Dissertation Report

On

CONSUMER PERCEPTION ON ONLINE SHOPPING

By

SHIKHAMBA-IV sem0903870045

Under the Supervision ofProf. Neha P. Shrotiya

ITS, Mohan NagarGhaziabad

In Partial Fulfillment of Award of Master of Business Administration

1

DECLARATION

I, Gurmeet Singh student of Masters of Business Administration from Amity Business

School, Amity University Uttar Pradesh hereby declare that I have completed Dissertation on “

STUDY OF CHANGING ATTITUDE OF INDIAN CONSUMERS TOWARDS ONLINE SHOPPING

” as part of the course requirement.

I further declare that the information presented in this project is true and original to the best of my

knowledge.

24/03/09 Gurmeet Singh

Noida A0101907148

MBA (G) 2007-09

2

CERTIFICATE

I Ms.Rushina Singhi hereby certify that Gurmeet Singh, student of Masters of Business Administration

at Amity Business School, Amity University Uttar Pradesh has completed dissertation on “Study of

changing attitude of Indian consumers towards

online shopping”, under my guidance.

This Dissertation is prepared in partial fulfillment of Master of Business Administration to be awarded

by Amity University, Uttar Pradesh.

To the best of my knowledge, this piece of work is original and no part of this report has been

submitted to any other Institute/University earlier.

Date Ms.Rushina Singhi

Lecturer

Amity Business School

Amity University

3

ACKNOWLEDGEMENT

I express my sincere gratitude to my Dissertation Guide, Ms. Rushina Singhi for his constant

support and guidance. Without his help and cooperation, this project would not have been

successfully completed

I owe my enormous intellectual debt towards my guide, who have augmented my knowledge

in the field of Marketing

I thank all the respondents, without whose cooperation, the project would not have been

successful.

I am also indebted to my parents and friends for their direct or indirect support and

cooperation.

Gurmeet Singh

A0101907148

MBA (G)

BATCH OF 2009

4

ABSTRACT

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, and then they can further develop their marketing

strategies to convert potential customers into active ones, while retaining existent online

customers. This project is a part of study, and focuses on factors which online Indian buyers keep

in mind while shopping online.

This research found that information, perceived usefulness; ease of use; perceived enjoyment and

security/privacy are the five dominant factors, which influence consumer perceptions of online

purchasing.

A model was developed indicating online shopping behavior and acceptance among customers in

India. The model was tested with a survey sample (n=150). Factor analysis technique in SPSS

was used to classify these factors which buyers keep in mind while shopping online.

5

CHAPTER -1

INTRODUCTION

Internet is changing the way consumers shop and buys 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 feed back and also to

conduct satisfaction surveys with customers.

Customers use 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. Many experts are optimistic about the prospect of online business.

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. Scholars

and practitioners of electronic commerce constantly strive to gain an improved insight into

consumer behavior in cyberspace. Along with the development of E-retailing, researchers

continue to explain E-consumers’ behavior from different perspectives. Many of their studies

6

have posited new emergent factors or assumptions that are based on the traditional models of

consumer behavior, and then examine their validity in the Internet context.

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.

If we observe the growth of Indian online transactions (Info by: IAMAI), it 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 is also getting tested in Bangalore and other cities in India. This will increase the usage

as it goes more on wireless internet.

Indians are proving every 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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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.

.

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.

8

Inline 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 2008 and it is expected to rise above $700 million by end March 2010.

Indians are also Shopaholics like other Asians. There is a strong booming young adult

population in India with good levels of disposable income.

IN INDIA

- Over $50 Billion and growing rapidly - Most popular online shopping products include: books

(45%), electronic gadgets (42%), railway tickets (38%), accessories apparel (35%), apparel

(35%), gifts (34%), computer and peripherals (32%), airline tickets (28%), music downloads

(21%), movie downloads (21%), hotel rooms (22%), magazines (18%), tools (16%), home

appliances (16%), toys (16%), jewelry (17%), movie ticket (15%), beauty products (12%), health

and fitness products (12%), apparel gift certificates( 11%) and sporting goods (7%). 

There are over 120 million people online in India and this is expected to grow to 200 Million by

the end of 2010

.

