Brand equity and financial
performance

The moderating role of brand likeability
Bedman Narteh

Department of Marketing, University of Ghana Business School, Accra, Ghana

Abstract
Purpose – The purpose of this paper is to examine the relationship between brand equity and financial
performance and the moderation role of brand likeability retail banking sector.
Design/methodology/approach – The study is quantitative and employed the survey methodology to
sample the views of 550 retail bank customers. Data were analyzed though the structuring equation modeling
using AMOS.
Findings – The study found out that service quality, brand association, brand loyalty, and brand relevance
positively and significantly predicted financial performance of the retail banks. In addition, brand likeability
also moderates the relationship between brand equity and financial performance.
Originality/value – The study contributes to the ongoing research in examining the linkage between brand
equity and financial performance. The study has also shown the value of brand likeability as a moderator of the
brand equity-financial performance linkage. The strategic implication of the results are discussed in the paper.
Keywords Brand equity, Financial performance, Brand likeability
Paper type Research paper

Introduction
Branding has assumed great significance in many organizations worldwide (Chen and
Green, 2009). It is an imperative for all kinds of organizations due to perceived benefits like
differentiation, profitability, customer loyalty and competitive advantage (Keller, 2013;
Zachary et al., 2011; Roll, 2009). It has indeed become evident that firms which engage in
branding efforts experience a myriad of benefits as opposed to firms that do not brand
(Capon, 2013). One of the key branding outcomes that stand out in literature is brand equity.
Customer-based brand equity (CBBE) has occupied the minds of several researchers, who
have highlighted its contribution to organizations in terms of performance-related measures
(Wang and Sengupta, 2016; Felício et al., 2014). To date, Keller (2003, p. 2) has offered what
many perceive to be the most widely referenced definition of CBBE. He defines brand equity
as “the differential effect of brand knowledge on consumer response to the marketing of the
brand.” This, as espoused by Keller (2003), enables organizations to elicit desired responses
from customers. Other scholars such as Capon (2013) have defined brand equity as the
consumer’s response to a brand’s actions relative to competing brand’s actions. Brand
equity is thus largely viewed as a strategic outcome of branding that encompasses strategic
advantages that accrue to a brand relative to its competitors (Wang and Sengupta, 2016).

A number of scholars led by Aaker (1991) have stated that brand equity creates value for
firms as well as their clients (García-Osma et al., 2015; Keller, 2013). This view has been
supported by others such as Aaker and Jacobson (2001) who identified the impact of brand
equity on firm profitability. They discovered that brand equity is positively associated with
profits and return on investment. However, Johansson et al. (2012) argue that the strength of
the relationship between brand equity and financial performance differs based on the
measures used to capture equity. Most researchers have argued that the relationship
between brand equity and financial performance is direct. But the key question outstanding
is, does brand equity automatically translate into financial performance? The need for
further studies to clarify this relationship is imperative. Moreover, the application of brand

Marketing Intelligence & Planning
Vol. 36 No. 3, 2018

pp. 381-395
© Emerald Publishing Limited

0263-4503
DOI 10.1108/MIP-05-2017-0098

Received 31 May 2017
Revised 17 August 2017

3 November 2017
28 December 2017

Accepted 30 January 2018

The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-4503.htm

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likeability as a moderator of the relationship between brand equity and financial
performance has not been properly explored, hence the import of this study.

The need to assess the impact of brand equity on the financial performance of firms has
become more critical in a dispensation where there is much scrutiny on marketers, owing to
the huge budgets that are bestowed on them (Sharma et al., 2016; Keller, 2008). Pressure has
been mounting steadily on marketing managers to justify their expenditure and show how it
affects financial performance in a practical manner (O’Sullivan and Abela, 2007). Marketing
literature is rife with studies that have examined the concept of brand equity and financial
firm performance. The likes of Sharma et al. (2016), Wang and Sengupta (2016), Felício et al.
(2014), Stahl et al. (2012) have conducted studies to determine how brand equity results in firm
performance. However, the effect of emotional constructs like brand likeability have not been
tested in the relationship between brand equity and firm performance. This study seeks to
contribute to literature by examining the relationship, as moderated by brand likeability.

