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

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  • Tien-Hsiang Chang

    (Department of Intelligent Commerce, National Kaohsiung University of Science and Technology, Kaohsiung City 824, Taiwan)

  • Kuei-Ying Hsu

    (Department of Marketing Management, Shu-Te University, Kaohsiung City 824, Taiwan)

  • Hsin-Pin Fu

    (Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Kaohsiung City 824, Taiwan)

  • Ying-Hua Teng

    (Graduate Institute of Management, National Kaohsiung University of Science and Technology, Kaohsiung City 824, Taiwan)

  • Yi-Jhen Li

    (Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Kaohsiung City 824, Taiwan)

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.

Suggested Citation

  • Tien-Hsiang Chang & Kuei-Ying Hsu & Hsin-Pin Fu & Ying-Hua Teng & Yi-Jhen Li, 2022. "Integrating FSE and AHP to Identify Valuable Customer Needs by Service Quality Analysis," Sustainability, MDPI, vol. 14(3), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1833-:d:742845
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    References listed on IDEAS

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    1. Necati Ertekin & Michael E. Ketzenberg & Gregory R. Heim, 2020. "Assessing Impacts of Store and Salesperson Dimensions of Retail Service Quality on Consumer Returns," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1232-1255, May.
    2. Getasew Taddese & Severine Durieux & Emmanuel Duc, 2021. "Sustainability Performance Evaluation of Faceshield Bracket Manufacturing by Using the Analytic Hierarchy Process," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    3. Diogo Rodrigues & Radu Godina & Pedro Espadinha da Cruz, 2021. "Key Performance Indicators Selection through an Analytic Network Process Model for Tooling and Die Industry," Sustainability, MDPI, vol. 13(24), pages 1-20, December.
    4. Lee, Kiljae & Yu, Chunyan, 2018. "Assessment of airport service quality: A complementary approach to measure perceived service quality based on Google reviews," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 28-44.
    5. Katarzyna Pietrucha-Urbanik & Janusz R. Rak, 2020. "Consumers’ Perceptions of the Supply of Tap Water in Crisis Situations," Energies, MDPI, vol. 13(14), pages 1-20, July.
    6. Fan-Yun Pai & Chien-Ping Chen & Tsu-Ming Yeh & Massoud Metghalchi, 2017. "The effects of promotion activities on consumers' purchase intention in chain convenience stores," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 12(4), pages 413-432.
    7. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    8. McCarty, John A. & Hastak, Manoj, 2007. "Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression," Journal of Business Research, Elsevier, vol. 60(6), pages 656-662, June.
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    Cited by:

    1. Marko Šostar & Vladimir Ristanović, 2023. "An Assessment of the Impact of the COVID-19 Pandemic on Consumer Behavior Using the Analytic Hierarchy Process Model," Sustainability, MDPI, vol. 15(20), pages 1-31, October.
    2. Jincang Yang & Xueqin Dong & Sishi Liu, 2022. "Safety Risks of Primary and Secondary Schools in China: A Systematic Analysis Using AHP–EWM Method," Sustainability, MDPI, vol. 14(13), pages 1-15, July.

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