apurva final mrp

INTRODUCTION

Conceptual Framework

Customer:

Entity that receives or consumes products (goods or services) and has the ability to choose

between different products and suppliers.

Perception:

Perception is the process by which an individual selects, organizes and interprets information

inputs to create a meaningful picture of the world.

Customer Perception:

Customer Perception is the process, by which an individual selects, organizes and interprets

information about a product or service offered by different marketers.

Online Shopping

Online shopping is the process whereby consumers directly buy goods or services from a seller

in real-time, without an intermediary service, over the Internet.

The growing use of Internet in India provides a developing prospect for online shopping. If E-

marketers know the factors affecting online Indian behavior, and the relationships between these

factors and the type of online buyers, then they can further develop their marketing strategies to

convert potential customers into active ones, while retaining existing online customers.

Internet is changing the way consumers shop and buy goods and services, and has rapidly

evolved into a global phenomenon. Many companies have started using the Internet with the aim

of cutting marketing costs, thereby reducing the price of their products and services in order to

stay ahead in highly competitive markets.

Companies also use the Internet to convey, communicate and disseminate information, to sell the

product, to take feedback and also to conduct satisfaction surveys with customers. Customers use

1

the Internet not only to buy the product online, but also to compare prices, product features and

after sale service facilities they will receive if they purchase the product from a particular store.

In addition to the tremendous potential of the E-commerce market, the Internet provides a unique

opportunity for companies to more efficiently reach existing and potential customers. Although

most of the revenue of online transactions comes from business-to-business commerce, the

practitioners of business-to-consumer commerce should not lose confidence. It has been more

than a decade since business-to-consumer E-commerce first evolved.

The Internet has developed into a new distribution channel and online transaction are rapidly

increasing. This has created a need to understand how the consumers perceive online purchasing.

Price, Trust and Convenience were identified as important factors. The internet has created a

paradigm shift of the traditional way people shop. A consumer is no longer bound to opening at

specific times or specific location. So he can become active at virtually any time any place and

purchase the products or services.

The internet is relatively a new medium for communication and the information exchange that is

present in everyday life. The number of internet user is constantly increasing which also

signifies that online purchasing is increasing. The internet is considered a mass medium that

provides the consumers with purchase characteristics as no other medium. Certain characteristics

are making it more convenient for the consumer compared to the traditional way of shopping,

Such as the ability to any time view and purchase products ,visualize the needs with products and

discuss products with other consumers.

Using the internet to shop online has increased due to the rapid development of the technologies

surrounding the Internet, a company that is interested in selling products from its web site will

constantly has to search for an edge in the fierce competition. Since there are so many potential

consumers, it is of the up most importance to be able to understand what the consumer wants and

needs. One of the primary reasons to use the internet is combined with searching for products

and finding the information about them.

The Internet, as a mean for both firms and individuals to conduct business, is nowadays one of

the most widely used non-store formats. According to Magee (2003), the growth in the number

of online shoppers is greater than the growth in Internet users, indicating that more Internet users

are becoming comfortable to shop online. Furthermore, not only does the number of adopters

grow, but also the volume of their purchases is proportionally increased . The two most

2

commonly cited reasons for online shopping have been convenience and price. The capability of

purchasing without leaving your place is of great interest to many consumers. Moreover, the use

of Internet tools for price searching and comparison provides an additional advantage in

consumers’ final decision, as they can purchase their desired products in the lowest available

price . On the contrary, privacy and security have been the great concerns , resulting many

people to browse the Internet for informational matters than for buying online .

Online Shopping In India

It is a fact that a great online shopping revolution is expected in India in the coming years. There

is a huge purchasing power of a youth population aged 18-40 in the urban area.

Few Factors That Boost Online Shopping in India

Rapid growth of cybercafés across India

Access to Information

The increase in number of computer users

Reach to net services through broadband

Middle-class population with spending power is growing. There are about 200 million of

middle-class population good spending powers. These people have very little time to spend for

shopping. Many of them have started to depend on internet to satisfy their shopping desires .

Rising Connectivity

The growth of Internet Subscribers is getting doubled year by year. The usage of internet in

India is only 4% of the total population. This is also getting increased day by day as the costs of

computers are decreasing and net penetration is increasing. The cost of internet usage is also

getting lower, with good competition among the providers. Wi-Fi & Wimax system has also

started in India. This will increase the usage as it goes more on wireless internet. Indians are

proving every 15 time that they can beat the world when it comes to figures of online shopping.

More and more Indians are going to online shopping and the frequency of India„s online buying is crossing the overall global averages.

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Few Facts about Online Shopping

The figures from IAMAI show that the internet users in India will grow to 200 million by 2010.

Around 25% of regular shoppers in India are in the 18-25 age groups, and 46% are in the 26-35

year range.

Indian online matrimonial sector is worth around $230 million

Worldwide E-commerce is only growing at the rate of 28%, since India being a younger

market, the growth of e-commerce is expected at 51% in the coming years.

In line with global trends finally India has also started shopping online these days. As per the

study by IAMAI online shopping in India has rose from $11million in 1999-2000 to $522

million in 2007 and it is expected to rise above $700 million by end March 2010.

