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CUSTOMER PURCHASE BEHAVIOR TOWARDS ONLINE SHOPPING: WITH
SPECIAL REFERENCE TO THOOTHUKUDI CITY
X. JUDE CHRISTO CEDRIC
Ph.D Research Scholar, V.O. Chidambaram College, Thoothukudi– 628 008
Affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli – 627012,
Tamil Nadu, India.
ABSTRACT
Online shopping is a form of electronic marketing that allows customers to buy products and
services directly from retailers over the internet using a web browser. This paper examines
the effects of customers’ online shopping experiences in Thoothukudi City. The following
goals were established when this research began:
1. To study the socio-economic characteristics of online consumers.
2. To identify the motive for buying online
3. To find out the satisfaction of consumer towards online shopping
Data for the analysis was gathered from both primary and secondary sources. A random
sampling technique was used to pick 175 online shopping customers for the current analysis
and the data and material about the years 2017-2018. Books, magazines, internet websites,
journals, newspapers, and other secondary data sources were used. Various statistical
methods such as simple percentage analysis, averages, T-Statistic, chi-square test, Garrett
ranking, and probability analysis were used to collect data. The respondents’ preference for
motivating factors for online product convenience was first, followed by the low price. The
superior range was ranked fourth, and easy to buy was ranked third. The fifth and sixth
positions were awarded for time savings and versatility in delivery time and place. Product
comparison was ranked eighth, and accessibility was ranked seventh. Rising wages, the role
of women in the workforce, infrastructure improvements, lifestyle changes, improvements in
computer literacy, and the availability of internet access are all expanding this demand and
hastening the fulfilment of customer preferences for online shopping. The young and
optimistic Indian consumers are heavily influenced by online shopping. Based on the above
debate, it appears that online shopping in Thoothukudi City has a bright future. Customers
have the best choice for saving money and time by shopping online. Online shopping’s
success is determined by its popularity, brand value, and specific promotional policies.
Keywords: online shopping, web browser, internet, consumer preference, lifestyle.
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INTRODUCTION
During the last decade, the internet has been the fastest-growing medium. In India, the
growing number of internet users offers a promising future for online shopping. Online
shopping, in particular, is a rapidly expanding e-commerce sector. Online shopping is a
rapidly growing phenomenon worldwide, especially among countries with advanced
information and communication technologies for internet marketing. The internet is now not
only a networking and connectivity tool but also a global business platform. Some customers
are now engaging in online shopping due to its many advantages and the opportunity to gain
new shopping experiences across online platforms. This paper examines the effects of
customers’ online shopping experiences in Thoothukudi City.
IMPACT OF ONLINE SHOPPING IN INDIA
Online stores are commonly available 24 hours a day, and many consumers have internet
access both at work and at home. In 2015, India had 408.4 million internet users. As a result,
E-commerce revenues in India will increase by more than five times by 2016, jumping from
the U.S. $1.6 billion in 2012 to the U.S. $8.8 billion in the year 20161. E-commerce market
growth in India is influenced by the massive investment by venture capitalists, expansion of
e-commerce in nonmetropolitan India, the online presence of large retailers, and mobile and
social media2.
By December 2014, India’s Internet users would have risen to 302 million, a 32 percent
increase year over year. It took more than a decade for India’s Internet to grow from 10
million to 100 million users and three years to grow from 100 to 200 million users. However,
it took only a year to move from 200 to 300 million users3. The online user growth has
primarily fueled the improved network infrastructure and growing need for online content
consumption4.
E-commerce sales in North America grew 13.9 percent to a world-leading $364.66 billion in
the year 20125. According to Interactive Media in Retail Group (IMRG), a U.K. Online Retail
Trade Organization, Global e-commerce sales will pass the 1 trillion euro ($1.25 trillion)
mark by 20136. Clothing, computers, and consumer electronics will continue to be everyday
purchases; these three categories currently account for 40% of all online sales, and this is
unlikely to change in the immediate future7.
As customers increasingly accept the benefits of shopping online, internet penetration and
infrastructure in emerging markets are improving8. According to Forester Research, the size
of the Indian e-commerce market is $1.6 billion in the year 2012, and it is expected to grow
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to $3 billion in 3 years. Thus, it might reach $15 billion by 2020, whereas it is expected to
contribute 4 percent of GDP9.
