Journal of Namibian Studies, 35 S1 (2023): 5385-5406 ISSN: 2197-5523 (online)

Online Shopping And Buying Behaviour: A

Study On Female Students With Special
Reference To Apparels And Fashion
Industry
1Dolly Tripathi, 2Dr. Akshat Dubey

1
Research Scholar, Department of Commerce, Sam
Higginbottom University of Agriculture, Technology and
Sciences, Prayagraj, Uttar Pradesh.
2
Head of Department, Sam Higginbottom University of
Agriculture, Technology and Sciences, Prayagraj, Uttar
Pradesh.

Abstract
This research article investigates the online shopping
patterns and purchasing behaviours of female students,
focusing particularly on their engagement within the
apparels and fashion industry. With the pervasive growth of
e-commerce, understanding consumer behaviour in online
shopping environments has become paramount for
businesses. Female consumers, in particular, represent a
significant segment in the online retail landscape, especially
concerning fashion and apparel purchases. The study
employs a mixed-methods approach, combining
quantitative surveys and qualitative interviews to
comprehensively explore the intricacies of female students'
online shopping behaviours. Through a structured survey,
data is collected on various factors such as frequency of
online shopping, preferred platforms, influencing factors,
and expenditure patterns. Additionally, qualitative
interviews provide deeper insights into the underlying
motivations, perceptions, and experiences of female
students when purchasing apparels and fashion items
online. The findings of this study shed light on the evolving
dynamics of online shopping among female students,
elucidating the factors driving their purchasing decisions and
the challenges they encounter in the digital marketplace.
Moreover, the research contributes to the existing literature
by offering practical implications for marketers and retailers
aiming to effectively target and cater to the preferences and
needs of female consumers in the online fashion domain.
Overall, this study provides valuable insights into the

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intricate relationship between female students, online

shopping, and the apparel and fashion industry, serving as a
foundation for future research endeavours and strategic
business initiatives in the rapidly evolving e-commerce
landscape.

Keywords: Online Shopping, Apparel Industry, Regression

analysis, Factor analysis.

Introduction
During this period of globalisation, Indian branded apparel
products have had a significant impact on individuals living in
both rural and urban areas due to their affordable prices and
vast selection of clothing for both men and women. Beginning
in the middle of the 1980s, there was a widespread notion that
tailors were the only individuals who were competent of
sewing different kinds of garments, including blouses, salwar
kameez, trousers and blowouts. In spite of this, businesses
were pushing pre-made brands for various client categories in
the highly competitive market for branded clothing. Globus
Stores, Pantaloon, Westside, Shoppers Stop, and Life Style are
some of the organisations that are considered to be key
participants in the ready-made business in India. 1.34 billion
people are now living in India, Males constitute 51.5% of the
population, while females comprises of 48.5%.
In urban areas, women make up 48.1% of the population,
whereas in rural areas, they make up 48.6% of the population.
The Central Statistics Organisation (CSO) and the International
Monetary Fund (IMF) both report that India's economy is
expanding at the fastest rate of any country in the world. Over
the next ten to fifteen years, it is anticipated that India would
become one of the top three economic powers in the world as
a result of its robust democracy and strategic collaborations.
(Muthumani, 2017). Over the next several years, it is
anticipated that the Indian economy would expand at a pace
of seven percent. Over the last several years, technological
advancements have significantly contributed to the rise in
popularity of internet commerce and app-based online
shopping in India. In this sector, there are a great number of
competitors that provide a diverse selection of goods that are
necessary for day-to-day life. By 2026, it is anticipated that
India will have 750 million people using the internet.
It is anticipated that India's gross domestic product would
increase at a compound annual growth rate (CAGR) of 10%,
which will place it as one of the countries that is expanding at

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a quick rate and as an attractive market. In contrast to India,

