Ashutosh Anil Sandhe
TeamLease Skills
University, India
E-mail:
ashutoshsandhe@yahoo.com
Submission: 5/22/2019
Revision:
6/04/2019
Accept: 9/19/2019
ABSTRACT
The focus of this research was to measure consumer-based brand equity (CBBE) of India’s most popular online retailing websites Amazon and Flipkart. However, for the sake of confidentiality and copyright, their names were not revealed anywhere in the paper. This was done with the help of Aaker’s and Keller’s concept of brand equity. A sample of 1000 respondents from across the state of Gujarat, India was examined. CBBE was measured by calculating mean scores of overall brand equity and its factors like brand loyalty, perceived quality, brand awareness, brand association, attitude and purchasing intention. The correlation coefficient between factors and brand equity was considered as weight. The research revealed through the data which retail site had a higher brand equity. One interesting fact that was identified was how keenly both the brands are trying to woo their customers. The results showed very similar trends. A positive relation was found between brand equity and its factors. Based on this relationship the research concluded with a regression model where brand equity was the dependent variable and factors were independent variables. It was observed that the factor ‘brand loyalty’ had the lowest mean value suggesting that with competition and wider choice to consumer, brand loyalty tends to be lower. Favorable attitude was observed for both brands with highest mean values among all factors.
Keywords: Brand Loyalty, CBBE, Perceived Quality, Brand Awareness, Brand Association, Attitude, Purchasing Intention
1.
INTRODUCTION
India
enjoys demographic dividend as compared to some of the developed nations like
the United States, Britain or even some of the emerging economies like Russia
or China. With
1.2 billion people and the world’s third largest economy in purchasing power
parity terms, India’s recent growth has been a significant achievement.
India has emerged as the fastest
growing major economy in the world as per the Central Statistics Organisation
(CSO) and International Monetary Fund (IMF). India's consumer confidence index stood at 132
in the first quarter of 2019, topping the global list of countries on the same
parameter, as a result of strong consumer sentiment, according to market
research agency, Nielsen. According to a
report published by IBEF in May 2019, India’s GDP has risen by 7.2 per cent in
2017-18 and 7 per cent in 2018-19. With these figures, the country India has
maintained its position as the third largest startup base in the world with
over 4,750 technology start-ups.
According
the latest report by Boston Consultancy Group, nominal expenditure growth of
12% is more than double the anticipated global rate of 5% and will make India
the third-largest consumer market by 2025.
1.1.
Internet Penetration in India
In today’s era, Indians have a wide
array of choices when it comes to spending their money. The choices range from unorganized retail
stores to organized ones and the recent trend is the mushrooming of online
shopping platforms. Especially with the
penetration of smartphones and faster internet technology supported by decent
internet penetration even to the rural areas, more and more people are likely
to make their purchases from online shopping platforms.
There is a great potential for operational
and financial success of online shopping platforms in India. According to ICUBE which tracks digital
adoption and usage trends in India, India witnessed a growth of 18% in internet
usage in Indna in the year 2018 and it is estimated to grow further in the
coming years.
The rise in internet penetration to
go with the positive figures of per capita incomes, demographic dividend and
rapidly growing economy, has paved a path for the digital India where a lot of
transactions will be done through the internet.
Figure 1: Internet Users in
India
Source : ICUBE
Currently, a good number of Indians prefer to shop for various types of products through the online shopping options available in the country. Some of the prominent ones are Amazon, Flipkart, Shopclues, Paytm, Snapdeal, Infibeam, Homeshop18, Myntra, Jabong, Voonik, Yepme, Yebhi, Pepperfry, Bigbasket, UrbanClap, Firstcry, Zivame, Clovia, Lenskart.
1.2.
Indian Retail Sector
According to a report published by
IBEF in March 2019, the Indian retail industry is one of the fastest growing
sectors in the world. It is expected to grow to US$ 1,200 billion by 2021 from
US$ 672 billion in 2017. The report
further said that the country is adopting online retail in a big way.
The Indian retail industry has
emerged as one of the most dynamic and fast-paced industries due to the entry
of several new players. It accounts for over 10 percent of the country’s Gross
Domestic Product (GDP) and around 8 percent of the employment. India is the
world’s fifth-largest global destination in the retail space.