Changing Attitude towards Online Shopping:

“Awareness, Future Demand Focus for Emerging Markets & Current Issues” Malls springing up

everywhere and yet people are E-shopping! And not in small numbers either. Consumers are

more rational nowadays and have ability to get the choices from the market. Awareness among

the consumers is spread through internet. The number of internet users is increasing day by day

which attracts people who have an option to buy online. It was never thought that Indians would

go in for e-shopping in such a big way. Ticketing, travel bookings and even books and movies

seem fine to buy online. Knowing that in India sizes vary from brand to brand and quality is

inconsistent, even of some electronic items, how is it that there are people buying these items

online? In India there are some segments of people who have not yet tried purchasing over

internet.

4

Rationale of Study

The Internet has developed into a new distribution channel and online transactions are rapidly

increasing. This has created a need to understand how the consumers perceive online purchasing

therefore this research is been conducted to understand customer perception towards online

shopping.

The main purpose of this research is to identify and get insight into factors the online consumer

takes into consideration when he/she buys products on internet, what affects their shopping

behavior and what persuades them to buy the products.

5

Objectives of Study

To study the online shopping behavior of customers

To study the factors influencing online shoppers and consumers.

To study the demographic variables (age, gender, income etc.) that can affect the online

shopping behavior of shoppers.

6

Literature Review

Bellman et al., (1999) examined the relationship among demographics, personal characteristics,

and attitudes towards online shopping. These authors find that people who have a more wired

lifestyle. and who are more time constrained tend to buy online more frequently, i.e., those who

use the Internet as a routine tool and/or those who are more time starved prefer shopping on the

Internet.

Bhatnagar et al., (2000) measured how demographics, vender/service/ product characteristics,

and website quality influence the consumers attitude towards online shopping and consequently

their online buying behavior. They report that the convenience the Internet affords and the risk

perceived by the consumers are related to the two dependent variables (attitudes and behavior)

positively and negatively, respectively.

Jarvenpaa et al., (2000) investigated how consumers perceived store size and reputation

influence their trust in the store, risk perception, attitudes, and willingness to buy at the specific

store. They discover that there is a positive relationship between consumer trust in Internet stores

and the stores perceived reputation and size. Higher consumer trust also reduces perceived risks

associated with Internet shopping and generates more favorable attitudes towards shopping at a

particular store, which in turn increases willingness to purchase from that store.

Jahng et al.,(2001) proposed and validated a Technology/Product Fit Model to describe and

predict the relationship between product characteristics, e-commerce environment

characteristics, and user outcomes. They classified products sold on the Internet as belonging to

four categories based on social and product presence requirements: simple, experiential,

complex, or social. When a positive fit is established between the ecommerce environment and

the product requirements, favorable user outcomes are generated that include user satisfaction,

decision confidence, e-commerce acceptance, and purchase intent.

Efthymios Constantinides(2004) in his research on the topic Influencing the online

consumer’s behavior: the Web experience included Research on the buying behavior and the

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factors influencing the decision-making process of online consumers has revealed similarities as

well as differences between them and the traditional customers. The uncontrollable factors

(external and personal ones) affecting consumer behavior are similar for both types of

consumers. The tools however used by traditional and online marketers in order to influence the

buying behavior of their customers are not quite the same. In the case of traditional consumers

the 4Ps of the marketing mix are considered as the main controllable tools influencing the buying

behavior. Research indicates that in the case of the Web consumer a set of elements experienced

during the virtual interaction are indeed the controllable factors affecting the online buyer. This

study identifies the main constituents of the online experience or Web experience as being:

The functionality of the Web site that includes the elements dealing with the site’s

usability and interactivity;

The psychological elements intended for lowering the customer’s uncertainty by

communicating trust and credibility of the online vendor and Web site; and

The content elements including the aesthetic aspects of the online presentation and the

marketing mix.

These three sets of factors are the main online marketing tools under the control of the e-

marketer.

Finally, the Web experience must be regarded as a dynamic and evolving subject rather than a

static one; developments in the virtual marketplace, changing customer techno graphics and

technological innovation will present e-marketers with new tools and methods for enhancing

their customers’ online experience.

Rajasee Rege (November 2007) conducted research on the topic What influences online

shopping behavior of consumers? Usability vs. Security perspective According to her in

today’s fast paced world, the popularity of e-commerce websites has grown by leaps and bounds.

Online purchasing of goods, both expensive and cheap, is prevalent to a much larger extent in

recent years due to convenience, speedy transactions and enhanced shopping experience at your

fingertips. This paper aimed at gauging the level of importance of various usability vs. security

factors affecting online shopping behavior by conducting a research study involving a task list,

debriefing questionnaire and a post-test survey. The paper aimed at contrasting the security-

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related awareness of consumers while performing transactions online with the usability factors

that influence the shopping behavior of the consumers.

Anders Hasslinger et al., (2008-02-01) in their study they showed that internet has developed

into a new distribution channel and online transactions are rapidly increasing. This has created a

need to understand how the consumer perceives online purchases. The purpose of this

dissertation was to examine if there are any particular factors that influence the online consumer.

