A well-designed supply chain management (SCM) system is important for improving competitive advantage in an era of international economics and rapidly developing information technology (Li & Wang, 2007). The gap between product quality and performance is closing with intensifying competition in the global market. Scholars and industries consider how to manage enterprise operation more efficiently in this competitive arena (Sarmah, Acharya, & Goyal, 2006). Effective supplier decisions are significant components for productions and logistics management in many firms, and a correct forecast is crucial for the electronic related industry (Hsu, 2003). In other words, accurate supplier forecasts help enterprises find proper supply chain partners and consequently enhance organizational performance.
The success or failure of supply chain management depends upon a suitable SCM system and appropriate suppliers. Many firms apply collaborative commerce by establishing strategic partnerships with suppliers, and involve them in the early stages of product research and development (Araz & Ozkarahan, 2007). Experts agree that supplier selection is one of the most important functions of a purchasing department, helping businesses save material cost and increase competitive advantage (Saen, 2007).
Supplier selection also acts as the pivotal role in an enterprise’s transport business development, with future competitive ability in an industrial environment (Jayaraman, Srivastava, & Benton, 1999). Only those suppliers who meet the firms’ needs can provide material and parts with comparative low cost and high quality. In an effective supply chain, enterprises must first find outstanding suppliers, and then establish long-term partnerships with these suppliers to increase enterprises’ competitive abilities (Shin, Collier, & Wilson, 2000). Today’s business environment emphasizes supplier relationship development for sustainable enterprise management (Krause & Ellram, 1997). Considerable research supports supply chain performance as highly influential in enterprise competitiveness (Quayle, 2003 and Sako, 2004). This finding has lead to considerable academic and real world interest, regarding supplier development strategies.
Many methods have been used in predicting industrial performance, including the Grey theory (Lin & Yang, 2003), and the two-stage fuzzy piecewise regression analysis method (Huang & Tzeng, 2008). Ni, Xu, and Deng (2007) applied a method with extended Quality Function Deployment (QFD) and data mining to investigate supplier selection (Ni et al., 2007). Li and Wang use a grey-based decision-making method to deal with fuzziness in supplier selection (Li & Wang, 2007). Pi and Low propose a supplier selection method that use Taguchi loss functions and the Analytic Hierarchy Process (AHP) to obtain weights of major criteria (Pi & Low, 2006). However, the method needs more data, such as customer data, maintenance records, and information from different marketing areas. Gencer and Gurpinar adopted the Analytic Network Process (ANP) to investigate supplier selection implementation in an electronic firm. Compared with AHP, ANP includes interaction among criteria (Gencer & Gurpinar, 2007).
However, few methods and studies have capable of demonstrating the relationship between factors that might affect SCM performance. Therefore, this study pioneer in using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method to select which supplier suit enterprises. The advantage of the DEMATEL method is the capability of revealing the relationship between these factors which influence other factors in supplier selection. This study obtains direct and indirect influence among criteria using the DEMATEL technique, and computes the causal relationship and strength among supplier selection factors. The DEMATEL technique does not need large amounts of data.
This paper is organized as follows: In Section 2, we present a literature review of SCM and Supplier selection. Section 3 describes the methodologies of fuzzy DEMATEL. Section 4 outlines an empirical study to show the process of fuzzy DEMATEL method to determine selection criteria of SCM supplier. Section 5 carries our conclusions and suggestions.
This study uses the DEMATEL method to analyze and forecast electronic industry suppliers. The results of this study can hopefully help enterprises precisely forecast which suppliers are suitable by focusing on crucial factors found in this study. Our research results show that stable delivery of goods has the greatest influence among the criteria for selecting suppliers. Although it was not the number one factor with the highest value of evaluation of significance, it can effectively help businesses to choose SCM suppliers. According to analysis results, stable delivery of goods could directly or indirectly influence many other characteristics such as product quality, product price, technology ability, service, delivery performance, lead-time, reaction to demand change in time, production capability and financial situation. This research suggests that businesses wanting to forecast and select suppliers should first observe which suppliers possess characteristic stable delivery of goods, since this evaluation criterion greatly influences other factors. Businesses generally pay close attention to product quality, product price and delivery performance when selecting or evaluating suppliers. This study however finds that stable delivery of goods is the real source that influences other factors, perceived as the most important factors by experts. A supplier with stable delivery of goods may have higher product quality and better delivery performance.
This study finds criteria that influence supplier selection, and constructs the strategy map among these criteria using DEMATEL. The strategy map finds interdependencies among these criteria and their strengths. Businesses typically evaluate select supplier criteria according to product quality, price, services and delivery performance of the supplier. The current study finds that “technology ability”, “stable delivery of goods”, “lead-time”, and “production capability” criteria are more influential than other evaluation criteria. These potential evaluate criteria could help businesses forecast appropriate suppliers. Businesses wanting to forecast suppliers should first observe suppliers according to evaluation criteria of ranking importance including “stable delivery of goods”, “technology ability”, “production capability” and “lead-time”. The results of this study could provide businesses with evaluation criterion to sieve out suitable ones from a large number of suppliers according to this factor. This study suggests that the fuzzy DEMATEL method be extended and applicable to many businesses which must deal with complex criteria problems that need to use group-decision-making in the fuzzy environment.
This research suggests further studies in order to extend the scope of this study. For example: the addition of a green supply chain could be explored in future studies. Such research could boost awareness of environmental protection from green design, green production, green purchasing, green products, green sales and marketing, green consumption to green living. Businesses could better maintain a balanced development within the economy and the environment. International electronic companies have been driven by green necessities for their products, reengineering green design and green products. Therefore, the green supply chain that is already a hot topic could become the new trend of the future.
