(2012). An Empirical Study on Brand Equity in Malaysian Fast Food

Transcription

CHAPTER 1
INTRODUCTION
1.1 Introduction
Fast food brand is defined as those restaurants that provide expedited food
service, established standard operating procedure, offered Western pattern diet, and had
franchises in multiple states or nationwide (Ashkanasy & Nicholson, 2003; Block,
Scribner & DeSalvo, 2004; Burdette & Whitaker, 2004; Slattery, Boucher, Caan, Potter
& Ma, 1998). According to Kim and Kim (2004), brand name is the key assets for fast
food companies. If manages appropriately, the positive brand name will drive to
competitive advantage (Szymanski, Bharadwaj & Varadarajan, 1993), price premium
(Keller, 1993), low switching to better competitors (Narayandas, 1996), and
recommendation to others (Russell-Bennett, McColl-Kennedy & Coote, 2007). Brand
equity existed when a consumer had preference in choosing a focal branded product,
but not an unknown brand that had the identical level of product features (Kamakura &
Russell, 1993). The concept of brand equity consists of different dimensions such as
perceived quality, brand awareness, brand image, brand loyalty, and other proprietary
brand assets (Aaker, 1996). Up-to-date, the existing literature on brand equity model
within the fast food industry was still sparse (Tan, Hishamuddin & Devinaga, 2011).
Besides, the identification of causal effects among brand equity dimensions was not
clearly extended by the implication of marketing theory (Gil, Andrés & Salinas, 2007;
Konecnik and Gartner, 2007). Such limitations have caused ambiguity in managing and
predicting the tangible and intangible characteristics of fast food brand (Kim and Kim,
2005). For these reasons, this study was conducted to fill in the limitations as
mentioned.
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1.2 Problems Background
1.2.1 Fast Food Industry in Global
According to Datamonitor (2009), in year 2008, global fast food market had
reached a value of RM479.57 billion, with growth rate of 6.6%. In term of transaction
value, the volume reached 85.8 billion of transactions, counted as 3% growth rate. On
the other hand, global fast food market were expected to reach a total revenue of
RM620 billion, while transactions value were projected to have a volume of 94.7
billion, an increase of 29.3% and 10.4% from year 2008 to 2013 (Datamonitor, 2009).
As a result, fast food was considered as an important industry due to its global trend
(Oyewole, 2007; Van Zyl, Steyn & Marais, 2010).
Out of numerous types of fast food segment, Quick Service Restaurant (QSR)
ranked as the leading segment; this was because QSR accounted for 66.3% of the
overall value in the global fast food market, and American brands dominated
approximately 52.4% of the overall global fast food market (Datamonitor, 2009).
1.2.2 Fast Food Industry in Malaysia
Hamisah (2007) declared that many U.S brand companies dominated the
Malaysian fast food industry, for instance McDonalds, Burger King, Kentucky Fried
Chicken, Kenny Rogers Roasters, A&W, Pizza Hut, Domino Pizza, Shakeys Pizza,
T.G.I.F, Chilis and so on. Kentucky Fried Chicken (KFC) brand became the most
flourishing fast food restaurant in Malaysia, this could be supported by KFC dominated
the market share with 44% (Aseambankers, 2007) and successfully expanded more
than 500 outlets in Malaysia (The Star, 2011).
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According to Aseambankers (2007), KFC Malaysia was owned by KFC
Holdings Bhd, a Malaysian public-listed company, which controlled over 60% of the
fast food market in Malaysia, inclusive other brands such as Pizza Hut, Rasamas, and
Ayamas. Figure 1.1 illustrated KFC, McDonald’s, and Pizza Hut were the leaders in
the Malaysian fast food industry.
Source: Aseambankers (2007)
Figure 1.1: Estimated Market Share of Fast food Segment in Malaysia
Hamid (2009) outlined that the government had been trying to provide support
to the Malaysian fast food brand through government assistance programs, but it was
still at an introductory stage. A number of Malaysian franchise systems had started
expanding to other countries, such as Singapore, Indonesia, China, Dubai, India, and
Bahrain. Hamid (2007) indicated that Marrybrown was present in over ten countries,
with Middle East as its stronghold. Bernama (2009) reported that 1901 Hot Dogs, a
Malaysian brand had enjoyed good response from overseas such as Singapore. Even
though Malaysian brands received good evaluation form other countries, only a few of
them were doing well, reason being lack of expertise in branding and marketing
(Marshall Cavendish, 2009). Furthermore, the market share of fast food in Malaysia
was subjugated by foreign brands (Aseambankers, 2007).
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1.2.3 Issues Related to Brand Equity in Fast Food Restaurants
Compared to other types and concepts of restaurant business, such as mid scale
restaurant, upscale restaurant, and café, fast food restaurants had gathered greater
interest in building a strong brand because of the products and services were not
naturally differentiated (Tan et al., 2011). Furthermore, the channels of distribution
were not unique. As a result, consumers relied on price setting and brand equity for the
purpose of differentiating one brand from another (Aaker, 1996).
William (2000) argued that managers could also depend on price manipulations
when there was nonexistence of well-built brands. Siguaw, Mattila and Austin (1999)
identified fast food players had treated price promotion as an important marketing
activity, such practice had resulted in continual price wars that reduced revenue,
earning per product sold and product quality. For instance, McDonald’s Weekday
Breakfast Special and McValue Lunch, KFC Jom Jimat, Marrybrown Makan Enak,
Makan Jimat, 1901 Hot Dogs 19th Lucky, and Domino’s Pizza Incredible Meal.
However, MIDF Research (2010) stated that food and beverage manufacturers could
not escape from high raw materials costs, for instance, Nestle, F&N, and fast-food
firms were expected to face some costs pressure. They had to increase the selling price
in order to mitigate the downsides. As a result, promotional strategies were not the best
marketing solution in gaining fast food market share.
Rao and Monroe (1989) advocated that brand name seemed to be positively
associated with consumer product evaluations, perceptions of quality and purchase
rates. Kim and Kim (2004) highlighted that brand name was the key assets for fast food
companies. This could be supported by the positive brand name, such as recognizable
brand identifiers would drive to competitive advantage (Szymanski et al., 1993). For
this reason, Kotler, Bowen and Makens (2003) indicated that consumers would not
have difficulty in recognizing the symbol of Thank Goodness It’s Friday (TG.I.
Friday’s) and McDonald’s.
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According to Keller (1993), branding could have great effect on the price
premium of the product offered, especially in a market where the product was identical.
It added value to a basic product or service, which prompted repeated purchase (Chiou
& Droge, 2006), low switching to better competitors (Narayandas, 1996), and
recommendation to others (Russell-Bennett et al., 2007). Consequently, brand equity
facilitated the sustainability of business by increasing market share, which directly
ensured the consistency of income stream and cash flow of the company (Aaker, 1996).
Therefore, fast food restaurant had to focus on the effort to develop brand equity. The
reason being given as brand equity had mitigated the focus on price promotion.
However, to the question “Is it sufficient to adopt the original four dimensions of brand
equity as proposed by Aaker (1991) in fast food study?” Such question remained
unclear and lead to the potentiality of a research gap.
Furthermore, most of brand equity studies were conducted in the United States,
Europe, China and Korea (Gil et al., 2007; Kim & Kim, 2005; Tong & Hawley, 2009;
Yoo, Donthu & Lee, 2000); the findings might not have been applicable to the market
without empirical testing. The results from previous studies might not be similarly
associated with consumers in other countries with different cultures and consumer
behaviors (Chou, Chen, & Wang, 2012), such as multiracial consumers in Malaysia.
Studies had indicated that consumers behave differently across countries and
cultures, thus, different value system existed among consumers from different parts of
the world (Corkindale & Lowe, 1998; Grunert & Scherhorn, 1990; McCracken, 1989;
Tansuhaj, Gentry, John, Manzer & Cho, 1991). This could be further supported by
some significant inconsistencies which existed in consumer responsiveness to different
marketing efforts, even though there are some similarity of geographical and cultural
between Malaysia, Taiwan, and Thailand (Huff & Alden, 1998). As a result, there was
a need to develop a consumer-based brand equity model in the Malaysian context of
fast food industry empirically.
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1.2.4 Brand Familiarity as Additional Dimension
Interestingly, most of the people knew fast food brands such as A&W,
McDonald’s, KFC, and Pizza Hut since childhood. Consumers were more familiar with
famous fast food brands as compared to well-known product brands such as MercedesBenz, BMW, Nike, Prada or Adidas (Tan et al., 2011).
Referring to Mano and Davis (1990), the familiarity of fast food brand played
an important role in product preference. The role of familiarity also appeared to be far
greater for the situation where the consumer was looking for a simple rule for decision
making (Batra & Ray, 1985), such as fast food. This could be explained by most of the
Generation Y, who were born between years 1982 to 2003, recognized fast food brand
(see Table 1.1) since childhood because they were frequently exposed to fast food
advertisement during children programs. Schlosser (2002) expressed the flavors of
childhood food which had left an indelible mark, and where adults often returned to
them, without always knowing why.
Table 1.1: Familiar Products of Fast Food Brands
Fast Food Brand
Products that Appeared from Our Mind Due to Familiarity
McDonald’s
Big MacTM, McChickenTM, Filet-O-FishTM, and Happy MealTM
KFC
Hot & Spicy Chicken, O.R. Chicken, Whipped Potato, and Zinger Burger
Pizza Hut
Super Supreme, Island Supreme, and Seafood Lasagna
A&W
Root Beer, Mozza Burger, and Coney Dog
Study conducted by other researchers had also indicated that brand familiarity
drove to positive attitude towards the brand, consumer confidence, and purchase
intention (Laroche, Toffoli, Kim & Muller, 1996). It also served as an important
platform in mitigating the possible unenthusiastic impact of a negative trial experience
(Smith, 1993). Besides, Schlosser (2002) stated brand familiarity had transformed fast
food to become “comfort food”, which served as a source of pleasure and reassurance.
Thus, brand familiarity served as an additional dimension of consumer-based brand
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equity in the context of fast food industry in Malaysia. The exclusion of brand
familiarity was not sufficient to explain the effort in developing brand equity (Baker,
Hutchinson, Moore & Nedungadi, 1986).
1.2.5 Brand Trust as Additional Dimension
Beside brand familiarity, what was the other factor that contributed to the
preference of fast food brand? There was a high consistency in the operation of fast
food, for instance taste, portion, price, presentation, promotion, services, business hours,
environment, and facilities. This was because fast food chains maintained standard
operating procedures.
For these reasons, the fast food meals that were bought from any outlets had
high similarity. For instance, McDonald’s French Fries that was presented in Mid
Valley Megamall, a Kuala Lumpur outlet was not different in term of taste and portion,
as compared to McDonald’s French Fries which was purchased from Api-Api Centre
outlet in Kota Kinabalu, Sabah. As a result, consumers relied on the capability and
accountability of the brand instead of people involved in the restaurants (Keller, 1993).
The reliability of the brand’s functions had led to the feeling of security held by the
consumer when interacted with the brand (Johnson & Grayson, 2005). This statement
was supported by Table 1.2 as extracted from the study of McDonald’s (2011), KFC
(2011), and Pizza Hut (2011).
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Table 1.2: Consistency of Business Operation and Performance of Fast Food
Brands
Items
Descriptions
Food preparation
Food presentation
Food category
Standard operating procedure (SOP)
Simple and clean
Children, breakfast, dessert, set meal,
beverage.
Accurately charge and same price
Fast and convenience
Yes
Breakfast, lunch, refillable
Yes
Available in every states
24 hours or according to standard hours
Air-conditional, Wifi, music
From time to time
Food price
Food served
Halal
Promotion
Nutrition information
Location
Operating hour
Environment
Advertising
Consistent
across
Different
Branches
Source: McDonald’s (2011), KFC (2011), and Pizza Hut (2011)
Morgan and Hunt (1994, p. 23) stated that trust exists “when one party has
confidence in an exchange partner’s reliability and integrity.” This could be further
explained that the formation of trusted business relationships would be established
when there is an understanding of exchanged partners in between the brand and
consumer (Morgan & Hunt, 1994). In the context of fast food business, both parties
would mutually benefit as trust is created with an exchange of environment in which
the brands provided consistent services to its customers across different outlets, which
indicated high reliability and integrity status of the brand itself, and results the brand is
reliable and responsible for the interests and welfare of them at anywhere and at
anytime, consequently such a situation could be explained as brand trust (DelgadoBallester & Munuera-Aleman, 2005). Therefore, brand trust serves as an important
dimension of consumer-based brand equity in the context of fast food industry in
Malaysia. The exclusion of brand trust was not sufficient to explain the efforts in
creating brand equity.
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1.2.6 Brief Literature Gaps in Brand Equity
The effort of developing brand equity is a long-term program and requires the
regularity of marketing efforts (Aaker, 1996). According to Kim and Kim (2005), there
are four dimensions of brand equity in fast food industry, namely perceived quality,
brand awareness, brand image, and brand loyalty. However, only brand awareness and
perceived quality had significant effects on corporate performance (Kim & Kim, 2005).
Tan et al. (2011) argued that the high numbers of brand equity dimensions, i.e.
six as proposed in has gained research interest among academician and practitioners.
For instance: “Are there any pre-determinate constructs among the brand equity
dimensions?” “Are there any direct contribution of a) each dimensions b) certain
dimensions to brand equity?” “What subsequent benefits could brand familiarity and
brand trust contribute in the context of fast food industry?”
Hence, there was a need to identify the causal relationships among dimensions
of brand equity in the Malaysian context of fast food industry; this could serve as a
platform in answering above stated research questions. The investigations of causal
directions for brand equity dimensions were important because it helped to identify a
clear direction for strategy planning.
Aaker (1991) indicated that the dimensions of brand equity were intimately
interrelated. However, Agarwal and Rao (1996) highlighted that the dimensions could
have causal effects; in other words, there was potentiality of causal relationships among
the dimensions of brand equity. Aaker (1991) suggested that brand loyalty could be
influenced by the other dimensions of brand equity, such as perceived quality. This was
supported by Gil et al. (2007), indicating that brand awareness/association had direct
effect on brand loyalty, and only brand loyalty positively affected on brand equity.
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Similarly, Yoo and Donthu (2001) noted that the dimensions of brand equity
had sequential effects. This could be further explained, as perceived value was the
antecedent of brand awareness and brand association, and both brand awareness and
brand association had influenced on brand loyalty. Tong and Hawley (2009)
empirically proved that only certain dimensions have causal effect on brand equity;
they further explained that the existence of indirect effects, both brand association and
brand loyalty served as mediating variables in explaining the relationships between
brand equity and perceived quality or brand equity and brand awareness.
In the apparel market, Tong (2006) argued that there were significant numbers
of causal effects existed among the dimensions of brand equity, which highlighted the
important of causal relationships. However, only few empirical research studies (Pike,
Bianchi, Kerr & Patti, 2010; Boo, Busser & Baloglu, 2009; Rosa & Riquelme, 2008)
focused on identifying the causal relationships among brand equity dimensions
simultaneously, due to the complexity of research design and analysis.
Most of the researchers purely indicated that the relationships between various
variables and brand equity (Tong & Hawley, 2009; Norjaya, Mohd Nasser & Osman,
2007; Yoo, Donthu & Lee, 2000), brand resonance (Norzalita & Norjaya, 2010), or
brand outcomes (Baldauf, Cravens & Binder, 2003; Henry, Catherine & Ada, 2010;
Kim & Kim, 2005). Furthermore, there were no implication of cognitive-affectiveconative on Aaker’s (1991, 1996) or Keller’s (1993, 1998) brand equity model, which
classified brand equity dimensions based on hierarchy of effects theory (Belch & Belch,
2009).
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1.3 Problem Statements
Previous studies found that perceived quality, brand awareness, brand image,
and brand loyalty were dimensions of brand equity (Henry et al., 2010; Kim & Kim,
2005). However, the findings for brand equity dimensions were inconsistent across
different industries and products (Boo et al. 2009; Pike et al., 2010; Xu & Andrew,
2009). Therefore, past studies had shown that brand equity dimensions had not assisted
in anticipating the development of brand equity in Malaysian fast food industry. This
was supported by brand familiarity as indicated by Schlosser (2002) and brand trust by
Delgado-Ballester and Munuera-Aleman (2005). These dimensions might play
important dimensions of brand equity in the context of fast food industry, but not for
other type of products or industry. Thus, the summary of the problem statement is
presented as below:
“To what extent do the brand familiarity and brand trust served as additional
dimensions of consumer-based brand equity in the Malaysian context of fast food
industry”
Although fast food industry had huge market size, increasing economy, and
growth opportunities, Malaysian fast food brands lacked expertise in branding and
marketing (Marshall Cavendish, 2009). Furthermore, despite the huge demand for U.S
brands and purchasing power for foreign fast food brands which existed in Malaysia,
only a few successful Malaysian fast food brands had survived (Hamid, 2009).
According to Keller (1993), branding had a great effect on the price premium of
product offered, especially in a market where the product is similar. Brand equity
added value to a basic product or service, for instance repeat purchase (Chiou & Droge,
2006), low switching to better competitors (Narayandas, 1996), and recommendation to
others (Russell-Bennett et al., 2007). Consequently, brand equity facilitated the
sustainability of business by increasing the market share, which directly ensured the
consistency of income stream and cash flow of the fast food company (Aaker, 1996).
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For these reasons, it is important to know how to develop a brand equity model
in the Malaysian fast food industry. Nevertheless, only few empirical research studies
(Pike, Bianchi, Kerr & Patti, 2010; Boo, Busser & Baloglu, 2009; Rosa & Riquelme,
2008) had focused on identifying the causal relationships among brand equity
dimensions simultaneously, due to the complexity of research design and analysis.
Furthermore, there was no classification of brand equity dimensions that was based on
hierarchy of effects theory, which was a general guideline for the development for most
of the available marketing models (Belch & Belch, 2009). Subsequently, the summary
of the problem statement is illustrated as follow:
“To what extent that the consumer-based brand equity could be developed in the
Malaysian context of fast food industry”
1.4 Research Questions
Four research questions were derived from the problem background and
problem statement such as:
1) Does brand familiarity serve as an additional dimension of consumer-based brand
equity in the Malaysian context of fast food industry?
2) Does brand trust serve as an additional dimension of consumer-based brand equity in
the Malaysian context of fast food industry?
3) What are the causal relationships among dimensions of consumer-based brand
equity in the Malaysian context of fast food industry?
4) How do we develop consumer-based brand equity model in the Malaysian context of
fast food industry?
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1.5 Research Objectives
Specifically, this study had derived four research objectives, which were
informed and inspired from the research questions as illustrated above. The following
four research objectives reflect to the current research gaps of consumer-based brand
equity in the Malaysian context of fast food industry. The detail of the research
objectives were discussed as below.
Research objective 1: To examine brand familiarity as the additional dimension of
consumer-based brand equity in the Malaysian context of fast food industry.
Thus, this study firstly identified the significance level of the hypotheses that related to
brand familiarity. Secondly, this study had focused on the squared multiple correlations.
Finally, the study had re-tested the model without the inclusion of brand familiarity.
Research objective 2: To examine brand trust as the additional dimension of
Basically, the investigations of brand trust were similar to brand familiarity as
mentioned above.
Research objective 3: To investigate the causal relationships among dimensions of
This study had included brand familiarity and brand trust in the proposed framework. A
comprehensive set of causal relationships among the dimensions of consumer-based
brand equity had been tested in a structural model simultaneously. Subsequently, the
sequential order among the brand equity dimensions, and the significant compound
paths could be identified.
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Research objective 4: To develop consumer-based brand equity model in the
Malaysian context of fast food industry.
Firstly, the proposed model had to conciliate all the reliability and validity assessments
for measurement and structural model, before it could be claimed as a statistically valid
model. Next, this study compared the proposed model with the existing theories, such
as Aaker’s (1991) and Gil et al.’s (2007) model. The main purpose of this study was to
identify whether there were any significant different of results, such as the causal
effects and squared multiple correlations. Lastly, the proposed model had to be
supported by the interpretation of general marketing literatures.
1.6 Justification of Research
This study highlights three important contributions in brand equity. Firstly, this
study is aimed to extend consumer-based brand equity model by decomposing brand
familiarity and brand trust. These could be supported by the role of familiarity appeared
to be far greater for the situation where the consumer was looking for a simple rule for
decision making (Batra & Ray, 1985), such as fast food. On the other hand, DelgadoBallester and Munuera-Aleman (2005) identified that brand trust could be resulted
from the high reliability and integrity status of the fast food brand itself. As a result, the
exclusion of brand familiarity and brand trust were not sufficient to explain the efforts
to develop brand equity, especially in the context of fast food industry.
Secondly, this study was attempted to fill the gap in research by demonstrating
a comprehensive set of casual relationships among brand equity dimensions. Up-todate, only few empirical research studies (Pike et al., 2010; Boo et al., 2009; Rosa &
Riquelme, 2008) focused on investigating the causal relationships among brand equity
dimensions. Furthermore, the identification of causal effects was not clearly extended
by the implication of hierarchy of effect theory (Gil et al., 2007; Konecnik & Gartner,
2007). For instance, there were still no consensus about the sequence or causality
between cognition and affect (Oliver, 1997; Franzen & Bouwman, 2001). In additional
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to that, Barry and Howard (1990) stated that there were significant disagreement
regarding the order of the three stages, the model could be presented in cognitionaffect-conation, cognition-conation-affect, affect-cognition-conation, affect-conationcognition, conation-cognition-affect, or conation-affect-cognition. Subsequently, this
might lead to the confusion for the justification of causal effects. This purposeful
research idea, served as an important research in contributing as a general guideline for
the establishment of causal effects among the dimensions of consumer-based brand
equity.
Thirdly, this study had provided a better conceptualization for the consumerbased brand equity dimensions, which have led to better measurement of the variables.
Several researchers have explored brand equity measurement based on customers’
perspectives (Park & Srinivasan, 1994; Washburn & Plank, 2002; Yoo et al., 2000).
However, there was lack of research focused on how to characterize the consumer’s
response towards the brand. Subsequently, some research studies indicated that brand
measurement model had to be free from the establishment marketing literature (Boo et
al., 2009; Delgado-Ballester & Munuera-Aleman, 2001). This study had incorporated
cognitive, affective, and conative components into categorization of brand equity
dimensions, which were extremely similar to the interpretation given by some scholars
to the term brand equity (Grimm, 2005). Consequently, it reduced the ambiguous for
the conceptualization of consumer-based brand equity dimensions.
As a conclusion, this study enhanced the conceptual framework of consumerbased brand equity. It empirically examined the applicability of the existing consumerbased brand equity models by integrating additional dimensions and provided a more
practical framework, which served as a platform for future research in the hospitality
industry.
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According to Marshall Cavendish (2009), Malaysian fast food brands lacked
expertise in branding and marketing. Importantly, they did not equip themselves with
the fundamental idea in designing and mapping branding tools. Practically, this study
had identified four distinctive steps of brand equity creation in the Malaysian fast food
industry, which have produced a source for brand management in improving
organizational decision making. Consequently, the findings had provided a good
guideline for fast food managers to allocate their resources accordingly, which included
the arrangement of priority, financial resources, and human capital. It also helped them
to develop clear directions in positioning their brands that was based on consumer
response (Mohd Rizaimy, Suhardi & Shamsul, 2011).
Most of the government assistance programmes were based on traditional
marketing, such as packaging (Small and Medium Enterprise Corporation Malaysia
[SME Corp. Malaysia], 2011b), business management (Ministry of International Trade
and Industry [MITI], 2011), financial assistance (Perbadanan Nasional Berhad [PNS],
2011), and collaboration with external parties (SME Corp. Malaysia, 2011a; MDTCC,
2011a).
There was lack of training programme that focused on the development of
fundamental knowledge among local entrepreneurs; reason being that most of the
branding trainings were focused on packaging (SME Corp. Malaysia, 2011a). Local
entrepreneurs had to equip themselves with the ideology of brand equity creation.
Consequently, they would response to the market changes independently and not have
the mindset of depending on the supported facilities from the government. That is, they
became more proactive than reactive and had a better direction for the planning of
branding strategy.
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The findings for this research will be useful for the development for branding
activities among local entrepreneurs. It also allowed our university to collaborate with
the Ministry of Domestic Trade, Co-operative and Consumerism (KPDNKK) and
Ministry of International Trade and Industry (MITI) in setting customized branding
strategy. The ministries could apply the findings as fundamental in formulating
government assistance programs for local entrepreneurs, especially in training
programs (SME Corp. Malaysia, 2011a).
As a conclusion, this study had provided a solution for assistance programmes,
highlighted alternative approach for the growth of Malaysian brand in fast food
industry, which was based on the development of fundamental knowledge among local
entrepreneurs
1.7 Scope of Study
This study had focused on Malaysian fast food industry, particularly for fast
food chains that provided expedited food service, established standard operating
procedure, offered Western pattern diet, and have franchises nationwide or in multiple
states (Ashkanasy & Nicholson, 2003; Block et al., 2004; Burdette & Whitaker, 2004;
Slattery et al., 1998).
The stimulated brands were McDonald’s, Kentucky Fried Chicken, Pizza Hut,
Marrybrown, and 1901 Hot Dogs as they controlled approximately 80% fast food
market share in Malaysia (Aseambankers, 2007). A total of 600 self-administrated
questionnaires were distributed among fast food consumers from Klang Valley. Klang
Valley was selected as it drew out with heterogeneous sample that constituted people
from all ethnic groups and various demographic characteristics (Norzalita & Norjaya,
2010). For these reason, Klang Valley are widely selected for Malaysian research
(Chan, 2009; Chok, 2008; Hee, 2009; Hishamuddin, 2007; Norjaya et al., 2007;
Norzalita & Norjaya, 2010; Ooi, 2009; Siti Safira, 2008; Yap, 2009).
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1.8 Definition of Terms
The following definitions would provide a better understanding of the concepts
for this study:
Attitudinal brand loyalty
The indication of consumer’s psychological commitment towards the brand (Chaudhuri
& Holbrook, 2001).
Brand
The identity of a specific product, service, or business and it could take many forms,
including a name, sign, symbol, color combination or slogan (Aaker, 1991).
Brand awareness
The potentiality of consumer to identify a particular brand from his or her memory
when encountering a selection process or decision making progress from the product
category (Aaker, 1991; Heding, Knudtzen & Bjerre, 2009).
Brand equity
Brand equity existed when a consumer had preference to choose a focal branded
product, but not an unbranded product that had the same level of product features
(Kamakura & Russell, 1993).
Brand familiarity
The number of brand-related experience that a consumer had built up (Alba &
Hutchinson, 1987).
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Brand knowledge
The brand served as a node of an associative network memory which linked various
types of associations, comprised of brand awareness and brand image (Keller, 1998).
Brand image
The overall consumer perception or impression towards a brand due to its superiority,
uniqueness, strength, favorability, and different kinds of association (Keller, 2003).
Brand trust
The positive emotional feeling and affective reactions that results from the trusted
brand (Chaudhuri & Holbrook, 2001; Corritore, Kracher & Wiedenbeck, 2003;
Riegelsberger, Sasse & McCarthy, 2005).
Consumer-based brand equity
The brand commitment that resulted from consumer’s perception of overall superiority
(cognitive to conative stage) of a particular product or service category carrying that
brand name (Belch & Belch, 2009; Heding et al., 2009).
Fast food brand
Fast food corporation that provided expedited food service, established standard
operating procedure, offered Western pattern diet, and had franchises in multiple states
or nationwide (Ashkanasy & Nicholson, 2003; Block et al., 2004; Burdette & Whitaker,
2004; Slattery et al., 1998).
Perceived quality
The overall customers’ cognitive response on the superiority of service quality as
offered by companies and employee (Chiou, Droge & Hanvanich, 2002).
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1.9 Organization of the Thesis
Chapter 1: Introduction
This chapter introduced the study by identifying the key meaning and variables. Later it
outlined problem background, which served as an important platform in understanding
current research gap. Next, the research questions and research objectives were
identified from the problem statement. Subsequently, the chapter indicated the
justification and scope of the study.
Chapter 2: Literature Review
This chapter reviewed theoretical development of consumer-based brand equity for this
study. Next, it reviewed the relevant literature to provide critical comments for the
dimensions of consumer-based brand equity, such as perceived quality, brand
awareness, brand familiarity, brand image, brand trust and attitudinal brand loyalty.
Chapter 3: Research Methodology
This chapter justified the development of research framework and hypotheses. Next, it
highlighted detail of questionnaire developments. The sample of the study, stimulated
brands, and data collection procedure were explained in the following sections. Later, it
was followed by the detail and result of pilot study. Finally, the chapter identified the
research design for the main study, which comprised sample size and data selection,
data collection procedures, and method of data analysis.
Chapter 4: Data Analysis
This chapter is to present the results from the main study. Basically, there are four
distinctive parts of this chapter. Firstly, the sample descriptions was presented, which
included the respondents’ background and descriptive analysis of the variables. Next, a
series of tests were conducted in order to satisfy the confirmatory factor analysis,
before the measurement model could be transferred to structural model. The chapter
was followed by the results of hypotheses. Lastly, model re-specification was carried
out to compare the proposed model with the existing theories.
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Chapter 5: Discussions on Findings
This chapter discussed and interpreted the result of hypotheses. Each of the hypotheses
was clearly identified, and was supported by the previous literatures. Subsequently, the
chapter overviewed general findings of this study, which served as a vital platform in
responding to the research objectives, such as the importance of brand familiarity and
brand trust, and the identification of causal relationships.
Chapter 6: Conclusion and Recommendations
This chapter firstly discussed on the achievement of research objectives. Next, the
study justified the contribution of this study, in term of both academicians’ and
practitioners’
perspective.
Lastly,
the
recommendation for future study.
21
chapter
covered
the
limitation
and
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
Basically, this Chapter is divided into three important categories. First, it
comprises of Section 2.2 and 2.3, which clearly identify the different types of brand
equity conceptualization in current marketing literature. The identification of
conceptualization was important because it serves as a good understanding of
conceptual framework for this study. Therefore, Section 2.3 indicates the summary of
the findings on brand equity from year 1991 to 2011.
Section 2.4 discusses the four widely used brand equity theory, by Aaker (1991),
Keller (1993), Lasser el at. (1995), and Gil et al. (2007). Next, the development of the
brand equity concept for fast food context is discussed, such as the replacement of
brand association with brand image, the inclusion of brand familiarity and brand trust,
and brief justification for the selection of attitudinal brand loyalty. The main purpose
was to ensure that the conceptual framework of this study was supported by
fundamental theory.
Section 2.5 to 2.10 reviews all the constructs that was used in this study, namely
perceived quality, brand awareness, brand familiarity, brand image, brand trust and
attitudinal brand loyalty. All of the discussions were based on previous researchers’
definitions, association of theoretical and empirical findings.
22
2.2 Brand Equity
In general, brand equity was the incremental utility and added value to a
product by its brand name, for instance Mercedes-Benz, BMW, Nike, Adidas, Coke,
Pepsi, Kodak, Gucci, Louis Vuitton, Levi’s, McDonald’s and Starbucks (Tan et al.).
There have been many definitions given, for instance incremental utility (Kamakura &
Russell, 1993); unique value added from the brand (Farquhar et al., 1991); superiority
and brand choice (Agarwal & Rao, 1996); and difference between overall brand first
choice (Park & Srinivasan, 1994).
According to Bello and Holbrook (1995), brand equity was the tremendous
value inherent in a famous brand name; it referred to the attractiveness of the brand
name associated to the products or services. This was explained by the willingness of
consumers to purchase the similar quality of products or services with higher price or
price premium, and this was explained as the effect of deep-rooted impression and
positive image of the brand in the minds of consumers (Bello & Holbrook, 1995).
Some researchers indicated that brand equity contributed in customer value
(Cobb-Walgren, Beal & Donthu, 1995; Keller, 1993). For example, it led to greater
consumers’ confidence, customer satisfaction, and information processing towards the
brands. Adler and Freedman (1990) further suggested that brand equity provided shortterm protection from competition (based on consumer loyalty and switching costs), and
served as basic to protect its market share from any new idea of competitors.
23
According to Lane and Jacobson (1995), brand equity created intangible assets
for company, for instance it increases credibility and reputation of company, and these
intangible assets were considered much superior than tangible assets. This could be
explained that an established brand name would serve as an important platform for the
product extension (Aaker & Biel, 1993).
Moreover, researchers stated that brand equity had positive impact on
company’s profitability and sustainable cash flow (Srivastava & Shocker, 1991),
willingness of consumer to pay premium prices (Keller, 1993), sustainable competitive
advantage (Szymanski et al., 1993), growth and stability of stock prices (Lane &
Jacobson, 1995; Simon & Sullivan, 1993), firm performance (Kim & Kim, 2005), and
successfulness of marketing efforts (Styles & Ambler, 1995).
Overall, the enhancement of brand equity led to higher purchase intention,
prices premium, lower probability of price elasticity, greater competitive advantages,
higher market value, and business profitability and sustainability (Keller, 2003). In
contrast, weaker brand equity had a negative effect in the long term (Ailloni-Charas,
1991). This could be supported by consumers were most likely to switch to other
brands in the marketplace if there was a lack of brand management.
For many years, brand equity had been a topic of interest in consumer goods
market, particularly the fast-moving consumer goods. However, there were different
findings could be found in brand equity study, especially for components such as brand
association or brand image. This could be evidenced in retailer brand equity; retailer
association was proved to be varied across store category (Grace & O’Cass, 2005;
Sinha & Uniyal, 2004).
24
Additionally, similar marketing instrument acted differently across consumer
goods market and service market. For instance, customer service was considered as part
of the elements of perceived quality, but it was treated as a marketing element in
consumer goods market (Bamert & Wehrli, 2005). Besides, there were different
perspectives on the conceptualization of brand equity. In the next section, the selection
of brand equity concepts would be discussed in detail.
2.2.1 Two Different Perspectives in Brand Equity Conceptualization
There were many measurements of brand equity due to the different concepts
created and, as a result, there is a wide spectrum of different perspectives on how brand
equity ought to be conceptualized and managed (Aaker, 1991; Keller, 1993; Lassar et
al., 1993). Brand equity subsumed to brand strength and brand value (Srivastava &
Shocker, 1991). According to Keller (1998), brand strength was referred to the set of
associations and behaviors on the part of a brand’s customers, channel members, and
parent corporation that permits the brand to enjoy sustainable and differentiated
competitive advantages (consumer-based perspective). On the other hand, brand value
was defined as the financial result (financial perspective) that was derived from the
skillful and strategic management of talent in leveraging brand strength, which served
its purpose to support the superiority of current and future profits; at the same vein it
lowered the risk of the corporation (Srivastava & Shocker, 1991).
The main aim of this study was to develop a consumer-based brand equity
model in the Malaysian context of fast food industry, which focused on understanding
the constitution of associations held by consumers towards the fast food brands (Yoo et
al., 2000). As a result, consumer-based perspective was selected to measure brand
equity. In order to obtain a clear picture of brand equity applied in this study, different
types of brand equity perspectives will be discussed in the next section.
25
2.2.2 Financial Perspective
Financial perspective of brand equity sometimes was addressed as firm level
approach or company-oriented perspective (Feldwick, 1996). This approach measured
the brand as a financial asset, which could be defined as either the asset management
for manufacturers or leverage for trades (Feldwick, 1996).
According to Shocker and Weitz (1988), financial approach explained that
brand equity served as a vital role in asset management. This was because it was
generally defined as incremental cash flow, which increased market share, premium
pricing, and reduced promotional expense from the products with the brand name over
unbranded products.
These could be further explained by a strong brand that was measured using the
brand valuation method, which valued assets of a company by employing momentum
of accounting (Farquhar et al., 1991; Farquhar & Ijiri, 1993). However, Barwise (1993)
pointed out that accounting system-based measurement was suitable only if all the
related information was recorded, and if there was little fluctuation of the future market.
On the other hand, Feldwick (1996) defined brand equity as the total brand
value as a separable asset, it could be sold out or embraced on a balance sheet; an
account of the associations and beliefs of the consumers about the brand or as a
measurement of the strength on consumer’s attachment towards a brand.
In the trade’s view, brand equity emphasizes the leverage products over other
brands in the marketplace, as a strong brand in this sense made it easy to deal with
retailers and easy to build a wide distribution (Farquhar, 1989). It had the power to
negotiate with middlemen, and, if extended to new products, the product would enter
the market more easily (Farquhar, 1989; Shocker & Weitz. 1988).
26
As a conclusion, financially-based measurement was based on the assessment
of expenditure and revenue that were derived from companies’ performance and
current accounting practices. Furthermore, it highlighted the experimental result from
market-share data and assessment of product selling price over its cost. Thus, the
measurement of financially-based brand equity included sustainability of cash flow,
market share, price premium and financial performance.
2.2.3 Consumer-based Perspective
In contrast, Marston (1992) indicated that brand equity reflected customer
perceived value, which was formed by the combination of a product’s functional
performance, emotional benefits, and consumer’s lifestyle. In other words, it was
referred to the positive brand’s impact that was derived from consumer’s evaluation on
products or services (Teas & Grapentine, 1996).
However, Shocker and Weitz (1988) suggested that brand equity goes beyond
the product or service attributes. They further explained that brand equity was a
function of associations that had been built and nurtured in the consumer’s mind
(Shocker & Weitz, 1988). The existence of strong association would consequently lead
to brand attitude (Lutz, 1975). The strength of brand attitude was a major determinant
for consumers’ behavior, such as actual purchase (Hwang, Yoon, & Park, 2011). For
these reasons, these associations and behaviors permitted the brand to increase its
market share and markup margin, which could not be easily exercised by unbranded
items or services (Park, MacInnis, Priester, Eisingerich, & Iacobucci, 2010). In addition,
there were two different approaches in consumer-based perspective, which were
economic-based approaches (Erdem & Swait, 1998) and psychological-based
approaches (Aaker, 1991; Keller, 1993; Loken & Roedder, 1993).