Primary data was collected through a survey that was conducted on students at the University of

Kristiansand. Price, Trust and Convenience were identified as important factors. Price was

considered to be the most important factor for a majority of the students. Furthermore, three

segments were identified, High Spenders, Price Easers and Bargain Seekers. Through these

segments we found a variation of the different factors importance and established implications

for online book stores.

Scott M. Smith et al.,(2008) in their research paper they discussed online shopping in context of

diffusion of innovation theory. It proposed that online shopping is a discontinuous innovation

whose adoption rate is influenced by several of Rogers' (2004) diffusion deterrents. A new 12-

item 'Computer Competence Index' (CCI) is proposed and tested using data from an internet-

administered US probability study of 1800 online users. EShoppers are profiled using a tertile

split of the CCI. Each tertile's demographics, computer activities, computer-oriented lifestyles,

and online purchase activities are reported. Evidence was presented that concepts related to the

diffusion of innovation may explain resistance in the growth of online shopping.

A.M. Sakkthivel (2009) in their research paper aimed to identify the impact of demographics on

consumer buying behavior towards online purchase of different products based on the

involvement and investment (High, Medium and Low). It attempted to unearth the impact of the

demographics on online purchase which is at present relatively limited. It would help the

marketers to identify the demographic profile of consumers which is otherwise not known due to

the intangible nature of internet. The findings would help the marketers to design their offerings

based on the demographic profile of online consumers and would help the online marketers to

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identify and segment the online consumers which will enhance their focus and eventually leads

to financial growth.

Bikramjit Rishi (2010) in their study on Online shopping is an innovative option of distribution

available in the hands of marketers. It is innovative and creative because marketers can

experiment with it in form, content, visibility and availability. In India online shopping is

considered as a relevant alternative channel for retailing and it is now an important part of the

retail experience. This research study is an empirical study to find out the motivators and

decisional influencers of online shopping. The sample has been selected from the youth

population as this group of people actually use internet to buy online. The study highlights that

reliability; accessibility and convenience are the major motivator factors which motivate the

Indian consumer to buy online. Similarly, reluctance and preference are the two decisional

factors which influence the decision.

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Research Methodology

The study

The study is descriptive in nature. The research approach to collect the data is survey and the

analysis is based on primary data.

The Sample

The sampling plan for the study decides the work area that is the population which has to be

surveyed.

Sample Size

200 respondents from Indore region.

Sampling technique

Non Probability Convenient Sampling Technique

The tools

For Data Collection

Both Primary and Secondary Data were used for data collection.

Primary Data was collected by conducting a survey on 200 respondents of Indore region who

will be asked questions through a self designed questionnaire to know their perception regarding

online shopping.

Secondary Data was taken from magazines, newspapers, related websites and journals.

For Data Analysis

Suitable statistical tools such as frequency distribution, t-test, one way anova are applied.

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GENDER

9 4 4 7 .0 4 7 .0 4 7 .0

1 0 6 5 3 .0 5 3 .0 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

Ma l e

F e ma l e

T o ta l

Va l i dF re q u e n c y Pe rc e n t Va l i d Pe rc e n t

Cu mu l a t i v ePe rc e n t

GENDER

Female

Male

12

AGE

90 45.0 45.0 45.0

64 32.0 32.0 77.0

35 17.5 17.5 94.5

11 5.5 5.5 100.0

200 100.0 100.0

15-25

25-35

35-45

45 and above

Total

ValidFrequency Percent Valid Percent

Cumulat ivePercent

AGE

45 and above

35-45

25-35

15-25

13

MINCOME

49 24.5 24.5 24.5

9 4. 5 4. 5 29.0

45 22.5 22.5 51.5

54 27.0 27.0 78.5

43 21.5 21.5 100. 0

200 100. 0 100. 0

less t han 10000

10000-20000

20000-30000

30000-40000

40000 and above

Total


Cumulat ivePercent

MINCOME

40000 and above

30000-40000

20000-30000

10000-20000

less t han 10000

14

Q1- Do you use Internet?

Q1

2 0 0 1 0 0 .0 1 0 0 .0 1 0 0 .0Ye sVa l i dFre q u e n c y Pe rc e n t Va l i d Pe rc e n t


Q1

Yes

15

Q2- How long have you been using internet?

Q2

33 16. 5 16. 5 16. 5

50 25. 0 25. 0 41. 5

54 27. 0 27. 0 68. 5

63 31. 5 31. 5 100. 0

200 100. 0 100. 0

Less t han 1 year

1-3 years

3-5 years

More t han 5 years

Tot al


Cumulat ivePercent

Q2

More t han 5 years

3-5 years

1-3 years

Less t han 1 year

16

Q3- On the average how much time (per week) do you spend in surfing the web?

Q3

44 22. 0 22. 0 22. 0

38 19. 0 19. 0 41. 0

52 26. 0 26. 0 67. 0

43 21. 5 21. 5 88. 5

23 11. 5 11. 5 100. 0

200 100. 0 100. 0

0-5 hours

6-10 hours

11-15 hours

16-20 hours

More t han 20 hours

Tot al


Cumulat ivePercent

Q3

More t han 20 hours

16-20 hours

11-15 hours

6-10 hours

0-5 hours

17

0-5 hours

11-15 hours

16-20 hours

More than 20 hours

6-10 hours

Q4- Where do u most often access the internet?

