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Drivers of Store Choice in an Evolving Market: An empirical
study
Dr Anupama Prashar
Associate Professor (Operations & Management Science), IILM Institute for Business and Management, Gurgaon, India;
Email: prasharanu@gmail.com
ABSTRACT
Retailing in India is at a crossroads. Currently, retailers are experimenting and trying different retail format based on local conditions. However, most of these formats are fetching moderate to lukewarm success. In such a scenario, it is important for retailers to understand the customer preferences of store atmospherics and their impact on store choice. The purpose of this study is
to explore the store attributes as perceived by customers that act as motivators in store choice in food & grocery retailing. Mall
intercept survey method using structured questionnaire is used for data collection. Descriptive (mean and standard deviation)
and inferential statistical tools (Factor analysis) are used to analyse the data collected from 250 food and grocery retail customers
from convenience stores, supermarkets and hypermarkets in tier-2 cities in Punjab in India. The findings suggest that customers
value availability and variety of products at store, store ambience, service and facilities, and value for money offered at store.
Further, the finding that the store location is overshadowed by other store atmospherics is in opposition to the common belief
that Indian customer look for proximity while shopping for food & grocery. The present study provides an understanding of
shoppers’ preferences related to store environment in an evolving Indian retail market. The findings may help the food & grocery retailers to use store atmospherics as a fertile opportunity of market differentiation. Due to lack of research in the field of
drivers of store choice, this study may serve as a departure point for future studies in this area of concern.
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Keywords : Retail format; Store choice; Food & Grocery; Factor analysis; Store atmospherics; Evolving market
1 INTRODUCTION
T
he pace of development in the Indian retail market has
been fast since the wave of reforms triggered by the Government to incentivize Foreign Direct Investment (FDI).
The Indian retail industry experienced a growth of 10.6% between 2010 and 2012 and is expected to grow faster to USD
750-850 billion by 2015. Food & Grocery is the largest category
within the retail sector with 60 % share followed by Apparel
and Mobile segment (Deloitte, 2013).The paradigm shift in the
customers’ socio-economic, demographic and psychographic
characteristics is the driving force behind this transition in
Indian retail scene from traditional family-owned mom & pop
stores towards organised retail formats (Prasad and Ansari,
2010; Roy and Goswami, 2007; Sinha, 2003).
Currently, retailers are experimenting and trying several
formats such as malls, cash & carry stores, convenience stores,
discount (value) stores, supermarkets and hypermarkets.
These formats are essentially a representation of retailing concepts to fit into the consumer mind space (Prasad and Reddy,
2007; Sinha and Kar, 2007). Though this experimentation for
an appropriate format based on local conditions is significant,
yet broadly the consumer perception about most of these new
formats is of insufficient additional value (Sinha, & Banerjee,
2004). In such a scenario, when retailers are finding it difficult
to create a differential advantage, store atmospherics are going
to offer the fertile opportunity of market differentiation (Baker
et al, 1992; Sinha and Uniyal, 2005).
The subject of retail store environment and store patronage
has been widely studied across the world (Martineau, 1958;
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Malhotra, 1983; Baker et al, 1992,). This fact is also gaining
greater significance in the Indian retail market with the opening of multiple store formats by domestic and foreign retail
players. Yet the research in this field is limited largely to the
shopper’s demographic profile, consumption and purchasing
patterns at these stores (Sinha, 2003). In this volatile climate, it
is important to explore how customers perceive and choose
among available retail formats.
Presently, the Indian retailers are keenly eyeing the tier-2
cities to cater to wider consumer base and to take advantage of
rising consumer income levels there (Jones Lang LaSalle,
2012). Given the fact that the consumer preferences and satisfaction drivers in these cities may be different than those in
metros, studying the preferences of customers in these cities
can be vital in designing an appropriate and customized store
environment. The present study is an attempt in this direction.
Food and grocery retailing, which is currently attracting the
entry of many domestic and foreign retail giants is chosen for
exploration. So, the purpose of the study is to identify, at a
macro level, the store attributes as perceived by customers that
act as motivators in store choice in food & grocery retailing.
The geographical scope of the study is limited to tier-2 cities of
Punjab, a state in northern India. The study proposes a
framework to evaluate the effectiveness of newer retail formats on the basis of consumer perceived value proposition.
