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Executive
Summary
Marketing Mix Elements Influencing
Brand Equity and Brand Choice
Tanmay Chattopadhyay, Shraddha Shivani and Mahesh Krishnan
This study develops and empirically tests a model for determining the determinants
and effects of brand equity for the Indian passenger car market. Towards the same,
the Brand Equity Creation Model developed by Yoo, Donthu and Lee (2000) was
expanded and combined with the Brand Choice Model developed by Erdem, et al
(1999). The dimensions of brand equity were thought to affect Overall Brand Equity,
which in turn affected the final brand choice made by the consumers. The effect that
ten selected marketing activities had on the dimensions of brand equity was examined. The passenger car market was differentiated on the basis of the price of car as
premium, volume, and economy type and shopping centre intercept survey was
conducted to collect respondent data across ten centres throughout the country.
Multiple time passenger car buyers were considered as the respondent base for the
study. A total of 1,932 consumers were contacted and 302 valid responses were received. Structural Equation Model was used as the tool for analysis.
The results showed that:
• Of the ten marketing mix elements considered, some had a very strong impact
on brand equity because they positively impacted both the dimensions considered for the study.
• However, contrary to what many previous studies reported, country of origin
and price promotion did not impact the brand equity for such consumers.
• Advertising frequency is not a builder of brand equity; word-of-mouth is a better
determinant of brand equity for repeat passenger car buyers.
KEY WORDS
Brand Equity
Marketing Mix Elements
Brand Choice Probability
Passenger cars
The different results obtained in this study vis-à-vis those from earlier studies suggest that the cultural differences between consumers of two countries mediates the
effect of the marketing efforts on brand equity creation. Again since each of the
dimensions of brand equity under this study was found to positively impact brand
choice, it has been posited that the probability of the consumers choosing the final
brand is increased with an increase in the equity of the brand. Geographical limitation of the sample and absence of interaction of marketing mix elements amongst
themselves were identified as some of the key limitations of the study.
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
67
M
arketing strategy is often considered the most
important means of establishing brand equity. Over the years, a large number of studies have explored how various marketing mix elements
affect brand equity. This study combines the established
models of Brand Equity Creation to examine the relationship between marketing activities and brand equity
for passenger cars in the Indian market. Brand equity
endowments come from the current or potential consumer learning which influences how the product is
encoded and acted upon by consumers. It stands to reason that such learning is dynamic and influences consumer choice processes and outcomes, either directly or
indirectly, by being influenced through the effectiveness
of the branded product’s marketing mix elements. This
work considers consumer choice as an outcome of brand
equity and tries to analyse the effect different marketing mix elements might have on consumer’s final brand
choice.
RELEVANCE OF THE STUDY
Compared to the previous studies, the authors explore
more detailed marketing practices, and not just the broad
marketing activities (the 4 P’s), to enhance the explanatory power of the brand equity phenomenon. None of
the earlier studies differentiated the first-time buyers
from the multiple-time buyers. Since, most of today’s
consumers are multiple-time buyers of some product
categories, the findings from this research should interest both the practitioners as well as the academics. Further, although considerable research has investigated
how to employ marketing efforts to build brand equity,
almost all the previous studies have focused mainly on
the American and the other Western countries’ consumers’. Since consumers in different parts of the world vary
in their attitudes and opinions concerning marketing
activities (Dawar and Parker, 1994), results from those
studies might not be suited for consumers in other countries having different culture and consumer behavior,
such as the consumers in emerging markets. Lastly,
while the outcome of building brand equity is manyfold, like brand extension (Susan Mc Donald, 1990), ability of the brand to charge a price premium (Srinivasan,
Park and Chang, 2005), and incremental cash flow
(Simon and Sullivan, 1993), a major advantage of building brand equity lies in influencing the consumer choice
decisions (Erdem, et al, 1999). This relationship of brand
equity and choice seems to be poorly researched, especially in the area of consumer durables. This study would
address these gaps in the existing literature.
CONCEPTUAL FRAMEWORK
Figure 1 exhibits our conception of brand equity, which
is in fact an extension of the model proposed by Yoo,
Donthu and Lee (2000). They expanded the model of
Aaker (1991) and placed a separate construct called
brand equity, between the dimensions of brand equity
and value for the customer and the firm. The brand equity construct showed how individual dimensions were
related to brand equity. Marketing activities were assumed to have significant effect on the dimensions of
brand equity and hence, marketing activities were added
as antecedents of brand equity in the model. We have
extended the model proposed by Yoo, Donthu and Lee
(2000), adding consumer choice due to the marketing
activities as an effect of brand equity. Investigating the
antecedents—dimensions—effect linkage is the objective
of this research.
LITERATURE REVIEW
Brand Equity and its Dimensions
According to Aaker (1991), brand equity is a multidimensional concept. It consists of brand loyalty, brand
Figure 1: Conceptual Framework of Brand Equity
Brand
Choice
Consumer Perception
developed by
Marketing Efforts
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Dimensions of
Brand Equity
Brand Equity
Value Perceived
by Consumer
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
awareness, perceived quality, brand association, and
other proprietary brand assets. Other researchers have
also proposed similar dimensions. While some researchers have proposed brand loyalty and brand associations,
Keller (1993) suggested brand knowledge, comprising
brand awareness and brand image. Perceived quality
has been defined as consumer’s subjective judgment
about a product’s overall excellence or superiority. Brand
loyalty is a deeply held commitment to re-buy a preferred product or service consistently in the future. Loyal
customers have been found to show more favourable
response to a brand than non-loyal customers. Brand
association has been defined as anything linked in the
memory of the consumers to a brand, while brand awareness has been defined as accessibility of the brand in the
customer’s memory (Chattopadhyay, Shivani and
Krishnan, 2008). Brand awareness along with strong
brand association forms a strong brand image. Brand
association, which results in high brand awareness, is
positively related to brand equity as it can be a signal of
quality and may thus help the buyer consider the brand
at the point of purchase.
Analysis by Erdem, et al (1999) showed that the brand
equity concept might be understood better if examined
in a broader framework that assesses the incremental
effect of the brand across the various stages of the consumer’s choice process. Thus, brand equity plays a role
in how information is learned and then retrieved and
used in making the choice. Information processing effects influence choice set generation and finally the decisions used in making the final choice. This broader
definition extends the aggregate conceptualization inherent in the “additive” brand impact notion of brand
equity to a more comprehensive approach that focuses
on the brand’s role across the dynamic consumer choice
processes.
