A STUDY ON CUSTOMER PERCEPTION TOWARDS ONLINE SHOPPING IN THE THOOTHUKUDI DISTRICT OF TAMILNADU STATE

Abstract

The fastest-growing medium over the past ten years has been the internet. Online shopping in India has a bright future thanks to the rising number of internet users. The e-commerce industry, and online shopping in particular, is expanding quickly. Online shopping is an increasingly popular trend across the globe, particularly in nations with developed information and communication technologies for Internet marketing. Today, the internet serves as a platform for global commerce in addition to being a tool for networking and connectivity. Due to the numerous benefits and the chance to discover new shopping opportunities across online platforms, some customers are now engaging in online shopping. The primary goal of this research is to examine how consumers view online shopping and what factors may affect a consumer's decision to make a purchase. The Kaiser-Meyer-Olkin (KMO) value of 0.716, which is higher than 0.5 and represents the measure of sample adequacy, demonstrates that the provided primary data is suitable for data analysis using factor analysis. Since the p-value is 0.000, or less than 0.05, it can be concluded that the correlation is significant. The Kaiser-Meyer-Olkin (KMO) value of 0.716, which is higher than 0.5 and represents the measure of sample adequacy, demonstrates that the provided primary data is suitable for data analysis using factor analysis. Since the p-value is 0.000, or less than 0.05, it can be concluded that the correlation is significant. The reliability test (alpha) for the entire data set used in the factor analysis is 0.824, which is higher than the usual cutoff point. The F-test is highly significant, demonstrating that our model's variables have a linear relationship with one another.

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Education and Society (  ) ISSN: 2278-6864
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A STUDY ON CUSTOMER PERCEPTION TOWARDS ONLINE SHOPPING IN THE
THOOTHUKUDI DISTRICT OF TAMILNADU STATE
X. Jude Christo Cedric, Ph. D Research Scholar in Economics, V.O.Chidambaram College,
Thoothukudi – 628 008, Affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli
– 627012, Tamil Nadu, India.
Dr.S. Kanthimathinathan,HOD and Associate Professor of Economics (Rtd), V.O.C. College,
Thoothukudi – 628 008, Affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli
– 627012, Tamil Nadu, India.
Abstract
The fastest-growing medium over the past ten years has been the internet. Online shopping in India has a
bright future thanks to the rising number of internet users. The e-commerce industry, and online
shopping in particular, is expanding quickly. Online shopping is an increasingly popular trend across the
globe, particularly in nations with developed information and communication technologies for Internet
marketing. Today, the internet serves as a platform for global commerce in addition to being a tool for
networking and connectivity. Due to the numerous benefits and the chance to discover new shopping
opportunities across online platforms, some customers are now engaging in online shopping. The
primary goal of this research is to examine how consumers view online shopping and what factors may
affect a consumer's decision to make a purchase. The Kaiser-Meyer-Olkin (KMO) value of 0.716, which
is higher than 0.5 and represents the measure of sample adequacy, demonstrates that the provided
primary data is suitable for data analysis using factor analysis. Since the p-value is 0.000, or less than
0.05, it can be concluded that the correlation is significant. The Kaiser-Meyer-Olkin (KMO) value of
0.716, which is higher than 0.5 and represents the measure of sample adequacy, demonstrates that the
provided primary data is suitable for data analysis using factor analysis. Since the p-value is 0.000, or
less than 0.05, it can be concluded that the correlation is significant. The reliability test (alpha) for the
entire data set used in the factor analysis is 0.824, which is higher than the usual cutoff point. The F-test
is highly significant, demonstrating that our model's variables have a linear relationship with one
another.
Keywords: online shopping, e-commerce, internet marketing, linear relationship, factors influence.
INTRODUCTION
Information and communication technology (ICT) is a key factor in the way that our world is changing.
The workforce can be prepared with the use of ICT for the information society and the new global
economy (D. Amutha, 2019). The media with the fastest growth over the past ten years has been the
Internet (D. Amutha, 2016).
Online shopping in India has a bright future thanks to the country's growing internet user population.
Notably, the e-commerce sector is expanding quickly. Online shopping is a rapidly growing
phenomenon in many countries around the world, particularly in those with advanced information and
communication technologies for online marketing. Currently, the internet serves as a platform for global
business transactions in addition to networking and communication (Amutha D, 2016). Currently, some
shoppers use online platforms to shop because of the benefits it offers and the new experiences it
provides.
Due to the internet's quick development and widespread accessibility, online shopping has become more
and more popular. Online shopping is gaining popularity in the United States as a result of the

