JOURNAL OF

GENERAL MANAGEMENT RESEARCH

Online Shopping Behaviour of Customers in

Tier III Cities of India
A Study of Bareilly Region

Naveen Kumar1, Abstract

Upasana Kanchan2 and Today, internet has developed to a highly
Abhishek Gupta3 competitive market. The size of e-commerce
market in India is worth around Rs 9,500
1 Assistant Professor, School of Management, crore, out of which the pure play online shopping
  Gautam Buddha University, Greater Noida, market is worth Rs 1,300 crore. While online
  Uttar Pradesh (India)
shopping globally is growing at around 8-10%,
2 Assistant Professor, Lal Bahadur Shastri Institute of in India the growth rate is upwards of 30%.
  Management & Technology, Bareilly,
  Uttar Pradesh (India) With the growing importance of the online retail
3 Assistant Professor, Shri Ram Murti Smarak College
industry in India, it becomes imperative for E-
  of Engineering & Technology, Bareilly, retailers and internet marketers to understand
  Uttar Pradesh (India) the determinants of online purchase behaviour
of customers to understand what is important to
the Indian online customer.
Purpose: The main purpose of the research is
to understand the behavior of customer while
purchasing online and to analyze the impact
of various demographic factors that affect the
behaviour of online shoppers in India.
Design/methodology/approach: A broad range
of published works in the field of online retail
industry especially in India have been reviewed
ISSN 2348-2869 Print to analyze the factors behind increase in growth
© 2016 Symbiosis Centre for Management of the industry. The author also conducted
Studies, NOIDA an empirical study which uses primary data
Journal of General Management Research, Vol. 4, collected through survey of 220 online shoppers.
Issue 2, July 2017, pp. 72–80

72 Journal of General Management Research

A structured-non-disguised questionnaire has INTRODUCTION
been employed for collecting the information Today we are living in the ‘e-era’. Internet has
from the respondents about their demographics, changed almost everything and has become
security and privacy concerns, technological an integral part of our lives. Year 2014 has
familiarity, past online shopping experiences been a monumental one for internet in India.
and intentions to buy various types of products According to a research report by IAMAI
through internet in future. The collected data
and IMRB, by December 2014, India would
was analyzed with the help of Statistical Package
have crossed 300 million internet users. The
for Social Sciences (SPSS18.0) for windows.
growth in number of internet users in India is
Practical Implications: Study findings entail remarkable. It took 10 years for India to grow
interesting implications for the marketers. They from 10 million to 100 million internet users
need to give adequate attention to consumer and another 3 years to go from 100 million
characteristics while designing their e-marketing to 200 million. While the journey from 200
strategies. Online marketers should target their million to 300 million users took less than
products to young and more educated customers two years and the next 100 million users will
earning higher income and ensure about the high be added in less than 18 months as expected
security of personal information of customers and
of now.
financial transactions along with providing good
experience of online shopping so that customer With the rapid development of new information
may continue purchasing online in future also. technologies, increasing adoption and usage
Major findings: The findings of the study indicate
of internet by customers, the Internet is
that customer online purchase behaviour is fast becoming an important new channel of
significantly related to their gender, education, commerce in a range of businesses that cannot
age, and income. It is found that both the gender be neglected any more. This robust growth in
are likely to purchase goods/services online with internet penetration and usage will disrupt
same frequency. People who have higher income existing business models specifically the retail
are more engaged in purchasing goods over formats.
internet. As per the results of the study, it is found One of the Internet business applications that
that convenience, perceived usefulness of medium, has received much attention in the last few
internet expertise; product risk, security risk, years is Online Shopping. Shopping is still a
convenience risk, non-delivery risk and return/
popular pastime of customers but shopping
shipment policy are the factors which influenced
in a traditional brick & mortar retail formats
the decision of customers while purchasing online.
like mom & pop stores & malls is growing
Originality/value: The framework of the less popular. More & more Indians are opting
research enhances understanding of the factors for online purchase through virtual stores that
affecting customer online shopping behaviour, exist in cyberspace by using computer, mobile,
helps in profiling typical Indian online shoppers television, tablets and other electronic devices
and may help e-marketers developing more specific with in a fraction of minutes.
marketing strategies to increase e-commerce sales.
The e-commerce industry in India that was
Keywords: Online purchase behaviour, Online non-existent a few years ago is today worth $5
shopping, e-shopping, e-retailing, e-commerce
billion. There are 35 million Indians who buy
variety of products online. This number will

