A fuzzy neural architecture for customer satisfaction assessment

Article type: Research Article

Authors: Temponi, Cecilia^; | Kuo, Ying-Feng | Corley, Herbert W.

Affiliations: School of Business, Southwest Texas State University, San Marcos, TX 78666, USA. E-mail: ct01@swt.edu | Department of Information Management, Kung-Shan Institute of Technology, Yung-Kang, Tainan, Taiwan | Department of Industrial and Manufacturing Systems Engineering, University of Texas at Arlington, USA

Note: [] Corresponding author.

Abstract: We present a fuzzy neural network for assessing customer satisfaction. It is a feedforward multilayer network with a fuzzy controller and utilizes back-propagation learning. The controller will measure customer satisfaction levels, thereby assessing current strategies and providing a means for evaluating possible changes. Preliminary results are promising and have provided new paths for future research.

Journal: Journal of Intelligent and Fuzzy Systems, vol. 7, no. 2, pp. 173-183, 1999