Q4

91 45.5 45.5 45.5

16 8.0 8.0 53.5

77 38.5 38.5 92.0

6 3.0 3.0 95.0

10 5.0 5.0 100.0

200 100.0 100.0

Home

College

Of f ice

Cyber Cafes

Others

Total


Cumulat ivePercent

Q4

O t hers

Cyber Caf es

O f f ice

College

Home

18

Q5- Have you purchased anything online ever?

Q5

99 49. 5 49. 5 49. 5

101 50. 5 50. 5 100. 0

200 100. 0 100. 0

Yes, cont inue t o buy

Yes, but discont inued

Tot al


Cumulat ivePercent

Q5

Yes, but discont inue

Yes, cont inue t o buy

19

6- Past experience from online shopping

Null Hypothesis: H0: There is no significant difference between the respondents of different

gender towards their past experience from online shopping.

Alternative Hypothesis: H1: There is significant difference between the respondents of different

gender towards their past experience from online shopping.

T-Test

Gro u p Sta tis tic s

9 4 3 1 .0 9 5 .7 7 5 .5 9 6

1 0 6 2 9 .1 2 5 .7 7 0 .5 6 0

g e n d e rMa l e

F e ma l e

T OT PEXPN Me a n Std . De v i a t i o n

Std . Erro rMe a n

Ind e p e n de nt Sa mple s Te s t

.0 0 0 .9 9 6 2 .4 0 0 1 9 8 .0 1 7 1 .9 6 .8 1 8 .3 5 0 3 .5 7 5

2 .4 0 0 1 9 5 .11 0 .0 1 7 1 .9 6 .8 1 8 .3 5 0 3 .5 7 5

Eq u a l v a ria n c e sa s s u me d

Eq u a l v a ria n c e sn o t a s s u me d

TOTPEXPF Sig .

L e v e n e 's T e s t fo rEq u a lity o f Va ria n c e s

t d f Sig . (2 -ta ile d )Me a n

Diffe re n c eStd . Erro r

Diffe re n c e L o we r Up p e r

9 5 % Co n fid e n c eIn te rv a l o f th eDiffe re n c e

t-te s t fo r Eq u a lity o f Me a n s

Interpretation:

The f value as per the above table is .000 which is significant at .996, which is higher than .05. It

implies that null hypothesis is accepted (not rejected) . Therefore we can conclude that there is

no significant difference between respondents of different gender towards their past experience

from online shopping.

20

Null Hypothesis: H0: there is no significant difference among the respondents of different age

group towards their past experience from online shopping.

Alternative Hypothesis: H1: There is significant difference among the respondents of different

age group towards their past experience from online shopping.

Oneway

Descr i pt i ves

TO TPEXP

90 29. 21 5. 795 . 611 28. 00 30. 42 16 39

64 30. 73 6. 014 . 752 29. 23 32. 24 17 40

35 31. 34 5. 785 . 978 29. 36 33. 33 20 40

11 28. 73 4. 606 1. 389 25. 63 31. 82 23 37

200 30. 05 5. 841 . 413 29. 23 30. 86 16 40

15- 25

25- 35

35- 45

45 and Abov e

Tot al

N M ean St d. Dev iat ionSt d. Er r or Lower Bound Upper Bound

95% Conf idence I nt er v al f orM ean

M inim um M ax im um

ANOVA

TOTPEXP

171. 054 3 57. 018 1. 689 . 171

6617. 541 196 33. 763

6788. 595 199

Bet ween Groups

Wit hin Groups

Tot al

Sum ofSquares df Mean Square F Sig.

Interpretation

The f value as per the above table is 1.689 which is significant at .171 , which is higher than .05.

It implies that null hypothesis is accepted (not rejected) . Therefore we can conclude that there is

no significant difference among respondents of different age groups towards their past

experience from online shopping.

21

Null Hypothesis: H0: there is no significant difference among the respondents of different

income groups towards their past experience from online shopping.


income groups towards their past experience from online shopping.

Oneway

Descr i pt i ves

TO TPEXP

49 28. 55 5. 813 . 830 26. 88 30. 22 16 38

9 31. 33 6. 576 2. 192 26. 28 36. 39 24 38

45 30. 40 5. 404 . 806 28. 78 32. 02 22 40

54 30. 61 6. 036 . 821 28. 96 32. 26 17 40

43 30. 40 5. 880 . 897 28. 59 32. 21 19 39

200 30. 05 5. 841 . 413 29. 23 30. 86 16 40

les s t han 10000

10000- 20000

20000- 30000

30000- 40000

40000 and above

Tot al

N M ean St d. Dev iat ionSt d. Er r orLower Bound Upper Bound



ANOVA

TOTPEXP

152. 560 4 38. 140 1. 121 . 348

6636. 035 195 34. 031

6788. 595 199

Bet ween Groups

Wit hin Groups

Tot al


Interpretation:

The f value as per the above table is 1.121 which is significant at .348 , which is higher than .05.

