is to “. . . centralize the function. Legacy processes are typically embedded in each of the enterprise’s operating units. Bring them together under a shared-services model, and put an operations-focused manager in charge. This will free resources that are performing duplicate functions” (Moore, 2004).

Framework for future research areas Given the needs and guidelines that have been identified, three fertile areas for future research are suggested: modeling, implementation, and daily operations. Research using modeling On the modeling side we propose six general areas/questions that lend themselves to the operational modeling techniques widely used by researchers: 1 If retail store inventory is maintained by the DC, what inventory models should be used? 2 If store inventory is maintained by the DC and they see a need for a product, but that product is currently unavailable, they can substitute a similar product. How would this effect store inventory and service levels? 3 In order to provide greater variety in a limited shelf space, smaller case packs could be used. How does case pack size affect supply chain performance? 4 How does frequency of delivery affect supply chain performance? 5 How does the distribution center’s access to current retail store inventory data affect responsiveness and service level? 6 How well can RFID-based supply chains handle extreme demand? In other words, are supply chain results affected by the existence of occasional outlier demands at the stores?

Research on daily operations Within the military, it is said that no plan lasts longer than the first contact with the enemy. In a similar vein, once an RFID technology plan is implemented, grocers must begin to address the daily operational issues that may change the assumptions of the plan. For example, as mentioned earlier, Kurt Salmon Associates argued that forward buying practices are inefficient and if removed could save around $10 billion (10.8 percent of sales turnover) in the dry grocery chain. However, grocers seem to be hooked on forward buying. How would this reliance on forward buying impact RFID use? On one hand, the research may show that RFID use allows firms to better adapt to varying demands and inventories brought on by the use of forward buying. On the other hand, experience has shown that once a technology is implemented, business people search for new ways to take advantage of it. This adaptation may have unforeseen consequences on the use of RFID. Another daily operations issue that must be addressed is security. Shoplifting is a serious problem in the retail industry. Every year, organized retail crime causes retail loses of $12 billion to $35 billion (Hayes and Roberts, 2003). One method is to stuff stolen merchandize into shopping bags lined internally with duct tape (the duct tape shields the security tags on stolen merchandize from sensors and scanners). An average “booster” steals purely for profit and will steal $5,000 on an average day. Many will make $125,000 per year on shoplifting (IOMA, 2003). Grocery stores implementing RFID must respond to this threat. The costs for increased security measures may somewhat offset the benefits of RFID. But to what degree will these benefits be impacted?

The results of this type of simulation research have a direct impact of category types A and C of the leaked market problems discussed previously. For example, a grocery’s entire inventory is on their shelves, so shelf space is at a premium. The use of RFID might allow grocery stores to keep smaller quantities of each product on their shelves while still retaining high service levels. This would allow them to offer more product lines without expanding their stores, which in turn reduces the amount of leaked market from category A and C customers. Research on RFID implementation In addition to modeling-based research on operational decisions, researchers need to investigate how to best implement RFID technology in the grocery industry. Figure 4 shows the various barriers to technology adoption. In applying this framework to the grocery industry, we have already seen that there is a compelling reason for grocery stores to manage their operations more efficiently, despite the failure of ARP implementations. The magnitude of effort required to adopt RFID is no greater than that required for ARP implementation. Concerning cost/benefit justification, the fact that Wal-Mart is moving ahead with this implementation (Boyle, 2003) should put downward pressure on the cost of the technology. In spite of RFID’s promises, adoption of any new or advanced technology (and the management thereof) includes risks and uncertainty. Further research on RFID applications in the grocery industry, such as the research issues proposed in this study, can help to mitigate many of these risks. 140

Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

Figure 4 Barriers to technology adoption

Summary

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RFID is an intriguing technology that has garnered a great deal of research interest. However, that research has primarily focused on RFID’s impact on general supply chain issues; failing to place the discussion within a specific business domain. This is necessary because the strategic environment of any business impacts the applicability of any technology. In this paper we have considered RFID research within the context of the grocery industry. We have outlined the market drivers that affect the way the grocery industry approaches RFID. We have also outlined specific areas of research on RFID that should be undertaken to better provide the grocery industry with managerial insights into this technology’s application. These research areas include research using modeling techniques, RFID implementation and the impact of RFID on daily operational issues. We believe that the adoption of RFID technology and its attendant supply chain management techniques holds the promise of being more successful than the ARP implementations of the 1990s. This should encourage research into this area, for as researchers provide insights into these issues, the grocery industry can immediately put the findings into practice.

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Future impacts of RFID on e-supply chains in grocery retailing

Supply Chain Management: An International Journal

Edmund Prater, Gregory V. Frazier and Pedro M. Reyes

Volume 10 · Number 2 · 2005 · 134 –142

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