An integrated Approach based on DEMATEL, ANP, and DEA for MCDM problems: Performance Measurement of Detection and Governmental Punitive Agency

In this paper a hybrid approach based on DEMATEL, ANP, and DEA-based Malmquist Productivity Index is proposed to solve complicated real world Multiple-Criteria Decision Making (MCDM) problems. First, DEMATEL is used to detect the network of interactive criteria through cause and effect relations. Then, the relative importance of the criteria is calculated using ANP method. Finally, a DEA-based Malmquist Productivity Index approach is used to evaluate the productivity of alternatives with multiple inputs and outputs during several planning periods while the relative importance achieved from ANP are also considered as constraints of the system. This approach can handle complicated real world MCDM problems effectively. In order to provide a clear picture of the performance of the proposed hybrid approach, it is used at Detection and Governmental Punitive Agency in all provinces in Iran and the results are analyzed. Important point of this study is the importance of accuracy in determining the weights of each criterion. The more accurately the weights, closer to the reality are results, and reliability will be higher. Closeness to reality is resulted when relations among criteria are determined correctly by experts through DEMATEL and ANP techniques.