The retail sector in India is
emerging as one of the largest sectors in the economy. The total market size of Indian retail
industry reached US$ 672 billion in 2017. It is forecasted to increase to US$
1,200 billion by 2021 and 1,750 billion by 2026. India will become a favourable market for
fashion retailers on the back of a large young adult consumer base, increasing
disposable incomes and relaxed FDI norms.
According to the latest IBEF Report
on retail sector in India which was published in January 2019, online retail
business is the next generation format which has high potential for growth.
Currently, it is estimated to be a US$ 50 billion opportunity. After conquering
physical stores, retailers are now foraying into the domain of e-retailing. It
had a market size of US$ 18 billion in 2017 and is forecasted to reach US$
32.70 billion by 2018. Online retail
market is estimated to reach US$ 60 billion by 2020. The online retail sales is
projected to reach US$ 73.00 billion by 2022.
India's ecommerce industry's sales
rose 40 per cent year-on-year to reach Rs. 9,000 crore (US$ 1.5 billion) during
the five-day sale period ending September 24, 2017, backed by huge deals and
discounts offered by the major ecommerce companies. The government plans to allow 100 per cent
FDI in e-commerce, under the arrangement that the products sold must be
manufactured in India to gain from the liberalized regime.
Figure 2:
Growth of Retail E-Commerce in India
Source: IBEF
If
the data on internet and growing retail sector is viewed together, there seems
to be a strong positive correlation between the two in the sense that with
increasing internet penetration and growth of organized retail sector, the
growth of online retail sector is likely to outperform its counterparts.
With
this scenario, it was deemed fit to conduct a research on brand equity of some
of the leading online retail stores. The
research is aimed at covering not only the brand equity of these online retail
stores but also consumer attitude and purchasing intention of consumers in
India. The reason for selection of
Amazon and Flipkart for the purpose of analysis was the market coverage.
Amazon
and Flipkart are in a fierce battle for market share in the Indian e-commerce
space. Both brands combined account for
more than 50 percent of the total Gross Merchandise Value (GMV). As on 31st March 2018, Amazon’s GMV reached
$7.5 billion follwed by Flipkart as $6.2 billion. As per the report by Barclays, Flipkart and
Amazon make up a majority of India’s online retail, whic is predicted to grow
two-fold to $40-45 billion by 2020. Based on the data, it was thought fit to
select these two retailers for the study.
2.
THEORETICAL CONSTRUCT
This
research would focus on three aspects of consumer behavior-
·
Brand Equity of online retail stores in
India
·
Consumer attitude towards these retail
stores in India
·
Purchasing intention towards these retail
stores.
2.1.
Brand Equity
In
order to study and analyse brand equity, there are numerous models. However, it was decided to use the concept of
consumer based brand equity (CBBE) since the value of brand is decided, among
all other factors, by consumers’ perception, attitudes and other psychological
norms.
Brand
is a unique identity that is associated with the product which enables
consumers to differentiate one product from another. The American Marketing Association defines
brand as a name, term, sign, symbol, or combination of them that is designed to
identify the goods or services of one seller or group of sellers and
differentiate them from competitors.
Brand equity is the value of brand in the marketplace.
Further,
the concept of brand equity covers the incremental utility or value addition to
a product by its brand name (YOO; DONTHU, 2001). The research has moved from brand to brand
equity and then to the concept of consumer based brand equity (CBBE). Brand equity is the added value endowed on products
and services. It may be reflected in the
way consumers think, feel and act with respect to the brand as well as in the
prices, market share and profitability the brand commands (KELLER, 2008).
Customer
based brand equity is the differential effect brand knowledge has on consumer
response to the marketing of that brand (KELLER, 2008). According to Yoo and
Donthu (2001), the difference in consumer response between the focal brand and
counterpart can be interpreted as brand equity of focal brand. Through research it has been found that brand
equity has a positive impact on future profits and long term cash flow
(SRIVASTAVA; SHOCKER, 1991) and consumers’ willingness to pay premium prices
(KELLER, 1993). Therefore, brand equity
has the capability to enhance the business potential.
Figure 3:
Consumer-Based Brand Equity Model
Source: Aaker
(1991)
2.2.
Brand Loyalty
Brand loyalty is a core dimension of
brand equity. According to David Aaker,
brand loyalty is the attachment that a customer has to a brand. There is a positive relationship between
brand equity and brand loyalty (LASSAR, 1995).
