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A perceived reliability-based customer satisfaction model in self-service technology

Author

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  • Zapan Barua
  • Wang Aimin
  • Xu Hongyi

Abstract

Technical reliability of self-service technologies (SSTs) has been found to be a strong determinant of satisfaction with tech-enabled services. Yet, the interpretation of the factors affecting reliability and its subsequent influences on customer satisfaction (CS) with SSTs is inadequate. The purpose of this investigation has, therefore, been to demarcate a model to fulfill the gap with an empirical examination, and accordingly a model was developed and tested by applying a global structural equation model. The model results of banking SST users specify how the reliability of SSTs is perceived by the users. The findings have reported that the best predictor of perceived reliability (PRe) is perceived security followed by perceived control. Surprisingly, no significant impact of perceived ease of use was found on PRe. The research also attempted to shed light on the influence of PRe on perceived risk, technology trust, and CS in the light of technology-enabled self-service.

Suggested Citation

  • Zapan Barua & Wang Aimin & Xu Hongyi, 2018. "A perceived reliability-based customer satisfaction model in self-service technology," The Service Industries Journal, Taylor & Francis Journals, vol. 38(7-8), pages 446-466, June.
    • Handle: RePEc:taf:servic:v:38:y:2018:i:7-8:p:446-466
    DOI: 10.1080/02642069.2017.1400533
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    Cited by:

    1. Badghish, Saeed & Shaik, Aqueeb Sohail & Sahore, Nidhi & Srivastava, Shalini & Masood, Ayesha, 2024. "Can transactional use of AI-controlled voice assistants for service delivery pickup pace in the near future? A social learning theory (SLT) perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    2. Asif Mahmood & Shazia Manzoor, 2021. "Which Service Attributes Sway Internet Service Providers? Analysis Through Triangulation Approach," SAGE Open, , vol. 11(4), pages 21582440211, December.
    3. Yuen, Kum Fai & Wang, Xueqin & Ma, Fei & Wong, Yiik Diew, 2019. "The determinants of customers’ intention to use smart lockers for last-mile deliveries," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 316-326.
    4. Nguyen Hong Quan & Nguyen Thi Binh & Bui Thi Ly, 2022. "Impact of smart locker use on customer satisfaction of online shoppers in Vietnam," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    5. Mitra Madanchian & Jay Ariken & Hamed Taherdoost, 2022. "Role of Effective Leadership on Empowerment, Effective Communication, and Motivation in Customer Service," Post-Print hal-03741852, HAL.
    6. Jiang, Yi & Lai, Po-Lin & Yang, Ching-Chiao & Wang, Xinchen, 2023. "Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    7. Sara Javed & Md. Salamun Rashidin & Wang Jian, 2021. "Predictors and outcome of customer satisfaction: moderating effect of social trust and corporate social responsibility," Future Business Journal, Springer, vol. 7(1), pages 1-18, December.
    8. Chong Li & Yingqi Li, 2023. "Factors Influencing Public Risk Perception of Emerging Technologies: A Meta-Analysis," Sustainability, MDPI, vol. 15(5), pages 1-37, February.
    9. Jang, Yeonju & Park, Eunil, 2020. "Social acceptance of nuclear power plants in Korea: The role of public perceptions following the Fukushima accident," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).

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