افزایش اثربخشی تصمیم گیری انتخاب تامین کننده در مرحله اولیه توسعه محصول جدید : یک روش ترکیبی فازی با در نظر گرفتن عوامل استراتژیک و عملیاتی به طور همزمان

The majority of the existing supplier selection approaches obtained their optimal solutions based on the operational metrics. This study considers the strategic and operational factors simultaneously to secure the efficacy of supplier selection (VS) on initial stage of new product development (NPD). We suggest strategic factors come from the supplier’s management system itself (i.e., customer-, long-term-, and process-oriented criteria) while the related performances indices of supplier constitute operational factors (i.e., producer-, short-term- and outcome-oriented criteria). The work adopts supplier’s process capability indices (PCIs) and process yields as operational factors to estimate their quality capabilities. The business process-oriented criteria related with the performance of business process improvement (BPI) are employed as the strategic criteria for supplier assessment visit. A fuzzy approach with supply risk consideration is employed then to aggregate the total scores of individual suppliers objectively. An empirical case study is performed to demonstrate the efficacy of the proposed system and to identify the best potential supplier(s) for further development. The results and processes of the case study also provide interesting managerial implications. The derived application of Herzberg’s two-factor theory to the realm of supplier selection is discussed as well.

Worldwide competition in global economies has posed significant challenges to companies wanting to fulfill the continuously changing requirements of the cost reduction, speedy time-to-market, and customization; they place increasing emphasis on supply chain management (SCM) and establish a sounder strategic alliance against competitors. Individual firms no longer compete as autonomous entities but rather by joining a supply chain alliance. Members in the supply chain always forge stronger alliances to compete against other supply chains (Lin & Chen, 2004). One of the competencies essential to supply chain success is an effective purchasing function (Cakravastia and Takahashi, 2004 and Sarkis and Talluri, 2002). In most industries the cost of raw materials, component parts, and services constitutes the main cost of a product, in some cases it can account for up to 70–80% of the product costs (Ghobadian et al., 1993 and Weber et al., 1991). Handfield, Ragatz, Petersen, and Monczka (1999) concluded that product design “lock in” as much as 80% of the total cost of a project, and that supplier involvement in buying firm’s new product development (NPD) stage could reduce the development time and cost of a project. Suppliers often possess much of this critical expertise. In recent years, firms have downsized, focused on core competencies, and attempted to achieve competitive advantage by leveraging their strategic suppliers’ capabilities and technologies (Kannan and Tan, 2002, Perona and Saccani, 2004 and Tracey and Vonderembse, 2000). Improvements in product quality, quicker integration of technological breakthroughs, and shorter DPD lead times are the expected outcomes of supplier involvement. Although it is clearly important to keep production costs as low as possible by some improvements, in many ways, attempting cost saving at the manufacturing phrase is analogous to closing the stable door after the horse has bolted. Supplier/vendor selection (VS) in industry is a group decision-making (GDM), cross-functional problem, frequently solved by a nonprogrammed decision-making process, with long-term commitment for firms. Researches found that the growing importance of cross-functional team involvement in the selection and evaluation of suppliers plays a significant role in the overall performance of a buying firm (Muralidharan et al., 2002 and Pearson and Ellram, 1995). Therefore, a good method for aggregating the various influences of individual opinions, evaluations, and ratings from multiple decision-makers (DMs) must be considered in VS problems. VS is a decision-making problem at the strategic management level with a semi-structured process (Chou, Shen, & Chang, 2007). The inherent imprecision nature of the relevant information and decision process from such types of problems is broad, has foresight, is nonrecurring and is external. The majority of these factors are evaluated by human perception and judgment, which cannot be quantified precisely. In addition, exclusive the straight re-buy situation, potential suppliers frequently lack a directly proven track record for buying firms. As such, VS at the initial NPD stage typically involve the vagueness inherent in linguistic assessment and multiple criteria/attributes decision-making (herein namely MCDM) processes. Approaches employing only exact numerical (crisp) values cannot support decision-making procedures for such evaluation problems. Fuzzy set theory (FST), as pioneered by Zadeh (1965), which allows for vague boundaries, provides a mechanism to utilize fuzziness in subjective or imprecise determination of preferences, constraints, and goals (Kahraman et al., 2003 and Yager, 1982). The rationale behind this approach is that decision-making process often involves gray areas where the term “maybe” is more appropriate. FST is incorporated into many concepts and procedures when enhancing their capabilities to treat MCDM problems in vague environment (Kuo and Chen, 2004, Chang and Wang, 2006 and Wang and Elhag, 2006). The most important task for buying firms on formulating VS criteria is assessing the key competitive factors in their industry and translating these dimensions into VS criteria. Strategic management decisions influence the relative importance of the various criteria in the VS process (Talluri and Narasimhan, 2004 and Weber et al., 2000). The choice and the number of criteria to be included in the VS process must be cautiously determined in order to represent the buying firm’s competitive strategies (Sarkis and Talluri, 2002 and Talluri and Narasimhan, 2003). The majority of VS models in existing publications ignore the fact that evaluation criteria must be in alignment with a firm’s strategy. The framework based on analytic network process (ANP) employed by Sarkis and Talluri (2002), the combined data envelopment analysis (DEA) method proposed by Talluri and Narasimhan (2004) for discriminating vendor strategic capabilities and performance metrics are to some extent relevant in this strategy-oriented context. This study is devoted to find a useful hybrid fuzzy MCDM approach considering strategic and operational factors simultaneously to select the strategy-oriented qualified supply chain partners on the initial stage of NPD with multiple DMs in a dynamic and uncertain environment. The proposed methodology has an intention of having the following characteristics in practice. The formulations of multiple criteria must be in alignment with a firm’s operations management and/or supply chain strategy. The model can treat VS problems on the initial NPD stage in which the potential supplier’s directly proven track records are not sufficient and the weights of the multiple criteria and the ratings of the alternatives can be associated with fuzzy values. The adjustment mechanism toward supply risks of individual potential suppliers must be considered in the VS model objectively. Simplify the problem to save subsequent implementation planning and evaluation cost while making decisions effectively without significant loss of quality in the dynamic and uncertain decision-making environment. The remainder of this paper is organized as follows. Section 2 discusses the related literatures. Section 3 presents a conceptual framework and illustrates the procedures of this model we proposed. Section 4 using an empirical example to perform the model’s efficacy and highlight the managerial implications based on the case analysis. The derived applications of Herzberg’s two-factor theory in VS realm are discussed as well. Conclusions and suggestions are finally drawn in Section 5.