Through research it was established that brand loyalty is directly
related to brand price (CHAUDHURI; HOLBROOK, 2001).
2.3.
Brand Awareness
Brand awareness is the ability for a
buyer to recognize or recall that brand is a member of a certain product
category (AAKER, 1991). It was also
defined as the ability to recall and recognize the brand as reflected by their
ability to identify the brand under different conditions and to link the brand
name, brand logo, brand symbol, etc. to certain associations in memory (AAKER,
1996).
2.4.
Perceived Quality
Perceived quality is the consumer’s
judgment about product’s overall excellence or superiority that is different
from objective quality (ZEITHAML, 1988).
Objective quality is the technical, measurable and verifiable nature of
products/services, processes and quality controls. Further it has been established that high
objective quality does not result into higher brand equity. Thus, perceived quality is a dimension of
brand equity.
2.5.
Brand Association
Brand association is the most
accepted aspect of brand equity (AAKER, 1991).
Brand association consists of all brand-related thoughts, feelings,
perceptions, images, experiences, beliefs, attitudes (KOTLER; KELLER, 2006) and
is anything linked in memory to a brand.
2.6.
Other Proprietary Assets
Other proprietary brand assets refer to patents, trademarks and channel relationships which can provide strong competitive advantage. A trademark will protect brand equity from competitors who might want to confuse customers by using a similar name, symbol or package.
This research does not aim to focus
on the other proprietary assets mentioned above. Instead, two additional dimensions i.e.
attitudes and purchasing intention towards online retail stores are considered.
2.7.
Consumer Attitude
The second aspect of consumer behavior towards online retail stores is the attitude of people in India. Lot of studies have been carried out to study and identify the parameters that affect attitude of consumers. Attitude is a learned predisposition to behave in a consistently favorable or unfavorable way based on feelings and opinions that result from an evaluation of knowledge about the object (Schiffman).
Attitude is based on three major components – cognitive factors, affective factors and conative factors. Cognitive factors lead to awareness and perceptions of a consumer about a product object. Affective factors lead to the emotional attachment or involvement about a product object or a brand and finally the conative component measures the purchasing intention towards a product object or brand.
2.8.
Purchasing Intention
The third and final part of the research is to measure the purchase intention for online retail stores in India. Purchasing intention is the willingness to purchase through a preferred mode. In this case that mode would be online retail outlets. It has been seen through research that purchase intention and attitudes result into brand equity levels (AGARWAL; RAO, 1996). In the research conducted by Yoo and Donthu also it was found that there was high positive correlation between brand equity and brand attitude.
Thus, based on the literature review, the following model is proposed to be used-
Figure
4: Proposed Model
for Research
This model is
based on the theoretical construct proposed by David Aaker. Modifications were made to include consumer
attitude and purchasing intention towards online retail stores.
3.
STUDY OF LITERATURE
Lassar et al. (1995) made an attempt
to develop a measure of consumer based brand equity. The researchers considered five factors or
dimensions that led to brand equity: performance,
value, social image, trustworthiness and commitment. Their research found that brands that had a
higher score of brand equity had higher prices.
Yoo and Donthu (2001) developed a scale to measure brand equity through a multistep study. They tried to validate a multi-dimensional consumer based brand equity measure which was taken from David Aaker’s and Kevin Keller’s concepts of brand equity. Sinha et al. (2008) proposed a method for measuring brand equity of a product category at the individual level. Such a method would permit managers to classify brand equity into its particular components and estimate the relative importance of these components.
They calculated the monetary equivalent value for each of the sub-components of brand equity. The authors further proposed two new methods to evaluate the long-term health of a brand. For this purpose a nested design based on conjoint methodology, coupled with a hierarchical linear Bayes model, was used to estimate brand equity.
Wang and Finn (2012) used the Multivariate Generalizability
Theory (MGT) to develop a brand equity scale.
The purpose of this theory was to check the reliability of the
measurement scale. They observed that individual differences, dimensions and
items were all found to be mixed with the concept of CBBE measures.
So, to clear this confusion, they
developed Many-facet Item Response Theory to further complement the information
provided by MGT analysis. The two measures when used together provided a
balanced and thorough analysis of brand performance and offered better ways of
improving performance measurement.