CHAPTER-29

LITERATURE REVIEW

The current literature on consumer online purchasing decisions has mainly concentrated on

identifying the factors which affect the willingness of consumers to engage in Internet shopping.

In the domain of consumer behavior research, there are general models of buying behavior that

depict the process which consumers use in making a purchase decision. These models are very

important to marketers as they have the ability to explain and predict consumers’ purchase

behavior.

The classic consumer purchasing decision-making theory can be characterized as a continuum

extending from routine problem-solving behaviors, through to limited problem-solving behaviors

and then towards extensive problem-solving behaviors [Schiff man et al., 2001].

The traditional framework for analysis of the buyer decision process is a five-step model. Given

the model, the consumer progresses firstly from a state of felt deprivation (problem recognition),

to the search for information on problem solutions. The information gathered provides the basis

for the evaluation of alternatives. Finally, post-purchase behavior is critical in the marketing

perspective, as it eventually affects consumers’ perception of satisfaction/dissatisfaction with the

product/service.

This classic five stage model comprises the essence of consumer behavior under most contexts.

Nevertheless, the management of marketing issues at each stage in the virtual environment has to

be resolved by individual E-marketers. Peterson et al. [1997] commented that it is an early stage

in Internet development in terms of building an appropriate dedicated model of consumer buying

10

behavior. Decision sequences will be influenced by the starting point of the consumer, the

relevant market structures and the characteristics of the product in question. Consumers' attitude

towards online shopping is a prominent factor affecting actual buying behavior. Source:

Jarvenpaa Journal of Electronic Commerce Research, VOL. 6, and NO.2, 2005

Todd [1997] proposed a model of attitudes and shopping intention towards Internet shopping in

general. The model included several indicators, belonging to four major categories; the value of

the product, the shopping experience, the quality of service offered by the website and the risk

perceptions of Internet retail shopping. In the research conducted by Vellido et al. [2000], nine

factors associated with users' perception of online shopping were extracted. Among those factors

the risk perception of users was demonstrated to be the main discriminator between people

buying online and people not buying online.

Other discriminating factors were; control over, and convenience of, the shopping process,

affordability of merchandise, customer service and ease of use of the shopping site. In another

study, Jarvenpaa et al. [2000] tested a model of consumer attitude towards specific webbase

stores, in which perceptions of the store's reputation and size were assumed to affect consumer

trust of the retailer. The level of trust was positively related to the attitude toward the store, and

inversely related to the perception of the risks involved in buying from that store. Jarvenpaa et al.

[2000] concluded that the attitude and the risk perception affected the consumer's intention to

buy from the store.

Consumer risk perceptions and concerns regarding online shopping are mainly related to aspects

involving the privacy and security of personal information, the security of online transaction

11

systems and the uncertainty of product quality. Trust is interwoven with risk [McAllister, 1995].

One of the consequences of trust is that it reduces the consumer’s perception of risk associated

with opportunistic behavior by the seller [Ganesan, 1994]. Lack of trust is frequently reported as

the reason for consumers not purchasing from Internet shops, as trust is regarded as an important

factor under conditions of uncertainty and risk in traditional theories.

Mayer et al. [1995] developed a model which combines traditional marketing philosophy on

consumer motivation to buy and the trust model. In this model, trust propensity; which is a

personality trait possessed by buyers; is an important antecedent of trust. In Internet shopping,

there is not much information available to the buyer regarding the seller, prior to purchase. A

buyer with a high propensity to trust will more likely be a potential customer than a buyer with a

lower propensity. Mayer et al. [1995] proposed that ability, benevolence and integrity constitute

the main elements of trustworthiness. Ability refers to skills, competencies and characteristics

that a seller has in a specific domain. In this context, sellers need to convince buyers of the

competence of their companies in the Internet shopping business. Benevolence is the extent to

which the seller is perceived by the buyer as wanting to ‘do well’. Sellers have to convince

buyers that they genuinely want to do good things for buyers, rather than just maximize profit.