Literature review
CBBE
CBBE exists in literature as one of the most prominent descriptions of brand equity.
A number of scholars such as Mackay et al. (1998) as well as Simon and Sullivan (1993) are
of the view that if a firm wants to assess the long-run effectiveness of its marketing
programs on the firm’s customers and revenue, brand equity represents the viable option to
select. Keller (2003), who is largely credited with the coining of the term CBBE, believed that
its underpinning objective was to harness the power of the brand through consumers’
responses to marketing programs (Keller, 2008). Within the services sector, the phenomenon
also holds, though it is underrepresented in studies (Christodoulides and de Chernatony,
2010). Chang and Liu (2009) confirmed that brand equity has a significant effect on brand
preference and purchase intentions within the services industry. Successfully applied within
the hospitality industry (Boo et al., 2009; Konecnik and Gartner, 2007; Kayaman and Arasli,
2007), CBBE has also been tested in the financial services sector. Taylor et al. (2007),
extending Netemeyer et al.’s (2004) operationalization of CBBE, found that customers do
differentiate between brands in the financial sector, and that their resulting attitudes toward
the brands can predict loyalty intentions. Again, Pinar et al. (2012) compared private, foreign
and state banks in Turkey, and found that overall CBBE was higher for private banks than
foreign and state banks. The researchers argued that this was as a result of the poor
perceived quality of foreign banks, especially.

Some scholars have offered diverse opinions on how brand equity can be measured and
which viewpoint it can be assessed from. According to Atilgan et al. (2005, p. 238), brand
equity “can be discussed from the perspective of the manufacturer, retailer or the
consumer.” Cobb-Walgren et al. (1995) argue that while manufacturers and retailers are
more inclined toward the strategic implications of brand equity, investors and shareholders
tend to lean more toward the financial implications of brand equity and its impact on the
balance sheet of the firm. Simon and Sullivan (1993) further added to this perspective by
stating that brand equity essentially can be considered as the incremental cash flows which
accrue to branded products over time, an advantage which does not apply to products or
services that are not branded.

In terms of the dimensions of CBBE, literature appears to have a plethora of options.
Aaker (1991), Keller (1993) have been recognized for profound contributions to the discourse
and measurement of brand equity. Whilst they have both sought to achieve the same
outcome, their approaches have varied. Aaker (1991) has focused on measuring brand
equity with five dimensions namely: brand awareness, brand associations, brand loyalty,
perceived quality and other proprietary brand assets. Keller (1993) on the other hand resorted
to two basic approaches (direct and indirect) in measuring customer based brand equity.

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Atilgan et al. (2005) in their study on determinants of the brand equity, opined that
Keller’s (2003) indirect approach in identifying brand equity sources examined channels of
distribution, effectiveness of marketing communications, and a measurement of a brand’s
success, via its brand awareness and brand associations. The direct approach on the other
hand focuses on how consumers respond to the various elements in a firm’s marketing
program (Keller, 2003). In this study however, brand equity would be conceptualized using a
combination of Aaker’s (1991) model as well as Stahl et al.’s (2012) adaptation of Young and
Rubicam’s brand equity assessment measure. Brand equity would thus be measured using
brand awareness, brand associations, brand loyalty, perceived quality (Aaker, 1991) as
well as relevance (Stahl et al., 2012; Young and Rubicam, 2000). In total, five variables will
measure brand equity, and these variables are discussed in the subsequent sections.

Firm performance
Felício et al. (2014) defined firm performance in terms of profitability, reduction of
investment risk, and outperformance of competitors. Financial performance is key to all
brands, as firms seek to maximize the value of the brands they manage to ensure
long-term sustainability and market dominance. Ogbonna and Harris (2000), in explaining
the link between brand equity and firm performance, stated that business performance is
a multi-dimensional and intricate phenomenon that requires specific measures for
tracking progress. Furthermore, Ambler (2000), Rust et al. (2000) believe that the type of
market a brand is situated in, determines the type of measures that would be used in
measuring performance. This assertion becomes all the more relevant to the Ghanaian
context given that most firms are reluctant to reveal their market position, and that there
exists little to no information that gives a clear picture on the market status of firms in
terms of actual market share. Even though some marketers have opined that the central
purpose of marketing is to generate healthy returns to shareholders by creating and
managing market based assets (Ambler, 2000; Doyle, 2000), other scholars such as Aaker
and Jacobson (2001) have maintained that firm performance can be measured in terms of
profits and returns on investment. For the purpose of this paper, firm performance will be
measured using the financial performance of the banks over a period of time. This is
largely due to the aforementioned lack of reliable information on the market position of
firms in the Ghanaian economy.

Model and hypothesis development
The research model appears in Figure 1. It assumes that the five dimensions of brand equity
predict firm performance. This relationship is moderated by brand likeability. The
components of the model, as well as the hypotheses developed, are discussed in a later section.

