Evolution of customer satisfaction in the e-banking service industry

  • Received January 25, 2022;
    Accepted February 25, 2022;
    Published March 1, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.18(1).2022.11
  • Article Info
    Volume 18 2022, Issue #1, pp. 131-141
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This work is licensed under a Creative Commons Attribution 4.0 International License

Since several commercial activities such as banking, shopping, transfers, and payments had been conducted online, many banks in Cambodia provided e-banking services to their customers to support these activities. Meanwhile, if the banks could provide such e-banking services to satisfy their customers’ needs, they could maintain their customers and profits. Thus, finding the main factors influencing customer satisfaction in the e-banking service industry is significant. Therefore, the objective of this paper is to investigate how customer satisfaction develops through examining the impacts of perceived risk (financial risk and performance risk) and perceived value on customer satisfaction in the e-banking. This study applied convenience sampling to get data from the respondents at convenient locations (near banks, markets, supermarkets, universities, and workplaces). 700 respondents who were currently using mobile banking or internet banking services at either commercial or retail banks in Cambodia were invited to fill in the questionnaires. In addition, the results of this study were generated through structural equation model (SEM) analysis based on 546 valid responses. The results revealed that perceived value was mainly influenced by performance risk, whereas financial risk did not significantly affect perceived value. Finally, perceived value and performance risk significantly influenced customer satisfaction, except financial risk. In addition, despite both perceived value and performance risk significantly influencing customer satisfaction, promoting customer satisfaction through increasing perceived value was far more effective than minimizing performance risk.

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    • Figure 1. Satisfaction model in the e-banking service industry
    • Figure 2. SEM results
    • Table 1. SEM model measurement
    • Table 2. Model fit
    • Table 3. Hypotheses summary
    • Conceptualization
      Long Kim
    • Formal Analysis
      Long Kim
    • Methodology
      Long Kim
    • Validation
      Long Kim, Teerasak Jindabot
    • Writing – original draft
      Long Kim
    • Project administration
      Teerasak Jindabot
    • Supervision
      Teerasak Jindabot
    • Visualization
      Teerasak Jindabot
    • Writing – review & editing
      Teerasak Jindabot