The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Investigating antecedents and consequences of brand identification
Abstract
Purpose: This study aims to analyse the influences of prestige, satisfaction, and communication on brand identification and to show how brand identification influences word‐of‐mouth and brand repurchase. Design/methodology/approach: A theoretical model is developed and tested with a sample of car owners in the UK of two global car brands. Structural equation modelling was used with LISREL 8.54 and the maximum likelihood (ML) method. Findings: This paper draws mainly on the theory of social identity to provide a comprehensive understanding of conditions under which brand owners are likely to identify with their brand and the bases and consequences of such identification. It was shown that prestige, satisfaction, and communication effect brand identification. The study confirms that consumers' development of relationships via brand identification results in word of mouth about the brand and intentions to repurchase the brand. Furthermore, it was found that brand identification fully mediates the influences of prestige, satisfaction, and communication on word of mouth and brand repurchase. Research limitations/implications: The focus was on one country and one industry. Practical implications: Managers are provided with strategies that enhance the identification of their customers with their brand so that they can strengthen the customers' brand identification. Areas for future research are suggested. For instance, it could be interesting to test the model in a different industry and/or cultural context. Originality/value: Very few previous studies have looked at brand identification which is surprising considering it is such an important variable to influence word‐of‐mouth and brand repurchase. The study tests three antecedents to brand identification and two outcomes that have not been investigated previously. Overall, the study adds knowledge in this somewhat neglected area.
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Cites
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
The commitment-trust theory of relationship marketing
Morgan, R. M., & Hunt, S. D. (1994) · Journal of Marketing · doi:10.1177/002224299405800302 · Cited by 22,355
Self-Reports in Organizational Research: Problems and Prospects
Podsakoff, P. M., & Organ, D. W. (1986) · Journal of Management · doi:10.1177/014920638601200408 · Cited by 17,102
A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions
Oliver, R. L. (1980) · Journal of Marketing Research · doi:10.1177/002224378001700405 · Cited by 14,494
The Social Identity Theory of Intergroup Behavior
Tajfel, H., & Turner, J. C. (2004) · Political Psychology · doi:10.4324/9780203505984-16 · Cited by 13,467
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Consumers and Their Brands: Developing Relationship Theory in Consumer Research
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Cited by
The influence of customer brand identification on hotel brand evaluation and loyalty development
So, K. K. F., King, C., Sparks, B. A., & Wang, Y. (2013) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2013.02.002 · Cited by 328
Kim, J., Leung, X. Y., & McKneely, B. (2023) · Journal of Fashion Marketing and Management: An International Journal · doi:10.1108/jfmm-05-2021-0126 · Cited by 26
Consumer Engagement in the Digital Era: Its Nature, Drivers, and Outcomes
Weitzl, W., & Einwiller, S. (2018) · The Handbook of Communication Engagement · doi:10.1002/9781119167600.ch31 · Cited by 14
Metadata
- Authors
- Kuenzel, S., & Vaux Halliday, S.
- Venue
- Journal of Product & Brand Management
- Publisher
- Emerald
- Published
- 2008-08-22
- Volume
- 17
- Issue
- 5
- Pages
- 293-304
- ISSN
- 1061-0421 (ISSN-L)
- OpenAlex
- W1980653206
- Cited by
- 383
- References
- 15
- FWCI
- 20.65
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.