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International Journal of Research in Economics and Social Sciences (IJRESS)
Available online at: http://euroasiapub.org
Vol. 8 Issue 3, March – 2018, Special Issue, pp. 111~119
ISSN(o): 2249-7382 | Impact Factor: 6.939 |
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
111
Predictors of Online Grocery Shopping: Study in Delhi NCR region of India
Dr. Pallavi Sharda Garg,
Assistant Professor,
Amity Institute of Competitive Intelligence & Strategic Management,
Amity University, Noida
Dr. Monika Saxena,
Assistant Professor,
Amity Institute of Competitive Intelligence & Strategic Management,
Amity University, Noida
With the increasing use of smartphones and better reach of internet penetration, the world of
ecommerce is slowly and steadily gaining momentum in India. A survey by Goldman Sachs in
2016 concludes that 52% of the consumers prefer online retail in comparison to offline. The
buying habit of Indian consumers is moving towards a shift from offline to online mode owing to
various factors. The online grocery market is still in its nascent stages and has many barriers to
its growth. Though the majority of customers still prefer buying groceries from local kirana
stores(‘mom and pop’stores) or offline stores but more consumers are going for trial and test
method to checkout various online grocery stores also. As per the report by eMarketer in 2017,
online grocery market is anticipated to be the biggest propeller and contributor of growth in the
ecommerce sector over the next five years. The Indian online grocery market has witnessed the
emergence of many players in past years but only few have been able to survive. The current study
is an attempt to identify the factors which are responsible for the choice of consumers for
selection of an online grocery store. The data analysis is a result of questionnaire responded by
194 respondents in Delhi NCR region in the year 2016.
Keywords: Online shopping, grocery, etailing, Online retail, e-grocery, Factor Analysis
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
112
Introduction:
Online retail is flourishing as consumers become comfortable while shopping online. The
expansion of the industry can be credited to increase in internet and mobile penetration,
acceptance of online modes of payments and favorable demographics. The e-commerce sector has
provided unique ways through which companies can connect with the consumer. The majority of
the consumer is young, net savvy Indian consumer in the age group of 15 – 35 who enjoys the
online shopping experience on his smartphone or laptop. The internet has opened up an ocean of
opportunities for the marketers. Every other day a new business idea is emerging in the
entrepreneurial mind of the talented which is exploiting the inherent advantages of the internet.
The main advantage of the internet is convenience and 24 * 7 availability which has lured the
shoppers to shop/purchase online. In today’s fast moving world where both husband and wife are
working, taking time out for purchasing groceries is also a tedious one. This problem has been
captured in form of a business opportunity and has led to the opening up of many online grocery
shops. A huge part of the urban population is shopping online for supplies such as groceries apart
from clothing and footwear. Apart from the local grocery stores coming up online, there are
exclusive stores which have only online presence. Also major e-commerce giants like Amazon,
flipkart have also ventured into the market. The competition is stiff and surely Darwin’s theory of
survival of the fittest is applicable on online grocery stores also. The current study is aimed at
identifying the factors which drives consumers for online grocery shopping.
The initial firms were founded in 2011 and since then online grocery industry has been expanding
and has also received funding from angel investors and venture capitalists. The market’s rise can
be attributed to consumer’s mindset for convenience, as well as huge discounts that have been
offered by the online stores. The growth in spending capacity of consumers and increasing digital
awareness are also responsible for progress of e-grocery market in India.
The e-grocery market in India is currently undergoing major structural shifts owing to severe
competition among players. The need of the hour is to understand the mindset and psychology of
the consumer about his preferences and reasons for selecting a particular e-store.
Literature review:
The online spending of consumers is increasing day by day. The trend is reflected in numerous
reports which show an increase in the overall ecommerce sector. But the path has not been easy
for the ecommerce marketer. There have been numerous challenges which they had to encounter
so that the consumer is attracted towards online shopping. One of the barriers was to provide an
interactive and user friendly interface to the consumer so that he does not feel the absence of the
face to face interaction. This has been an important criterion during the design of the website so
that the consumer spends time on the merchant website.
Chiang & Dholakia (2003) have concluded that convenience and product type motivates a
consumer to get involved in online shopping. Hanus (2016) concluded that most important
advantages of online shopping are convenience and time saving. Sheth & Sisodia (1999) in their
research emphasized upon time and location as the major reasons which distinguishes online
shopping from traditional shopping. Park & Kim (2003) have studied the association amongst
several features of online shopping and consumer purchase behavior. They concluded that
information quality, user interface quality, and security perceptions impact information
satisfaction and relational benefit which are significantly related to consumer’s site commitment
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
113
and actual purchase behavior. Yulihasri et. al(2011) have concluded compatibility, usefulness,
ease of use and security as important predictors towards buying behaviour in on-line shopping.