Theoretical Framework
In order to generate meaningful research results for examining consumer attitudes towards marketing strategies of passenger cars, the proposed theoretical
frameworks and findings from previous studies were
analysed and a modified model was developed. Aaker
(1991) formulated the proposal of brand equity, defining it as a set of assets and liabilities linked to a brand
that create value for both customers and the firm. Aaker
(1991, 1996) also suggested that each brand equity diVIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
mension can be achieved by a variety of marketing strategies.
Based on Aaker’s concept, Yoo, Donthu and Lee (2000)
created the Brand Equity Creation Process Model to systematically examine the relationship among marketing
efforts, brand equity dimensions, and brand equity.
Their model was an extension of Aaker’s proposal which
indicated that marketing activities had significant effects
on brand equity dimensions, which in turn created and
strengthened the equity. Thus, the relationship between
marketing activities and brand equity is mediated by
these dimensions. The study proved that significant relationship exists amongst the dimensions themselves.
As one of the first studies of its kind, this model provided a good starting point for further research on the
linkage between marketing activities and brand equity.
Since the Brand Equity Creation Process Model developed by Yoo, Donthu and Lee (2000) has been modified
and expanded in this study to explore the relationship
of marketing activities with brand equity and finally with
brand choice in the passenger car market, the relationship between marketing efforts and brand equity would
also be one of the primary focus of this study.
In this study, we have put together the model proposed
by Yoo, Donthu and Lee (2000) and the one proposed
by Erdem, et al (1999) to get a common model predicting consumer brand choice as an effect of the marketing
mix variables. When Yoo, Donthu and Lee’s Brand Equity Creation Process Model was applied in this study,
more marketing activities (like peer recommendation,
event sponsorship, celebrity endorsement, and country
of origin) were added to enhance the explanatory power
of the brand equity phenomenon. In line with the work
by Erdem, et al (1999), we estimated a pure brand choice
model, ignoring the issues of quantity choice and inventories.
THE APPROACH
In line with the works by Desarbo and Manrai, 1992;
Kirmani, Sood and Bridges, 1999; and Park, Milberg and
Lawson, 1991, we distinguished between three types of
automobiles: premium brands, volume brands, and
economy brands and applied the classification to the
Indian market. Accordingly, we defined prestige brands
as brands which are priced greater than Rs. 9 lakh (20,000
USD); volume brands as brands priced between Rs. 5
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lakh-9 lakh (11,000 USD-20,000 USD) while economy
brands priced at less than Rs. 5 lakh (11,000 USD). All
the prices considered were ex-showroom, New Delhi as
on March 2008. Prestige brands have a high status symbol. These brands usually have a relatively small market share and are purchased to communicate wealth,
status, and exclusivity (Bagwell and Bernheim, 1996;
Park, Millberg and Lawson, 1991). Volume brands are
usually priced near the market average and economy
brands are sold in the low-end of the market.
RESEARCH HYPOTHESES
Throughout the study, we examined the perceived as
against the actual marketing mix elements for two reasons — first, it was not feasible to control the actual
marketing mix elements in the study; second, perceived
marketing efforts play a more direct role in consumer
psychology than actual ones. Actual marketing actions
cannot change consumer behaviour unless consumers
perceive them to exist. Objective or actual marketing
efforts have been conceptualized differently by consumers from perceived marketing efforts; actual efforts
have been encoded by consumers to be “expensive” or
“cheap” (Olson, 1977). Consumers are not likely to remember the actual marketing efforts like prices, even at
the point of purchase (Dickson and Sawyer, 1990) nor
are they expected to know many of the marketing mix
elements that are done by different brands (advertising
spends, number of dealers, etc) .
Marketing Mix Elements and Brand Equity
Our model proposes that the effects of marketing activities are mediated by the dimensions of brand equity.
To examine this relationship, we first had to investigate
and determine the relationships between marketing activities and brand equity dimensions. We investigated
consumers’ perceptions on ten selected marketing elements—price, store image, distribution intensity, advertising frequency, celebrity endorsement, price promotion, non-price promotions, event sponsorship, countryof-origin and word-of-mouth (WOM) recommendation.
The selected factors do not embrace all types of marketing efforts, but are representative enough to demonstrate
the relationship between marketing efforts and the dimensions of brand equity.
Amongst the four dimensions of brand equity, we have
considered perceived quality and brand awareness as
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the dimensions to be studied. Since we have clubbed
passenger cars as premium, volume, and economy and
also since consumers can upgrade from a low end version of passenger cars towards the upper end version,
brand loyalty was not studied as one of the dimensions.
Further, in line with the study of Yoo and Donthu (2000),
we did not study brand association as a separate dimension and combined brand association and awareness as
one dimension — brand awareness — because brand
association relied on the establishment of brand awareness (Aaker and Alvarez del Blanco, 1995). The effects
of each of these dimensions on brand choice were also
measured in the study.
Price
H1. The perceived quality of a brand is related
positively to the extent to which the price of the
brand is perceived to be high. Price premia being
a proxy for elasticity of demand, this in turn, is a
measure of brand perceived quality. Price premium reflects the brand’s ability to command a
price higher than its competitors. The price premium construct is consequently important for all
types of brands, despite their actual positioning
within a category (Chattopadhyay, Shivani and
Krishnan, 2009).
Prestige brands have a high status symbol because of
higher pricing. Volume brands are usually priced near
the market average and have relatively high market
shares. Finally, economy brands are sold in the low-end
segment of the market. These brands are more affordable and hence have the highest share amongst different brackets of cars in India. From the literature, we did
not find any relationship between price and brand
awareness.
Distribution Intensity
H2A: Perceived quality of a brand is related positively to the extent to which the brand is available in stores.
H2B: Brand awareness is related positively to the
number of outlets for the brand.
Distribution is defined as intensive when products are
available in a large number of stores in the market. It
has been argued that certain types of distribution fit certain types of products. Consumers are expected to be
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
more satisfied, when a product is available in a greater
number of stores. Intensive distribution reduces the time
the consumers spend searching for the stores and travelling to and from the stores, provides convenience in
purchase, and makes it easier to avail services of the
products bought. The increased value results mostly
from the reduction of sacrifices the consumers must
make to acquire the product (Yoo, Donthu and Lee,
2000). Accordingly, increased distribution is likely to
develop a positive perceived quality of the consumer
towards the product. Distribution intensity helps develop brand awareness and recognition (Smith, 1992).
