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Measuring customer satisfaction using a fuzzy inference system

Darestani, A. Y ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. Publisher: 2009
  3. Abstract:
  4. This study presents a new method called FCSMM (Fuzzy Customer Satisfaction Measurement Method) for measuring individual customer satisfaction using a fuzzy inference system. The main advantage of this method is its simplification in evaluation of Customer Satisfaction Index (CSI) based on simple linguistic statements collected from experienced people. In contrast with assumptions used in other methods such as linear regression principles and predefined criteria weights, the aforementioned statements form the FCSMM computational structure. Since the drivers of satisfaction and dissatisfaction and performance indexes can be simultaneously applied, concurrent direct and indirect customer satisfaction measurement is provided by the model. A set of average indexes is proposed for calculation of total CSI and average satisfaction index for each driver. Other analytical tools are applied to analyze results of this method. An example is provided in this study to demonstrate the implementation process of FCSMM. © 2009 Asian Network for Scientific Information
  5. Keywords:
  6. Customer satisfaction index ; Inference engine ; Linguistic statement ; Rule base ; Computational structure ; Customer satisfaction indices ; Experienced people ; Fuzzy inference systems ; Implementation process ; Measurement methods ; Performance indices ; Rule base ; Fuzzy systems ; Inference engines ; Linguistics ; Customer satisfaction
  7. Source: Journal of Applied Sciences ; Volume 9, Issue 3 , 2009 , Pages 469-478 ; 18125654 (ISSN)
  8. URL: https://scialert.net/abstract/?doi=jas.2009.469.478