The document presents a research study on online shopping on Flipkart.com in India. It includes: 1) An introduction to online shopping and its history globally and in India. Major online shopping players in India are discussed including Flipkart. 2) The objectives of the study which are to analyze the impact of gender, age and other factors on online shopping experience on Flipkart. 3) The research methodology which uses a questionnaire survey with 220 respondents in Ahmedabad, India. Statistical analysis methods like frequency distribution, chi-square tests, t-tests and factor analysis are to be used.

1. Presented By:
Jay Prajapati
MBA(MM)
CMS-Ahmedabad.
Guided By:
Dr Rachita Jayswal
CMS-Ahmedabad

2. Content
 Introduction of online shopping
 Introduction of Flipkart.com
 Objectives
 Research Methodology
 Data Analysis & Interpretation
 Findings & Discussion
 Recommendations

3. Introduction of Online Shopping
 Online shopping has become a popular shopping method ever since the internet has
declared a takeover
 Online shopping is a form of electronic commerce which allows consumers to
directly buy goods or services from a seller over the Internet using a web browser.
 There are many advantages of online shopping; this is the reason why online stores
are a booming business today.
 Consumers can buy a huge variety of items from online stores, and just about
anything can be purchased from companies that provide their products online.
 Books, clothing, household appliances, toys, hardware, software, and health
insurance are just some of the hundreds of products consumers can buy from an
online store.

4.  History of online shopping
 English entrepreneur Micheal Aldrich invented online shopping in 1979 .
 The first World Wide Web server and browser, created by Tim Berners-Lee
in 1990, opened for commercial use in 1991.
 The first secure retail transaction over the Web was either by NetMarket
or Internet Shopping Network in 1994.
 Amazon.com launched its online shopping site in 1995 and eBay was also
introduced in 1995. Alibaba’s sites Taobao and Tmall were launched in 2003
and 2008, respectively.

5.  History of online shopping in India
 India had an internet user base of about 354 million as of June 2015 and is
expected to cross 500 million in 2016. Despite being the second-largest user
base in world, only behind china.
 In India, cash on delivery is the most preferred payment method,
accumulating 75% of the e-retail activities.
 Demand for international consumer products is growing much faster than
in-country supply from authorized distributors and e-commerce offerings

6.  1991: Introduction of E-Commerce.
 2002: IRCTC teaches India to Book ticket online.
 2003: Introduction of Low Cost Airline with AirDeccan.
 2007: The Deep Discounted model of Flipkart.com

7. Players in India
 Flipkart
 Amazon
 Snapdeal
Others:
 PayTM
 Jabong
 Ebay
 Shopclues
 MakeMyTrip
 AskmeBazaar
 Goibibo

8. Flipkart
 Flipkart is an e-commerce company founded in 2007 by Sachin
Bansal and Binny Bansal.
 The company is registered in Singapore, but has its headquarters
in Bangalore, Karnataka, India.
 Flipkart has launched its own product range under the name "DigiFlip" with
products including tablets, USBs, and laptop bags.
 Flipkart's last fundraising round in May 2015 had pegged its valuation at
$15 billion. In May 2016, Morgan Stanley lowers Flipkart's valuation at
$9.39 billion

9.  Flipkart now employs more than 33,000 people.
 Flipkart allows payment methods such as cash on
delivery, credit or debit card transactions, net banking, e-gift voucher and
card swipe on delivery.

10. Objectives
 To analyze how Gender effects on online shopping in Flipkart.
 To analyze how Age effects on online shopping in Flipkart.
 To analyze how much difference there between Expected and
Perceived Variables.
 To find what the major factors are affects on online shopping
experience Flipkart.
 To know the impact of factors towards online shopping experience of
Flipkart.