A wide variety of possible distribution channels can
improve the awareness of brands amongst potential consumers. Thus, on the basis of the literature cited above,
the above hypotheses was proposed.
Store Image
H3A: Perceived quality of a brand is related positively to the extent to which the brand is distributed through stores with a good image.
H3B: Brand awareness is related positively to the
extent to which the brand is distributed through
stores with a good image.
Store image encompasses characteristics such as physical environment, service levels, and merchandise quality (Baker, Grewal Parasuraman, 1994; Zimmer and
Golden, 1988). The influence of today’s channels on
brand equity is beyond the “availability” factor in the
marketing share equation, and retailers’ brand equity
has been found to enhance the equity of the brands they
carry based on the value the retailers provide to their
customers (Srivastava and Shocker, 1991). Grewal,
Krishnan and Borin (1998) found that store image provided a tremendous amount of information to consumers about store environment, customer service, and
product quality; and the perceived quality of the brand
was found to have a positive relationship with store
image. A positive store image can increase a brand’s level
of exposure in the marketplace, which can improve
brand recognition and awareness. The distribution channel can directly affect the equity of the brands it sells by
its supporting actions. However, when Ahmed and
Astous (2004) investigated Indian consumers’ judgments
of apparel products made in highly and newly industrialized states; they found that store type did not have a
significant impact on judgments of perceived quality.
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
They explained that the channels of distribution in
emerging economies like India were establishing themselves as product promotional tools; so, the negligible
effect of store type was understandable.
On the basis of the literature reviewed, we assume that
there is a positive relationship between store image and
perceived quality and brand awareness in the Indian
automobile market.
Advertising Frequency
H 4A: Perceived quality of a brand is related positively to the advertising frequency of the brand.
H 4B: Brand awareness is related positively to the
advertising frequency of the brand.
One of the major contributors to brand equity is advertising (Aaker and Biel, 1993). Lindsay (1990) argued that
the greatest source of added value is consumer perceptions of the product or brand, which came from advertising that built a brand image. Maxwell (1989) further
suggested that advertising is vital for creating a consistent flow of sales for brands, rather than relying on the
artificial peaks and valleys of price promotion.
Advertising can influence brand equity in a number of
ways. Across both service and product category research,
Cobb-Walgren, et al (1995) found that the brand with
the higher advertising budget had substantially higher
levels of awareness. In other words, advertising creates
awareness and increases the probability of the brand
being included in the consumer’s choice set. According
to Rice and Bennett (1998), effective advertising increases
the level of brand awareness and improve attitudes toward the brand.
Studies have demonstrated that heavy advertising improves perceived quality (Nelson 1974) and higher levels of advertising signal higher brand quality (Milgrom
and Roberts, 1986). Kirmani and Wright (1989) suggested
that the perceived expense of a brand’s advertising campaign could influence consumers’ expectations of product quality. Klein and Leffler (1981) found that advertising levels were positively related to quality. Works by
Philip P Abey (2007), revealed a strong bi-directional
relationship between advertising and consumption pattern in emerging markets like India.
This study measures the advertising frequency of a
71
brand as perceived by the consumers across all advertising media that the consumer’s might consume.
Price Promotions
H5A: Perceived quality of a brand is related negatively to the price promotions used for the brand.
H5B: Brand awareness is related positively to the
price promotions used for the brand.
H5C: Brand awareness is related positively to the
non-price promotions used for the brand.
The characterization of equilibrium probability distribution over a range of prices has been defined as price
promotion. The same can be implemented over a large
number of periods where the demands over subsequent
periods are independent of each other (Lal and VillasBoas, 1996).
Past research, has studied the effect of such factors as
inventory carrying costs, usage rates, number of loyal
consumers on the price promotional strategies used by
competitive brands. Blattberg, Briesch and Fox (1985)
showed that retailers used price promotional strategies
to reduce their inventory carrying costs. Works by Raju,
Srinivasan and Lal (1990) showed that if some consumers had a lower inventory carrying costs than the retailers, then the optimal strategy for the retailer would be
to offer periodic price discounts. Price discounts are
likely to have a negative influence on perceptions of
quality (Blattberg and Neslin, 1990), because a consumer
who purchases a discounted product often “attributes”
the fact of discounting to it being a poorer quality product (Dodson, Tybout and Sternthal, 1978).
On the basis of the literature reviewed, the above hypotheses on price promotion with brand equity was
made.
Frequency of Non-Price Promotions
Sales promotion is a type of non-price promotion. There
exists a distinction between price promotion and nonprice promotion. While non-price promotions are usually framed as gains, price-oriented promotions are perceived as “reduced losses (Campbell and Diamond, 1989).
Non-price promotions are adapted primarily for their
ability to meet such longer-term objectives as enhancing brand image or strengthening brand awareness.
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They add excitement and hence value to the brands
(Aaker, 1991; Conlon, 1980). Some research has shown
that non-price promotions can be employed to establish
brand awareness and build primary demand for the
product during the product introduction stage (Jagoda,
1984). However, we have not found any significant relationship between non-price promotion and perceived
quality in the previous studies.
Country of Origin
H6A: Perceived quality is more for a brand which
has originated outside India.
H6B: Brand awareness is higher for brands which
have originated outside India
In the present study, we define country of origin as “the
country from which the brand had originated initially from.”
In today’s era of globalization, country of origin of the
manufacturing brands is increasingly becoming more
important than the actual country of manufacture. Thus,
for example, though Honda and Chevrolet brands might
be manufactured in India, for Indian consumers, Honda
brand connotes a Japanese country of origin, while
Chevrolet consumers feel that they are using an American brand. The impact of country-of-origin on consumer
perceptions or evaluations of products is called the country-of-origin effects (Samiee, 1994). Thakor and Katsanis,
(1997) suggested that country of origin effects impact
the equity of certain brands. Indeed, a foreign sounding
name is known to affect a brand’s equity (Leclerc,
Schmitt and Dube, 1994).