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widespread availability of high-speed Internet access. Customers can now shop at their convenience
from home thanks to online shopping (Niranjanamurthy et al.,2013).
People who are concerned about their health frequently choose to purchase organic food products online
(M.Mohanraj, J.Sureshkumar, & A.T.Jaganathan, 2019). Education, the number of times they shop
online, and preferred payment methods all play a big part in how well someone understands and uses the
online shopping experience (M.Vidya & P.Selvamani, 2019).
They appreciate how convenient it is to be able to shop whenever they want. Online shopping is more
common in India now that there are more computers and internet access (Dr S Shanti, S Anuska, Dansi,
& Senthilkumari, 2017). Due to the widespread use of online shopping, marketing has undergone a
paradigm shift (Sharma, 2016).
The three stages of the online purchasing process that customers anticipate are pre-purchase, during-
purchase, and post-purchase (Kotnia, 2019). If the vendor does not offer a free or significantly reduced
delivery service, buyers are typically responsible for shipping costs (Gupta, Bansal & Bansal, 2013). E-
commerce can help you save money and give you more options if a product isn't offered locally (Nilashi
et al.,2011). The motivation of consumers in Thoothukudi City to make purchases online and their level
of satisfaction with their online shopping experiences are the subjects of this study.
OBJECTIVES OF THE STUDY
The study has the following objectives.
1. To study the socio-economic outline of the sample consumers.
2. To find out the factors that influence buying online.
3. To understand the time spent online shopping.
4. To analyse motivation to buy in online shopping and level of satisfaction services of online
shopping.
5. To know the bad experience while online shopping.
RESEARCH METHODOLOGY
The proposed research is descriptive. Online shoppers are the intended audience. After determining the
study's dependent and independent variables, a questionnaire was created for the respondent. 120 people
comprise the sample. Using simple random sampling, the respondents are chosen. Online and offline
surveys were the main methods used to gather all the data. the main information gathered between
February and April 2023. On a five-point Likert scale, each of the 14 items was evaluated. The
instrument was in good condition, and the scales were trustworthy. No item was removed from the
survey questionnaire due to the acceptable levels of Cronbach's alpha. Factor analysis, multiple linear
regression modelling, and descriptive statistics are the statistical tools used in the study.
RESULTS AND DISCUSSION
TABLE 1: AGE-WISE CLASSIFICATION OF THE RESPONDENTS
Sl.No
Age
Respondents
Percentage
1
Below 20
5
4.16
2
21 – 30
11
9.17
3
31 – 40
29
24.17
4
41 – 50
47
39.17
5
51 and above
28
23.33
Total
120
100
Source: Primary data

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According to Table 1, 9.17 percent of respondents were between the ages of 21 and 30 and 4.16
percent were under the age of 20. Ages 31 to 40 are represented by 24.17 percent of respondents, and 41
to 50 represent 39.17 percent. Ages 51 and older make up 23.33 percent of respondents. The calculated
mean age of the participants was 42.33 years. The results, which indicate that the majority of
respondents are between the ages of 41 and 120, support this conclusion.
TABLE 2:GENDER-WISE CLASSIFICATION OF THE RESPONDENTS
Sl.No
Sex
Respondents
Percentage
1
Male
85
70.83
2
Female
35
29.17
Total
120
100
Source: Primary data
Out of the 120 respondents in the sample, 70.83 percent are men and 29.17 percent are women,
according to the above table.
TABLE 3:EDUCATION QUALIFICATION OF THE RESPONDENTS
Sl.No
Education qualification
No. of Respondents
Percentage
1
School Level
17
14.17
2
College Level
58
48.33
3
Technical Level
32
26.67
4
Illiterate
13
10.83
Total
120
100
Source: Primary data
Out of 120 survey participants, 48.33 percent had a college degree, followed by 26.67 percent
who had professional training, 14.17 percent who only had a high school diploma, and 10.83 percent
who were illiterate, as shown in Table 3.
TABLE 4: MARITAL STATUS
Sl. No.
Marital Status
Number of Respondents
Percentage
1.
Married
106
88.33
2.
Unmarried
11
9.17
3.
Widow/ Widower
3
2.50
Total
120
100
Source: Primary data.
According to Table 4, 69 out of the 120 survey participants—or 88.33 percent of the total—are
married. Similarly, 2.5% of people are widowed or widowers, while 9.17% of people are not married.
TABLE 5: OCCUPATION BACKGROUND
Sl.No
Occupation background
No. of respondents
Percentage
1
Agriculturalist
17
14.17
2
Private employee
28
23.33
3
Business
44
36.67
4
Government employee
19
15.83
5
Professionals
12
10.00