Brand building helps in creating, evolving and enhancing a brand's positioning and its perceptions among stakeholders which are important in affecting the behavior and performance of an institution Sharma et al. (2013).
The authors measured brand equity of select Indian business schools from the viewpoint of students through a familiarity–perception–preference–choice framework. Their framework suggested how consumer-based brand equity measures could be utilized for improvement in business school positioning and enhance brand image. Juan Carlos Londoño et al. (2016) developed the concept of Consumer-based Brand–Retailer–Channel Equity (CBBRCE). The results suggested that CBBRCE can be created through CBBRC Awareness.
4.
RESEARCH METHODOLOGY
This exploratory research focusses
on three important facets of two of India’s top an online retail stores, i.e.
consumer-based brand equity, consumer attitude and purchasing intention. A sample size of 1000 covering the entire
state of Gujarat was considered as appropriate keeping in mind the time and
resources in hand. The population considered for this research was only those
respondents who shop or are likely to shop online. The two brands considered for
this research were Amazon and Flipkart.
However, for the sake of confidentiality, due to intellectual property
rights rules, the names haven’t been disclosed in the results.
Data was collected through a
structured questionnaire in English covering all the aforesaid aspects of the
research and also the demographic profile of respondents. The size of questionnaire was restricted so
that respondents find it easy and less time consuming to answer all the
questions without getting bored. In
order to get objective and genuine information, opinion of the respondents was
asked through statements on a five point likert scale which ranged from 5
(strongly agree) to 1 (strongly disagree).
The questionnaire was divided into
eight parts covering the parameters brand loyalty, perceived quality, brand
awareness, brand association, overall brand equity, attitude, purchasing
intention and finally the demographic profile.
The demographic profile collected
information regarding city, age, occupation, gender, family size, marital
status and income. The data was
collected through an online questionnaire.
For this purpose, probabilistic sampling technique was used. The sampling method was stratified random
sampling where occupation of the respondents was considered as the strata. Preliminary test of the data for reliability
and consistency showed that the data was highly reliable and consistent as is
clear from the Cronbach Alpha values shown below-
Table 1: Reliability Analysis through Cronbach Alpha
Measure
|
Factor |
Brand X |
Brand Y |
|
BL |
0.81 |
0.81 |
|
PQ |
0.75 |
0.76 |
|
BAS |
0.69 |
0.74 |
|
BAW |
0.68 |
0.73 |
|
OBE |
0.82 |
0.82 |
|
PI |
0.89 |
0.89 |
|
AT |
0.66 |
0.76 |
|
Overall |
0.935 |
0.925 |
An
alpha value of more than 0.60 is considered to be reliable. In this research each individual factor had alpha
value of more than 0.60 and the overall reliability statistics gave values for
0.935 and 0.925 for Brand X and Brand Y respectively.
For
the purpose of confidentiality, instead of the actual brands, Brand X and Brand
Y have been mentioned for both the brands.
Which brand is X and which one is Y is kept confidential.
4.1.
Research Objectives
The
objectives of the research were to study and analyse-
·
Overall
brand equity for online retail stores in India.
·
Multi-dimensional
brand equity for online retail stores in India.
·
Brand
loyalty for online retail stores.
·
Perceived
quality of online retail stores.
·
Brand
awareness for online retail stores.
·
Brand
associations for online retail stores.
·
Overall
attitude towards online retail stores in India.
·
Purchase
intention for purchasing through online retail stores in India.
Following
was hypothesized on the basis of the above mentioned objectives.
|
H1: |
There is lack of
significant levels of overall brand equity of online retail stores. |
|
H2: |
There is lack of significant
levels of multi-dimensional brand equity of online retail stores. |
|
H2a: |
There is lack of
significant level of brand loyalty for online retail stores in India |
|
H2b: |
There is lack of
significant level of perceived quality of online retail stores. |
|
H2c: |
There is lack of
brand awareness of online retail stores |
|
H2d: |
There is lack of
brand association for online retail stores. |
|
H3: |
There is lack of
significant purchasing intention for online retail stores in India |
|
H4: |
There is lack of significant
brand attitude for online retail stores in India |
5.