27
a) Economic-based Approaches
Erdem and Swait (1998) conceptualized economic-based approaches from the
customer’s perspective that addressed the issue of how brand delivered added value to
customers. Essentially, customers were willing to pay price premiums, or to become
loyal to a brand because their expected utility was increased (Erdem & Swait, 1998).
This could be illustrated by given the imperfect and asymmetrical information structure;
as which customers were uncertain about product attributes or quality by conveying
credible product claims and information on a product’s position, brands decreased in
both information and perceived costs for customers (Erdem & Swait, 1998).
Consecutively, increasing customers’ expected utility.
b) Psychological-based Approaches
On the other hand, psychological-based approaches proposed that brand was
seen as a node in the memory with different types of associations, varying in strength,
and linked together (Keller, 1993). According to Loken and Roedder (1993), this
approach assumed consumers would connect to a brand by category specific, based on
its specific attributes with different types of association that represented in the mind of
consumers.
There were numerous concepts and principles from psychology and social
cognition in developing models of consumer brand-related decisions, such as affect
referral mechanisms, attributional processes, accessibility-diagnosticity considerations,
expectancy value formulations, and so on (Barton & Robin, 2002). Both Aaker (1991)
and Keller (1993) models were the well-established brand equity models that were
based on the principles of consumer psychology in various ways. Aaker (1991)
approached principally from a corporate and managerial perspective; however it was
constituted from the standpoint of consumer behavior. On the other hand, Keller (1993)
approach of brand equity was focused on consumer behavior perspectives.
28
2.3 Consumer-based Brand Equity
Kamakura and Russell (1993) suggested that consumer-based brand equity as
dissimilarity of consumers’ responsiveness between a focal brand and an unbranded
product or service. It could be explained as different effects of consumers’ response on
marketing efforts of the brands, when both of the given brands have the similar level of
marketing stimuli and product attributes (Yoo et al, 2000).
McQueen (1991) referred consumer-based brand equity as the different between
consumers’ evaluation to the branded product and the product without branding. Lassar,
Mittal and Sharma, (1995, p.13) had stated that consumer-based brand equity as “the
enhancement in the perceived utility and desirability a brand name confers in a
product”. Generally, they defined brand equity as the consumer’s perception of the
overall superiority of a product or service carrying that brand name when compared to
other brands. According to Aaker (2011), in order for the marketer to make the most
relevant consumer-based brand strategy, it was worthwhile to think about which
competitors were the real threat. Subsequently conducted comparative analyses and
formulated the brand strategy in relation to them.
On the other hand, some scholars (Keller, 2003; Shocker, Srivastava & Ruekert,
1994) presented the focus on consumer, which highlighted that the approach should be
based on analyzing the responsiveness of consumer to a brand name. However, Erdem
and Swait (1998) argued that consumer-based brand equity should be evaluated based
on the brand credibility value of a product or service position, more than consumers’
responsiveness. Keller (2001) argued that brand equity occurred when the consumers
were familiar with the brand and associated with some strong, favorable, and unique
memory towards the brand. For these reasons, consumers would have positive behavior,
purchase intention, and preference towards the brand.
29
Keller (1998) further highlighted that brand equity was driven by personal
meanings and images. Rust, Lemon and Zeithaml (2001) pointed out that value equity
taps into a customer’s head, while Aaker (1997) discovered brand equity addressed
what existed in a customer’s heart and soul. Lately, Lovelock and Wirtz (2007) defined
it as a more subjective, emotional, and experiential appraisal of a corporation or a brand.
According to Heding et al. (2009), Keller’s (1993) customer-based brand equity
(CBBE) was derived by consumer-based approach, which indicated brand was the
cognitive construal that existed in the consumers’ perception or mind. This assumption
also showed that consumers have the full control over the brand-consumer exchange
(Heding et al., 2009). Belch and Belch (2009) stated that most of the marketing models
considered full set of consumer’s response model (cognitive, affective, conative stage),
for instance action, desire, interest, action (AIDA), hierarchy of effects, innovation
adoption, information processing. However, CBBE only focused on consumers’ brand
image (types of association, favorability, strength, and uniqueness) and brand
awareness (Keller, 1993). In other words, it purely based on cognitive and affective
processing regardless other component of mind such as conative.
In another study by Blackston (1992), brand was the consumers’ idea about the
product, while product was what the company physically made. But what the
consumers purchased was psychologically and actually a brand, which offered
something more than its functionality (Kapferer, 1992), where could be referred as the
sequential process of consumers attitudes (Lannon, 1993). As a result, it made this
study rational by including the hierarchy of effect theory (causal effects) in explaining
brand equity concept.
30
2.3.1 Hierarchy of Effect Theory (Cognitive-affective-conative)
Researchers such as Bagozzi (1978) and Breckler (1984) argued that the
evaluation of consumers’ response was assumed as people’s attitudes and, thus, it was
classified as three distinguishing classes, such as cognition, affect, and conation
(Bagozzi, 1978; Breckler, 1984). Cognition was referred to the thoughts towards a
particular attitude object, which consisted of belief, mental, “rational” states,
intellectual or belief in the statement of fact (Lavidge & Steiner, 1961).
Next, the affect could be deliberated by physiological responses or a collection
of verbal report, which consisted of emotional responses, feelings and moods.
Importantly, Eagly and Chaiken (1993) stated that the affective responses could be
exceptionally identified in both positive and negative range, and was positioned on an
evaluative dimension of meaning. Oliver (1997) further stated the components of
affective responses consisted of caring, involvement, and liking. Most of the time,
people provided a favorable evaluation towards an attitude object when there was a
positive experience, which directly associated with the positive side of affective
reactions (Oliver, 1997). At the same time, people also presented negative affective
reactions when they experienced an unfavorable evaluation towards an attitude object
(Oliver, 1997).
Finally, the conation included behavioral willingness or intentions to act.
According to Bagozzi (1978, p. 10), conation was said to “depict the action tendencies
one had to approach or avoid an object or perform some response”. Lavidge and
Steiner (1961) defined conation as motivational component, such as the “striving”
states, which could be referred to both positive and negative tendency to treat an
attitude object.
31
The four-stage loyalty theory by Oliver (1997) became one of the most popular
applications of hierarchy of effect theory, which gained interest among marketing
researchers. Oliver (1997) classified customer loyalty into four different stages in
psychological loyalty, namely cognitive loyalty, affective loyalty, conative loyalty, and
action loyalty.
According to Oliver (1999), cognitive loyalty existed when consumers have
preference towards a service provider, this could be based on the identification of its
attribute performances and brand information. Oliver further stated that cognitive
response was derived by the consumers’ recent experience or vivid knowledge with the
firms. Thus, cognitive loyalty was considered as the first stage of loyalty in hospitality
industry (Back & Parks, 2003).
Affective loyalty could be emerged when consumers have greater form of
commitment towards the service provider (Oliver, 1999). In this stage, consumers have
an attributed satisfaction towards the product experience; consequently, they not only
depended on the attribute performances and brand information, but also on the response
of consumers “like” the service provider (Oliver, 1999).
The behavior of brand switching for affective loyal consumers would be
slightly lower, as compared to cognitive loyal consumers when there was counterargumentation from other brands (Oliver, 1999). This was because consumers were
satisfied with the service providers; however, such situation might lead to “satisfaction
trap”. This could be supported by there were large number of satisfied consumers who
depended on various service providers (Reichheld, 1996). In other words, they were
loyal to many brands; as a result, this level of loyalty was still vulnerable to avoid
switching behaviors (Oliver, 1999).
32
Conative loyalty could be referred to deeper level of attitudinal commitment
that held by consumers (Oliver, 1999). In this stage, consumers would have greater
brand commitment and repurchase intention, as they had repeated affirmative cognitive
and affective experiences with the brand or service provider (Oliver, 1999). He argued
that even though the intention was good, subsequently it did not always serve as the
main objective for many managers. This could be explained as to why managers prefer
to have financial result, such as the increase of revenue from repurchase behavior,
instead of the repurchase motivation held by consumers (Oliver, 1999). For these
reason, Kuhl and Beckmann (1985) stated that the mechanism of transforming conative
loyalty into real actions should be highlighted. In other words, the focus should be
based on the establishment of loyal bond between consumers and a brand, ultimately
led to the consumers’ action (Kuhl & Beckmann, 1985).
According to Ajzen and Fishbein (1977), action loyalty served as the strongest
form of behavioral intention in the behavior formation of attitudinal framework. This
was because it combined consumers’ intention and motivation, subsequently led to the
readiness to act, such as constant purchase and enhanced regularity of purchase
(Bandyopadhyay & Martell, 2007). Even though action loyalty was considered as final
stage of loyalty, however the sustainability of action loyalty was heavily depended on
conative loyalty (Bandyopadhyay & Martell, 2007; Evanschitzky & Wunderlich, 2006).
This could be further supported in a hospitality study, as action loyalty was a positive
function of conative loyalty developed through the cognitive and affective stages (Back
& Parks, 2003).
33
Based on the above sequential process, many social scientists assumed loyalty
phase which was based on cognitive-affective-conative approach, considered to be
emerging consecutively rather than concurrently (Back & Parks, 2003; Evanschitzky &
Wunderlich, 2006; Oliver, 1997, 1999). As a result, sequential process formation
served as an important fundamental theory for the evaluation of consumer, which was
also be highlighted in some of the brand equity studies (Agarwal & Malhotra, 2005;
Brown, 1998; De Chernatony, 2002; Keller, 2003; Malhotra, 2005).
However, the empirical research for sequential process formation was very
limited (Da Silva & Sharifah, 2006; Merrilees & Fry, 2002; Sirgy & Samli, 1985;
Selnes, 1993). Furthermore, there was no clear categorization of cognitive-affectiveconative on the dimensions of brand equity as defined by Aaker’s (1991) model.
Studies show that the application of the hierarchy of effect theory as a general reference
for the model development was due to two main reasons. Firstly, it related to the
consumers’ response in term of psychological perspective (Barry, 1987). Secondly, it
was a general guideline for the development of most of the available marketing models
(Belch & Belch, 2009).
2.3.2 Different Dimensions of Brand Equity across Industries
Different industries contributed dissimilarity of brand equity dimensions.
According to Yoo et al.’s (2000), perceived quality, brand awareness/association, and
brand loyalty dimensions were based on athletic shoes, camera film, and television sets.
Angel and Manuel (2005) replaced brand association as brand image in durable goods
study. Besides, Norjaya et al. (2007) classified the brand equity dimensions of
household electrical appliances as brand loyalty, brand distinctiveness and brand
association/awareness. Wang, Wei and Yu (2008) suggested that global brand equity
consisted of four indicators, such as quality perception, brand awareness, brand
resonance, and corporation ability association.
34
Table 2.1: Summary of Previous Finding for Dimensions of Brand Equity
Author(s) and Year
Dimensions
Industry/Product
Aaker (1991, 1996)
Perceived quality, brand awareness,
N/A
brand associations, brand loyalty
Srivastava & Shocker (1991)
Brand strength
N/A
Keller (1993)
Brand awareness, brand image
N/A
Lassar et al. (1995)
Performance, social image,
Television, watches
commitment, value, trustworthiness
Cobb-Walgren et al. (1995)
Brand awareness, perceived quality,
Hotels, cleansers
brand associations
Yoo et al. (2000)
Perceived quality,
Athletic shoes, camera
brand awareness/associations,
film, television sets
brand loyalty
Baldauf et al. (2003)
Perceived quality,
Tile
brand awareness,
brand loyalty
Pappu, Quester & Cooksey
(2005)
brand Image, brand loyalty
Angel & Manuel (2005)
Car , television
Washing machine
brand Image, brand loyalty
Kim & Kim (2004, 2005)
Fast-food restaurants,
brand image, brand loyalty
luxury hotel
Pappu, Quester & Cooksey
Television, car
(2006)
Esch, Langner, Schmitt &
Brand awareness, brand image
Chocolate, athletic shoes
Milk, olive oil, toothpaste
Geus (2006)
Gil et al. (2007)
brand loyalty
Kayaman & Arasli (2007)
Perceived quality, brand image,
Hotel
brand loyalty
Norjaya et al. (2007)
Brand distinctiveness,
Television, refrigerator,
brand awareness/association,
air-conditioner
brand loyalty
35
Table 2.1: Summary of Previous Finding for Dimensions of Brand Equity
(Continued)
Author(s) and Year
Dimensions
Industry/Product
Buil, de Chernatony, &
Soft drink, car,
Martínez (2008)
brand loyalty, perceived value, brand
sportswear, consumer
personality, organization
electronics
Corporation ability association,
Shampoos, color TV,
brand awareness, quality perception,
hi-tech products
Wang et al. (2008)
brand resonance
Rosa & Riquelme (2008)
Brand awareness, brand value, brand
Online businesses:
loyalty, brand trust
Amazon, e-Bay, CD, and
Dell
Xu & Andrew (2009)
Brand awareness, brand association,
Hotel
brand loyalty, quality of experience
Boo et al. (2009)
Tong & Hawley (2009)
Brand quality, brand awareness, brand
Destination: Las Vegas
image, brand loyalty, brand value
and Atlantic City
Sports shoe
brand association, brand loyalty
Henry et al.(2010)
Casino
Pike et al. (2010)
Norzalita & Norjaya (2010)
Brand quality, brand image, brand
Long-haul tourism
loyalty, brand salience
destination
Brand salience, brand performance,
Banking services
brand judgments, brand feelings,
Patwardhan &
Inclusion of brand romance
N/A
Brand awareness, brand strength,
Generic drugs
Balasubramanian (2011)
Sanyal & Datta (2011)
country of origin image
Hess, Story & Danes (2011)
Brand reliability, brand fidelity, service
quality
36
Investment
Where else in the hotel industry, Kayaman and Arasli (2007) indicated that
brand equity dimensions consisted of brand loyalty, brand image and perceived quality,
whereas perceived quality was divided into five mechanisms of service quality, which
consisted of responsiveness, tangibility, assurance, reliability, and empathy. Recently,
Xu and Andrew (2009) defined the conceptual framework of hotel brand equity as
brand loyalty, brand association, brand awareness and quality of experience. For further
supporting the argument, Table 2.1 summarizes the variation of brand equity
dimensions across different industries or products for the last twenty years.
According to Christodoulides and de Chernatony (2010, p. 61), “a brand equity
monitor should incorporate dimensions that drive value within the specific industry.”
Therefore, both brand familiarity (Schlosser, 2002) and brand trust (Delgado-Ballester
& Munuera-Aleman, 2005) were proposed as additional dimensions as they served as
important dimensions in the context of fast food (Morgan & Hunt, 1994; Smith, 1993).
2.4 Theoretical Review of Brand Equity
As mentioned in the previous section, this study adopted the consumer-based
brand equity. The following sections discuss the four theories of the consumer-based
brand equity, by Aaker (1991), Keller’s brand knowledge (1993), Lassar et al. (1995),
and Gil et al. (2007). According to Faircloth, Capella and Alford (2001), the first three
brand equity theories were widely recognized and accepted within the marketing field
due to its unique contribution for identifying the degree of difference in consumer
behavior effect of the firm’s marketing mix activities. Gil et al.’s theory was included
where it implied the hierarchy of effect theory and investigated the causal relationships
between dimensions of brand equity.
37
2.4.1 Aaker’s Theory of Brand Equity (1991)
There were five dimensions proposed by Aaker’s (1991) brand equity model,
namely brand awareness, perceived quality, brand associations, brand loyalty, and other
proprietary brand assets. Brand awareness was the ability of the possible customer to
recall or recognize brand names or symbols, thus brand would not be chosen if it was
not considered (Aaker, 1991). Aaker further supplied evidence with regards to the
importance of brand awareness in contributing to brand loyalty, which helped to make
the brand more familiar and top-of-mind, where increased the probability of being
chosen by the consumers.
Perceived quality was referred to as the overall perception of consumers
towards the product or service of a brand (Zeithaml, 1988). Positive perceived quality
resulted from the supremacy of perception; negative perceived quality was identified
from the inferiority of perception (Zeithaml, 1988). Therefore, it was important for the
firm to produce an objectively measured quality product and to be able to link the
positive quality associations with the brand, consequently could lead to the basis for
achieving premium prices (Aaker, 1991).
Brand association was linked to the consumers’ memory (Keller, 1993); a
strong association to a brand by assisting consumers to process or retrieve information,
distinguish the brand, give consumers a reason to purchase, build an encouraging
attitude in consumers’ minds, and provide a basis for extending brands (Aaker, 1996;
Craik & Lockhart, 1972; Lockhart, Craik & Jacoby, 1976). Brand associations were
organized in a manner that reflected brand image, which ranged from very clear to very
diffuse (Aaker, 1996). The associations represented the utility received from
purchasing or consuming the brand and thus represented the actual or perceived reason
for buying behavior (Keller, 1993). Besides, brand associations also provided the key
of company’s strategic differentiation and positioning, product recall, development for
positive brand evaluations, and extensions (Aaker, 1996).
38
Brand loyalty was defined as a measure of the attachment that customers had to
a brand (Back, 2005). Aaker (1996) stated that brand loyalty enhanced brand awareness
by ensuring the brand was visible on a continuous basis and offered testimonial
reassurance to new customers. In addition to that, he also highlighted that brand equity
contributed to other proprietary brand assets, such as patents, trademarks, channel
relationships. These were also considered valuable because they protected brand equity
from competitors. Thus, brand equity helped to ensure the company’s long-term cash
flow, strategic advantage, and reduce marketing costs (Aaker, 1991). Figure 2.1
illustrates how brand equity generated value to the customer and the firm.
Brand
Loyalty
- Reduced Marketing Costs
- Trade Leverage
- Attracting New Loyalty
Customers
- Time to Respond to Competitive
Threats
Provides Value to
Customer by
Enhancing
Customer’s:
Brand
Awareness
- Anchor to Which Other
Associations Can Be Attached
- Familiarity-Liking
- Signal of Substance/Commitment
- Brand to Be Considered
• Interpretation/
Processing of
Information
• Confidence in the
Purchase Decision
• Use Satisfaction
Brand
Equity
Perceived
Quality
- Reason-to-Buy
- Differentiate/Position
- Price
- Channel Member Interest
- Extensions
Brand
Association
- Help Process/Retrieve Information
- Reason-to-Buy
- Create Positive Attitude/Feelings
- Extensions
Other
Proprietary
Brand
Assets
- Competitive Advantages
Provides Value to
Firm by Enhancing:
• Efficiency and
Effectiveness of
Marketing Programs
• Brand Loyalty
• Prices/Margins
• Brand Extensions
• Trade Leverage
• Competitive
Advantage
Source: Aaker (1991)
Figure 2.1: The Theory of Brand Equity by Aaker (1991)
39
Aaker’s (1991) theory relied on the managerial and corporate strategies
approaches underpinning consumer behavior. It covered the whole circle of value flow
from the brand to customers and firms respectively. This could become the major
drawback of this theory as it covered a wide range of perceptual and behavioral
concepts without operationally define them. Subsequently, later researchers had to
adapt the components with their own operational definitions (Anantachart, 1998).
2.4.2 Keller’s Theory of Brand Equity-Brand Knowledge (1993)
Keller (1993) defined brand equity as the different effect of brand knowledge
on consumer’s response to the marketing of the brand. Brand knowledge was referred
to the brand as a node of an associative network memory which linked various types of
associations (Collins & Loftus, 1975; Raaijmakers & Shiffrin, 1981; Ratcliff &
McKoon, 1988). It was distinct in terms of two components, brand awareness and
brand image as presented in Figure 2.2.
Keller stated brand awareness could be evidenced when the brand was strongly
held in consumers’ memory. Therefore, it reflected an individual’s ability to recognize
a variety of brand elements, such as the brand name, logo, symbol, character,
packaging and slogan under different conditions (Keller, 1993). On the other hand,
brand image was the combination of the favorability, strength, and uniqueness of brand
associations, which played important roles in identifying the degree of difference
among branded products (Keller, 1993). Besides, it was also referred to as customers’
perceptions of the brand, which included attributes, benefits, and attitudes (Keller,
1993). Attributes, the most concrete level of association, represented the brand’s
descriptive features (Myers & Shocker, 1981). Benefits could be conceptualized as the
personal value or motivations of the attributes (Park, Jaworski, & Maclnnis, 1986).
Finally, brand attitudes were the consumers’ overall evaluation towards the brand
(Wilkie, 1986) and was most commonly seen in the context of multiattribute attitude
model (Keller, 1993).
40
Brand Recall
Brand
Awareness
Brand Recognition
Price
Non
ProductRelated
Brand
Knowledge
Attributes
Types of Brand
Associations
User
Imagery
Usage
Imagery
Functional
Benefits
Favorability of
Brand Associations
Brand
Image
ProductRelated
Packaging
Experiential
Symbolic
Strength of Brand
Associations
Attitudes
Uniqueness of
Brand Associations
Source: Keller (1993)
Figure 2.2: The Brand Knowledge by Keller (1993)
Keller (1993) indicated that enhanced brand awareness and brand image
resulted in increasing consumer brand knowledge, which would cause a differential
consumer behavior response to the firm’s marketing mix. This is because higher the
levels of recall or recognition would also drive to higher brand equity; whereas positive
brand image would increase brand knowledge and logically resulted in greater brand
equity (Keller, 1993).
41
In Keller’s model, three types of brand associations were introduced to subsume
the level of abstraction (Alba & Hutchinson, 1987; Johnson, 1984), which had
differential effect on the formation of brand knowledge. Keller (1993) implicitly noted
that the types of associations and the dimensions of strength, favorability, and
uniqueness should cause different levels of brand image and brand equity. Keller
further provided conceptual support for the impact of brand image and different brand
associations on brand choice, which based on the notion of self-concept, product image
congruency, and consumer brand preference and choice.
The major drawback of this theory was because it focused on the consumer,
which highlighted that the marketers or practitioners had to focus on collecting the
information or database about the consumer mind of brand association regarding their
company brand (brand knowledge and evaluation) (Heding et al., 2009). Consequently,
marketing initiatives had to be designed by backward-looking, which had leaded to
lack of organizational vision. Furthermore, it may be more complex to measure brand
image since it must be evaluated from the characteristics of brand associations, such as
favorability, strength, and uniqueness (Anantachart, 1998).
2.4.3 Lassar, Mittal and Sharma’s Theory of Brand Equity (1995)
Performance
Social Image
Trustworthiness
Brand Equity
Commitment
Social Value
Source: Lassar et al. (1995)
Figure 2.3: The Theory of Brand Equity by Lassar, Mittal and Sharma (1995)
42
Figure 2.3 shows that there were five dimensions of consumer-based brand
equity; social image, performance, commitment, value and trustworthiness (Lassar et
al., 1995). Performance was referred to as the physical performance of the brand, such
as the product itself and service provider. Lassar et al. (1995) indicated the evaluation
of performance was related to consumers’ judgment, which included the brand’s error
free and ongoing physical operation, and flawless in the products’ physical production.
Performance served as a vital element, this was because it would directly affect the
consumers’ purchase frequency (Lassar et al. 1995). Consumers would become
reluctant to have future purchase intention once they had aversion experience with the
brand, such as failure to deliver the required specification, thus led to low levels of
brand equity (Anantachart, 1998).
Social image could be referred as consumers’ perception of the esteem, and it
could be identified as the level of brand that is held by a particular social group, such as
the status, social class, social symbol, perception, identity and so on (Lassar et al.,
1995). Social image was considered as value added because it enhanced the brand’s
social reputation and market value. Most of the time, social image had contributed
more to brand equity in fashion related industry, such as clothes, jewelries, perfumes,
and beauty products (Anantachart, 1998).
Lassar et al. (1995) stated commitment was related to the strength of affirmative
feeling held by consumers towards the brand; it was measured in term of perceptual
rather than behavioral. This could be further explained as the development of
sentimental attachment, which had come about from the positive identification with the
brand (Lassar et al., 1995).
43
Value was referred to the perceived brand value in relation to its cost. It
highlighted the assessment of brand utility as compared to its price (Lassar et al., 1995).
Sometimes, it could be identified as the value of money (Brucks & Zeithaml, 1993).
Consequently, higher brand equity was evidenced when the brand provided consumers
with higher perceived value; reason being that consumers would always go for a
particular brand choice as they perceived the brand could provide them with higher
utilities value (Lassar et al., 1995).
Lassar et al. (1995) argued trustworthiness was related to the level of
consumers’ confidence with the brand and firm’s communications. Furthermore, it
referred to the level of firm’s actions in serving the best interest of the consumers
(Chaudhuri & Holbrook, 2001). Trustworthiness was included because the consumers
placed greater value for the brand when they trusted it, as compared to the distrusted
brands (Macintosh & Lockshin, 1997). Correspondingly, the existence of trusted brand
positively affected brand equity (Hu, Chang, Hsieh, & Chen, 2010).
Each of the dimensions played major implication in enhancing brand equity and
there existed with a halo effect across dimensions of brand equity (Lassar et al., 1995).
For instance, once there was a positive evaluation on neither one of the dimensions (e.g.
performance), the expectation on other dimensions (e.g. social image, commitment,
value and trustworthiness) would be set at a higher level. On the other hand, consumers
did not place high expectation on other dimensions (e.g. performance, commitment,
value and trustworthiness) once there was a failure or negative evaluation on neither
one of the dimensions (e.g. social image) (Lassar et al., 1995). This implication showed
major drawback of the theory as there was high possibility of a brand which provided
greater social image, and did not necessary supply good performance. The performance
was something with a functional purpose while a brand offered something more than its
functionality; it came from the consumers’ idea about the product (Blackston, 1992;
Jones, 1986). Consequently, the claim of halo effect might not represent the true picture
across dimensions of brand equity.
44
Besides, Lassar et al. (1995) argued that when consumers have equity towards
brands, they would accept higher market price of that brand than other brands with
lower or no equity. However, this implication showed inconsistency in fast food
industry. For instance, McDonald’s was indicated to have the highest score of total
brand equity among Korean consumers, but the product price of McDonald’s was
lower than other similar types fast food brands, such as Burger King, Hardee’s, and
Lotteria (Kim & Kim, 2004). Subsequently, the relationship between higher brand
equity and greater market price could not be generalized.
2.4.4 Gil, Andrés and Salinas’s Theory of Brand Equity (2007)
Gil et al. (2007) extended Aaker’s (1991) theory by including the effect of both
family and marketing activities on the brand equity formation process. Based on Chiou
et al.’s (2002) cognitive-affective-conative hierarchical model, Gil et al. established
causal relationship between the dimensions of brand equity.
Referring to research framework of Gil et al. (2007), brand loyalty had been
considered as an antecedent of other dimensions, based on the hierarchy of effects
theory (Lavidge & Steiner, 1961). Their initial literature review proposed brand
awareness, brand association and perceived quality had direct effects on brand loyalty
and brand equity.
Nevertheless, their results indicated that both brand awareness and band
association were considered as a joint construct in the structural model. Besides, the
findings also showed that there was non-significant direct effect from perceived quality
on brand loyalty, highlighting a missed link in explaining perceived quality as an
important dimension of brand equity. Consequently, the empirical framework did not
support perceived quality as a critical dimension of brand equity (Gil et al., 2007).
45
Source: Gil et al. (2007)
Figure 2.4 The Theory of Brand Equity by Gil, Andre’s and Salinas (2007)
Gil et al. (2007) also indicated that family information contributed significantly
on brand awareness/association and perceived quality. However, they claimed there
were difficulties to distinguish between brand awareness and brand association, which
was in line with some of the researchers’ findings (see Yoo et al., 2000; Washburn &
Plank, 2002). In addition to that, Gil et al. argued that the existence of brand
awareness/association and perceived quality were not sufficient to establish the
superiority of a brand over other challenging brands, because both of the dimensions
were considered as cognitive character, whereas only brand loyalty was considered as
the closest dimension to the concept of brand equity (Yoo et al., 2000).
2.4.5 Selection of Brand Equity Theory for the Study
For the purpose of this study, Gil et al.’s (2007) theory was adopted and
modified to generate a meaningful research in examining the attitudes of Malaysian fast
food consumers. The main reason was because the model was adequately extended and
integrated i.e. the theory of both brand equity (Aaker, 1991) and hierarchy of effects
(Lavidge & Steiner, 1961). The details of the explanations were illustrated in the
following section.
46
Firstly, Gil et al. (2007) clearly identified the causal relationships among the
dimension of consumer-based brand equity based on the explanation of cognitiveaffective-conative, which served as a justification for the establishment of causal effect
that provided better explanation than some of the recent studies (e.g. Boo et al., 2009;
Hess et al., 2011; Patwardhan & Balasubramanian, 2011; Pike et al. 2010; Rosa &
Riquelme, 2008; Sanyal & Datta, 2011; Xu & Andrew, 2009).
Secondly, Gil et al. (2007) categorized the dimensions of consumer-based brand
equity with theoretical justification. For instance, perceived quality and brand
awareness/association were considered as cognitive constructs, while brand loyalty was
considered conative construct. The main advantage of this approach was this could lead
to the better development of measurement items, which to ensure there were clear
operational definition of the constructs and no overlapping of the observed variables
(Gil et al., 2007).
Thirdly, Gil et al.’s (2007) study used a sample of actual consumers (nonstudent). Consequently the results were more open to generalization (Pappu & Quester,
2008). Besides, the selection of products/brands was based on the level of involvement
that derived from the perception of consumer rather than the inherent characteristic of
the product itself (Malär, Krohmer, Hoyer & Nyffenegger, 2011). For instance, they
conducted a pre-test to indicate the degree of brand familiarity and level of usage. This
was because the high degree of respondents’ brand familiarity and brand experience
served as important criteria to ensure the reliability and validity of the questionnaire.
As a conclusion, this study extends Gil et al.’s (2007) research framework by
investigating greater numbers of causal relationships between brand equity dimensions.
This study also examined the importance of two additional dimensions, which were
brand familiarity and brand trust (Delgado-Ballester & Munuera-Aleman, 2005;
Schlosser, 2002). However, marketing activities and family information were excluded
from this study due to the objectivity of research study.
47
2.4.6 Development of Brand Equity Theory for the Study
The development of the conceptual framework for fast food context was
discussed in the next paragraphs, such as replacement of brand association with brand
image, the inclusion of brand familiarity and brand trust, brief justification for the
selection of attitudinal brand loyalty, and the integration of cognitive-affective-conative.
Muller and Woods (1994) pointed out the importance of restaurant brand
management instead of product management. They proposed the concept for the
development of brand image depended on the brand name, which was vital in
maintaining restaurant business. Muller (1998) highlighted that restaurant firms should
focus on three key areas, which were the execution of service delivery, quality products
and services, and the establishment of symbolic and evocative image. He further argued
that these strong combinations had been attributed to opportunity for accusing price
premium and developing customer loyalty.
Although the brand equity concepts for Aaker (1991) and Keller (1993) were
conceptualized in a different way, but, both theories focused on customer perspective
and illustrated the importance value of brand equity or brand knowledge on the firms
and consumers. As a result, brand image was reasonably proposed to replace brand
association because fast food industry was grouped under the hospitality industry.
Furthermore, brand association had been substituted with brand image in most of the
hospitality research (see Henry et al., 2010; Kayaman & Arasli 2007; Kim & Kim,
2004, 2005).
Referring to consumers’ brand knowledge, the assessment of brand personality
was expected to be affected by consumers’ knowledge and familiarity (Alba &
Hutchinson, 1987). Furthermore, Aaker (1996) argued that brand recognition reflected
familiarity and linking as acquired from past exposure. As a result, it was safe to
include brand familiarity.
48
With respect to brand trust, this study also included trustworthiness, which was
used by Lassar et al. (1995); however, trustworthiness was defined as brand trust in this
study. Brand trust was considered as a vital dimension to be evaluated in the fast food
industry (Delgado-Ballester & Munuera-Aleman, 2005), the reason being to evaluate
the affective response on the consistency of business operation and performance.
According to Chaudhuri and Holbrook (2001), brand loyalty could be classified
as behavioral brand loyalty and attitudinal brand loyalty. Attitudinal brand loyalty was
selected because it was based on consumers’ commitment rather than consumers’
actual purchase behavior (Bloemer & Kasper, 1995), which served as an important and
relevant outcome of other brand equity dimensions, and also was indicated as the
closest element to the concept of brand equity (Zinnbauer & Bakay, 2004). On the
other hand, behavioral brand loyalty was referred as spurious loyalty; this is because it
refers as the physical continual buying behavior of consumer without any attachment of
emotional or psychological (Bloemer & Kasper, 1995). Consequently, the dimensions
of consumer-based brand equity for this study were perceived quality, brand awareness,
brand familiarity, brand trust, brand image and attitudinal brand loyalty.
In addition, this study categorized the dimensions of fast food consumer-based
brand equity into cognitive-affective-conative. This is because such different stages of
consumer passes had provided useful diagnostic information to the academicians and
practitioners (Agarwal & Rao, 1996). The concept of this study was in line with the
concept of advertising as proposed by Lavidge and Steiner (1963), which indicated that
consumers would not transformed to a convinced purchasers without any sequential
consumer’s behavior. Therefore, in order to have strong commitment with a brand,
consumers have to go through a series of steps, such as cognitive, affect and conative
(Barry, 1987).
49
The statement was further supported by consumers’ affective and emotional
were derived from cognitive evaluation, based on research of consumer behavior and
psychology (Oliver, 1997, Franzen & Bouwman, 2001). Therefore, positive cognition
evaluation (via functional/utilitarian reason) would result first, and then led to affective
or emotional, finally drove to conative and behavior intention (Da Silva & Sharifah,
2006).
However, Petty, Cacioppo and Schumann (1983) stated that the high-low level
of involvement should be considered when applying the concept of cognitive-affectiveconative. Involvement was referred as the mental readiness, such as the cognitive
response towards a particular consumption object or brand (Park & Mittal, 1985). The
level of involvement was depended by the degree of personal relevance or importance,
which could be referred to the consumer’s degree of interest or arousal for a given
object (Celsi & Olson, 1988; Richins & Bloch, 1986). Therefore, the high and low
involvement of product was depended on the perception of consumer rather than the
inherent characteristic of the product itself (Malär et al., 2011). This could be further
supported by Marsden (2006), indicated 750,000 consumers who had treated daily
Procter & Gamble product, for instance soap and laundry detergent as high
involvement products instead of low involvement products.
As a result, it was safe to apply the concept of cognitive-affective-conative into
brand equity study, such as fast food brand because consumers would treat the brand as
high involvement due to the existence of emotional brand attachment (Malär et al.,
2011). This could be further supported by some brand equity studies, which had used
the products that were inherently characterised as low involvement, such as candy bars
(Agarwal & Rao, 1996), milk, toothpaste and olive oil (Gil et al., 2007), disposable
razors and potato chips (Grimm, 2005), and bookstore (Da Silva & Sharifah, 2006).
50
2.5 Perceived Quality
According to Zeithaml (1988), perceived quality was not referred to the actual
quality of the products or services; it was related to the overall perception of consumers
towards the product or service of a brand. Positive perceived quality could be the result
from the supremacy of perception that resulted from its deliberated function, compared
to other alternatives (Zeithaml, 1988). On the other hand, negative perceived quality
could be identified from the inferiority of perception (Zeithaml, 1988).
Aaker (1991) stated that perceived quality was not only just another brand
association, it was importantly related to the status of a brand, and thus it served as a
separate dimension of brand equity. Quality was materialized as the primary criterion
for the brand choice. Researchers advocated that perceived quality was measured as a
core or primary facet across the frameworks of brand equity (Dyson, Farr & Hollis,
1996; Farquhar, 1989; Keller, 1993). Aaker’s (1991) surveys discovered that quality
was the most significant consideration of selection. Research conducted by Michell,
King and Reast (2001) further affirmed that quality, reliability, and performance ranked
first, second, and third positions respectively. Therefore, perceived quality was
consistently proven as an essential criterion.
According to Aaker (1991), positive perceived quality could influence
consumers’ selection, motivate consumers in making purchase decision, brand
differentiation, serve as a basic for brand extension, and provide opportunity for
charging a price premium. Aaker also linked perceived quality to corporate profitability.
Here, it was important for the firm to produce an objectively measured quality product
and to be able to link the quality associations with the brand.
51
Unfortunately, Aaker (1991) justified that perceived quality could not be
reasonably determined due to its intangibility. The characteristic of intangibility
stemmed from the perception and judgment of what is considered important to the
customers involved. Therefore, in order to be successful, firms must be able to identify
attributes that consumers were looking with regards to quality. Firms must be able to
define perceived quality attribute specific to the industry and recognize the cues or
signals that exist for perceived quality (Aaker, 1991).
Although perceived quality was unquantifiable, it was usually determined based
on the characteristics of the goods and services, namely the reliability and performance
to which it was branded (Aaker, 1996). Besides, there existed a link between perceived
quality with price elasticity, stock return, price premiums and brand usage (Aaker,
1996). Additionally, communication on the quality of its brands had to be done through
quality signals in marketing efforts. Grönroos (1984) showed that consumers perceived
brand quality through first-hand experiences with the brand and also via information
acquired from surrounding environmental.
In the service industry, perceived quality could be classified into two types.
Firstly, it was referred to as the service quality that provided physical facilities, such as
business hours, physical environment, and modern equipment (Kim & Kim, 2005).
Secondly, it was referred to the service quality that provided by employees, such as
courtesy, responsiveness, and helpfulness (Kim & Kim, 2005).