the developed markets of the United States, Europe, and Japan
are expected to expand at a more moderate rate of two to
three percent each year. The majority of the women's clothing
section of the market is controlled by businesses that are not
specifically structured. In recent times, a great number of well-
established firms have shown an interest in this sector. Upon
seeing the potential of the industry, these structured
companies have swiftly evolved aggressively by using e-
commerce and other innovative distribution tactics. The
market sector has been spurred by the expanding proportion
of working women, which has contributed to a rise in those
women's incomes that are available for discretionary spending.
A greater understanding of fashion trends and style has been
achieved as a result of globalisation and fast fashion. The
women's clothing industry is now valued at Rs 1,02,358 crore,
and it is anticipated that it would increase at a compound
annual growth rate (CAGR) of 11% to reach Rs 2,89,518 crore
by the year 2025. Not only will this expansion entail an increase
in market size, but it will also require a transition from non-
branded clothing to branded clothing as well as from ethnic
clothing to western clothing. According to projections, the
market for women's clothing in India is expected to exceed that
of men's clothing between the years 2025 and 2030.
There have been a number of causes that have led to the
amazing rise of the online garments and fashion business in
India. These factors have altered the retail landscape the
country. E-commerce platforms are becoming increasingly
accessible in both urban and rural regions as a result of the
increasing number of people who have smartphones and the
penetration of the internet (Alam 2016). The broad availability
of the internet has led to an increase in the accessibility of
online shopping, which in turn has given rise to the growth of
the online clothing and fashion business. There is also a
possibility that the shifting interests and lifestyles of customers
in India are contributing to the rise in online garment sales in
the country. Due to the fact that they lead busy and stressful
lives, customers, particularly members of the millennial and
Gen Z generations, are increasingly resorting to online
platforms in order to acquire fashionable things and apparel.
Consumers in India have become used to the ease of browsing
and purchasing from the comfort of their own homes or while
they are on the go, which has resulted in a shift away from
conventional brick-and-mortar establishments and towards
online platforms.

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Customers now have more alternatives to choose from when

it comes to making purchases thanks to the proliferation of e-
commerce platforms and marketplaces, which has increased
the level of competition in the clothing and apparel business.
Amazon, Flipkart, and Myntra are examples of well-established
companies that have made significant investments in
technology, logistics, and marketing in order to improve the
shopping experience and expand their market share. Other
fashion-focused platforms, including as Ajio and Koovs, have
also adopted these strategies. As a result of the severe rivalry,
there have been developments in product offers, marketing
techniques, and customer service efforts, which have
contributed to the expansion of the online clothing and fashion
business. In addition, the growing impact of social media and
digital marketing has been a significant factor in significantly
contributing to the expansion of online fashion commerce in
India. In order to successfully exhibit their items, interact with
customers, and generate traffic to their online storefronts,
fashion manufacturers and merchants may make use of social
media sites such as Facebook, Instagram, and YouTube.
Sponsored content, influencer partnerships, and targeted
advertising campaigns are becoming more important
components of marketing plans that are aimed at India's
growing tech-savvy clientele. In addition, the democratisation
of fashion via the use of internet platforms may be credited
with contributing to the growth of the garment and fashion
industry in India. By providing customers with a wide variety of
brands, styles, and trends, online marketplaces are able to
accommodate a wide variety of demographics, including
preferences, budgets, and hobbies. Consumers are becoming
more independent in their ability to experiment with and
investigate fashion, which has led to an increase in the demand
for both well-established brands and up-and-coming designers
in the internet marketplace.
Between the years 2010 and 2020, the Indian market for online
shopping saw a compound annual growth rate (CAGR) that was
between fifty and sixty percent. This growth was exponential.
This fast expansion may be attributed to a number of major
factors, including as the increasing prevalence of e-commerce
platforms, the rise in the number of people using smartphones,
and the increased availability of internet connection. As more
people gained smartphones and internet access, the
convenience and availability of online shopping expanded. This
led to a rise in the number of digital transactions that took
place across a wide range of goods and services thanks to the

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proliferation of digital transactions. It is possible to attribute

the rise in the compound annual growth rate (CAGR) of online
shopping in India to the introduction of large e-commerce
enterprises as well as new business tactics. Companies like
Flipkart, Amazon, Snapdeal, and others have revolutionised
the retail industry by offering a wide variety of products at
affordable prices and providing a variety of delivery options
that are convenient for customers. The proliferation of mobile
commerce (m-commerce) and the development of mobile
shopping applications have contributed to the expansion of
online shopping by providing customers with the ability to
make purchases in a convenient manner while they are
currently on the go.
In addition, factors that contributed to the Compound Annual
Growth Rate (CAGR) of online shopping in India included shifts
in customer tastes and behaviours, particularly among younger
demographic groups. Internet shopping is the favoured way of
retail therapy for members of Generation Z and Millennials
because of the convenience and technologically sophisticated
lifestyles of these generations. The transition towards online
platforms has been influenced by a number of factors,
including the development of more effective methods, the
expansion of product availability, and the simplicity of
comparing reviews and costs. Businesses in India that are
involved in e-commerce have made significant contributions to
the expansion of online shopping by continuously innovating
and investing in technology, logistics, and the overall customer
experience. Enhanced user interfaces, tailored suggestions,
quicker delivery, and secure payment choices all contributed
to an improved online shopping experience, which in turn led
to increased consumer satisfaction and retention rates. It is
anticipated that the Compound Annual Growth Rate (CAGR)
for online shopping in India will continue to increase as the
industry continues to develop, but at a rate that is considerably
slower than originally anticipated. As a result of the
widespread use of developing technologies like augmented
reality and artificial intelligence, secondary and tertiary cities
are becoming more prevalent. There is also growth in
specialised industries such as online grocery shopping and
health and wellness, all of which are anticipated to contribute
to the continuous development of the e-commerce industry.
When it comes to our nation, the textile sector plays a role that
is both distinctive and important. A long and illustrious history
of great workmanship and widespread acceptance may be
traced back to Indian clothing and materials. India is a producer