It implies that null hypothesis is accepted (not rejected) . Therefore we can conclude that there is

no significant difference among respondents of different income groups towards their past

experience from online shopping.

22

Q7- Which category (ies) of goods/ services are you planning to buy through internet in the near future?

Books

Q7 .1

1 2 8 6 4 .0 6 4 .0 6 4 .0

7 2 3 6 .0 3 6 .0 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l

Va l i dFre q u e n c y Pe rc e n t Va l i d Pe rc e n t

Cu mu la t i v ePe rc e n t

Computer softwares

Q7 .2

1 5 2 7 6 .0 7 6 .0 7 6 .0

4 8 2 4 .0 2 4 .0 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



CD’s/Videos

Q7 .3

1 5 9 7 9 .5 7 9 .5 7 9 .5

4 1 2 0 .5 2 0 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l

Va l i dF re q u e n c y Pe rc e n t Va l i d Pe rc e n t


Clothing

Q7 .4

1 5 3 7 6 .5 7 6 .5 7 6 .5

4 7 2 3 .5 2 3 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



Travel/Hotel/Car Rental

Q7 .5

1 0 3 5 1 .5 5 1 .5 5 1 .5

9 7 4 8 .5 4 8 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



23

Event Tickets

Q7 .6

1 2 5 6 2 .5 6 2 .5 6 2 .5

7 5 3 7 .5 3 7 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



Electronics

Q7 .7

1 4 9 7 4 .5 7 4 .5 7 4 .5

5 1 2 5 .5 2 5 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



Jewelery/Accessories

Q7 .8

1 6 1 8 0 .5 8 0 .5 8 0 .5

3 9 1 9 .5 1 9 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



Movie Tickets

Q7 .9

7 3 3 6 .5 3 6 .5 3 6 .5

1 2 7 6 3 .5 6 3 .5 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

No

Ye s

To ta l



24

Q8- Please rate the importance of the following factors that might motivate you to purchase online.

Saves Time

F8.1

1 .5 .5 .5

1 .5 .5 1. 0

7 3. 5 3. 5 4. 5

41 20.5 20.5 25.0

150 75.0 75.0 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.1

Most I mpor t ant

4

3

2

Least I mpor t ant

25

Ease of Purchase

F8.2

4 2. 0 2. 0 2. 0

13 6. 5 6. 5 8. 5

37 18.5 18.5 27.0

68 34.0 34.0 61.0

78 39.0 39.0 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.2

Most I mpor t ant

4

3

2

Least I mpor t ant

26

Avoid hassels of shopping in store

F8.3

6 3. 0 3. 0 3. 0

12 6. 0 6. 0 9. 0

46 23.0 23.0 32.0

64 32.0 32.0 64.0

72 36.0 36.0 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.3

Most I mpor t ant

4

3

2

Least I mpor t ant

27

Ability to shop anytime

F8.4

5 2. 5 2. 5 2. 5

6 3. 0 3. 0 5. 5

22 11.0 11.0 16.5

75 37.5 37.5 54.0

92 46.0 46.0 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.4

Most I mpor t ant

4

3

2

Least I mpor t ant

28

Price

F8.5

7 3. 5 3. 5 3. 5

18 9. 0 9. 0 12.5

53 26.5 26.5 39.0

69 34.5 34.5 73.5

53 26.5 26.5 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.5

Most I mpor t ant

4

3

2

Least I mpor t ant

29

Superior selection/Availability

F8.6

4 2. 0 2. 0 2. 0

11 5. 5 5. 5 7. 5

42 21.0 21.0 28.5

79 39.5 39.5 68.0

64 32.0 32.0 100. 0

200 100. 0 100. 0

Least Important

2

3

4

Most Important

Total


Cumulat ivePercent

F8.6

Most I mpor t ant

4

3

2

Least I mpor t ant

30

9- Factors which restrict from purchasing online.


gender towards the factors which restrict them to purchase online.


gender towards the factors which restrict them to purchase online.

T-Test


9 4 3 2 .2 0 7 .0 0 9 .7 2 3

1 0 6 3 2 .2 4 6 .2 6 6 .6 0 9

g e n d e rMa l e

F e ma l e

T OT RESF RN Me a n Std . De v i a t i o n

Std . Erro rMe a n

Inde pe nde nt Sa mple s Te s t

.6 1 3 .4 3 4 -.0 3 6 1 9 8 .9 7 1 -.0 3 .9 3 9 -1 .8 8 5 1 .8 1 7

-.0 3 6 1 8 7 .9 3 1 .9 7 2 -.0 3 .9 4 5 -1 .8 9 8 1 .8 3 1



TOTRESFRF Sig .

L e v e n e 's Te s t fo rEq u a lity o f Va ria n c e s






Interpretation:

The f value as per the above table is .613 which is significant at .434 , which is higher than .05. It

implies that null hypothesis is accepted (not rejected) . Therefore we can conclude that there is

no significant difference between respondents of different gender towards the factors which

restrict them to purchase online.