2 REVIEW OF LITERATURE
The role of store attributes in understanding the consumer
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patronage behavior is widely explored across the world. Martineau (1958) categorized store attributes into two main categories: functional and psychological. The functional category
included attributes viz., location, assortment of products and
store layout. The psychological category represented the feelings generated by the functional elements of the store. The
study highlighted that functional category gains more attention in the store choice than the psychological category. Fisk
(1961) identified attributes such as location accessibility, merchandise suitability, value for price, sales efforts and store service. In a subsequent study, Berry (1969) identified three general factors that predominantly influenced consumer's store
choice regardless of store type viz., quality and variety of merchandise, sales staff, and store atmosphere. A prominent and
widely-cited work on the topic of store image was of Lindquist (1974). Based on a review of 19 research articles, he synthesized the framework of these studies into a set of nine
groups: merchandise, service, clientele, physical facilities,
promotion, accessibility, store atmosphere, institutional and
post-transaction satisfaction. Doyle & Fenwick (1975), proposed that price, product variety, one-stop shopping, quality,
location of the store, advertisement, general appearance of the
store and convenience are some of major attributes looked
upon by the customers while evaluating a grocery store.
Bearden (1977) distinguished seven attributes as potentially
significant for store patronage viz. price, quality of merchandise, assortment, atmosphere, location, parking facilities and
friendliness of staff. Arnold et al. (1983) extended the accessibility attribute to the ease of mobility through the store and
fast checkout. Baker et al (1992) extended the literature on retail store atmospherics for providing an experimental method
that can be utilized by retailers to examine the various aspects
of store environment and its impact on store patronage. They
proposed that the affective states of pleasure and arousal have
a positive relationship with customer’s willingness to buy at a
store. Mason et al (1994) proposed that reasonable prices in a
retail store induce customer satisfaction as well as build customer loyalty. The study found that in the retailing sector, the
store having reasonable prices will often capture a large market share. Hasty and Reardon (1997) classified store attributes
into three general categories viz., accessibility (e.g., location,
layout, appearance, and knowledgeable staff), facilitation of
sales (e.g., low-priced specials, promotional offers and accepted methods of payments) and auxiliary attributes (e.g., play
areas for children and food court). Bawa and Ghosh (1999)
proposed a model to understand the factors that account for
variations in shopping behaviour across households. The results showed that the relationship between household characteristics and shopping behavior is complex. Shopping may
have a recreational aspect for some households. However, for
others it competes directly with wage earning activity. Solgaard and Hansen (2003) identified several store attributes
that were considered important for the consumer's evaluation
of stores. These attributes include merchandise, assortment,
merchandise quality, personnel, store layout, accessibility,
cleanliness and atmosphere. Sinha and Banerjee (2004) attempted to correlate the distinct store features as perceived by
respondents with the true motivations of various customers in
196
patronising various stores. Sinha (2003) attempted to understand shoppers from their disposition towards shopping. The
study found that there are differences in orientation of Indian
shoppers from shoppers of developed countries in the way
that they value entertainment more than the functional value.
Carpenter and Moore (2006) studied the grocery shoppers’
retail format choice in the context of US. The study identified
the demographic groups who frequent specific formats and
examined the store attributes as drivers of format choice. Sinha and Uniyal, (2005) proposed a methodology for segmenting
the shoppers. The study found that the segments were differentiated largely on the basis of the type of products the stores
sold and the format of the stores. The study pointed out that in
an evolving retail market a store could add value through
store format design to create differentiation in the market
place.
3 RESEARCH METHODOLOGY
Literature indicates that consumer perception about the store
significantly impact the store choice behavior. Further, consumer store perception is substantially driven by store attributes. Keeping this in view, it was decided to design an exploratory study to identify the store attributes as perceived by customers that act as motivators in store choice. The following
research question was developed for the exploratory research:
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“What are the attributes in store environment that act as motivators
in store choice?”
The study involved a mall intercept survey conducted across
the tier-2 cities of Punjab. The population frame for the study
(27 million) was the retail customers of food & grocery in the
state of Punjab. The sampling frame for the study comprised
adult retail customers of food & grocery formats in cities of
Ludhiana, Patiala, Mohali, Jalandhar, and Amritsar. These
cities are economically and commercially more vibrant with
presence of most domestic and foreign retail brands such as
Reliance Retail, Spencer’s, Aditya Birla group, Rahejas, ITC,
RPG enterprises, A. G. Metro, Bharti Wal-Mart, and The Future Group.
The data was collected at food & grocery retail stores across
the five selected cities. These stores belong to retail format
category of convenience stores, supermarkets and hypermarkets. These formats were classified on the basis of floor area
and services offered by the stores (Sinha and Kansal, 2005;
Warren and Mark, 2005).The retail format classification is given in Table 1.