As a conclusion, perceived quality was considered as an important
measurement in the food service industry as there were many social scientists had
ensured that service quality was the primary cognitive assessment of service provider at
the attribute level (Chiou et al., 2002; Dabholkar, 1995; Donovan, Rossiter, Marcoolyn
& Nesdale, 1994; Parasuraman, Zeithaml & Berry, 1988). Furthermore, practitioners
must be able to identify which attributes consumers were looking for in regard to
quality for the purpose of brand equity creation (Tan et al., 2011).
52
2.6 Brand Awareness
Aaker (1991) indicated that brand awareness was the capability of prospect
buyer to recognize or recall a particular brand when in the selection process of certain
category of product. However, Alba and Hutchinson (1987) defined it as the level of
consumers’ brand exposure. Woodward (2000) argued that a consumer’s brand
awareness would be higher as his or her exposure to the brand increased. Grover and
Srinivasan (1992) stated that brand awareness could be enhanced in different marketing
activities such as advertising, communication, direct mail, promotion activities, trade
press, and word-of-mouth.
Valkenburg and Buijzen (2005) suggested that brand awareness was commonly
referred to an individual’s active and passive knowledge of a specific brand. Therefore,
Aaker (1991, 1996) proposed it as the consumers’ ability to associate a brand with its
product category, referred to the strength of a brand’s presence in the consumer’s mind.
Moreover, Hoyer and Brown (1990) represented it as a basic level of brand knowledge.
Brand awareness could be evidenced when the brand was strongly held in consumers’
memory (Keller, 2003). Therefore, it was reflected by an individual’s ability to
recognize a variety of brand elements, such as the brand name, logo, symbol, character,
packaging and slogan under different conditions (Keller, 2003).
Keller (1993) indicated brand recognition and brand recall as the two core subdimensions of brand awareness. Basically, brand recognition was related to the level of
consumers’ ability to confirm a particular brand without any assistance of the brand cue
or brand information. This could be further explained as the recognition level of brand
attributes or communications among consumers (Keller, 1998). Mandler (1980)
discovered brand recognition could also be characterized as the process of perceiving a
brand that is based on encountered experience in the past.
53
On the other hand, Keller (1998) defined brand recall as the ability of
consumers to recover or regain the brand when given some cues, such as product
category, and purchase or usage situation. That is, individuals would specify a
particular brand name, without further delay when given the product category or
purchase situation (Keller, 1998). Keller (2003) further indicated that brand recall was
seen as a more advanced level of brand awareness than brand recognition as
recognizing a brand was easier than recalling it from memory in general.
Macklin (1996) explained that there was a high possibility for consumers to
recognize a brand, but less likely to recall it. Nevertheless, Keller (2003) highlighted
that both brand recognition and recall influence consumer’s decision making. Hoeffier
and Keller (2003) determined in their research that brand awareness was characterized
into two distinct ways; through depth and breadth. Depth referred to how easily
customers could recall or recognize the brand, while breadth referred to the range of
purchase and consumption situations in which the brand came to mind (Keller, 2003).
In addition, Hoeffier and Keller (2003) established the strength of brand awareness
when the consumer could recall “known” brands versus “unknown” brands when
making purchase decisions. This was accomplished by linking the brand to memory
through such things as the brand name, a logo, a symbol, or even a tag line. However,
Ye and Raaij (2004) suggested that the most effective way to build strong brand
awareness in consumers’ memory is to attract their attention.
Because different response tasks (e.g., recall, recognition) invited different
types of processing, and the findings underscored the notion that related to a particular
measure of advertising effectiveness which depended on whether that measure truly
captured the demands of consumers confronted in the relevant purchase or
consumption context (Meyers-Levy & Maheswaran, 1991).
54
For example, it would seem that recall would be a valuable indicator of
advertising effectiveness only if, in the ultimate decision context, when consumers
were likely to retrieve specific advertising claims when making a purchase decision, as
they appeared to do during recall (Meyers-Levy & Maheswaran, 1991).
Besides, brand awareness was the simplest level of cognitive response, and it
was the knowledge for the existence of a product or a brand (Alba & Hutchinson, 1987;
Hoyer & Brown, 1990). It could be determined by the percentage of potential buyers
who named the company as the first brand that had came to mind in a particular
product category.
Based on the literature review as stated above, brand awareness was considered
as a vital dimension in the context on fast food industry as brand awareness was the
prerequisite for brand equity (Heding at al., 2009). If the consumer was not aware of
the brand, it was not relevant to talk about brand equity in the first place; then the
company competed on the product rather than the brand (Aaker, 1991; Tan et al., 2011).
Nevertheless, this study considered brand awareness as a uni-dimensional construct
rather than multi-dimensional (e.g. brand recall, brand recognition). This was because it
would lead to the simplicity of research process.
2.7 Brand Familiarity
Mano and Davis (1990) defined brand familiarity as product familiarity which
related to the number of product experiences that a consumer had. Marks and Olson
(1981) discovered another view of brand familiarity, which focused on information
processing. Brand familiarity, in this view, referred to the cognitive representations of
experiences stored in memory instead of prior experience with a brand (Marks & Olson,
1981). These cognitive representations of experiences with a brand were organized in
the memory as a structure or schema in the form of representations for brand names,
attributes, uses, choice criteria, and so on (Marks & Olson, 1981).
55
Based on this information processing view, brand familiarity was a continuous
variable (Kent & Allen, 1994). Thus, people with different cognitive structures or
schemas varied in their levels of brand familiarity. Phelps and Thorson (1991) pointed
an alternative view of brand familiarity, which was the amount of time spent in
processing of brand information regardless of the type or content of processing that was
involved. The greater the amount of time spent in processing brand information, the
greater the level of familiarity with that information, regardless of whether the type of
processing was semantic (e.g., words, name, logo) or sensory (e.g., pictures, attributes)
(Bettman, 1979).
According to Das, Stenger and Ellis (2009), brand understanding required
greater degree of cognitive response, such as brand familiarity, where the greater time
the consumers were involved with the brand, the higher their degree of familiarity and
these lead to higher probability of brand choice. As a result, brand awareness alone was
not sufficient to create a satisfactory level of understanding (Das et al. 2009).
Alba and Hutchinson (1987) defined brand familiarity as the number of brandrelated experiences that a consumer had built up. Thus, it emphasized the direct and
indirect knowledge available to the consumer. On the other hand, brand familiarity was
referred to the total time spent processing information about the brand (Baker et al.,
1986). The familiarity of a brand might be due to physical factors such as, its newness
and age in the market (Carpenter & Nakamoto, 1989), as well as competitive factors
such as its prominence and positioning relative to other brands (Hoyer & Brown, 1990).
Besides, Kent and Allen (1994) converged on the significance of brand familiarity as
an important moderator on consumer response to various types and forms of
advertising. Consequently, brand familiarity moderated the influence of emotional
advertisements on brand evaluations (Machleit & Wilson, 1988).
56
In addition, Kent and Allen (1994) proposed brand familiarity moderated the
effects of competitive advertising interference. Campbell and Keller (2003) also argued
that brand familiarity attenuated the negative effects of wear-out caused by providing
repeat advertisements. Typically, this study identified brand familiarity as wellestablished through cognitive representations of knowledge that stored in memory with
the brand, as consumers became familiar with the brand; they were more likely to
perceive the brands’ relevance (Aaker, 2011).
The role of familiarity also appeared to be far greater for the situation where the
consumer was looking for a simple rule for decision making (Batra & Ray, 1985), such
as fast food. Schlosser (2002) expressed the flavors of childhood food which had left an
indelible mark, and where adults often returned to them, without always knowing why.
As a conclusion, brand familiarity was considered as an important donor to fast food
brand equity as it drove to positive attitude towards the brand, consumer confidence,
and purchase intention (Laroche et al., 1996).
2.8 Brand Image
Brand image is an essential element in marketing research (Paul, Gary, & Hsiao,
2010). Keller, (1998 p. 93) defined it as “perceptions about a brand as reflected by the
brand associations held in consumer’s memory”. Keller (1993) in his research used
brand image as a vital element of brand equity; and brand personality (Aaker, 1997) as
an indicator of brand image.
The term of brand image had been broadly defined and used in various ways.
However, Dobni and Zinkhan (1990) stated a general definition of brand image, which
was referred as the development of overall impression towards a specific brand,
subsequently; this cognitive construal would affect both perception and emotion of the
person while interact with that brand. In term of consumers’ perspective, brand image
was stored in the minds of consumers and was affected by how consumers developed,
maintained, and gave meaning to the influence of personal experienced on the
57
stimulated brands (Keller, 1993). Bullmore (1984) stressed that the creation of brand
image was due to an individual psychological center (individual psyche); the opposite
of the image belonged to the nature of assumptions and to respond to the image with
goodwill was possible only in individual mind. In term of mentality, the creation of
brand image was resulted from the experience of the consumer through coordination
and stimulation (Harris & de Chernatony, 2001).
In view from the marketers’ perspective, brand image was determined by the
selection of marketing personnel, development, implementation and management, and
acceptance of consumers in creating image (Park, 2009). Consumers were assumed to
have passive roles in developing or changing a particular brand image in the market
place (Dobni & Zinkhan, 1990). Both Aaker (1996) and Keller (1998) described brand
image as attributes and associations that consumers connected to the brand name.
These “evoked associations” was referred to specific perceptions of functional
attributes, such as speed or user friendliness (Aaker, 1996; Keller, 1998). In addition
there could also be emotional attributes, such as excitement, masculinity, fun, or
innovation (Keller, 2003).
In term of brand knowledge, Keller (1993, 1998) presented that brand image
was the combination of the favorability, strength, and uniqueness of brand associations.
He further identified that favorability, strength, and uniqueness were the dimensions
that played an important role in identifying the degree of different response on branded
products. For this reason, a positive brand image was created, if it had unique,
favorable, and had strong associations linked to the brand (Keller, 1993).
Keller (1993) further proposed that brand image was composed of image
drivers. This could be explained by the association between the brand name and
intangible symbolic benefits as perceived by consumers, which served as platform to
satisfy consumers in term on social class, self-emotional, and any other perception of
needs. Neal and Bathe (1997) further argued that the image drivers were also referred
to lifestyle, trustworthiness, and self-concept.
58
According to Dobni and Zinkhan, (1990), many researchers had applied
different kind of technical and casual application on deriving the measurement and
categorization of brand image (Park, 2009). Nevertheless, there was no consistency of
measurement for the dimensionality of brand image (Dobni & Zinkhan, 1990). For
instance, Park et al. (1986) proposed brand image could be measured in term of how
consumers perceived the unique meaning of the brand, in term of its functionality,
experiential, and symbolic benefits. In the same vein, Hsieh (2002) argued the
dimensionality of brand image should be measured in term of its sensory, utilitarian,
economic, and symbolic.
Interestingly, some researchers found that functional and symbolic as vital
concepts of brand image (Bhat & Reddy, 2001; Dobni & Zinkhan, 1990; Sirgy & Samli,
1985). Functional brand image was likely to be referred to by product-related attributes
of the brand; in other words, inherent characteristics of the brand to execute its utility.
In the product category, Grace and O’Cass (2002) identified that reliability, design
quality and other features of the core product could be examples of product-related
attributes that formed a functional brand image. In contrast, symbolic brand image was
most likely referred to as non-product related attributes of the brand. Referring to
Keller (1993), it could be generally acquired from extrinsic characteristics of the brand
to satisfy higher-level needs of consumers, such as social approval needs or personal
expression that maintained or increased their self-esteem.
Besides, Kandampully and Suhartanto (2000) highlighted the symbolic of brand
image attributes could be referred to the shop layout, environment, reputation, physical
appearance such as renovation. On the other hand, Dobni and Zinkhan (1990)
highlighted brand image could be assigned to blanket definitions, emphasized on
meanings or messages, personification, psychological, and symbolism dimensions. On
the destination image side, researchers defined brand image as a multidimensional
construct that consisted of two primary characters, namely cognitive and affective
destination image (Lawson & Band-Bovy, 1977).
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Social scientists defined cognitive destination image as the knowledge and
belief of physical attributes. On the other hand, affective destination image was related
to the affective quality feelings of attributes and the surrounding environments
(Baloglu & Brinberg, 1997; Burgess 1978; Baloglu & McClearly, 1999; Gartner, 1993;
Genereux, Ward & Russel, 1983; Hanyu, 1993; Holbrook, 1978; Proshonsky, Fabian &
Kaminoff, 1983; Walmsley & Jenkins, 1993; Ward & Russel, 1981; Zimmer & Golden,
1988).
Even though both of the dimensions could naturally be differentiated, however,
many researchers argued that they were also interrelated (Crompton, 1979; Mayo &
Jarvis, 1981; Woodside & Lysonski, 1989). This was because cognitive evaluation
relied on the affective appraisals of attitude objects, and affective response, such as
pleasure and exciting were formed as a function of the cognitive assessment (Gartner,
1993; Holbrook, 1978; Russel & Pratt, 1980; Stern & Krakover, 1993).
As a
conclusion, brand image was considered important to be included in this study. These
were because fast food consumers may be more prone to choose brands for overall
perceptions and images than for objective product attributes (Boulding, 1956; Ogilvy,
1985). That is, consumers choose fast food brand images, not fast food products for
decision making. This could be further explained that brand image served as a
foundation for the brand ultimately meeting the consumers’ needs (Park et al., 1986).
2.9 Brand Trust
According to Doney and Cannon (1997), trust had been classified as two
different dimensions, namely perceived credibility and benevolence. Perceived
credibility was focused on the objective believability of an exchange partner, which
could be referred to the level of expectancy that someone could rely on, neither verbal
nor nonverbal (Doney & Cannon, 1997). Perceived benevolence was related to the
extent to which someone was authentically fascinated in the other’s interests and the
enthusiasm to search for mutual benefits (Doney & Cannon, 1997). Furthermore,
Doney and Cannon emphasized that notion of trust was only applicable in condition of
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uncertainty. This could be further supported as consumers felt comfortable on trusted
brand because trust increased their confidence level in the uncertain environment
(Chaudhuri & Holbrook, 2001).
In contrast, other researchers (Aaker, 1996; Lasser et al., 1995) defined brand
trust as the consumers’ readiness to believe on a particular brand, referred to its
capability of promised functionality and attributes, which the value of brand had
achieved greater satisfaction as expected by the consumers. Apart from that, Anderson
and Weitz (1989, p. 312) referred brand trust as “one party’s belief that its needs would
be fulfilled in the future by actions undertaken by the other party.”
According to Delgado-Ballester and Munuera-Aleman (2001), brand trust was
defined as the level of brand in achieving consumption expectations, which resulted in
a feeling of security towards the brand. They further identified that consumerrelationship brand trust consisted of only one dimension instead of two general
dimensions that exists in marketing literature, such as brand reliability and brand
intentions. Brand reliability implied brand as a promise of future performance, which
could be referred to the ability of the brand to fulfill its consumer’s need (Deighton,
1992). For instance, offering a constant quality level and updated products or services
to consumers. On the other hand, Michell, Reast and Lynch (1998) referred brand
intention to affective response and emotional roots. As it supported the brand by
ensuring consumers would not experience from any unwillingness incidents again as
this dimensions concerned with the belief that the latter was not going to take
opportunity advantage of the former vulnerability (Delgado-Ballester & MunueraAleman, 2001).
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Drawing on conceptualizations of trust in the social psychology literature,
researchers differentiated cognitive and affective trust in the following definition,
instead of brand reliability and brand intention (Lewis & Weigert, 1985). Cognitive
trust was based on based on evaluating the competence, reliability, and predictability of
the trusted object and reflects the economic understanding of trust as a rational choice
(Lewis & Weigert, 1985; Riegelsberger et al., 2005; Johnson & Grayson, 2005). It
could be assumed that cognitive trust towards a specific brand was greater when the
utilitarian value of the product in terms of quality or convenience was high (Chaudhuri
& Holbrook, 2001). On the other hand, affective trust was the emotion-driven form of
trust that was based on instant affective reactions, signals of benevolence, aesthetics,
and attractiveness. Frequently trust-based behavior resulted from a mix of affective and
cognitive trust (Corritore et al., 2003; Riegelsberger et al., 2005). For instance, products
with a high pleasure had provided non-tangible, symbolic benefits and were likely to
hold a greater potential to evoke positive emotions and affect-based brand trust.
Apart from definition and conceptualization, trust had become one of the key
variables in discussions of relationship marketing (Macintosh & Lockshin, 1997).
Relationship marketing could be referred to development of long term and value-laden
relationships with patrons and business partners, as well as with other stakeholders
(Kotabe & Helsen, 2001). Morgan and Hunt (1994) indicated that both commitment
and trust were necessary for the successful of relationship marketing. In their study of
commitment-trust theory, trust had a positive impact and was a key determinant and
necessary antecedents of relationship commitment and cooperation. Accordingly, trust
and commitment were major factors in the formation, development, and maintenance
of interpersonal and marketing relationships (Morgan & Hunt, 1994). Based on the
commitment-trust theory of Morgan and Hunt, it was obvious that trust was a key
factor in collaborative relationships with customers in business marketing (Lau & Lee,
1999). For these reasons, the management of customers’ trust was particularly vital in
service marketing (Zboja & Voorhees, 2006). This could be further supported by
consumers would never know the outcome of service before it was delivered, and in
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most of the time, consumers did not have the absolute judgment to differentiate the
performance of service provider even they had experienced it (Trawick & Swan, 1981).
Chiou et al. (2002) highlighted that trust preceded satisfaction for three main
reasons. Firstly, customers’ satisfaction would not be existed if consumers did not have
trust appraisal with service provider from past experience. Secondly, based on social
exchange theory, customers’ pre-exchange trust would positively relate to postpurchase satisfaction, which explained the formation of causal relationship from trust
on satisfaction (Singh & Sirdeshmukh, 2000). Thirdly, it was evidenced in the study of
long-term relationships experience.
According to Gwinner, Gremler and Bitner (1998), there are three major
components of benefits, which consisted of confidence benefit, social benefit, and
special-treatment benefit. The confidence benefit was considered as the most important
elements (Gwinner et al., 1998). This was because it served as the purposes to reduce
anxiety, diminish risk perception, and increase confidence level of service providers
(Gwinner et al., 1998). Subsequently, the overall satisfaction could be enhanced when
consumers felt confidence benefit, where it was relatively similar to the characteristic
of trust value (Chiou et al., 2002).
For the purpose of this study, affective brand trust was selected as it served as a
function in investigating the affective component of attitude, such as feeling held by an
individual or a group that is based on psychological perceptive. Cognitive brand trust
could be referred to perceived quality that had been discussed in pervious section. As a
conclusion, brand trust was considered to be a significant contributor to fast food brand
equity; consumers were more likely to trust the quality of fast food brands and prepared
to pay more for the reliability impact of brand quality that the brands imply (Rubinstein,
1996). This could be further explained as the consumer-brand relationship became a
promising framework to explain the value of fast food brands to consumers (Fournier,
1998; Morgan & Hunt, 1994).
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2.10 Brand Loyalty
Oliver (1997) referred brand loyalty referred to propensity of loyal consumer to
treat a focal brand as primary choice, prolong to buy a product or service of focal brand
even the alternative choices were superior, lower price and convenience. Apart from
that, Schoell and Guiltinan (1990) identified brand loyalty as the degree to which a
buying unit, such as a household, concentrated its purchases over time on a particular
brand within a product category. That is, it was related to the exclusive purchase, and
where a consumer constantly re-purchased for a particular brand, where repurchase
intentions appeared an as important conceptualization of loyalty construct (Brown,
1952). Griffin (1997) stated repeat patronage as the most crucial attitude for the
creation of loyalty and highlighted both loyalty and purchase cycle by representing the
repurchase loop. He further stated that the consumer would keep on changing or testing
other brand if there was no existence of loyalty on a focal brand.
Historically, brand loyalty was measured behaviorally via repeat purchase.
Conversely, Keller (1998) argued that there were more broad views instead of simple
purchase behaviors to measure brand loyalty, such as low level of brand switching.
Brand switching happened when the consumer had increased their willingness or desire
to accept other alternative brands, subsequently; the existence of brand loyalty would
be decreased (Keller, 1998). Bowen and Shoemaker (1998) stated a loyal customer was
less probability to switch to another competitive brand simply due to price difference,
and indicated that a high frequency of repurchase behavior as compared to non-loyal
customers. However, Ehrenberg (1988) argued that loyalty did not exist in consumer
perspective and the concept was unclear. Researchers proved that there was no support
from any empirical study of non-brand switching behavior among majority of loyal
consumers (Klein, 2001; Trivedi & Morgan, 1996). McAlister and Pessemier (1982)
indicated that intrinsic and extrinsic motivations affected brand switching behavior. For
instance, variety of options played a major role in intrinsic motivations (McAlister &
Pessemier, 1982) and the switching behavior could be the result of attribute satiation
(Zuckermann, 1979) or either curiosity (Sheth & Raju, 1974).
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Besides the definition, the measurement for brand loyalty also expressed in
various way; for example self-concept, social cost and image (Auty, 2001), satisfaction,
perceived value and brand familiarity (Wood, 2004), usage experience and convenience
(Rowley, 2005). Rust, Ambler, Carpenter, Kumar and Srivastava (2004) advocated that
brand loyalty had been accepted as a popular and credible metric of marketing success
in the market. Therefore, building brand loyalty was a worthy marketing objective
which should result in providing warrant business success and revenues (Kumar et al.,
2004).
For instance, Brand loyalty had generated cash flow to a firm and also
contributed brand profitability (Chaudhuri & Holbrook, 2001; Howell, 2004). This was
because brand loyalty enhanced efficiency and effectiveness of marketing programs by
reducing expenditure on promotion, giving competitive advantage, and providing a
platform for development through brand extensions (Chaudhuri & Holbrook, 2001;
Howell, 2004). Furthermore, loyal customers are happily paid premium prices for the
benefits and quality of the brand that alternative brands could not provide (Aaker,
1991). In addition, Gremler and Brown (1996) further stated three specific component
of loyalty in service context, which were the purchase, attitude and cognition. On the
other hand, Ha (1998) stressed that the development of brand loyalty measurement
were recommended to be identified in three distinctive aspect, namely cognitive
response, subjective norm, and purchase behavior.
Apart from the above arguments, Morgan (2000) classified that there were
different interpretations of loyalty, ranging from affective loyalty (“what I feel”) to
behavioral loyalty (“what I do”). Nevertheless, Chaudhuri and Holbrook (2001)
indicated the most commonly perspective of brand loyalty were behavioral and
attitudinal perspective. They further recommended that behavioral loyalty had a
tendency to expand to greater market share, while attitudinal loyalty had led to greater
relative brand pricing. Both behavioral and attitudinal brand loyalty are discussed in the
next section.
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2.10.1 Behavioral Brand Loyalty
Ehrenberg and Goodhardt (2000) defined behavioral brand loyalty as focusing
on the consistency of consumers’ actual buying behavior towards a particular brand,
this could be explained by a consumer who only considered a particular brand when
repurchased a product, without seeking on brand-related information. In other words,
these could be referred to as consumers’ repeat purchasing behavior towards a brand
without considering the consumers’ intention (Ehrenberg & Goodhardt, 2000).
Alternatively, Dick and Basu (1994) explained behavioral aspect of loyalty,
which focused on a measuring the proportion of consumer’s prior purchase of a
specific brand to the certain purchase habit. Schoell and Guiltinan (1990) defined it as
the degree to which a purchasing unit, such as a household, had focused its purchases
over time on a particular brand within a product category.
Behavioral approaches outfitted loyalty in four ways. First, measurement based
on the actual consumption of the goods or services (Veloutosou, Gioulistanis &
Moutinho, 2004). Researchers suggested it as combination of volume and frequency of
consumption over prescribed time periods (Lin, Wu & Wang, 2000; Veloutosou et al.,
2004). Ehrenberg (1988) highlighted that marketing practitioners also had put a great
amount of effort to categorize the purchaser patterns, such as frequent purchasers and
heavy purchasers. Secondly, behavioral loyalty concept was clearly fell within class of
measure, which focused on the amount of brand consumptions within a nominated
retail location or defined market (Driver, 1996; East, Harris, Willson & Hammond,
1995).
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Thirdly, it measured based on the probability of repeated purchase (Brown,
1952). Lastly, Tsao and Chen (2005) described this behavioral approach as
examination of time where consumers switched to other brands. In this perspective,
researchers measured behavioral loyalty as patterns of actual customer purchase by
asking consumers as to how often they purchased certain brands or services (Back &
Parks, 2003; Pritchard, Havitz & Howard, 1999 ; Reynolds & Arnolds, 2000).
1
Bloemer and Kasper (1995) characterized spurious behavioral brand loyalty as
repeated purchasing behavior without any attitudinal or psychological bonding brand
attributes and distinguished it from true brand loyalty, which was a function of
psychological processes based on brand commitment.
As a conclusion, behavioral aspects of loyalty could be referred as spurious
loyalty, such as simple repeated purchase behavior without emotional or psychological
bonding; true loyalty referred to attitudinal aspects of loyalty with consumers’
commitment (Bloemer & Kasper, 1995).
2.10.2 Attitudinal Brand Loyalty
According to Caruana (2002), attitudinal brand loyalty was measured by
psychological commitment to the target object. A consumer was defined as attitudinal
brand loyally when he or she expressed positive preference and commitment towards a
brand (Bloemer & Kasper, 1995). Besides, Farr and Hollis (1997) specified attitudinal
brand loyally on the consumer’s expression instead of physical action, such as
consumers’ beliefs, affection, and intention (Jacoby & Chestnut, 1978). Subsequently,
Oliver (1997) further discovered that attitudinal brand loyalty could be extended to a
chain of consumer favorable attitude towards a particular brand, which is the
commitment of consumer with the explanation of cognition, affect, and conation.
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Importantly, the classifications of three phases were in line with general
explanation of attitude (Ajzen, & Fishbein, 1977). Bagozzi (1978) and Breckler (1984)
argued that consumers’ evaluation was derived from different level of responses, and
these responses could be referred to as people’s attitude.
Cognition could be referred to as people’s thoughts about the attitude object,
which consisted of belief, mental, “rational” states, intellectual or belief in the
statement of fact (Lavidge & Steiner, 1961). Affect could be deliberated by
physiological responses or a collection of verbal reports, which consisted of emotional
responses, feelings and moods (Lavidge & Steiner, 1961).
Eagly and Chaiken (1993) further stated that the affective responses could be
exceptionally identified in both positive and negative range, and was positioned on an
evaluative dimension of meaning. Conation was defined as motivational component,
such as the “striving” states, which could be referred to both positive and negative
tendency to treat an attitude object (Lavidge & Steiner, 1961).
According to Back and Parks (2003), based on the general components of
attitude, sequential process could be evidenced in attitudinal brand loyalty as
consumers would become “loyal first in a cognitive sense, then later in an affective
sense, and still later in a conative manner” (Oliver, 1997, p. 392). This could be further
explained as consumers first, became cognitively loyal that based on the belief on
brand attribute (Oliver, 1997).
Next, consumers had turned out to be affectively loyal, indicating quality
feeling such as exciting and pleasure (Oliver, 1997). Lastly, consumers had become
conatively loyal, revealing a brand-specific commitment (Oliver, 1997). Consequently,
this sequential justification was in line with the theory of reasoned action as presented
by Ajzen and Fishbein (1980), which related to consumers’ belief about and attitudes
towards their behavioral intentions, as well as to actual behaviors.
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In term of measurement, Knox and Walker (2001) explored that attitudinal
loyalty was assessed on the basis of responses to the statement by asking the favorite
brand name regardless of price. Besides, the measurement of attitudinal loyalty was
based on other factors, such as customer’s intention of repeat purchase (Anderson &
Sullivan, 1993; Cronin & Taylor, 1992; Chiou & Droge, 2006), recommendation to
others (Boulding, Kalra, Staelin & Zeithaml, 1993; Reich, McCleary, Tepanon &
Weaver, 2005; Russell-Bennett et al., 2007), low switching to better competitors
(Narayandas, 1996), attachment (Back, 2005), or willingness to pay a price premium
(Narayandas, 1996; Zeithaml, Berry & Parasuraman, 1996).
As a conclusion, attitudinal brand loyalty was considered as an important
dimension in the context of hospitality sector (e.g. fast food) as loyalty customers
would commit on post-consumption behavior (Kim, Magnini & Singal, 2011). That is,
it was referred as the depth and of the psychological bond consumers had with the fast
food brands, such as recommendation to other, active engagement sense of community,
and positive word-of-mouth (Keller, 2001).
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2.11 Conclusion
A comprehensive literature review was done in this chapter; basically, there
were two different perspectives in brand equity conceptualization, which were financial
and consumer-based. This study had adopted consumer perspective brand equity with
psychological-based approach.
There were different dimensions of consumer-based brand equity across
industries, in this study; six dimensions were identified, namely perceived quality,
brand awareness, brand familiarity, brand image, brand trust and attitudinal brand
loyalty.
For the purpose of this study, Gil et al.’s (2007) theory was adopted and
modified to generate a meaningful research in examining the attitudes of Malaysian fast
food consumers. Reason being they had highlighted the causal relationships between
dimensions of consumer-based brand equity, which based on the explanation of
cognitive-affective-conative.
Additional dimensions such as brand familiarity and brand trust were included
as they served as important dimensions in the context of fast food. All the variables in
this study were considered as a uni-dimensional constructs rather than a multidimensional. This was because the purpose of this study was to develop a new model of
consumer-based brand equity rather than to identify dimensionality of the constructs.
Subsequently, all of the variables were measured wholly in term of its truth, having no
detail breakdown of elements.
Each of the constructs was extensively discussed, and the definition for each of
the variables was indicated, based on previous researchers’ definition and suitability for
this study. Chapter Two would lead to better measurement for the development of
instrument in Chapter Three.
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CHAPTER 3
RESEARCH METHODOLOGY
3.1 Introduction
Firstly, this chapter starts with the presentation of research framework, which
has extended Gil et al.’s (2007) model. Additionally, each of the hypotheses was
elaborated. Next, the chapter is followed by the formation of questionnaire and the
selection of instrument items for each of the variables.
Basically, there were three studies conducted, namely preliminary study, pilot
study and main study. The main objective of the preliminary study was to identify
stimulated brands and brand image measurement in the Malaysian context of fast food
industry. Therefore, open-ended question was conducted to allow the respondents to
freely express brand image by means of their own terms. Subsequently, the design of
the pilot study and main study are also presented. The main study was described by a
sample selection and data collection procedures. Information about collection
procedures for collecting data is also included. The last part of the chapter explains the
methods of the data analysis. This section involved the justification for the use of
Structural Equation Modeling (SEM). Lastly, the chapter presents the detail of
descriptive analysis, assessment the fit of measurement model and assessment the fit of
structural model.
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3.2 Overview of Proposed Research Framework
Note: BA=Brand awareness, PQ=Perceived quality, BF=Band familiarity, BI=Brand
image, BT=Brand trust, ABL=Attitudinal brand loyalty, BE=Brand equity
Figure 3.1: Proposed Research Framework
Based on Gil et al.’s (2007) theory of brand equity, a proposed research
framework was developed as presented in Figure 3.1. Brand familiarity and brand trust
were identified as additional dimensions because they served as important dimensions
in the context of fast food (Morgan & Hunt, 1994; Smith, 1993). The research
framework postulated that there are causal relationships among dimensions of
consumer-based brand equity. It served as an important platform in explaining the
missing link between perceived quality and brand equity as indicated in Gil et al.’s
(2007) framework. With reference to the above framework, perceived quality might
have influenced on brand equity via other variables, for instance brand image, brand
trust and attitudinal brand loyalty.
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Besides, the research framework also had shown that attitudinal brand loyalty
played as the key variable in explicating the relationships between other dimensions
and overall brand equity. In other words, brand equity did not exist when there was no
attitudinal brand loyalty. This proposition corresponded to Gil et al.’s (2007) research
framework.
In addition, the dimensions of consumer-based brand equity were categorized as
cognitive-affective-conative characters. One possible explanation could be that the
traditional attitude structure started with cognitive beliefs (perceived quality, brand
awareness, brand familiarity and cognitive brand image), followed by affective
response (affective brand image and brand trust), and followed by conative responses
(attitudinal brand loyalty and overall brand equity) (Ajzen & Fishbein, 1980; Oliver,
1997).
As highlighted above, brand image covered a border view of consumers’
response, both cognitive and affective characters. The results from preliminary study
(see section 3.4.2 Result of Preliminary Study) supported the view that consumers
would have both cognitive and affective image towards the fast food brands. More ever,
this findings has been echoed by many studies in environmental psychology which had
indicated consumers would have both cognitive and affection images towards a
destination (Russel & Pratt, 1980). The element of cognitive was referred to the
knowledge that consisted of objective attributes (Keller, 1993). On the other hand,
affective component was referred to as the emotional feeling and affective quality
(Genereux et al., 1983).
As a conclusion, the proposed research framework was in line with Gil et al.’s
(2007) theory. However, it had extended their model by including the categorization of
cognitive-affective-conative in consumer-based brand equity setting. Furthermore, it
covered greater numbers of consumer-based brand equity dimensions and examined
greater numbers of causal effects.
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3.3 Development of Hypotheses
According to Erdem and Swait (1998), when there was existence of uncertainty
about product attributes, brand could be served as a platform to ensure credibility and
position of the product by decreasing perceived risk and information costs as identified
by consumers. Therefore, the reduction of uncertainty leads to higher quality as
expected by consumers (Erdem & Swait, 1998).
Dodds, Monroe and Grewal (1991) indicated that brand awareness or brand
popularity had positive effect on consumers’ perception of quality and value. Therefore,
brand awareness allowed consumers to associate the brand with its product category,
referring to the potency of the brand presented in the consumers’ mind (Aaker, 1996).
This could be supported by Grewal, Krishnan, Baker and Borin (1998) bicycle brand
study; both perceived quality and brand awareness were positively correlated. As a
result, this study concluded that there was positive correlation between perceived
quality and brand awareness.
On the other hand, Gursoy and McCleary (2004) argued brand familiarity was
formed by the acquired information through external sources, for instance word-ofmouth, advertising, and internal sources (such as the use of product). Researchers
stressed out that the higher the brand awareness, the greater the brand familiarity and
reputation (Cobb-Walgren et al., 1995; D’Souza & Rao, 1995). Researchers also
proved that brand awareness was the dominant selection process among consumers
(Reynolds & Olson, 1995). This could be supported by Alba and Hutchinson’s (1987)
argument, where a consumer’s recognition and recall of a certain brand name would
build a sense to familiarity.
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Referring to Keller (1993), there were three reasons which indicated the
importance on brand awareness in consumer decision making. Firstly, it was essential
that the brand came to consumers’ mind, when they thought about the product category.
Consequently, the high level of brand awareness had established the brand in the
consumer’s mind set and eventually influence on consumer decision making (Hoyer &
Brown, 1990; Macdonald & Sharp, 2000).
Secondly, brand awareness had enhanced the level of consumers to consider or
purchase the brand, regardless whether there was any other brand associated with it.
Studies indicated that a low level of brand awareness could significantly result in
product purchase decisions, particularly when consumers had to make simple rule of
decision (Hoyer & Brown, 1990; Petty & Cacioppo, 1986a), for instance fast food.
Thirdly, brand awareness insisted that consumers had to have greater
association with its brand image, in other words, it served as a vital element in
formatting and presenting a strong brand in consumers’ memory (Keller, 1993). This
could be further supported by brand awareness generated differences in information
processing, and these differences, which were created by brand associations in the
consumer’s memory, directly affected brand image (Hoyer & Brown, 1990). Studies
had supported these statements with the evidence that brand awareness positively
affected brand image in consumer goods product (Angel & Manuel, 2005; Esch,
Langner, Schmitt & Geus, 2006).
In addition, Aaker (1991) emphasized that the awareness of brand was the
beginning of loyalty. If a customer was aware of a certain product or brand, there was a
higher possibility that the customer would have a favorable image of the product or
brand. Therefore, positive brand image through high brand awareness had increased the
likelihood of brand purchase leading to brand loyalty (Keller, 1993).
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Brand awareness was an important component of brand equity; it referred to the
brand salience that existed in consumers’ memory (Aaker, 1996). Recall, recognition,
brand dominance, top-of-mind, brand opinion and brand knowledge were the difference
levels of brand awareness (Aaker, 1996). According to Aaker (1991), brand awareness
contributed brand equity creation that focused on consumers’ memory, referring to
brand node, brand popularity, signal of brand trust, and consideration set of the brand
(Aaker, 1991). Even though brand awareness was a vital component of brand equity as
discussed. There was no causal effect on brand equity or brand loyalty empirically
(Rosa & Riquelme, 2008; Tong & Hawley, 2009; Wang et al., 2008). This could be
supported by Rosa and Riquelme’s (2008) online study where brand awareness did not
show a significant effect on brand equity. They indicated that brand awareness alone
could not guarantee the successful of brand equity in sportswear market. Moreover,
Wang et al. (2008) advocated brand resonance, which was brand loyalty in term firm
perspective (Keller, 2001), did not support the hypothesis of related positively to the
extent to which brand awareness was evident in global brand equity model. Conversely,
Gil et al. (2007) proved that brand awareness/association had causal effects on brand
loyalty in consumer goods. However, there were only two observed variables existed in
the variable, and most of the observed variables were deleted to satisfy the statistical
result (Gil et al., 2007). At one hand, previous studies concretely had supported that
brand awareness lead to better brand familiarity and brand image. On the other hand,
brand awareness did not show a consistency of positive effect on brand loyalty and
brand equity. Therefore, the following hypotheses were formulated:
Hypothesis 1:
There is positive correlation between brand awareness and perceived quality
Hypothesis 2:
The higher the awareness of a brand, the greater the brand familiarity
Hypothesis 3:
The higher the awareness of a brand, the greater the brand image
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Researchers suggested that consumers evaluated the brand more positively
when they were familiar with the brand and therefore created favorable images for
familiar brand (Janiszewski, 1993; Holden & Vanhuele, 1999). Ho and Chong (2003)
suggested that the level of brand familiarity and consumption experiences influenced
consumers towards brand attributes, and brand attributes. Brand attributes was one of
the components of brand image (Keller, 1993). For this reason, consumers individually
assessed each descriptive feature of characterized products or services based on
familiarity and experience that they had with the brand (Ha & Perks, 2005).