DATA ANALYSIS
Table 2: Demographic Profile of Respondents
|
Factor |
N |
N% |
Factor |
N |
N% |
||
|
Age |
15-25 |
724 |
72.40 |
Occupation |
Student |
310 |
31.00 |
|
26-35 |
137 |
13.70 |
Homemaker |
48 |
4.80 |
||
|
36-45 |
47 |
4.70 |
Business |
142 |
14.20 |
||
|
46-55 |
43 |
4.30 |
Service |
371 |
37.10 |
||
|
Above 55 |
49 |
4.90 |
Profession |
129 |
12.90 |
||
|
Total |
1000 |
100 |
Total |
1000 |
100 |
||
|
Family Size |
1-4 |
649 |
64.90 |
Gender |
Male |
565 |
56.50 |
|
5-7 |
321 |
32.10 |
Female |
435 |
127.57 |
||
|
More than 7 |
30 |
3.00 |
Total |
1000 |
100 |
||
|
Total |
1000 |
100 |
Income |
0-4 |
341 |
34.10 |
|
|
Marital Status |
Married |
592 |
59.20 |
4.01-8.00 |
355 |
35.50 |
|
|
Unmarried |
408 |
40.80 |
8.01-12.00 |
177 |
17.70 |
||
|
Total |
1000 |
100 |
Above 12 |
127 |
12.70 |
||
|
|
|
|
|
Total |
1000 |
100 |
|
Table
2 provides an overview of the demographic profile of the respondents who
provided data for this research. From
the table it is clear that majority of the respondents are between the age 15
and 45 (97.31%). Further, majority of
the respondents belong to nuclear families which have members between 1 and 4
(76.68%). With regards to occupation of
the respondents, majority belong to service cadre (38.12%).
|
H1: |
There is lack of
significant levels of overall brand equity of online retail stores. |
Table 3: Simple Mean Analysis of Leading Online
Stores in India
|
Factor |
Brand X |
Brand Y |
||||||
|
Mean |
S.D. |
Chi |
Sig. |
Mean |
S.D. |
Chi. |
Sig. |
|
|
BL |
3.28 |
0.99 |
61.304 |
0.00 |
3.61 |
0.99 |
60.723 |
0.000 |
|
PQ |
3.51 |
0.86 |
141.063 |
0.00 |
3.65 |
0.87 |
136.964 |
0.000 |
|
BAW |
4.05 |
0.86 |
183.813 |
0.00 |
4.17 |
0.87 |
181.723 |
0.000 |
|
BAS |
3.57 |
0.67 |
97.161 |
0.00 |
3.96 |
0.64 |
183.393 |
0.000 |
|
AT |
3.65 |
0.79 |
191.741 |
0.00 |
3.77 |
0.79 |
190.830 |
0.000 |
|
PI |
3.38 |
0.77 |
197.312 |
0.00 |
3.88 |
0.66 |
196.375 |
0.000 |
|
Brand Equity |
3.41 |
0.86 |
123.357 |
0.00 |
3.55 |
0.86 |
230.286 |
0.000 |
(Significance
levels at 95%)
As can be seen in Table 3, mean
values for all the factors for both the brands was above the 2.5 suggesting
positive opinion from respondents. The
overall brand equity for Brand Y was found to be slightly higher than Brand X. However, these mean values were considered
independently without the impact of factors affecting brand equity. All the values were found to be significant
as is clear from the goodness of fit test.
Brand awareness was found to be high
for both the brands. As a result of the findings, the null hypothesis was
rejected and alternate hypothesis was accepted.
Thus, brand equity for both the brands was found in the study and
further the brand equity of Brand Y was found to be higher than Brand X.
|
H2: |
There is lack of
significant levels of multi-dimensional brand equity of online retail stores. |
|
H2a: |
There is lack of
significant level of brand loyalty for online retail stores in India |
|
H2b: |
There is lack of significant
level of perceived quality of online retail stores. |
|
H2c: |
There is lack of
brand awareness of online retail stores |
|
H2d: |
There is lack of
brand association for online retail stores. |
Brand equity is the result of the
effects of its factors. The factors in
the present study were ‘Brand Loyalty’, ‘Perceived Quality’, ‘Brand Awareness’,
‘Brand Associations’, ‘Attitude’ and ‘Purchasing Intention’. The mean values for all these factors for
both the brands were found to be significant and positive.