11. Research Methodology
 Research Design : Conclusive
 Sampling design:
(a) Target population definition
Target population:
All customers of Flipkart.com
Sampling unit:
A customer of Flipkart.com
Sampling element:
A customer of Flipkart.com
Extent:
Ahmedabad, Gujarat

12. (b) Sampling method:
Non-probability sampling:
Convenience sampling
(c) Sample size determination:
220 Questionnaires
 Scale: Likert Scale
 Questionnaires design:
Question type:
Structure questionnaire

13. Structured question types:
Scaling, Multiple choice questions
Pre-testing of questionnaires:
It will be done with 10 respondents
 Data analysis software: SPSS
 Data analysis techniques:Frequency distribution, Chi-
square, Paired Samples T-test, Exploratory Factor
analysis, Multiple Regression Test
 Data collection tools: Questionnaire
 Data collection method: Survey, personal

14. Data Analysis & Interpretation
 Frequency

15.  Crosstabs Analysis
H1: Male Consumers spend more time in surfing the web than female consumers.
Time spend Gender Crosstabulation
Gender Total
Male Female
Time spend
0-5 hours 42 29 71
6-10 hours 45 28 73
11-15 hours 34 15 49
16-20 hours 6 6 12
More than 20 hours
13 2 15
Total 140 80 220

16.  Chi-square Test
• *p=0.10
Conclusion
 As the significance value is less than 0.10, we can say that alternate hyposethsis is
accepted i.e. “Male Consumers spend more time in surfing the web than female
consumers”.
 After doing crosstabs analysis with Chi Square method we concluded that 13 out of
15 are males who’s using internet more than 20 hours and only 2 female consumers
are using more than 20 hours.
 There are same numbers of Male and Female consumers that spend 16-20 hours. But
Male consumers which uses 6-15 hours are more in numbers than female consumers
so its proved that male consumers uses more internet than females.
Value Sig. (2-sided)
Pearson Chi-Square 6.374a .095*
Likelihood Ratio 8.321 .040
Linear-by-Linear
Association
.221 .638

17. How Often Use Flipkart Age Crosstabulation
Age Total
15-25 26-35 36-45 above 45
How Often Use
Flipkart
Daily 14 14 8 1 37
Weekly 41 33 24 12 110
Monthly 28 19 12 7 66
Yearly 5 1 0 1 7
Total 88 67 44 21 220
H2: Young age Consumers use Flipkart regularly than Old age Consumers

18. Chi-Square Table
*p=0.05
Conclusion
 As the significance value is more than 0.05; so we null hypothesis is accepted.
 Here we analyzed Age with How often use of flipkart with crosstabulation method
and we have concluded that Consumers with age 15-35 use Daily or Weekly online
shopping and in 36 or above age consumers use less time.
Value Sig. (2-sided)
Pearson Chi-Square 7.416 .594*
Likelihood Ratio 9.279 .412
Linear-by-Linear
Association
.108 .743

19.  Paired Samples T-Test
Reliability Statistics of constructs
Variable Number of Variables Cronbach’s Alpha
Expectation 17 0.876
Perception
17 0.863
Pair of Expectation
&
Perception
34 0.830

20.  Hypothesis-There is Significant difference between perception of Factor
and expectation of Factor at online shopping in Flipkart.
 Here total number of factors is 17.
Paired samples
Statistics
Paired samples
Correlations
Paired samples Test
Mean Std.
Deviation
Correlatio
ns
Sig. Mean Std.
Deviatio
n
t df Sig. (2-
tailed)
Pair 1
Conveni
ence
3.7409
2.8818
.91719
1.14463
-.042 .532 .85909 1.49677 8.513 219 .000
Pair 2
Easy to
use
3.9182
3.3136
.88242
1.01891
.151 .026 .60455 1.24342 7.211 219 .000
Pair 3
Discoun
t
3.8500
3.1727
.91174
1.03685
.057 .404 .67727 1.34145 7.489 219 .000
Pair 4
Save
time
3.9680
3.5205
.91565
2.97440
.067 .325 .44749 3.05316 2.169 218 .031
Pair 5
More
variety
3.8227
3.3273
.97476
1.04343
.170 .012 .49545 1.30155 5.646 219 .000
Pair 6
Detailed
informa
tion
3.8045
3.3591
.85634
1.09092
.173 .010 .44545 1.26481 5.224 219 .000