Brand awareness
One thing that gives brands power is the level of awareness of the brand in the minds of
consumers. As a construct, brand awareness is important in measuring brand equity
because without it, brand equity would be weakened or almost non-existent (Keller, 2003).
Aaker (1991, p. 61) defined brand awareness as “the ability of the potential buyer to

Brand equity

Brand awareness (H1)
Brand associations (H2)
Perceived quality (H3)
Relevance (H4)
Brand loyalty (H5)

Firm performance

Brand likeability

(H1 – H5)

H6 Figure 1.
Conceptual framework

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recognize and recall that a brand is a member of a certain product category.” Brand
awareness is important in the development of brand equity because it gives the brand a
distinct place in the minds of consumers. Keller (2013) opines that brand awareness is
critical in the decision making of consumers as it helps them to know which brands are
available and preferred in a given product category. As brand awareness consists of brand
recognition and recall (Keller, 2013), brands that are able to generate a high level of
awareness amongst their customers will increase their sales, which will in turn increase
profit and positively affect firm performance. Thus, the following hypothesis is proposed:

H1. Brand awareness has a positive effect on firm performance.

Brand associations
The aim of every firm must be to create favorable brand associations (Keller, 2008).
These have been defined as “anything linked in memory to a brand” (Aaker, 1991, p. 109),
and the more consumers associate certain experiences with a brand, the stronger the brand
association will be with that particular experience or cue (Aaker and Keller, 1990).
Customers form perceptions based on their encounters with the brand, its marketing
programs and its product performance. Brands that are able to satisfy consumers will
succeed in creating strong brand associations which inform consumers’ perceptions of the
brand, and will be protected against competitive action. A number of scholars (e.g. Belén del
Río et al., 2001) posit that brand associations are key in building brand equity, as they
represent the basis for consumer purchases (Aaker, 1991). Keller (1993) confirmed thus
when he posited that there are three types of brand associations that lead to the creation of
brand equity: attributes, benefits and attitudes. Thus, if a brand is able to successfully
create favorable associations with its attributes, benefits and attitudes, brand equity would
be enhanced, which would boost the financial performance of the firm (Aaker and Jacobson,
2001). The second hypothesis is thus proposed as:

H2. Brand association has a significant effect on firm performance.

Perceived quality
The concept of brand equity cannot be discussed without touching on perceived quality.
Aaker (1991, p. 85) defined it as “the customer’s perception of the overall quality or
superiority of a product or service with respect to its intended purpose, relative to
alternatives.” Perceived quality is an important component of brand equity and shows how
customers’ perception of a brand’s quality influences their purchase decisions. When
customers perceive a brand to be of a superior quality, they tend to prefer it and engage in
repeat purchases and positive word of mouth (Kotler and Armstrong, 2010; Keller, 2013).
Kotler (2000) asserts that there is a link between product and service quality, customer
satisfaction and company profitability, while O’Neill et al. (2016) found a direct relationship
between the quality management orientation of a firm and financial performance. Thus, the
following hypothesis is made:

H3. There is a positive relationship between perceived service quality and firm
performance.

Brand relevance
Even though brand relevance has not traditionally been included as a component of brand
equity, Stahl et al. (2012) include it as a dimension and define relevance as “the extent to
which customers find the brand to be relevant to their needs” (p. 46). They explain that for
firms to be successful in creating brand equity, their products and services must be relevant

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to the needs of customers. The brand must be able to provide some level of fulfillment which
will be distinct to customers. As explained by Aaker (2011), the consumer market is
currently so dynamic that brand categories are created and fade out at a quick pace. Brands
must therefore constantly evolve in order to remain relevant and successful with their
consumers. The importance of brand relevance to brand equity has been observed, as the
differentiation of a brand will only matter when it is perceived to be relevant by the
consumer (Mizik and Jacobson, 2008; Young and Rubicam, 2000). Indeed, Young and
Rubicam (2000), who classify the relevance of a brand as a pillar that contributes to the
overall strength of the brand, indicate that if the brand is low in relevance to consumers, it
will not be highly patronized by them. These assertions have been buttressed by the likes of
Keller (2013) and Park et al. (1986) who state that brands create relevance through
functional, experiential or symbolic benefits. Roll (2009) believes that firms must invest in
creating brands that can deliver on their core promises and in doing so, deliver relevant
products and services that will satisfy customers and create a strong sense of commitment
to the brand. Tolba and Hassan (2009) reiterated the importance of relevance as a
determinant of brand equity, and found that brand equity is positively linked with a firm’s
performance. In view of this, the study includes brand relevance as a dimension of brand
equity, and proposes the following hypothesis:

H4. Relevance is positively associated with firm performance.

