انتخاب تامین کننده سبز با استفاده از چارچوب AHP-Entropy-TOPSIS Green supplier selection using an AHP-Entropy-TOPSIS framework

Between 1979 and 2010, China’s real gross domestic product (GDP) growth averaged over 9.9 per cent per annum and has hardly slackened since. Unfortunately, these remarkable economic results have come at the expense of soaring industrial effluence which Chinese authorities have yet to reverse. This is despite billions of yen of investment resulting from a succession of major government anti-pollution initiatives (Chiou et al., 2008) including, for example, the Administrative Measure on the Control of Pollution Caused by Electronic Information Products in March 2007 (Tsai et al., 2013) . It is estimated that air pollution, on its own, is responsible for an estimated 350,000-500,000 premature deaths in China every year (Chen et al., 2013). As poisoning of the country’s air, water and soil continues to take its toll, it comes as no surprise that young Chinese consumers are increasingly drawn to “green”/environmental measures and alternatives. Hence, the growing importance of green supply chain management (GSCM), which, in effect, promotes cooperation amongst environmentally friendly suppliers to their long-term trading advantage (Rao, 2002). Operations research methods have become increasingly prevalent in GSCM-related analysis: in particular, decision support systems and inventory management feature prominently in an e-logistics study by Sarkis et al. (2004); analytic network process and portfolio modelling are used by Zhu et al. (2010) to evaluate suppliers’ relative power and performance and structural equation modelling is exploited by Lee et al. (2012) to provide evidence that GSCM practice influences business performance indirectly – through the mediating variables of operational and relational efficiency. Most recently, data envelopment analysis has been used by Bai and Sarkis (2004) to identify key performance indicators (KPI’s) influencing suppliers’ sustainability performance, whereas resource-based, institutional, stakeholder and social network perspectives have been adopted by Varseyi et al. (2014) to assess supplier’s sustainability performance. In contrast, Bai et al. (2012) provide an assessment of supplier performance using grey-based neighbourhood rough set theory. Building on this diverse analytical experience, the study now described involves the use of analytic hierarchy process (AHP), Entropy and technique for order preference by similarity to the ideal solution (TOPSIS) for optimising green supplier selection (Hu and Hsu, 2006; Seuring and Muller, 2008).To assist with the latter, an index system was developed, which integrated traditional supplier and environmental supplier selection criteria simultaneously. A case design approach was adopted for the research – data being provided by a People’s Republic of China (PRC)-based small and medium-sized enterprise (SME) – see Zhu et al. (2005) on unrelated PRC-based GCSM research. The next section reviews recent literature on GCSM, supplier selection index systems and supplier selection models. Following on, data collection methods are detailed and the case company and analytical approach introduced.