Measuring and managing brand loyalty of banks` clients

  • Received May 12, 2020;
    Accepted September 18, 2020;
    Published October 1, 2020
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  • Article Info
    Volume 15 2020, Issue #3, pp. 160-170
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    1 articles

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

The purpose of the study is to measure behavioral, attitudinal and other brand loyalty antecedents, and to develop an operating model for measuring and managing brand loyalty of commercial banks clients. A random sample of 500 members of the South African Commercial Institute, who are also commercial banks’ clients, received a 5-point Likert scale questionnaire to be completed online via Twitter and Facebook. About 196 people completed the questionnaire. The data possess construct validity and reliability (α ≥ 0.70). The results show that seven of the 12 original antecedents are banking related, namely five Attitudinal antecedents (r2 = 0.557) and two Other antecedents (r2 = 0.442). Behavioral antecedents were not important to bank clients. All the antecedents have factor loadings above 0.60, and there is a significant positive correlation between Attitude and the Other antecedents (r = 0.75; p ≤ 0.01). This means that the model is useful for managers in managing brand loyalty at their banks. It is also of value to researchers and academia looking to conduct further research on how to measure and manage brand loyalty. However, a caution is that the data originated from South African banks’ clients. Country-specific influences can cause different brand loyalty preferences among international banks’ clients.

I wish to acknowledge Mr. Sarel Salim for his contribution to administering the data collection for the original research on brand loyalty in banking (see also Salim and Bisschoff, 2014 in the reference list).

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    • Figure 1. A theoretical model to measure and manage brand loyalty of banks’ clients
    • Figure 2. An empirical model to measure and manage brand loyalty of banks’ clients
    • Table 1. Classification of antecedents (Jacoby & Chestnut, 1978; Aaker, 1996; Fischer, Völckner, & Sattler, 2010)
    • Table 2. Multicollinearity of antecedents
    • Table 3. Construct validity analysis
    • Table 4. Goodness of model fit indices
    • Conceptualization
      Christo Bisschoff
    • Formal Analysis
      Christo Bisschoff
    • Methodology
      Christo Bisschoff
    • Project administration
      Christo Bisschoff
    • Validation
      Christo Bisschoff
    • Visualization
      Christo Bisschoff
    • Writing – original draft
      Christo Bisschoff
    • Writing – review & editing
      Christo Bisschoff