Online Shopping Behaviour of Customers In Tier Iii Cities Of India 73

reach around 100 million by 2016, according on the World Wide Web (WWW). They
to a recent research by Forrester Consulting related the reactions of consumers to the
and Google. factors of product perception, shopping
There is a huge opportunity for e-retailers experience, customer service, and perceived
as the average annual growth of this market consumer risk. With regards to product
is estimated around 70% by Internet and perceptions they found that consumers
Mobile Association of India. The no. of were impressed by the breadth of stores but
online buyers is expected to increase to disappointed with the depth of merchandise
approximately 100 million users transacting offered. Shopping experience was found to be
online by 2016. Today, an Indian shopping generally enjoyable, time and effort saving by
online may do two to three transactions per the consumers but the goal directed shopping
month. In just another two to three years as was reported as difficult. Customer service
the market grows and matures, the average was not very satisfactory for many of the
online shopper could be doing four to five respondents. The study also reported perceived
transactions per month. risks as being a barrier to shopping on the
internet.
If as expected, online retailing proves to
be a success and is accepted by the Indian A study by Kunz (1997) on Internet shopping
consumers, it would mean some changes in the found that online shoppers are opinion
way of doing business for the manufacturers leaders, innovators, and domain specific to the
and retailers. To remain competitive, these Internet. The study also found that men are
manufacturers and retailers must decide how more likely to purchase via the Internet, and
to react to the new opportunities. Online those who intend to shop online are likely to
retailers will be successful only if they provide be young. People living in large metropolitan
value to the consumers; hence, Internet areas are less likely to shop online as compared
marketers should understand the customers’ to those living in suburban areas of small
expectations and intentions regarding Internet metropolitan populations. This research also
shopping. summarized the findings of previous studies
on what store characteristics of catalog, in-
home, and Internet shopping influence
LITERATURE REVIEW consumers’ choice of alternate shopping
Many recent studies have investigated mediums. According to Kunz (1997): If
the feasibility of electronic commerce consumers perceive the medium will 1) save
from the manufacturer or the retailer’s them time, 2) be convenient to use/patronize,
side (Berthon, Leyland & Watson, 1996; 3) provide merchandise with good value for
Breitenbach & VanDoren, 1998; Hoffman the price and 4) merchandise of good quality,
& Novak, 1996; Jones & Biasiotto, 1999; 5) involve low risk, 6) provide customer
Murphy, 1998;Peterson, Balasubramanian satisfaction, while 7) offering credit accounts
& Bronnenberg, 1997; Reynolds, 1997). and accepting charge cards, they will be more
But relatively few have focused on this issue likely to choose that alternative shopping
from the consumers’ perspective. Jarvenpaa medium. Another research conducted by
and Todd (1996-97) conducted research on Donthu & Garcia (1999) for consumer
Consumer reaction to electronic shopping characteristics related to online shopping,