Brand equity remains a complex phenomenon in the
international context (Onkvisit and Shaw, 1989) and the
impact of country-of-origin on some of its components
(e.g. perceived quality) has been widely researched in
the marketing literature (Chao, 1998). Researchers have
suggested that the effect varies from category to category
(Pappu, Pascale and Ray, 2006). In this context, this research aims to develop a better understanding of the
effect of the country-of-origin on brand equity for multiple-time car buyers in emerging markets like India
since such buyers are expected to be more educated on
the cars while going through the purchase behaviour.
Word-of-Mouth (WOM)
H7A: Perceived quality is positively influenced
by positive WOM.
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
H7B: Brand awareness is positively influenced by
positive WOM.
WOM is a form of communication that conveys information about the product and service in a verbal format, mainly through communication (Brown and
Reingen, 1987; Herr, et al, 1991). At its core, WOM is a
process of personal influence, in which interpersonal
communications between a sender and a receiver can
alter the receiver’s behaviour or attitudes (Merton, 1968).
Researches have suggested that the effectiveness of
WOM information could be explained by the fact that
the information is received in a face-to-face manner and
this information is more accessible to the memory, rather
than information received from a less vivid format, like
mass media (Herr, et al, 1991). Other researchers have
further suggested that the effectiveness of WOM can be
attributed to the confidence and perceived credibility
the receiver has in the information received. Often the
information is sought out from people in whose opinions the receiver has extreme confidence (Kapferer,
1990). WOM has been found to be more pervasive under certain market conditions inclusive of evaluation of
high involvement products and services. Kapferer (1990)
explains this stating that high involvement products are
important to consumers and the services received on
such products could be classified as credence goods that
are goods for which buyers have difficulty evaluating
even after they consume the same. Under such conditions, consumers rely on information that represents the
experiences of others and only such information is perceived as credible. Goldsmith and Horowitz (2006)
proved that consumers relied on other consumers’ opinions to reduce their risks and obtain pre-purchase information. Escalas and Bettman (2003) in their work stated
that reference groups are a strong source of brand awareness as they are linked to one’s mental representation of
self to meet self-verification or enhancement goals.
Brands used by member groups and aspiration groups
are connected to consumer’s representation of self mentally as they use these brands to define and create their
self construct.
Celebrity Endorsement
Hypothesis B8-1: Perceived quality of a brand is
related positively to the celebrity endorsement
used for the brand.
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
Hypothesis B8-2: Brand awareness is related positively to the celebrity endorsement used for the
brand
Celebrities have been defined as individuals who are
known to the public (i.e., actor, sports figure, entertainer,
etc.) for their achievements in areas other than that of
the product class endorsed (Friedman and Friedman,
1979).
According to recent research statistics, the number of
celebrity advertisements has doubled in the past ten
years. One in four advertisements features celebrities
today as opposed to one in eight in 1995 (Seno and Lucas,
2007). Though this statistics is related to consumer goods
and services, there has also been an increase in the use
of celebrities in the brand message communications
among luxury brands.
Several studies suggest that when a brand becomes associated with a celebrity via the endorsement process,
information regarding the celebrity’s activities and
achievements get transferred to the brand and have an
effect on its image (e.g., Till and Shimp, 1998). When a
celebrity endorses a brand, the brand hopes that it can
benefit from customers’ awareness of the celebrity,
which could include the perception of quality, educational value, or a certain image. A credible celebrity endorser is normally a sign of high quality in consumers’
minds. Celebrity endorsement can be used for a variety
of purposes — e.g., to attract attention to the product or
brand (Kaikati, 1987), communicate its merits (Kamins,
1990), and penetrate commercial clutter (Miciak and
Shanklin, 1994). Spielman (1981 showed that celebrities
could be employed to enhance the subject’s attentiveness to the ad, make the copy more memorable, credible, or desirable, and effectively glamourize the product.
Event Sponsorship
H9A: Perceived quality of a brand is related positively to the events sponsored by the brand.
H9B: Brand awareness is related positively to the
events sponsored by the brand.
Cornwell (1995) defined sponsorship-linked marketing
as “the orchestration and implementation of marketing
activities for the purpose of building and communicating an association to a sponsorship.” Previous research
suggests that event sponsorship may increase both per-
73
ceived brand superiority (Crimmins and Horn, 1996) and
corporate image (Stipp and Schiavone, 1996). According to Dean (1999), once a link between the sponsoring
company and the event has been created and the feeling
of goodwill towards the event has resulted in a feeling
of goodwill towards the sponsor, a “halo effect” might
then suggest to consumers that the sponsor’s products
are superior to its competitors. The sponsorship of sports,
causes, and events has become an established communication tool to build brand awareness and preference
(Javalgi et al, 1994; Quester, 1997). Keller and Lehmann
(2002) suggested that sponsored events can contribute
to brand equity by increasing the awareness of the company or product name.
Amongst the emerging economies, event sponsorship
has become an important marketing tool especially in
China. Fan and Pfitzenmaier (2002) found that one of
the benefits of event sponsorship in China was the opportunity to establish direct contact with the opinion
leaders and innovators. Though we could not find any
study which correlated event sponsorship and brand
equity in the Indian context, on the basis of the previous
studies in other countries, we have proposed our hypothesis.
Relationship amongst Brand Equity Dimensions
H10: The perceived quality of a brand is related
positively to the extent to which brand awareness
is evident in the product.
Perceived quality is based in part on brand awareness,
as a visible brand might be considered more able to provide superior quality. Moreover, the principal characteristic of a brand is its position on the perceived quality
dimension. High quality enables consumers to recognize the brand’s distinctiveness and superiority. Results
from Yoo, Donthu and Lee (2000) support that there are
significant intercorrelations amongst the dimensions of
brand equity. In our current study, we have proposed
the following relationship amongst the two brand equity dimensions that we have considered.
Relationship amongst Brand Equity Dimensions and
Brand Choice
H11A: Brand choice is related positively to the
perceived quality of the consumers.
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H11B: Brand choice is related positively to the
brand awareness of the brand.
Consumer Based Brand Equity (CBBE) as a concept,
shares the view that the value of a brand to a firm is
created through the brand’s effect on consumers. Past
researches have shown that brand equity accrues over
time via consumer learning and decision making processes (Erdem, et al., 1999; Erdem, Imai and Keane, 2003).