21. Pair 7
Deliver
y
system
3.8091
3.3864
.87581
1.11887
.024 .719 .42273 1.40398 4.466 219 .000
Pair 8
Return
policy
3.6545
3.2500
.94542
1.06254
-.068 .314 .40455 1.46962 4.083 219 .000
Pair 9
Credit-
card
Detail
3.4864
2.9182
1.04458
1.07382
.129 .056 .56818 1.39794 6.029 219 .000
Pair
10
Security
of
Paymen
t
3.7580
3.2283
.92412
1.09750
.050 .460 .52968 1.39882 5.604 218 .000
Pair
11
Better
quality
3.6636
3.2136
.87874
1.09750
.047 .489 .45000 1.36568 4.887 219 .000
Pair
12
Service
3.8818
3.4273
.84109
2.19987
.032 .633 .45455 2.32962 2.894 219 .004
Pair
13
Mercha
ndise
availabl
e
3.6727
3.1636
.91770
.93660
-.028 .683 .50909 1.32930 5.680 219 .000

22. Pair
14
Error
free
3.6818
3.1364
.94053
1.09359
.144 .032 .54545 1.33541 6.058 219 .000
Pair
15
Custom
er
complai
nts
3.7364
3.1773
.88289
1.13090
.102 .132 .55909 1.36196 6.089 219 .000
Pair
16
Product
knowle
dge
3.8182
3.2591
.87775
1.01638
.145 .031 .55909 1.24275 6.673 219 .000
Pair
17
Paymen
t
3.9773
3.3909
.85711
1.06925
.169 .012 .58636 1.25214 6.946 219 .000

23. Conclusion
 Perceived and Expected Factors were weakly and positively correlated (r =
0.077765, p < 0.001)
 There is a significant average difference between Perceived and Expected Factor(1-
17)
Pair
14
Error
free
3.6818
3.1364
.94053
1.09359
.144 .032 .54545 1.33541 6.058 219 .000
Pair
15
Custom
er
complai
nts
3.7364
3.1773
.88289
1.13090
.102 .132 .55909 1.36196 6.089 219 .000
Pair
16
Product
knowle
dge
3.8182
3.2591
.87775
1.01638
.145 .031 .55909 1.24275 6.673 219 .000
Pair
17
Paymen
t
3.9773
3.3909
.85711
1.06925
.169 .012 .58636 1.25214 6.946 219 .000

24.  Exploratory Factor analysis
 The KMO Measure of Sampling Adequacy was 0.934 indicating analysis
results are meritorious
 In total, there were seventy (17) in the data. Items with higher cross
loadings (more than 0.20) and those with lower than 0.5 Measures of
Sampling Adequacy (MSA) were checked.
 Eventually Five statements were trimmed. Finally, remaining twelve
statements were used to compute factors.
 EFA was repeated again excluding the trimmed measurement. Varimax
rotation method was used with factors extraction with Eigen value over 1.It
resulted into extraction of two factors
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett's Test of Sphericity
.934
Approx. Chi-Square 1145.780
Df 66
Sig. .000

25. Composition of each factor identified in factor analysis
Factor Items Extraction
Convenient .645
Easy to Use .619
More Variety .524
Factor 1
Detailed Product Information
.582
Expected Online Delivery System .532
Shopping Environment Better Quality product .559
Error free .506
Customer Complains .634
Product Knowledge .501
Reliable Payment .542
Factor 2 Credit Card System .586
Expected Trust Serviced as Promised .615