74 Journal of General Management Research

it was found that consumers who seek RESEARCH HYPOTHESES
convenience & variety do more shopping On the basis of literature review, following
online. They also found that such people are hypotheses were formulated:
also more innovative and spontaneous.
H1: There is a significant relationship
In a study by, Siu and Cheng (2001) it between gender and the type of products
was found that economic benefits, product purchased online.
availability, security risk are also important
factors in classifying online shoppers. H2: There is a significant relationship
between the gender and online purchase
As highlighted above many studies have frequency.
shown that product type, characteristics, ease
of using technology & its adaptation and H3: There is a significant relationship
customer characteristics are important when between the income and the online purchase
it comes to online purchase behaviour of frequency.
customer. Still there is a dearth of empirical
studies performed on Indian customers for RESEARCH METHODOLOGY
determining the customer acceptance of Population & Sample: Findings of previous
online shopping and this is the reason that researches showed that the youth are the main
e-marketers are facing difficulty in correctly buyers who use the internet to buy products
identifying the target customers and design online. So, as the universe of this study,
appropriate marketing mix strategies. In the researcher considered higher education
order to overcome this limitation, this students and their teachers in Bareilly district
research is done to examine how different who used the internet for different purposes
factors like customer characteristics, product and were above the age of 18 years. A self
characteristics, website quality and services administered questionnaire was developed
affect customer purchase behaviour while and was distributed to 250 students of
shopping online in India. selected institutes. Out of which the useable
questionnaire were 220 only. Sampling
RESEARCH OBJECTIVES technique can be described as convenient
The main purpose of the research is to cum purposive sampling. The collected data
understand the behavior of customer while was analyzed with the help of Statistical
purchasing online and to assess the impact of Package for Social Sciences (SPSS18.0) for
various factors on online purchase behaviour windows. Factor analysis is the main tool that
of customers in India. was considered for data analysis.
Following are the objectives of research: Instrument Development: The data was gathered
through a self administered structured
• To study about the online purchase be- questionnaire. The questionnaire was divided
havior of customers. into two parts. The variables were identified
• Identifying and assessing the impact of with the help of the literature review. The first
various demographic factors that influ- part of the questionnaire included questions
ence an individual customer’s purchase about demographic profile of the respondents.
decisions in an online shopping context. The second part of the questionnaire included

Online Shopping Behaviour of Customers In Tier Iii Cities Of India 75

variables that may affect online purchase students). Most of the respondents were
behaviour of individuals. The questionnaire students while rests were salaried employees.
was pre-tested among a group of students The income of majority of respondents was
and academicians. The suggestions received found to be below Rs. 20 thousands because
from them were incorporated and the revised most of them were students and was getting
questionnaire was then floated for data pocket money only.
collection during December 2014 to January Online Shopping Behaviour: Table 2
2015. shows the online shopping behaviour of the
Data Analysis: The results of the survey are respondents. It can be observed that majority
shown in two sections. In the first section, of the respondents do online shopping. The
the demographic profile of the respondents is mostly purchased category of goods online
represented. The second section provides the is ‘Apparels’ followed by ‘Electronic goods’.
result of the Chi-Square Tests. Majority of the people prefer to purchase
goods from flipkart. Most of the respondents
make online purchase once a month.
DATA ANALYSIS AND RESULTS However, the method of payment adopted
Demographic Characteristics: Table1 shown by majority of the respondents is Cash on
below exhibits the demographic characteristics Delivery.
of the respondents considered for the study.
Table 2: Online Purchase Behaviour
It can be observed that majority of the
respondents were males (54.5%) with age Variable Responses Frequency Percentage
between 20-29years. As far as marital status (N= 220)
was concerned, majority of the respondents Category Clothing 90 40.9
of Goods Electronics 80 36.4
were single (probably because they were purchased goods/Mobile
Books/CDs 26 11.8
Table 1: Demographic Characteristics
Others 24 10.9
Frequency (cosmetics &
Variables Categories Percentage
(N= 220) jewellery, etc.)
Gender male 120 54.5 Websites flipkart 80 36.4
female 100 45.5 used for Amazon 60 27.3
Age under 20 60 27.3 online Jabong 20 9.1
20-29 80 36.4 shopping
Home Shop 18 40 18.2
30-39 40 18.2 Snapdeal 20 9.1
40-49 40 18.2 Online Once a week 80 36.4
Marital single 140 63.6 Purchase Once a month 100 45.5
Status married 80 36.4 Frequency Once in two 40 18.2
Occupa- student 140 63.6 months
tion salaried employee 80 36.4 Payment Credit Card 40 18.2
Monthly below 20K 100 45.5 Method Debit Card 40 18.2
Income 20 K- 30K 60 27.3 Cash on 100 45.5
30K- 50K 60 27.3 delivery
Source: Primary data Net Banking 40 18.2