Analysis of the different research streams shows that
brand equity concept is understood better if examined
in a broader framework that assesses the incremental
effect of the brand in the consumer’s choice process.
Brand equity could play a role in how information is
learned and retrieved and used in decisions and choice.
This definition extends the aggregate conceptualization
inherent in the additive brand impact notion of brand
equity (i.e., enhanced attractiveness captured in the utility function) to a more comprehensive approach that
focuses on the brands in the consumer choice process.
Although any specific sequential characterization (Lynch,
Chakravarti and Mitra, 1991) of consumer choice processes is fundamentally limited, the elements belonging
to a multi-staged and dynamic characterization of consumer choice is fairly general. Thus, product attributes
arising out of perceived quality and brand awareness
are selectively encoded and represented in consumer
memory in a learning stage. These representations may
also be selectively retrieved for subsequent use. Choice
amongst the members of this set would depend on the
specific decision rule invoked by the consumer.
Multi-attribute utility theory implies that the main building blocks in the consumer choice process are consumer
perceptions about the product, i.e., the perceived quality and consumer taste arising out of their awareness
(Erdem, et al, 1999). These building blocks are in fact the
dimensions of brand equity that we have considered in
our study.
METHOD
On the basis of definitions in the literature, we identified factors that can be affected by marketing mix elements and generated a pool of sample measures. Items
were measured on a 5-point Likert scale, with anchors
of 1 (strongly disagree) and 5 (strongly agree).
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
Category Selection
To test our hypotheses, we had selected the Indian passenger car industry. More specifically, samples were
chosen from the consumers who had bought at least a
second passenger car in the last six months. The category
chosen was indeed a very interesting one. According to
J D Power, only 37 per cent of the Indian car buyers are
first-time buyers, compared to 80 per cent in China. Even
this appears to be a skewed figure because a large chunk
of this 37 per cent is from car owning households (Arvind
Saxena, CEO Hyundai Motors India Limited, 2007). The
trend is in fact turning stronger as the market matures
as just 10 years ago, 50 per cent of the buyers in India were
first-time car buyers (Mr. M Takedagawa, President and
CEO of Honda Siel, in his interview in the Economic
Times, 2007).
Sampling and Procedure
In line with the work by Desarbo and Manrai, 1992;
Kirmani, Sood, and Bridges, 1999; and Park, Milberg and
Lawson, 1991, we distinguish between three brand types
for automobiles: premium, volume, and economy. Accordingly, we define prestige brands as brands which
are priced > Rs. 9 lakh, volume brands as priced between
Rs. 5-9 lakh, and economy brands priced less than Rs. 5
lakh. All the prices being considered are ex-showroom,
New Delhi as on March 2008. This method of differentiation finds merit as the Soceity of Indian Automobile
Association (SIAM) classifies passenger vehicle types
along the same lines. The magazine, “Auto Car,” publishes the prices of all automobile models in all its issues. Its March 2008 issue was used as the reference for
all our brand categorization.
It is projected that in 2011, 80 per cent of the cars sold in
India would be in the economy range, 14 per cent in the
volume range, and 6 per cent in the premium range (Global Insight, 7th Sept. 2007). Accordingly, we stratified our
sample, wherein 80 per cent of our respondents were
people whose last car purchased was economy brand,
14 per cent volume brand, and 6 per cent premium
brand. The purpose of stratification was to ensure covering respondents across all price points.
As per the Department of Transport Ministry, Government of India, 2004, the states having the 10 largest population of passenger car vehicles excluding the taxi
segment in India as on 2004, contributes to 78 per cent
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
of the All-India vehicle population. Being the last published report from the Ministry of Transport, we have
considered this report for stratifying the samples.
Post-stratification, a random sampling was done. The
pre-test method was used to assess the clarity of the
questions and the reliability of the measures of the variables with respect to the questionnaire. In November
2007, a total of 50 pre-test surveys were collected from a
non-probability sample of Indian automobile owners
across the six metros of the country. The six metros are
Mumbai, Delhi, Chennai, Bangalore, Hyderabad, and
Kolkata. The questionnaire was sent by email to the respondents, who then returned the completed questionnaire to the researchers by email. The respondents were
asked to indicate if they had any difficulty understanding and answering the questions besides providing other
related suggestions that could be used to improve the
questionnaire. Based on their feedback, adjustments to
the questionnaire items were made. Cronbach’s alpha
and test for convergent validity (using the formula of
Bagozzi and Baumgartner (1994)) were analysed for all
the constructs, and items found to be unreliable were
dropped. In summary, the questionnaire was improved
on the basis of the findings of the pre-test.
The final research employed shopping centre intercept
surveys to collect consumer information. Due to the lack
of up-to-date telephone directories, mail and telephone
surveys are not a desirable method to collect data in India. Shopping centres were selected based on a marketing investigation. The criteria to select the shopping
centre were that it must have a footfall of over 1,000 per
day and a parking capacity of 250 cars at any time. Respondents were selected from visitors in the shopping
centre who were willing to complete the questionnaire
while shopping. The study was conducted across 10 centres and in each of the centres, three shopping malls were
chosen for the survey. A research agency, PROADVENT,
having branches across five cities in India, was engaged
for administering the survey. Interviews in each of the
centres were conducted by two people from the research
agency. Since the research was conducted in 10 centres,
a total of 20 interviewers were employed and each of
them was extensively trained for three days before the
formal survey.
To randomize our samples in each shopping mall in
every centre, every third person who had parked his/
75
her car between 3 pm and 9 pm on Friday, Saturday,
and Sunday were contacted for interview. Since there
were three shopping malls in each centre, interviews
were carried out in a total of 30 spots across ten centres
and a total of 1,932 consumers were contacted. While
contacting the respondents, there was no discrimination
by gender or age. A total of 644 consumers agreed to be
a respondent. An incentive (a small gift) was offered with
each questionnaire, but participation was entirely voluntary. Only one questionnaire was made with the respondents being asked the brand of automobile they had
last purchased. On the basis of their answers, they were
then stratified into economy, volume or prestige brand
samples. A respondent could essentially complete only
one questionnaire.
Table 3A: Cronbach Alpha of Construct
To be eligible for participation in the study, consumers
had to meet three criteria. First, they should have bought
more than one car; second, their last car purchased
should be within the last six months; and third, the last
car could not be a second hand car. Stratification of the
respondents (basis their last car purchase) in line with
vehicle population (premium, volume, and economy)
was maintained. This reduced the number of sample size
to 310, as per the state-wise and vehicle-wise skew shown
in Table 2.