31

Null Hypothesis: H0: There is no significant difference among the respondents of different

income groups towards the factors which restrict them to purchase online.


income groups towards the factors which restrict them to purchase online.

Oneway

Descr i pt i ves

TO TRESFR

49 34. 49 5. 424 . 775 32. 93 36. 05 26 50

9 33. 89 6. 112 2. 037 29. 19 38. 59 26 46

45 33. 47 6. 040 . 900 31. 65 35. 28 18 45

54 32. 17 6. 895 . 938 30. 28 34. 05 20 45

43 28. 05 6. 473 . 987 26. 05 30. 04 16 41

200 32. 22 6. 609 . 467 31. 30 33. 14 16 50

les s t han 10000

10000- 20000

20000- 30000

30000- 40000

40000 and above

Tot al




ANOVA

TOTRESFR

1096. 579 4 274. 145 7. 038 . 000

7595. 741 195 38. 953

8692. 320 199

Bet ween Groups

Wit hin Groups

Tot al


Interpretation:

The f value as per the above table is 7.038 which is significant at .000 , which is less than .05. It

implies that null hypothesis is rejected. Therefore we can conclude that there is significant

difference among respondents of different income group towards the factors which restrict them

to purchase online.

32

Null Hypothesis: H0: There is no significant difference among the respondents of different age

groups towards the factors which restrict them to purchase online.


age groups towards the factors which restrict them to purchase online.

Oneway

Descr i pt i ves

TO TRESFR

90 34. 01 5. 988 . 631 32. 76 35. 27 18 50

64 30. 38 7. 245 . 906 28. 57 32. 18 16 45

35 31. 14 6. 731 1. 138 28. 83 33. 45 17 45

11 31. 73 3. 228 . 973 29. 56 33. 90 27 36

200 32. 22 6. 609 . 467 31. 30 33. 14 16 50

15- 25

25- 35

35- 45

45 and Abov e

Tot al




ANOVA

TOTRESFR

549. 864 3 183. 288 4. 412 . 005

8142. 456 196 41. 543

8692. 320 199

Bet ween Groups

Wit hin Groups

Tot al


Interpretation:

The f value as per the above table is 4.412 which is significant at .005 , which is less than .05. It


difference among respondents of different age group towards the factors which restrict them to

purchase online.

33

Q10- Did you face any problem while making an online purchase?

Q1 0

1 0 8 5 4 .0 5 4 .0 5 4 .0

9 2 4 6 .0 4 6 .0 1 0 0 .0

2 0 0 1 0 0 .0 1 0 0 .0

Ye s

No

To ta l



Q10

No

Yes

34

11. Problems faced while purchasing online.


gender towards the problem faced while purchasing online.


gender towards the problem faced while purchasing online.

T-Test


9 4 1 3 .0 1 1 4 .3 1 8 1 .4 7 7

1 0 6 1 7 .4 7 1 4 .3 8 5 1 .3 9 7

g e n d e rMa l e

F e ma l e

T OT PRBF CN Me a n Std . De v i a t i o n

Std . Erro rMe a n

Inde pe nde nt Sa mple s Te s t

.3 0 5 .5 8 1 -2 .1 9 4 1 9 8 .0 2 9 -4 .4 6 2 .0 3 4 -8 .4 7 1 -.4 5 1

-2 .1 9 4 1 9 5 .3 6 5 .0 2 9 -4 .4 6 2 .0 3 3 -8 .4 7 1 -.4 5 2



TOTPRBFCF Sig .

L e v e n e 's Te s t fo rEq u a lity o f Va ria n c e s






Interpretation:

The f value as per the above table is .305 which is significant at .581 , which is more than .05. It

implies that null hypothesis is accepted (not rejected). Therefore we can conclude that there is no

significant difference between respondents of different gender towards the problem faced while

purchasing online.

35

Null Hypothesis: H0: There is no significant difference among the respondents of different age

group towards the problem faced while purchasing online.


age group towards the problem faced while purchasing online.

Oneway

Descr i pt i ves

TO TPRBFC

90 18. 56 13. 934 1. 469 15. 64 21. 47 0 36

64 12. 78 14. 589 1. 824 9. 14 16. 43 0 36

35 14. 60 14. 849 2. 510 9. 50 19. 70 0 36

11 6. 91 12. 037 3. 629 - 1. 18 15. 00 0 31

200 15. 38 14. 490 1. 025 13. 35 17. 40 0 36

15- 25

25- 35

35- 45

45 and Abov e

Tot al




ANOVA

TOTPRBFC

2150. 406 3 716. 802 3. 545 . 016

39634. 469 196 202. 217

41784. 875 199

Bet ween Groups

Wit hin Groups

Tot al


Interpretation:

The f value as per the above table is 3.545 which is significant at .016, which is less than .05. It


difference among respondents of different age group towards the problem faced while

purchasing online.

36

Null Hypothesis: H0: There is no significant difference among the respondents of different

income group towards the problem faced while purchasing online.


income group towards the problem faced while purchasing online.