76 Journal of General Management Research

 Table 3: Cross Tabulation between Gender *
Which Category of Products You Buy from Internet
Electronics Cosmetics and Total
Clothing Books
Goods Jewellery
Count 34 60 16 10 120
Male
Expected Count 49.1 43.6 14.2 13.1 120.0
Gender
Count 56 20 10 14 100
Female
Expected Count 40.9 36.4 11.8 10.9 100.0
Count 90 80 26 24 220
Total
Expected Count 90.0 80.0 26.0 24.0 220.0
Source: Primary data

OTHER RESULTS In order to test the hypothesis, Chi-square

Testing of Hypothesis 1: Another hypothesis Test was conducted. Table 3 shows the cross
is formulated as given below tabulation between gender and the type of
products purchased online by customers.
H0: There is no significant relationship
between gender and the type of products Table 4 shows the results of Chi-Square test.
purchased online. The significance value is 0.000 which is less
than 0.05 and therefore the null hypothesis is
H2: There is a significant relationship between
rejected and H2 is accepted which states that
gender and the type of products purchased
there exists a relationship between gender
online.
and the type of product purchased online by
Table 4: Chi-Square Tests customers.
Value df Asymp. Sig.
(2-sided) Testing of Hypothesis 2: Another hypothesis
Pearson Chi-Square 25.824a 3 .000 is formulated as given below-
Likelihood Ratio 26.609 3 .000
H0: There is no significant relationship
Linear-by-Linear .167 1 .682
Association between gender and online purchase
N of Valid Cases 220 frequency.
a. 0 cells (.0%) have expected count less than 5. The H3: There is a significant relationship between
minimum expected count is 10.91. gender and online purchase frequency.
Table 5: Cross-tabulation between Gender
How Frequent do You Buy Online?
Total
Once a Week Once a Month Once in Two Months
Count 40 60 20 120
Male
Expected Count 43.6 54.5 21.8 120.0
Gender
Count 40 40 20 100
Female
Expected Count 36.4 45.5 18.2 100.0
Count 80 100 40 220
Total
Expected Count 80.0 100.0 40.0 220.0
Source: Primary data

Online Shopping Behaviour of Customers In Tier Iii Cities Of India 77

In order to test the hypothesis, Chi-square in Table 8. The significance value is 0.04
Test was conducted. Table 5 shows the which is less than 0.05 and therefore the null
cross tabulation between gender and online hypothesis is rejected and H4 is accepted
purchase frequency. which states that there exists a relationship
between income levels of buyers and their
Table 6: Results of Chi-Square test
online purchase frequency.
Value df Asymp. Sig.
(2-sided) Table 8: Chi-Square Tests
Pearson Chi-Square 2.200a 2 .333 Value Value df Asymp. Sig.
Likelihood Ratio 2.206 2 .332 (2-sided)
Linear-by-Linear .118 1 .731 Pearson Chi-Square 10.024a 4 .040
Association Likelihood Ratio 11.138 4 .025
N of Valid Cases 220 Linear-by-Linear 7.882 1 .005
Association
a. 0 cells (.0%) have expected count less than 5. The
minimum expected count is 18.18. N of Valid Cases 220
a. 0 cells (.0%) have expected count less than 5. The
Testing of Hypothesis 3: hypothesis 4 is minimum expected count is 8.73.
formulated as given below:
H0: There is no significant relationship DISCUSSION AND PRACTICAL
between income level of buyers and online IMPLICATIONS
purchase frequency. The results of the study indicate that most
H4: There is a significant relationship popular category of goods purchased online
between the income and the online purchase is ‘Apparels’ followed by ‘electronic gadgets’.
frequency. Most of the respondents purchase goods
via Flipkart and Amazon. Majority of
Again Chi-square Test was conducted to
respondents pay cash on delivery and make
test the hypothesis. Table 7 shows the cross
online purchase once a month. The findings
tabulation between income levels and online
of Chi-square Tests indicate that males and
purchase frequency.
females shop online for different categories of
Results of Chi-Square Tests are shown goods. Males mainly purchase electronic goods