Table 3B: Convergent Validity of Constructs
Table 2: No. of Interviews Targeted Pan India
Place
No. of Interviews Targeted
Total
Premium
Volume
Economy
Maharashtra
84
5
13
66
Tamil Nadu
27
2
4
21
Andhra Pradesh
44
3
5
36
Gujarat
46
3
6
37
Delhi
41
2
7
32
Karnataka
32
2
4
26
Rajasthan
11
1
2
8
West Bengal
13
1
2
10
Punjab
6
0
1
5
UP
6
0
1
5
Total
310
19
45
246
The items of the construct were developed from literature review and Cronbach alpha and test for convergent
validity conducted (Refer to Tables 3A and 3B).
76
Construct
Number of Items
Cronbach’s Alpha
Price
3
0.76
Store image
4
0.72
Distribution intensity
3
0.75
Celebrity endorsement
3
0.79
Advertising frequency
3
0.78
Price promotion
3
0.84
Non price promotion
3
0.92
Peer recommendation
3
0.89
Country of origin
3
0.77
Event sponsorship
4
0.89
Perceived quality
4
0.91
Brand awareness
4
0.80
Convergent Validity of Construct
Composite Reliability
Price
0.6
Store image
0.5
Distribution intensity
0.51
Celebrity endorsement
0.6
Advertising frequency
0.7
Price promotion
0.59
Non-price promotion
0.56
Peer recommendation
0.51
Country of origin
0.65
Event sponsorship
0.58
Perceived quality
0.82
Brand awareness
0.55
FINDINGS
Effect of Marketing Mix Elements on the
Type of Car
To know the effect that the marketing mix elements have
on the type of car, we plotted a histogram with outline
and groups with the help of Minitab 14.0. The results of
the same are shown in Figure 2.
Analysis of Marketing Mix Elements Influencing
Dimensions of Brand Equity and Dimensions of
Brand Equity Influencing Final Choice
We used Structural Equation Model (SEM) as the tool
and SPSS 13.0 for our analysis. SEM is an extension of
the general linear model (GLM) that enables researchers to test a set of regression equations simultaneously.
The general form of SEM consists of two parts: the meas-
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
Figure 2: Effect of Marketing Mix Elements on Type of Passenger Cars
urement model and the structural model. The measurement model specifies how the latent variables or the hypothetical constructs are measured in terms of the
observed variables and describes the measurement properties. The structural equation model specifies the causal
relationships among the latent variables and describes
the causal effects and the amount of unexplained variance.
Hu and Bentle (1999) suggest that GFI, NFI, CFI, and
RMR values above 0.90 and AGFI values above 0.80 are
generally interpreted as representing a good fit, whereas
a value of RMSEA below 0.10 indicates a good fit. Due
to large samples, a significant Chi-square (X2) does not
indicate poor fit because the Chi-square is easily influenced by the size of the sample (unlike other criteria). In
addition to the disadvantage of the Chi-square statistic,
the ratio of Chi-square to its degree of freedom, X2/df, is
further used to indicate a good fit. It is suggested that a
ratio of 3:1 or less indicates an adequate fit.
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
Measurement Model Testing
CFA is particularly useful for testing a measurement
model as it allows for correlated errors of measurement
(Hair, et al., 1998). A measurement model was set to have
40 items comprising 12 constructs (latent variables) in
this study. AMOS 5.0 maximum likelihood method was
used to examine each construct and its standardized
loadings.
Standard Loading and the Squared
Multiple Correlation
Bollen (1989) suggested that standard loading and
squared multiple correlations between items and constructs should be used for measurement model testing.
The analysis results for this study indicated that all 40
items were loaded highly on their corresponding construct (p>0.05 in all cases) and the t-values of those items
were greater than 2.0 (Segars and Grover, 1993). The
analysis of the squared multiple correlations demonstrated that, except for a few items, most of the items
77
met the recommended criteria of 0.40 (Taylor and Todd,
1995). This means, overall, that the items shared substantial variance with their hypothesized constructs (see
Table 4).
In terms of model fit, the test of the measurement model
demonstrated that it had a good fit to the data. The data
shown in Table 5A suggests that, except for Chi-square
(X2) and NFI, all other criteria met the recommended
Table 4: Parameter Estimates for the Measurement Model
Constructs
Items
Brand price
Brand price 1
Brand price 2
Brand price 3
Store image 1
Store image 2
Store image 3
Store image 4
Distribution intensity 1
Distribution intensity 2
Distribution intensity 3
Celebrity endorsement 1
Celebrity endorsement 2
Celebrity endorsement 3
Advertising frequency 1
Advertising frequency 2
Advertising frequency 3
Price promotion 1
Price promotion 2
Price promotion 3
Non-price promotion 1
Non-price promotion 2
Non-price Promotion 3
Country of origin 1
Country of origin 2
Country of origin 3
Word-of-mouth (WOM) 1
Word-of-mouth (WOM) 2
Word-of-mouth (WOM) 3
Event sponsorship 1
Event sponsorship 2
Event sponsorship 3
Event sponsorship 4
Perceived quality 1
Perceived quality 2
Perceived quality 3
Perceived quality 4
Brand awareness 1
Brand awareness 2
Brand awareness 3
Brand awareness 4
Store image
Distribution intensity
Celebrity endorsement
Advertising frequency
Price promotion
Non-price promotion
Country-of-origin
Word-of-Mouth
Event sponsorship
Perceived quality
Brand awareness
Standardized
Loadings
T – values
Squared Multiple
Correlations
0.71 **
0.74 **
0.76 **
0.65 **
0.55 **
0.64**
0.48 **
0.61 **
0.67 **
0.46 **
0.72 **
0.61**
0.8 **
0.81 **
0.87 **
0.77 **
0.79 **
0.72 **
0.78 **
0.69 **
0.77 **
0.64 **
0.72 **
0.64**
0.8**
0.53 **
0.79 **
0.88**
0.77 **
0.82 **
0.86 **
0.83 **
0.78 **
0.85 **
0.85 **
0.88 **
0.56 **
0.63 **
0.58 **
0.64 **
10.23
-2
-2
8.04
-2
-2
-2
-2
5.3
-2
16.54
-2
-2
20.22
-2
-2
8.54
8.78
-2
-2
-2
-2
20.9
-2
-2
14.9
-2
-2
15.33
-2
-2
-2
16.63
-2
-2
-2
8.85
-2
-2
-2
0.5
0.58
0.61
0.42
0.4
0.46
0.38
0.44
0.46
0.3
0.52
0.64
0.58
0.65
0.6
0.76
0.56
0.52
0.58
0.63
0.69
0.55
0.5
0.51
0.54
0.35
0.55
0.76
0.6
0.68
0.65
0.71
0.62
0.73
0.78
0.74
0.32
0.4
0.45
0.41
** indicates significant correlation at t > 2.0;
- 2 means first path was se t to 1, therefore, no SE’s or t-value are given.
