A post-COVID model to measure brand loyalty of banking clients
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DOIhttp://dx.doi.org/10.21511/bbs.18(2).2023.03
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Article InfoVolume 18 2023, Issue #2, pp. 24-37
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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.
- Keywords
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JEL Classification (Paper profile tab)G21, M31, M39
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References86
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Tables3
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Figures1
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- Figure 1. Structural model
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- Table 1. Biographic information
- Table 2. Pearson correlations between antecedents
- Table 3. The goodness of fit indices
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