Table 1: Retail formats
The data was collected at 10 convenience stores (6-Ten), 30
supermarkets (Reliance Fresh, MORE, Easy Day) and
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10hypermarkets (Big Bazaar, Vishal, Amartex). The data was
collected by mall intercept survey using structured questionnaire (Sinha and Banerjee, 2004).The respondents were customers who had completed their shopping in retail store and
were willing to respond to the questions. The respondents
were carefully selected so that they belonged to the higher
socio-economic classes (SEC) in order to ensure that the sample had similar representation in terms of respondent profile
(Sinha, 2003).The responses were recorded using a set of
30variables measured on a 5-point Likert scale. These variables were derived from the review of literature (Sinha,
Banerjee and Uniyal, 2002; Lindquist, 1974; Arnold et al. 1983;
Baker et al 1992; Solgaard and Hansen 2003; Dabholkar,
Thorpe & Rentz, 1996).The internal consistency of the questionnaire was tested through reliability analysis using
Cronbach’s alpha. The value of Cronbach’s alpha was found to
be 0.71, which was considered to be acceptable. For the purpose of pre-testing the questionnaires, a pilot survey was conducted in the city of Mohali. As an outcome of the pilot study,
some of the variables were amended and improved. The modified versions of questionnaires were finally administered on
the respondents. A total of 250 valid responses were obtained
from the survey.
4 ANALYSIS
197
and the remaining are in the age category of ‘more than 65
years’. 66% of respondents who participated in the survey had
income between INR 40,000 and INR 60,000.52% were male
respondents and 42% female respondents. 29% of respondents
were postgraduates, 30% were graduates, 6% were high school
pass outs, and 35% had other qualifications. 39% of respondents who participated in the survey were in private jobs, 19%
were in public services, 10% were in business, and 32% were
in other occupations. The profile of the respondents is summarized in Table 3.
Table 3: Profile of respondents
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Exploratory factor analysis was conducted to reduce the 30
variables on consumer preference related to shopping of Food
and grocery (Questionnaire annexed in Annexure II). The data
was processed using SPSS (version 16) software. The Extraction Method used was the Principal Component Analysis. Rotation Method used was Varimax with Kaiser Normalization.
Prior to running the factor analysis, the Kaiser-Meyer-Olkin
(KMO) measure of sampling adequacy and Bartlett's test of
sphericity were performed. The generated score of KMO was
0.71(> 0.5), reasonably supporting the appropriateness of using factor analysis (Malhotra, 2006; Hair et al. 1998). The Bartlett's test of sphericity was highly significant (p<0.000), which
revealed that variables were not correlated in the population
(Table 2).
Table 2: KMO and Bartlett’s Test of Sphericity
5.2 Customer perceived drivers of store patronage
Factor analysis output generated extracted only those factors which
had the Eigen values greater than 1. Factors were labeled on the
basis of their salient loadings. The total variance explained by the
eight factors was 65.033%. The list of extracted factors is given in
Table 4.
5 RESULTS
5.1 Profile of respondents
A total of 250 valid responses were obtained from the survey
conducted at 50 retail stores across the five cities of Punjab.
Out of these, 15% of respondents were in the age category of
18-25 years, 24% in the age group of 26-35 years, 26% were in
age category of 36-50 years, 22% in age category of 51-65 years,
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Table 4: List of extracted factors
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Table 5: Factor loadings of variables
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Rotation Method used was Varimax with Kaiser Normalization. The rotated matrix gave a clear picture of the variable
groupings. Factor loading above 0.450 was retained for further
analysis. Table 5 shows the factor loadings of variables.
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ing of 0.794).
The results of factor analysis revealed the following store attributes as perceived by customers that acts as motivators in
store choice in food & grocery retailing:
5.2.1 Availability and Variety
The factor with maximum variance of 11.873% of total variance with Eigen value of 5.404 was named as ‘availability and
variety of products’. Four variables had high factor loading on
this factor: V1 (Products never out of stock with highest factor
loading of 0.821), V6 (Brands are available for every grocery
item with a factor loading of 0.647), V4 (Variety of grocery
items is available with a factor loading of 0.634, V14 (Everything under one roof with 0.601).