78
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
values suggested by Hu and Bentle (1999). A Chi-square
(X2) value of 873.35 with a degree of freedom of 455 for
the measurement model was found. The p value was
equal to 0.00, which did not meet the criteria for a fit
model (P >= 0.05). However, it was accepted that X2
was not an appropriate criterion for a study that had a
large sample size (Browne and Cudeck, 1993; Marsh,
1994), and that X2 became more sensitive as the number
of indicators rises (Hair, et al., 1998). This study had a
fairly large sample size (302 valid respondents) and a
large number of indicators, so X2 was not an appropriate testing criterion for model fit for this study. NFI was
also above than the recommended value of 0.90 (0.95).
Table 5A: Reported Values of Model Fit for the
Measurement Model
Fit Measure
Recommended
Values
Values from
Model
Conclusion
Chi Square (X2)
p>=0.05
0
Not fit
Chi Square (X2)/df
<= 3.00
1.9
Fit
Goodness of Fit
(GFI)
>= 0.9
0.93
Fit
Adjusted Goodness
of fit (AGFI)
>=0.8
0.9
Fit
Norm Fit Index (NFI)
>=0.9
0.95
Fit
Comparative Fit
Index (CFI)
>=0.9
0.94
Fit
Root Mean Square
Residual (RMR)
<=0.9
0.05
Fit
Root Mean Square
Error of Approximation
(RMSEA)
<=0.1
0.04
Fit
Table 5B: Reported Values of Model Fit for the
Structural Model
Fit Measure
Recommended
Value
Values from
Model
Conclusion
P>=0.05
0.00
Not fit
Chi square (X2)/dF
<=3.0
2.36
Fit
Goodness of Fit (GFI)
>=0.9
0.99
Fit
Adjusted Goodness
of Fit (AGFI)
>=0.8
0.92
Fit
Norm Fit Index (NFI)
>=0.9
0.99
Fit
Comparative Fit
Index (CFI)
>=0.9
0.99
Fit
Root Mean Square
Residual (RMR)
<=0.09
0.02
Fit
Root Mean Square
Error of Approximation
(RMSEA)
<=0.1
0.06
Fit
Chi square (X2)
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
Therefore, it could be articulated that the measurement
model of this study had an acceptable level of fitness.
Other fitness indices met the recommended minimum
values as well (see Table 5B).
Structural Model Testing
Once the measurement model had been tested for suitability, the estimation of the structural model followed.
A structural model was employed to examine the relations among the latent variables in the proposed model
(Byrne, 1998). AMOS 5.0 Graphics was used to run the
structural model and test the hypothesized relationship
between constructs. Maximum likelihood estimation and
correlation matrix were used to test the structural model.
The structural model included all variables from the
measurement model, since all of them had significant
factor loadings. It specified the actual brand choice as
exogenous variables, and they were related to the endogenous variables— perceived marketing efforts and
brand equity dimensions.
The constructs and their hypothesized relations were
tested simultaneously. The model fit criteria used in testing the measurement model were employed to test the
structural model, and goodness-of-fit statistics indicated
that the structural model revealed a satisfactory fit. A
Chi-square (X2) value of 36.94 with a degree of freedom
of 11 for the measurement model was found in this study.
The p value of X2 was equal to 0.00, which did not meet
the criteria for a fit model (p > 0.05). However, this could
be because of a large sample size and a large number of
indicators in the study. All other fitness indices met the
recommended values: Chi-square (X2)/df of 2.36, GFI of
0.99, AGFI of 0.92, NFI of 0.99, CFI of 0.99, RMR of 0.02,
and RMSEA of 0.06 (see Table 5B). Therefore, the structural model study showed an acceptable model fitness
level.
SUMMARY OF FINDINGS
The histogram shows that for any economy, brand consumers price, distribution intensity, celebrity endorsement, event sponsorship, non-price promotion, WOM
and country-of-origin of the brand are important parameters. For consumers of volume brands, advertisement
frequency, event sponsorship, and non-price promotion
are important, while for premium brand consumers,
celebrity endorsement, non-price promotion are the
79
important marketing mix variables influencing their final choice.
H1 posited that brand price was a significant clue consumers used to evaluate brand quality. In this study,
the path to perceived quality from brand price was positive. This result indicates that Indian consumers use
brand price as an important cue in determining the quality of automobile brands. For them, expensive products
mean higher quality. Thus, H1 was supported.
H2 argued that intensive distribution was likely to improve brand awareness. The results from this study supported this proposed relationship. That is, channel
convenience provided by being closer to home/
workplace in India could effectively increase their products’ popularity among the Indian consumers, since
automobiles are regarded as a service-driven activity.
People would thus want the dealers close by so that ‘help
at hand’ is available.
H3A and H3B hypothesized that good store image was
likely to increase brands’ perceived quality and brand
awareness. The proposed relationships were supported
by the results: perceived quality and brand awareness
were influenced by store image. These results suggest
that good store image of automobile dealers in India
influence the perceived quality of the brand that the
dealers carry. Also, the retailers’ brand equity can enhance the brand awareness based on the value the retailers provide to their customers (Srivastava and
Shocker, 1991).
H4A and H4B postulated that advertising frequency was
positively related to perceived quality and brand awareness. The results reveal that the relationship to perceived
quality is not significant but the relationship to brand
awareness is significant. This means that higher the
advertisement frequency, more the brand awareness,
though the perceived quality is not affected by the same.