Consequently, the higher level of brand familiarity led to the better evaluation of brand
attributes, which ultimately contributed to higher level of brand image (Keller, 2003).
The above statement could be supported by Zajonc and Markus’ (1982) study; they
proposed that brand familiarity caused consumers to have favorable evaluations on a
service or brand. When a consumer was confronted with a familiar brand, he or she had
felt emotional closeness and confidence and increased the level of consumer experience,
thus drove to greater formation process of brand image (Zajonc & Markus, 1982).
Campbell and Keller (2003) advocated that increasing brand familiarity through
accumulated customer experiences not only created a knowledge structure for the
consumer, but also built up consumer confidence about the brand (i.e. positive
evaluation), which led to brand trust (Zajonc & Markus, 1982; Sen & Johnson, 1997).
These could be further supported by the development of familiarity which leads to
higher level of brand trust (Keller, 1998). According to Alba and Hutchinson (1987),
brand familiarity could be derived from customers’ experience. In other words, brand
experience can be served or used as criteria for brand familiarity. As a result, brand
familiarity had significant influenced on brand trust as the trust of the brand could be
derived from positive customer experience (Fullerton, 2005; Papadopoulou, Kanellis &
Martakos, 2001; Smith & Wheeler, 2002).
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For these reasons, the following hypotheses were stated:
Hypothesis 4:
The higher the familiarity of a brand, the greater the brand image
Hypothesis 5:
The higher the familiarity of a brand, the greater the brand trust
According to brand knowledge (Keller, 1993), good evaluation of perceived
quality had increased brand association. This was because when there is a good
perception of quality, a positive brand image had been created as there were strong,
favorable, and unique associations linked to the brand due to greater brand attributes,
benefits, and attitudes as perceived by consumers. This could be supported by
Kayaman and Arasli’s (2007) study, where tangibility, reliability and empathy
(perceived quality in service industry) showed positive effect on brand image in a hotel
study.
Mohd Rizaimy et al., (2011) showed that perceived quality could be existed
when there is positive satisfactory towards the service providers and food quality.
Consequently, these would lead to the establishment of bond between consumers and
the brand due to the present of trust feeling (Delgado-Ballester & Munuera-Aleman,
2001). This could be supported by the positive quality evaluation increased consumers’
knowledge and perception of the brand (Keller, 1998), which ultimately influenced the
level of trust. For these reasons, positive perceived quality would lead to the
enhancement of trust as perceived by consumers (Papadopoulou et al., 2001).
According to Gil et al. (2007), brand loyalty preceded brand awareness, brand
associations and perceived quality. This was because they applied the theory of
cognitive-affective-conative, which classified perceived quality as cognitive construct.
They also argued that cognitive construct (perceived quality) had influenced affective,
and affective response would drive to conative (attitudinal brand loyalty) and led to
purchase decision. Consequently, causal effect could be identified (Chiou et al., 2002).
78
On the other hand, Roberts, Morrison, Chandrashekaran and Gordon (2004) had
also applied the concept of purchase decision stages to rationalize the causal
relationships between perceived quality and loyalty. In this case, they had identified
perceived quality as information evaluation stage, which proceeded to purchase
decision stage, referring to loyalty. However, the study of Gil et al. (2007) showed that
perceived quality was not significantly affecting brand loyalty and brand equity.
Furthermore, Tong and Hawley (2009) indicated that perceived quality did not have
causal effect on brand equity; they further explained that by just maintaining high
quality or awareness of the brand, was not adequate in ensuring the successfulness of a
brand in the sportswear industry. As a result, perceived quality alone was not sufficient
in securing overall brand equity (Tong & Hawley, 2009). However, attitudinal brand
loyalty could serve as precede construct of perceived quality. Thus, this study had
derived the following hypotheses:
Hypothesis 6:
The higher the perceived quality of a brand, the greater the brand image
Hypothesis 7:
The higher the perceived quality of a brand, the greater the brand trust
Hypothesis 8:
The higher the perceived quality of a brand, the greater the attitudinal brand
loyalty
Indeed brand image has a strong dominant factor in the level of consumer trust
(Esch et al, 2006). A positive corporate image such as high competence and reliability
would lead to higher level of consumer trust (Sichtmann, 2007). In the retail setting,
Esch et al. (2006) confirmed that there was a direct impact of brand image on a
consumer’s brand trust, and both direct and indirect influences of brand image on
current and future purchases. In the website setting, Yoon (2002) argued there was
significant influence of corporate image (i.e. brand image) on consumers’ trust.
79
Besides, a financial study had stressed that brand image was one of the
fundamental in building a sincere relationship of trust between customer satisfaction
and loyalty (Flavián et al., 2006). If customers had favorable images towards a certain
brand, this process would exercise a positive influence on the customer’s trust (Esch et
al., 2006; Flavián et al., 2006) and eventually reinforced their loyalty (Back, 2005;
Kandampully & Suhartanto, 2000; Kandampully & Hu, 2007). Therefore, this study
proposed the following hypotheses:
Hypothesis 9:
The higher the image of a brand, the greater the brand trust
Hypothesis 10:
The higher the image of a brand, the greater the attitudinal brand loyalty
According to Pitta, Franzak and Fowler (2006), in a perfect world, trust was
unnecessary, but in the real world, it reduced the perceived risk by decreasing the
possibility of incurring a loss. As a result, Rauyruen and Miller (2007) argued that in
order to gain loyalty of customers, one must first gain their trust. For this reason, brand
trust had been recognized as a prominent variable leading to long-term relationship
with customers, which in turn affected brand loyalty in a positive way (Chiou & Droge,
2006; Flavian et al., 2006; Sichtmann, 2007; Matzler et al., 2008). This could be further
supported by many studies which proved that there was positive consumers trust on
customer loyalty (Morgan & Hunt, 1994; Mayer, Davis & Schoorman, 1995; Harris &
Goode, 2004). Furthermore, some researchers indicated that trust could positively
affect attitudinal brand loyalty neither directly nor indirectly via mediating variable,
such as customer satisfaction (Chiou & Droge, 2006). In addition, brand trust had a
substantial impact on consumer behaviors, such as the selection of existing products
and word-of-mouth (Sichtmann, 2007), repurchase intention (Esch et al., 2006), and
recommendations to others (Lau & Lee, 1999).
80
Furthermore, Aaker (1996) declared that brand trust went beyond consumer’s
satisfaction, which was based on the functional performance of the product and its
attributes. In conclusion, brand trust was the key variable to maintain continuous
relationships with customers, which sequentially led to attitudinal brand loyalty
(Matzler et al., 2008). Thus, the following hypothesis was derived:
Hypothesis 11:
The higher the trust of a brand, the greater the attitudinal brand loyalty
Many scholars argued that loyalty was the foundation of brand equity (Aaker &
Joachimsthaler, 2000; Clarke, 2001), because loyal consumer would treat a focal brand
as primary choice, prolong to buy a product or service of focal brand even the
alternative choices were better than the focal brand (Oliver, 1997). Many studies
indicated attitudinal brand loyalty had causal effect on brand equity (Gil et al., 2007;
Kim & Kim, 2004; Norjaya et al., 2007; Tong & Hawley, 2009; Yoo et al., 2000). This
showed the essential role of attitudinal brand loyalty in brand equity creation. This
could be further supported by attitudinal brand loyalty such as customer’s intention of
repeat purchase (Anderson & Sullivan, 1993; Clarke, 2001; Cronin & Taylor, 1992;
Chiou & Droge, 2006), recommendation to others (Boulding et al., 1993; Reich, et al.,
2005; Russell-Bennett et al., 2007), low switching to better competitors (Narayandas,
1996), positive word-of-mouth (Clarke, 2001), and brand attachment (Back, 2005).
Therefore, the following hypothesis was recommended:
Hypothesis 12:
The higher the attitudinal loyalty of a brand, the greater the brand equity
81
3.4 Questionnaire Development
The purpose of instrument items was to test the twelve formulated research
hypotheses. It was important to ensure that the instrument accurately measured the
underlying constructs or variables. The majority of the instruments were borrowed
from previous studies, which were constructed from other countries and industries.
Therefore, it was necessary to test the instruments prior to the data collection
process to ensure its applicability in the Malaysian fast food market. Subsequently,
brand image instruments were developed through preliminary study as different
industry would have different consumers’ response on brand image (Aaker, 1996; Kim
& Kim, 2005). A six-point scale (with anchors of 1 = strongly disagree and 6 = strongly
agree) was employed to indicate a degree of agreement for each of the items
(Hishamuddin, 2007). There are two major parts in the survey form: (1) Evaluation of
brand equity, and (2) Demographic questions.
3.4.1 Preliminary Study
The main objective of preliminary study was to select fast-food restaurant
chains for pilot study and main study. Besides, it also serves as a function in
developing brand image measurement. According to Low and Lamb Jr. (2000), the
development of brand image scale was designed to be product-specific. Chowdhury,
Reardon, and Srivastava (1998) also stated that a free response technique needed to be
applied in brand image studies. Therefore, open-ended question was proposed as it
allowed for gathering consumers’ point of view, feelings and any perspective that
related to the issues (Lindlof & Taylor, 2002).
82
In order to explore brand image associations from the consumer’s selfexplicated perceptions, a free response technique was adopted for this study, rather than
answers to definitional questions provided by the researcher (Park, 2009). This was
because it allowed respondents to freely express a given motivation by means of their
own terms (Jain & Etgar, 1976-1977). During preliminary study, two open-ended
questions were addressed; the second question was adopted from previous studies
(Zimmer & Golden, 1988; Keller, 2003). Two questions were illustrated below:
Questions 1:
Please list three fast food restaurant chains in which you had most frequently dined.
Questions 2:
You can freely describe any characteristics that come to mind when you think about …
(above brand(s) name)… using any words/phrases your choice.
According to Zimmer and Golden (1988), respondents would express greater
cognitive attribute-related descriptions as compared to affective type, even affective
descriptions present in the consumer’s mind. Since open-ended question was used, the
study was not restricted to any type of answer (cognitive or affective) being provided
by consumers, it covered different type of brand image as associated by consumers.
The preliminary study consisted of 45 consumers, which had been conducted from 20th
November 2010 to 28th November 2010, as presented in Table 3.1
Table 3.1 Time Slot of Preliminary Study
11 a.m.
12 p.m.
2 p.m.
4 p.m.
6 p.m.
Total
Respondents
20Nov
1
1
1
1
1
21Nov
1
1
1
1
1
22Nov
1
1
1
1
1
23Nov
1
1
1
1
1
24Nov
1
1
1
1
1
25Nov
1
1
1
1
1
26Nov
1
1
1
1
1
27Nov
1
1
1
1
1
28Nov
1
1
1
1
1
5
5
5
5
5
5
5
5
5
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3.4.2 Result of Preliminary Study
At the beginning of the research, the respondents were informed of the
objective of the study and were requested to list down three fast food restaurant chains
that they had most frequently visited. The result showed that the most popular fast food
brands were McDonald’s, Kentucky Fried Chicken (KFC), Pizza Hut, A&W, Burger
King, Marrybrown, 1901 Hot Dogs, Domino Pizza, and Subway as indicated in Table
3.1
Table 3.2 Identified Fast Food Brands
Fast Food Brands
Number of Hits
McDonald’s
44
Kentucky Fried Chicken (KFC)
39
Pizza Hut
27
A&W
4
Burger King
4
Marrybrown
4
1901 Hot Dogs
4
Domino Pizza
3
Subway
2
Papa John’s
1
Carl’s Jr.
1
Nando’s
1
Rasamas
1
In order to identify the brand image of fast food, the second open-ended
question was asked. There was no right or wrong answer; respondents were free to
express their answer based on the selected brands in question 1.
84
Table 3.3 Identified Brand Image Items
Brand Image Instruments
Number of Hits
Delicious
33
Easy and fast
25
Good physical environment
17
Pleasure
14
Free WiFi
13
Good customer service
11
A place for gathering
10
Many types of choices
8
Free refill
7
Convenience
7
Widely distributed
4
Initially, there were 46 items had been identified from the preliminary study
(see Appendix A). However, only 11 items were selected as the numbers of hits were
more than 1 time (see Table 3.3). Consequently, 35 items were excluded. One
additional item, “Long history” was added to the brand image measurement, based on
previous studies on brand image (Aaker, 1991; Keller, 1993; Kim & Kim, 2005). Thus,
there were 12 initial observed variables of brand image that was created to enhance the
consumers’ understanding about the measurement.
85
3.4.3 Selection of Fast Food Brands
In this study, fast food brand was defined as those restaurant corporations that
provided expedited food service, established standard operating procedure (SOP),
offered Western pattern diet, and had franchises in multiple states or nationwide
(Ashkanasy & Nicholson, 2003; Block et al., 2004; Burdette & Whitaker, 2004;
Slattery et al., 1998).
Initially, the study tried to approach all the thirteen fast food head offices to
participate in this study (see Table 3.1). First and foremost, phone calls were made to
invite those companies to participate. Next, it was followed up with an electronic
official letter on the university’s letter head to further support the application. The
study later confirmed that the data gathered would be reserved for research purpose
only. Nevertheless, only Marrybrown and 1901 Hot Dogs were willing to give
permission to conduct survey in their restaurants. Both of the companies were very
cooperative and helpful. The person-in-charge (PIC) provided verbal consent to
conduct research fieldwork at their outlets. However, the PIC reminded the researcher
to ensure that data collection process did not interrupt their daily operations and
customer service.
The managers of other fast food brands with head offices located in Kuala
Lumpur did not allow third parties to conduct any surveys on their products and
services because they did not want any interruptions in business operations.
Importantly, they had to get permission from their franchisees and had accounted for all
the consequences of this survey. However, their advice was to approach the supervisors
of targeted outlets informally. Eventually, verbal permission was obtained from the
branch supervisors of McDonald’s, Kentucky Fried Chicken, and Pizza Hut.
86
According to Bernama (2009), Malaysian brands enjoyed popularity from
overseas, which included food products such as Secret Recipe, 1901 hotdogs, and
Marrybrown. These could be supported in year 2010, Business Times (2010) reported
Marrybrown Fried Chicken private limited had successfully expanded Malaysian
foodservice franchise to 10 other countries, and 1901 Hot Dogs currently had expanded
their business to Singapore and Indonesia with eight outlets. On the other hand, there
were 475 KFC outlets, 194 McDonald’s outlets (Hoe, 2009), and 193 Pizza Hut outlets
(MIDF Research, 2009) in Malaysia. According to Aseambankers (2007), they
controlled approximately 80% fast food market share in Malaysia. As a result, the
selected fast food brands (1901 Hot Dogs, Marrybrown, McDonald’s, KFC, and Pizza
Hut) represented relevant and reliable brands which finalized in this study.
3.5 Operational Definitions and Development of Measurement Scales
As mentioned in Chapter 2, there were seven variables which had been
identified in this study, such as perceived quality, brand awareness, brand familiarity,
brand trust, brand image, attitudinal brand loyalty and brand equity. The measurement
scales for each of the variables were derived from the previous authors, except for
brand image. Next section discusses the measurement items for each of the variables.
3.5.1 Perceived Quality Instruments
In the service industry, Kim and Kim (2005) indicated that perceived quality
could be classified into two types. Firstly, it was referred to as the service quality that
was provided by physical facilities, such as business hours, physical environment, and
modern equipment. Secondly, it was referred to service quality provided by employees,
such as courtesy, responsiveness, and helpfulness. Both of these perceived quality
evaluations had cognitive responses at the attribute level (Chiou et al., 2002). The
current study defines perceived quality as the overall customers’ cognitive response on
the superiority of service quality when offered by companies and employee.
87
In this study, performance-based approach was selected to measure perceived
quality, rather than expectation and perception approach (Olorunniwo, Hsu, & Udo,
2006). This was because the focus of this study was to identify the perception of
consumers towards the brands instead of examining consumers’ expectation
(Olorunniwo et al. 2006). Therefore, the measurement scheme was adopted from
SERVPERF, also well-known as SERVQUAL’s approach (Fick & Ritchie, 1991; Lee
& Hing, 1995; Parasuraman, Zeithaml & Berry, 1985). There were number of
components that had been classified under SERVQUAL, in order to measure unidimensional of perceived quality, this study implemented ten items of SERVQUAL as
recommended by Kim and Kim (2005, p.559) in their fast food chains study.
3.5.2 Brand Awareness Instruments
Brand awareness was defined as the potentiality of consumer to identify a
particular brand from his or her memory when encountering a selection process or
decision making progress. Three items were developed from previous studies (Park,
2009, p.56), another item: “When I think about [fast food category], X is the first brand
that comes to my mind” was adopted from the study by Gil et al. (2007, p.193).
3.5.3 Brand Familiarity Instruments
This study characterized brand familiarity as well-established through cognitive
representations of knowledge stored in memory with the brand, as consumers became
familiar with the brand; they were more likely to perceive the brands’ relevance.
Subsequently, three items were adopted from previous research studies (Park, 2009,
p.57). One additional item was added: “I do not know about X”.
88
3.5.4 Brand Image Instruments
Brand image was considered as a uni-dimensional construct rather than a multidimensional as the purpose of this study was to develop a new model of consumerbased brand equity, rather than to identify the dimensionality of brand image. Thus, this
study defined brand image as overall image that was formed from the result of both
cognitive and affective images towards fast food brands. The element of cognitive was
referred to as the knowledge that consisted of objective attributes. On the other hand,
affective component was referred to as the emotional feeling and affective quality
(Genereux et al., 1983). Low and Lamb Jr. (2000) stated the development of brand
image scale should be designed according to product-specific. A total of 11 items had
been identified from preliminary study (see Table 3.3 Identified Brand Image Items).
Besides, this study also had adopted one additional item “Long history” from Kim and
Kim’s (2005, p.559) measurement due to its common use in fast food studies.
3.5.5 Brand Trust Instruments
Brand trust was operationally defined as the affective component of attitude
towards a brand, such as feelings held by an individual that was based on psychological
perceptive. Brand trust was measured by four items that was adopted from Matzler et al.
(2008, p.156) and Park (2009, p.57).
3.5.6 Attitudinal Brand Loyalty Instruments
Attitudinal brand loyalty was defined as the propensity to be loyal to a focal
brand as presented by the brand choice, brand intention and brand commitment. Four
items were adapted from Chiou and Droge (2006, p.625) to measure brand attitudinal
brand loyalty.
89
3.5.7 Brand Equity Instruments
Consumer-based brand equity was operationally defined as the brand
commitment that resulted from consumer’s perception of overall superiority of a
particular product or service category carrying that brand name. Brand equity was
measured using four items from Gil et al. (2007, p.193).
Table 3.4 Instrument Items
Instrument Items
Authors
Perceived quality
The staff gives customers individual attention.
The staff is well-dressed, clean, and neat.
The staff provides its prompt services at promised times.
The staff handles complaints of customers effectively.
The staff is always willing to help customers.
The staff is knowledgably and confidence.
X provides clean dining areas and appealing decorations.
X has operating hours convenient to all of its customers.
X maintains its food quality.
X insists on error-free service.
Brand Awareness
I am aware of X as a fast food brand.
X is highly recognized.
I have heard a lot about X.
When I think about [fast food category], X is the first
brand that comes to my mind.
Brand Familiarity
I am familiar with X.
I have been to X multiple times.
I am knowledgeable of X.
I do not know about X.
Kim and Kim
(2005, p.559)
Park (2009, p. 56)
Gil et al. (2007, p.193)
Park (2009, p. 57)
90
Table 3.4 Instrument Items (Continued)
Instrument Items
Authors
Brand Image
Delicious
Easy and fast
Pleasure
Free WiFi
Free refill
Convenience
Widely distributed
Long history
Preliminary study
Kim and Kim
(2005, p.559)
Brand Trust
This brand feels safe to me.
I trust this brand.
This brand is reliable to me.
This brand is dependable to me.
Matzler et al.
(2008, p.156)
Park (2009, p. 57)
Attitudinal Brand Loyalty
If I had to do it over again, I would choose X.
I try to visit X because it is the best choice for me.
I consider myself to be a loyal customer of X.
This brand is special to me.
Brand Equity
It makes sense to visit X instead of any other brand, even
if they are the same.
If there is another [fast food category] brand as delicious
as X , I prefer to visit X.
X is definitely my choice in [fast food category].
Even if another [fast food category] brand has the same
price as X, I would still visit X.
91
Chiou and Droge
(2006, p.625)
Gil et al. (2007, p.193)
3.6 Pilot Study
A pilot study was conducted to assess the clarity of the questions, as well as the
reliability and validity of the measurement items (Hishamuddin, 2007). Initially, the
study tried to include the validity test for both academicians and practitioners. It was
followed up with an electronic official letter on the university’s letter head to further
support the request. Nevertheless, only academicians were willing to give suggestion
for the improvement of questionnaire. Eventually, the validity of the questionnaire was
determined by Associate Professor Dr. Norjaya Mohd. Yasin (Universiti Kebangsaan
Malaysia), Professor Dr. Kim Hong-Bumm (Sejong University, Seoul, Korea), and Mr.
Lai Kim Piew (Multimedia University, Melaka campus, Malaysia), three of them are
academicians, who are experts in the area of branding research studies.
Firstly, “The staff is knowledgably and confidence”, the perceived quality
instrument was split into two separate observed variables to avoid double barrel
questions. Thus, the item was split into two items: “The staff of X are knowledgeable”
and “The staff of X are confident”. Besides, “Free refill”, a brand image instrument
was replaced to “Good value for money”, “Fast and easy” was suggested to be
expressed into two different items, which were “Fast” and “Prompt service”
respectively. There were only minor amendments recommended by the experts, most of
the suggestions were related to the structure of the statements and English proficiency.
The feedback from branding experts served as an important source for the validation of
question.
A total number of 50 surveys were collected from a nonprobability convenience
sampling from fast food consumers. The questionnaires were distributed to consumers
who had dined-in the fast food restaurants; they would then return the completed
survey to the researcher. Upon receiving the survey form from respondents, they were
asked if they had any doubts or difficulties in answering the questions (Yoo et al.,
2000). The respondents were asked to present their suggestions or to provide ideas to
improve the questionnaire.
92
Thus, adjustments to the items were made only after the consultation from the
experts. The Cronbach’s alpha, Skewness and Kurtosis test were used to analyze the
reliability of measurement items, and any items that were found to be unreliable were
dropped. According to Nunnally (1978), Cronbach’s alpha between 0.50 and 0.60 was
acceptable for pilot study. Referring to result in Table 3.5, the range for Cronbach’s
Alpha was from 0.75 to 0.91, which satisfied the cut-off value as suggested, indicated
internal consistency for the constructs. Besides, Skewness and kurtosis were used to
determine the test for normality, and a common rule-of-thumb for normal distribution
data was the observed variables should be ranged within absolute value of 2 (Tong,
2006). The result indicated that the values of skewness and kurtosis for all the observed
variables (except BA3) were within absolute value of 2. Higher kurtosis meant that
more of the variance resulted of infrequent extreme deviations, as opposed to frequent
modestly sized deviations (Mbogdan, 2010).
Since there were only 50 respondents, it had not provided sufficient evidence to
conclude the findings for BA3; it might be due to lack of power (Hair, Black, Babin &
Anderson, 2010). Thus, this study concluded that the data was normally distributed and
all of the listed instruments be used for the main study. Lastly, the results of the pilot
study also confirmed that the construct reliability of brand image, were derived from
the preliminary study. This was because the items of the brand image were normally
distributed and Cronbach’s Alpha (α = 0.84) was above cut-off value.
93
Table 3.5 Results of Mean, Normality and Reliability for Pilot Study
Instrument Items
Mean
Skewness Kurtosis
Brand awareness (α = 0.75)
BA1
I am aware of X.
5.48
-0.95
-0.24
BA2
5.66
-1.58
1.54
BA3
5.34
-2.29
8.06
BA4
When I think about [fast food category], X
is the first brand that comes to my mind.
5.32
-1.27
1.07
4.17
-0.14
-0.66
4.79
-0.51
0.55
4.43
0.07
-0.66
4.11
-1.12
2.14
4.34
0.06
-0.23
4.17
0.34
-0.41
The staff of X are confident.
X has operating hours convenient to all of
its customers.
4.36
-0.12
-0.29
5.19
-1.26
1.36
4.55
-0.67
0.75
PQ10 X insists on error-free service.
The physical facilities of X are visually
PQ11 appealing (e.g. dining areas decorations,
building).
4.06
-0.54
1.03
4.53
-0.55
0.19
Perceived quality (α = 0.86)
The staff of X gives customers individual
PQ1
attention.
The staff of X are well-dressed, clean, and
PQ2
neat.
The staff of X provides its prompt services
PQ3
at promised times.
The staff of X handles complaints of
PQ4
customers effectively.
The staff of X are always willing to help
PQ5
customers.
PQ6 The staff of X are knowledgeable.
PQ7
PQ8
PQ9
Brand image (α = 0.84)
BI1
Delicious
5.00
-0.79
0.85
BI2
Easy
5.06
-0.39
-0.37
BI3
Prompt service
4.80
-0.23
-0.83
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(Continued)
Instrument Items
Mean
Skewness Kurtosis
BI4
Good dining environment
4.76
-0.11
-0.96
BI5
Pleasant
4.82
-0.23
-0.83
BI6
Free WiFi
4.82
-0.57
-0.63
BI7
4.37
-0.55
1.01
BI8
A place for social gathering
4.80
-0.27
-1.06
BI9
Variety of choices
4.63
0.00
-0.97
BI10
Good value for money
4.41
-0.10
-0.86
BI11
Convenient
5.04
-0.36
-0.29
BI12
Widely distributed
5.14
-0.68
-0.29
BI13
Long history
4.82
-0.49
-0.69
Brand familiarity (α = 0.83)
BF1
5.20
-1.16
1.89
BF2
5.32
-0.51
-0.74
BF3
4.90
-0.24
-1.11
BF4
I can easily recognize X.
5.44
-0.81
-0.43
Brand trust (α = 0.88)
BT1
X is safe to me.
4.86
-0.94
1.37
BT2
X is reliable to me.
4.86
-0.31
-0.88
BT3
I trust X.
4.78
-0.41
-0.57
BT4
X is dependable to me.
4.54
-0.25
-0.86
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(Continued)
Instrument Items
Mean
Attitudinal brand loyalty (α = 0.91)
If I had to do it over again, I would choose
ABL1
X.
I try to visit X because it is the best choice
ABL2
for me.
I consider myself to be a loyal customer of
ABL3
X.
ABL4 X is special to me.
I would love to recommend X to my
ABL5
friends.
Skewness Kurtosis
4.90
-0.58
-0.39
4.57
-0.68
0.70
4.12
-0.37
-0.51
4.10
-0.21
0.02
4.51
-0.61
0.90
4.50
-0.85
0.60
4.06
-0.34
-0.65
4.18
-0.52
0.18
4.36
-0.81
0.30
Brand equity (α = 0.91)
BE1
BE2
BE3
BE4
It makes sense to visit X instead of any
other brand, even if they are the same.
Even if there is another [fast food
category] brand as delicious as X, I still
prefer X.
X is definitely my choice in [fast food
category].
Even if another [fast food category] brand
has the same price as X, I would still buy
X.
Note: α = Cronbach’s Alpha
96
3.7 Sample Size and Data Selection
This study targeted fast food consumers in the respective restaurants. This was
because they were easy to be accessed when customers dined-in at fast food restaurants.
The sample size comprised of consumers’ age range from 18 to 45 years old. Five fast
food restaurants from different area of Klang Valley were selected for this study. With
respect to sample selection, Peninsular Malaysia was selected because most of the fast
food outlets were based in Peninsular Malaysia than in East Malaysia, while it was also
impracticable to study the whole of Malaysia because of budget and time constraints
(Saunders, Lewis & Thornhill, 2003).
According to Norzalita and Norjaya (2010), Klang Valley was considered as the
most highly populated region in Malaysia, which consisted of people from diverse
ethnic compositions and demographic groups, such as people from different states of
Malaysia. In addition, Klang Valley was located within the Federal Territory of
Malaysia, populated with economically and socially most advances people (Norzalita
& Norjaya, 2010). Furthermore, it composed of approximately 25% population in
Malaysia (Horlic, 2011). For these reason, Klang Valley are widely selected for
Malaysian research (Chan, 2009; Chok, 2008; Hee, 2009; Hishamuddin, 2007; Norjaya
et al., 2007; Norzalita & Norjaya, 2010; Ooi, 2009; Siti Safira, 2008; Yap, 2009).
The main reason of using nonprobability sampling was because the use of
random sampling was not possible in fast food study. Importantly, the number of fast
food consumers could not be identified as there was no statistical support data.
Everyone in this world could become fast food consumers, thus it would lead to the
inaccuracy of sampling frame if probability sampling was proposed. Furthermore, the
conceptual model of this study was derived from theoretical generalizability, not
population generalizability (Calder, Philips & Tybout, 1982). For these reasons,
nonprobability sampling method had been selected.
97
Therefore, non-probability convenience sampling method was adopted as it was
efficient and appropriate (Cavana, Delahaye & Sekaran, 2000). In addition, this method
was used in most of the brand equity or fast food studies (Bamert & Wehrli, 2005;
Chan, 2009; Gil et al., 2007; Henry et al., 2010; Kayaman & Arasli, 2007; Kim & Kim
2004, 2005; Kobayashi, 2011; Lin, Marshall & Dawson, 2009; Namkung & Jang, 2010;
Pike et al., 2010; Mohd Rizaimy, Abdul Sabur, Suhardi, Shamsul, Muna & Maznah,
2011; Mohd Rizaimy et al., 2011; Rosa & Riquelme, 2008; Ryu, Han & Jang, 2010;
Tong & Hawley, 2009; Henry et al., 2010; Wang et al., 2008; Van Zyl et al., 2010; Yoo
et al., 2000; Zainuddin, Kamaruzaman, Muhammad Abi, and Wan Asri, 2009).
Those consumers who had agreed to participate were given self-administrated
questionnaire, where respondents were instructed to complete the questionnaire and
return the survey to the administrator in the respective restaurants. With reference to
Table 3.6, a total number of 600 questionnaires were distributed because this study was
in line with nonprobability sampling of previous studies (Halim & Hamed, 2005; Perez,
Padgett & Burgers, 2011; Yoo et al., 2000), and the sample size was adequately above
the number of nonprobability convenience sampling for most of the recent studies that
focused on brand equity or fast food research (see Table 3.6).
According to Loehlin (1992), structural equation modeling (SEM) required at
least 100 sample sizes, with 200 being better. On the other hand, Stevens (1996) stated
that a good rule of thumb was at least 15 cases were needed for every predictor in a
standard ordinary least squares multiple regression analysis. There were 6 predictors;
therefore 90 observations met the minimum sample size for the SEM analysis as
defined in the multiple regression. However, Hair et al. (2010) stated that the proposed
guidelines varied with analysis procedures and model characteristics. Thus, they further
highlighted that five considerations affecting the required sample size for SEM to
include multivariate normality of the data, estimation technique, model complexity,
amount of missing data, and average error variance among the reflective indicators.
98
Table 3.6 Sample Size of Previous Research
Author(s) and Year
Lassar et al. (1995)
Research Field
Sampling Method
Brand equity
Nonprobability
- Television, watches
convenience sampling
Cobb-Walgren et al.
Brand equity
Nonprobability
(1995)
- Hotels, cleansers
Yoo et al. (2000)
Brand equity
Nonprobability
- Athletic shoes, camera
Sample Size
113
Hotel – 90
Cleanser - 92
600
film, television sets
Lam & Qiu Zhang
Job satisfaction
Nonprobability
(2003)
- Fast food
Kim & Kim (2004,2005)
Brand equity- Fast-food
Nonprobability
restaurants, luxury hotel
Consumer values
Nonprobability
- Fast food
Brand equity
Systematic sampling
539
Proportional sampling
268
Purchase intention - Fast
Nonprobability
600
food, traditional restaurant
Brand equity
Nonprobability
- Chocolate, athletic shoes
Service recovery
Nonprobability
- Fast food
Brand equity
Nonprobability
- Milk, olive oil, toothpaste
judgmental sampling
Kayaman & Arasli
Brand equity
Nonprobability
(2007)
- Hotel
judgmental sampling
Norjaya et al. (2007)
Brand equity- Television,
Two-stage probability
refrigerator, air-conditioner
cluster sampling
Service quality
Nonprobability
- Fast food
Brand equity
Nonprobability quota
- consumer goods
sampling
Park (2004)
Pappu et al. (2005)
250
Fast Food - 950
Hotel - 840
279
- Car , television
Angel & Manuel (2005)
Brand equity
- Washing machine
Halim & Hamed (2005)
Esch et al. (2006)
De Run & Ting (2006)
Gil et al. (2007)
Oyewole (2007)
Buil et al. (2008)
99
400
264
360
345
501
400
UK - 417
Spain – 414
Table 3.6 Sample Size of Previous Research (Continued)
Author(s) and Year
Research Field
De Run & Kusyarnadi
Service recovery
(2008)
- Fast food
Tong & Hawley (2009)
Lin et al. (2009)
Chan (2009)
Zainuddin et al. (2009)
Sampling Method
Sample Size
Stratified sampling
264
Brand equity
Nonprobability
330
- Sports shoe
Consumer attitudes - Private
Nonprobability
brand food products
Brand perception - Mobile
Nonprobability
phone network service
Brand awareness
Nonprobability
474
500
65
Van Zyl et al. (2010)
Fast food intake
Nonprobability
341
Henry et al. (2010)
Brand equity
Nonprobability
- Casino
Norzalita & Norjaya
Brand equity
Probability cluster
(2010)
- Banking services
sampling
Ryu et al. (2010)
Consumer behavior
Nonprobability
- Fast food
Perceived service
Nonprobability
fairness - Restaurant
Self-monitoring
Experimental design
- Restaurant
with scenario
Namkung & Jang (2010)
Hu & Parsa (2011)
204
399
400
354
471
approach
Sanyal & Datta (2011)
Brand equity
Random sampling
200
Brand preferences
Nonprobability quota
600
- Intergenerational influence
sampling
Fast food consumption
Nonprobability
- Daily television viewing
Mohd Rizaimy, Abdul
Purchase Intention
Nonprobability
Sabur, et al. (2011)
- Fast food
Mohd Rizaimy et al.
Food quality attributes
Nonprobability
(2011)
- Fast food
- Generic drugs
Perez et al. (2011)
Kobayashi (2011)
100
325
120
120
To summarize, sample size could be determined by looking at the number of
constructs (Hair et al., 2010), predictors (Stevens, 1996), parameter estimates (Benter
& Chou, 1987). There were seven constructs to be examined in SEM, thus the
minimum sample size was 150, where provided the modest communalities which were
greater than 0.50 and with no under-identified (fewer than three observed variables)
constructs (Hair et al., 2010). Therefore, sample size of 600 was statistically sufficient.
3.8 Data Collection Procedures
According to Yoo et al. (2000), if respondents had known and experienced the
brand well, they would have been able to provide reliable and valid responses to the
questionnaire. Thus, respondents were selected individually or in group conveniently
from fast food restaurants that were willing to complete a self-administrated
questionnaire inside or outside these restaurants. Table 3.7 showed the sampling design
for 600 questionnaires that accomplished from the shopping complexes in the area of
Klang Valley, Malaysia. The main reason was to reduce the potential bias and increase
the precision of estimates for non-probability sampling (Chang & Chieng, 2006).
Table 3.7 Sampling Design
McD
KFC
Ph
Mb
1901
Total
Suria KLCC
25
75
100
Mid Valley Megamall
25
75
100
Berjaya Times Square Shopping Mall
25
Jusco Metro Prima Shopping Centre
25
Pavilion KL
50
Sungei Wang Plaza
75
25
Total
100
100
75
100
75
100
50
100
100
100
150
150
600
Note:
McD=McDonald’s, KFC = Kentucky Fried Chicken, Ph=Pizza Hut, Mb=Marrybrown,
1901=1901 Hot Dogs
101
The study was conducted from 1st April 2011 to 1st May 2011 as presented in
Appendix B. The schedule was planned according to the locations as agreed by the
person-in-charge of fast food brands. Table 3.8 had presented the summary of data
collection as extracted from Appendix B, which indicated the numbers of
questionnaires that collected from Monday to Sunday.
Table 3.8 Summary of Data Collection
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
McDonald’s
KFC
Pizza Hut
Marrybrown
1901 Hot Dogs
24
13
4
30
15
24
13
4
30
15
19
14
4
30
15
24
10
4
30
15
3
17
28
10
30
3
17
27
10
30
3
16
29
10
30
Total
86
86
82
83
88
87
88
Before the actual data collection, there was one briefing session that was
conducted for all survey administrators. During the briefing, the instruments items and
objectives of conducting the research were discussed. Survey administrators were given
chances to ask any unclear statements used as instruments in the questionnaire. Survey
administrators had the responsibility to explain the research objective, meaning of the
questionnaire, the words and the exact meaning to individual respondents. To avoid the
same respondents being selected more than once, the survey administrators must ask
respondents whether they had completed the survey at a prior time. If the respondents
had completed the survey before or declined to do the questionnaire, then the next
eligible respondents were selected. In the beginning of the questionnaire, a written
statement “there are no right or wrong answers; only your personal opinions matter”
was included for minimizing possible response bias (Aronson et al., 1990). All the
instrument items were assessed via the respondents’ perceptual evaluations and recall
of their experiences.
