Analysis of Customer's Expectations and Satisfaction in the Zanjan Municipality Using Fuzzy Multi-Criteria Decision Making (FMCDM) Approach

Document Type: Review Paper

Authors

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

Abstract

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.‎

Highlights

  • Using  a combination of fuzzy multiple-criteria decision-making is used for the optimal selection.
  • The research method used in this study is described and applied types and field method is used to collect data.
  • For Identifying customer expectations, data have been collected from the study population.
  •  To rank the dimensions of customer's expectations and make optimal selections for municipal zones, data have been collected from the study population. 

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Journal of Optimization in Industrial Engineering

Volume 10, Issue 21
Winter and Spring 2017
Pages 47-57

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