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考量買方風險接受態度的供應商選擇：結合效用函數的簡單多屬性評比方法
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1. Introduction
Over the last few decades, supply disruptions have become more prominent. Supply
disruptions may be due to natural (e.g., earthquakes or hurricanes) or manmade (e.g., power
breakouts or labor strikes) disasters (Sawik, 2013). These disruptions would significantly
affect the operations of companies in a supply chain. For instance, the earthquake and
tsunami that struck Japan on March 11, 2011, caused several manufacturers to be disrupted
for a few weeks. Companies such as Nokia and Apple, were also affected because the
suppliers of their chips are located in Japan. The flood, which hit Thailand in 2011, also
caused a tremendous commotion in the hard-disk drive industry. To mitigate impacts of
supply disruptions, companies try to shift to an agile and resilient supply chain by adopting
various strategies (e.g., information sharing, supply portfolio and postponement) and making
them part and parcel of their business continuity plans (Lu, Tsai, and Chen, 2012).
Supply portfolio is one of the methods for achieving agile and resilient supply chains in
response to supply disruptions. HP, for instance, used this method to reduce its supply risks
(Billington, 2002). A key for making a successful supply portfolio is effective evaluation and
selection of suppliers, and various methods have been proposed in the literature in this
regard. Traditional ways of evaluating and selecting suppliers considered mainly cost/price
of products. As companies realized that cost/price should not be the only attribute to be
considered, other attributes such as quality, management, manufacturing capability,
reliability and attitude, were also taken into account during supplier selection (Cheraghi,
Dadashzadeh, and Subramanian, 2004).
This paper presents an approach that integrates the simple multi-attribute rating
technique (SMART) (Edwards, 1977; Olson and Wu, 2010) with the utility theory (Keeney
and Raiffa, 1993) for ranking effectively a set of suppliers. As indicated in the references
(e.g., Barla, 2003; Edwards, 1977; Huang and Keskar, 2007; Olson and Wu, 2010), SMART
considers simultaneously multiple attributes of each alternative in an integrated framework
and provides one of the easiest tools for multi-criterion (or multi-attribute) decision-making
(MCDM). Although other MCDM methods, such as data envelopment analysis (DEA),
mathematical (multi-objective) programming, analytical hierarchy process (AHP) and
analytical network process (ANP), have also been employed to deal with the supplier
selection problem, these approaches are generally more complex and require more
computational efforts than SMART. Industrial experiences have shown that procurement
managers may prefer simple but effective approaches for selecting their suppliers (e.g.,