102
3.9 Method of Data Analysis
Structural Equation Modeling (SEM), a statistical methodology with a
confirmatory approach was selected to analyze multivariate data. This was because
SEM was frequently and widely used technique in psychology and social sciences
research (Bentler, 1983; Browne, 1984; Hair et al., 2010; Schumacker & Lomax, 2004).
According to Hair et al. (2010), SEM was the most appropriate and efficient estimation
technique for estimating a series of separates multiple regression equations
simultaneously, and provided evidence of systematic covariation that demonstrated
causal relationship was not spurious. Thus, SEM is often referred to as causal modeling
(Hair et al. 2010). As a result, this method is widely used among the recent study in
branding which investigated the causal effects (see Bergkvist, & Bech-Larsen, 2010;
Biedenbach, & Marell, 2010; Carroll & Ahuvia, 2006; Chang & Chieng, 2006 ; Da
9
Silva & Sharifah, 2006; Gil et al., 2007; Hess, & Story, 2005; Malär et al. 2011; Martin
& Stewart, 2001; Park et al., 2010; Thomson, MacInnis & Park, 2005; Tolba, & Hassan,
2009). Exploratory factor analysis (EFA) was not recommended to be performed as this
study had identified the numbers of composite dimensions (Hair, et al., 2010). That is,
it required the confirmation process of pre-specified observed variables in representing
a particular construct instead of data summarization. Thus, confirmatory factor analysis
(CFA) was recommended rather than EFA (Hair, et al., 2010). Firstly, CFA was
performed to identify the measurement model, which to confirm the relationship
between the observed variables and latent variables. Bentler (1983) further highlighted
that it also enabled a comprehensive assessment of construct validity, which included
convergent and discriminant validity. Secondly, the structural model was conducted to
estimate the causal relationships between the latent variables, and tested the hypotheses
in a path diagram. Byrne (2010) stated that it indicated a direct and indirect influence
between particular latent variables and other latent variables in the model. In this study,
statistical software SPSS 16.0 and AMOS 16.0 were used and the data analysis were
conducted using a three steps approach, namely descriptive analysis, assessment the fit
of measurement model and assessment the fit of structural model.
103
3.9.1 Descriptive Analysis
The sample characteristics of respondents and the observed variables were first
presented, which included mean, frequencies, percentages, and standard deviations.
3.9.2 Assessment the Fit of Measurement Model
According to Hair et al. (2010), standardized loading estimate for each of the
item should be 0.5 or higher, and ideally 0.70 to ensure validity of the constructs. In
general, there were potentially of unacceptable degree of error that might call for the
omission of an observed variable if the standardized residuals for any pair of the items
were greater than absolute value of 4.0, however, absolute value between 2.5 and 4.0
deserved for attention (Hair, et al. 2010). This would be further followed by factor
cross-loading that was based on modification indices (Byrne, 2010). Next, a
measurement of the internal consistency of the construct, construct reliability was taken
into consideration, with a minimum criterion of 0.70 (Hair et al. 2010).
A confirmatory factor analysis was conducted to measure the adequacy of the
measurement model. Gerbing and Anderson (1988) highlighted the importance of unidimensionality in the scale development process. They further argued that the
traditional exploratory analyses (e.g., item-total correlation and factor analysis) were
not theory based analysis and hence they failed to assess uni-dimensionality directly.
To overcome this limitation, confirmatory factor analysis (CFA) was employed for the
assessment of measurement model fit and uni-dimensionality (Hair, et al., 2010).
Convergent validity was determined by standardized factor loading, t value, and
average variance extracted (AVE) (Hair, et al., 2010). The cut-off value of AVE for
each of the constructs was 0.50 thresholds (Fornell & Larcker, 1981).
104
Discriminant validity was conducted to test whether the two constructs were
statistically different (Hair et al. 2010). According to Fornell and Larcker (1981),
discriminant validity was determined by the variance extracted value, whether or not it
exceeded the squared inter-construct correlations associated with that construct.
Besides, Nomological validity was tested to examine whether the correlations among
the constructs in a measurement theory made sense (Hair et. al, 2010). The overall
model fit for both measurement and structural models were evaluated using
conventional fit indices, which included Chi-Square/df ratio, Root Mean-Square Error
of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR),
Goodness of Fit (GFI), Comparative Fit Index (CFI), Normed Fix Index (NFI),
Incremental Fit Index (IFI), and Tucker-Lewis Index (TLI) (Hair et al., 2010).
3.9.3 Assessment the Fit of Structural Model
The structural model was used to estimate parameters and test hypotheses (Hair
et al., 2010). First, the specification of the structural model was conducted, followed by
the validity assessment of structural model, which included the comparison of
standardized factor loadings and construct reliability for both proposed structural and
final measurement models. Next, Goodness-of-Fit statistics and the examination of
structural model diagnostics were monitored before testing the hypotheses. The
structural relationships (causal effect) were represented by single headed straight arrows.
All the structural relationships were specified according to the established hypotheses.
Hypotheses were assessed by determining the significance level, t value, and
standardized coefficient (β), which is similarly addressed as standardized parameter
estimates. In addition to that, the unstandardized parameter estimates (b), standard error
(se) and confidence interval (CI) were highlighted to explain the 95% confidence
interval for the range of b. Models re-specification was conducted to investigate the
contribution of proposed model to the existing models of consumer-based brand equity.
For instance, the proposed model was compared with Aaker’s (1991) and Gil et al.’s
(2007) model, which included Goodness-of-fit index, structural parameter estimates,
and squared multiple correlations.
105
3.10 Relevancy of the Research Framework
In order to ensure the relevancy of the research framework to research
objectives as discussion in section 1.5, the following explanation was listed.
Figure 3.2: Relevancy of Research Framework and Research Objectives
Remarks: Research Objectives (page 15 to 17)
RO 1: To examine brand familiarity as the additional dimension of consumer-based
brand equity in the Malaysian context of fast food industry
RO 2: To examine brand trust as the additional dimension of consumer-based brand
equity in the Malaysian context of fast food industry
RO 3: To investigate the causal relationships among dimensions of consumer-based
RO 4: To develop consumer-based brand equity model in the Malaysian context of fast
food industry
106
3.11 Conclusion
A total of twelve hypotheses had been proposed in this study. The stimulated
brands were McDonald’s, KFC, Pizza Hut, Marrybrown, and 1901 Hot Dogs. This was
because this study received permission to conduct research in their restaurants.
Furthermore, the selected brands controlled approximately 80% fast food market share
in Malaysia. Basically, the format of questionnaire were categorized into two parts;
evaluation of brand equity and demographic questions. Initially, a total of forty-two
items, 6-point scale were proposed. All of the instrument items were adopted from
previous studies except brand image.
The validity of the question was determined by academicians who are expert in
branding study. There were only minor amendments, which had been recommended by
the experts, most of the suggestions were related to English proficiency and structure of
statements, such as double barrel questions. Fifty pilot surveys were collected from fast
food consumers for the validation of survey answer. The results of pilot study indicated
that a total of forty-five instrument items were proposed to be used in main study.
Nonprobability convenience sampling was suggested in this study. A total number of
600 self-administrated questionnaires were proposed to be distributed in the fast food
restaurants from different area of Klang Valley.
Structural Equation Modeling (SEM) was selected for the data analysis. There
were three steps in the approach for data analysis, namely descriptive analysis,
assessment the fit of measurement model and assessment the fit of structural model. As
a conclusion, chapter three had presented a clear picture and fundamental idea of the
research methodology, which serves as an important platform for data analysis in
chapter four.
107
CHAPTER 4
DATA ANALYSIS
4.1 Introduction
The main objective of this chapter is to present the results from the main study.
Basically, there are four distinctive parts of this chapter, descriptive analysis,
assessment the fit of measurement model, assessment the fit of structural model, and
model re-specification.
Descriptive analysis included sample descriptions such as the frequency and
percentage for respondents’ gender, ethnic group, age, occupation, income group, and
average fast food spending. Next, analyzes of constructs were conducted for each of the
observed variable. Assessments the fit of measurement model included the
investigation of Goodness-of-Fit (GOF) statistics, model identification, construct
reliability, convergent validity, discriminant validity, and nomological validity.
Assessments the fit of structural model consisted of model specification,
structural model identification, recursive model justification, model validity, GOF
statistics, model diagnostics, and finally the results of the structural parameter estimates,
referring to hypotheses testing (Hair et al, 2010). Finally, model re-specification was
examined, referring to the comparison of different concepts between the proposed
model and Aaker (1991), as well as with Gil et al. (2007).
108
4.2 Sample Descriptions
A total number of 600 questionnaires were distributed in the Malaysian
(Marrybrown and 1901 Hotdogs) and foreign (McDonald’s, KFC and Pizza Hut) fast
food brand restaurants. The study was collected from a nonprobability sample from 1st
April 2011 to 1st May 2011 in the following locations of Klang Valley:
a) Suria KLCC
b) Mid Valley Megamall
c) Berjaya Times Square Shopping Mall
d) Jusco Metro Prima Shopping Centre
e) Pavilion KL
f) Sungei Wang Plaza
After the data screening process, 15 surveys were excluded due to incomplete
responses. Thus, 585 or 97.50% of respondents were qualified and used for further
analysis. Out of the pool of completed survey forms, 49.74% were Malaysian brands
and 50.26% were foreign brands as indicated in Table 4.1. Only two Malaysian fast
food brands were selected (as discussed in Chapter 3), however, the total number of
survey forms between Malaysian and foreign brands did not notably vary, which were
291 and 294 respectively.
Table 4.1 Fast Food Brands
Fast Food Brands
Frequency
Percentage
Marrybrown (Malaysian)
144
24.62
1901 hotdogs (Malaysian)
147
25.13
KFC (Foreign)
94
16.07
McDonald’s (Foreign)
100
17.09
Pizza Hut (Foreign)
100
17.09
109
4.2.1 The Respondents’ Background
As shown in the Table 4.2, the respondents of this study were 50.43% male and
49.57% female, which were almost equally distributed. With respect to ethnic group,
63.09% were Malays, followed by Chinese (26.15%), Indian (4.96%), and others
(5.80%). The breakdown of the sample in term of gender and ethnic group were
considered representative of the population of Malaysia (Index mundi, 2011; U.S. State
Department, 2010). Even though the conceptual model of this study was derived by
theoretical generalizability, and not population generalizability, but it served as
additional credit for this study, for instance to reduce the possibility of selection bias,
which produced conducive to statistical analysis in representing the true picture of the
population in Malaysia.
Table 4.2 Respondents’ Gender
Gender
Frequency
Percentage
Male
295
50.43
Female
290
49.57
Table 4.3 Respondents’ Ethnic Group
Ethnic Group
Frequency
Percentage
Malay
369
63.09
Chinese
153
26.15
Indian
29
4.96
Others
34
5.80
In this study, some of the descriptions were not completed as the respondents
did not signify the information. Thus, they were indicated as missing data and were not
reported as part of the percentage (Example: Table 4.4 to Table 4.7).
110
The sample comprised of a high proportion of respondents above 20 years old
(78.94%), with a total number of 461. However, further analysis indicated that age 35
and below dominated 82.36% of the survey, the main reason for the high proposition in
the sample was probably due to high numbers of Malaysian fast food consumers are
from this range. 334 were come from workforce, such as entrepreneur, manager,
researcher, engineer, clerk, executive, teachers, technician, chef, designer, consultant,
accountant, banker, promoter, lawyer, doctor, artist, designer, webmaster, freelance or
social worker and so on.
On the other hand, there were 154 students, 5 housewives and 1 retired. This
could be further explained that most of the fast food breakfast and lunch promotions
nowadays were targeted on workforce and students market. Referring to Table 4.5, it
was hardly to obtain retired person and housewife from the sample; obviously, they
were not the core target groups for fast food entrepreneurs. Furthermore, the target
market of fast food business no longer focused on children and adolescence, they were
moving to other consumer segmentation such as college students and workforces.
Table 4.4 Respondents’ Age Group
Age Group
Frequency
Percentage
20 years old or less
123
21.06
21- 25 years old
162
27.74
26 – 30 years old
106
18.15
31 – 35 years old
90
15.41
36 – 40 years old
59
10.10
Above 40 years old
44
7.54
* Note: 1missing data
111
Table 4.5 Respondents’ Occupation
Occupation
Frequency
Percentage
154
31.17
Housewife
5
1.01
Own Business
12
2.43
Retired
1
0.20
106
21.46
124
25.10
79
16.00
13
2.63
Student
Professional/Managerial Position
Executive/Technician/Supervisor/Planner/
Teacher
Clerk/Junior Officer/Driver/Security/Promoter
Artist/Designer/Webmaster/Freelance/
Social Worker
* Note: 91missing data
Table 4.6 Respondents’ Income Group
Income Group
Frequency
Percentage
Below RM 1,500
205
37.89
RM 1,500 - RM 2,499
106
19.59
RM 2,500 - RM 3,499
98
18.11
RM 3,500 - RM 4,499
59
10.91
RM 4,500 - RM 5,999
27
5.00
Above RM 6,000
46
8.50
* Note: 44 missing data
In terms of monthly income of the respondents, 37.89% and 19.59% of the
respondents were in the income category of below RM 1,500 and RM 1,500 to RM
2,499 respectively. Surprisingly, in Malaysia, the level of income did not closely relate
to the profession. This was supported by where 4 managers’ income was below RM
1,500, 7 managers, 3 teachers/lecturers, and 3 consultants’ income were in the range
between RM 1,500 to RM 2,499.
112
Besides, there were 12 managers, 5 engineers, 7 teachers/lecturers, 5
consultants, 7 accountants, and 4 bankers earned within RM 2,500 to RM 3,499.
Consequently, only 24.41% of the respondents’ income did exceed the threshold of RM
3,500 even though there was high percentage of workforce samples (67.62%) as
indicated in Table 4.5. In addition to that, cross tabulation analysis indicated only 46
out of 132 respondents who earn higher than RM 3,500 (i.e., above 35 years old). On
the other hand, there were 51 respondents had monthly income less than RM 3,500
with above 35 years old. Thus, there was no strong evidence to support such findings
due to the predominantly younger aged respondents who were still in the early stage of
their career path.
Table 4.7 Respondents’ Average Fast Food Spending Group
Average Fast Food Spending Group
Frequency
Percentage
Below RM 10
27
5.30
RM 10 - RM 19.90
185
36.27
RM 20 - RM 29.90
122
23.92
RM 30 - RM 39.90
55
10.78
RM 40 - RM 49.90
10
1.96
RM 50 - RM 59.90
59
11.57
Above RM 60
52
10.20
* Note: 75 missing data
Turning to Table 4.7, more than 40% of respondents agreed that they had spent
less than RM 20.00 on average visit in fast food restaurants. The result had
corresponded to the price setting of fast food brands; McDonald’s, Marrybrown, and
1901 Hot Dogs were considered the most affordable among students and young adults
as the set meals were below RM20.00. Alternatively, Pizza Hut was showed as the
highest price among other fast food brands, this was because most of the Malaysia
consumers would visit Pizza Hut outlets with their family members or friends instead
113
of individual. Furthermore, Pizza Hut was apprehended where customers were charged
10% extra as service charge for dine-ins, which inflated the final price.
4.2.2 Descriptive Analysis of the Variables
This section focused on the descriptive analysis of all the variables in this study.
As illustrated in the research framework, the exogenous variables were perceived
quality and brand awareness; endogenous variables were brand familiarity, brand
image, brand trust, attitudinal brand loyalty, and brand equity. Firstly, the overall
constructs were identified. Next, the analysis for each of the variables was specified
into observed variables.
Table 4.8 Descriptive Analysis (Constructs)
Mean
Standard
Deviation
Brand awareness
4.42
1.10
Perceived quality
4.35
0.85
Brand image
4.43
0.80
Brand familiarity
4.42
1.09
Brand trust
4.30
1.07
4.00
1.11
Brand equity
3.95
1.20
Scale Items of Overall Constructs
All the observed variables were measured by a 6-point scale ranging from 1
(strongly disagree) to 6 (strongly agree). Thus, cut-off point of 3.5 [(3+4)/2] was
assigned to indicated the difference between disagree and agree opinions for each of
statements (Hishamuddin, 2007). The average score for each of the constructs were
presented in Table 4.8. The highest mean score was brand image (4.43), which was
slightly above brand awareness (4.42) and brand familiarity (4.42). The lowest
constructs were brand equity and attitudinal brand loyalty, 3.95 and 4.00 respectively.
114
The result advocated the logicality of brand equity theory; both brand equity
and attitudinal brand loyalty were more complicated to be achieved as compared to
brand image, brand awareness and brand familiarity (Aaker, 1991). Thus, brand equity
and attitudinal brand loyalty were expected to have lower scores.
Table 4.9 Descriptive Analysis (Brand Awareness)
Scale Items of Brand Awareness
Mean
Standard
Deviation
BA1
I am aware of X.
4.72
1.22
BA2
4.60
1.20
BA3
4.32
1.36
BA4
When I think about [fast food category], X is the first
brand that comes to my mind.
4.06
1.56
Table 4.9 listed the observed variables of brand awareness. The item with the
highest score was BA1 “I am aware of X” with the mean score of 4.72. From
statements BA1 to BA3, which indicated the level of recognition and exposure towards
the fast food brands, BA4 “When I think about [fast food category], X is the first brand
that comes to my mind” was related to the consumers’ top-of-mind for a particular
product category (Aaker, 1996). In other words, top-of mind was referred to the first
brand that automatically appeared on our mind while mentioning a product category,
such as hamburger for McDonald’s.
Nevertheless, there were varieties of brands available in Malaysian fast food
industry nowadays. For example fried chicken for KFC, Marrybrown, pizza for Pizza
Hut and Domino Pizza, hot dogs for 1901 Hot Dogs and AMW, hamburger for
McDonald’s and Burger King. Furthermore, most of the fast food brands in Malaysian
had extended their brand identify to other product category such as Ayam Goreng
McDTM, Nasi Marrybrown, O.R. Chicken Chop and so on. Thus, the brand itself no
longer represented a single product category; it might cover multiplicity of
identification.
115
As a result, the mean score for BA4 would be the lowest (4.06) as compared to
other observed variables. Furthermore, the standard deviation was 1.56, the highest
among other items, which showed that BA4 was the highest variation among other
items and data were spread out over a large range of value as measured up to the mean
score.
Table 4.10 Descriptive Analysis (Perceived Quality)
Scale Items of Perceived Quality
Mean
Standard
Deviation
PQ1
The staff of X gives customers individual attention.
4.21
1.15
PQ2
4.52
1.05
4.42
1.06
4.15
1.09
PQ5
The staff of X are well-dressed, clean, and neat.
The staff of X provides its prompt services at
promised times.
The staff of X handles complaints of customers
effectively.
The staff of X are always willing to help customers.
4.32
1.07
PQ6
The staff of X are knowledgeable.
4.25
1.07
PQ7
The staff of X are confident.
X has operating hours convenient to all of its
customers.
4.26
1.08
4.54
1.01
4.47
1.06
4.22
1.08
4.46
1.05
PQ3
PQ4
PQ8
PQ9
PQ10 X insists on error-free service.
PQ11
The physical facilities of X are visually appealing
(e.g. dining areas decorations, building).
The highest mean score was PQ8 (4.54) “X has operating hours convenient to
all of its customers”, followed by PQ2 (4.52) “The staff of X are well-dressed, clean,
and neat”. The result explained that the selected brands had provided satisfactory
services to their customers. The lowest mean score was PQ4 (4.15), which was related
to customer’s complaints. Therefore, fast food managers should put more effort in
handling customer feedback or complaint efficiently, for instance immediate
replacement for complaints, cash refund for wrong order, verbal apologize statements
and so on.
116
Table 4.11 Descriptive Analysis (Brand Image)
Scale Items of Brand Image
Mean
Standard
Deviation
BI1
Delicious
4.63
1.01
BI2
Easy
4.73
0.97
BI3
Prompt service
4.55
0.97
BI4
Good dining environment
4.47
1.07
BI5
Pleasant
4.47
1.01
BI6
Free WiFi
4.23
1.33
BI7
4.39
1.09
BI8
A place for social gathering
4.32
1.18
BI9
Variety of choices
4.32
1.12
BI10 Good value for money
4.35
1.16
BI11 Convenient
4.54
1.04
BI12 Widely distributed
4.31
1.10
BI13 Long history
4.26
1.13
Brand image was measured by 13 items as reported in Table 4.11. The question
was illustrated as “To what extent do you agree the following characteristics are
descriptive of X?” which was adopted from Park (2009). The higher average scores
were BI2 (4.73) “Easy”, followed by BI1 (4.63) “Delicious” and BI3 (4.55) “Prompt
service”. Brand image was defined as overall image that was formed from the result of
both cognitive and affection images towards fast food brand. Thus, it could be referred
to as usage imagery (Keller, 1993), emotional benefit and self-expressive benefit
(Aaker, 1996). For instance, “Pleasant” was the positive feeling that linked to brand
while “Easy” was a symbol of a person’s self-concept that was derived from brands.
117
Alternatively, BI6 “Free WiFi” scored the lowest mean, 4.23. This result
indicated that the functional benefits such as Free WiFi, was not perceived as an
essential criteria for the creation of brand image when evaluated for emotional or selfexpressive benefit.
Table 4.12 Descriptive Analysis (Brand Familiarity)
Scale Items of Brand Familiarity
Mean
Standard
Deviation
BF1
4.56
1.21
BF2
4.44
1.34
BF3
4.14
1.25
BF4
I can easily recognize X.
4.53
1.20
Table 4.12 described the scale items of brand familiarity, BF1 “I am familiar
with X” scored 4.56, indicated the highest among the 4 observed variables. The lowest
value was 4.14, which was BF3: “I am knowledgeable of X”. Remarkably, the standard
deviation for BF2 “I have been to X multiple times” was obviously greater than other
items, 1.34, which showed that BF2 was high variability.
Table 4.13 Descriptive Analysis (Brand Trust)
Scale Items of Brand Trust
Mean
Standard
Deviation
BT1
X is safe to me.
4.37
1.18
BT2
X is reliable to me.
4.36
1.14
BT3
I trust X.
4.36
1.15
BT4
X is dependable to me.
4.12
1.23
118
There were high consistency of measurements items (BT1, BT2, and BT3) for
brand trust as indicated in Table 4.13, mean values were 4.37, 4.36, and 4.36
respectively. In the same vein, BT4 “X is dependable to me” did not show consistent
values for both mean and standard deviation as compared to others. However, the result
concluded that most of the consumers consistently ranked the trust level across selected
brands. In other words, consumers relied on established fast food brands due to the
nature in operations.
Table 4.14 Descriptive Analysis (Attitudinal Brand Loyalty)
Mean
Standard
Deviation
ABL1 If I had to do it over again, I would choose X.
4.18
1.17
ABL2 I try to visit X because it is the best choice for me.
4.03
1.18
ABL3 I consider myself to be a loyal customer of X.
3.89
1.27
ABL4 X is special to me.
3.85
1.27
ABL5 I would love to recommend X to my friends.
4.08
1.25
Scale Items of Attitudinal Brand Loyalty
The highest value of observed variables was 4.18, ABL1: “If I had to do it over
again, I would choose X”. The value of ABL1 was the highest as the statement request
a lower level of brand commitment as compared to other items. However, higher level
of brand commitment that related to best choice, loyal customer, special and
recommendations to others (ABL2 to ABL5) were proven to have lower mean scores.
119
Table 4.15 Descriptive Analysis (Brand Equity)
Scale Items of Brand Equity
BE1
BE2
It makes sense to visit X instead of any other brand,
even if they are the same.
Even if there is another [fast food category] brand as
delicious as X, I still prefer X.
Mean
Standard
Deviation
3.97
1.24
3.87
1.32
BE3
X is definitely my choice in [fast food category].
3.99
1.31
BE4
Even if another [fast food category] brand has the
same price as X, I would still buy X.
3.96
1.37
Table 4.15 stated that mean scores for scale items of brand equity were
consistent and above the cut-off value of 3.50 (BE1:3.97, BE2:3.89, BE3:3.99,
BE4:3.96), which indicated positive evaluation of brand equity existed in the sample
size. Yet, only BE2, BE3, and BE4 indicated the overall assessment of brand equity on
a particular food category.
4.3 Normality
According to Bagozzi and Yi (1988), the first things that should be performed
for the assessment of structural model were to ensure that all the data input were
normally distributed and the statistical assumption was identified. The estimation of
SEM parameters required continuous data with normal distribution (Hair et al, 2010).
According to Tong (2006), skewness and kurtosis could be used to determine the test
for normality. A common rule-of-thumb for normal distribution data was the observed
variables should be ranged within absolute value of 2 (Tong, 2006). The normality
analysis for 45 observed variables were conducted by AMOS 16.0. The results
indicated that the values of skewness and kurtosis of all the observed variables were
within absolute value of 2 (see Table 4.16). This means that they were normally
distributed.
120
Table 4.16 Skewness and Kurtosis of Observed Variables
Constructs
Observed Variable
Brand awareness
BA1
BA2
BA3
BA4
BF1
BF2
BF3
BF4
PQ1
PQ2
PQ3
PQ4
PQ5
PQ6
PQ7
PQ8
PQ9
PQ10
PQ11
BI1
BI2
BI3
BI4
BI5
BI6
BI7
BI8
BI9
BI10
BI11
BI12
BI13
Brand familiarity
Perceived quality
Brand image
121
Skewness
Kurtosis
-0.73
-0.57
-0.43
-0.30
-0.61
-0.64
-0.40
-0.69
-0.49
-0.61
-0.69
-0.30
-0.46
-0.37
-0.47
-0.41
-0.62
-0.42
-0.26
-0.44
-0.70
-0.46
-0.65
-0.47
-0.67
-0.51
-0.59
-0.54
-0.65
-0.45
-0.32
-0.33
-0.07
-0.22
-0.67
-1.03
-0.15
-0.13
-0.19
0.17
0.05
0.47
0.67
-0.11
0.19
0.05
0.14
-0.11
0.52
0.27
-0.55
-0.12
0.60
0.26
0.61
0.27
0.00
0.08
0.01
0.24
0.30
0.08
-0.39
-0.14
Table 4.16 Skewness and Kurtosis of Observed Variables (Continued)
Constructs
Observed Variable
Brand trust
BT1
BT2
BT3
BT4
ABL1
ABL2
ABL3
ABL4
ABL5
BE1
BE2
BE3
BE4
Brand equity
Skewness
Kurtosis
-0.63
-0.60
-0.60
-0.56
-0.43
-0.40
-0.31
-0.29
-0.48
-0.53
-0.41
-0.40
-0.37
0.31
0.52
0.43
0.22
-0.07
-0.16
-0.19
-0.27
-0.06
0.07
-0.29
-0.29
-0.34
4.4 Structural Equation Modeling (SEM)
SEM technique was employed to test the proposed model fit. The proposed
model consisted of five endogenous constructs (brand familiarity, brand image, brand
trust, attitudinal brand loyalty, and brand equity) and two exogenous constructs (brand
awareness and perceived quality).
In SEM, researchers reached a consensus that “validity is the most important
concept in measurement” (Patterson 2000, p. 17). The measurement scale was first
tested for reliability and validity, and then only followed by assessment on structural
model for hypotheses testing (Hair et al, 2010). To test the validity of measurement
model, confirmatory factor analysis (CFA) was employed to assess, develop, and
modify the proposed model.
122
4.5 Confirmatory Factor Analysis (CFA)
CFA was conducted by using a correlation matrix for all the constructs, it
served as a purpose to investigate the items of each construct more strictly (Hair et al,
2010). In particular, it was used to provide evidence for the underlying construct to be
represented by a set of unique observed variables (Anderson & Gerbing, 1988).
Gerbing and Anderson (1988) highlighted the importance of uni-dimensionality
in the scale development process. They further argued that the traditional exploratory
analyses were not theory based analysis and hence they failed to assess unidimensionality directly. To overcome this limitation, confirmatory factor analysis
(CFA) was employed for the assessment of measurement model fit and unidimensionality (Hair et al, 2010).
This study had identified the number of observed variables (factors) that could
be loaded for each of the constructs (latent variables). CFA was performed before the
result for the interpretation of dimensionality was determined (Hair et al, 2010). As a
result, it provided a more rigorous test for the measurement theory; this was because
the assessment of measurement model was performed by a numbers of constructs
(latent variables), which were derived from different groups of observed variables that
was not directly measured (Hair et al., 2010).
The assessment of measurement model served as an important step in providing
confirmatory assessment for convergent and discriminant validity (Anderson &
Gerbing, 1988). Both convergent and discriminant validity had to be satisfied before it
could be transformed to structural model (Hair et al, 2010). Therefore, a good
measurement model was considered as a foundation for the estimation of structural
model (Hair et al, 2010). The following section covers important discussions relating to
CFA which includes the assessment of measurement model and structural model
validity.
123
1
e4 1
e3 1
e2 1
e1
BA4
BA3
BA2
BA1
1
Brand Awareness
BF4
BF3
BF2
BF1
1
Brand Familiarity
1
e8 1
e7 1
e6 1
e5
1
e191
e181
e171
e161
e151
e141
e131
e121
e111
e101
e9
PQ11
PQ10
PQ9
PQ8
PQ7
PQ6
PQ5
PQ4
PQ3
PQ2
PQ1
e321
e311
e301
e291
e281
e271
e261
e251
e241
e231
e221
e211
e20
BI13
BI12
BI11
BI10
BI9
BI8
BI7
BI6
BI5
BI4
BI3
BI2
BI1
1
Perceived Quality
1
Brand Image
1
1
e361
e351
e341
e33
BT4
BT3
BT2
BT1
1
ABL5
ABL4
ABL3
ABL2
ABL1
1
BE4
BE3
BE2
BE1
1
Brand Trust
1
e411
e401
e391
e381
e37
A. Brand Loyalty
1
e451
e441
e431
e42
Brand Equity
Figure 4.1 Initial Measurement Model (CFA 1)
124
4.5.1 Assessment of Fit and Uni-dimensionality of the Measurement Model
The initial measurement model had incorporated seven latent variables, which
was indicated by respective items pertaining to each scale: brand awareness, brand
familiarity, perceived quality, brand image, brand trust, attitudinal brand loyalty, and
brand equity. The details of the goodness-of-fit measures for the measurement models
(CFA 1 to CFA 21) are presented in Table 4.17.
Concerning construct validity criteria, observed variables with standardized
loading lower than 0.70 were removed to make certain of the ideal results (Hair et al.,
2010). Specifically, BI6, BA4, PQ11, PQ8, BI12, BI13, BI8, and PQ9 were gradually
eliminated, which had led to the modification of measurement models from CFA 1 to
CFA 9. Next, any pair items of standardized residuals (SD) with greater than l4.0l were
removed, as well as those pair items between l2.5l and l4.0l was given attention (Hair et
al. 2010). CFA 9 did not present in any pairs observed variables of SD that higher than
absolute value of 4.0, however, PQ10 was found to have significant pair numbers of
SD between l2.5l and l4.0l with other observed variables (BI7 = SD 3.854, BE1 = SD
3.092, BL4 = SD 3.229, BT4 = SD 3.690, BT3 = SD 2.696). Thus, PQ10 was
confiscated and guided to CFA 10.
Byrne (2010) stated that observed variables on a measuring instrument should
clearly target only one of its underlying constructs, hence cross-loading incurred if an
observed variable had two more factor loadings exceeding the threshold value (Hair et
al, 2010). The measurement models (CFA 11 to CFA 21) indicated that BE1, BI7, BF2,
BT4, PQ7, BI1, BI2, ABL1, PQ6, PQ2, and BI11 were progressively eradicated based
on modification indices (MIs) as provided in AMOS 16. The final modified model
(CFA 21) is shown in Figure 4.2.
125
Table 4.17 Goodness-of-fit Results for the Measurement Models
Model
χ²
χ²/df
RMSEA SRMR
GFI
CFI
NFI
IFI
TLI
Action
CFA 1
4,199.790 4.545
0.078
0.065 0.738 0.859
0.826
0.859
0.849
CFA 2
4,036.282 4.581
0.078
0.064 0.745 0.862
0.831
0.863
0.852
Deleted BI6
CFA 3
3,781.380 4.507
0.077
0.061 0.753 0.869
0.838
0.869
0.859
Deleted BA4
CFA 4
3,627.216 4.545
0.078
0.061 0.757 0.872
0.842
0.872
0.861
Deleted PQ11
CFA 5
3,436.309 4.533
0.078
0.060 0.767 0.876
0.847
0.876
0.866
Deleted PQ8
CFA 6
3,125.070 4.346
0.076
0.059 0.779 0.885
0.857
0.886
0.876
Deleted BI12
CFA 7
2,984.093 4.382
0.076
0.058 0.783 0.888
0.860
0.889
0.878
Deleted BI13
CFA 8
2,785.494 4.325
0.075
0.058 0.791 0.894
0.867
0.894
0.884
Deleted BI8
CFA 9
2,604.816 4.284
0.075
0.054 0.800 0.898
0.872
0.899
0.889
Deleted PQ9
CFA 10 2,514.691 4.389
0.076
0.053 0.801 0.899
0.873
0.899
0.889
Deleted PQ10
CFA 11 2,293.898 4.256
0.075
0.051 0.808 0.904
0.879
0.905
0.894
Deleted BE1
CFA 12 2,128.374 4.206
0.074
0.049 0.816 0.909
0.884
0.909
0.899
Deleted BI7
CFA 13 2,014.189 4.249
0.075
0.047 0.819 0.910
0.886
0.910 0.900
Deleted BF2
CFA 14 1,885.109 4.255
0.075
0.045 0.825 0.913
0.889
0.913
0.902
Deleted BT4
CFA 15 1,745.952 4.227
0.074
0.044 0.833 0.916
0.893
0.916
0.906
Deleted PQ7
CFA 16 1,590.951 4.143
0.073
0.042 0.845 0.921
0.899
0.921
0.911
Deleted BI1
CFA 17 1,418.878 3.986
0.072
0.040 0.856 0.928
0.906
0.928
0.918
Deleted BI2
CFA 18 1,209.081 3.675
0.068
0.039 0.871 0.937
0.915
0.937
0.927
Deleted ABL1
CFA 19 1,094.171 3.611
0.067
0.037 0.879 0.941
0.920
0.941
0.931
Deleted PQ6
CFA 20 953.917
3.431
0.065
0.037 0.887 0.947
0.927
0.947
0.938
Deleted PQ2
CFA 21 859.593
3.384
0.064
0.037 0.893 0.950
0.931
0.951
0.942
Deleted BI11
Note: CFA 1 to CFA 9 (Modified as standardized loading estimate < 0.7), CFA 10 (Modified as standardized residuals between l2.5l
and l4.0l, CFA 11 to CFA 21 (Modified as factor cross-loadings)
126
1
e3 1
e2 1
e1
BA3
BA2
BA1
1
Brand Awareness
BF4
BF3
BF1
1
Brand Familiarity
e131
PQ5
e12 1 PQ4
e111
PQ3
e9
PQ1
1
Perceived Quality
1
e8 1
e7 1
e5
1
1
e29 1 BI10
e28 1
BI9
e241
BI5
e231
BI4
e22
BI3
1
Brand Image
1
e351
e341
e33
BT3
BT2
BT1
1
Brand Trust
ABL5
ABL4
ABL3
ABL2
1
A. Brand Loyalty
1
e411
e401
e391
e38
1
e451
e441
e43
BE4
BE3
BE2
1
Brand Equity
Figure 4.2 Final Measurement Model (CFA 21)
127
4.5.2 Goodness-of-Fit Statistics for Measurement Model
The initial measurement model (CFA 1) did not indicate an adequate model fit
for the data in the basic of fit statistics (χ² = 4,199.790, χ²/df = 4.545, RMSEA = 0.078,
SRMR = 0.065, GFI = 0.738, CFI = 0.859, NFI = 0.826, IFI = 0.859, TLI = 0.849,
PCLOSE = 0.001), and the p-value associated with chi-square was 0.001. According to
Hair et al. (2010), the significant p-value did not indicate that the observed covariance
matrix matched the estimated covariance matrix in the empirical data. Therefore, other
goodness-of-fit indices were examined closely given the sensitivity of chi-square
statistical test to sample size (Byrne 2010). After the items purification process, final
measurement models (CFA 21) consisted of 25 observed variables (see Figure 4.2), the
number of observations (N) were 585. Referring to Hair et al.’s (2010) characteristics
of different fit indices demonstrating Goodness-of-Fit across different model situation,
all fit statistic values proved adequate and obtained values above the recommended
value; indicated measurement models had demonstrated perfect results for the degree
of uni-dimensionality (χ² = 859.593, χ²/df = 3.384, RMSEA = 0.064, SRMR = 0.037,
GFI = 0.893, CFI = 0.950, NFI = 0.931, IFI = 0.951, TLI = 0.942, PCLOSE = 0.06),
and the p-value associated with chi-square was 0.001.
4.5.3 Root Mean Square Error of Approximation (RMSEA)
In general, there were three reasons for the use of RMSEA. Firstly, model
misspecification could be detected as RMSEA emerged to be sufficiently sensitive (Hu
& Bentler, 1998). Secondly, RMSEA emerged to become one of the widely used
interpretative guideline in determining the quality of assessment model (Hu & Bentler,
1998, 1999). Thirdly, the confidence intervals level could be derived from RMSEA
(Byrne, 2010). According to Browne and Cudeck (1993), a value below 0.05 was
considered good fit, and value below 0.08 was considered reasonable for the errors of
approximation in the population.