Oneway

Descr i pt i ves

TO TPRBFC

49 22. 55 12. 944 1. 849 18. 83 26. 27 0 36

9 13. 89 13. 374 4. 458 3. 61 24. 17 0 29

45 12. 18 14. 699 2. 191 7. 76 16. 59 0 36

54 16. 63 14. 332 1. 950 12. 72 20. 54 0 36

43 9. 28 13. 123 2. 001 5. 24 13. 32 0 36

200 15. 38 14. 490 1. 025 13. 35 17. 40 0 36

les s t han 10000

10000- 20000

20000- 30000

30000- 40000

40000 and above

Tot al




ANOVA

TOTPRBFC

4686. 042 4 1171. 511 6. 158 . 000

37098. 833 195 190. 250

41784. 875 199

Bet ween Groups

Wit hin Groups

Tot al


Interpretation:

The f value as per the above table is 6.158 which is significant at .000, which is less than .05. It


difference among respondents of different income group towards the problem faced while

purchasing online.

37

Q12- What was the impact on your attitude towards the site where you faced problems?

Q12

29 14. 5 14. 5 14. 5

55 27. 5 27. 5 42. 0

27 13. 5 13. 5 55. 5

89 44. 5 44. 5 100. 0

200 100. 0 100. 0

St opped visit ing t hatpar t icular websit e

St opped purchasing att hat par t icular websit e

St opped purchasingf rom t hat company'sof f line st ore

I t had no impactwhat soever

Tot al


Cumulat ivePercent

Q12

I t had no impact wha

St opped purchasing f

St opped purchasing a

St opped visit ing t ha

38

Q13- Please the rate your overall level of satisfaction on your experience of online shopping.

Q13

5 2. 5 2. 5 2. 5

23 11. 5 11. 5 14. 0

47 23. 5 23. 5 37. 5

101 50. 5 50. 5 88. 0

24 12. 0 12. 0 100. 0

200 100. 0 100. 0

St rongly Disagree

Disagree

Neut ral

Agree

St rongly Agree

Tot al


Cumulat ivePercent

Q13

St rongly Agree

Agree

Neut ral

Disagree

St rongly Disagree

39

Q14- What was the impact on your online shopping behavior in general?

Q14

39 19. 5 19. 5 19. 5

54 27. 0 27. 0 46. 5

107 53. 5 53. 5 100. 0

200 100. 0 100. 0

St opped shopping online

St opped shopping f ort hat product cat egory

I t had no impactwhat soever

Tot al


Cumulat ivePercent

Q14

I t had no impact wha

St opped shopping f or

St opped shopping onl

40

RESULTS

1. 47% respondents are male and 53% respondents are female.

2. 45% respondents fall in 15-25 age group, 32% in 25-35, 17.5% in 35-45 and 5.5% fall in

45 and above age group.

3. 24.5% respondents have less than 10000 monthly family income, 4.5% fall in 10000-

20000, 22.5% fall in 20000-30000, 27% fall in 30000-40000 income category, 21.5%

respondents fall in 40000 and above income category.

4. 100% respondents are using internet in their day to day lives.

5. 16.5% consumers have been using internet from less than 1 year, 25% respondents from

1-3 years, 27% from 3-5 years, and 31.5% have been using internet from more than 5

years.

6. 22% respondents spent 0-5 hours per week surfing the web, 19% for 6-10 hours, 26%

respondents spend 11-15 hours per week on net, 21.5% respondents for 16-20 hours and

11.5% respondents spent more than 20 hours surfing the web.

7. 45.5% respondents surf internet from their home, 8% from college, 38.5% respondents

surfed web from office, 3% from cyber cafes and 5% used other medium.

8. 49.5% respondents have purchased online and still continue to do so whereas 50.5%

respondents have purchased online but discontinued due to some reasons.

9.

10. Categories of products/services mostly purchased by respondents include Books(36%) ,

Computer softwares (24%), CD’s/Videos (20.5%), Clothing (23.5%), Travel/Hotel/Car

rental (48.5%), Event tickets (37.5%), Electronics (25.5%), Jewelery/Acessories (19.5%),

and Movie tickets (63.5%).

11. According to respondents the factors which motivate them to purchase online are – saves

time (75%), ease of purchase (39%), avoid hassels of shopping in store (36%), ability to

shop anytime (46%), price (26.5%), superior selection/availability (32%)

9.

10. 54% respondents did not face any problem while purchasing through internet while

46% respondents faced problem.

11.

41

12. 14.5% respondents stopped visiting that particular website on which they faced

problems, 27.5% respondents stopped purchasing from that particular website,13.5%

respondents stopped purchasing from that company’s online store, 44.5% respondents had no

impact whatsoever.

13. 12% respondents were highly satisfied with their online shopping experience, 50.5%

respondents were satisfied, 23.5% respondents were neutral, 11.5% were dissatisfied and

2.5% respondents were highly dissatisfied.

14. 53.5% respondents had no impact on their online shopping behavior in general, 27%

respondents stopped shopping for that particular category, 19.5% respondents stopped

shopping online.

42

SUMMARY

The report of the present study has been divided into six chapters.

Chapter 1- Introduced the conceptual framework with review of literature, rationale of

the study and objective of the study.

Chapter 2 - Described the methodology of the study in terms of nature of the study and

tools for both data collection and analysis.