Moshrefjavadi et. Al. (2012) have emphasized that e-retailers should make their website safer and
assure customers for delivery of their products. Lee & Lin(2005) have concluded through their
research that the features of web site design, reliability, responsiveness, and trust affect the
service quality and customer satisfaction.
Shergill & Chen(2005) also concluded the same in their research and identified four major
feactures which affect the perception of consumer for online shopping. They are website design,
website reliability/fulfilment, website customer service and website security. Grabner(2002)
emphasized on the role of consumer trust as a necessary element for the diffusion and acceptance
of electronic commerce. Boyer & Hult(2005) results indicate that eBusiness-, product-, and
service-quality, all have a substantial direct impact on customer behavioral intentions towards
repurchase. Ramus & Neilsen(2005) concluded in their research consumers view internet grocery
shopping better compared to conventional grocery shopping because of convenience, product
range and price.
Objective and Methodology
The research aims to identify the factors which motivate the consumers to engage in shopping of
groceries online. The further analysis was done using Factor Analysis to segregate the variables
into factors and Kruskal Wallis test to identify the most important variable which motivates
consumers towards online grocery shopping. The authors have used primary survey as a tool for
data collection for which a questionnaire was developed.
Research Design
A set of 13 variables was identified on the basis of past researches to study the consumers
intentions towards online grocery shopping. These were then converted into a questionnaire. The
data presented and analyzed in this paper was collected from an online (web-based) survey of
consumers of Delhi NCR Region using self-administered questionnaires. The total respondents
were 193 out of which 110 respondents (57%) have done online grocery shopping while 83(43%)
have not done online grocery shopping.
The respondents were asked to rate these variables on a five point Likert scale. The variables used
for the purpose of this study are time saving, convenience, return policy, home delivery, on-time
delivery, multiple delivery slots, price, discounts & coupans, range of products, multiple payment
options, quality products, no grocery store nearby and 24 * 7 availability.
Table 1. Definition of the variable
X1
Time saving
X6
Multiple delivery slots
X11
Quality Products
X2
Convenience
X7
Price
X12
No grocery store
nearby
X3
Return Policy
X8
Discounts & Coupons
X13
24 * 7 availability
X4
Home delivery
X9
Range of products
X5
On time delivery
X10
Multiple payment
options
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
114
Analysis & Findings:
With the help of Factor Analysis, we are trying to segregate the variables into set of manageable
factors.
The Tables 1 and 2(Annexure 1) present the results of Factor analysis using SPSS software. The
results of factor analysis were obtained after two iterations. The result of the first iteration has
been summarized in Table 1 (Annexure 1). The result of Bartlett Test of Sphericity leads us to the
rejection of null hypothesis that the variables are uncorrelated. The approximate chi-square is
671.652with 78 degrees of freedom. The value of Kaiser-Meyer-Olkin Measure of Sampling
Adequacy is .860 which is greater than .50 which makes the data fit to be analysed through factor
analysis.
In order to determine the number of factors to be extracted we need to compute the eigenvalue.
Higher the eigenvalue, higher is the variance explained by the factor. Therefore we select only
those factors which have an eigenvalue greater than 1. It is clear from the above results that total
of 3 factors have been extracted with 63% of Total Variance Explained (T.V.E). As per the
communalities table we will consider only the variables with factor loading greater than .5.
Accordingly the variable X13 (24 * 7 availability) is removed and we will run the factor analysis
with reduced set of 12 variables.
After the second iteration the results are shown in Table 2(Annexure 1). The result of Bartlett Test
of Sphericity leads us to the rejection of null hypothesis that the variables are uncorrelated. The
approximate chi-square is 628.780 with 66 degrees of freedom. The value of Kaiser-Meyer-Olkin
Measure of Sampling Adequacy is .857 which is greater than .50 which makes the data fit to be
analysed through factor analysis.
It is clear from the above results that 3 factors are extracted with 65.9% TVE; and the 12 variables
converge on these three factors. From the rotated factor matrix following observations can be
drawn : X1, X2, X4, X5, X6,X11 have high factor loading under Factor 1 i.e. .722, .771, .750, .804,.799
respectively. X7, X8, X9,X10 have high factor loading under Factor 2 i.e. .741, .838, .789, .632
respectively. X3, X12 have high factor loading under Factor 3 i.e. .531, .746, respectively.
