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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.,