Identification and stereotypes as determinants of brand extension potential

Laura Marie Schons; Philipp Thöne

doi:http://dx.doi.org/10.21511/im.13(1).2017.04

Identification and stereotypes as determinants of brand extension potential

Received April 19, 2017;

Accepted May 18, 2017;

Published May 25, 2017
Author(s)
Laura Marie Schons , Philipp Thöne
DOI
http://dx.doi.org/10.21511/im.13(1).2017.04
Article Info
Volume 13 2017, Issue #1, pp. 33-54
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This work is licensed under a Creative Commons Attribution 4.0 International License

Current research suggests that social identification processes play an important role in markets. In this study, the authors propose that marketing research has neglected one important factor, which influences the success of a brand extension, namely the group processes between social groups and brand communities framing the new product introduction. Based on social identification theory, the authors derive a framework integrating identification and stereotyping processes, simultaneously testing for drivers of brand extension potential, which have been found to be important in past empirical studies. Using a structural equation modeling approach, the authors test for in-group and out-group effects in two hypothetical brand extension scenarios of one snowboard brand (Burton), and a surf brand (Billabong) into the ski market. They find that the social identification processes underlying the new product introduction significantly drive the potential success of the brand extension. By being the first study to explore the role of identification and stereotype effects in brand extension, the authors make an important contribution to research in this area. Moreover, our study provides important implications for brand managers planning to extend their brands into new product categories.

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Keywords
brand extension potential, brand extensions, identification, stereotypes
JEL Classification (Paper profile tab)
M37
References
87
Tables
6
Figures
3

- Fig. 1. Conceptual framework
- Fig. 2. Structural equation models with path coefficients and model fit measures
- Fig. 3. Multiple group analysis

- Table 1. Reliability statistics of the individual constructs
- Table 2. T-test for verifying significant differences of the mean values of the structural models
- Table 3. Chi-square difference test for verifying the metric invariance
- Table 4. T-test for verifying significant differences of the path coefficients
- Table 5. T-test for verifying significant differences of the mean values of the multiple group comparison
- Table 6. Local measures of goodness of the individual constructs

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