The above discussion suggests that Factor 1 is a combination of 6 variables Time saving,
Convenience, Home delivery, on time delivery, Multiple delivery slots and Quality Products. They
together represent the ease of using online stores and therefore the factor can be named as Value
for time or Time Value. Factor 2 is formed from Price, Discounts & Coupons, Range of products
and multiple payment options. They are pointing towards the attraction of customers for lower
price, array of products and various payment options given . Hence we rename Factor 2 as
Economic Value. Return Policy and No grocery store nearby are falling under Factor 3. These
variables represent the reason to select online grocery or we can say they are the reasons which
make online grocery stores hassle free. Hence the factor is renamed as Shopping Ease.
The Table 2 summarizes the results of factor analysis.
S.no
Variables
Name of the Factor
1
Time saving, Convenience, Home delivery, on
time delivery, Multiple delivery slots and
Quality Products.
Value for time or Time Value
2
Price, Discounts & Coupons, Range of
products and multiple payment options
Economic Value
3
Return Policy and No grocery store nearby
Shopping Ease
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
115
Next question arises that out of the 13 variables taken which one is responsible for attracting the
customers towards online grocery shopping. In order to find out the same a Kruskal Wallis test is
performed on the data. The test also verifies the null hypothesis that
H0: There is no difference between the influencing variables.
H1: There is difference between the influencing variables.
Table 3(Annexure 1) shows the results of Kruskal Wallis Test variables influencing the adoption
of online grocery shopping. The results clearly show that Home Delivery is the most important
reason for choosing online grocery shopping. It has a mean rank of 949.49. It is followed by Time
Saving at a mean rank of 863.62. The lowest mean rank has been secured by No Grocery Store
Nearby which means that the location of grocery store is not much of a luring variable for the
consumers. The other listed variables have more impact for shaping the consumer’s mindset for
online grocery shopping. If we check the Monte Carlo significance at 95% confidence level we find
that it is less than .05. This means that the null hypothesis is rejected and we conclude that there
is difference between the influencing variables.
Conclusion:
The business opportunity for online grocery stores is still largely untapped. The marketer needs
to understand the consumer psychology and accordingly customize his services and offerings. The
e-grocery stores have visibility and clientele only in metro cities, they can look for business
prospects in tier 1 and tier 2 cities also. The consumers preferring online groceries or online
shopping are searching for convenience as well as value for money. This is clearly indicated from
the findings which suggest that the consumers are looking for hassle free shopping in terms of
home deliveries and saving on time. The research has also formulated three basic components for
the success of e-grocery stores: Time Value, Shopping Ease and Economic Value. The e-grocery
stores which are already successful need to keep the following factors always at the topmost
priority to keep the consumers with them while the new players in the market have to design their
services around these three factors.
The way ahead is full of challenges for the existing players as well as new entrants. As the e-
grocery stores are also dealing with perishable items hence they need to maintain the steady
supply of the product which is fresh and of high quality. Not only they need to focus on the
suppliers of the products but they also have to provide on-time delivery to the consumers, This
requires a real time tracking with the logistics partner so that the goods are delivered as per the
quality and packaging standards. Another point to consider is the assortment or the variety in
product which they offer to the customer so that he stays with you and does not switch to the
competitor. This also raises the concerns of maintaining inventory and incurring the inventory
costs. The marketer has to constantly make efforts to keep the trust of consumer intact. This
would require proper return policies and secure money transactions. Key to success is customer
service and after sales support that is unparalleled.
The research has tried to uncover the factors which motivate the consumers towards online
shopping and listed certain challenges for the e-groceery stores in India. Though the path is
challenging but yet achievable.
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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Annexure 1:
Table 1: Results of Principal Component Analysis (Iteration 1)
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
.860
Bartlett's Test of
Sphericity
Approx. Chi-Square
671.653
df
78
Sig.