Brand loyalty
Keller (2008) defines brand loyalty in terms of resonance: that level of customer-brand
relationship which depicts a sync between the brand and its customers, and which generates
peculiar behavioral outcomes such as customers actively seeking means to interact with and
share their brand experiences with others. Aaker (1991) on the other hand defines brand
loyalty as a situation which reflects how likely a customer will be to switch to another
brand, especially when that brand makes a change, either in price or in product features.
Loyalty can squarely be placed as a component of brand equity as, when consumers
respond more strongly to a brand’s actions relative to competing brands, the brand can
experience a surge in sales and resultant profitable returns on investment (Capon, 2013).
Furthermore, it has been detected that brand loyalty has an effect on firm performance
(Keller, 2003). Through brand loyalty, firms increase their profit margins whilst also
leveraging the brand and putting measures in place to withstand competitive action.
Additionally, a host of researchers such as Delgado-Ballester and Luis Munuera-Alemán
(2005), Chaudhuri and Holbrook (2001) have opined that brand loyalty provides substantial
competitive and economic benefits to a firm. Without loyalty, firms cannot achieve a
sustainable competitive advantage. The following hypothesis is proposed:

H5. Brand loyalty positively predicts firm performance.

Moderating variable
Brand likeability
Every firm desires its consumers to like and patronize their products their services (Kotler
and Armstrong, 2010). Brand likeability therefore becomes an important variable that can
be used to determine the magnitude of the relationship between brand equity and firm
performance. According to Zarantonello et al. (2016), the moment consumers begin to hate a
brand, the brand starts to decline. In recent years, researchers have tried to understand the
role of consumer emotions in purchase decisions, leading to studies on concepts such as
brand likeability (Nguyen et al., 2015). Brand likeability has been explained as based on
“attractiveness, credibility, and expertise in order to create attachment and love by

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delivering beneficial outcomes for consumers and brands alike” (Nguyen et al., 2013, p. 372).
Thus, it has been conceptualized as constituting the three dimensions of attractiveness,
credibility, and expertise (Nguyen et al., 2013). According to Landwehr et al. (2011),
consumers are indeed affected by how attractive the brand and its marketing is in
conjunction with their perceptions of its quality and superiority. Marketers have attempted
to engender the emotion of likeability through advertisements and customer experiences
(Yilmaz et al., 2011; Helkkula et al., 2012), as it is no secret that consumers gravitate toward
brands they like, and that this adoration forms the basis of their purchase decisions (Carroll
and Ahuvia, 2006). Batra et al. (2012) have also stated that consumers who have a great
liking for brands are significant assets to the firm as they are characterized by brand
advocacy and evangelism, resistance to competitor advances as well as consistent purchase
of the firm’s products and services over the course of their lifetime. In view of this, the
following hypothesis is proposed:

H6. Brand likeability moderates the relationship between brand equity and firm
performance.

Methodology
Research setting
The current study is quantitative, and a survey methodology was used to gather data from
respondents. The sample frame for the study was the 28 banks operating in Ghana as at
June 2015. Letters were sent to all the banks, explaining the rationale of the study to them
and requesting their permission to participate. At the end of three weeks, 22 banks
responded favorably to the requests and were used in the study. A list of customers who
have had current or savings accounts with the banks for at least one year was obtained from
the participating banks to serve as the respondents of the study. This was to ensure that
they could reliably rate the brand equity of the bank, from their perspective as customers. In
total, 1,100 respondents (50 from each bank) were targeted.

Questionnaire was the data collection tool. The items of the questionnaire were
anchored on a five-point Likert scale with 1 labeled as “strongly disagree” and 5 labeled as
“strongly agree.” The questionnaire was divided into three sections as:
personal information on respondents; dimensions of bank brand equity; and financial
performance. The items for brand equity were adapted from scales in the literature
(Sharma et al., 2016; Keller, 2008). Financial performance was also operationalised with
five variables and adopted from the literature (Felício et al., 2014). Finally, the five items
used to measure brand likeability were adapted from the scale developed by Nguyen et al.
(2013). To reduce potential bias resulting from forced response, “N/A” was included on
each question as an option.