5.2.2 Store Ambience
The next factor with maximum variance of 10.340% of total
variance with Eigen value of 3.319 was labeled as ‘store ambience’. This factor had high coefficients on five variables which
included variable: V23 (clean and free from clutter has the
highest factor loading of 0.792, V27 (Good music with soothing colours on walls with a loading of 0.688), V12 (Shop in
stores with comfortable air conditioned environment with a
factor loading of 0.643), V29 (Sufficient lighting with a factor
loading of 0.573), V22 (displays are attractive with 0.498).
5.2.6 Store Location
The next factor with variance of 6.660% with Eigen value of
1.512 was labeled as ‘store location’ explained. Two variables
had high loading on this factor: V2 (neighbourhood stores for
purchasing food and grocery items with factor loading of
0.649), V13: (convenient location with factor loading of 0.588).
5.2.7 Pride associated with Purchase from Store
This factor with variance of 5.993% of total variance with Eigen value of 1.241 was named as ‘pride associated with purchase from store’. The following variables had high loading on
this factor: V9 (Matter of pride with factor loading of 0.781),
V28 (Elite class of society with factor loading of 0.632).
5.2.8 Fun associated with Purchase from Store
The factor with maximum variance of 5.313% of total variation
with Eigen value of 1.116 was named as ‘fun associated with
purchase from store’. Two variables with high factor loading
on this factor were variable V16 with factor loading of 0.794
and variable V19 with 0.593.
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5.2.3 Store Service and Facilities available
The third factor with variance of 9.087% of total variance with
Eigen value of 2.936 was tagged as ‘store service and facilities
available’. This factor had high coefficients on nine variables:
V15 (Insufficient parking spaces with 0.601), V18 (Stores which
are open till late hours with factor loading 0.531), V25 (Stores
where baskets and trolley with factor loading of 0.512), V8
(Salespersons are there to help with 0.511), V11 (Salespersons
are helpful with factor loading of 0.502), V5 (Home delivery
with factor loading of0.494, V26(Billing counters for faster
check out with 0.489),V21(Products are easy to locate with
0.482),V17(Stores which offer return or replacement policy
with 0.479).
5.2.4 Value for Money
The factor with maximum variance of 8.193% with Eigen value
of 2.271 was labeled as ‘value of money’. This factor had high
coefficients on five variables: V7 (Stock quality food & grocery
items with factor loading of 0.728), V20 (Billing system is reliable with factor loading of 0.512), V24 (Offer attractive discount offers with factor loading of 0.711, V30 (Visit stores
which offer best prices in the town with factor loading of
0.801).
5.2.5 Store Recommendation
This factor with maximum variance of 7.573% with Eigen value of 1.711 was tagged as ‘store recommendations’. The variables with high factor loading on this factor includes ‘store advertisements’ (V3 with factor loading of 0.617) and ‘store recommendation by friends and relatives’ (V10 with factor loadCopyright © 2013 SciResPub.
7 SUMMARY AND IMPLICATIONS
Retailing in India is at a crossroads. The Indian retail scenario
is presently facing the similar situations as the ‘mom and pop’
stores in the developing nations faced at the emergence of big
box retailers. The new expansions of retail formats are adaptations of western formats fetching moderate to lukewarm success. The challenge lies in retailer’s understanding of customer’s needs, and most importantly, such perceptible dimensions
of the store attribute which acts as motivators for store patronage. The study is an effort in this direction.
The study found that the respondents value availability
and variety of products at store, store ambience, service and
facilities, and value for money offered at store. These findings
are in consistence with the findings of a number of previous
studies appeared in the literature (Ghosh, 1990; Grewal and
Sharma, 1991; Baker et al, 2002; Mattila and Wirtz, 2001). Further, the finding that the store location is overshadowed by
other store atmospherics is in opposition to the common belief
that Indian customer look for proximity while shopping for
food & grocery. The study brought out a multitude of dimensions with low eigen values (such as store recommendation,
pride associated with purchase from store, fun associated with
purchase from store). This could be attributed to the constitution of the Indian retail industry. Since the customers are exposed to limited choice of retail formats, they do not seem to
expect distinctive characteristics of different stores.
The implication of the above findings is critical for the new
store formats emerging in the market. The results indicate the
nascent preferences of Indian customers related to store atmospherics which could act as a differentiation ground for the
upcoming retailers.
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APPENDIX B: FACTOR ANALYSIS
7 APPENDICES
APPENDIX A: QUESTIONNAIRE
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COMMUNALITIES T ABLE
Continued…
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ROTATED COMPONENT MATRIX
TOTAL CUMULATIVE VARIANCE
Continued…
Continued…
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