For Brand X, the mean values were in
the range between 3.28 (Brand Loyalty) and 4.05 (Brand Awareness) and those for
Brand Y were in a slightly higher range of 3.61 (Brand Loyalty) and 4.17 (Brand
Awareness). Since all mean values were
above 2.5, they were considered as favorable. Further, Chi-square values
indicated that these values were highly significant. Thus, the hypothesis and its related
hypotheses were rejected and alternate hypotheses were accepted.
Table 4: Correlation between Brand Equity and
Factors Affecting Brand Equity for Leading Online Stores in India
|
Factor |
Brand
X |
Brand Y |
||
|
Correl. |
Sig |
Correl. |
Sig |
|
|
BL
– BE |
0.571 |
0.000 |
0.573 |
0.000 |
|
PQ
– BE |
0.628 |
0.000 |
0.631 |
0.000 |
|
BAW
– BE |
0.566 |
0.000 |
0.570 |
0.000 |
|
BAS
– BE |
0.462 |
0.000 |
0.359 |
0.000 |
|
AT
– BE |
0.762 |
0.000 |
0.764 |
0.000 |
|
PI
– BE |
0.642 |
0.000 |
0.512 |
0.000 |
Through
the literature, it has been observed that brand equity is a result of its
factors. Mean analysis gave a preliminary
result of that there was brand equity for both the brands and that respondents
rated all the factors affecting brand equity favorably.
However,
how strongly these factors affected brand equity could be studied through
correlation analysis. It can be seen in
Table 4 that there was positive correlation between brand equity and its
factors for both the brands. The highest
impact on brand equity for Brand X and Brand Y, both was of attitude. Thus, attitude plays a vital role in
determining brand equity.
Figure 5:
Correlation between Factors Affecting Brand Equity and Brand Equity
The
above figure shows the relationship between all the factors that lead to brand
equity. Results show that there is a
positive relationship between all the factors and brand equity. The correlation coefficient was further
considered as a weight for calculating mean scores in order to determine
overall brand equity for both the brands.
Table 5: Comparative Brand Equity of Leading Online
Stores in India
|
Factor |
Brand X |
Brand Y |
||||
|
Mean |
r |
Mean Score |
Mean |
R |
Mean Score |
|
|
BL |
3.28 |
0.571 |
1.87 |
3.61 |
0.573 |
2.07 |
|
PQ |
3.51 |
0.628 |
2.20 |
3.65 |
0.631 |
2.30 |
|
BAW |
4.05 |
0.566 |
2.29 |
4.17 |
0.570 |
2.38 |
|
BAS |
3.57 |
0.462 |
1.65 |
3.96 |
0.359 |
1.42 |
|
AT |
3.65 |
0.762 |
2.78 |
3.77 |
0.764 |
2.88 |
|
PI |
3.38 |
0.642 |
2.17 |
3.88 |
0.512 |
1.99 |
|
Brand Equity |
3.41 |
|
3.57 |
3.55 |
|
3.83 |
Instead of just calculating simple
mean to study the brand equity, a slightly different approach was adopted. Mean scores of all the factors was calculated
and based on that brand equity was determined for both the brands. The mean score was a product of mean and
correlation coefficient between the given factor and brand equity. Thus, a weighted mean was calculated under
the premise that the factor that would affect the most, would have more impact
on the value of brand equity.
Thus,
based on the values obtained, attitude had the maximum impact on brand equity
(r=0.762) for Brand X as well as Brand Y (r=0.764). Based on the weighted mean scores, the overall
brand equity of Brand X was 3.57 as compared to Brand Y which as 3.83. Thus, the brand equity of Brand Y was found
to be higher. The final mean score for
both the brands was calculated by the given formula-
|
Brand Equity = |
|
|
∑ Correlation Coefficient |
|
H3: |
There is lack of
significant purchasing intention for online retail stores in India |
As shown in Table 3, there was
positive purchasing intention for both the brands. A mean value of 3.88 for Brand Y and 3.38 for
Brand X hinted at the fact that purchasing intention for Brand Y was higher
than Brand X. This factor was positively
correlated to brand equity for both the brands.
