Analysis of Customer's Expectations and Satisfaction in the Zanjan Municipality Using Fuzzy Multi-Criteria Decision Making (FMCDM) Approach
محورهای موضوعی : تکتونواستراتیگرافیMasoumeh Rahimi 1 , amir najafi 2
1 - MSc, Department of Management, Zanjan branch, Islamic Azad University, Zanjan, Iran
2 - Prof. in Industrial Engineering, Department of Industrial Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
کلید واژه: Customer Expectations, Fuzzy Analysis Network Process (FANP), Fuzzy ELECTRE method, Fuzzy TOPSIS method, Multi criteria decision making,
چکیده مقاله :
Customer satisfaction is the most important step in the process of identifying customer expectations. Identify customer expectations ‎without referring to him and get his view, is impossible. In order to identify customer expectations, service suppliers are also using ‎statistical techniques, surveyed their customers. According to the studies, there is no appropriate framework for expectation model to ‎prioritize regions of organizations and make the favorable selection according to the organization’s policies and strategies. In this ‎research, a combination of fuzzy multiple criteria decision making is used for the optimal selection. The research method used in this ‎study is of descriptive and applied type, and field method is used to collect data. For Identifying customer expectations, data has ‎been collected from study population (customers of Zanjan municipality) is 303 people through random sampling method. To ranking ‎the dimensions of customer's expectations and make optimal selections of municipality zones, data has been collected from study ‎population (engineer contractor of the municipality) is 30 people. The data collection instrument was questionnaire and interview, which ‎had been valid. The Expert Choice, Web-based TOPSIS, SPSS and Excel software were used for calculations. It is interesting to ‎observe that the choices of the best municipality zone solely depend on the criterion having the maximum priority value. Based on ‎calculations on the stages of the proposed model, "municipality Zone 2" was selected as the optimal the region and had the highest rating ‎in response to customer expectations. Results show that the proposed model has a systematic fit with the defined procedures and known ‎inputs.‎