There is no hesitation that Indian consumer Internet space is undoubtedly on the increase,
with more than 200 million Internet users and predictable to have the second-largest Internet
user base in the world likely, and the largest in terms of incremental evolution, with 330
million to 370 million Internet users in 2015 the market is here to grow10. Social networking
sites also play an essential role in driving consumers online and getting them to engage with
brands. India has 51 million Facebook users, the third-largest audience in the world after the
U.S. and Brazil11.
OBJECTIVES
This study was started with the following objectives:
1. To study the socio-economic characteristics of online consumers.
2. To identify the motive for buying online
3. To find out the satisfaction of consumer towards online shopping
METHODOLOGY
Data for the analysis was gathered from both primary and secondary sources. Primary data
was obtained using the respondent field survey approach with the aid of a specially crafted
questionnaire. The district of Thoothukudi was chosen for this study on purpose. A random
sampling technique was used to pick 175 online shopping customers for the current analysis
and the data and material about the years 2017-2018. In addition, books, magazines, internet
websites, journals, newspapers, and other secondary data sources were used. Various
statistical methods such as simple percentage analysis, averages, T-Statistic, chi-square test,
Garrett ranking, and probability analysis were used to collect data.
REVIEW OF LITERATURE
Vellido et al. (2000)12 found that nine factors influence a user’s perception of online shopping
in his study. Among these variables, users’ risk perceptions were the most critical
differentiator between those who bought online and those who did not. Other perceptual
considerations included the ability to monitor and expedite the shopping process, the
availability of produce, customer service, and the ease with which the shopping site could be
used.
Lohse et al. (2000)13 used panel data to explore the predictors of online purchasing behaviour.
They found that the typical online consumers characterised by their wired lifestyle and are
time-starved. As a result, they proposed offering personalised information to online shoppers
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who buy standard or repeat products, giving them a sense of increased convenience and
enabling them to make faster purchasing decisions.
Goldsmith and Bridges (2000)14 found that consumers who handled that it was easy to buy
over the web were more likely to buy, inferring that confidence leads to higher purchase
likelihood. A positive relationship between Internet experience/confidence and the amount of
shopping thus found in his study.
Price, quality of service and content, speed and reliability of delivery, ease of online ordering,
and trust in vendors are all important factors for consumers considering online purchases that
will increasingly decide their propensity to engage in e-commerce, according to Goldman
Sachs (2001).15
Sang Yong Kim and Young-Jun Lim (2001)16 inspect the relationship between consumers’
perceived importance and satisfaction with Internet shopping. They find that entertainment,
convenience, reliability, information quality, and speed are essential for choosing shopping
sites and find that entertainment, speed, information quality, and reliability are related to
consumers’ satisfaction with Internet shopping.
Miyazaki and Finandez (2001)17 attempted to explore the relationship among the internet
experience levels, risk perception and online purchasing rates. They analysed that a higher
level of internet experience could lead to lower risk perception regarding online shopping,
fewer specific concern regarding system security or fraud and more concerns regarding
privacy. Furthermore, consumer participation in other remote purchase methods relates to
lower risk perception regarding online shopping. It concluded that higher internet experience
and other remote purchasing methods were related to lower levels of supposed risk towards
online shopping, resulting in higher online purchase rates.
Athiyaman (2002)18 also highlighted the importance of such word of mouth
recommendations, finding that social influences are an essential determinant of internet users’
intention to purchase air travel online, second only to the attitude towards online purchasing.
ANALYSIS AND INTERPRETATION
The current study is about consumers’ online shopping experiences in Thoothukudi City. The
frequency and percentage research were used to investigate the socio-economic status of
online shopping customers.
