Corporate social responsibility, electronic word-of-mouth and customer loyalty in Vietnam’s banking sector

  • Received June 17, 2022;
    Accepted August 11, 2022;
    Published August 18, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.17(3).2022.04
  • Article Info
    Volume 17 2022, Issue #3, pp. 38-48
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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This research explored and examined the link between electronic word-of-mouth, corporate social responsibility, and loyalty of 282 customers using banking services in Vietnam (PLS-SEM) through the Partial Least Squares Structural Equation Modeling. The data were gathered using convenience sampling, with a sample of 282 customers who used banking services in Vietnam and interacted with the bank through social media. The survey is intended to include 16 questions separated into two parts: the first part contains 5 demographic questions, and the second part contains 11 questions divided into three sets of factors: corporate social responsibility, electronic word-of-mouth, and loyalty.
The survey was emailed to customers using banking services and interacting with banks via social media in Vietnam. According to the findings of the empirical study, there is a direct and indirect link between corporate social responsibility, electronic word-of-mouth, and customer loyalty in Vietnam’s banking sector. The results of empirical research in Vietnam’s banking industry indicate that corporate social responsibility has direct and positive impact on customer loyalty; corporate social responsibility has a direct and positive impact on customer’s word-of-mouth; electronic word-of-mouth has a direct and positive impact on customer loyalty; and finally, corporate social responsibility has an indirect impact on customer loyalty through customer’s electronic word-of-mouth.

Acknowledgment
The author would like to thank all the customers who completed the survey. The author would like to thank all parties and the Banking University of Ho Chi Minh City for their excellent support and assistance in completing this research.

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    • Figure 1. Proposed research model
    • Figure 2. The PLS-SEM algorithm analysis results
    • Table 1. Demographic variable descriptive statistics
    • Table 2. Mean, standard deviation, kurtosis and skewness
    • Table 3. PLS-SEM algorithm analysis results
    • Table 4. The results of the hypothesis test
    • Conceptualization
      Nguyen Minh Sang
    • Data curation
      Nguyen Minh Sang
    • Formal Analysis
      Nguyen Minh Sang
    • Methodology
      Nguyen Minh Sang
    • Visualization
      Nguyen Minh Sang
    • Writing – original draft
      Nguyen Minh Sang
    • Writing – review & editing
      Nguyen Minh Sang