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of denim, cotton, and silk, all of which are quite popular in

other parts of the world. The development of Indian design
talents has led to an increase in the popularity of Indian
clothing in fashion hubs throughout the world. India is the
world's second-largest exporter of textiles and apparel due to
its massive raw material resources and strong industrial base.
This has enabled India to achieve this position with great
success. The textile sector provides a significant contribution
to the economy, both in terms of the percentage of the
domestic market that it holds and the amount of goods that it
ships abroad. In this research, topics like as preferences,
influences, and purchasing behaviour are categorised and
subjected to an in-depth analysis. There are a variety of
elements that impact the choices and decisions that individuals
make about their purchases. These aspects include personal
preferences, culture, traditions, events, the economy, and the
influence of reference groups. For this reason, the purchasing
habits of women have varied from person to person over the
years. The purpose of this research is to get an understanding
of the shopping behaviour of women, with a particular
emphasis on their preferences for design, fabric, and style, as
well as the variables that influence their choices while buying
women's clothing.

Review of Literature
Aziz (2018) there are a number of factors that influence
people's habits of making purchases online. These include
household migration to higher income groups, rising
disposable income per capita, shifting family composition,
widespread media coverage, lifestyle shifts, increased health
and education awareness, and urbanisation. Researcher also
highlights the impact of technological advancements, such as
the increased availability of internet access and smartphones,
on the growth of online shopping habits. Additionally, she
emphasizes the role of social media and e-commerce platforms
in shaping consumer behaviour towards online purchases. A
number of sociodemographic criteria, including age, gender,
economic status, and attitude, are among the elements that
indicate the preferences of women when it comes to making
purchases over the internet.
Pawan Kumar, Kanchan (2018) In the research that they
conducted in 2018, investigate the monetary, social, and
psychological factors that influence the decisions that
customers make about the purchase of branded clothing.
Customers may browse for branded clothes in a variety of

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different ways, depending on the purpose of their purchase.

For example, customers shopping for a special occasion may
prioritize style and presentation, while those looking for
everyday wear may focus more on comfort and durability.
Understanding these different browsing behaviours can help
retailers tailor their marketing strategies to better meet the
needs and preferences of their target customers. The effect of
social media, the internet, and television has resulted in
significant developments in the fashion business. These
innovations have been made possible by the fashion industry.
One of the most important players in the contemporary
fashion business is branded clothing.
Nurfajrinah (2017) According to the research visual marketing
methods do have an effect on the purchasing decisions of
consumers and may even prompt people to make purchases
on the spur of the moment. The study found that women are
more likely to be influenced by visual marketing techniques
such as high-quality images and videos when making online
purchases. Additionally, the research suggests that companies
should focus on creating visually appealing content to attract
female consumers and increase sales. The aspects that were
found to have the strongest connections to buy intention were
found to be colour, style, presentation, lighting, route to
objects, sensory characteristics of materials, and awareness of
fixtures.
Sivanesan (2017) established a method for consumers to
purchase products and services from a business that accepts
customers both in-store and online. This method allows
customers to purchase goods and services from the firm
online. This omni-channel approach has become essential for
fashion brands to stay competitive in the market and cater to
the evolving shopping habits of consumers. By offering a
seamless shopping experience across different platforms,
brands can better connect with their target audience and drive
sales. Through the use of the web search engine for the items
that the customer has selected, the customer is able to
monitor the estimated arrival time of their purchase as well as
the delivery window. This level of transparency and
convenience enhances customer satisfaction and loyalty,
ultimately leading to repeat business and positive word-of-
mouth referrals. Additionally, providing real-time tracking
information can help reduce customer inquiries and
complaints regarding order status, further improving the
overall shopping experience.

