面對全球化和競爭激烈的挑戰，企業透過供應鏈管理，在全球化的競爭市場達到降低成本、提高利潤和增加企業競爭優勢。如何從眾多的優劣供應商中挑選符合企業本身需求的廠商，並建立良好穩固的供應商關係，一起合作參與供應鏈管理的規劃、流程設計和資訊分享，將是供應鏈管理成功的最初步要求。為了進行供應商的選擇，企業必須事先收集與供應商的相關資料。隨著資訊科技的發達，使資料的收集整理工作更容易進行，因此如何從收集的資料中彙整處理成有用的資訊提供企業使用，便成為近來熱門的議題。除此之外，考量到資料本身可能因為人為或不可控制因素造成的不正確 (imprecision)、不確定(uncertainty)、模糊(vagueness)或不完整(incompleteness) 的情形，和同時處理定性和定量資料時分析的困難性，本研究擬使用約略集合理論(rough set theory)來克服上述情況。透過此理論方法對供應商資料進行歸納推導，找出供應商評等的關聯性績效指標和建立分類與選擇的規則庫，提供決策者參考和使用，並運用至預測供應商績效評估結果。模擬資料的分析證實本研究所提出的供應商分類與選擇方法能夠達到避免不必要的全面性供應商審核與評估，降低供應商選擇的處理時間和提高效率，並能選擇出合理的最合適供應商。且藉由約略集合理論推導得到的決策規則，其預測供應商績效表現的效果不錯，證實決策規可以幫助使用者預測供應商的績效評估結果。

Facing with the globalization and intense competition, enterprises apply Supply Chain Management (SCM) to reduce costs, raise profits, and gain the business competitive advantages in the world market. In performing SCM, the first step is to select the suitable supplier from a number of supplier candidates for meeting the company’s needs. Then the company can establish a firm-supplier relationship to design the SCM process together. Therefore, the data collection and analysis of supplier candidates are very important prior to supplier selection. In addition, the data obtained may be of imprecision, vagueness and incompleteness in nature. In the analyses, it’s also difficult to deal with the qualitative and quantitative data simultaneously. In this research, we used rough set theory to overcome the data process and analysis problems. Through rough set theory, we can induce the decision rules from the supplier data and find out the key performance factors of suppliers’ evaluation. We not only established a supplier classification and selection rule base, but used these rules to predicate the supplier’s performance. From the simulation analysis, we concluded that the proposed supplier classification and selection method can avoid unnecessary suppliers’ examination, decrease the process time of the supplier selection, and increase the efficiency of selection effort. The supplier selected by the proposed approach can achieve the required conditions.

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