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The consumer-based brand equity inventory: scale construct and validation

Author

Listed:
  • Bruno Schivinski

    (Gdansk University of Technology, Gdansk, Poland)

  • Dariusz Dabrowski

    (Gdansk University of Technology, Gdansk, Poland)

Abstract

The present study aims to meet the need for a refinement of the consumer-based brand equity scale and to address the limitations of the previous research on the subject. Based on previous measurements of brand equity, CBBE is conceptualized in this study as a four-dimensional model consisting of brand awareness, brand association, perceived quality, and brand loyalty. A sample of 1874 Polish consumers was used to test the proposed dimensions. To measure the construct, we used a combination of exploratory and confirmatory factor analyses employing structural equation modeling in 12 product categories and across 24 brands. Additionally, for the purpose of cross-validation, we tested the framework for the factorial invariance of instrument scores. The results of our research support the hypothesized four-factor CBBE model. Moreover, the subscales designed to measure the construct operate equivalently across different product categories, which allows the meaningful comparison of scores and a wider empirical application.

Suggested Citation

  • Bruno Schivinski & Dariusz Dabrowski, 2014. "The consumer-based brand equity inventory: scale construct and validation," GUT FME Working Paper Series A 22, Faculty of Management and Economics, Gdansk University of Technology.
    • Handle: RePEc:gdk:wpaper:22
    as

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    File URL: https://cdn.files.pg.edu.pl/zie/Strona%20polska/Nauka/Publikacje/Working%20Papers/WP_GUTFME_A_22.pdf
    File Function: First version, 2014
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    References listed on IDEAS

    as
    1. Carol J. Simon & Mary W. Sullivan, 1993. "The Measurement and Determinants of Brand Equity: A Financial Approach," Marketing Science, INFORMS, vol. 12(1), pages 28-52.
    2. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    3. Wynne W. Chin & Barbara L. Marcolin & Peter R. Newsted, 2003. "A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study," Information Systems Research, INFORMS, vol. 14(2), pages 189-217, June.
    4. Yoo, Boonghee & Donthu, Naveen, 2001. "Developing and validating a multidimensional consumer-based brand equity scale," Journal of Business Research, Elsevier, vol. 52(1), pages 1-14, April.
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    Cited by:

    1. Dr. Rana Muhammad Shahid Yaqub & Muhammad Aqeel Atif & Fawad Waseem & Ehtisham, 2023. "Unveiling The Dynamics: Exploring The Stimulus-Organism-Response (Sor) Model In The Context Of Social Media Influencer Marketing, Electronic Word Of Mouth, And Purchase Decisions, With A Focus On The ," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 12(2), pages 427-438.
    2. W. Puwirat & S. Tripopsakul, 2019. "The Impact of Digital Social Responsibility on Customer Trust and Brand Equity: An Evidence from Social Commerce in Thailand," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 181-198.
    3. Shu Wang & Ying-Kai Liao & Wann-Yih Wu & Khanh Bao Ho Le, 2021. "The Role of Corporate Social Responsibility Perceptions in Brand Equity, Brand Credibility, Brand Reputation, and Purchase Intentions," Sustainability, MDPI, vol. 13(21), pages 1-19, October.

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    More about this item

    Keywords

    consumer-based brand equity; brand awareness; brand associations; perceived quality; brand loyalty;
    All these keywords.

    JEL classification:

    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • Y1 - Miscellaneous Categories - - Data: Tables and Charts

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