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Chaturvedi (2016) asserts that we are compelled to purchase

online due to our hectic schedules and the growing prevalence
of internet access. She also suggests that the convenience of
online shopping, such as 24/7 availability and delivery options,
further encourages women to make purchases through digital
platforms. The advantages of purchasing online are unrivalled
in terms of convenience, safety, and time savings saved.
Additionally, it provides you with access to a large range of
items that are available at affordable prices. Ultimately, online
shopping offers women the opportunity to make informed
decisions and compare prices easily, leading to a more
satisfying shopping experience. Furthermore, the ability to
read reviews and recommendations from other shoppers can
help women feel more confident in their purchases.
Jadhav (2016) the accessibility, simplicity of use, dependability,
and speed of answers are aspects of service quality that have a
substantial impact on how individuals view the process of
making purchases and transactions online . This highlights the
importance of providing a seamless and user-friendly online
shopping experience for women, ultimately leading to
increased customer satisfaction and loyalty. Additionally, the
convenience of being able to shop from anywhere at any time
adds to the appeal of online shopping for women with busy
schedules.
Huseynov (2016) men and women make distinct decisions
while contemplating the acquisition of a product or service.
This suggests that understanding the unique preferences and
behaviours of female online shoppers is crucial for businesses
looking to attract and retain this demographic. By tailoring
their online shopping platforms to better meet the needs of
women, companies can gain a competitive edge in the e-
commerce market. It is possible that the purchase intentions
of female consumers, who are impacted by factors such as
product use and cost, might be influenced by rich contextual
settings that boost the emotional worth of a product while it is
being shown. Therefore, businesses should focus on creating a
seamless and personalized shopping experience for female
customers to increase their likelihood of making a purchase.
Additionally, incorporating elements such as detailed product
descriptions, customer reviews, and interactive features can
help enhance the overall shopping experience for women.
Chaturvedi (2016) There are a number of factors that influence
online buying habits such as age, possession of a credit card,
employment, income, and level of education.

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Kumar (2016) A research that was conducted not too long ago
by looked at the similarities and differences in the ways that
men and women behave while they are shopping online. To
add insult to injury, individuals of both sexes had generally
positive perceptions of online retailers and electronic payment
methods. The study found that women tend to value
personalized recommendations and interactive features more
than men, while men prioritize convenience and speed in their
online shopping experience. These findings suggest that
tailoring online shopping platforms to cater to gender-specific
preferences can lead to increased customer satisfaction and
loyalty. Social influence is more powerful and of a more
favourable nature when it comes to the buying habits of
women on the internet. Despite the fact that both sexes
experience privacy concerns, women suffer disproportionately
more from them. So, previous study has identified a few
elements that influence the shopping behaviours of women
who do their shopping online. There are hardly many studies
that give detailed insights into the buying behaviours of
women who purchase online.

Jayasubramanian (2015) this study provides a succinct

summary of the purchasing patterns and factors that affect the
clothing purchases made by college-bound students. The study
highlights the importance of understanding consumer
behaviour in order to tailor marketing strategies effectively. By
identifying key trends and preferences, retailers can better
meet the needs of their target demographic and increase sales.
According to the findings, students were price-conscious, loyal
to their brands, and interested in trying new and different
kinds in order to stay current with trends. Additionally, the
study found that social media and influencers played a
significant role in influencing the purchasing decisions of
college-bound students. This suggests that incorporating social
media marketing strategies may be crucial for retailers looking
to effectively reach this demographic.

Research Objectives
The present research examines the buying behaviour of female
students in apparel and fashion industry, including
dimensions, shopping habits, expenditure, and frequency.
1. To understand the demographic profile of the
respondents.

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2. To analyse the key factors influencing the women

students in choosing online shopping for purchase
of apparel products.
3. To apprehend the impact of social influence in
buying decisions of apparel products among
female students.

