A post-COVID model to measure brand loyalty of banking clients

  • Received November 23, 2022;
    Accepted February 25, 2023;
    Published April 21, 2023
  • Author(s)
    Dries Els
    ORCID ,
    Christo Bisschoff
    ORCID
  • DOI
    http://dx.doi.org/10.21511/bbs.18(2).2023.03
  • Article Info
    Volume 18 2023, Issue #2, pp. 24-37
  • TO CITE АНОТАЦІЯ
  • Cited by
    2 articles
  • 824 Views
  • 370 Downloads

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This work is licensed under a Creative Commons Attribution 4.0 International License

The study investigates the relationship between customers’ loyalty, trust and satisfaction concerning an organization’s reputation in the South African banking sector. High service levels exist in this highly competitive and price-sensitive market. Access to banking has also digitized significantly, and banks adapted their service strategies to comply with COVID-19 restrictions such as hard lockdowns and limited movements. Customers were not able to attend banks. Hence the whole personal (contact) service and loyalty scenario required aggressive reengineering. A bank’s competitiveness can be impacted significantly by service quality, price competitiveness, and product diversity. As a result, the study with the primary objective is to determine the new relationships between customer loyalty and antecedents such as service quality, customer satisfaction, customer trust, brand image, reputation, customer loyalty, and word of mouth. Data were gathered from South African customers using a 5-point Likert scale distributed via an electronic platform (Google Forms). More than 1,000 questionnaires were distributed, and 150 were completed and returned (representing a 15% response rate). The reliability is satisfactory (Cronbach alpha coefficient on all antecedents exceeded 0.775). The literature model was confirmed using confirmatory factor analysis. The analysis showed that the model possesses convergent- (r2 < Sqrt AVE) and discriminant (AVE > 0.5) validity and possesses satisfactory fit indices (CFI = .951, TL = .941, NFI = .922, RMSEA = .089, CMIN/df = 129.072/592.188 = 2.188). This indicates that the model can be operationalized in South Africa to measure post-COVID-19 bank loyalty.

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    • Figure 1. Structural model
    • Table 1. Biographic information
    • Table 2. Pearson correlations between antecedents
    • Table 3. The goodness of fit indices
    • Conceptualization
      Dries Els, Christo Bisschoff
    • Project administration
      Dries Els
    • Validation
      Dries Els, Christo Bisschoff
    • Writing – original draft
      Dries Els
    • Formal Analysis
      Christo Bisschoff
    • Methodology
      Christo Bisschoff
    • Writing – review & editing
      Christo Bisschoff
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Banks and Bank Systems
Banks and Bank Systems