供應商選擇一直是供應鏈管理的領域中一個重要的議題，目前有關供應商選擇的研究，大多是以企業與供應商合作關係較穩定的供應鏈環境為主要範疇;而利用歷史資料預估供應商可能達交表現的作法也一直是常用的方法。但是在國內航太產業中，因為訂單的不穩定以及供應商對訂單的重視度低，導致企業與供應商無法建立長期穩定的關係，而企業在選擇供應商時，通常只單純以價格競標的方式作為選擇的依據。因此經常發生供應商因產能不足或製造能力不穩定而造成無法達交的情況，使企業在外包成本上大幅增加。基於上述原因，本研究欲以系統化的角度提出一個適用航太產業的第一階供應商選擇的機制，解決目前國內航太產業的外包問題，並能夠幫助企業與供應商之間建立長期夥伴的關係，以建立供應鏈體系的概念。本研究所提出的第一階供應商選擇的機制第一部分先以文獻探討蒐集有關供應商選擇的量度，同時透過專家訪談的方式了解航太產業的特性以及企業與上下游之間的合作關係並擷取相關量度，最後以平衡計分卡基礎理論補強其第一階供應商量度之完整性。第二部分則是將第一部分所收集到的量度整合，並作分群的動作，再與專家所提供的意見作比對，最後完成選擇第一階供應商之機制。 The selection of supplier is always an important issue in supply chain management (SCM) area. Previous studies of supplier selection focused mostly on such situation when enterprises and their suppliers had stable relationship. Moreover, it’s also common to use those historical data to estimate suppliers’ possible performance about on-time delivery.For the Aerospace Industry in Taiwan, however, the insufficient sub-contract order quantity made it difficult to build long-term and stable relationship between enterprise can only select its suppliers based on the bidding price. Therefore, delayed delivery is often happened due to suppliers’ insufficient capacity or unstable manufacturing process capability.Based on the above reasons, our study was intended to establish a systematic tier one supplier selection framework that application to the Aerospace Industry. The first tier supplier selection framework not only solves the current problem of outsourcing domestic aerospace industry, but also helps building long-term partnerships between enterprises and suppliers relationship to establish the concept of supply chain system.The tier-one supplier selection framework proposed in this study, the first part was collecting literature about the supplier selection metrics, while understanding the characteristics of the aerospace industry partnerships as well as between the upstream and downstream businesses through expert interviews and capture relevant metrics, and finally reinforcing the metrics complete by the basic theory of the Balanced Scorecard. The second part was the metrics of clustering and making comparison with the expert advice.
