民間資金在參與公共建設的過程中，資金來源可概括為兩部分，一為發起人以權益工具籌措資金的自有資本或稱「權益融資」，另一為經由債務工具籌措資金的專案融資或稱「債務融資」；而投資計畫是否具備足夠的自償性是吸引民資的關鍵因素，且投資計畫的自償性與其風險水準與資金成本是相對應的。本論文即以利率─風險結構的觀點，提出一個「整合性的風險評估與分析模式」，作為探討公共建設專案融資風險評估方法與風險性資金成本分析的架構，並以台灣高鐵BOT計畫驗証此一模式。
在整合性風險評估方面所考慮的風險範圍不僅限於財務面，舉凡與專案融資有關者皆予納入。因此首先藉由模糊集群分析重新將風險屬性與次屬性加以分類；其次針對重分類後的風險屬性與次屬性之重要性與風險性，以模糊多屬性決策的二維模糊集合運算得出整合性的風險指標；最後以此整合性風險指標透過群體決策求得不同風險等級之風險溢酬替代變數，再將此風險溢酬替代變數代入類似資本資產訂價模式以導出風險調整折現率。
在整合性風險分析方面，考量的重點在於如何降低風險性資金成本提高投資計畫的自償性，因此在模式建構時以前述之整合性風
險評估所導出之風險調整折現率作為資金成本分析之基礎個案，探討引進政府補助（優惠利率、特許開發）與特許公司採用實質選擇權（延遲選擇權、擴張選擇權、多重實質選擇權）等兩項政策的效果，所以推導出「傳統NPV分析」與「擴展NPV分析」。
最後以台灣高鐵BOT計畫進行個案研究與模式驗証，在「整合性風險評估模式」的驗證方面，經由「模糊多屬性決策」的評估後得到興建階段營運階段的風險項目，且模式的信度與效度均通過檢定。在「整合性風險分析模式」的驗證方面，乃基於「整合性風險評估模式」的風險分析結果，其風險溢酬水準為年利率6%，在加計十年期長期政府公債之無風險年利率6.52%，則「風險調整折現率」為年利率12.52%。由於本論文研究個案的資金來源包括自有資金與專案融資兩部份，出資比分別為30%與70%；因此在稅率25%情況下其「加權平均資金成本」為11.97%，以此作為風險性資金成本分析的基礎，探討政府補助與採用實質選擇權的效果；研究顯示本模式可以有效說明此種現象且能達到預測的功能。總而言之本論文的研究貢獻有三點，其一為整合性風險評估與分析模式的建構，其二為對資本資產訂價模式適用性之擴充，其三為外部性與政府補助政策、實質選擇權對投資計畫資金成本與自償性的實証性研究。

There are two sources of private capital to support the requirements of build-operate-transfer (BOT) infrastructure project. One is equity financing which is financed by debt instruments, the other is debt financing which is financed by equity instruments. Theoretically, the self-liquidation of project is the key factor of private capital in the investment of the infrastructure project, and the self-liquidation is related to the cost of capital. This research is based on the risk structure of interest rate to propose an integrated risk assessment and analysis model (IRAM) and use this model to calculate the cost of capital in project finance. The Taiwan High Speed Rail BOT program will be used to test and verify the IRAM model.
The first part of IRAM is integrated risk assessment model which creates a process of assessing the risk factors and introduces a methodology to evaluate the risk adjustment discount rate(RADR) of project finance. In the area of risk assessment of project finance, IRAM focuses not only on the financial condition but also on the whole domain of project risks. So the first step is to re-identify the risk attributes and sub-attributes by fuzzy clustering. The second step is to establish an integrated risk index by two-dimensional fuzzy set operations. The last step uses group decision method to develop a risk premium proxy, and then find out the RADR.
The main purpose of the second part of IRAM is to analyze the self-liquidation of
BOT project. This model utilizes RADR to develop a base case. Then we consider the government subsidiary policy and project company’s real options to discuss the effectiveness of these two policies by using net present value (NPV) and expanded net present value( expanded NPV) analysis.
Finally, we verify the IRAM model by the case study of Taiwan High Speed Rail
BOT program. The validity and reliability of integrated risk assessment model has past the test. On the verification of the integrated risk analysis model, the risk premium of base case is 6%, and the risk-free discount rate for the long term T-Bond is 6.52%, then the weighted average cost of capital(WACC) of base case is 11.97%. Generally, the pay off of BOT project can not cover the costs invested, which means the BOT project is not fully self-liquidated. But the coverage is gradually improved during the implementation of government subsidiary policy and project company’s flexibility policy. The case study has proved IRAM is effective. Generally speaking, there are three main contributions of this research: the establishment of an integrated risk assessment and analysis model, an expanded application of Capital Asset Pricing Model and empirical research results of real options.