Table 7: Cross-Tabulation between Monthly Income

How Frequent do You Buy Online?
Total
Once a Week Once a Month Once in Two Months
Count 34 50 28 112
below 20K
Expected Count 40.7 50.9 20.4 112.0
Monthly Count 20 20 8 48
20 K-30K
Income Expected Count 17.5 21.8 8.7 48.0
Count 26 30 4 60
30K-50K
Expected Count 21.8 27.3 10.9 60.0
Count 80 100 40 220
Total
Expected Count 80.0 100.0 40.0 220.0
Source: Primary data

78 Journal of General Management Research

and mobiles while females purchase apparels fraction of internet users in India are currently
online most of the time. Another result has online shoppers. The reason could be that it is
shown that online purchase frequency has no not the technology but the way customers feel
relationship with the gender that means both about high-tech purchasing that is holding
male and female buyers shop online with the back the development of the industry. Hence
same frequency. Also it has been tested that this is imperative that marketers understand
there is a significant relationship between the depth of customer intentions for this
the income level of buyers and their online medium of retailing.
purchase frequency, i.e. people with higher It can be concluded on the basis of study that
income purchase more online as compared to online shopping is gaining popularity among
those having less income. people of young generation. Higher income
groups and educated people are purchasing
LIMITATIONS AND SCOPE FOR more via e-retailing websites. People have
FURTHER RESEARCH hesitations in doing online shopping due
The study was aimed to meet all the objectives to security concerns, non-delivery risk,
and ultimately all objectives were met, but still convenience risk and complex return policies
a few limitations were identified in the course of the e-retailer. At the same time people are
of the study. The study was focused on the resistant to change because of technological
higher education students and teachers in two complexity in making online purchase.
districts and this could limit the generalization Companies involved in online retailing should
of findings and references to entire section of focus on building trust-worthy relationship
online customers. However, this creates an between producers and customers.
ideal opportunity to consider more diverse
demographic group of respondents. Another REFERENCES
limitation was the use of limited number [1] Alba, J., Lynch, J., Weitz, B., Janiszewski, c.,
of variables in the study. Researchers can Lutz, R., Sawyer, A. and Wood, S. (1997)
use more variables such as, website design, ‘Interactive home shopping: consumer, retailer
service quality, trust, shopping motives etc. to and manufacturer incentives to participate in
electronic marketplaces’, Journal of Marketing,
explore consumer behaviour towards online 61 :3, pp. 38-54.
shopping. [2] Ansary, Osama El. And Roushdy, Ahmed Samir
(2013), Factors Affecting Egyptian Consumers’
CONCLUSION Intentions for Accepting.
[3] Bai B, Law R, Wen I (2008) The impact of
Though online shopping is very common website quality on customer satisfaction and
outside India, its growth in Indian market, purchase intentions: evidence from Chinese
which is a large customer market, is still not online visitors. Int J Hosp Manag 27(3):
in line with the global market. According 391–402.
to India B2C E-Commerce Report 2013, [4] Brecht, F., Baumann, A. and Günther O. (2011),
Shopping Online – Determining Consumer
e-tailing accounts for less than 1 percent of Acceptance of Online Shops, Proceedings of the
the overall retail market in India in 2012. Seventeenth Americas Conference on Information
While it accounts for over 5 percent if the Systems, Detroit, Michigan August 4th-7th 2011.
total retail market in China and 10% in the [5] Clarke, K. R. (July 2000). Shopping for apparel
UK and the US. This shows that only a small online gains popularity, from http://www.