Socio-personal characteristics of respondents (n=175)
Variable Categories Percentage
Sex Male 65.45
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Female 34.55
Age (in years) Below 30 20.91
30 – 40 44.55
40 – 50 31.36
50 and above 3.18
Education Illiterate 3.64
School Level 11.36
College Level 70.91
Technical Level 14.09
Family Size Below 3 9.55
3 – 5 60.91
Five and above 29.54
Family Type Nuclear Family 83.64
Joint Family 16.36
Marital Status Unmarried 14.54
Married 83.64
Widow/ Widower 1.82
Occupation Agricultural Labourer 38.64
Government employee 31.36
Private employee 25.00
Unemployed/student/retired/house
wife
5.00
Monthly income Less than Rs.5,000 2.73
Rs.5,001 – Rs.10,000 41.36
Rs.10,001 – Rs.15,000 28.64
Rs.15,001 – Rs.20,000 10.00
Above Rs.20,000 17.27
Source: Primary Data
RESULTS AND DISCUSSION
In the table above, the socio-economic characteristics of respondents were analysed and
presented. It has been deduced that 65.45 percent of the population is male, and 34.55 percent
is female. It was deduced that the bulk of the respondents (44.55%) are between the ages of
30 and 40, with 40 to 50 years accounting for 31.36 percent of the total. 20.91 percent of the
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respondents are under 30 years old, with 50 years old accounting for 3.18 percent of the total.
The respondents were 34.59 years old on average.
It was discovered that 11.36 percent of the respondents had a high school diploma, with 14.09
percent holding a professional diploma. A total of 70.91 percent of those polled have at least
a bachelor’s degree. It was deduced that 83.64 percent of the population belonged to a
nuclear family system, while 16.36 percent belonged to a joint family system.
According to the table, 83.64 percent of respondents are married, 14.54 percent are single,
and 1.82 percent are widows or widowers. A total of 60.91 percent of respondents have a
family of three to five members, with 9.55 percent having a family of less than three and
29.54 percent having a five or more family. Therefore, the average family size was calculated
to be 4.71.
It was discovered that 38.64 percent of the respondents have significant agricultural labourer
experience. Unemployed/student/retired/housewife is the background of 5% of the
respondents. Private jobs are the background of 25% of the respondents, and government
employees are 31.36 percent of the respondents.
The table shows that a maximum of 41.36 percent has a monthly income of Rs. 5,001–
10,000, followed by 28.64 percent with a monthly income of Rs. 10,001–15,000. 17.27
percent have a monthly income of Rs. 20,000 or more. 10% of them earn between Rs. 15,001
and Rs. 20,000 per month, while 2.73 percent earn less than Rs.5000 per month. The
respondents’ average monthly income comes to Rs. 13,857.
Opinion about the use of the Internet by a user
Opinion about the use of the
Internet No of Respondents Percentage
Working Place/ Office 45 25.71
House 87 49.71
School 14 8.00
College / University 29 16.57
Total 175 100.00
Source: Primary Data
From the above results, it is vital that the majority (25.71 percent) of respondents use the
internet at work, while only 49.71 percent use the internet at home, and 16.57 percent use the
internet from their school, college, or university.
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The motive for buying online
The motive for buying online Average Score Rank
Easy to Purchase 59.17 III
Saves Time 51.83 V
Accessibility 44.81 VII
Convenience 68.53 I
Superior selection 54.82 IV
Price 62.94 II
Product comparison 39.15 VIII
The flexibility of delivery time and place 47.03 VI
Source: Computed from Primary Data
It is clear from the table that the survey online consumers prioritised motivating factors that
induced them to purchase online. Using Garrett’s score, this can be deduced. The
respondents’ preference for motivating factors for online product convenience was first,
followed by the low price. The superior range was ranked fourth, and easy to buy was ranked
third. The fifth and sixth positions were awarded for time savings and versatility in delivery
time and place. Finally, product comparison was ranked eighth, and accessibility was ranked
seventh.
Satisfaction of consumer towards online shopping
Satisfaction No of Respondents Percentage
Satisfied 138 78.86
Not satisfied 37 21.14
Source: Primary Data
The study revealed that 78.86 percent of respondents were pleased with online shopping,
while 21.14 percent were dissatisfied.
Association between socio-economic profile and frequency of purchase of products
through online mode
Sl
No.