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110
Total
120
100
Source: Primary data
Table 5 demonstrates that 120 respondents have a work history. 17 (14.17 percent) of the
respondents are from the agricultural industry, 28 (23.33 percent) are employed by private companies,
44 (36.67 percent) are entrepreneurs, and 19 (15.83 percent) are employed by the government. 12
people, or 10%, have a team of professionals.
TABLE 6: FAMILY INCOME PER MONTH OF THE RESPONDENTS
Sl.No
Family Income
No. of respondents
Percentage
1
Less than Rs.10,000
11
9.17
2
Rs.10,001 – Rs.20,000
15
12.50
3
Rs.20,001 – Rs.30,000
21
17.50
4
Rs.30,001 – Rs.40,000
45
37.50
5.
Above Rs.40,001
28
23.33
Total
120
100
Source: Primary data
Table 6 lists the percentage of residents of the Thoothukudi area who have a monthly family
income of Rs. 10,000 or less (9.17%) and between Rs. 10,000 and Rs. 20,000 (12.50%). The majority of
45 people (37.50 percent) earn between Rs 30,001 and Rs 40,001 per month, and 28 people (23.33
percent) earn more than Rs 40,001 per month. 17.50 percent of people earn between Rs 20,001 and Rs
30,000 per month. The family's gross monthly income totals Rs. 30333.83.
TABLE 7: KMO AND BARTLETT'S TEST
Kaiser-Meyer-Olk in Measure of Sampling Adequacy.
.716
Bartlett's Test of Sphericity
Approx. Chi-Square
1305
df
122
Sig.
.000
Table 7 shows the Kaiser-Meyer-Olkin (KMO) value of 0.716, which is greater than 0.5, as the sample
adequacy indicator and demonstrates that the provided primary data are suitable for factor analysis.
Since the p-value is 0.000, or less than 0.05, it can be concluded that the correlation is significant.
TABLE 8: RELIABILITY STATISTICS
Cronbach's Alpha
No of Items
.824
14
The reliability test α (alpha) of the entire data set used for factor analysis is 0.824, which exceeds
the common threshold value recommended by Nunnally (1978).
REGRESSION ANALYSIS FOR COMPETENCY-RELATED ATTRIBUTES INFLUENCE ON
BUYING ONLINE
Multiple linear regression (MLR) tests using enter regression method were subsequently conducted to
find the level of influence of four factors (Accessibility, Convenience, Price, and Product comparison)
on Shopping Intention among online shoppers.
TABLE 9: MODEL SUMMARY
Model
R
R Square
Adjusted R Square
Std. The error in the
Estimate
1
.891a
.832
.822
.18342539

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Predictors: (Constant), Accessibility, Convenience, Price, Product comparison
Dependent Variable: Shopping Intention
Table 9 shows the multiple regression model summary and overfit statistics. The adjusted R2 of the
model is .822 with an R2 value of.832 which means the linear regression explained is 83.2 % of the
variance in the data. TABLE 10: ANOVA
Model
Sum of Squares
Df
Mean Square
F
Sig.
1
Regression
117.351
3
29.057
372.58
.000a
Residual
7.279
122
.054
Total
124.63
125
A. Predictors: (Constant), Accessibility, Convenience, Price, Product comparison
b. Dependent Variable: Shopping Intention
As per Table 10, the F-test is highly significant, thus it proves that there is a linear relationship between
the variables in our model.
TABLE 11:TIMES SPENT ONLINE SHOPPING.
Source: Primary data
According to the table, once every three to six months falls to a higher percentage, which is 45.83
percent. It indicates that respondents aren't frequently used. falls of 26.67 percent each month. Weekly
falls at a 20% rate. Only 7.50 percent of respondents said they regularly went shopping online.
TABLE 12:SERVICES OF ONLINE SHOPPING
Source: Primary data
It is evident from the above table that each respondent gives the online shopping services a good rating
in 52.50 percent of cases, an excellent rating in 30 percent of cases, and a poor rating in 17.50 percent of
cases, indicating both their past interactions with online shopping sites and their general preference for
it.
TABLE 13: FIND THE PRODUCT MORE AFFORDABLE
Sl. No
Times spent
No. of Respondents
Percentage
1.
Daily
9
7.50
2.
Weekly
24
20.00
3.
Monthly
32
26.67
4.
Once in 3-6 months
55
45.83
Total
120
100
Sl. No
Services of online shopping
No. of Respondents
Percentage
1.
Excellent
36
30.00
2.
Good
63
52.50
3.
Poor
21
17.50
Total
120
100
Sl. No
Affordable
No. of Respondents
Percentage
1.
Yes
55
45.83
2.
No
21
17.50
3.
Sometimes
44
36.67

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Source: Primary data
Based on the above table, out of 120 respondents, 45.83 percent shop online because they believe it to
be more affordable, 36.67 percent believe it to be occasionally affordable, and 17.50 percent believe it to
be prohibitively expensive.
CONCLUSION
Today's society is embracing online shopping more and more. The study shows that most consumers
have done online shopping. Although customers think that shopping online is preferable to manual
shopping, they still think that it is more expensive and that delivery times for goods and services are
longer. Most customers struggle with issues like returning defective or incorrect goods, perplexing
websites, and poor customer service. According to customers, the most concerning barrier to online
shopping is the inability to personally verify the product.
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