However, the relationship was found to be stronger for Brand X (r=0.642)
as compared to Brand Y (r=0.512). This
would ultimately affect the overall brand equity for both the brands. The hypothesis was rejected on the basis of
chi-square values obtained which were highly significant for both sets of
data. Thus, alternate hypothesis was
accepted. There is a favourable
purchasing intention for both the brands and that it is higher for Brand Y as
compared to Brand X.
|
H4: |
There
is lack of significant brand attitude for online retail stores in India |
Like purchasing intention, attitude
towards both the brands was found to be highly favourable. This could be one of the reasons that both
these brands are leading brands in India.
The mean value for Brand Y was 3.77 and for Brand X it was slightly less
at 3.65. However, on a five point scale
these values suggested a favourable opinion of respondents. Further, attitude was found to be positively
correlated to brand equity. The values
obtained were on the higher side for both Brand Y (r=0.764) and Brand X
(r=0.762). The goodness of fit tests
indicated highly significant values for both the brands. Based on these results, the null hypothesis
was rejected and alternate hypothesis was accepted.
6.
DISCUSSION
This research yielded some interesting
findings about the brand equity of two leading online retail websites in
India. The data underlined the fact as
to why there is keen competition between both the brands to capture markets in
India. The results were found to be
highly similar. The overall brand equity
based on weighted mean scores was found to be marginally higher for Y.
All the factors that result into
higher or lower brand equity were positively related to brand equity. The relationship was found to be significant
for all the factors for both brands. Of
all the factors, attitude had the highest impact on brand equity. Further, attitude was observed as highly
favorable for both the brands, even though slightly better for Brand Y. Of all
the factors, ‘Brand Loyalty’ had the least mean value again suggesting the fact
that when there are alternatives available to consumers in the market, brand
loyalty tends to be lower.
Since the results were positive for
both the brands in terms of relationship between factors affecting brand equity
and brand equity itself, we constructed a regression model to predict brand
equity based on its factors.
Table 6: Regression Analysis
for Brand X
|
Model Summaryb |
|
|||||||||||||||||
|
Model |
R |
R
Square |
Adjusted
R Square |
Std.
Error of the Estimate |
Durbin-Watson |
|
||||||||||||
|
1 |
.795a |
.631 |
.621 |
.53056 |
1.927 |
|
||||||||||||
|
a.
Predictors: (Constant), Average Purchase Intention, Average Brand Loyalty,
Average Brand Association, Average Perceived Quality, Average Brand Awareness,
Average Attitude |
|
|||||||||||||||||
|
b. Dependent Variable: Average
Overall Brand Equity |
|
|||||||||||||||||
|
ANOVAa |
|
|||||||||||||||||
|
Model |
Sum
of Squares |
df |
Mean
Square |
F |
Sig. |
|
||||||||||||
|
1 |
Regression |
104.630 |
6 |
17.438 |
61.949 |
.000b |
|
|||||||||||
|
Residual |
61.084 |
217 |
.281 |
|
|
|
||||||||||||
|
Total |
165.714 |
223 |
|
|
|
|
||||||||||||
|
a.
Dependent Variable: Average Overall Brand Equity |
|
|||||||||||||||||
|
b. Predictors: (Constant), Average Purchase Intention, Average Brand Loyalty,
Average Brand Association, Average Perceived Quality, Average Brand
Awareness, Average Attitude |
|
|||||||||||||||||
|
Coefficientsa |
||||||||||||||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||||||||||||||
|
B |
Std. Error |
Beta |
||||||||||||||||
|
1 |
(Constant) |
-.059 |
.226 |
|
-.263 |
.793 |
||||||||||||
|
Average Brand Loyalty |
.095 |
.050 |
.109 |
1.905 |
.048 |
|||||||||||||
|
Average Perceived Quality |
.182 |
.062 |
.181 |
2.956 |
.003 |
|||||||||||||
|
Average Brand Awareness |
.042 |
.064 |
.041 |
.656 |
.513 |
|||||||||||||
|
Average Brand Association |
.015 |
.075 |
.011 |
.195 |
.845 |
|||||||||||||
|
Average Attitude |
.557 |
.079 |
.509 |
7.066 |
.000 |
|||||||||||||
