یک مدل برای بررسی تاثیر استراتژی های خرید بر سنجش SRM الکترونیکی مورد نیاز کاربر

Recently, business managers have touted supplier relationship management (SRM) as the next core competency and a source of competitive advantage. This suggests the need of an e-SRM installation. SRM domain involves relatively wide and complex business processes and without the support of IT, it would not be accomplished easily. As the Internet became popular and many firms were quick to launch e-SRM, however, the effect went farther than was expected. In particular, the fundamental is in the determination of user requirements, commonly considered to be the key to the success of system installation and often inappropriately planned. This study involves a strategy-based planning process to guide user requirements determination. Moreover, the implementation step in this process, identification of supplier selection criteria, has rarely been considered and the literature has only discussed it isolatedly for the choice of a supplier. Basically, the process includes three steps: define purchasing strategies, identify supplier selection criteria, and determine system requirements. Empirical results have indicated that purchasing strategies significantly influence the performance of user requirements determination.

The rapid growth of the Internet has fundamentally reshaped business structure and offered unprecedented business opportunities for e-commerce (EC). According to Forrester Research, business-to-business (B2B) e-business will soon reach $1.3 trillion, outpacing business-to-consumer (B2C) by a factor of 10. The compound average growth rate is estimated to reach a relatively high rate about 90%. Supplier relationship management (SRM) has been recognized as an important issue in B2B EC. The traditional view focuses on leveraging transaction-oriented processes to achieve the lowest purchase price while assuring supply. The fundamental assumption is that trading partners are interchangeable and encouraged to reduce cost due to fierce competition. Tremendous changes have occurred in supplier management practices during the last decade [16] and [35]. In the automobile sector, for example, all three U.S. manufacturers and most of their European competitors have launched programs to decrease their level of vertical integration, reduce their total number of direct suppliers, and move toward publicly declared strategic partnerships. This practice was basically built on a foundation of trust and commitment from trading partners [29]. Consequently, future competition will not only be firm-to-firm, but also strategic partnership-to-partnership [12]. However, while creating new value, partnerships are costly to develop, nurture, and maintain. In addition, they are risky, given the specialized investments they require. However, managers and business consultants believe that effective supplier relationships will offers firms competitive advantage [27]. In essence, the SRM domain involves relatively wide and complicated processes, including the management of numerous suppliers of raw material, parts, components, sub-assembly, etc., the delivery of various products’ quantity, value, and quality, and suppliers’ reputation, financial condition, and technical ability. The Internet has offered tremendous opportunities for developing web-based online interactive systems to support the SRM process (e-SRM) [9], [19] and [30]. Many firms rushed into e-SRM but the results were less than expected [1], probably due to lack of strategic planning to guide information requirements determination [4], [15] and [34]. This approach can be described as that a type of purchasing relationship with suppliers is once developed for a firm and as a result, shifts the paradigm of organizational buying behaviors and further creates a need for understanding the detailed procurement process. Obviously, purchasing strategies will have fundamental impact on requirements determination of e-SRM. Therefore, the solution proposed here aims at setting a well-planned and unique SRM strategy and further, upon which the determination of e-SRM system requirements is based. This would assure that system requirements is guided by or matched with marketing strategies of relationship building. This solution process basically includes three steps: define purchasing strategies, identify supplier selection criteria, and determine system requirements. Existing literature has not discussed the important role of purchasing strategy in developing an effective e-SRM. The further implementation step for this process, such as identifying supplier selection criteria, was only discussed isolatedly for choosing a specific supplier. There has been a lack of an integrated approach in literature to provide a specific requirement determination process of e-SRM. The techniques used to analyze the steps were also discussed. Finally, this framework was examined by an empirical study to understand its practical applications.

While SRM was recognized as an important issue in B2B EC, the selection of an ideal relationship with suppliers would be a major advantage to a firm and a way to achieve competitive advantage. This justifies the need for better supplier relationship management. SRM involves relatively complex business processes and without the support of IT, it would not be accomplished easily. Moreover, the Internet and communication technologies have increasingly become popular in support of SRM. This approach proposed a three-step process to effectively develop e-SRM: define purchasing strategies, identify supplier selection criteria, and determine system requirements. In general, the manufacturing firms in Taiwan balance a portfolio of different types of purchasing relationships rather than rely on only one type. Successful SRM practice, therefore, requires management of a portfolio of relationships with suppliers. There are significant differences in the choice of supplier selection criteria for various supplier relationships. The major implication for academicians lies in that the particular connection of purchasing strategies and supplier selection criteria for commonly determining user requirements of e-SRM is unique in literature. Moreover, this study contributes not only in developing a well-defined process of user requirements determination but also determining useful techniques to effectively implement it. In conclusion, the new approach fundamentally overcomes the impact of problem unstructured issues associated with SRM domain on user requirements determination of e-SRM. The implications for practitioners are as below. A strategy-base analysis is important because firms are able to adopt various purchasing strategies to match their various product characteristics, market competition, and supplier conditions. Thus, system development unit should start to communicate with relevant functional units to define the appropriate type of supplier relationship. Alternatively, system developers can approximately identify the purchasing strategies in terms of the firms clustered as high-tech sub-sector or traditional sub-sector in this analysis. Moreover, the emphases on supplier selection criteria, which are the underlying determinants of user requirements of e-SRM can, therefore, be determined from this analysis of the relationship between purchasing strategies and supplier selection criteria. Leverage and non-critical types of relationships both consider the price factor as one of the emphasis on selecting suppliers. Strategic and bottleneck types of relationships both consider consistency factor as one of the emphases on selecting suppliers. Finally, the user requirements for the particular e-SRM would be determined in a more efficient and effective way. Although this study has produced some interesting results, it has some limitations. First, although the response rate was low, systematic non-response bias did not exist in the sample; it is representative of the sample frame. Second, CIOs from larger firms were chosen to be the participants in this survey; however, some questionnaires might have been completed by subordinates and thus the data may include bias.