Research Methodology
This study employs a mixed-methods approach to investigate
the online shopping and buying behaviour of female students
in India, with a specific focus on apparels and the fashion
industry. The research methodology encompasses both
quantitative surveys and qualitative interviews to provide a
comprehensive understanding of the factors influencing
female students' online shopping behaviour. A structured
questionnaire is designed to collect quantitative data from a
sample of female students across various educational
institutions in India. The questionnaire is administered online
to ensure wider reach and accessibility. The survey includes
questions pertaining to the frequency of online shopping,
preferred platforms, influencing factors, expenditure patterns,
and demographic information. The quantitative data obtained
from the survey is analyzed using statistical software such as
SPSS (Statistical Package for the Social Sciences) to derive
descriptive statistics, correlations, and inferential analysis.
In addition to quantitative surveys, qualitative insights are
gathered through in-depth interviews with a subset of female
students. The qualitative interviews aim to explore the
underlying motivations, perceptions, and experiences of
female students when purchasing apparels and fashion items
online. Semi-structured interview guides are used to facilitate
open-ended discussions, allowing participants to express their
thoughts, preferences, and challenges related to online
shopping. The qualitative data obtained from the interviews is
analyzed thematically to identify recurring patterns, themes,
and insights.Quantitative data obtained from the surveys is
analyzed using SPSS software to generate descriptive statistics
such as demographic analysis, regression and factor analysis.

Data Analysis and Interpretation

This section of the study focuses on presenting the data
analysis based on the information gathered from respondents;
the sample population was selected using the convenience
sampling approach. The data was evaluated using the SPSS

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statistical package, with methods such as percentage rate

analysis, regression analysis, and the chi square test.

Table 1: Demographic analysis

Age Frequency Percent
18 - 20 years 40 30.10
21 - 22 years 44 33.10
23 - 25 years 18 13.50
25 - 26 years 31 23.30
25 - 44 years 46 31.90
45 - 64 years 18 12.50
Above 65 years 31 21.50
Location Frequency Percent
Urban 62 46.60
Semi Urban 48 36.10
Rural 23 17.30
Type of family Frequency Percent
Fully aware 85 59.00
Somewhat aware 59 41.00
Type of family Frequency Percent
Joint family 79 59.40
Nuclear family 54 40.60
Education Frequency Percent
Pursuing Under graduation 61 45.90
Pursuing Post graduation 33 24.80
Pursuing Professional course 21 15.80
Other courses 18 13.50
Frequency of purchase in online Frequency Percent
Every Week 36 27.10
Once in a fortnight 35 26.30
Once a month 24 18.00
Once a quarter 27 20.30
Once in 6 months 11 8.30
Total 133 100.00

The provided data presents the demographic characteristics

and online shopping behaviour of female students in India,
with a focus on age distribution, location, type of family,
education level, and frequency of online purchases.The data
indicates that the majority of respondents fall within the age
groups of 18-22 years, comprising approximately 63.2% of the
sample. This suggests that a significant proportion of female
students engaging in online shopping and buying behaviour are

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relatively young, which aligns with the trend of younger

demographics being more active participants in e-commerce
activities. However, it's noteworthy that a considerable portion
of respondents also belong to older age groups, indicating a
diverse age distribution among female students involved in
online shopping.
In terms of location, the data reveals that urban areas have the
highest representation among the respondents, accounting for
46.6% of the sample. This is followed by semi-urban areas with
36.1%, and rural areas with 17.3%. The higher prevalence of
respondents from urban and semi-urban areas reflects the
greater accessibility and penetration of e-commerce platforms
in these regions compared to rural areas. However, the
presence of respondents from rural areas indicates a growing
adoption of online shopping among female students in non-
urban settings as well. Regarding the type of family, the
majority of respondents belong to joint families, comprising
59.4% of the sample, while nuclear families account for 40.6%.
This distribution suggests that a significant proportion of
female students engaging in online shopping come from joint
family setups, which may have implications for their
purchasing behaviour and decision-making processes
influenced by familial dynamics and preferences.
In terms of education level, the data reveals that a majority of
respondents are pursuing undergraduate degrees, constituting
45.9% of the sample. This is followed by those pursuing
postgraduate degrees (24.8%), professional courses (15.8%),
and other courses (13.5%). The predominance of
undergraduate students in the sample reflects the
demographic composition of female students actively
participating in online shopping activities, with higher
education levels potentially correlating with higher disposable
incomes and purchasing power. Regarding the frequency of
online purchases, the data indicates a relatively even
distribution among different purchase frequencies.
Approximately 27.1% of respondents make online purchases
every week, followed closely by 26.3% once in a fortnight, and
18% once a month. This suggests that female students engage
in online shopping regularly, with a significant portion making
purchases at least once a week or once a fortnight, indicating
a high level of involvement and reliance on e-commerce
platforms for their apparel and fashion needs.