128
Nevertheless, the cut-off value of RMSEA (neither 0.05 nor 0.08) could not be
confidently concluded that there were absolutely no errors of approximation in the
population for the model. In some cases, the value of RMSEA could be small (e.g.
0.04), however the confidence interval was widely ranged (0.02 to 0.10). In this case,
the estimation discrepancy value was considered not precise. In order to determine the
RMSEA value reflected a model fit in the population, the confidence interval should be
narrowly ranged (MacCallum, Browne & Sugawara, 1996). In AMOS software, we
could test whether the RMSEA was “good” in the population by indicating value of
closeness of fit (PCLOSE) to be greater than 0.05 (Jöreskog & Sörbom, 1996b).
The RMSEA value for CFA 21 model was 0.064, with the 90% confidence
interval ranging from 0.059 to 0.069 and the PCLOSE value of 0.06, with 90%
confident that the true RMSEA value had ranged within the bounds of 0.059 to 0.069,
which showed reasonable goodness-of-fit and good degree of precision (Byrne, 2010).
This could be further explained with a) The RMSEA point estimate was lesser than
0.08 (0.064), b) The upper bound of RMSEA was 0.069, which indicated the highest
value was less than the 0.08 value as suggested Browne and Cudeck, (1993), and c)
The PCLOSE value was greater than 0.05 (p = 0.06). As a result, CFA 21 was
concluded as a model which fits data well.
4.5.4 Standardized Root Mean Square Residual (SRMR)
Specifically, root mean square residual (RMR) was used to identify the value of
average residual, which was another descriptive model fit statistic (Byrne, 2010). On
the other hand, the standardized RMR (SRMR) represented the average value across all
standardized residuals, and the value should be lesser than 0.05 to indicate as a wellfitting model (Bryne, 2010). In this study, RMR value was 0.051 and the SRMR value
of CFA 21 was 0.037, which represented that there was an average discrepancy or error
of 0.037 between the samples observed and hypothesized correlation matrices (Bryne,
2010).
129
4.5.5 Goodness-of-Fit Index (GFI)
GFI could be classified as an absolute index of fit because it basically compared
the proposed model with no model at all (Hu & Bentler, 1995). According to Hair et al.
(2010), GFI value of greater than 0.90 typically were considered as good. Besides,
Jöreskog and Sörbom (1993) highlighted that, theoretically, it was possible for GFI to
be negative; Fan, Thompson and Wang (1999) further cautioned that GFI value could
be overly influenced by sample size. This, of course, should not occur as it would
reflect the fact that the model fits worse than no model at all (Byrne, 2010). The value
of GFI was reported as 0.893, slightly below recommended value. Thus, the current
study concluded that the final measurement model (CFA 21) fitted the sample data
fairly well.
4.5.6 Comparative Fit Index (CFI)
The value for CFI was ranged from 0 to 1, which was derived form the
comparison of the proposed model against the standard model (Bryne, 2010). Standard
model was referred to a baseline model; sometime it was addressed as an independence
(or null) model (Bryne, 2010). There were different cutoff values for CFI to represent a
well-fitting model as some researchers identified that it should be greater than 0.90
(Bentler, 1992) or 0.95 (Hu & Bentler, 1999). Recently, Hair et al. (2010) suggested a
range of cutoff value (0.95, 0.92 or 0.90), which was determined by the number of
observed variables and sample size. Referring to CFA 21, there were 25 observed
variables and 585 number observations. Therefore, the cutoff value of 0.92 was
considered adequate (Hair et al., 2010). Table 4.17 presents the proposed model which
is well fitted, sufficiently described by the sample data (CFI: 0.950). On the other hand,
the Normed Fit Index (NFI) value had also indicated that the proposed model was only
marginally fitted (0.931). However, some researchers suggested choosing CFI value as
model fit indicator, this was because CFI did not encounter a problem for estimating fit
in small samples (Bentler, 1990; Byrne, 2010).
130
4.5.7 Incremental Fit Index (IFI)
IFI had the similar computation with Normed Fit Index (NFI). However, it
excluded the consideration of taking account into degrees of freedom (Bollen, 1989). It
was used to determine the issues of parsimony and sample size of the proposed model.
According to Hu and Bentler (1999), the cutoff value of 0.95 was considered good.
Referring to Table 4.17, it was not surprising that the value of IFI (0.951) was close to
the CFI value, which reflected the proposed model as a well-fitted model.
4.5.8 Tucker-Lewis Index (TLI)
TLI was theoretically identical to the NFI, but it varied in that it was actually a
comparison of the normed chi-square values for the null and specified model, which to
some degree took into account model complexity (Bryne, 2010). Consistent with other
indices, TLI yields values ranging from 0 to 1 (Byrne, 2010). According to Hair et al.
(2010), model with a higher value suggested a better fit than a model with lower value.
As shown in Table 4.17 (TLI = 0.942), CFA 21 was considered as a good fit model as
it was just slightly below cutoff value of 0.95 (Hu & Bentler, 1999).
4.5.9 Measurement Model Identification
According to Hair et al. (2010), an additional requirement for SEM was
identification, which was referred to the idea whether enough information existed to
identify a solution to a set of structural equations. In other words, there was at least one
unique distinct sample moments for each parameter to be estimated in the SEM model
(Hair et al., 2010). In SEM model, one parameter could be estimated for each unique
variance and covariance in the observed covariance matrix. Thus, the covariance matrix
provided the degree of freedom used to estimate parameters just as the number of
respondents provided degree of freedom in regression (Hair et al., 2010).
131
Even though more items did produce higher reliability estimates and
generalizability (Bacon, Sauer & Young, 1995), more items also required larger sample
sizes, thus making it difficult to produce truly uni-dimensional factors. According to
Hair et al. (2010), models and even constructs could be characterized by their degree of
identification, which was defined by the degree of freedom of a model after all the
parameters to be estimated were specified. There were three levels of identification
models, namely under-identified model, just-identified model, and over-identified
model (Hair et al., 2010). Over-identified models had more unique covariance and
variance terms than parameters to be estimated, which could be identified with a
positive degree of freedom and a corresponding chi-square of goodness-of-fit value
(Hair et al., 2010).
Table 4.18 Summary of Initial Measurement Model (CFA 1) Parameters
Weights Covariance
Variances
Means
0
0
0
52
0
0
0
Labeled
Number of
distinct
38
21
52
parameters to
be estimated
90
21
52
Total
Note. Number of distinct sample moments = 1035
Degrees of freedom (1035 – 111) = 924
0
0
0
0
0
111
0
0
163
Fixed
52
0
Intercepts Total
Referring to Table 4.18 and Table 4.19, the sample covariance matrix
comprised of a total of CFA 1 = 1,035 / CFA 21 = 325 pieces of information (or
number of distinct sample moments) respectively. Of the CFA 1 = 163 / CFA 21 = 103
total parameters in the measurement models, only CFA 1 = 111 / CFA 21 = 71 were to
be freely estimated; all other CFA 1 = 52 / CFA 21 = 32 had fixed parameters in the
models (i.e., they were constrained to equal 1 value). As a consequence, the initial
(CFA 1) and final (CFA 21) measurement models were over-identified with 924 and
254 degree of freedom respectively.
132
Table 4.19 Summary of Final Measurement Model (CFA 21) Parameters
Weights
Covariance
Variances
Means
Intercepts Total
Fixed
32
0
0
0
0
32
Labeled
0
0
0
0
0
0
Number of
distinct
parameters to
be estimated
18
21
32
0
0
71
50
21
32
Total
Degrees of freedom (325 – 71) = 254
0
0
103
4.5.10 Construct Reliability
Table 4.20 Results of Construct Reliability
Brand equity dimensions
Construct Reliability
0.86
0.86
0.90
0.87
0.94
0.93
0.94
Brand awareness
Brand familiarity
Perceived quality
Brand image
Brand trust
Brand equity
According to Hair et al. (2010), reliability was used to measure the internal
consistency of the construct (latent variable). It highlighted the degree of unobserved
factor in the construct. In SEM, construct reliability (CR) had to be tested prior to
construct validity, however, CR was one of the indicators for convergent validity (Hair
et al., 2010), and the formula as presented in next page.
133
{Σ(SLi)} ²
-------------------------{Σ(SLi)} ² + {Σ(ei)}
Σ
= Sum
SLi
= Factor loading
ei
= Error variance terms for a construct
The most commonly used threshold for CR measures was 0.70 or higher
(Nunnally, 1978), which indicated the existence of internal consistency, in other words;
the observed variables had consistently measured the same latent variable (Hair et al.,
2010). Referring to Table 4.20, the CR values had ranged from 0.86 to 0.94,
enormously above the cutoff value of 0.70, which indicated high internal consistency
for all the constructs in this study.
4.5.11 Construct Validity
Establishing construct validity of the measurement model was essential in
confirming the accuracy of measurement (Hair et al., 2010). Construct validity assessed
the degree to which a scale or a set of measured items actually represented the
theoretical latent variable in the model (Hair et al., 2010). Therefore, it dealt with the
accuracy of measurement which provided the assurance to the observed items of the
survey reflected the real score that existed in the population (Hair et al., 2010).
The present study adopted Hair et al.’s (2010) measurement validation
procedures to test construct validity. Prior to structural model testing, the construct
validity was tested by checking the convergent validity, discriminant validity, and
nomological validity (Hair et al., 2010). The whole process of scale validation was
delineated in the following sub-sections.
134
4.5.12 Convergent Validity
According to Kline (2005), measurement model presented the relationships
between the observed variables with the unobserved constructs (latent variables).
Therefore, convergent validity was employed in investigating to what extent that the
observed variables could converge or share a high proportion of variance within the
unobserved constructs (Hair et al., 2010). The convergent validity was assessed by
checking the loading of each observed indicator on their underlying unobserved
constructs (Anderson & Gerbing 1988). Table 4.20 presented three indicators for
convergent validity, which included standardized factor loading, average variance
extracted and construct reliability (Hair et al., 2010).
4.5.13 Standardized Factor Loadings
Table 4.21 presented standardized factor loading, t value as well as average
variance extracted for each latent variable. Firstly, the standardized factor loading
(i.e., the path estimate linked construct to observed variables) were examined to
identify potential problem with the CFA 21 model. Referring to Hair et al. (2010), the
standardized factor loading for each of the observed variables were proposed to have at
least 0.50 and ideally exceed 0.70, such condition had given evidenced that there was a
significant link between the observed variables and latent variable. For this reason, low
loading estimate were removed (CFA 1 to CFA 9 in Assessment of Fit and Unidimensionality of the Measurement Model section) to avoid potential measurement
problem. The results of final measurement model (CFA 21) (see Table 4.21) indicated
that each standardized factor loading were statistically significant at 0.001 levels. The t
values for each of the observed variables were considered above the rule of 1.65 t value
(Yoo et al., 2000). In addition, the standardized factor loading had ranged from 0.71
(BA1 & BI10) to 0.94 (BT2), and no factor loading was less than the ideal level of 0.70
135
Table 4.21 Final Results of the Analysis of Convergent Validity
Brand equity dimensions
Items
Standardized
factor
loadings
T value
Brand awareness
BA1
BA2
BA3
BF1
BF3
BF4
PQ1
PQ3
PQ4
PQ5
BI3
BI4
BI5
BI9
BI10
BT1
BT2
BT3
ABL2
ABL3
ABL4
ABL5
BE2
BE3
BE4
0.71
0.90
0.83
0.81
0.80
0.83
0.79
0.87
0.84
0.83
0.78
0.79
0.75
0.76
0.71
0.92
0.94
0.88
0.89
0.85
0.89
0.88
0.91
0.92
0.92
19.44
18.31
21.01
21.86
23.38
22.24
21.83
19.53
18.52
18.54
17.39
39.41
33.38
28.89
31.36
30.80
35.61
36.56
Brand familiarity
Perceived quality
Brand image
Brand trust
Brand equity
Average
Variance
Extracted
0.67
0.67
0.69
0.58
0.83
0.77
0.84
Notes: – means the path parameter was set to 1, therefore, no t value was given; all
loadings are significant at 0.001 level.
136
4.5.14 Average Variance Extracted (AVE)
Other than fulfilling the factor loadings and item reliability criteria, the
convergent validity assessment also included the measure AVE (Hair et al., 2010).
According to Fornell and Larcker (1981, p.45), AVE was referred to as “the amount of
variance that is captured by the construct in relation to the amount of variance due to
measurement error”. Furthermore, Fornell and Larcker (1981) suggested that AVE to
be a more conservative measurement than construct reliability. AVE was an indicator
of convergent validity and it was proposed to have at least 0.50 or higher (Hair et al.,
2010; Fornell & Larcker, 1981). Higher AVE values signified that the indicators were
representative of the latent variable (Hair et al., 2010). The initial formula of AVE is
illustrated in formula 1. Besides, there was another formula for AVE as presented by
Hair et al. (2010), which highlighted AVE to be simplified as the total of squared
standardized factor loadings divided by the number of observed variables, as indicated
in formula 2.
Σ (SLi) ²
--------------------Σ(SLi) ² +Σ(ei)
Σ (SLi) ²
--------------------n
Formula 1
Formula 2
Σ
= Sum
SLi
= Factor loading
ei
= Error variance terms for a construct
n
= Nnumber of observed variables in the latent variable
Table 4.21 showed that all the AVE values of constructs were above 0.50,
ranged from 0.58 to 0.84, meaning to express that less than 50% of the error remained
in the terms than variance explained by the latent factor structure imposed on the
measure (Hair et al., 2010). That is, the observed variables were significantly
represented its latent variables respectively. As a result, the test indicated that all the
latent variables had satisfied the convergent validity.
137
4.5.15 Discriminant Validity
In addition to convergent validity, discriminant validity analysis was also
needed to be considered in this study. This was because it served as a test to ensure that
all the constructs (latent variables) that was uniquely derived from the observed
variables, and were not highly correlated (Hair et al., 2010). That is, each of the
constructs is distinguishable and there is no overlapping of constructs in the
measurement model (Hair et al., 2010). The average variance extracted (AVE)
estimated in each construct had exceeded the squared inter-construct correlations
associated with constructs in the model (Hair et al., 2010; Fornell & Larcker, 1981).
The logic here was based on the idea that a construct should explain more of the
variance in its item measures when it was shared with another construct (Hair et al.,
2010). Table 4.22 presented the results for discriminant validity. It was found that the
AVE of each constructs was above squared correlation with other constructs. The result
provided evidence that the seven constructs were unique and captured some
phenomena where other measures did not. It was evident that these results provided
adequate evidence for discriminant validity of the final measurement model (CFA 21).
4.5.16 Nomological Validity
According to Hair et al. (2010), nomological validity was used to examine
whether the correlations among the constructs in a measurement theory made any sense,
and it could be assessed by the matrix correlations among the constructs. As indicated
in Table 4.22, correlations among the constructs were statically significant (p<0.01),
ranged from 0.27 to 0.87. An investigation of the final measurement model (CFA 21)
results revealed that none of the indicators were found to be problematic. According to
this assessment, the measures in the main study were adequate and the scales exhibited
high convergent, discriminant and nomological validity (Gil et al. 2007; Hair et al.,
2010; Malär et al, 2011; Park et al., 2010).
138
Table 4.22 Result of the Discriminant Validity Analysis
Construct
(AVE)
1. Brand awareness
2. Brand familiarity
3. Perceived quality
4. Brand image
5. Brand trust
6. Attitudinal brand loyalty
7. Brand equity
1
0.67
1
0.55(0.74**)
0.09(0.29**)
0.14(0.38**)
0.22(0.47**)
0.23(0.48**)
0.17(0.42**)
2
0.67
1
0.08(0.27**)
0.23(0.48**)
0.47(0.69**)
0.40(0.63**)
0.32(0.57**)
3
0.69
4
0.58
5
0.83
6
0.77
1
0.44(0.67**)
1
0.26(0.51**) 0.53(0.73**)
1
0.29(0.54**) 0.52(0.72**) 0.55(0.74**)
1
0.21(0.46**) 0.35(0.59**) 0.36(0.60**) 0.75(0.87**)
a. **. Correlation is significant at the .01 level (2-tailed).
b. Average Variance Extracted (AVE) are greater than the squared correlation estimates, showing discriminant validity.
139
7
0.84
1
4.6 Assessment of the Structural Model
A structural theory was a conceptual representation of the structural
relationships between constructs (Hair et al., 2010). The structural relationships
between constructs were represented empirically by the structural parameter estimate,
also known as a path estimate (Hair et al., 2010). Structural models were referred to by
several terms, including a theoretical model or, occasionally, a causal model (Hair et al.,
2010). CFA 21 tested measurement theory by providing on the validity of individual
measures based on the model’s overall fit and other evidence of construct validity as
discussed previously. However, CFA 21 alone was limited in its ability to examine the
nature of relationships between constructs (Hair et al., 2010).
Next, this study focused on the structural model and hypothesized relations
among the seven constructs. According to Hair et al. (2010), the hypothesized model
will be supported if (1) the model had showed a good fit, and (2) the hypothesized
paths were significant (e.g. significance relationship for H1 to H12). In addition,
hypothesized model with satisfied goodness-of-fit indices did not mean that some
alternative model(s) might not fit better or be more accurate (Hair et al., 2010). The
relationships in the structural model had to be consistent with the theory that suggested
they should be a positive or negative. If the relationships did not make senses, they
should not be relied upon (Hair et al., 2010). Besides, model re-specifications were
conducted for the purpose to identify the best model (Hair et al., 2010). The additional
proposed models were examined via three distinctive steps. Firstly, the re-specified
models should meet all the goodness-of-fit indices, which applied the same empirical
data as employed for the original proposed model (Hu & Bentler 1999). Secondly, the
significant levels for each of the path estimates were examined for the re-specified
models (Hair et al., 2010). Thirdly, the squared multiple correlations for each of the
endogenous were examined to determine the proportion of variance that was explained
by the predictors in the structural model (Hair et al., 2010).
140
4.6.1 Specifying the Structural Model
Model specification was defined as to how a research framework was
represented in a visual diagram (Hair et al., 2010). These processes included
determining the approach unit analysis, representing the research framework in a path
diagram, clarifying which constructs were exogenous and endogenous, and several
related issues such as sample size and identification (Hair et al. 2010).
In a structural model (known as visual diagram or path diagram), fixed
parameter was the relationship that would not be tested or hypothesized on the
structural equation modeling routine; it was typically assumed to be set as zero and
were not shown on the structural model or path diagram (Hair et al. 2010). Free
parameters were relationships that would be estimated; they were generally depicted by
an arrow in the structural model (Hair et al. 2010). Figure 4.3 showed both fixed and
free parameters. For instance, no relationship was specified between Brand Equity and
Brand Awareness. Therefore, no path estimate (arrow) was shown, and the theory
assumed that this path was fixed at zero. On the other hand, there was a path between
Brand Equity and Attitudinal Brand Loyalty that represented the relationship between
these two constructs and for which a parameter was estimated.
Referring to Figure 4.3, the parameters represented structural relationships
among the constructs. According to Hair et al. (2010), there are three ways where the
correlation and regression coefficients could be interpreted in this model: (1)
relationships between two exogenous constructs, (2) relationships between exogenous
and endogenous constructs and (3) relationships between two endogenous constructs.
141
e50
1
1
Brand Equity
1
BE2 1 e43
BE3 1 e44
BE4
e45
e49
1
1
A. Brand Loyalty
1
ABL2 1
ABL3 1
ABL4 1
ABL5
e38
e39
e40
e41
e48
1
1
Brand Trust
1
BT1 1 e33
BT2 1 e34
BT3
e35
e46
1
1
Brand Image
Brand Familiarity
BF4
1 1
BI10 BI9
1
1
e29
e28
BI5
1
e24
BI4
1
e23
1
1 e5
BF3 1 e7
BF1
e8
BI3
1
e47
e22
Brand Awareness
Perceived Quality
1
1
PQ5 PQ4 PQ3
11
e13 e12
1
e11
BA3 BA2 BA1
PQ1
1
1
11
e3
e9
Figure 4.3 Proposed Brand Equity Structural Model
142
e2
e1
4.6.2 Transforming to Structural Model
The correlation relationships that depicted in CFA 21 model (see Figure 4.2)
were specified as structural model (Figure 4.3). In this process, it involved a series of
changes, such as notation and substantive issues (for example changing from
exogenous to endogenous constructs). The following sections describe the theoretical
and notational changes involved in the process.
4.6.3 Theoretical Change
As illustrated previously, the structural theory was specified by using free
parameters (those to be estimated) and fixed parameters (those fixed at zero value) to
represent twelve hypothesized relationships. However, in specifying the structural
relationships, two other significant changes had occurred. Firstly, a distinction was
made between endogenous and exogenous constructs (Hair et al., 2010). Secondly, an
error term was associated with endogenous constructs as they were not fully explained
Based on the proposed framework in this study, there were two exogenous
constructs and five endogenous constructs. Brand awareness and perceived quality
were exogenous construct as there was no arrow pointing on them. Brand Equity,
Attitudinal Brand Loyalty, Brand Trust, Brand Image, and Brand Familiarity were
endogenous (arrows pointing on it), based on research framework of this study.
Therefore, as compared to CFA 21, the relationships among constructs had
changed entirely. There was a correlation between Brand Awareness and Perceived
Quality, and other constructs had indicated to have the path relationships (causal effect).
Consequently, only one covariance (correlation relationship) was shown in the
proposed model, and other relationships between the constructs were represented by
path coefficient.
143
No relationships were shown between Brand Equity and other constructs (Brand
Familiarity, Brand Trust, Brand Image, and Perceived Quality or Brand Awareness)
except Attitudinal Brand Loyalty, as well as no relationship between Attitudinal Brand
Loyalty and Brand Awareness or Brand Familiarity. This was because they were fixed
to zero, in other words, this study did not hypothesize direct or causal relationships in
the research framework as there were theoretically justified in Chapter 3.
4.6.4 Notational Change
Five new terms appeared, e46 to e50 (Figure 4.3). They represented the error
variance of the prediction for the five endogenous constructs (Hair et al., 2010). After
these error variances were standardized, they were demonstrated as R2. Particularly,
they were similar to the residual in regression analysis (Hair et al., 2010).
4.6.5 Structural Model Identification
The computation of degrees of freedom in a structural model were the same as
the indicated in measurement model, except in the variation of estimated parameters
(Hair et al., 2010). This was because the numbers of observed variables had not
changed; neither did the total number of degree of freedom available (Hair et al., 2010).
Table 4.23 shows the total of 325 number of distinct sample moments had
corresponded to CFA 21 as both models had the identical observed variables, but the
degree of freedom now differed in the relationships between the seven constructs.
Referring to Table 4.23, it was noticed that there was changes of the numbers of
distinct parameters to be estimated (free parameters) for weight and covariance as
compared to Table 4.19. This was because the weights parameter was increased from
18 to 29, extra 11 path parameters (causal effects) were added, these could be explained
by the additional hypothesized path relationship (H2 to H12).
144
Table 4.23: Summary of Structural Model Parameters
Weights
37
0
Covariance
0
0
Variances
0
0
Fixed
Labeled
Number of
distinct
parameters to
29
1
32
be estimated
66
1
32
Total
Degrees of freedom (325 - 62) = 263
Means
0
0
Intercepts
0
0
0
0
0
0
Total
37
0
62
99
Nevertheless, the numbers of covariance were reduced from 23 to 1; only one
hypothesized correlation relationship (represented H1) was remained in the research
framework. Consequently, the model of current study indicated 263 degree of freedom,
which highlighted that the structural model was over-identified (Hair et al., 2010).
4.6.6 Justification of Recursive Model
The proposed brand equity structural model was considered as a recursive
model as the paths between constructs all proceed only from the predictor constructs to
the outcome constructs without any feedback loop (Hair et al., 2010). Therefore, the
research framework of this study indicated that it did not contain any constructs that
were both determined by some predictors and at the same vein assisted in determining
that predictors (Hair et al., 2010). In other words, there was no pair of constructs which
had arrows going both ways between them.
Nonrecursive model existed when the model contained feedback loops (Hair et
al., 2010). A feedback loop was considered when a construct was seen as a playing role
for both predictor and outcome of another single construct. Most of the time,
nonrecursive model seem to have problems with statistical identification as a unique
estimate for a single parameter may no longer exits (Hair et al., 2010).
145
4.6.7 Assessing the Structural Model Validity
The hypothesized brand equity structural model (see Figure 4.3) was then tested
for model fit. Prior to model testing, the standardized loading estimates for the
structural model were examined to ensure that there were no problems associated with
interpretational confounding as compared to final measurement model (Hair et al.,
2010). According to Hair et al. (2010), since the same set of observed variables was
used for both final measurement and structural models, there were rationality to fix the
value of standardized loading estimates for each of the observed variable as these
values were not subject to change just because of the structural model. The advantage
to this approach was that the structural model was easier to estimate because there were
more parameters which had values that were fixed. A disadvantage was that the change
in fit between the final measurement model and the structural model could have been
due to problems with the measurement instead of with the structural theory (Hair et al.,
2010). In order to reduce the possibility of the disadvantage as discussed, method such
as comparing the standardized loading estimates between final measurement model and
structural model could be executed (Hair et al., 2010). If the standardized loading
estimates varied substantially, then there was evidence of interpretational confounding
(Hair et al., 2010). Small fluctuations as long as below 0.05 were acceptable (Hair et al.,
2010). The beauty of this approach was that the original final measurement model fit
became a convenient basis of comparison in assessing the fit for the structural model
(Hair et al., 2010). Table 4.24 showed that the standardized loadings estimates were
virtually unchanged from the CFA 21 result. Even though eight estimated standardized
loadings were changed (BF1, BF4, BI3, BI4, BT1, & BT2), however the maximum
changes was only 0.01, and importantly, all the construct reliabilities were identical.
Thus, if parameter stability had not already been tested in the CFA stage, there would
be evidence of stability among the observed indicator variables (Hair et al., 2010). As a
conclusion, the result showed that all the indicators were found to have no problem in
supporting the validity of measurement of model and no evidence for interpretational
confounding (Hair et al., 2010).
146
Table 4.24 Comparison of Standardized Factor Loadings and Construct
Reliabilities for Hypothesized and CFA 21 Models
Proposed
model
Brand equity
dimensions
Brand awareness
Brand familiarity
Perceived quality
Brand image
Brand trust
Brand equity
Items
BA1
BA2
BA3
BF1
BF3
BF4
PQ1
PQ3
PQ4
PQ5
BI3
BI4
BI5
BI9
BI10
BT1
BT2
BT3
ABL2
ABL3
ABL4
ABL5
BE2
BE3
BE4
SFL
0.71
0.90
0.83
0.82
0.80
0.84
0.79
0.87
0.84
0.83
0.77
0.78
0.75
0.76
0.71
0.91
0.93
0.88
0.89
0.85
0.89
0.88
0.91
0.92
0.92
CR
0.86
0.86
0.90
0.87
0.94
0.93
0.94
CFA 21
Model
SFL
0.71
0.90
0.83
0.81
0.80
0.83
0.79
0.87
0.84
0.83
0.78
0.79
0.75
0.76
0.71
0.92
0.94
0.88
0.89
0.85
0.89
0.88
0.91
0.92
0.92
CR
0.86
0.86
0.90
0.87
0.94
0.93
0.94
Notes: SFL=Standardized factor loadings; CR=Construct reliability; All loadings are
significant at 0.001 level.
147
4.6.8 Goodness-of-Fit Statistics for Structural Model
Next, Table 4.25 reported fit statistics of the overall model fit for proposed
brand equity model and the final measurement model (CFA 21). The same set of fit
indices of measurement model was used to assess the structural model. The χ² was
917.953 with 263 degrees of freedom (p<0.001) and the normed chi-square was 3.490.
The model CFI was 0.946, with a RMSEA of 0.065 and 90% confidence interval of
0.061 to 0.070. The CFI index was substantially above the preferred .92 threshold (Hair
et al., 2010). The absolute fit measure of RMSEA was also well below the
recommended cut-off of 0.07 to be indicative of good model fit (Hair et al., 2010). All
of these measures were within a range that was associated with a good fit as
recommended by Hair et al. (2010), provided with 25 observed variables and carried
out 585 numbers of observations.
According to Hair et al. (2010), the closer the values of goodness-of-fit for both
structural model and measurement model, the better the structural model fitted because
the measurement model fit provided an upper bound to the goodness-of-fit measures of
a conventional structural model. Furthermore, as long as the structural theory was a
recursive model, then it could not include more relationship between constructs than
the final measurement model from which it was developed (Hair et al., 2010).
Consequently, a recursive model could not have a lower χ² value and better model fit
than that obtained in final measurement model (Hair et al., 2010).
Table 4.25 indicated that values of goodness-of-fit for proposed brand equity
model (structural model) changed very little from the CFA 21. The only substantive
difference was a chi-square (χ²), which increased of 58.36 and a difference of nine
degrees of freedom. As a conclusion, these results are reported in Table 4.25 suggests
clear understanding of structural model fit from final measurement model fit.
148
Table 4.25 Comparison of Goodness-of-fit Measures between Proposed Brand
Equity and CFA 21 Models
Goodness-of-fit index
Absolute measures
χ² (chi-square)
Degrees of freedom
χ²/df
Probability
GFI
RMSEA
Confidence interval of RMSEA
RMR
SRMR
Brand equity model
CFA 21 model
917.953
263
3.490
0.001
0.887
0.065
0.061 - 0.070
0.074
0.050
859.593
254
3.384
0.001
0.893
0.064
0.059 - 0.069
0.051
0.037
Incremental fit measures
NFI
CFI
RFI
0.927
0.946
0.916
0.931
0.950
0.919
Parsimony measures
AGFI
PNFI
0.860
0.812
0.863
0.789
Note: GFI=Goodness-of-Fit Index, RMSEA=Root Mean Square Error of
Approximation, RMR=Root Mean Square Residual, SRMR=Standardized Root
Mean Square Residual, NFI=Normed Fit Index, CFI=Comparative Fit Index,
RFI=Relative Fit Index, AGFI=Adjusted Goodness-of-Fit Index, PNFI=Parsimony
Normed Fit Index.
149
4.6.9 Examining Structural Model Diagnostics
In the structural equation modeling (SEM), several diagnostic measures were
available to evaluate the SEM models. The diagnostic measures ranged from fit indices
to standardized residuals (SR) and modification indices (MIs) (Byrne, 2010). There
were three important things which had to be emphasized on while using MIs. Firstly,
covariance could only be exercised if the measurement error of the constructs was
identical, and it could not be executed by when there was any cross-covariance (Byrne,
2010). Secondly, there were substantive numbers of suggested parameters found from
the MIs, however, the action for freeing up the parameter must be theoretically
supported and must gradually be exhibited depending on the largest MIs value
(Jöreskog & Sörbom, 1993). Lastly, it was important to know where to stop for the
model re-specification; which served as the purpose of avoiding over-fitted model
(Wheaton, 1987).
Residual could be either positive or negative, depending on whether the
estimated covariance was under or over the corresponding observed covariance (Hair et
al., 2010). Typically, SR less than l2.5l did not suggest a problem, value between l2.5l
and l4.0l deserved some attention, but might not suggest any changes to the model if no
other problems were associated with those two items, residual greater l4.0l raised a red
flag and suggest a potentially unacceptable degree of error (Hair et al., 2010). Table
4.26 showed that there was no SR value that greater than l4.0l, yet, there were seven
pairs of SR that fell in between l2.5l and l4.0l. The study indicated that there were no
other problems associated with these pair items as there were no significant values such
as higher than 4.0 as highlighted by Hair et al. (2010). For this reason, all the observed
variables were suggested to be retained in this model.
150
Table 4.26 Model Diagnostic for Proposed Brand Equity Structural Model
a. Standardized residuals (all residuals greater than l2.5l)
Largest negative standardized residual (None)
Largest positive standardized residuals
BF3
and
BE3
BF4
and
BE3
BF1
and
ABL2
BF3
and
BE4
BF4
and
ABL2
BF1
and
ABL3
BF1
and
PQ5
b. Modification indices for correlation relationships
Items Items Relevancy
Error term
Error Term
↔ BI5 - e24
BI4 - e23
Yes
↔ BI10 - e29
BI9 - e28
Yes
↔ ABL3 - e39
BF3 - e7
No
↔ BI10 - e29
BI4 - e23
Yes
↔ BE2 - e43
BT3 - e35
No
↔
ABL2 - e38
BE3 - e44
No
↔
BI9 - e28
ABL - e49
No
↔
ABL2 - e38
BE5 - e45
No
↔
BI3 - e22
BI9 - e28
Yes
↔
BI5 - e24
BI10 - e29
Yes
↔
BT1 - e33
ABL - e49
No
↔
BF4 - e8
BE3 - e44
No
↔
BA1 - e1
BF - e46
No
↔
BI4 - e23
ABL - e49
No
↔ ABL5 - e41
ABL3 - e39
Yes
↔ PQ5 - e13
BE2 - e43
No
3.92
3.61
3.32
3.20
2.72
2.63
2.58
Δ χ²
85.04
46.30
26.80
28.69
18.89
18.12
16.30
15.70
15.50
14.40
14.09
13.37
13.19
13.00
12.27
12.10
Δ Par
0.20
0.19
0.13
-0.14
0.07
0.07
0.09
-0.06
-0.08
-0.10
-0.06
0.07
0.11
-0.08
-0.07
0.06
c. Modification indices for structural relationship
Structural relationship (not estimated)
BF
BA
→
→
Relevancy
ABL
ABL
No
No
Δ RW Δ Par
16.44
14.53
0.13
0.14
Notes: χ²=Chi square, Par=Parameter, RW=egression weights, BA=Brand awareness,
PQ=Perceived quality, BF=Band familiarity, BI=Brand image, BT=Brand trust,
ABL=Attitudinal brand loyalty, BE=Brand equity
151
According to Byrne (2010), all parameter change statistics (Δ Par) related to the
error covariance revealed not significant values less than, or close to l0.10l, and all MIs
for the change of chi-square (Δ χ²) or change of regression weights (Δ RW) were less
than 10.00 (Byrne, 2010). In other words, serious attention had to be given to those MIs
that were greater than l0.10l Δ Par and 10.00 Δ χ² / Δ RW (Byrne, 2010). However, if
there were situations where MIs presented greater (lower) than l0.10l Δ Par and lower
(greater) than 10.00 Δ χ² / Δ RW, it was suggested to focus on size of the Δ Par, rather
than on the Δ χ² / Δ RW (Kaplan, 1989). Turning to the result of MIs for correlation
relationships (see Table 4.26), the error covariance related to the same constructs
(indicated “Yes” in relevancy column), BI4 & BI5, BI9 & BI10, BI4 & BI10, BI3 &
BI9, BI5 & BI10, and ABL3 & ABL5 remained above 10.00 misspecification chisquare in the model (85.04, 46.30, 28.69, 15.50, 14.40, and 12.27 respectively). Only
four pairs’ (BI4 & BI5, BI9 & BI10, BI4 & BI10, and BI5 & BI10) estimated
parameter change statistic did suggest that this parameters were significant
incorporated into the model as the recommended value were above l0.10l (Byrne, 2010).
Since the structural model was statistically fitted, it was not necessary for the model respecification to avoid over-fitted model (Wheaton, 1987). In reviewing the MIs for
structural relationship, the results suggested to include path coefficients of Brand
Familiarity and Brand Awareness on Brand equity (Δ RW = 16.44, Δ Par = 0.13 and Δ
RW = 14.53, Δ Par = 0.14). However, there were no theoretical supports for the causal
relationships as suggested in MIs. For this reason, the inclusion of both structural
relationships would not make sense even if it helped to improve the model fits (Byrne,
2010). Thus, there were no further modifications for the proposed model. In general,
the issue of over-fit model was raised when there were over re-specification of
additional parameter in the model (Wheaton, 1987). Therefore, if a researcher selects to
use SEM, it was vital to understand the analysis to be conducted within the
confirmatory mode, rather than exploratory that was based on MIs. In other words,
there was the end of SEM analytic approach once the hypothesized CFA or structural
model had failed to fulfill the specific criteria (Byrne, 2010).
152
4.7 Results of Hypotheses Testing
In Chapter 3, twelve hypotheses were proposed based on theoretical and
extensive literature which reviewed for inclusions in the model. Hair et al. (2010)
argued that the validation of model was not complete without examining the individual
parameter estimates. Consequently, the last part of the validation of model was to
determine if there were any significant relationships which existing in the model. Out
of twelve hypotheses, nine statements were supported and three hypotheses were
rejected due to insignificant statistic. An outline of the hypotheses is presented in Table
4.27, which included unstandardized parameter estimates (b), standardized parameter
estimates (β), standard error (se), t value, and statistical significance level (α).
Structural parameter estimates or path estimates (including unstandardized and
standardized) were comparable as a regression coefficients that measured the linear
relationship between predictor construct and an outcome construct in structural
equation modeling (Hair et al., 2010). In other words, it reflected the change in the
dependent measure for each unit change in the independent variables (Hair et al., 2010).
Unstandardized parameter estimates retained scaling information of variables and could
only be interpreted with reference to the scales of the variables (Suhr, 2008). In contrast,
standardized parameter estimate was the transformation of unstandardized estimates
that removed scaling, and it could be further used as an informal comparison of
parameters throughout the model (Suhr, 2008).