One possible reason for the same is that the consumers
considered here are multiple-time automobile buyers
having a fair idea of the product quality without focusing on advertisement messages.
H5A and H5B posited that price promotion negatively
affected perceived quality and brand awareness. The
paths from price promotion to perceived quality and
brand awareness were not related to each other. The
80
possible reason for the same could be that cars are purchased after a period of time. Thus price promotion, offered by a brand, was more likely to be forgotten by the
consumers, by the time he came for a repeat purchase.
Again, since the respondents of our study are multipletime automobile buyers who are expected to be in the
higher income levels, price promotion as a cue, might
not necessarily induce brand awareness. H5C argued
that non-price promotion was likely to strengthen brand
awareness. Results reveal that non-price promotion can
significantly enhance brand awareness. Again the possible reason for the same could be that the respondents
chosen are multiple-time automobile buyers, who see
non-price promotions as gaining something extra without cheapening the product. Hence, they are more likely
to concentrate on such deals.
H6A and H6B argued that perceived quality and brand
awareness was more for a brand which had originated
outside India. A path from country-of-origin to perceived quality showed that they were not related to each
other. Again, this might be because the respondents are
multiple time car buyers who have a fair knowledge
owing to their earlier use experience on the merits and
demerits of an Indian brand vis-a- vis the brands of foreign origin.
H7A and H7B posited that WOM would enhance both
the perceived quality and brand awareness. The results
support the hypotheses. The paths to WOM and perceived quality and brand awareness were also found to
be positive. For the country level culture, India is still a
collectivist society as a whole. People in collectivist societies such as India interdependently interpret advertising messages and make implicit or explicit joint product
purchase decisions, conforming to in-group members’
dominant opinions and behaviour, thereby diluting the
impact of advertising.
H8A and H8B postulated that celebrity endorsement was
likely to increase a brand’s perceived quality and brand
awareness. Positive paths were found to perceived quality and brand awareness from celebrity endorsement.
That is, credible celebrity endorsers serve as a sign of
high quality in Indian consumer’s minds, and can be
used to generate more traffic to the brand. Simultaneously, the celebrity endorsement also increases the brand
awareness for the brand.
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE
H-9A and 9B hypothesized that event sponsorship was
positively related to perceived quality and brand awareness. The path to perceived quality was found to be positive. However, the path to brand awareness from event
sponsorship was found to be weaker and insignificant.
That is, event sponsorship in India is not effective at
promoting a sponsor’s brand and communicating brand
personality to the audience.
Hypothesis 10 was formulated to determine whether
significant relationships existed among brand equity
dimensions in the Indian automobile market. The results
indicate that the proposed relationships among brand
equity dimensions, which were based mainly on the findings from studies conducted in the Western cultures,
were supported in the Indian market also for the relationship studied.
Hypotheses H11A and H11B suggested that brand
choice was related to both perceived quality and brand
awareness. Again, the results of our study support the
hypotheses. The paths to perceived quality and brand
awareness from brand choice were found to be positive.
Thus, it has been shown that the data in this study
achieved acceptable levels of measurement reliability
and validity, while the measurement model showed a
good fit. Besides, the structural model demonstrated that
14 out of 19 proposed hypotheses in this study were
supported with a good fit level.
MANAGERIAL IMPLICATIONS
One of the major findings of this study is that brand
choice probability could be enhanced if dimensions of
brand equity are enhanced. This study is also one of the
first studies to analyse the factors affecting brand equity (and brand choice) for multiple-time consumers of
a category. Yoo, Donthu and Lee’s (2000) brand equity
creation model was expanded and tested in the Indian
context. It was found that not all parameters affecting
brand equity in the US have a significant impact in India. For example, advertisement frequency is not a very
successful builder of brand equity in the Indian context,
while price promotion has no effect on brand equity for
such consumers. The study proves that brand managers need not go for event sponsorship if their objective
VIKALPA • VOLUME 35 • NO 3 • JULY - SEPTEMBER 2010
is to increase brand awareness, but event sponsorship
helps to increase perceived quality of a product. WOM
is another marketing mix element that has been found
to be impacting the dimensions of brand equity and ultimately final brand choice. Possibly, collectivistic culture of Indians are prevailing and making it a significant
determinant of brand equity versus advertising frequency. The study has also given indication on the most
effective marketing mix elements across car owners of
different categories — premium, volume, and economy.
This study should serve as a guideline to the brand managers in automobiles and consumer goods industry, on
the marketing mix elements that should be focused on to
strengthen the dimensions of brand equity. For ultimately,
increased brand equity means better choice probability
for consumers, which can translate into an increase in
sales.
LIMITATIONS AND DIRECTIONS
FOR FUTURE RESEARCH
Our study is limited by several factors that can be addressed in future research. First, our sample is limited
geographically. Our hypothesis should be tested further
in other countries to get a universal data. Again, the data
we had collected were after repurchase had been made.
So, the respondents might be biased towards the actual
decision. Ideally, all the data gathered should have been
on consumer’s perception and hence should have been
prospects. However, as we interviewed consumers
shortly after their repurchase, this bias should not be
too problematic (Punj and Brookes, 2002). Third, we have
collected cross-sectional data. Future research could collect longitudinal perceptual data and longitudinal
switching data. Again, we use perceptual, not actual,
measures of marketing mix variables. It would be meaningful from a managerial perspective to use hard marketing data from secondary sources, such as published
survey reports. Perceived pricing efforts may create illusive reflections on brand equity, distinct from the actual pricing efforts. Again perceived advertising data
might be different from what a brand is actually spending. Hence, we call on future research to examine the
effects of actual marketing mix elements on brand equity.
81
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Tanmay Chattopadhyay is the Marketing Manager of Amara
Raja Batteries Limited in India and a Doctoral Student in Marketing at the Birla Institute of Technology, Mesra, Jharkand.
ogy, Mesra, Jharkhand.
e-mail: tanmaychat@gmail.com
Mahesh Krishnan is the Vice President (Lifestyle Business) at
the Phillips India Limited, New Delhi.
Shradha Shivani is a Ph. D. in Management and is working
as a Professor of Marketing at the Birla Institute of Technol-
84
e-mail: shraddhashivani@bitmesra.ac.in
e-mail: gundans@hotmail.com
MARKETING MIX ELEMENTS INFLUENCING BRAND EQUITY AND BRAND CHOICE