.000
Communalities
Initial Eigenvalues
Initial
Extraction
Total
% of
Variance
Cumulative
%
time_saving
1.000
.529
5.66
43.51
43.51
Convenience
1.000
.622
1.41
10.86
54.37
return_policy
1.000
.536
1.15
8.88
63.25
home_delivery
1.000
.718
0.95
7.28
70.53
on_time_delivery
1.000
.693
0.80
6.15
76.68
multiple_delivery_slots
1.000
.670
0.64
4.94
81.62
Price
1.000
.708
0.60
4.62
86.24
discounts_coupons
1.000
.780
0.44
3.42
89.66
range_rpoducts
1.000
.669
0.34
2.59
92.24
multiple_payment_options
1.000
.699
0.31
2.35
94.60
quality_products
1.000
.557
0.26
2.00
96.59
no_grocery_nearby
1.000
.635
0.24
1.9
0.24
availability_24_7
1.000
.407
0.20
1.54
0.20
Extraction Sums of Squared Loadings
Rotation Sums of Squared
Loadings
Factor
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
Factor 1
5.66
43.51
43.51
4.15
31.91
31.91
Factor 2
1.41
10.86
54.37
2.87
22.04
53.95
Factor 3
1.15
8.88
63.25
1.21
9.30
63.25
Rotated Component Matrixa
Component
1
2
3
time_saving
.698
.204
.014
Convenience
.722
.298
.110
return_policy
.474
.261
.493
home_delivery
.747
.367
-.159
on_time_delivery
.822
.120
-.050
multiple_delivery_slots
.805
.122
-.084
Price
.217
.764
.278
discounts_coupons
.165
.850
.172
range_rpoducts
.217
.773
-.154
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
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Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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multiple_payment_options
.453
.596
-.373
quality_products
.568
.473
-.105
no_grocery_nearby
-.098
-.007
.791
availability_24_7
.612
.140
.113
Table 2: Results of Principal Component Analysis (Iteration 2)
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.857
Bartlett's Test of
Sphericity
Approx. Chi-Square
628.780
Df
66
Sig.
.000
Communalities
Initial
Extraction
Total
% of
Variance
Cumulative
%
time_saving
1.000
.558
5.37
44.73
44.73
convenience
1.000
.689
1.40
11.66
56.39
return_policy
1.000
.584
1.14
9.47
65.85
home_delivery
1.000
.718
0.86
7.14
72.99
on_time_delivery
1.000
.673
0.80
6.65
79.64
multiple_delivery_slots
1.000
.666
0.61
5.12
84.76
price
1.000
.704
0.45
3.78
88.54
discounts_coupons
1.000
.775
0.34
2.83
91.37
range_rpoducts
1.000
.682
0.31
2.55
93.93
multiple_payment_options
1.000
.721
0.27
2.27
96.20
quality_products
1.000
.556
0.24
2.03
98.23
no_grocery_nearby
1.000
.576
0.21
1.77
100.00
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Factor
Total
% of
Variance
Cumulative %
Total
% of
Variance
Cumulative %
1
5.37
44.73
44.73
3.84
31.99
31.99
2
1.40
11.66
56.39
2.85
23.75
55.74
3
1.14
9.47
65.85
1.21
10.11
65.85
Rotated Component Matrixa
Component
1
2
3
time_saving
.722
.184
.050
convenience
.771
.260
.164
return_policy
.504
.219
.531
home_delivery
.750
.370
-.133
on_time_delivery
.804
.146
-.066
multiple_delivery_slots
.799
.141
-.091
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
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Email:- editorijrim@gmail.com, http://www.euroasiapub.org
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price
.223
.741
.323
discounts_coupons
.164
.838
.213
range_rpoducts
.205
.789
-.133
multiple_payment_options
.432
.632
-.369
quality_products
.544
.499
-.106
no_grocery_nearby
-.139
-.002
.746
Table 3 : Result of Kruskal Wallis Test on the different variables influencing the adoption
of online grocery shopping
Var
N
Mean Rank
Time Saving
110
863.62
Convenience
110
846.55
Hassle free return policy
110
616.45
Home delivery
110
949.07
On - time delivery
110
744.99
Multiple Delivery Slots
110
712.09
Price
110
621.47
Discounts & Coupons
110
667.05
Wide Array of products
110
717.91
Multiple Payment Options
110
747.25
Good Quality Products
110
679.15
No Grocery shop nearby
110
356.71
24 * 7 Availability
110
779.18
Total
1430
Test Statisticsa,b
Factor
Chi-Square
171.305
df
12
Asymp. Sig.
.000
Monte Carlo Sig.
Sig.
.000c
99% Confidence
Interval
Lower Bound
0.000
Upper Bound
.000
International Journal of Research in Economics and Social Sciences (IJRESS)
Vol. 8 Issue 3, March- 2018
ISSN(o): 2249-7382 | Impact Factor: 6.939
International Journal of Research in Economics & Social Sciences
Email:- editorijrim@gmail.com, http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
119
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