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題名：談判群體之風險衡量模式-以民間參與公共建設計畫為例
作者：康照宗
作者(外文)：Chao-Chung Kang
校院名稱：國立交通大學
系所名稱：交通運輸研究所
指導教授：馮正民
學位類別：博士
出版日期：2000
主題關鍵詞：民間參與公共建設；風險；風險衡量；動態規劃；效用；風險事件；BOT；risk assessment；risk identification；negotiation group；dynamic programming；MAU；multiobjective programming
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當BOT特許公司與政府部門進行BOT特許契約談判時，若BOT談判群體能事前進行風險分析與風險評估，則有助於談判者了解談判事項。換言之，談判者可藉由風險評估來發現談判籌碼。
本研究即是架構在上述談判群體希望擁有之分析架構與工具，此一分析架構考慮兩個層面，一是考量談判者彼此之間沒有討論，二是考量談判者彼此之間有討論情形。前者可以以談判者彼此之間效用獨立視之，後者可以談判者彼此之間效用不獨立視之，後者係放寬前者效用獨立之假設條件。
在效用獨立方面，則以風險及效用理論為基礎，結合多屬性決策理論，採數學解析方式，構建談判者效用及談判群體效用模式，藉以衡量事件屬性之風險狀態，並進一步發展群體總計效用模式，衡量風險事件或非風險事件。在效用不獨立方面，則採效用線性相依及偏好可分性觀念，以動態規劃及多目標數學規劃方法構建談判群體效用衡量模式，同時研擬疊代求解法，進行模式求解。
為了解模式之可用性，本研究採範例分析方式，驗證模式之可操作性，發現以下重要結論：一是效用期望值可作為風險衡量之門檻值，若事件之群體總計效用值小於效用期望值時，即屬風險事件；反之，事件屬非風險事件；二是利用本研究所定義之效用交互影響值可構建動態多目標規劃模式，模式收斂條件與效用交互影響值變數及討論次數有關；三是談判者之間的討論次數增減受談判者彼此之間的效用差異影響，當效用差距越大，討論次數會增加；四是若於第1次討論即獲得收斂，則談判群體效用值可由談判者之最初效用來加總。
經由本研究之範例分析顯示，本研究所發展之群體風險衡量分析架構與模式可作為衡量BOT計畫特許契約風險事項之用；更重要的是，此模式可了解談判者對事件之風險偏好態度。
Decision-makers must adopt risk measurement to evaluate uncertain factors of BOT projects, thereby reducing loss in investment cost. This approach can also help clarify risk events by using risk evaluation when the BOT concession company and governmental sectors are involved in BOT concession contract negotiations. Restated, risk evaluation allows decision-makers to identify the negotiation items.
This study presents a novel analysis approach and risk analysis framework to satisfy the decision-makers. The proposed risk analysis approach consists of two elements, in which (a) negotiations do not negotiate and (b) negotiations occur among the negotiators. The former is a utility-independence case and the latter is a utility-dependence one. A multi-attribute utility model and dynamic multi-objective programming model for these two cases we used. The multi-attribute utility model is based on the utility, risk, and MAU theories, and the dynamic multi-objective programming model is based on the preference decomposition and linear in utility theories in order to clarify the risk events, non-risk events, main risk events, and secondary risk events. In addition, the iterative algorithm is proposed herein to obtain a convergent solution of the dynamic multi-objective programming model. In addition, a numerical example is provided to demonstrate the effectiveness of the proposed model. Numerical results indicate that the proposed model can satisfy the decision-makers’ objective of identifying risk events, main risk events, and secondary events.
The numerical example provides some interesting findings. First the expected utility value can be used to determine risk or non-risk events. Second, the dynamic multi-objective programming model can be used to demonstrate the discussion behavior. Third, the interactive utility value (IUV value) affects the number of discussion. Fourth, the dynamic multi-objective programming model reduces to the additive utility model when the dynamic multi-objective programming model satisfies the converged condition in the first discussion model.
This study demonstrates the feasibility of applying the proposed model and risk analysis framework to measure the risk of BOT concession contract. Furthermore, the risk measurement model can show risk preference behavior of the negotiators.
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