Standardized parameter estimate (standardized coefficient) was calculated from
standardized data, thus it allowed for an assessment of practical significance in term of
relative predictive power of the added variable (Hair et al., 2010). Standard error (se)
was an estimate of how much the structural parameter estimate would vary between
samples of the same size taken from the same population, and a smaller standard error
implied more reliable prediction and therefore smaller confidence intervals (Hair et al.,
2010).
153
Table 4.27 Results of the Hypotheses
Correlation estimate
H1
Brand awareness
↔ Perceived quality
Structural parameter estimates
H2
Brand awareness
→
H3
Brand awareness
→
H4
Brand familiarity
→
H5
Brand familiarity
→
H6
Perceived quality
→
H7
Perceived quality
→
H8
Perceived quality
→
H9
Brand image
→
H10 Brand image
→
H11 Brand trust
→
H12 Attitudinal brand loyalty →
Brand familiarity
Brand image
Brand image
Brand trust
Brand image
Brand trust
Brand trust
Brand equity
b ( 95% CI )
β
se
0.24 (0.16-0.32)
0.30
0.04
0.83 (0.71-0.95)
-0.07 (-0.17-0.03)
0.31 (0.21-0.41)
0.48 (0.40-0.55)
0.48 (0.41-0.56)
0.10 (0.00-0.20)
0.09 (-0.01-0.19)
0.67 (0.51-0.83)
0.44 (0.26-0.62)
0.46 (0.36-0.56)
0.98 (0.90-1.06)
0.73
-0.09
0.40
0.43
0.59
0.09
0.08
0.46
0.31
0.48
0.86
0.06
0.05
0.05
0.04
0.04
0.05
0.05
0.08
0.09
0.05
0.04
t value
α
Conclusion
6.04
**
Supported
14.08 **
-1.38 0.17
6.37 **
10.96 **
12.65 **
1.94 0.06
1.84 0.07
8.49 **
5.00 **
9.43 **
24.95 **
Supported
Not Supported
Supported
Supported
Supported
Not Supported
Not Supported
Supported
Supported
Supported
Supported
Notes: b=Unstandardized parameter estimates, CI=Confidence interval, β=Standardized parameter estimates, se=Standard error,
α=Statistical significance level , ** Path analysis is significant at the .001 level
154
The t value was derived from dividing the unstandardized parameter estimates
by the standard error (Hair et al., 2010). It was used to measure the significance of the
partial correlation of the variable reflected in the structural parameter estimated (Hair et
al., 2010). As such, it indicated whether the researcher could confidently conclude,
with a stated level of error, that the structural parameter estimated was not equal to zero.
Statistical significance level was also known as Alpha (α) or Type I error. It was the
probability of rejecting the null hypothesis when it was actually true, generally referred
to as a false positive and conventional guidelines suggested α levels of 0.05 or 0.01
(Hair et al., 2010). By specifying an α level, the researcher had set the acceptable limits
for error which indicated that the probability of concluding that significance exists
when it really did not (Pallant, 2005).
As shown in Table 4.27, H1 to H3 examined the relationships between brand
awareness and perceived quality, band familiarity and brand image. The correlation
between brand awareness and perceived quality was statistically significant (β = 0.30,
se = 0.04, t value = 6.04, α < 0.001). The causal relationship for brand awareness on
brand familiarity was statistically significant (β = 0.73, se = 0.06, t value = 14.08, α <
0.001). This meant that band familiarity was expected to improve by 0.73 standard
deviation; given a change in brand awareness of one full standard deviation, while
other variables were controlled (Pallant, 2005). The standard error (se) of structural
parameter estimates were 0.04 and 0.06, denoting that the 95% confidence interval for
unstandardized parameter estimates (b) would be ranging from 0.16-0.32 and 0.71-0.95
correspondingly. The t values were 6.04 and 14.08, which were statistically significant
at the 0.001 level. Brand awareness gave a high level of assurance that the structural
parameter estimates were not equal to zero and can be assessed as a predictor of brand
familiarity. On the other hand, the result revealed that brand awareness was not
positively related to consumers’ brand image (β = -0.09, se = 0.05, t value = -1.38, α =
0.17). Thus, H1 and H2 were supported; however H3 was not evidently proven.
155
H4 and H5 predicted brand familiarity was the foundation of building brand
image and brand trust. The results showed significant path analyses, brand familiarity
positively influenced brand image (β = 0.40, se = 0.05, t value = 6.37, α < 0.001), and
brand trust (β = 0.43, se = 0.04, t value = 10.96, α < 0.001). Hence, H4 and H5 were
supported. In testing H6, H7 and H8, it was evident that the perceived high quality of
products was likely to help in constructing a favorable brand image (β = 0.59, se = 0.04,
t value = 12.65, α < 0.001), yet unsuccessfully in contributing strong brand trust (β =
0.09, se = 0.05, t value = 1.94, α = 0.06) and attitudinal brand loyalty among consumers
(β = 0.08, se = 0.05, t value = 1.84, α = 0.07). That is, the perception of Malaysian
consumers towards fast food brand image was based on the perceived quality. However,
solely depended on quality alone did not support in the creation of brand trust and
attitudinal brand loyalty. Therefore, H6 was supported but H7 and H8 were rejected.
H9 and H10 proposed that favorite brand image could lead to greater brand trust
and strong attitudinal brand loyalty. The results indicated statistical significant effect of
brand image on brand trust (β = 0.46, se = 0.08, t value = 8.49, α < 0.001) and
attitudinal brand loyalty (β = 0.31, se = 0.09, t value = 5.00, α < 0.001). Focused on the
highest se of structural parameter estimates was 0.09, which denoting that the 95%
confidence interval for b would be 0.44 ± (1.96 X 0.09), or ranging from the lowest of
0.26 to the highest of 0.62. Even though the range of confidence interval was quite
larger, but the t value was 5.00 and statistically significant at the 0.001 level. Therefore,
H9 and H10 were supported.
H11 argued that brand trust was likely to be a predictor of consumers’
attitudinal brand loyalty. The results from this study supported this proposed causal
relationship (β = 0.48, se = 0.05, t value = 9.43, α < 0.001). Lastly, H12 posited the
relationship between consumers’ attitudinal brand loyalty and their overall brand equity.
The result revealed that overall consumer-based brand equity was significantly
predicted by their attitudinal brand loyalty (β = 0.86, se = 0.04, t value = 24.95, α <
0.001). Hence, H11 and H12 were supported.
156
4.8 Model Re-specification: Comparison of Different Models
Model re-specification must have strong theoretical as well as empirical support
(Hair et al., 2010). It could be executed by considering the diagnostic measures in
Structural Equation Modeling (SEM), for instance the modification indices (MIs) that
is available in the output of AMOS software (Byrne, 2010). Thus, a further assessment
of SEM model in relation to causal effect, which was the post hoc analysis, would be
conducted if there were any improvement of the model fit with theoretically justified
In reviewing MIs, the result revealed that there was evidence of misfit in the
proposed model as additional structural relationship (causal effect) was included in the
model (see Table 4.26: part c. Modification indices for structural relationship).
However, as stated above, any model re-specification should have strong theoretical
background in supporting the execution. Since the proposed structural parameter did
not have any relevance of theory behind them, thus the proposed model was considered
as the final model (Hair et al., 2010). Referring to Table 4.28, the squared multiple
correlation (i.e., R² in multiple regression) for brand equity was 0.74, attitudinal brand
loyalty (0.62), brand trust (0.67), brand image (0.55), and brand familiarity (0.54).
However, squared multiple correlation was not applicable for exogenous constructs
such as perceived quality and brand awareness. It was estimated that the predictors of
brand equity explained 74 percent of its variance. In the same vein, the error variance
of brand equity was approximately 26 percent of the variance of brand equity itself.
This could be explained that 74% of variability in brand equity was explained
by direct predictor (attitudinal brand loyalty) and indirect predictors (brand trust, brand
image, brand familiarity, perceived quality and brand awareness). Consequently, the
proposed model was considered as an ideal model as it met all the goodness-of-fit
indices and the values of endogenous’ squared multiple correlations were above 0.50.
157
According to Kenny (2011), another strategy to take in re-specifying a model
was focusing on theoretically meaningful complications and simplifications of the
model. In other words, the re-specification of model could be performed model
comparison on other researchers’ concepts, which had strong theoretical justification
(Kenny, 2011). As discussed in Chapter 2 and 3, most of the constructs or latent
variables were adopted from Aaker’s (1991) and Gil et al.’s (2007) model. Therefore,
both of the established theoretical concepts were tested in the structural models to
investigate whether there were significant difference of goodness-of-fit indices (GOF),
causal relationships (structural parameter estimates), and squared multiple correlation
(R²) as compared to the proposed model.
Table 4.28 supported that the chi-square for Aaker (A) and Gil et al. (G) models
were 549.986, which was significant different from the proposed model (P) by 367.967,
with 121 degrees of freedom, and 3.873 normed chi-square (p< 0.05). However, there
were not much difference for GFI (P: 0.887, A: 0.907, G: 0.907), RMSEA (P: 0.065, A:
0.070, G: 0.070), Confidence interval of RMSEA (P: 0.061-0.070, A: 0.064-0.076, G:
0.064-0.076), NFI (P: 0.927, A: 0. 938, G: 0. 938), CFI (P: 0.946, A: 0. 953, G: 0. 953),
RFI (P: 0.916, A: 0. 925, G: 0. 925), and AGFI (P: 0.860, A: 0. 875, G: 0. 875).
Turning to results on relationships among constructs, the findings among three
models were consistent and the value for standardized structural parameter estimates
did not vary dramatically. For instance, the direct relationships between brand
awareness and brand equity was not significant for both A and G models, brand image
and attitudinal brand loyalty was significant for both P (0.31) and G (0.58), perceived
quality and brand equity was insignificant for A and G models, perceived quality and
attitudinal brand loyalty was not significant for P and G models. In additional to that,
the path analysis from brand image to brand equity was insignificant for A and G
models. Lastly, the result showed a statistically significant causal effect of attitudinal
brand loyalty on brand equity among three models (P: 0.86, A: 0.91, G: 0.91).
158
Figure 4.4: Implication of Aaker’s Model (1991)
Note: BA=Brand awareness, PQ=Perceived quality, BI=Brand image, ABL=Attitudinal
brand loyalty, BE=Brand equity
Figure 4.5: Implication of Gil at al.’s Model (2007)
159
Table 4.28 Comparison of Structural Models
Goodness-of-fit index
χ² (chi-square)
Degrees of freedom
χ²/df
Probability
GFI
RMSEA
Confidence interval of RMSEA
RMR
SRMR
NFI
CFI
RFI
AGFI
PNFI
Parameter estimates
BA ↔ PQ
BA → BF
BA → BI
BA → ABL
BA → BE
BF → BI
BF → BT
BF → ABL
BF → BE
PQ → BI
PQ → BT
PQ → ABL
PQ → BE
BI → BT
BI → ABL
BI → BE
BT → ABL
BT → BE
ABL → BE
Proposed
Model
Aaker
Gil et al.
917.953
263
3.490
0.001
0.887
0.065
0.061 - 0.070
0.074
0.050
0.927
0.946
0.916
0.860
0.812
549.986
142
3.873
0.001
0.907
0.070
0.064-0.076
0.052
0.039
0.938
0.953
0.925
0.875
0.779
549.986
142
3.873
0.001
0.907
0.070
0.064-0.076
0.052
0.039
0.938
0.953
0.925
0.875
0.779
0.30**
0.73**
-0.09
0.40**
0.43**
0.59**
0.09
0.08
0.46**
0.31**
0.48**
0.86**
0.01
0.03
-0.08
0.91**
160
0.23**
0.01
0.09
0.03
0.58**
-0.08
0.91**
Table 4.28 Comparison of Structural Models (Continued)
Squared multiple correlation
BF
BI
BT
ABL
BE
0.54
0.55
0.67
0.62
0.74
0.75
0.56
0.73
Notes: - Not applicable, ** Significant at the .001 level
BA=Brand awareness, BF=Brand familiarity, PQ=Perceived quality, BI=Brand
The squared multiple correlations of brand equity did not indicate significant
changes across the three models (P: 0.74, A: 0.75, G: 0.73), with the differences of
±0.01. In other words, the R² of brand equity was proven to have slightly 1%
improvement (0.01 X 100%) once the proposed model (P) was re-specified to Aaker
model. Interestingly, in P model, the value of squared multiple correlations were found
to have greater than 0.5 for brand familiarity, brand image, brand trust, attitudinal
brand loyalty, and brand equity. In contrast, A and G models only indicated squared
multiple correlations value for brand equity or attitudinal brand loyalty.
Based on the arguments as discussed above, the proposed model was
considered as an imperative contribution in the Malaysian field of fast food brand
equity. This was because it demonstrated more comprehensive causal relationships,
good goodness-of-fit indices, consistent structural parameter estimates, and did not
significantly different from the Aaker’s (1991) and Gil et al.’s (2007) framework.
Moreover, it covered a broader view of squared multiple correlations.
161
4.9 Conclusion
A total number of 600 questionnaires were distributed among Malaysian
(Marrybrown and 1901 Hotdogs) and foreign (McDonald’s, KFC and Pizza Hut) fast
food restaurants. Only 15 surveys were excluded due to incomplete responses. Thus,
585 or 97.50% of respondents were qualified and were used for further analysis.
Basically, there were 50.43% male and 49.57% female, which were equally distributed.
With respect to ethnic groups, 63.09% were Malays, followed by Chinese (26.15%),
Indian (4.96%), and others (5.80%).
The final measurement model (CFA21) was over-identified with 254 degree of
freedom, and the Goodness-of-Fit was above the recommended value (χ² = 859.593,
χ²/df = 3.384, RMSEA = 0.064, SRMR = 0.037, GFI = 0.893, CFI = 0.950, NFI =
0.931, IFI = 0.950, TLI = 0.942, PCLOSE = 0.06), and the p-value associated with chisquare was 0.0001. Besides, CFA21 was proven to meet all the criteria for construct
reliability, convergent validity, discriminant validity, and nomological validity. The
same set of fit indices of measurement model was used to assess the structural model.
The χ² was 917.953 with 263 degrees of freedom (p<0.001) and the normed chi-square
was 3.490. The model CFI was 0.946, with a RMSEA of 0.065 and 90% confidence
interval of 0.061 to 0.070.
The results suggested that the proposed model provided a good overall fit. Out
of 12 hypotheses, 9 statements were supported and 3 were rejected due to insignificant
statistic. The results of the comparison among the three models (proposed model,
Aaker, and Gil et al.) were consistent and the value for standardized structural
parameter estimates did not vary dramatically. Moreover, proposed model covered a
broader view of squared multiple correlations as compared to previous model.
162
CHAPTER 5
DISCUSSION ON FINDINGS
5.1 Introduction
First and foremost, the chapter starts with the discussion on the result of the
hypotheses, and each of the hypotheses had been identified with previous studies. Next,
the chapter justifies the importance and inclusion of brand familiarity as well as brand
trust in this study.
It is followed by the identification of causal relationships in the proposed model,
which highlights the rational linkage of causal relationships between dimensions of
brand equity and overall brand equity.
5.2 Discussion on Hypotheses Results
The results of this study predicted the relationship between constructs of
consumer-based brand equity, namely perceived quality, brand awareness, brand
familiarity, brand image, brand trust, attitudinal brand loyalty and brand equity. There
is no causal relationship between brand awareness and perceived quality, yet, there is
existence of correlation. The deliberations for each of the hypotheses are stated in
Figure 5.1.
163
Notes:
a. BA=Brand awareness, PQ=Perceived quality, BF=Band familiarity, BI=Brand image,
BT=Brand trust, ABL=Attitudinal brand loyalty, BE=Brand equity
b. ** Significant at .05 level
Figure 5.1 Results of Proposed Model
Hypothesis 1
There is positive correlation between brand awareness and perceived quality
(Supported: β = 0.30 t value = 6.04 α = 0.001)
The finding confirms the results of previous researchers that the quality as
perceived by consumers is positively correlated with the brand awareness (Grewal et al.,
1998; Dodds et al., 1991). In the same vein, when consumers are uncertain about a
particular brand, the risk as perceived by consumers had increased (Hoeffier & Keller,
2003).
164
For this reason, the awareness or popularity of the brand will definitely drive to
better quality as expected by consumers (Erdem & Swait, 1998). Therefore, the
positive (negative) result from fast food brand awareness and perceived quality would
serve as a helpful (unhelpful) platform to ensure credibility and visibility for each other.
Hypothesis 2:
The higher the awareness of a brand, the greater the brand familiarity
The result of this study is in line with most of the branding research papers and
conceptual papers (Alba & Hutchinson, 1987; Cobb-Walgren et al., 1995; D’Souza &
Rao, 1995; Gursoy & McCleary, 2004; Reynolds & Olson, 1995). According to Keller
(2003), brand awareness is related to the strength of the brand elements such as logo,
symbol, character, packaging, slogan and so on, that store in consumers’ memory. For
this reason, fast food brand elements instantly processed once the brand was retrieved
from consumers’ mind, consequently, the repeated frequency of fast food brand
information processing was stored as cognitive representations of knowledge.
Hypothesis 3:
The higher the awareness of a brand, the greater the brand image
(Not Supported: β = -0.09 t value = -1.38 α = 0.17)
Other researchers examined the causal relationship between brand awareness
and brand image (Angel & Manuel, 2005; Esch et al., 2006; Hoyer & Brown, 1990).
Contrast with previous studies, this study indicated the causal relationship between the
two constructs was not supported. Hoyer and Brown (1990) stated that brand awareness
generated the differences in information processing, and these differences, which were
created by brand associations in the consumer’s memory, directly affect brand image.
165
However, some scholars argued that brand awareness was referred to as the
level of consumers’ brand exposure (Alba & Hutchinson, 1987; Woodward, 2000). As
a result, brand awareness alone was not sufficient to generate different type of
associations and attributes that consumers connect to the brand name (Das et al., 2009),
and also highlighted the existence of different degrees of cognitive (Frey, 1982) in
brand equity formation. Notably, the repeated brand awareness had driven to brand
familiarity, which is the number of brand-related experiences, direct and indirect
knowledge available to the consumer (Alba & Hutchinson, 1987) before constructing
any cognitive brand image. In other words, solely depended on brand awareness was
not sufficient to explain the formation of brand image, and the familiarity of brand
serves as a vital variable to explain the relationship in between brand awareness and
brand image in the Malaysian context of fast food industry.
Hypothesis 4:
The higher the familiarity of a brand, the greater the brand image
This study supported consumers’ formation process of brand image, which is
related positively to the extent to which the familiarity of the brand was evidenced,
correspond with previous studies (Holden & Vanhuele, 1999; Janiszewski, 1993;
Zajonc & Markus; 1982). Therefore, when a consumer was confronted with a familiar
fast food brand, he or she felt emotional closeness and confidence. Subsequently,
enhance in the association of the brand in consumers’ mind, and positively affected
consumers’ image towards the fast food brand. On the other hand, when a consumer
was unfamiliar with the fast food brand, he or she was incapable to stimulate the fast
food brand because of the lack of knowledge and experience with the brand’s attributes,
benefits, and attitudes.
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Hypothesis 5:
The higher the familiarity of a brand, the greater the brand trust
This study had supported the hypothesis that higher brand familiarity led to
better brand trust, which was line in with previous studies (Campbell & Keller, 2003;
Fullerton, 2005; Keller, 1998; Papadopoulou et al., 2001; Sen & Johnson, 1997; Smith
& Wheeler, 2002; Zajonc & Markus, 1982). As a result, the increases in fast food brand
familiarity through accumulated customer experiences and greater amount of time
spent in processing brand information were not only created better knowledge structure,
but also build up confidence and trust for the fast food brand.
Hypothesis 6:
The higher the perceived quality of a brand, the greater the brand image
According to Keller (1993), good evaluation of perceived quality had bought
about customers to have strength, favorability, or uniqueness type of brand association.
Again, the empirical result of this study confirmed the above statement, which
corresponded with Kayaman and Arasli’s (2007) hospitality study. Therefore, the
perception of quality served as an important antecedent of brand image creation in the
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Hypothesis 7:
The higher the perceived quality of a brand, the greater the brand trust
(Not Supported: β = 0.09 t value = 1.94 α = 0.06)
Remarkably, the perception of good quality was not positively affected by
brand trust. The result revealed a contradict result to Papadopoulou et al.’s (2001)
online study. Possibly, the perceived quality in impersonal business was critically
evaluated by consumers, but did not apply in interpersonal business, such as fast food
business. Furthermore, brand trust was classified as affective character, which referred
physiological responses, such as positive moods, feelings, and emotional responses.
Hence, the establishment of bond between consumers and the fast food brand trust
required greater association and cognitive representations of consumers’ knowledge,
rather than the perception of quality.
Hypothesis 8:
The higher the perceived quality of a brand, the greater the attitudinal brand loyalty
(Not Supported: β = 0.08 t value = 1.84 α = 0.07)
The empirical result highlighted that perceived quality did not statistically cause
attitudinal brand loyalty in the context of fast food industry. Nevertheless, this result
was in line with some of the previous studies (Aydin & Özer, 2005; Gil et al., 2007;
Tong & Hawley, 2009). This could be further explained that attitudinal brand loyalty
had been considered as a conative construct, while perceived quality was considered as
a cognitive construct, based on arguments of cognitive-affective-conative hierarchical
model (Chiou et al., 2002). Therefore, in fast food context, perceived quality could
only drive an effect on attitudinal brand loyalty through affective construct(s).
Affective construct would serve as the mediating variable, referring to the result from
affective component of attitude, such as “emotional” or “feeling” responses (Lavidge &
Steiner, 1961).
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Hypothesis 9:
The higher the image of a brand, the greater the brand trust
Next, this study had confirmed that brand image had lead to higher level of trust
as perceived by consumers. The result was in conjunction with online study (Esch et al.,
2006; Yoon, 2002), hotel study (Back, 2005; Kandampully & Hu, 2007; Kandampully
& Suharanto, 2000), financial study (Flavián et al., 2006), as well as restaurant study
(Lee, Park, Park, Lee & Kwon, 2005). As a result, the existence of fast food brand
image was considered as vital criteria for the development of brand trust.
Hypothesis 10:
The higher the image of a brand, the greater the attitudinal brand loyalty
The result supported that brand image was one of the causes for attitudinal
brand loyalty, in line with previous studies (Back, 2005; Flavián et al., 2006;
Kandampully & Suhartanto, 2000; Kandampully & Hu, 2007). In addition to that,
current result served as an important explanation to identify the relationship between
brand image and attitudinal brand loyalty, based on the theory of cognitive-affectiveconative (Lavidge & Steiner, 1961). As discussed in the literature review, brand image
was classified as both cognitive and affective characters, while attitudinal brand loyalty
was considered as conative construct. Therefore, the image of fast food brand could be
classified an essential predictor for the formation of attitudinal brand loyalty.
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Hypothesis 11:
The higher the trust of a brand, the greater the attitudinal brand loyalty
In this study, brand trust had been recognized as a prominent variable that had
led to long-term relationship with customers, which affected attitudinal brand loyalty in
a positive way. The empirical result was consistent with most of the previous studies
(Chiou & Droge, 2006; Flavian et al., 2006; Sichtmann, 2007; Martzler et al., 2008;
Rauyruen & Miller, 2007). Therefore, fast food brand trust was the key variable to
maintain continuing relationships with customers, and served as an important criterion
in forming consumers’ positive behavioral intention, such as the intention to repurchase
and to make recommendations to the other party (Lau & Lee, 1999).
Hypothesis 12:
The higher the attitudinal loyalty of a brand, the greater the brand equity
Many studies had proven that brand loyalty had significant effect on brand
equity (Baldauf et al., 2003; Gil et al., 2007; Kim & Kim, 2004; Norjaya et al., 2007;
Tong & Hawley, 2009; Yoo et al., 2000), this indicated that the essential role of
developing brand loyalty in brand equity creation. Therefore, attitudinal brand loyalty
could be considered as the most important dimension of brand equity. The result was
supported by many researcher findings, which indicated customer loyalty served as the
basic for the development of brand equity (e.g. Aaker & Joachimsthaler, 2000; Clarke,
2001; Davis & Dunn, 2002). This was because loyalty had been identified as a
favorable attitude, which would lead to the consistency of repurchase behavior towards
a brand (Assael, 1992). As a conclusion, the finding ratified the importance of
managing loyalty as part of the brand management strategy (Christodoulides & de
Chernatony, 2004; O’loughlin, 2006), and it have to be extended to the Malaysian fast
food sector.
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5.3 The Importance of Brand Familiarity and Brand Trust
Notes:
Figure 5.2 Brand Equity Model – The Exclusion of Brand Familiarity and
Brand Trust
Referring to Figure 5.1 (p. 164), there were significances in the results for most
of the hypotheses which were either related to brand familiarity or brand trust. Turning
to Figure 5.2, the model (excluded brand familiarity and brand trust) was indicated a
missing link of brand awareness on other brand equity dimensions. Besides, there were
only four significant causal effects which existed in the model. Furthermore, there was
no variable which was absolutely characterized as affective brand dimensions. By
including brand familiarity, the missing link of brand awareness could be justified. For
instance, brand awareness contributed significantly on brand familiarity, which showed
that the linkage between brand awareness and other variables, such as brand image,
brand trust, attitudinal brand loyalty, and brand equity.
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On the other hand, brand trust was considered important because it was the
absolute variable that classified as affective brand dimensions. In addition, there were
three significant causal effects could be evidenced in relation to brand trust. Besides,
the value of squared multiple correlations for brand familiarity and brand trust were
found to have 0.55 and 0.67 respectively, which was greater than 0.50. For these
reasons, there was a positive conformity for the inclusion of both additional dimensions
in the Malaysian context of fast food industry.
5.4 Identification of Causal Relationships in the Model
Notes:
b. Red bolded path=Significant at .05 level; Dotted path=Non-significant at .05 level
Figure 5.3 The Overview of Causal Relationships in Malaysian Fast Food
Industry
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Referring to Figure 5.3, a rational linkage could be evidenced from the causal
relationships among dimensions of brand equity and overall brand equity in the
Malaysian context of fast food industry. According to Aaker (1991), brand awareness
was a critical factor for brand equity, and the awareness of the brand was the beginning
of loyalty. If a customer was aware of a certain brand, there was a higher possibility
that the customer would have a favorable image towards the brand (Keller, 1993).
However, most of the empirical studies failed to indicate a significant causal effect of
brand awareness on brand equity, for instance in online branding (Graebner-Kraeuter,
2002; Rosa & Riquelme, 2008), hotel study (Bailey & Ball, 2006), sportswear market
(Tong & Hawley, 2009), and consumer products (Wang et al., 2008). In order to
provide further explanation, this study found there were numerous of significant
compound paths from brand awareness to brand equity, for instance via brand
familiarity, brand image, brand trust and attitudinal brand loyalty. Thus the findings
explained the linkages from brand awareness to brand equity could be significantly
determined, even though brand awareness did not significantly affect brand equity
directly, based on the result from model re-specification as indicated in Aaker and Gil
et al. frameworks. As a result, this study showed the possibility of significant indirect
effects when directs effects are absent (Rucker, Preacher, Tormala, & Petty, 2011).
Subsequently, this study supported brand awareness was a key dimension for fast food
brand equity, it had affected consumer decision making by influencing the formation
and strength of other brand equity dimensions, which drove to brand equity indirectly
via other dimensions.
This study provided explanation for the non-significant causal effect of
perceived quality on brand loyalty (Gil et al., 2007) and brand equity (Tong & Hawley,
2009). Referring to Gil et al. (2007) and Tong and Hawley (2009), they did not
investigate the causal effect of perceived quality on other brand equity dimensions.
Consequently, there was a missing link of perceived quality in their research model. By
establishing the causal relationships on greater numbers of brand equity dimensions,
the results indicated brand image had been considered as a construct preceded by
perceived quality. This could be further explained by the theory of cognitive-affective-
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conative, that is, perceived quality was considered as a cognitive construct which
resulted in affective response towards the brand. This affective response had
determined consumer behavior, and lead to product purchase and brand loyalty.
Therefore, in the Malaysian fast food industry, perceived quality would only have
effect on attitudinal brand loyalty and overall brand equity when there was existence of
affective responses towards the brand, such as the subsistence of affective brand image.
The familiarity of brand names could create a favorable brand image which in
the long run led to creation of brand image and brand trust. This was because
consumers were likely to buy a certain product or brand that had a favorable brand
image (Keller, 1998). Accordingly, the familiarity of fast food brand convinced
consumers in term of first brand that appeared in their minds from many existing brand
options in a particular fast food category. Furthermore, greater brand familiarity had
caused consumers to have greater trust due to higher confidence towards the fast food
brand. It included a sense of reduced anxiety, faith in the provider, reduced perceptions
of risk, and knowing what to expect.
In addition, this study also provided evidences for brand image in retaining
brand trust and attitudinal brand loyalty in the Malaysian context of fast food industry.
The combination of the favorability, strength, and uniqueness of fast food brand image
had led to greater affective reactions and less likely to change to a competitor’s brand
(Bowen & Shoemaker, 1998). Thus, it highlighted brand image as a vital antecedent of
brand trust and attitudinal brand loyalty in the context of fast food branding.
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Importantly, trust had a positive impact and also was a key determinant of the
relationship commitment (Morgan & Hunt, 1994). This commitment was directly
proportionate to the consumers’ level of affect, or in general terms, it was based on
how much the customer “like” the service provider (Oliver, 1999). When consumers
were affectively loyal, it became much more difficult for competitors to enact
switching behaviors through counter-argumentation (Oliver, 1997). Therefore, the
trustworthiness of fast food brand had contributed to the most significant causal effect
on attitudinal brand loyalty. It also served as an imperative variable in developing the
linkage between the brand equity dimensions, especially with attitudinal brand loyalty.
As a conclusion, most of the dimensions of brand equity had not influenced
brand equity directly in the Malaysian context of fast food industry. Attitudinal brand
loyalty was the only dimension that had driven brand equity, which was considered as
affirmative attachment or commitment between consumers and the fast food brands.
Lastly, based on the identified causal relationships, the findings highlighted a
sequential process of brand equity formation, which was further explained by the
hierarchy-of-effect theory.
5.5 Conclusion
The proposed model supported the premise that brand awareness and perceived
quality were necessary steps to create brand equity in the Malaysian context of fast
food industry. In addition to that, both brand familiarity and brand trust served as
essential variables in the model. By including brand familiarity, the missing link of
brand awareness was justified as it showed the linkage between brand awareness and
other dimensions. Brand trust was considered important because it was the absolute
variable that was classified as an affective character. Overall, this study presented a
comprehensive set of causal relationships among the dimension of brand equity.
Consequently, it highlighted numerous of compound paths that existed in the model.
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CHAPTER 6
CONCLUSION AND RECOMMENDATION
6.1 Introduction
First and foremost, the chapter starts with the discussion on the research
objectives. Basically, it highlights the relevancy between the findings of this study and
research objectives as discussed in Chapter 1.
Next, the chapter discusses the significant contributions of this study in both
academician and practitioners (fast food managers) area. The chapter explains the
interpretation of consumer-based brand equity model in the Malaysian context of fast
food industry, which indicates the logical explanation of proposed model with the
existing marketing theory such as hierarchy-of-effects theory, Gil et al.’s (2007), and
Aaker’s (1991) brand equity theory.
Remarkably, this study illustrates a practical 4 step brand equity creation for
fast food entrepreneurs, which was derived on the model of this study. Besides, it also
included the usefulness of these research findings in formulating Malaysian
government assistance programmes. Last but not least, the limitations and
recommendations of this study is also presented carefully.
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6.2 Discussion on Objectives
Objective 1: To examine brand familiarity as the additional dimension of consumerbased brand equity in the Malaysian context of fast food industry
Brand familiarity was related positively to the extent to which awareness was
evidence in the brand. Besides, it generated strong effect on both brand image and
brand trust. In addition, it served as a vital variable in explaining the relationships
between brand awareness and other brand equity dimensions as well as overall brand
equity. For instance, the results from the current study indicated that brand familiarity
(direct effect) and brand awareness (via brand familiarity) significantly contributed to
brand image. Furthermore, brand familiarity had high value of squared multiple
correlations (R²=0.54). Thus, it provided strong positive agreement for research
question 1: “Does brand familiarity serve as additional dimensions of consumer-based
brand equity in the Malaysian context of fast food industry?”
Objective 2: To examine brand trust as the additional dimension of consumer-based
In the Malaysian fast food industry, there were only brand image (β=0.31) and
brand trust (β=0.48) which had significantly influenced attitudinal brand loyalty. Brand
trust had contributed higher coefficient beta (β) value than brand image, specifically,
the trust of fast food brand was considered as the most critical affective feeling as
perceived by Malaysian consumers in brand creation. Therefore, the existence of brand
trust provided a better understanding in explaining the relationships among brand
equity dimensions. Furthermore, brand trust had high value of squared multiple
correlations (R²=0.67). As a result, there was positive conformity for the research
question 2: “Does brand trust serve as additional dimensions of consumer-based brand
equity in the Malaysian context of fast food industry?”
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Objective 3: To investigate the causal relationships among dimensions of consumerbased brand equity in the Malaysian context of fast food industry
The third objective of this study was to investigate the causal relationships
among dimensions of consumer-based brand equity in the Malaysian context of fast
food industry. The proposed model was empirically investigated within the context of
fast food industry, along with 10 hypotheses that related to causal effects, were tested
simultaneously. The results highlighted that there were 7 significant causal effects
which existed among brand equity dimensions. Thus, the findings of this study
presented an important answer for research question 3.
Indeed, causal relationships existed among brand equity dimensions, and
interestingly, attitudinal brand equity served as the only variable that linked between
brand equity dimensions and overall brand equity in the Malaysian context of fast food
industry. Practically, the result showed that the creation of brand equity was not an
easy task; it had fulfilled the sequential order of brand elements (cognitive-affectiveconative). Theoretically, the findings supported the existence of causal relationships
among brand equity dimensions. It also highlighted the potential indirect influence of
brand equity dimensions (e.g. brand awareness and perceived quality) on overall brand
equity via other variable(s). This could be supported by the causal effects which were
identified in model simultaneously. Importantly, there was no missing link of causal
effects among the brand equity dimensions. Therefore, the findings provided
meaningful explanation for both academician and fast food manager.
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Objective 4: To develop consumer-based brand equity model in the Malaysian context
of fast food industry
Overall, the proposed consumer-based brand equity model was tested using
structural equation modeling (SEM), which suggested an acceptable Goodness-of-fit
statistics (GOF). Besides, it also satisfied a series of reliability and validity assessments
for measurement as well as structural model. In addition to that, the model showed
greater numbers of brand equity dimensions. The inclusion of brand familiarity and
brand trust had not been investigated by most of the previous researchers (Tong &
Hawley, 2009; Rosa & Riquelme, 2008; Gil et al., 2007; Angel & Manuel, 2005; Yoo
et al., 2000).
Remarkably, the squared multiple correlation (R²) of brand equity dimensions,
such as brand familiarity, brand image, brand trust, and attitudinal brand loyalty were
all above 0.50 value. Besides, the R² of overall brand equity was 0.74, which served as
additional supporting evidence for the development of this model. In addition to that,
the present results supported the proposed model based on psychological consumer
response, explaining the implication of cognitive-affective-conative in consumer-based
brand equity. Thus, the model in this study provided a vital road map for the
implication of branding strategy in the Malaysian fast food industry.
Apart from that, the findings further presented in 4 distinctive steps (see
managerial implication), for the purpose to serve the best understanding of implication
among Malaysian fast food managers. Therefore, the development of model served in
answering the research question number 4: “How do we develop consumer-based brand
equity model in the Malaysian context of fast food industry?”
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6.3 Contribution of Study
6.3.1 Brand Image Measurements
From an academic standpoint, the measurement of brand image had been
specified to a product category (Dobni & Zinkhan, 1990; Kim & Kim, 2005; Low &
Lamb Jr., 2000). Therefore, this study had developed the measurements of fast food
brand image, which assisted in predicting the future performance of fast food brands in
market place, following consumer perceptions. A total number of 13 observed variables
were identified in this study. The result corresponded to the fact that consumers’
knowledge about a place and environment were characterized as cognitive and
affective quality (Burgess, 1978; Hanyu, 1993; Genereux et al., 1983, 1993; Lynch,
1960; Proshonsky et al., 1983; Russel & Pratt, 1980; Russel et al., 1989). As a result,
the cognitive and affective characters of observed variables are presented in Table 6.1.
Table 6.1 Cognitive and Affective Brand Image Measurements
Cognitive Character
Affective Character
• Delicious
• Prompt service
• Free WiFi
• Good customer service
• Variety of choices
• Good value for money
• Convenient
• Widely distributed
• Long history
• Good dining environment
(Relaxing & Exciting)
• Pleasant
(Pleasure)
• A place for social gathering
(Arousal)
• Easy
(Pleasure)
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6.3.2 A Sequential Process of Brand Equity Formation
The main contribution of this research was the development of a theoretical
model which identified the causal relationships among brand equity dimensions within
Malaysian fast food context. Even though several other research were conducted on
brand equity framework in the consumer-goods industry (Norjaya et al., 2007), banking
industry (Norzalita & Norjaya, 2010), entrepreneur perspective (Zainuddin et al., 2009),
small to medium-sized enterprises (Maznah & Mohd Noor, 2010), but there was lack of
research that had been done relating to Malaysian fast food industries.
The present study had applied Gil et al.’s (2007) brand equity model into fast
food context and proposed a modified model that was meaningful, both conceptually
and statistically. Consequently, this research extended the understanding of consumerbased brand equity phenomena and its measurement, by exploring the sequential
relationships between the dimensions of brand equity, along with the enlightenment of
Lavidge and Steiner’s (1961) cognitive-affective-conative.