To ensure the validity of the questionnaire two professors with a special research focus
on bank marketing were first contacted to review the research instrument in terms of
content and wording. Their recommendations were used to restructure the questionnaire.
The resulting questionnaire was then pilot-tested with ten Executive MBA students of the
University of Ghana Business School with a wide experience in banking. Their responses
further ensured that the content and wording of the instrument adequately reflected the
banking sector. Thus, the research instrument was considered valid to be administered.
As English language is the official language in Ghana, the respondents speak and
understand a fair amount of the language, and therefore there was no need for translation
of the research instrument.

Three research assistants were hired and trained for the survey design and
questionnaire administration. At the end of one month, 550 questionnaires were collected
out of a total of 1,100 administered to the respondents. The Ghanaian banking industry has

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an almost equal number of foreign and local banks. Twelve of the banks contacted were
local banks while the remaining ten were foreign owned. At the end of the period, the
550 responses received were used for the data analysis.

Demographic profile of the respondents
Descriptive analysis indicates that 50.6 percent of the respondents were male while
49.4 percent were female. Majority of the respondents (52.4 percent) were aged from
20-30 years. There were also 33.0 percent within the ages of 31-40 and about 12.1 percent
within the ages of 41-50. Approximately 1.2 percent each of the sampled respondents were
below 20 years or above 50 years, respectively. On education, majority of the respondents
(86.9 percent) had degrees or post-graduate degrees. Similarly, about 65.5 percent of the
respondents were salaried employees, 26.7 percent were students while 7.6 percent were
self-employed with only 0.3 percent described as unemployed. Furthermore,
the nationality statistics of the respondents indicated that 80.9 percent were Ghanaians
whereas the remaining 19.1 percent were foreigners. Finally, about 82 percent had dealt
with their banks for more than five years. The remaining 18 percent were customers who
have dealt with their banks for either five years or below.

Confirmatory factor analysis (CFA)
Structuring equation modeling using Amos 22.0 was used for measurement scale validation
and structural analysis. The two-step process using a CFA and structural path analysis, as
suggested by Anderson and Gerbing (1988), was adopted. The estimation of the
measurement model was first conducted through a confirmation factor analysis and later
on, the structural model was estimated to test the proposed hypotheses among the variables
(Hair et al., 2010). The first part involves conducting a CFA for assessing the contribution of
each indicator variable and for measuring the adequacy of the measurement model. As the
sample size of 550 was adequate and the data set was normally distributed, the model was
first specified using the maximum likelihood estimation method (Byrne, 2013). In the second
stage, an iterative model specification was done in order to develop the best set of items to
represent the various constructs through refinement and retesting. At that stage, items that
did not meet the validity and reliability tests were dropped (Byrne, 2013). The final stage
was the estimation of the goodness of fit parameters of the overall model to test the extent to
which the data supported the research model. The most commonly used parameters for this
assessment are the likelihood ratio χ2, the ratio of χ2 to degrees of freedom ( χ2/df ), the root
mean square error of approximation (RMSEA), and comparative fit index (CFI). As indicated
in Table I, the measurement model results showed a very good model fit with χ2¼ 493.57
(df¼ 274), χ2/df¼ 1.8, CFI¼ 0.958, TLI¼ 0.95 and NFI¼ 0.91. The RMSEA was 0.05,
PCFI¼ 0.827, PNFI¼ 0.778, CFI¼ 0.96, TLI¼ 0.95.

Reliability and validity test
Two types of reliability tests were used in this study: internal consistency and construct
reliability (Fornell and Larcker, 1981). Using SPSS version 20.0, Cronbach’s α coefficients
were used to test the internal consistency of the instrument. The α coefficient measures
the extent to which the multiple indicators for a latent variable cluster together.
For unidimensional scales, a Cronbach’s α value of 0.6 or more is considered acceptable
(Hair et al., 2010). The results indicate high Cronbach’s α results for the items, ranging
between 0.88 and 0.93, as provided in Table I. Furthermore, for structural equation
modeling, construct reliability is measured using composite reliability (CR) because it is
more parsimonious than the Cronbach’s α (Bagozzi and Yi, 1988). Thus, as evidenced in

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Table I, CR values for the constructs also ranged from 0.89 to 0.93, which exceed the
threshold value of 0.7 (Hair et al., 2010).