Socio Economic
Profile
Calculated
Chi-square
Table value of chi-square
at 5 per cent level
Inference
1. Age 38.64 21.026 Significant
2. Education 42.53 15.507 Significant
3. Nature of Family 7.6279 9.488
Insignificant
4. Marital status 11.8431 15.507 Insignificant
5. Family size 18.59 15.507 Significant
6. Occupational 12.0418 31.410 Insignificant
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background
7. Monthly income 58.17 26.296 Significant
Source: Computed from Primary Data
Since the estimated value of chi-square is higher than the table value of these variables, the
correlation between the frequency of online product purchases and socio-economic variables
such as age, education, family size, and monthly income per month is essential at the 5%
level. The other variables did not have an important relationship with the level of online
product purchases.
Purchase decision score with gender and marital status
S.No Factors T-Test Value Table Value Significant / Not Significant
1. Gender 1.4726 1.964 NS
2. Marital Status 7.3841 2.584 **
(NS-Not Significant, ** Significant at 1% level)
To see whether there is a substantial difference between gender and marital status, the t-test
was used. The hypothesis is accepted (not significant) in the first case and rejected in the
second case, as seen in the table above (Significant). Consequently, it can be contingent that
gender has no significant effect on purchase decision-making results, while marital status
does.
CONCLUSION
Online shopping in India is currently evolving at a pace unrivalled anywhere else globally;
the effect of this growth rate will be felt by all parties involved. The coming years will be
among the most significant in India’s online shopping growth. Rising wages, the role of
women in the workforce, infrastructure improvements, lifestyle changes, improvements in
computer literacy, and the availability of internet access are all expanding this demand and
hastening the fulfilment of customer preferences for online shopping. The young and
optimistic Indian consumers are heavily influenced by online shopping.
Based on the above debate, it appears that online shopping in Thoothukudi City has a bright
future. Customers have the best choice for saving money and time by shopping online.
Companies include detailed product details, a natural payment method, the ability to compare
prices, and a significant, utterly stress-free shopping experience. Online shopping’s success is
determined by its popularity, brand value, and specific promotional policies.
REFERENCES
1. Asia Pacific Online Retail Forecast 2011 To 2016
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2. Trends in India’s e-commerce market, published by Forrester as the research partner for
ASSOCHAM‟s 2nd National Conference August 2012.
3. Internet in India 2014 jointly published by the Internet and Mobile Association of India
(IAMAI) and IMRB International.
4. State of E-Commerce in India published by Internet analytics and audience measurement
company comScore and trade association ASSOCHAM.
5. eMarketer, Jan 2013
6. Interactive Media in Retail Group (IMRG), a U.K. Online Retail Trade Organization, 2013
7. Forrester Research, 2011.
8. Global Online Retail Sales to Top One Trillion Euro This Year, Published by Ms Tatiana
Teplova on Thursday, October 16, 2014, at http://www.fibre2fashion.com/
9. E-Commerce Industry: Current Online Retail & E-Commerce Market Scenario in India,
published by Dart Consulting on February 5, 2014, at http://www.dartconsulting.co.in/
10. An Article published by Subodh Kolhe on June 30, 2014, at 9:37 am at
http://yourstory.com/
11. E-Commerce Rides On The Back Of Smart Marketing Published By Devansh Sharma on
November 11, 2013, at http://pitchonnet.com/
12. Vellido, A., P.J.G. Lisboa, and K. Meehan, “Quantitative characterisation and prediction
of online purchasing behaviour: A latent variable approach,” International Journal of
Electronic Commerce, Vol. 4, 2000, pp 83- 104.
13. Lohse, G.L., Bellman S. and Johnson, E. J., “Consumer Buying Behavior On The
Internet: Findings from Panel Data”, Journal of Interactive Marketing, Vol.14, No. 1: 15-29,
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14. Goldsmith, R. E., Bridges, E.: E-tailing vs Retailing: Using Attitudes to Predict Online
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15. Goldman Sachs, Internet: Consumer e-Commerce - United States, Feb 2001.
16. Sang Yong Kim; Young-Jun Lim”, Consumers’ Perceived Importance of and Satisfaction
with Internet Shopping,” Electronic Markets (11:3) 2001, pp 148-154.
17. Miyazaki.D; Fernandez. P, “Consumer perception of privacy and security risks for online
shopping,” Journal of Consumer Affairs, Vol. 1, Issue 35, 2001, pp.27.
18. Athiyaman, A., Internet users’ intention to purchase air travel online: an empirical
investigation, Marketing Intelligence and Planning, 20, 234-242.
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