Regression Analysis

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The goal of the study is to figure out the crucial connection

between the independent variables:

Table 2: Regression Analysis

Adjusted R
R R Square Square

0.932 0.869 0.864

Sum of Mean
ANOVA Squares df Square F P Value

Regression 195.009 4 48.752 211.413 .000b

Residual 29.517 128 0.231

Total 224.526 132

Regressions B Std. Error Beta t P Value

(Constant) -0.422 0.163 -2.584 0.01

Price 0.049 0.089 0.042 0.547 0.00

Convenience 0.853 0.089 0.798 9.591 0.00

Brand and Trust 0.113 0.075 0.1 1.498 0.01

Social Influence 0.011 0.086 0.01 0.128 0.02

The provided statistical output represents the results of a

regression analysis conducted to examine the relationship
between several independent variables (Price, Convenience,
Brand and Trust, Social Influence) and a dependent variable
(let's assume it's online shopping buying behaviour). Here's the
interpretation of the key components of the output:
R-Square (R^2): This indicates the proportion of variance in the
dependent variable (online shopping buying behaviour) that is
explained by the independent variables included in the
regression model. In this case, the R-square value is 0.869,
suggesting that approximately 86.9% of the variability in online
shopping buying behaviour can be explained by the
independent variables.Adjusted R-Square: This adjusts the R-
Square value based on the number of predictors in the model
and provides a more accurate estimate of the model's
goodness of fit. The adjusted R-Square value of 0.864 suggests
that the model is well-fitted and accounts for a significant
amount of variance in the dependent variable.
The ANOVA table assesses the overall significance of the
regression model. The F-value (211.413) is highly significant (p
< 0.001), indicating that the regression model as a whole is

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statistically significant in predicting online shopping buying

behaviour.The regression coefficients (B) represent the
estimated change in the dependent variable (online shopping
buying behaviour) for a one-unit change in the independent
variable, holding other variables constant.
The constant term (-0.422) represents the estimated value of
the dependent variable when all independent variables are
zero. In this case, it suggests a negative intercept, but the
magnitude alone doesn't convey much meaning without the
context of the other coefficients.The coefficients for the
independent variables (Price, Convenience, Brand and Trust,
Social Influence) indicate the strength and direction of their
relationship with online shopping buying behaviour. For
instance, the coefficient for Convenience (0.853) suggests that
for every one-unit increase in Convenience, there is an
estimated increase of 0.853 units in online shopping buying
behaviour, holding other variables constant. This coefficient is
statistically significant (p < 0.001), indicating that Convenience
has a significant positive effect on online shopping buying
behaviour. Similarly, the coefficients for Price (0.049), Brand
and Trust (0.113), and Social Influence (0.011) indicate the
estimated change in online shopping buying behaviour
associated with a one-unit change in each respective
independent variable.
Overall, the regression analysis suggests that Convenience,
Brand and Trust, and Price are significant predictors of online
shopping buying behaviour among the variables examined,
while Social Influence may have a weaker influence. These
findings can provide valuable insights for marketers and
retailers in understanding the factors driving online shopping
behaviour among female students in the context of apparels
and the fashion industry in India

Factor analysis:
The last section is factor analysis.

Table 3: KMO analysis

KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.93

Bartlett's Test of Sphericity Approx. Chi-Square 2426.02

df 66
Sig. 0.00

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The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy

assesses the suitability of data for conducting a factor analysis.
In this case, the KMO measure is 0.93, indicating an excellent
level of sampling adequacy. This suggests that the variables
included in the analysis are highly correlated, making them
suitable for factor analysis. Generally, a KMO value above 0.6
is considered acceptable, while values closer to 1.0 indicate
better suitability for factor analysis.Bartlett's test of sphericity
is a statistical test used to determine whether the observed
correlations between variables in a dataset are significantly
different from zero, indicating the presence of significant
relationships among the variables. In this analysis, Bartlett's
test yields an approximate chi-square value of 2426.017 with
66 degrees of freedom and a significance level (Sig.) of 0.00.
The significance level being less than 0.05 indicates that there
are significant correlations among the variables in the
dataset.Overall, the high KMO measure and the significant
result from Bartlett's test suggest that the dataset is
appropriate for conducting factor analysis, as there is strong
evidence of intercorrelations among the variables. This
provides confidence in the validity of the data for exploring
underlying factors or constructs within the studied
phenomenon.