According to Hair et al. (2010), validity measures the extent to which the set of indicators
accurately represent a construct. In this study, two measures of validity were tested;
convergent validity and discriminant validity. Convergent validity measures the degree to
which the items truly represent the intended latent construct. It is assessed by factor
loadings and average variance extracted (AVE) (Hair et al., 2010). A rule of thumb is that the

Item Loading t-value

Brand associations (CR¼ 0.90, AVE¼ 0.75, α¼ 0.89)
My bank has an image doing the right things BAS8 0.72 Fixed
I have good memories linked to my bank BAS9 0.94 15.35
My bank has good association with third parties BAS10 0.92 15.13

Perceived quality (CR¼ 0.93, AVE¼ 0.73, α¼ 0.93)
My bank products are of better quality than the generic alternatives PQ5 0.78 Fixed
My bank’s products are worth the money PQ6 0.86 15.87
I think that my bank has good-quality products PQ7 0.90 16.90
I think that my bank products are of good quality PQ8 0.91 17.08
In general, I believe that my bank products are superior in quality compared to the
alternatives

PQ9 0.81 14.62

Brand relevance (CR¼ 0.93, AVE¼ 0.76, α¼ 0.93)
The services my bank offers makes life easier for me BR2 0.87 Fixed
My bank has various products/services tailored to meet my needs BR3 0.85 18.69
My bank is a one stop centre for all my banking activities BR4 0.88 19.87
The bank provides me with solutions to my banking problems BR5 0.88 19.82

Brand loyalty (CR¼ 0.91, AVE¼ 0.66, α¼ 0.92)
I am loyal to my bank BL5 0.77 Fixed
I consider myself an advocate of my bank BL6 0.81 14.42
I will continue to save with my bank BL8 0.83 14.86
If I need bank services, I usually use my bank BL9 0.85 15.29
If similar bank services cost the same, I choose my bank BL10 0.80 14.09
I love my bank BL4 0.79 13.96

Brand awareness (CR¼ 0.75, AVE¼ 0.69, α¼ 0.69)
I easily recognize my bank among other banks BA1 0.88
I have a good opinion about my bank BA2 0.82
I know the color of my bank BA3 0.79
I know the services my bank offers BA4 0.78
I recognize the logo of my bank BA5 0.84
If someone asks me about banks, my bank easily comes to mind BA6 0.86

Brand likeability (CR¼ 0.73, AVE¼ 0.63, α¼ 0.63)
My bank is attractive BL1 0.76
My bank is honest in its dealings with me BL2 0.79
I am emotionally attached to my bank BL3 0.84
I love my bank BL4 0.78
It is convenient to deal with my bank BL5 0.80

Brand performance (CR¼ 0.87, AVE¼ 0.62, α¼ 0.88)
My bank consistently increases its revenue BP9 0.75 Fixed
My bank is profitable BP10 0.62 10.29
My bank has grown over the years BP11 0.90 15.43
My bank has increased its market share BP12 0.74 12.45
My bank is interested in social projects that benefits all stakeholders BP13 0.88 15.01

Table I.
Confirmatory factor
analysis – results

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factor loadings should be at least 0.50 or higher, and be statistically significant (Hair et al.,
2010). Following the rules described above, nine items were deleted from their indicators
because of low loadings, re-specifications and retesting. In addition, the AVE from items
by their respective constructs should be greater than the variance unexplained
(i.e. AVEW0.50). The results presented in Table II indicate AVE values between 0.6 and
0.75. The values were all greater than 0.50, thereby meeting the AVE criteria set by Fornell
and Larcker (1981). The loadings and the AVE results indicated convergent validity.

Discriminant validity measures the extent to which latent factors are distinct, i.e. they should
not correlate so highly that they seem to measure the same underlying dimension (Siekpe, 2005).
Discriminant validity is established if the AVE of a variable (within factor shared variance) is
larger than the squared correlation coefficients between variables (Fornell and Larcker, 1981).
The results in Table II provide support to indicate strong discriminant validity.

Assessment of the hypothesized relationships
The structural model was used to examine the proposed hypotheses for the study.
The results appear in Table III. In the first place, we assessed the impact of the control
variables on bank performance. The result indicates that age and number of years with the
bank were significant on the relationship between bank brand equity and bank
performance. Next, we estimated the main effect model where the direct relationship
between the brand equity construct and bank performance were estimated. The results
indicate that brand relevance, perceived quality, brand loyalty and brand associations were
significant in predicting retail bank performance. This implies that H2-H5 were accepted
while H1 was rejected. We also investigated the direct relationship between brand
likeability and financial performance. The relationship was found to be significant. In the
final hypothesis, we estimated the moderating role of brand likeability on the relationship
between the dependent and the independent variable. This was assessed by interacting
brand likeability, represented by a construct with a standardized computed score of its
items, with the various dimensions of brand equity. The result indicates that brand
likeability moderates or improves the relationship between brand loyalty, perceived quality
and brand relevance and bank performance thereby providing support for H5.