26.  In total, there were seventy (17) in the data. Items with higher cross loadings (more
than 0.20) and those with lower than 0.5 Measures of Sampling Adequacy (MSA)
were checked
 Eventually Eight statements were trimmed. Finally, remaining nine statements were
used to compute factors.
 EFA was repeated again excluding the trimmed measurement.
 Varimax rotation method was used with factors extraction with Eigen value over 1.It
resulted into extraction of three factors
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett's Test of Sphericity
.778
Approx. Chi-Square
398.890
Df 36
Sig. .000

27. Composition of each factor identified in factor analysis
Factors Items Extraction
Return Policy
.658
Factor 1
Security of Payment
.508
Perceived Reputation
Product Knowledge
.561
Reliable Payment
.655
Factor 2
Convenient
.618
Perceived Ease of use
Easy to Use
.622
Discount
.567
Factor 3
Credit Card System
.604
Perceived Risk
Better Quality product
.573

28. Regression
 Hypothesis-Customer’s expected online shopping environment, expected trust,
perceived reputation, perceived ease of use, perceived risk has significant influence
over his/her overall online shopping experience on Flipkart
Factor Mean Std. Deviation
Online shopping Experience 3.8636 .85983
Exp_OnlineShop_Env 3.2445 .80734
Exp_Trust 3.1727 1.23206
Per_Reputation 3.8023 .64691
Per_Ease_of_use 3.8295 .76855
Per_Risk 3.6667 .69498

29. Variables
Online Shopping Experience
Ba Bb T Sig. VIF
Exp_OnlineShop_Env
-.131 -.123 -1.949 .053 1.254
Exp_Trust .010 .015 .234 .815 1.213
Per_Reputation .353 .266 4.047 .000 1.347
Per_Ease_of_use .260 .233 3.655 .000 1.268
Per_Risk .249 .201 3.086 .002 1.332
Variables Values
R .562
R Square .316
Adjusted R Square .300
Std.Error .71945
F 19.760
Sig, Level .000

30. Findings & Discussion
FINDINGS
 In this study we have found that male consumers are using more online shopping
than female consumers. It is may be because in India Men use more internet than
Women but mobile users are almost same in numbers.
 Old age consumers don’t shop online much according to this study compares to
Young age consumers. Internet shopping is more popular since 2007, so new
generation is likely to use internet more and do shop online but for old age people its
very difficult to shop online shopping because its new for them.
 There is minor significance difference between consumers perceived and expected
service which is positive. Four factors: Expected Trust, Perceived Reputation,
Perceived Ease of Use , Perceived risk has positive impact on overall online
shopping experience while Expected Online shopping Environment has negative
impact on it.
 Expected online shopping environment, expected trust, perceived reputation,
perceived ease of use and perceived risk factors have 31%. It is less than half of the
total influence on overall online shopping experience. These factors are likely to
find overall experience

31. Findings & Discussion
DISCUSSION
 This study tried to examine the impact of Expected and Perceived
Factors on overall shopping in Flipkart. In addition, It also attempted
to find Expected and Perceived Factors attitude towards customer’s
overall experience in shopping in Flipkart.
 Here after result we have found that four out of five factors have
positive influence on overall online shopping in Flipkart.
 Highest Number of positive influence is by Perceived Reputation on
online shopping in Flipkart which is 0.266.

32.  Lowest Number of positive influence is by Expected Trust on online
shopping in Flipkart which is 0.15.
 Only one Factors influence negatively towards online shopping in
Flipkart which is Expected online shopping Environment valued -
0.19.
 Perceived Ease of use and Perceived Risk are factors which
influence positively towards online shopping in Flipkart valued
2.666 and 2.333 accordingly

33. Recommendation
 Flipkart should provide more awareness to female consumers like work on
advertisement; arrange some public awareness programs, etc.
 Make design of site very easy and simple so that they can use them without
difficulty.
 Flipkart can do some work on conveniences, ease of use, reliable payment
method and discount that consumer expecting high level of services and
perceived low level of services.
 There are other factors that not included in this study can be studied by
some other methods which effects very much on online shopping in Flipkart