Customer satisfaction assessment through a fuzzy neural controller
Ying‐Feng Kuo, Cecilia Temponi, Herbert W. Corley · 2002
Customer satisfaction measurement is an important part of marketing research in industrial organizations since it is the key to formulating customer value strategies and to continuously improving implementation of these strategies. We propose a general fuzzy neural network with back propagation learning for control tasks. The controller will measure customer satisfaction level for assessing advanced customer satisfaction strategies. This model is capable of tuning the membership function parameters and fuzzy IF-THEN rules simultaneously. The preliminary results presented in the research are promising and have opened new paths for future research.