Online Shopping Behaviour of Customers In Tier Iii Cities Of India 79

 pwcglobal.com/extweb/ncsurvres.nsf/docid/3D [19] Maditinos Dimitrios, Sarigiannidis Lazaros
29888D297A7AA8852569230046325C and Kesidou Elisavet (June 2009), Consumer
[6] Donthu, N. and Garcia, A. (1999), ‘The Internet Characteristics and Their Effect on Accepting
Shopper’, Journal of Advertising Research, Online Shopping, In the Context of Different
39(2).52-58 Product Types, Proceedings of 5th HSSS
[7] Fram, E. H., & Grandy, D.B. (1997), “Internet Conference, Democritus University of Thrace,
shoppers: Is there a surfer gender gap?”, Direct Xanthi, Greece.
Marketing, Vol.59, No. 1, pp. 46-50. [20] Mathwick C, Rigdon E (2004) Play, flow, and
[8] Gupta, Sunil, Donald R Lehmann and Jennifer the online search experience. J Consumer Res
Ames. Stuart (2004), “Valuing Customers,” 31(2): 324–332.
Journal of Marketing Research (JMR), 41(1), [21] Mathwick, C., Malhotra, N. K., & Rigdon, E.
7-18. (2001). Experiential value: Conceptualization,
[9] Hawkins, D., Best, J. and Coney, K. A. measurement and application in the catalog
1995, Consumer Behaviour: Implications for and Internet shopping environment. Journal of
Marketing Strategy, Chicago II, Irwin. Retailing, 77(1), 39-56.
[10] Hollensen, S. (2004) Global Marketing- A [22] Online Shopping”, The Journal of American
Decision oriented Approach (3rd edition), Academy of Business, Cambridge, Vol. 19, No.
Pearson Higher Education. 1, pp. 191-201.
[11] Jain Sanjay K. and Jain Manika (2011), [23] Peterson, RA., Balasubramanian, S. and
Exploring Impact of Consumer and Product Bronnenberg, BJ. (1997) ‘Exploring the
Characteristics on E-Commerce Adoption: A implications of the internet for consumer
study of consumers in India, Proceedings of 5th marketing’, Journal of the Academy of Marketing
International Conference on Services Management. Science, 25: 4, pp. 329-346.
[12] Jarvenpaa, S.L. and Todd, PA. (1996), [24] Phau, I. and Sui, M.P. (2000) ‘Factors
‘Consumer reactions to electronic shopping on influencing the type of products and services
the World Wide Web’, International Journal of purchased over the internet’, Internet Research:
Electronic Commerce, 1:2, pp. 59-88. Electronic Networking Applications and Policy,
[13] Kotler, P. and Armstrong, G. (2007), Principles 10(2), pp. 102-113
of Marketing (12th edition), Upper Saddle [25] Smith, d. A. and Rupp, T W. (2003), ‘Strategic
River, Prentice-Hall. Online Customer Decision Making: leveraging
[14] Kumar Shefali, (August 2000), Consumers’ the transformational power of internet.’ Online
Behavioral Intentions Regarding Online Information Review 27:6, 418-432.
Shopping, Published thesis of University of [26] Sultan, F., & Henrichs, R.B. (2000), “Consumer
North Texas. preferences for Internet services over time:
[15] Kunz, M.B. (1997), “On-line customers: initial explorations”, The Journal of Consumer
identifying store, product and consumer Marketing, Vol. 17, No. 5, pp. 386-403.
attributes which influences shopping on the [27] The Internet Shopper, Business World Marketing
Internet”. Published doctoral dissertation. The Whitebook 2013-14.
University of Tennessee, Knoxville. [28] Then, N., & DeLong, M. (1999). Apparel
[16] Li Jianguo (January2001), A Framework of shopping on the Web. Journal of Family and
Individual Consumer’s Acceptance of Online Consumer Sciences, 91(3).
Shopping. [29] Wu, S. (2003), ‘The Relationship between
[17] Li, N & Zhang, P 2002, Consumer online Consumer Characteristics and attitude towards
shopping attitudes and behavior: An assessment Online Shopping’, Marketing Intelligence and
of Research, Paper presented at the Eighth Planning 21: 1, 37-44.
Americas Conference on Information Systems. [30] Zhou Lina, Dai Liwei and Zhang Dongsong
[18] Lin Pin-Wuan (2006). The Effects of Consumers’ (2007), Online Shopping Acceptance Model —
Online Shopping Goals and their Characteristics A Critical Survey of Consumer Factors In Online
on Perceived Interactivity and Shopping Shopping, Journal Of Electronic Commerce
Behaviors, Published Thesis of University of Research, Vol 8, No.1.
Missouri-Columbia

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