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


در حال بارگذاری
11 سپتامبر 2024
فایل ورد و پاورپوینت
2120
4 بازدید
۶۹,۷۰۰ تومان
خرید

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بخشی از متن مقاله Analysis of Customer”s Expectations and Satisfaction in the Zanjan Municipality Using Fuzzy Multi-Criteria Decision Making (FMCDM) Approach :

سال انتشار : ۲۰۱۷

تعداد صفحات :۱۸

Customer satisfaction is the most important step in the process of identifying customer expectations. Identify customer expectations â€without referring to him and get his view, is impossible. In order to identify customer expectations, service suppliers are also using â€statistical techniques, surveyed their customers. According to the studies, there is no appropriate framework for expectation model to â€prioritize regions of organizations and make the favorable selection according to the organization’s policies and strategies. In this â€research, a combination of fuzzy multiple criteria decision making is used for the optimal selection. The research method used in this â€study is of descriptive and applied type, and field method is used to collect data. For Identifying customer expectations, data has â€been collected from study population (customers of Zanjan municipality) is 303 people through random sampling method. To ranking â€the dimensions of customer”s expectations and make optimal selections of municipality zones, data has been collected from study â€population (engineer contractor of the municipality) is 30 people. The data collection instrument was questionnaire and interview, which â€had been valid. The Expert Choice, Web-based TOPSIS, SPSS and Excel software were used for calculations. It is interesting to â€observe that the choices of the best municipality zone solely depend on the criterion having the maximum priority value. Based on â€calculations on the stages of the proposed model, “municipality Zone 2” was selected as the optimal the region and had the highest rating â€in response to customer expectations. Results show that the proposed model has a systematic fit with the defined procedures and known â€inputs.â€

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