Discussion
The study was conducted to determine the moderating role of brand likeability on the
relationship between brand equity dimensions and retail bank performance. Our results
indicate that brand equity indeed influences the financial performance of retail banks.
This implies that the image a retail bank occupies in the minds of customers influences its
patronage and subsequent financial performance. Our research is consistent with prior
studies (García-Osma et al., 2015; Aaker and Jacobson, 2001; Ogbonna and Harris, 2000) who
have found that brand equity creates value for firms which leads to financial performance.

Mean SD 1 2 3 4 5 6 7

1 Brand association 3.5 0.95 0.75
2 Perceived quality 3.5 0.90 0.55 0.73
3 Brand relevance 3.5 1.07 0.42 0.59 0.76
4 Brand loyalty 3.6 1.05 0.46 0.55 0.67 0.66
5 Brand awareness 3.7 1.40 0.45 0.43 0.37 0.42 0.69
6 Brand likeability 3.8 1.61 0.51 0.28 0.46 0.47 0.35 0.63
7 Brand performance 3.4 0.93 0.31 0.26 0.41 0.28 0.42 0.44 0.62
Notes: Diagonal elements are the AVEs; off-diagonal elements are the squared correlations

Table II.
Correlations
and AVEs

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On the direct predictors, it was found that perceived service quality is a brand equity
construct that directly predicts bank performance. The quality of the service a retail bank
delivers to customers is essential in ensuring patronage and subsequent profitability. When
a bank provides reliable services, when the atmosphere is conducive for customers, when
the services are better than that of the competition, when the retail banks show care and
concern for customers, and when they stick to promises made to customers, it enhances
consumer perceptions of the bank’s service delivery, which affects customer satisfaction
and retail bank performance. Our results resonate with that of O’Neill et al. (2016), Keller
(2013), who found a direct relationship between service quality and financial performance.

Brand relevance also directly predicted retail bank performance. This indicates that
when retail banks perform services which are relevant to customers in terms of fulfillment of
their needs, when the retail banks provide one stop service centers and when they provide
solutions to all customer needs, they become relevant and irreplaceable to customers, with a
concomitant increase in retail bank performance. Our results are similar to that of Stahl et al.
(2012), Roll (2009), Tolba and Hassan (2009) who found a positive relationship between
brand relevance and firm performance.

In addition, the study found that brand associations predict financial performance. For
retail banks, the memories associated with them, the country of origin effects, the linkage to
a corporate brand, and the quality of management could all have an impact on retail bank
performance. The result is consistent with scholars who have associated positive brand
image with brand performance, with the understanding that brand associations contribute
to building brand image (Belén del Río et al., 2001).

Model 1 Model 2
β t-value β t-value

Controls
Age 0.66 4.21** 0.66 4.56**
Gender 0.05 0.36 0.05 0.26
Education 0.22 1.40 0.07 0.56
Years with bank 0.12 2.27** 0.22 0.35

Hypothesized paths
Brand awareness 0.07 0.140 0.63 0.55
Brand association 0.21 −3.07* 0.38 2.41**
Brand relevance 0.36 4.04** 0.45 5.62**
Perceived quality 0.54 6.33*** 0.66 6.81**
Brand loyalty 0.26 3.45** 0.32 4.55**
Brand likeability 0.51 2.29** 0.22 2.26**

Interaction effects
Likeability× brand awareness 0.61 0.22 1.56
Likeability× brand association 0.22 0.61 2.59**
Likeability× brand relevance 0.32 0.32 ***
Likeability× perceived quality 0.19 0.19 ***
Likeability× brand loyalty 0.61 0.62 ***
χ2/df 1.8 1.76
CFI 0.96 0.96
TLI 0.95 0.95
NFI 0.91 0.91
RMSEA 0.05 0.05
PCFI 0.83 0.83
PNFI 0.78 0.77
Notes: *p⩽ 0.05; **p⩽ 0.01; ***p⩽ 0.001

Table III.
Structural model

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The study also found that brand loyalty leads to retail bank performance. When
customers show frequent and repurchase behaviors, and when they display positive word of
mouth about their retail banks, this triggers increased revenue and profitability for retail
banks. Thus, firms that achieve continuous purchase of their services are firms who satisfy
customers and thus, improve their financial performance.

Again, the study found that brand likeability has a significant relationship with brand
performance. This indicates that when customers dislike brands, it influences their repeat
purchases, which ultimately influences the financial performance of retail banks in Ghana.
Thus, the often-assumed direct relationship between brand equity and financial
performance could be complicated by brand likeability.

