營造廠商的良窳為工程專案成功的關鍵。在工程發包時，除了考量投標者承諾的成本與工期外，如何遴選履約風險較低的投標者為承攬廠商，已成為營建業重要的課題。
本研究主要的目的在於提供營建專案業主一個選擇總承包商的改良方法，針對工期與成本兩項選商準則，評估候選營造廠之投標承諾帶給業主的經濟效用，也評估候選營造廠實現投標承諾的可能性風險，並整合分析經濟效用與實現可能性，避免錯誤決策，提升決策品質。
針對營建專案選擇總承包商的決策，本文提出「選商多準則展望模式」，對投標者的「成本折扣」與「工期折扣」二項投標承諾，以廠商提供之標單與佐證資料為基礎，讓業主有效地評估「成功實現」和「失敗實現」兩種結果的可能性與主觀效用，再整合求得整體展望值，作為業主遴選營造總承包商之決策參考。本模式首先以模糊偏好關係評估投標承諾付諸實現「成功」與「失敗」的兩種可能性，再以效用函數量化業主對投標承諾的主觀效用，最後以累積展望理論計算「實現可能性」與「主觀效用」乘積求得候選營造廠的整體展望值。

The contractor is the key factor for successful implementation of a construction project. How to avoid elevated risk of not implementing contracted obligation is an important issue for construction industry.

This paper proposes a “Multi-Criteria Prospect Model” (MCPM) to support a construction contractor selection process. This model is based on bidder’s tender promise and related proof documents. Through this transparent competition model, not only utility but also implementation probability (as provided time/cost discounts related to success and failure implementations) can be effectively evaluated by clients. In the model, implementation probabilities are evaluated using Fuzzy Preference Relations and Predefined Decision Utility curves allow each bid to provide utility to the client. Both probability and utility are integrated by using the Cumulative Prospect Theorem. The overall prospect value for each candidate contractor is provided to support the final selection.

The primary contribution of this study is to propose the clients an enhance method to support a construction contractor selection process in which two criteria, the construction cost and completion time, are taken into account. Both the implementation probabilities and the economic utilities of tenders’ promise time/cost discounts are evaluated in this method. Above evaluation results are integrated to reduce the poor decision making and to improve the decision quality. The MCPM meets the clients’ preference by defining the time/cost decision utility function, and ensures the objectivity of decision process by group evaluation, and provides an easy and efficient quantification tool for user by designing linguistic questionnaire with multiplicative preference relation, and reflects the decision preference of evaluators by using probability weighting function. Such characteristics of the proposed model are benefit to select the most appropriate general contractor from the candidates for the clients to succeed in project implementation.

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