12

13

CHAPTER-3

Project Profile

Problem Definition

Online selling can be a very effective tool for a marketer to reach his customers. But at present

the marketer does not know the attitude of consumers towards online shopping and what are the

factors that shape the consumer’s attitude towards online shopping. Also what are key concerns

from the point of view of consumer while online shopping? If the marketer gets to know these

factors, then he really can use internet in the most effective manner to market his products. So

this study makes attempts to solve this problem.

Objectives of the Study

The objective of this study is to synthesize the representative existing literature on consumer

online shopping attitudes and behavior based on an analytical literature review. In doing so, this

study attempts to provide a comprehensive picture of the status of this subfield and point out

limitations and areas for future research.

The purpose of this research study is to investigate online consumer behavior, which in turn

provides E-marketers with a constructional framework for fine-tuning their E-businesses’

strategies. The specific objectives of this research are:

1. To identify key factors influencing online shopping purchase behavior.

14

2. To identify the factors that can explain the differences in online buying behavior among

different online buyers.

3. To study the consumer’s attitude towards mobile advertising

Scope of the Study

1. The Study was conducted among the Internet users.

2. The Geographical area covered was Sec-18 Noida, Sec-29 Noida, Cannaught place, Karol

Baugh, Delhi.

3. The Study was based on a Schedule of Questions.

Rationale of Study

Selling on internet has a large potential due to the very high targeting possibilities As a result of

this exceptional development, the online selling industry is becoming interested in the use of

internet to reach their customers. Hence a better understanding of online shopping is critical to

the effective use of this channel of approach to the consumer. It is especially important to know

what is the consumers’ attitude towards online shopping, benefits perceived by them and what

factors attract them towards online shopping.

15

16

CHAPTER -4

Research Methodology

Phase 1: Problem definition:

Online selling can be a very effective tool for a marketer to reach his customers. But at present

the marketer does not know the attitude of consumers towards online shopping and what are the

factors which shape the consumer’s attitude towards online shopping. Also what are key

concerns from the point of view of consumer while online shopping? If the marketer gets to

know these factors, then he really can use internet in the most effective manner to market his

products. So this study makes attempts to solve this problem.

Phase 2: Determination of information needs and sources:

The following was the information required:

What is consumer’s attitude towards online shopping?

What are the key concern areas for consumers while online shopping?

Which factors shape the consumer’s attitude towards online shopping?

How has been recent shift taking place in online shopping?

Phase 3: Research Framework:

Eleven different factors were identified by studying the existing models of consumer

attitudes(Refer Annexure3,4 & 5 ) that play an important role in online purchase, then a model

was proposed leading to online shopping.

17

The data was collected only through Questionnaires. The sample size was 150. And random

sampling was done among the internet users. The analysis of the data was carried out using SPSS

software and the various tools used were Cross Tabs, and Factor analysis,

PROPOSED MODEL

After examining the 10 empirical studies, we identify a total of eleven interrelated factors for

which the empirical evidences show significant relationships. These ten factors are perceived

usefulness, perceived ease of use, perceived enjoyment, information on online shopping, security

and privacy, quality of internet connection, attitude towards online shopping, intention to shop

online, online shopping decision making, online purchasing, and consumer satisfaction.

Six (perceived usefulness, perceived ease of use, perceived enjoyment, information on online

shopping, security and privacy, quality of internet connection )are found to be ordinarily

independent and five (attitude toward online shopping, intention to shop online, decision making,

online purchasing, and consumer satisfaction) are ordinarily dependent variables.

Consumer satisfaction is considered to be a separate factor in this study. It can occur at all

possible stages depending on consumer’s involvement during the online shopping process. The

relationships between satisfaction, attitude, intention, decision making and online purchasing are

proposed to be two-way relationships due to the reciprocal influences of each on the other. In

addition, three of the antecedents, perceived usefulness, perceived ease of use, perceived

enjoyment , have been found to have direct impact on consumer satisfaction.

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Perceived Usefulness

Perceived usefulness is defined as the degree to which a person believes that using a particular

system would increase his or her job performance. It is an important factor affecting acceptance

of an information system, because the ultimate aim of any person is the superior job

performance.