Table 4: Extraction
Constr Initi Extract
ucts Variables al ion
Online shopping for apparels and
fashion items saves me time compared
to shopping in physical stores 1 0.895
The availability of online shopping
platforms makes it easier for me to
Price
access a wide range of apparels and
fashion items 1 0.901
I prefer online shopping for apparels
and fashion items because it allows me
to shop anytime and anywhere. 1 0.869
Online shopping platforms offer a
diverse selection of apparels and
Conven fashion items to choose from. 1 0.878
ience Online shopping allows me to access
fashion trends and styles that may not
be available in local stores 1 0.911

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I find it convenient to browse through

online platforms to discover new
fashion trends and styles 1 0.9
I am motivated to shop online for
apparels and fashion items due to the
availability of discounts and
promotional offer 1 0.863
Brand
Discounts and deals influence my
and
decision to purchase apparels and
Trust
fashion items online. 1 0.97
I am more likely to make a purchase
online if there is a discount or
promotional offer available 1 0.905
I am influenced by fashion trends and
styles I see on social media platforms
when making online purchases. 1 0.936
Recommendations from influencers on
Social
social media influence my decision to
Influen
buy apparels and fashion items online. 1 0.902
ce
I trust the opinions and reviews shared
by other users on social media
platforms when considering online
purchases 1 0.854

The provided data presents the initial and extracted factor

loadings for variables representing different constructs related
to online shopping behaviour among female students in India,
specifically focusing on the constructs of Price, Convenience,
Brand and Trust, and Social Influence.
Price: The factor loadings indicate strong correlations between
the variables and the underlying construct of Price. The
variables "Online shopping for apparels and fashion items
saves me time compared to shopping in physical stores," "The
availability of online shopping platforms makes it easier for me
to access a wide range of apparels and fashion items," and "I
prefer online shopping for apparels and fashion items because
it allows me to shop anytime and anywhere" all exhibit high
loadings ranging from 0.869 to 0.901. This suggests that these
variables collectively represent the construct of Price,
highlighting the importance of factors such as time-saving,
accessibility, and convenience in influencing online shopping
behaviour related to pricing considerations among female
students in India.
Convenience: Similarly, the variables associated with
Convenience demonstrate strong factor loadings, indicating a

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clear association with the underlying construct. The variables

"Online shopping platforms offer a diverse selection of
apparels and fashion items to choose from," "Online shopping
allows me to access fashion trends and styles that may not be
available in local stores," and "I find it convenient to browse
through online platforms to discover new fashion trends and
styles" exhibit high loadings ranging from 0.878 to 0.911. These
findings underscore the significance of convenience, variety,
and accessibility in driving online shopping behaviour among
female students, highlighting the role of online platforms in
catering to their preferences and needs.
Brand and Trust: The variables representing Brand and Trust
also demonstrate strong factor loadings, indicating a robust
association with the underlying construct. The variables "I am
motivated to shop online for apparels and fashion items due to
the availability of discounts and promotional offers,"
"Discounts and deals influence my decision to purchase
apparels and fashion items online," and "I am more likely to
make a purchase online if there is a discount or promotional
offer available" exhibit high loadings ranging from 0.863 to
0.970. These findings underscore the importance of brand
reputation, trustworthiness, and promotional incentives in
shaping online shopping behaviour related to brand
considerations among female students in India.
Social Influence: Lastly, the variables associated with Social
Influence also demonstrate strong factor loadings, indicating a
significant association with the underlying construct. The
variables "I am influenced by fashion trends and styles I see on
social media platforms when making online purchases,"
"Recommendations from influencers on social media influence
my decision to buy apparels and fashion items online," and "I
trust the opinions and reviews shared by other users on social
media platforms when considering online purchases" exhibit
high loadings ranging from 0.854 to 0.936. These findings
highlight the impact of social media, peer recommendations,
and influencer endorsements in influencing online shopping
behaviour related to social influence considerations among
female students in India.

Table 5: Total variance explained.

Rotatio
Init Extracti n Sums
ial on Sums of
Eig of Square
env Squared d

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alu Loading Loading

es s s
C
o
m
p % Cu % Cu % Cu
o of m of m of m
n Va ul Va ul Va ul
e ria ati ria ati ria ati
n Tot nc ve nc ve nc ve
t al e % Total e % Total e %
82 82 82 82 44 44
9.9 .7 .7 .7 .7 .6 .6
1 3 5 5 9.93 5 5 5.36 8 8
86 86 25 69
0.4 3. .3 3. .3 .0 .7
2 36 63 8 0.44 63 8 3.01 7 5
89 89 20 89
0.4 3. .8 3. .8 .1 .8
3 18 48 7 0.42 48 7 2.41 2 7
92
0.3 2. .5
4 2 67 4
94
0.2 1. .2
5 01 68 1
95
0.1 1. .7
6 83 53 4
96
0.1 1. .9
7 48 23 7
97
0.1 0. .8
8 04 86 4
98
0.0 0. .5
9 79 66 0
99
1 0.0 0. .1
0 72 60 0
99
1 0.0 0. .6
1 66 55 5