The fuzzy strategy-oriented with supply risk consideration approach we proposed considers the strategic and operational factors simultaneously to secure the efficacy of supplier selection on the initial stage of NPD under GDM situation. Our study adopts the process-oriented criteria related with the performance of BPI as the strategic factors for supplier’s assessment visit. On the opera- tional dimensions, the PCIs of different but comprehensive quality characteristics are employed to evaluate and integrate the process yields and ratings of individual supplies. The novel points and merits of the proposed system are fivefold: First, it is the only method that considers the strategic and opera- tional dimensions simultaneously on initial PND stage for VS prob- lem. Second, the underlying concept of the proposed approach is simple and comprehensible, and the computation involved is effi- cient. Third, we derived the applications of Herzberg’s two-factor theory from organization behavior field into the realm of MCDM, as such the empirical VS case in this work. The managers of case company do agree that Herzberg’s two-factor has the function for identifying and clarifying the strategic and operational metrics more clearly and easily. Fourth, the proposed approach can adequately handle the inherent uncertainty and imprecision of the human decision-making process and reduce the complexity of traditional methods for ranking fuzzy numbers. Fifth, the con-ventional FRS combined with FST has been extended to the domain of the VS in GDM processes and vague environments. The proposed model creates a realistic decision procedure. The architecture of this work can be applied to other management fields, especially on the decision-making problems with semi-structured and unstructured decision process, such as business strategy selection, high level personnel selection, and project management. These merits of our proposed system can facilitate its use in practical sit- uations for making effective decisions. Some areas that merit future research are as follows: (1) Devel- oping a generalized methodology or algorithm for breaking down a specific business or operations strategy into an associative VS cri- teria structure. (2) Future research also could adopt this approach to examine and develop a generalized model for different buying situations, i.e., new task purchase, modified re-buy, and straight re-buy situations (De Boer et al., 2001). (3) The illustrated empiri- cal case of this study belongs to the 3C industry in Taiwan. To in- crease the external validity, further research could be undertaken in different industries and different scales.