Perceived Ease of Use

This is an important factor that affects the acceptance of a particular information system. It is

defined as the degree to which a person believes that using a particular information system

would be free of effort. Hence an application perceived to be easier to use would more likely be

accepted by the user.

Perceived Enjoyment

Enjoyment refers to the extent to which the activity of using a computer is perceived to be

enjoyable in its own rights. This is seen as an intrinsic source of motivation to use a particular

application.

Amount of Information

Amount of information is defined as the information which is available for the product which a

person wants to buy through online shopping. This factor eases the decision of the user to

19

actually buy the product or not, or which product to buy. This factor becomes even more

important in case of High Involvement product.

Security and Privacy

Security and privacy are the main factors which hinder the growth of online shopping. The user

is concerned about his ID and Password which can be stolen by persons with wrong intentions

and then misuse it. At the same time they are concerned that their personal information may be

sold to the third party which poses a serious threat to their privacy.

Quality of Internet Connection

Not only is the presence of internet connection necessary but also its Quality is important to shop

online. This is an important factor which determines whether the user would shop online or not

because presence of internet is a basic necessity for this mode of shopping

Attitude towards online shopping

Consumer’s attitudes toward online shopping have gained a great deal of attention in the

empirical literature. It is believed that consumer attitudes will affect intention to shop online and

eventually whether a transaction is made. It refers to:-

1) The consumer’s acceptance of the Internet as a shopping channel

2) Consumer attitudes toward a specific Internet store (i.e., to what extent consumers think that

shopping at this store is appealing).

Intention to shop online

20

Consumer’s intention to shop online refers to their willingness to make purchases in an Internet

store. Commonly, this factor is measured by consumer’s willingness to buy and to return for

additional purchases. The latter also contributes to customer loyalty. Consumer’s intention to

shop online is positively associated with attitude towards Internet buying, and influences their

decision-making and purchasing behavior. In addition, there is evidence of reciprocal influence

between intention to shop online and customer satisfaction.

Online shopping decision making

Online shopping decision-making includes information seeking, comparison of alternatives, and

choice making. The results bearing on this factor directly influence consumer’s purchasing

behavior. In addition, there appears to be an impact on user’s satisfaction. Though it is important,

there are only five studies that include it.

According to Haubl and Trifts (2000), potential consumers appear to use a two-stage process in

reaching purchase decisions.

Initially, consumers typically screen a large set of products in order to identify a subset of

promising alternatives that appears to meet their needs. They then evaluate the subset in greater

depth, performing relative comparisons across products based on some desirable attributes and

make a purchase decision.

Online purchasing

This is the most substantial step in online shopping activities, with most empirical research using

measures of frequency (or number) of purchases and value of online purchases as measures of

online purchasing; other less commonly used measures are unplanned purchases

21

Online purchasing is reported to be strongly associated with the factors of personal

characteristics, vendor/service/product characteristics, website quality, attitudes toward online

shopping, intention to shop online, and decision making (Andrade 2000;

Bellman et al. 1999)

Consumer satisfaction

It can be defined as the extent to which consumer’s perceptions of the online shopping

experience confirm their expectations. Most consumers form expectations of the product, vendor,

service, and quality of the website that they patronize before engaging in online shopping

activities.

These expectations influence their attitudes and intentions to shop at a certain Internet store, and

consequently their decision-making processes and purchasing behavior. If expectations are met,

customers achieve a high degree of satisfaction, which influences their online shopping attitudes,

intentions, decisions, and purchasing activity positively. In contrast, dissatisfaction is negatively

associated with these four variables (Ho and Wu 1999; Jahng et al. 2001; Kim et al. 2001).

22

Phase 4: Sampling Design:

Sample Universe

The sample universe includes the people of NCR region.

Sample Size

The sample size of the participants was of 150 customers

Information on online shopping

Security & Privacy

Perceived Usefulness

Perceived Ease of use

Attitude towards online shopping

Intention to shop online

Decision Making

Online Purchase

CONSUMER SATISFACTION

Perceived Enjoyment

23

Phase 5: Data Collection:

A Survey method was undertaken to complete this project. For this Structured Questionnaire was

designed using various scaling techniques. The Questionnaire (shown in Annexure) was used

mainly to test the model proposed for Attitude towards online shopping. Likert five point scales

ranging from Strongly Agree to strongly disagree was used as a basis of Questions. The data

collection was done over a period of 8 weeks

This was done by going directly to the respondents or through mails.

