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Journal of the Academy of Marketing Science

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13-08-2022 | Original Empirical Research

How has the effect of brand personality on customer-based brand equity changed over time? Longitudinal evidence from a panel data set spanning 18 years

Authors: Jonathan Luffarelli, Sebastiano A. Delre, Polina Landgraf

Published in: Journal of the Academy of Marketing Science | Issue 3/2023

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Abstract

Using a panel data set (n = 49,626), this research tests opposing hypotheses about the influence of brand personality dimensions (BPDs) on customer-based brand equity (CBBE) and the evolution of this influence over an 18-year period. The results show that, on average, the BPDs of excitement, competence, and sincerity have more positive effects on CBBE than sophistication and ruggedness. Furthermore, the effects of sincerity, sophistication, and ruggedness on CBBE have declined over time while the effects of excitement and competence have grown more positive: A 1% change in excitement is associated with a .45% change in CBBE in 2001 and a .71% change in 2018 (a 58% increase), while a 1% change in competence is associated with a .42% change in CBBE in 2001 and a .60% change in 2018 (a 43% increase). How these effects vary between countries, industry sectors, and brand types is also explored.

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Both “customer-based brand equity” and “consumer-based brand equity” have been used to refer to the same construct. We employ the former, which is more frequently used in the marketing literature, including Keller’s (1993) seminal article.

This search, conducted in April 2022, included all the journals in the marketing category of the 2018 Chartered ABS Journal Guide, the Journal of Business Research, and the Journal of Business Ethics. Only articles with the keywords “brand personality(ies)” in the abstract or title were counted. Therefore, this estimate is conservative.

This was the number of citations in April 2022.

The BPDs established initially among U.S. customers can diverge in other countries. In Spain, for example, the BPDs are excitement, sincerity, sophistication, passion, and peacefulness (Aaker et al., 2001). The data set for this study includes responses only from U.S. customers. However, we also report a preliminary, exploratory analysis of the effects of BPDs in Japan.

The data set we received from the BAV group contains information about 7,483 unique brands. However, because we enforce a more conventional definition of what constitutes a brand than the BAV group uses, we exclude several types of brands from our analyses: religions (e.g., Hinduism), festivals and holidays (e.g., Thanksgiving), military and governmental organizations (e.g., the U.S. Congress), locations (e.g., Argentina), loyalty programs (e.g., Delta SkyMiles), nonprofit organizations (e.g., Doctors Without Borders), celebrities and mascots (e.g., George Clooney), and a few brands classified as miscellaneous (e.g., Santa Claus). A robustness test shows that our findings are not a byproduct of this sampling decision.

The BAV measure is often adjusted to accommodate research objectives (for examples, see Batra et al., 2017; Heitmann et al., 2020; Stahl et al., 2012). We adjust it to avoid mechanical correlations between our dependent and independent variables. We recalculate the BAV scores after excluding the items “unique,” “leader,” and “reliable” because these items are BP traits in Aaker’s framework. The adjusted measure correlates strongly with the original, unadjusted BAV measure (r = .96).

Most studies do not use all of the BP traits in Aaker’s framework to measure BPDs (for examples, see Aaker et al., 2004; Brakus et al., 2009; Lovett et al., 2013; Luffarelli et al., 2019; Wentzel 2009), seemingly because BP traits are best conceptualized as reflective indicators of BPDs. Thus, using some but not all of the traits to capture BPDs should not alter their conceptual meaning (for a discussion, see Jarvis et al., 2003). The empirical evidence offered in WA 1 supports this view. For the same reason, the addition of the trait “cool” to the Excitement_it measure when Year_t = 2018 and the removal of the trait “tough” from the Ruggedness_it measure when Year_t ≥ 2006 should not threaten the validity of our findings. A robustness test offers empirical support for this assertion.

Hausman specification tests indicate that brand fixed effects are more appropriate than random effects to estimate Eq. 1 (χ² = 25,076, p < .001) and Eq. 2 (χ² = 34,492, p < .001).

In models that include BPD × Year_t interaction terms, the VIF exceeds the rule-of-thumb threshold of 10. However, high VIFs created by the inclusion of interaction terms can be safely ignored because they neither imply a multicollinearity problem nor should raise concerns for the estimation and interpretation of the results (for discussions, see Disatnik and Sivan 2016).

“Generally, using log(1 + x) and then interpreting the estimates as if the variable were log(y) is acceptable when the data on y contain relatively few zeros” (Wooldridge 2012, p. 193). Our BPD measures contain only eighteen zero values. For simplicity, then, we interpret the estimates as if our variables were log(y) transformed.

We find financial data for relatively few brands, because the Compustat database provides access only to data for publicly traded brands, whereas our data set includes many brands not listed on the stock market.

This analysis is available in WA 9. We find that luxury brands benefit more from nurturing a sophisticated BP than other types of brands and have not experienced a decline in the effect of this BPD.

These analyses are available in WA 9.

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Title: How has the effect of brand personality on customer-based brand equity changed over time? Longitudinal evidence from a panel data set spanning 18 years
Authors: Jonathan Luffarelli
Sebastiano A. Delre
Polina Landgraf
Publication date: 13-08-2022
Publisher: Springer US
Published in: Journal of the Academy of Marketing Science / Issue 3/2023
Print ISSN: 0092-0703
Electronic ISSN: 1552-7824
DOI: https://doi.org/10.1007/s11747-022-00895-2

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