|
Average Purchase Intention |
.068 |
.078 |
.060 |
.866 |
.388 |
|||||||||||||
|
a. Dependent
Variable: Average Overall Brand Equity |
||||||||||||||||||
Table 7: Regression Analysis
for Brand Y
|
Model Summaryb |
|
||||||||||||||||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
Durbin-Watson |
|
|||||||||||||
|
1 |
.795a |
.632 |
.622 |
.53111 |
1.928 |
|
|||||||||||||
|
a. Predictors: (Constant),
Average Purchase Intention, Average Brand Association, Average Brand Loyalty,
Average Brand Awareness, Average Perceived Quality, Average Attitude |
|
||||||||||||||||||
|
b. Dependent Variable: Average Overall Brand Equity |
|
||||||||||||||||||
|
ANOVAa |
|
||||||||||||||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|||||||||||||
|
1 |
Regression |
105.320 |
6 |
17.553 |
62.229 |
.000b |
|
||||||||||||
|
Residual |
61.211 |
217 |
.282 |
|
|
|
|||||||||||||
|
Total |
166.531 |
223 |
|
|
|
|
|||||||||||||
|
a. Dependent Variable:
Average Overall Brand Equity |
|
||||||||||||||||||
|
b. Predictors:
(Constant), Average Purchase Intention, Average Brand Association, Average
Brand Loyalty, Average Brand Awareness, Average Perceived Quality, Average
Attitude |
|
||||||||||||||||||
|
Coefficientsa |
|||||||||||||||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
|||||||||||||||
|
B |
Std. Error |
Beta |
|||||||||||||||||
|
1 |
(Constant) |
-.089 |
.234 |
|
-.381 |
.703 |
|||||||||||||
|
Average Brand Loyalty |
.097 |
.050 |
.112 |
1.957 |
.042 |
||||||||||||||
|
Average Perceived Quality |
.185 |
.062 |
.185 |
2.990 |
.003 |
||||||||||||||
|
Average Brand Awareness |
.030 |
.062 |
.030 |
.483 |
.630 |
||||||||||||||
|
Average Brand Association |
.056 |
.069 |
.041 |
.809 |
.419 |
||||||||||||||
|
Average Attitude |
.589 |
.070 |
.540 |
8.473 |
.000 |
||||||||||||||
|
Average Purchase Intention |
.016 |
.073 |
.012 |
.222 |
.824 |
||||||||||||||
|
a. Dependent Variable: Average Overall Brand Equity |
|||||||||||||||||||
From
the regression analysis, following model was summarized-
Y1 =
β0 + β1X1i + β2X2i + β3X3i
+ β4X4i + β4X5i + β4X6i +
μi,
Where Y = Consumer-Based Brand
Equity (CBBE), X1 is Brand Loyalty (BL), X2 is Perceived Quality (PQ), X3 is
Brand Awareness (BAW), X4 is Brand Association (BAS), X5 is Attitude (AT) and
X6 is Purchase Intention (PI). In the
equation i is the sample size from 1 to 1000 and μ is the random error. For
both the brands, the regression model was–
CBBE (Brand X) =
-0.059 + 0.109BL + 0.109PQ + 0.181BAW + 0.041BAS + 0.509AT + 0.060PI
CBBE
(Brand Y) =
-0.089 + 0.112BL + 0.185PQ + 0.030BAW + 0.041BAS + 0.540AT + 0.012PI
Of all the factors, the coefficient
for Brand Loyalty, Perceived Quality and Attitude were highly significant for
both the brands. Further, Durbin-Watson
values for both the brands were in the range of 1.5 to 2.5 which was acceptable
statistically. The regression model was
highly significant as is clear from the above data.
7.
CONCLUSION
Based on the results, there was a
negligible difference in the brand equity towards both the brands in
India. For both the brands, overall
attitude was found to be positive and at the same time there was close
similarity in the values for the independent variables affecting brand equity. Brand loyalty for both the brands was low
suggesting that consumers tend to shift to different retail websites as per
their needs.
However, they prefer these two
brands the most and tend to shift more between these two brands. This also proves the fact that there is close
competition between the two brands in India.
People prefer either Amazon or Flipkart most of the time when it comes
to buying goods online in India.
8.
LIMITATIONS AND FUTURE SCOPE FOR
RESEARCH
The study was based on data
collected from Gujarat, India. The scope
can be expanded to include other parts of the country as well. Due to intellectual property rights issues,
the actual brand names couldn’t be disclosed.
We considered only two brands.
With proper resources and time, the study could be extended to cover
more brands.
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