Integrating FSE and AHP to Identify Valuable Customer Needs by Service Quality Analysis

Abstract

In this study, we explore the needs of different valuable customer groups for service quality and how limited resources are allocated to enhance service quality. Accordingly, we propose a hybrid multi-criteria decision-making (MCDM) tool that uses fuzzy synthetic evaluation (FSE) in combination with the analytic hierarchy process (AHP) to help companies enhance understanding of quantitative data (the weights of the factors that affect service quality) and qualitative information to identify valuable customers. Fifty-three experts and 304 consumers at convenience stores (CVS) comprise the data set. We employed the AHP to obtain index weights in the second step of FSE and conducted FSE to determine the importance of various valuable customer groups. The results demonstrate that different valuable customer groups have dissimilar perceptions and feelings about service quality. The findings indicate that customers between “20 to 29 years old” are the most valuable customer group and that most consumers do not care much about “problem solving”. The analysis is distinct from extant work in that it examines the effect of receiving service quality from a consumer viewpoint, as we conducted a comprehensive analysis from both customer and expert perspectives.