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10
1 0.0 0. 0.
2 42 35 00

The provided table presents the initial eigenvalues, extraction

sums of squared loadings, and rotation sums of squared
loadings for each component extracted during factor analysis.
Eigenvalues represent the variance explained by each
component or factor. Extraction sums of squared loadings and
rotation sums of squared loadings indicate the proportion of
variance accounted for by each component after extraction
and rotation, respectively.Overall, the interpretation of the
eigenvalues and sums of squared loadings suggests that the
first component is the most significant in explaining the
variance in the dataset, followed by the second and third
components. These components likely represent distinct
factors or constructs underlying the observed variables,
providing insights into the underlying structure of the data and
potential patterns in the relationships between variables.
Rotation of the components aims to simplify interpretation by
maximizing the variance accounted for by each component
while enhancing the clarity of the factor structure.

Discussion
The discussion section of the article on "Online Shopping and
Buying Behaviour: A Study on Female Students with Special
Reference to Apparels and Fashion Industry" delves into the
findings related to price, convenience, brand, and social
influence as key factors influencing the online shopping
behaviour of female students in India within the apparels and
fashion industry. The study reveals that price considerations
play a significant role in shaping the online shopping behaviour
of female students. The convenience of comparing prices
across multiple online platforms and the availability of
discounts and promotional offers emerge as crucial factors
driving purchase decisions. Female students are more inclined
to shop online due to perceived cost savings, as online
shopping for apparels and fashion items often offers
competitive pricing compared to traditional brick-and-mortar
stores. This highlights the importance of price sensitivity
among female students and the role of pricing strategies in
attracting and retaining customers in the highly competitive
online fashion market.
Convenience emerges as a key determinant of online shopping
behaviour among female students. The study findings indicate

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that the ease of access to a diverse range of apparels and

fashion items, coupled with the flexibility to shop anytime and
anywhere, significantly influences purchase decisions. Online
shopping platforms are perceived as convenient channels for
exploring new fashion trends, styles, and brands, providing
female students with a hassle-free shopping experience. The
convenience factor underscores the transformative impact of
digital technologies in reshaping consumer preferences and
behaviours, with online platforms catering to the evolving
needs and lifestyles of female students in India.Brand
reputation and trustworthiness play a crucial role in influencing
the online shopping behaviour of female students. The study
reveals that discounts, promotional offers, and brand
endorsements influence purchase decisions, indicating the
importance of brand perception in driving customer
engagement and loyalty. Female students are more likely to
shop online from brands they trust, highlighting the role of
brand equity in mitigating perceived risks associated with
online shopping, such as product quality and authenticity
concerns. This underscores the significance of brand building
and reputation management strategies for e-commerce
companies seeking to capture the attention and trust of female
students in the competitive online fashion market.
Social media platforms exert a significant influence on the
online shopping behaviour of female students, serving as
sources of inspiration, recommendations, and validation. The
study findings indicate that fashion trends, styles, and
purchasing decisions are heavily influenced by social media
content, including influencer endorsements and user-
generated reviews. Female students rely on social media
platforms to stay updated on the latest fashion trends and seek
validation from peers and influencers when making purchase
decisions. This underscores the power of social influence in
shaping consumer behaviour and driving engagement with
online fashion brands, highlighting the need for e-commerce
companies to leverage social media as a strategic marketing
tool to effectively reach and engage with female students in
India.

Conclusion
In conclusion, this study provides valuable insights into the
online shopping behaviour of female students in India, with a
specific focus on the apparels and fashion industry. The
findings underscore the significance of price, convenience,

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brand, and social influence as key determinants influencing

purchase decisions in this demographic segment.
Price sensitivity among female students is evident, with the
availability of competitive pricing and promotional offers
driving their inclination towards online shopping. Convenience
emerges as a critical factor, with the flexibility to browse and
purchase fashion items anytime and anywhere resonating
strongly with the busy lifestyles of female students. Brand
reputation and trust play a pivotal role in shaping purchase
decisions, emphasizing the importance of building brand
equity and credibility in the competitive online fashion market.
Additionally, social media platforms wield significant influence,
serving as sources of inspiration, recommendations, and
validation for fashion trends and styles.

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