Chapter 3 - Presented results.

Chapter 4 - Deals with the discussion part.

Chapter 5 – For summary, conclusion and suggestion.

Chapter 6 - Presented implications of the study to highlight the application value of the

study.

References have been given in standard format to facilitate the future researchers for tracing the

source of literature.

43

CONCLUSION

Increased Internet penetration, a hassle free shopping environment and high levels of Net

saviness see more and more Indians shopping online. But at the same time the companies need to

reduce the risks related to consumer incompetence by tactics such as making purchase websites

easier to navigate, and introducing Internet kiosk, computers and other aids in stores. The goal is

not to convert all shoppers to online purchasing, but to show them it„s an option. In addition to

above, efforts need to be taken to educate the online buyers on the steps that need to be

undertaken while making an online purchase. Moreover, the feedback of an online buyer should

be captured to identify flaws in service delivery. This can be done through online communities

and blogs that serve as advertising and marketing tools and a source of feedback for enterprises. I

found that it is a challenge for E-marketers to convert low frequency online buyers into regular

buyers through successful website design and by addressing concerns about reliable

performance. Thus, the online retailing raises more issues than the benefits it currently offers.

The quality of products offered online and procedures for service delivery are yet to be

standardized. Till the same is done, the buyer is at a higher risk of frauds.

44

SUGGESTIONS

These are some of the suggestions which could be adopted by companies dealing in online

shopping:

1. Test your site early and often.

2. Test the integrity of your content. Check for misspelled words, broken links, busted pictures, etc. An unprofessional appearance may lead to a bad customer experience and kill your chances to sell online.

3. Make sure images load quickly. A slow-loading page may simply drive customers away to click on to the next site. You want to minimize page download time.

4. "Load test" your site. You’re expecting (or at least hoping for) a rush of customers. So it’s a good idea to determine how much traffic your Web site can support. You can’t sell online if customers can’t reach your site.

5. Create sample transactions. These can simulate expected customer traffic and Web transactions. By running "synthetic" transactions periodically - say, every five to 15 minutes – you’ll know there’s a problem before your customers do.

6. Check the performance of your network provider. You can do this by looking at a site that’s similar to yours and in your area, but connected to another network. In a fiercely competitive business, every second matters.

7. Add cross-sell and up-sell opportunities throughout your site.

8. Make your policies easy to find and provide customer service contact details for a real person. Providing an easy-to-find phone number on the site helps online shoppers feel more secure and increases your chance to sell online. Clearly state your company’s return policy. Remind customers of the last possible day to order and receive a product in time for the holidays.

9. Make your search function more effective. Your search function should accommodate common misspellings by returning similarly spelled items or your site’s most popular search terms.

45

IMPLICATIONS OF STUDY

For online shopping companies:

The study would help the online shopping companies in identifying the potential audience also

knowing the major factors which influence online purchasing decision of customers and knowing

the past experience from online shopping and the factors which restrict them to purchase online.

This research would thus be very helpful for online shopping companies in making decisions on

strategies to be adopted to increase traffic.

For Researchers:

This study would help researchers in their further study on related topics also would help in

identifying other factors which may influence customers in shopping online. Researchers can

also find out what companies have done or will have to do to increase online traffic.

For Students:

This study would help students of Marketing Management in studying the perception of

customers about online shopping. The study would act as a guide for them in further study.

Particularly for students who wish to build their career in this field this study would be of interest

to them.

46

References

http://analogik.com/article_analysis_of_consumer_behaviour_online.asp

http://www.essays.se/essay/e1fb0c636f/

http://www.tealeaf.com/Harris/

http://inderscience.metapress.com/app/home/contribution.asp?

referrer=parent&backto=issue,2,6;journal,15,40;linkingpublicationresults,1:110844,1

http://www.iamai.in/Upload/Research/book.pdf

Anders Hasslinger, et al, “Consumer Behaviour in Online Shopping,” Kristiand

University Department of Business Studies,2008

Rajasee Rege, “What influences online shopping behavior of consumers? Usability vs.

Security perspective,” Indiana University, Bloomington, School of Informatics, 2007

Efthymios Constantinides,” Influencing the online consumer’s behavior: the Web

experience,” Internet Research Volume 14 · Number 2 · 2004 · 111-126

Bellman et al., “The relationship among demographics, personal characteristics, and

attitudes towards online shopping,” Journal Of Consumer Marketing, 1999

Scott M. Smith et al., “Online shopping in context of Diffusion of Innovation theory,”

Internet Research , 2008

Bikramjit Rishi, “Study on Online shopping,” International Journal of Electronic

Commerce, 2010

47

http://www.iamai.in/Upload/Research/book.pdf

http://inderscience.metapress.com/app/home/contribution.asp?referrer=parent&backto=issue,2,6;journal,15,40;linkingpublicationresults,1:110844,1

http://inderscience.metapress.com/app/home/contribution.asp?referrer=parent&backto=issue,2,6;journal,15,40;linkingpublicationresults,1:110844,1

apurva final mrp

Documents

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internet users

existing online customers

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growing use of internet

number of internet user

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