The model of this study was extended to consumers’ response, which was
highly related to psychological-based approaches associated with the brand information
(Aaker, 1991; Keller, 1993; Loken & Roedder, 1993). The conceptualization of
consumers’ response (attitude) toward the brand had incorporated cognitive, affective,
and conative components, which were extremely similar to the interpretation given by
some scholars to the term brand equity (Grimm, 2005). Referring to the current model,
it was identified with strong synchronous connections among cognitive-affectiveconative, and also had provided a non-missing link of causal effects model among
brand equity dimensions. In other words, this study was successfully extended the
existing brand equity framework by adopting a sequential brand view of each
consumers response phase.
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This study had classified the brand equity dimensions into three different brand
phases, corresponding to Lavidge and Steiner’s (1961) hierarchy-of-effect theory.
Notably, perceived quality, brand awareness, brand familiarity, and cognitive brand
image were considered as cognitive phase, which was related to knowledge. In other
words, it referred to the information, evaluation, and beliefs that were held by
consumers towards the brand (Lavidge & Steiner, 1961).
Recently, Grimm (2005) stated that there was overlapping of attitude
components (cognitive and affective) in relation to the brand knowledge presented in
the paper of Keller (1993). Therefore, the product attribute was consistent with the
operationalization of perceived quality and cognitive brand image, while the
experiential benefits had corresponded to affective brand image and brand trust that
was used in this study (Keller, 1993). As a result, it was relevant to present brand
image as both cognitive and affective characters in this model, which was in line with
Keller’s conceptualization of brand image. Moreover, in most of the branding
discussions, consumer behavior and psychology had appeared to suggest the affective
and emotional usually stemmed from cognitive evaluation (Oliver, 1997; Franzen &
Bouwman, 2001). In other words, cognition appeared first and emotion second. For
example, Franzen and Bouwman (2001, p. 32) stated “it is often assumed that
emotional reactions always stem from cognitive evaluation”. This could be evidenced
in the affective phase of the model, referring affective brand image and brand trust to
feelings, moods, or emotional responses towards brands that were measured by
collecting verbal reports or by physiological responses (Lavidge & Steiner, 1961).
Apart from that, affection action also was judged as an important response that
could not be overlooked. This was because affective reaction was considered as first
reactions, which occurred quickly and automatically, consequently led to information
processing and judgments about the objects, activities, and other stimuli with a direct
and primary role in motivating behavior (Slovic et al., 2002; Zajonc, 1980, 2000).
Some researchers supported that affective response was a direct and primary role in
behavior (LeDoux, 1996; Slovic, Finucane, Peters & MacGregor, 2002; Zajonc, 1980).
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Besides, affective evaluation had taken place without conscious stimulus recognition,
and as a key antecedent of current and future purchases (Esch et al., 2006). Therefore,
affective brand image and brand trust were essential and played as important role in
determining the existence of conative brand phase in the fast food brand equity creation.
As a conclusion, this model viewed brand equity as a three sequential brand
phases, thus the subsistence of cognitive and affective constructs served as prerequisite
for attitudinal brand loyalty and brand equity (conative character). The model was in
line with Aaker’s (1996) implication that product related characteristics (cognitive
elements) could be primary drivers of brand personality. In other words, cognitive
thinking could have taken place first (through functional/utilitarian reason) which then
led to emotional or affective reaction. This in turn had driven to the overall satisfaction
and thus led to individual’s commitment to purchase the brand (conative response) and
subsequently, actual behavior (Oliver, 1993). Interestingly, albeit the dimensions of
brand equity was classified into three brand phases, the model specified that the
dimension(s) from a particular brand phase (cognitive dimension - e.g. brand awareness)
did not necessary indicate a significant direct relationship for the next level of brand
phase (affective dimension – e.g. brand trust). This can be further explained by the
different degrees of cognitive (Frey, 1982), affective (Oliver, 1993) and conative
(Reitan & Wolfson, 2000).
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6.3.3 The Role Brand Familiarity and Brand Trust in Malaysian Fast Food
Industry
The development of consumer-based brand equity in Malaysian fast food
industry is a long-term process; it reflects to the different phases of brand character,
such as cognitive, affective and conative. It also involves greater numbers of brand
equity dimensions, such as brand familiarity and brand trust, which might not play
important roles in other industry. This study is consistent with the observation of
Christodoulides and de Chernatony (2010, p. 61), “a brand equity monitor should
incorporate dimensions that drive value within the specific industry.” For instance,
brand familiarity and brand trust were proven to contribute significantly in the model as
the inclusion had provided a better understanding of consumer response towards the
fast food brands. This could be further explained by both of the dimensions appeared to
be far greater for the situation where the consumer looked for a simple rule for
decision-making (Batra & Ray, 1985). For instance, brand familiarity served as a
source of pleasure and reassurance, which transformed fast food into “comfort foods”
(Schlosser, 2002). Thus, it not only emphasized on the total time spent processing
information about the brand (Baker et al., 1986), but also indicated the direct and
indirect knowledge available to the consumer (Alba & Hutchinson, 1987).
On the other hand, brand trust was created from an exchange environment in
which the fast food brands provided consistent services to its customers across different
outlets (Tan et al., 2011). Therefore, a feeling of security held by the consumer in his or
her interaction with the fast food brand, such that it was based on the perceptions that
the brand was reliable and responsible for the interest and welfare of the consumer
(Morgan & Hunt, 1994).
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6.3.4 Consumer-based Brand Equity Model in Malaysian Fast Food Industry
This study had classified perceived quality, brand awareness, brand familiarity,
and cognitive brand image as cognitive characters. On the other hand, affective brand
image and brand trust were categorized as affective characters, while attitudinal brand
loyalty and brand equity were grouped into conative characters.
This model states that both perceived quality and brand awareness were the
initial stage of brand building in consumer-based context (Alba & Hutchinson, 1987;
Hoyer & Brown, 1990). As noted in literature review, perceived quality was not the
actual quality but the overall customer’s perception of the brand (Zeithaml, 1988).
Positive or negative perceived quality incurred when consumers cognitively processed
the available knowledge between a particular brands with others. On the other hand,
brand awareness was related to capability of prospect buyer to recognize or recall a
particular brand (Aaker, 1991). It could be determined by the ability of potential buyers
who successfully associate a brand with its product category. Thus, perceived quality
and brand awareness had been referred to as the simplest level of cognitive response
that existed in the knowledge of consumers for the brand (Alba & Hutchinson, 1987;
Hoyer & Brown, 1990). For these reasons, it had not made sense neither would cause
the other. It could be further explained that the awareness of fast food brand was not
the prerequisite for the creation of perceived quality and vice versa. Positive perceived
quality could be existed when consumers previously had grateful experiences with the
fast food brand or better perception for a higher price brand. On the other side, brand
awareness could be referred to the recognition of the fast food brand character, such as
the brand name, McDonald’s logo, KFC symbol, or even 1901 Hot Dogs tagline; it did
not necessary related to the quality of the fast food brand.
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Remarkably, the awareness of fast food brand alone was not sufficient in
providing the brand image hold in the consumer’s memory. This was because the
creation of brand image in term of mentality resulted from the brand strength,
uniqueness, favorability, experience, and strong perception of the consumer through
coordination and stimulation (Keller, 2003). Furthermore, image of fast food brand
required ideas, feelings, attitudes, mental constructs, understandings or expectations
that from the brand in the memory of consumers, in other words, it involved greater
association of consumers’ memory than just recalling or recognizing. Apart from that,
the awareness of fast food brand was not considered as increasing consumers’
confidence level in the uncertain environment. However, consumers had felt
comfortable on trusted brand because the brand had long-term relationships with them
(Chiou & Droge, 2006; Flavián et al., 2006; Sichtmann, 2007; Matzler et al., 2008).
Therefore, the familiarity of fast food brand was essential, as it enhanced consumers’
formation process of brand image (Holden & Vanhuele, 1999; Janiszewski, 1993;
Zajonc & Markus; 1982) and feelings of greater trust between the restaurant brand and
the consumers (Lee et al, 2005). These were because brand familiarity had driven to a
sense of reduced anxiety, faith in the provider, reduced perceptions of risk, and
consumers knew what to expect directly. For these reasons, brand familiarity served as
an important role in enlightening the relationships between brand awareness and other
brand equity dimensions in the Malaysian context of fast food industry.
Perceived quality required greater information processing as it focused on
explaining how consumers cognitively had established an overall brand impression,
before reaching a fast food consumption choice. Perceived quality was involved in the
perception of brand’s quality and superiority. The perception could be based on past
experience (Dabholkar, 1995; Donovan et al. 1994) and affective quality signals in
marketing efforts (Grönroos, 1984). Thus perceived quality was sufficient for the
creation of brand image as it involved consumers in developing, maintaining, and
giving meaning to the influence of personal experience of the stimulated brands.
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Brand image, in particular, exercised a strong direct influence on brand trust
and attitudinal brand loyalty. The findings were line with studies which investigated the
effect of brand image on customer’s trust (Esch et al., 2006; Flavián et al., 2006; Yoon,
2002) and brand loyalty (Aaker, 1996; Back, 2005; Kandampully & Suhartanto, 2000;
Kandampully & Hu, 2007; Keller, 1998). Therefore, the image of fast food brand was
considered important because it served as image drivers, such as the association
between the fast food brand and intangible symbolic benefits as perceived by
consumers, which satisfied consumers in term on social class, self-emotional, and any
other perception of needs (Keller, 1993). In addition, the image drivers were also
extended to lifestyle, trustworthiness, and self-concept (Neal & Bathe, 1997).
Besides brand image, brand trust also contributed significantly on attitudinal
brand loyalty, which corresponding to most of the previous findings (Chaudhuri &
Holbrook, 2001; Chiou & Droge, 2006; Flavián et al., 2006; Harris & Goode, 2004;
Matzler et al., 2008; Morgan & Hunt, 1994; Mayer et al., 1995; Sichtmann, 2007).
Specifically, this study defined brand trust as positive emotional feeling and affective
reactions that results from the trusted brand. Therefore, it presented an emotion-driven
aspect (affective character) of long-term relational exchanged between fast food brands
and consumers, rather than the utilitarian value (cognitive character) of the brands.
Importantly, attitudinal brand loyalty played as a key variable for explicating
the relationships between other dimensions and brand equity. In other words, fast food
brand equity would not exist when there was no attitudinal brand loyalty. Nevertheless,
when there was absence of brands’ affective reactions, attractiveness, aesthetics, or
signals of benevolence (affective sense of brand trust), consumers would less likely in
repeat purchase intention, recommendation to others, or willingness to pay a price
premium. Thus, the trustworthiness of fast food brand served as a vital antecedent for
the development of attitudinal brand loyalty, which ultimately drove to overall brand
loyalty.
187
6.4 Managerial Implication
6.4.1 Brand Image Measurements
The brand image measurements provided an opportunity for fast food managers
to improve specified brand image strategies. Specifically, the managers of fast food
restaurant chains can utilize the brand image scales from this study, as a diagnostic
instrument, to examine whether the consumers’ associations towards their restaurants
are in line with the brand’s mission, vision and goals. By identifying the consumers’
association of brand image towards their brand, managers can compare and
differentiate their brands with competing brands from the similar industry.
6.4.2 Steps of Brand Equity Creation in Malaysian Fast Food Industry
The model of this study had provided a useful and applicable guideline for the
development of Malaysian fast food brands. Importantly, it indicated the brand phase,
which was related to different phase of consumers’ response towards the fast food
brands. Thus, it was highly relevant for the implication of marketing research
initiatives, branding strategy, and brand tracking. The consumer-based brand equity
model was simplified into four steps as illustrated in Figure 6.1. It was identified into
step processes as consumers would not jump into attitudinal brand loyalty or brand
equity unless there were existences of brand cognition (brand awareness, perceived
quality, brand familiarity, and cognitive brand image) and brand affect (affective brand
image and brand trust). For this reason, this study had highlighted that each steps was
contingent upon the successful completion of previous step, in line with “branding
ladder” as introduced by Keller (2001).
188
Notes:
BA=Brand awareness, PQ=Perceived quality, BF=Band familiarity, BI=Brand image,
Figure 6.1 Steps of Brand Equity Creation in Malaysian Fast Food Industry
Figure 6.1 showed that the creation of consumer-based brand equity involved
four differentiated steps. Remarkably, each of the preceding steps served as a
prerequisite for the next successful marketing effort. In addition to that, step 1 and step
2 revealed to have impacts on step 4 as identified in compound paths. Therefore, to
create a sustainable and strong brand name in Malaysian fast food industry,
practitioners had to take into consideration that there was no “shortcut”; each of the
steps had to be created and brand building process had be monitored consistently.
189
Step 1: Establishing brand awareness, relatively relevant to a specific product
class
The first step is to make sure that fast food managers had established the most
relevant brand input in consumers’ mind; which clearly had identified the product or
service categories that was offered, as compared to other competitors. Therefore, the
identification of the brand position and category served as a necessity and crucial
marketing plan in creating brand equity.
Accordingly, Keller’s (1998) consumer categorization processes was employed
as the technique in registering a brand in the consumers’ memory. Table 6.2 presented
the general hierarchical fashion of Malaysian fast food industry. Firstly, fast food
managers had to decide on which consumer categorization processes had to be targeted
for brand awareness programs, such as product class information, product category and
product type information. Next, it was followed by the design of programs which
highlighted the visibility of brand information as compared to brands. Consumers had
on top-of-mind and sufficient mind share of a particular fast food brand when there was
a high relevancy of consumer categorization processes along with the marketing efforts.
As shown in the Figure 6.1, the brand awareness influenced brand equity and
other dimensions indirectly, in other words, whatever efforts that had been executed in
increasing the brand awareness had to be in line with the objective of overall brand
equity, for instance fast food category, brand meaning, brand name, logo, symbol,
tagline, and so forth. In addition to that, the design of brand awareness programs had to
be focused on satisfying consumers’ affective needs. That is, fast food managers had to
illustrate the satisfaction on affective response, such as pleasure, relax, excitement, and
arousal, social class, self-emotional, lifestyle, trustworthiness, and self-concept instead
of focusing on food quality.
190
Table 6.2 Consumer Categorization Processes on Fast Food Brands
Product Class
Information
Product
Category
Brand Information
Product Type
Information
McD
All Day
Fried/Baked
Non-Fried
Dessert
Beverage
Breakfast
Fried/Baked
Non-Fried
Beverage
Note:
McD=McDonald’s,
Apple Pie
Breadstick
Burger
Chicken Chop
Chicken Wing
Fish and Chips
French Fried
Fried Chicken
Garlic Bread
Nuggets
Pizza
Popcorn Chicken
Potato Wages
Toasted Twister
Coleslaw
Hot Dogs
Mashed potato
Oriental Rice
Pasta
Porridge
Salad
Soup
Ice Cream
Blended Ice Cream
Egg Tart
Pudding
Shake
Carbonated Soft Drink
Float Drink
Fruit Juice
Hot Drink
Iced Blended Drink
Mock tails
Egg Bun
Hash Brown
Pancake
Sausage Patty
Scrambled Egg
Toasted Twister
Porridge
Hot Drink
KFC=Kentucky
Mb=Marrybrown, 1901=1901 Hot Dogs
191
Fried
KFC
Ph
Mb
1901
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
Chicken,
Ph=Pizza
Hut,
These could be supported in cognitive psychology, as memory was considered
very durable (Keller, 1993). Things that were stored in memory tended to stay there for
a long time (brand category, brand meaning, brand name, logo, symbol, tagline,
illustration of affective response). Besides, brand awareness had to be the most
important use of heuristics (the simplifying strategies) where consumers tended to
choose a well-known brand as it facilitated the choice process. As a result, consumers
displayed a tendency to accept more advertising repetition by a familiar brand than
from an unknown or unfamiliar brand. Thus, pioneer brands always had tremendous
advantages when it came to conquer the permanent positive memory codes. Therefore,
building the highest possible degree of brand awareness had been based on targeted
category of new fast food brands as it ensured the successfulness of marketing efforts.
Step 2: Creating constructive brand cognition
Basically, there are three dimensions that needed to be focused by fast food
managers, namely brand familiarity, perceived quality, and cognitive brand image.
Stage 2 served as a role in creating constructive brand cognition. Fast food managers
had to provide not only positive, but constructive inputs for consumers regarding their
fast food information. According to Heding et al. (2009), memory was activated by a
sensory input and thus would start the spreading activities. Thereby, knowledge was
retrieved from memory; knowledge in memory consisted of nodes and was structured
into associative networks, where nodes are the stored information connected by link in
associative networks (Heding et al., 2009). The nodes vary in strength; some
associations are stronger than others. Subsequently, fast food managers had to “supply”
a constructive set of input about their brands for the purpose of creating a meaningful
set of associative networks. The main reason was to avoid the fast food brands from
establishing an indistinguishable brand meaning, consequently which could lead to the
difficulty in creating strength, favorability, and uniqueness of their brands as associated
by consumers.
192
As discussed previously, the awareness of fast food brands transformed brand
familiarity before it was sufficient for further association in consumers’ mind. In other
words, stage 1 served as the most important stage to identify the level of brand
familiarity that existed in consumer’s memory. As a result, there was necessary for fast
food managers to maintain the consistency of brand exposure from time to time, this
was because in cognitive consumer research, repeated exposure to an advertising
message was considered very important (Baker et al., 1986). Furthermore, the exposure
should be designed in a constructive, understandable and meaningful flow of
information with respect to the brand, which implicitly drove to the enhancement of
consumers’ association on brand image and brand trust.
Positive quality perception served as a very important role in establishing a
strong brand image. This was because positive perception formed a strong interactive
relationship with customers. In Malaysian fast food industry, managers had to be
cautious on the appraisal of service performance as consumers had different
expectation on the nature operation, for instance prompt services, handling complaints,
individual attention, and willingness to help. As a result, the effectiveness and
efficiency of services quality was an important aspect (Lane & Dupre, 1997). Apart
from that, Gregoire and Spears (2007) stated that fast food, also referred to as limitedservice, limited menu or quick service which was designed to provide a limited number
of food items to a customer in a relatively short period of time. Therefore, perceived
quality could be created by providing fast service with the minimum of waiting time.
Interestingly, food quality and restaurants appearance were associated as brand
image instead of perceived quality. As a result, fast food managers emphasized on
variety of choices, good value for money, and good dining environment, for the
purpose of creating strong brand image. Besides maintaining the food quality; fast food
managers also had to consider the consumers’ willingness to pay for the food when
compared to other fast food brands. In addition to that, fast food managers had to focus
on the concept design of “good dining environment” for the store renovation. There
had been no value added if the expenditure only focused on the physical appearance. In
193
this stage, fast food managers had to make sure consumers could associate their brands
into cohesive and meaningful mental networks, which corresponded to the “spreading
activity” of the brand node as explained by Heding et al. (2009). An example of
spreading activity might be the word “McDonald’s”. The retrieval of the node
McDonald’s triggers a spreading activity that potentially could look like Figure 6.2.
This association could continue in all directions until they had lost relevance for the
node McDonald’s.
image.
Source: Adopted and modified Aaker’s (1996) mental network
Figure 6.2 Mental Network of McDonald’s
194
Step 3: Eliciting encouraging brand affect
In this step, fast food managers focused on affective brand image and brand
trust. According to Eagly and Chaiken (1993), affective responses ranged from
extremely positive to extremely negative and could be located on an evaluative
dimension of meaning. In addition to that, when consumers are affectively loyal, it
becomes much more difficult for competitors to enact switching behaviors through
counter-argumentation (Oliver, 1999). In other words, it was highlighted that a fast
food brand had been generally (rarely) accepted by consumers when there was
existence of positive (negative) brand affect.
Step 3 was highly depended on step 1 and step 2 (flow of effects). If there were
no strong fundamentals of step 1 and step 2, for instance a consumer was not aware and
familiar about brand A, or did not have any idea about the quality of brand A.
Undoubtedly, the consumer had not associated a clear image and trust value of the
brand. However, step 3 was considered important as it transformed beliefs and
knowledge about the fast food brand to affective quality in an encouraging way.
The main role of Step 3 was to encourage consumers to have brand affect
proactively. Affective response could be motivated by illustrating the superiority of
affective feeling, such as arousing, pleasant, exciting and relaxing as defined by Russell
(1980). For instance, McDonald’s introduced “I’m lovin’ it” campaign in year 2003,
together with this campaign, various contests and programs had been carried out to
encourage the brand affect of McDonald’s. Thus, in order to have a great affective
brand image, fast food managers could have planned for a long-term theme campaign,
along with the campaign title; sub-topic could be launched to proactively encourage
affective response of consumers. Besides, fast food managers had to ensure that there
were high consistency of brand reliability, credibility, operational, and serviceability
across different outlets as these had contributed to the creation of affective brand image
and brand trust.
195
Step 4: Forming longevity brand conation
The last step was the most critical and crucial step for a creation of fast food
brand equity. According to Kotler, Keller, Ang, Leong and Tan (2009), acquired new
customers can cost five times more than the costs involved in satisfying and retaining
current customers. When a consumer was classified as attitudinal loyalty, he or she had
exhibited a brand-specific commitment (Oliver, 1999). Attitudinal brand loyalty existed
as formation stems from an affirmative attachment and commitment between
consumers and brand. Subsequently, this attitude, in turn, occurred from the
coincidence between the consumers’ preferences and the brand. The attitudinal brand
loyalty and brand equity (brand conation) could be formed by increasing the longevity
of the relationship between consumers and the brand. That is, the more involved the
brand was with a consumer, the more likely the brand was to stick around with him/her.
Consequently, the relationship between the brand and the consumer could be
incessantly retained from time to time, along with efforts from step 1 to 3.
For brand managers, focusing on brand image and awareness was usually seen
as central to the success of marketing campaigns. However, the creation of brand
equity required beyond brand image and brand awareness, which in line with Esch et al.
(2006). As indicated by Keller’s (2001) branding ladder, relationship was the key for
long-term brand success. Therefore, customer loyalty programs such as frequency
programs, club marketing programs or gift card programs had been based on the
element of longevity, focused on long-term relationship between the fast food brand
and consumers. Fast food managers had designed loyalty programs based on the brand
relationship quality as recommended by Fournier (1998), namely love/passion, selfconnection, commitment, interdependence, intimacy, and brand partner quality. These
six facets were identified as influencing the durability and quality of the relationship, as
it illustrated the characteristic of the human relationships, and the way that connected
the brand with the identity of the consumers’ live experience (Heding et al., 2009).
196
6.4.3 Formulation of Government Assistance Programmes
There were numerous numbers of government assistance programmes which
had been conducted by the Ministry of Domestic Trade, Co-operative and
Consumerism (KPDNKK) and Ministry of International Trade and Industry (MITI) to
help the local entrepreneurs to promote their brands (Ministry of Domestic Trade,
Cooperative and Consumerism [MDTCC], 2011b).
Most of the programmes were based on traditional marketing, such as
packaging (Small and Medium Enterprise Corporation Malaysia [SME Corp. Malaysia],
2011b), business management (Ministry of International Trade and Industry [MITI],
2011), financial assistance (Perbadanan Nasional Berhad [PNS], 2011), and
collaboration with external parties, for instance Carrefour, Giant, Jusco, Mydin, Tesco,
The Store, Sunshine and Limkokwing University of Creative Technology (SME Corp.
Malaysia, 2011a; MDTCC, 2011a). In other words, the nature of the Malaysian
government assistance programmes were focused on providing advisory services,
market access, infrastructure facilities, financial assistance, and business and
networking opportunities (Performance Management & Delivery Unit [Pemandu],
2012).
Nevertheless, educating entrepreneurial among existing entrepreneurs and
future entrepreneurs was critical because knowledge was the most valuable resources to
achieve sustainable competitive advantage (Akio, 2005; Alvarez & Busenitz, 2001;
Foss, Klein, Kor & Mahoney, 2008; Liu, 2006; Mathews, 2002; Ong, Hishamuddin &
Yeap, 2010). Therefore, in order to formulate a better government assistance program
in the fast food branding, the program should be based on the understanding of
consumer-based brand equity model, directed to the development of fundamental
knowledge among local entrepreneurs.
197
Table 6.3 Examples of Branding Tools based on Brand Equity Dimensions
Brand equity dimensions – Cues
Examples of Branding Tool
Perceived quality
• Rely on 1 or 2 cues that associate with • Total Quality Management (TQM)
quality that consumers are looking for • Quality Function Deployment (QFD)
• Service quality – SERVQUAL
• Supportive culture
• Rely on 1 or 2 cues that associate with
quality
• Quality packaging
Brand awareness
• Enhancing consumer’s ability to • Coupon discounts
retrieve the brand from memory when • Creative packaging
given the product category
• Events sponsorship
• Funny/humor advertising
• Logo
• Publicity
• Road show
• Sample
• Symbol
• Target marketing
Brand familiarity
• Greater the amount of time to improve • Brand souvenir
consumers memory towards the brand • Promotion set meal
• Creating consistency
• Seasonal promotion/product
• Single core product promotion – Anytime
• Special collection –Mascot
• Tagline
Brand image
• Indicating favorability, strength, and • Breakfast/lunch/dinner/supper promotion
uniqueness of brand associations
• Celebrity endorsement
• Demonstrating an advantage
• Cooperative advertising
• Looking to the core identity
• Widely distribute
• Innovative packaging
• Movie/song/drama sponsorship
• Standardization of store image
• Trade shows
• Value-based pricing strategies
198
Table 6.3 Examples of Branding Tools based on Brand Equity Dimensions
(Continued)
Brand equity dimensions – Cues
Examples of Branding Tool
Brand trust
• Analyzing consumers’ feedback – After
• Encouraging consumers’ positive
sales service
emotional feelings and affective
• Customer relationship management
reactions
(CRM)
• Standard operating procedures
• Forming long-term commitment and • Customer clubs
purchase intention
• Database marketing
• Frequent-buyer programs
• Loyalty segmentation
• Refunds/rebates
Local fast food entrepreneurs had to equip themselves with the ideology of
brand equity creation. Importantly, there were no “shortcut” branding (Keller, 2001;
Tan et al., 2011), each of the steps had to be created and brand building process should
be monitored consistently (see Figure 6.1). For these reasons, the characteristic for each
of the brand equity dimensions had to be communicated clearly. Consequently, they
would response to the market changes independently and not have the mindset of
depending on the supported facilities from the government. That is, they should aim to
become knowledge entrepreneurs and be more proactive to fast food market changes.
As a result, local fast food entrepreneurs would have their own blueprint for brand
equity creation. This was because they had the ability to identify the antecedents and
consequences of brand equity dimensions, thus planed the branding tools which in line
with the direction or objective of the whole branding strategy. Besides, these findings
also contributed to the Entry Point Projects 5 (EPP 5) of National Key Economic Areas
(NKEAs), which increases the standard of professional management among the of
local food entrepreneurs by polishing their brand management skills (Pamandu, 2012).
199
For instance, With reference to Table 6.3, several examples of branding tool
were identified from the dimensions of consumer-based brand equity. Thus, local
entrepreneurs had a better direction for the planning of branding strategy. Importantly,
Local fast food entrepreneurs designed their own branding tools, which were in line
with the dimensions’ cue. As a conclusion, this study had served as an important input
for the formulation of government assistance programmes. It provided a solution for
assistance programmes, highlighted alternative approach for the growth of Malaysian
fast food brand, which was based on the development of fundamental knowledge
among local entrepreneurs.
6.5 Limitation and Recommendation for Future Study
Several limitations were recognized in this study, each of the recommendations
for future study is illustrated. First, there were a total number of 13 items of brand
image which had been identified from preliminary study, but, only 5 observed variables
had been used in the proposed model after the purification process. Therefore, in future
research, there is a need to cover greater number of observed variables in the model,
which could provide a clear definition and operationalization of cognitive and affective
brand image in the Malaysian context of fast food industry.
Although this study proposed the research model based on extensive reviewed
of previous literature and reliable theoretical framework, cross-sectional data might
have had limited the detection of causal inferences (Hair et al, 2010). Therefore, a
longitudinal study should be designed, which was often used in psychology, involved a
series of observations made over long period of time. Future research could explore the
possibility of a longitudinal study through repeated observations, and invariance test
across different samples should be conducted to make certain the components of
measurement model and structural model are remained equivalent. Consequently, it
would yield more insightful results than a cross-sectional observation study.
200
Besides, the sample was not chosen at random as the sampling frames of fast
food consumer were unknown. As a result, there was an existence of inherent bias in
convenience sampling as the sample was unlikely to represent the population being
studied. This undermined the findings to make generalizations from this study to the
population. Furthermore, the sample was made up of volunteers, and then it was likely
to be biased because the volunteers might be actively supporting their views towards
the survey.
Despite greater variance explained in the full structural model of brand equity
compared to previous research, there were still some proportions of the variance which
are left unexplained. Beyond cognitive-affective-conative attitude research, there was a
need to explore the broader information-processing implications, including the
contextual effects (Norris & Colman, 1992; Page, Thorson & Heido, 1990), consumer
psychology (Bettman, 1979, 1986) and elaboration likelihood model (Petty &
Cacioppo, 1986b).
Recently, there had been attempts to understand the interaction process between
cognition-affect in branding (Agarwal & Malhotra, 2005; Grimm, 2005). In
consumption/satisfaction studies, there could be several possibilities of sequence
between cognition and affect. For example, emotion (affect) can appear first and
cognition second or vice-versa. In other words, dual processing might have existed
(Oliver, 1997; Franzen & Bouwman, 2001), and nonrecursive model could be derived.
Even in most of the time, nonrecursive model seemed to have problems with statistical
identification (Hair et al., 2010), but we could not have undervalued the justification of
consumer psychology. As a result, future research should focus on nonrecursive model
with theoretical justified and investigate the relationships simultaneously.
201
Besides, current study did not investigate the indirect effects and mediating
variables. A mediating effect was created when a third variable/construct intervenes
between two other related constructs (Bacon et al., 1995). Traditionally, Sobel test was
conducted for the purpose of measuring mediation or indirect effects as it was very
conservation (MacKinnon, Warsi & Dwyer, 1995). However, the proposed model was
more meaningful if the indirect effect could be conducted simultaneously in a path
diagram. Thus, bootstrapping from Shrout and Bolger (2002) was proposed as this
method could involve multiple mediations.
In term of moderation effect, numerous consumer-studies have shown that there
are indeed differences in terms of cognitive processes as well as behaviors between the
two genders (Fisher and Dubé, 2005; Meyers-Levy, 1988, 1989; Meyers-Levy and
Maheswaran 1991; Meyers-Levy and Sternthal, 1991). According to Moutinho and
Goode (1995), who conducted a study on the automobile industry, males were found to
be more loyal toward the automobile brands when it comes to making purchases. On
the other hand, Meyers-Levy and Maheswaran (1991) revealed that female consumers
paid more detailed attention on brand information compared to their male counterparts,
and thus resulting in different levels of brand awareness across gender, based on
Selectivity Model (Darley and Smith, 1995; Walsh and Mitchell, 2005; Handlin, 2007).
In addition to this, ethnic groups might play as a moderator as Burton (2002) had
indicated that ethnic minority market offers significant marketing potential. Besides,
Chien (2007) had stated there were variations of brand loyalty, perceived quality, and
brand image across the age groups, and educational level was appeared to influence the
level of brand awareness. As a result, future study should consider the potential effect
of moderating variables in the development of brand equity model, which have not
been investigated in this study yet.
202
6.6 Conclusion
All the objectives of this study were accomplished. Both brand familiarity and
brand trust were proven to serve as additional dimensions of consumer-based brand
equity. Besides, most of the causal relationships were significantly identified. As a
result, this study had successfully developed consumer-based brand equity in the
Remarkably, this study was in line with the theory of cognitive-affectiveconative, which classified perceived quality, brand awareness, brand familiarity, and
cognitive brand image as cognitive characters. On the other hand, affective brand
image and brand trust were categorized as affective characters, while attitudinal brand
loyalty and brand equity were grouped into conative characters. Attitudinal brand
loyalty played as a key variable for explicating the relationships between other
dimensions and brand equity. In other words, brand equity had not existed when there
was no attitudinal brand loyalty.
In term of managerial implication, the finding of proposed model was
simplified into four steps, each steps was contingent upon the successful completion of
previous step, in line with “branding ladder” as introduced by Keller (2001). Lastly, it
provided a vital input for government assistance programmes in developing the
fundamental knowledge of branding strategy among local entrepreneurs.
203
APPENDIX
Appendix A: Identified Brand Image Items (Preliminary Study)
Number of Mentioned
Delicious
33
Easy and fast
25
17
Pleasure
14
Free WiFi
13
11
10
8
Free refill
7
Convenience
7
Widely distributed
4
Affordable price
1
Famous
1
Happy meal
1
Toys
1
Rubbish food
1
Oily
1
Burger
1
Fries
1
Crunchy
1
Ice-cream
1
Coke
1
Wings
1
Whipped potato
1
Soft drink
1
Spicy
1
Pizza
1
Nugget
1
204
Appendix A: Identified Brand Image Items (Preliminary Study) (Continued)
Number of Mentioned
Bun
1
Float
1
Big Mac
1
Sundae
1
Chicken
1
Wedges
1
Chili source
1
McFlurry
1
Finger
1
Cheese wedges
1
Original chicken
1
Big chicken
1
Cheese
1
Pineapple pie
1
Potato
1
Vegetable
1
Pineapple
1
Chicken frigs
1
205
Appendix B: Schedule of Data Collection
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
1-Apr
2-Apr
3-Apr
Location: Suria KLCC
4-Apr
5-Apr
6-Apr
7-Apr
Ph
8
1901
25
Ph
8
1901
25
Ph
9
1901
25
8-Apr
9-Apr
10-Apr
Location: Mid Valley Megamall
Ph
4
1901
15
Ph
4
1901
15
Ph
4
1901
15
Ph
4
1901
15
Ph
3
1901
5
Ph
3
1901
5
Ph
3
1901
5
11-Apr
12-Apr
13-Apr
14-Apr
15-Apr
16-Apr
17-Apr
Location: Berjaya Times Square Shopping Mall
McD
4
Mb
15
McD
4
Mb
15
McD
4
Mb
15
McD
4
Mb
15
McD
3
Mb
5
McD
3
Mb
5
McD
3
Mb
5
18-Apr
19-Apr
20-Apr
21-Apr
22-Apr
23-Apr
24-Apr
Location: Jusco Metro Prima Shopping Centre
KFC
8
Mb
15
KFC
8
Mb
15
KFC
9
Mb
15
Mb
15
Mb
5
Mb
5
Mb
5
25-Apr
26-Apr
27-Apr
28-Apr
29-Apr
30-Apr
1-May
Location: Sungei Wang Plaza
KFC
5
McD
20
KFC
5
McD
20
KFC
5
McD
15
KFC
10
McD
20
Location: Pavilion KL
KFC
17
Pizza
17
KFC
17
Pizza
16
KFC
16
Pizza
17
Note:
1.Number (e.g. 12, 11, 25…) = Total numbers of respondents
2.McD=McDonald’s, KFC = Kentucky Fried Chicken, Ph=Pizza Hut, Mb=Marrybrown, 1901=1901
Hot Dogs
206
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LIST OF PUBLICATIONS
Journal:
[1]
Tan, T. M., Devinaga, R., and Hishamuddin, I. (In press). The Common Challenges of Brand
Equity Creation among Local Fast Food Brands in Malaysia. International Journal of Business
and Management, 8(2).
[2]
Tan, T. M., Liew, T. W., William L., Michelle, O. S. F. and Tan, S.-M. (2012). Consumerbased Brand Equity in the Service Shop. International Journal of Marketing Studies, 4(4), 6077
[3]
Tan, T. M., Hishamuddin, I. and Devinaga, R. (2012). Malaysian Fast Food Brand Equity. LAP
LAMBERT Academic Publishing, Saarbrücken, Germany.
[4]
Devinaga, R. and Tan, T. M. (2012). Review of Credit Guarantee Corporation Malaysia
(CGCM) Initiatives to Enhance Small and Medium Enterprises Performance. International
Journal of Business and Management, 7(20), 101-111.
[5]
Tan, T. M., Tan, S.-M., William L., Michelle, O. S. F. and Liew, T. W. (2012). Does brand
equity model vary between female and male? Result of an empirical investigation. International
Journal of Research in Management, 2(3), 1-15.
[6]
Tan, T. M., Hishamuddin, I. and Devinaga, R. (2011). Hierarchical chain of consumer-based
brand equity: Review from the fast food industry. International Business & Economics
Research Journal, 10(9), 67-80.
[7]
Tan, T. M. and Devinaga, R. (2011). A review of online trust branding strategies of financial
services industries in Malaysia and Australia. Advances in Management and Applied Economics,
1(1), 125-150.
[8]
Kogilah, N., Devinaga, R. and Tan, T. M. (2011). The adoption and concerns of e-finance in
Malaysia. Electronic Commerce Research, 11, 383-400.
[9]
Devinaga R. and Tan T. M. (2010). A theoretical review of improving self service effectiveness
using customer feedback at commercial banks. European Journal of Economics, Finance and
Administrative Sciences, 23, 149-160.
Conference:
[1]
Tan, T. M., Hishamuddin, I. and Devinaga, R. (2011, Dec 10-13). The importance of indirect
effects in restaurant brand equity research. Proceedings of the 1st World Research Summit for
Tourism and Hospitality Conference, Hong Kong Polytechnic University School of Hotel and
Tourism Management, Hong Kong.
235

(2012). An Empirical Study on Brand Equity in Malaysian Fast Food

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Aeropostale - Super Brands