由於企業的管理階層在經營管理企業時，時常會面臨到複雜性高的決策問題，需要及時做出正確的決策與提供解決問題的方案，所以有效的分析工具對決策者而言就變得非常重要，因為正確使用有效的分析工具可以提高決策的正確性及決策的效率。本博士論文的研究就是在探討整合多準則方法於決策問題的分析與運用，對不同的多準則方法加以分析，並整合應用在經營管理上所面臨到的問題，作為管理階層決策的依據，以提高決策效率。

本研究的方向分成兩主軸：一是在不確定的環境下，利用Fuzzy TOPSIS的方法結合權重計算，再對多個製造業的工廠做生產績效的評估，提供高階決策者經營管理工廠一個績效衡量的一個標準；其中權重是影響結果的重要因素，本研究利用DEA的方法論，修正原有數學模型讓評估者對評估準則，可以用投票的方式取得權重，進而可以使用Fuzzy TOPSIS的方法評估多個製造廠工廠的生產績效；同時以個案實例來驗證此模型是可以被產業界所廣泛使用的。

另一主軸是結合ISM和ANP兩個方法論，在各準則因子間探討相互的關係，並利用層級分析法找出各準則間權重的關係，以排序各準則的重要順序。此整合性的模型應用在排序改善護理之家照護服務品質的關鍵因素，並針對此影響因素作分析尋找可能的解決方法，提供給管理階層作為改善護理之家照護服務品質的依據，讓住院的院民及其家屬都能對其醫療照護及生活照顧的環境擁有高度的滿意度。

Due to the importance and need of giving managers an overall tool for supporting the decision making process from a more general perspective, the present research introduces integrated multi-criteria approaches for decision making problems and applications. The aspect of this dissertation is to address two key studies. One of studies relates to the performance evaluation of the multiple manufacturing plants. This study develops an integrated approach that combines the voting method based on modified DEA and the fuzzy TOPSIS method to evaluate the performance of multiple manufacturing plants in a fuzzy environment. Fuzzy TOPSIS helps decision makers carry out analysis and comparisons in ranking their preference of the alternatives with vague or imprecise data. Since the evaluation result is often greatly affected by the weights used in the evaluation process, the voting method is used in this study to determine the appropriate criteria weights.

The other study relates to the identification of key factors in improving the service quality of nursing homes. This study looks at improving the service quality in nursing homes as well as the intricate relationships between various factors. We use two research models herein. First, Interpretive Structural Modeling establishes the criteria for the inter-relationship structure, categorized according to their driving power and dependence. This methodology provides a means by which order can be imposed on the complexity of such criteria. Insights from this model can help top managers in strategic planning to improve the service quality in nursing home care. Second, because ISM does not provide any weighting associated with the criteria, we employ the Analytic Network Process approach to calculate the weighted importance of the key factors and to identify those factors impacting the service quality of nursing home care.

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