Service Quality Evaluation Model of Automated Teller Machines Using Statistical Inference and Performance Evaluation Matrix

Kuen-Suan Chen (), Wen-Chih Chiou and Mei-Hua Ko
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Kuen-Suan Chen: Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taiwan
Wen-Chih Chiou: Department of Business Administration, National Chin-Yi University of Technology, Taiwan
Mei-Hua Ko: Department of Business Administration, National Chin-Yi University of Technology, Taiwan

Journal of Economics and Management, 2018, vol. 14, issue 2, 173-190

Abstract: Automated teller machines (ATMs) provide customers with safe and efficient financial services round-the-clock, while simultaneously reducing operating costs. They have consequently become an integral aspect of financial service systems across the world. Clients' satisfaction with ATM service is an important concern for these firms. High-quality service provision necessitates analysis of factors underlying service failure. This paper uses a questionnaire survey to aggregate customer responses regarding their use of ATMs and their overall satisfaction toward this experience, and then employs a simple regression model to explore how individual service items affect their overall satisfaction. Lastly this paper presents an influence index which, combined with the satisfaction index, allows for the construction of a performance evaluation matrix. This paper also uses the mean of the two indices to create dynamic standards for ongoing quality management. Statistical inference is conducted to obtain interval estimations regarding both indices in order to counter the uncertainty of service quality evaluation caused by sampling error. Using this criterion, financial market operators can determine the standard of their service quality, as well as outline strategies for improvement.

Keywords: financial service industry; automated teller machine; performance evaluation matrix; statistical inference (search for similar items in EconPapers)
JEL-codes: C44 (search for similar items in EconPapers)
Date: 2018
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