Nowadays, competitive business environment has forced companies to satisfy customers who demand increasing product variety, lower cost, better quality, and faster response (Vondrembse, Uppal, Huang, & Dismukes, 2006). Therefore, offering higher product quality is the main requirement to gain global market share. In addition, companies operate at the lowest possible cost in a competitive market to generate substantial profit (Lau, Pang, & Wong, 2002). These objectives should deal carefully in the supplier selection process, since it enables companies to reduce purchasing cost and improve corporate competitiveness (Demirtas and Ustun, 2008 and Ghodyspour and O’Brien, 2001).
However, selecting the right supplier is always a difficult task for many purchasing managers (Liu & Hai, 2005). Managers should realize that no supplier can satisfy all their requirements. Commonly, one supplier satisfies one part of the requirements and another supplier satisfies the other part of the requirements. Therefore, the company has to evaluate and select all possible supplier candidates to various requirements or attributes (Ghodyspour & O’Brien, 1998). These requirements are composed by qualitative as well as quantitative attributes, and the company has to choose the most suitable supplier as its supply chain members.
In Dickson (1966), proposed quality, cost and delivery performance as three of the most important attributes. Since then, many conceptual and empirical studies for supplier selection have been reported (Verma & Pullman, 1998). In general, there are two types of supplier selection problem, single sourcing and multiple sourcing (Demirtas & Ustun, 2008). Many studies proposed to deal with single sourcing problem, such as the well-known AHP (Barbarosoglu and Yazgac, 1997, Bhutta and Huq, 2003, Çebi and Bayraktar, 2003, Ghodyspour and O’Brien, 1998, Khurrum and Faizul, 2002, Korpelaa et al., 2001, Liu and Hai, 2005, Mohanty and Deshmukh, 1993, Narasimhan, 1983, Nydick and Hill, 1992, Sarkis and Talluri, 2000, Sarkis and Talluri, 2004, Weber and Current, 1991 and Yahya and Kingsman, 1999) and ANP (Meade and Presley, 2002 and Sarkis and Talluri, 2000), have been used. For multiple sourcing problem, scholars tend to use linear weighting methods (De Boer, Van der Wegen, & Telgen, 1998), mathematical programming (MP) techniques (Akinc, 1993, Barbarosoglu and Yazgac, 1997, Benton, 1991, Bender et al., 1985, Current and Weber, 1994, Degraeve and Roodhooft, 2000, Karpak et al., 1999, Narula and Vassilev, 1994, Rosenthal et al., 1995 and Sadrian and Yoon, 1994), and the combination of ANP and MP techniques (Demirtas & Ustun, 2008). The bundling problem can be done by using MP techniques (Rosenthal et al., 1995 and Sarkis and Semple, 1999), and this study integrates ANP and mixed integer programming to select the best supplier when they use product bundling strategy and defines the optimum quantities among the selected suppliers.
The context of this paper is the notebook industry in Taiwan, since it is the 4th largest manufacturer of computer-related products. Seventeen items of IT products made in Taiwan occupy over a half of the world’s market. Among them, notebook computers occupy 61% of the world’s market; main board, 75%; and LCD monitors, 61% (Lu, 2005). Although these facts mainly contributed to Taiwan’s OEM industry, there is a growing sales trend that some of the Taiwanese notebook producers succeed in selling under their own brand. Due to a rapid technology change and high competition among the Taiwanese notebook manufacturers as well as abroad competitors, selecting suppliers is one of the most important steps to offer innovative products with high quality and reasonable price.
Relevant literature is reviewed in the section that follows. This article develops the ANP model based on the discussion results among practitioners and experts, which is followed by collecting the data by using Delphi method. Thereafter, the ANP results were used as coefficients of an objective function in MIP to allocate order quantities if the supplier uses bundling strategy. The ANP as well as MIP procedure is illustrated through numerical results based on experts’ interview from Taiwan’s notebook producers. The data were used to demonstrate the ANP and MIP application and examine its effectiveness. Finally, the conclusions and suggestions of the paper are described.
