Abstract

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. AcknowledgmentI 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).

Highlights

  • None of the banks actively measures and manages brand loyalty to their bank. This strategic oversight is partly due to limited operating models or measurement tools, and the inability to accurately manage brand loyalty among their banks’ clients

  • In prac- The theoretical model was developed from a myritice, this means that a positive attitude leads ad of seminal brand loyalty models developed as far to increased brand loyalty

  • The results show that limited multicollinearity exists and that all the antecedents are within the ideal variance inflation factor (VIF) and tolerance ranges (VIF ≤ 3; Slovin’s tolerance ≥ 0.4)

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Summary

INTRODUCTION

Christo Bisschoff, Ph.D., Professor of Marketing, Faculty of Economic and Management Sciences, NWU Business School, North-West University, South Africa. Studies by Jacoby and Chestnut (1978), and others (Basson, 2014; Bisschoff & Moolla, 2015) report that a significant positive correlation exists between a product and brand loyalty. Antecedent and abbreviation Brand trust (BTS) Brand affect (BAF) Culture orientated (CUL) Commitment (COM) Brand relevance (BRV) Relationship proneness (RPR) Involvement (INV) Repeat purchase (RPS) Switching cost (SCR) Brand performance (BPF) Perceived value (PVL) Customer satisfaction (CUS). Aaker (1991; 1996), showed that behavior (stochastic approach) and attitude (determinist ap- The aim of this study is to develop an operationproach) are the two main drivers of brand loy- al management model to measure and manage alty These researchers found that brand loyalty among banks’ clients. Attitude influences brand loyal behavior and identified significant positive and negative relationships (p ≤ 0.05; p ≤ 0.10) between these

RESEARCH METHODOLOGY
RESULTS
Findings
CONCLUSION
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