Brand awareness was not found to be significant in predicting financial performance.
This indicates that simply being aware of brands is not enough to push customers into
repeat purchases, which improves financial performance.

Implication of the study
Our study contributes to prior literature on the relevant dimensions of brand equity. Most
firms exist with the objective of ensuring adequate profitability for the owners. Brand
equity literature provides a way by which this could be achieved for firms. While the
traditional operationalization of brand equity uses four items, our study extends the brand
equity model to include brand relevance (Stahl et al., 2012), and has found it to be a
significant component of the construct. Again, we have shown from this study that the
components of brand equity can lead directly to bank performance. Our result supports the
burgeoning literature that argues for the brand equity-performance link (Keller, 2013;
García-Osma et al., 2015; O’Neill et al., 2016). In addition, however, by moderating the
relationship with brand likeability, we have shown that the often-assumed direct
relationship between brand equity and financial performance can be complicated by
emotional constructs like brand likeability. Furthermore, most of the prior studies were
conducted from the Western world. To date, no study has addressed these issues from the
sub-Saharan African context and our study fills the void. Our result provides empirical
evidence from Ghana, an emerging economy.

Moreover, the study has some managerial implications for building strong brand equity
that could improve on the financial performance of retail banks. The need to improve service
quality as an element of brand equity in the banking sector in order to improve on financial
performance has been highlighted in this study. Service quality is arguably one of the most
desirable objectives firms pursue in today’s competitive environment. It includes the core
service delivered, as well as when and how it is delivered. The need for banks to have
service blueprints and trained personnel to deliver services as promised cannot be
overemphasized. Banks must have products that are of superior quality on the market, and
worth the money that customers pay for the services. These products must be better than
the alternatives available, and be delivered in the right atmosphere to improve overall
customer experience.

In addition, customer loyalty must be strongly pursued in order to achieve brand equity
since it leads to financial performance. Customers must be brought to the point where they
love the bank, and are not only loyal to it themselves, but also act as advocates of the bank
to their friends and family. They must consistently choose the bank over other similar
banks whenever they need bank services, and plan to continue saving with their banks.
Loyalty rewards and customer relationship building strategies, among others, could be
implemented as defensive marketing strategies to prevent customers from switching to
other service providers.

Brand association was also found to be a predictor of financial performance in retail
banks. Techniques such as strong management, and linkage with parent brands and adored

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celebrities could be used by banks to create strong memories and images for customers.
Customers must recognize that their bank has a good association with third parties, and has
an image of doing the right things. Their experiences with the bank must engender good
memories which they will associate with the brand. Managers must therefore pursue these
as aims of their brand-building activities.

Furthermore, the core promises of the bank must be delivered in order to enhance the
brand’s relevance to customers. The services of the bank must make life easier for
consumers, being tailored as much as possible to their personal needs. Additionally, the
bank must provide comprehensive solutions to consumers’ banking problems in a way that
enhances the relevance of the brand in their lives. Again, although brand awareness was not
found to be significant, retail banks must continue to create strong awareness for their
brands in order to attract customers, leading to greater revenue.

Finally, it is necessary for retail banks to engage in activities that enhance their likeability.
As the results have shown, brand likeability strengthens the relationship between brand
equity and financial performance. Retail banks must invest in doing what it takes to bond
emotionally with their consumers. They must create convenience for their consumers, being
attractive to them and honest in their dealings with them, thus engendering strong emotional
attachments that are based on attractiveness, credibility, and expertise.

Limitations of the study and directions for future study
The addition of brand relevance as a construct to the original dimensions proposed by
Aaker (1991), and its significance in predicting financial performance indicates that the
framework by Aaker (1991) is illustrative and not comprehensive. Future studies could
integrate other variables in measuring the brand equity construct. Additionally,
performance was measured subjectively with self-reported items. Future studies may
attain greater precision with their findings by implementing objective measures such as
net profits, return on assets and equity, or deposits, for determining bank performance.
Moreover, literature is ripe with emotional-laden constructs like brand love and brand
engagement, which affect how customers interact with their brands. Future studies must
engage more of such variables in order to provide evidence of moderation or mediation
in the relationship between brand equity and notable outcomes such as loyalty,
satisfaction and financial performance. In that case, we could demonstrate that the direct
relationship between brand equity and financial performance, for instance, has been
over-simplified in prior studies. Finally, the study was focused on one country and on only
retail banks. Further studies could expand the scope of the study into multiple sectors and
even other counties.

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Corresponding author
Bedman Narteh can be contacted at: bnarteh@ug.edu.gh

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