24

CHAPTER-5

ANALYSIS

The Research was conducted by mode of questionnaire and respondents obtained following

results after analyzing the sample size of 150 questionnaires. The analysis was done using factor

analysis and cross tabs.

FACTOR ANALYSIS

1) FOR FACTORS AFFECTING ONLINE SHOPPING

Respondents were asked to rate the factors influencing online shopping purchase behavior. In all

six different factors were taken in questionnaire for getting the responses of consumers .Here are

those factors:

Information about online products and services

Perceived usefulness

Ease of use

Perceived enjoyment

Security

25

Quality of internet

Factor analysis was done using SPSS to extract the most important benefits derived by

customers’ point of view from the usage of online shopping.

RESULTS OF FACTOR ANALYSIS

KMO AND BARTLETT'S TEST

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy..667

Bartlett's Test of

Sphericity

Approx. Chi-

Square83.193

df 15

Sig. .000

26

Communalities

Initial Extraction

Information1.000 .572

Percieved

usefulness 1.000 .675

Ease of use1.000 .763

Percieved

enjoyment1.000 .812

Security1.000 .260

Quality of internet

connection1.000 .673

Extraction Method: Principal Component Analysis.

27

Total Variance Explained

Compo

nent

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total

% of

Varianc

e

Cumulat

ive % Total

% of

Varianc

e

Cumulat

ive % Total

% of

Varianc

e

Cumulat

ive %

1 2.571 42.853 42.853 2.571 42.853 42.853 2.417 40.276 40.276

2 1.184 19.732 72.584 1.184 19.732 72.584 1.338 22.308 72.584

3 .970 16.162 78.746

4 .695 11.592 90.338

5 .350 5.840 96.178

6 .229 3.822 100.000

Extraction Method: Principal Component Analysis.

Component Matrix (a)

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Component

1 2

Information.563 .505

Percieved

usefulness .797 .201

Ease of use.836 -.253

Percieved

enjoyment .886 -.166

Security.365 -.355

Quality of internet

connection.054 .819

Extraction Method: Principal Component Analysis.

a 2 components extracted.

29

Rotated Component Matrix(a)

Component

1 2

Information.362 .664

Percieved

usefulness .684 .456

Ease of use.873 .040

Percieved

enjoyment .890 .139

Security.463 -.213

Quality of internet

connection-.222 .790

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a Rotation converged in 3 iterations.

30

Component Transformation Matrix

Componen

t 1 2

1 .943 .334

2 -.334 .943

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Interpretation:

The value of KMO test is coming out to be 0.667, which suggests the validity for factor analysis.

The principal component analysis is giving 72.584 as commutative % which is good enough

because data redundancy is less. Two components have been extracted with Eigen values more

than 1 after principal component analysis and rotated component analysis.

The output value shows that following factors can be safely extracted after factor analysis:

Information about online products and services(Extracted from component 2)

Perceived usefulness (Extracted from component 1)

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Ease of use(Extracted from component 1)

Perceived enjoyment(Extracted from component 1)

2) FOR FACTORS CONCERNING ONLINE SHOPPING

Respondents were asked to rate the factors of concern for online shopping purchase behaviour.In all

six different factors were taken in questionnaire for getting the responses of consumers .Here are those

factors:

Not sure of product quality

Cannot bargain/negotiate

Not sure of security of transactions/credit card misuse

Need to touch and feel the product

Significant discounts are not there

Have to wait for delivery

32

Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared

Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total % of Variance Cumulative %

1 2.437 40.625 40.625 2.437 40.625 40.625 2.418 40.292 40.292

2 1.226 20.428 61.052 1.226 20.428 61.052 1.221 20.357 60.649

3 1.021 17.013 78.065 1.021 17.013 78.065 1.045 17.416 78.065

4 .809 13.491 91.556

5 .507 8.444 100.000

6 -2.182E-

16-3.636E-15 100.000

Extraction Method: Principal Component

Analysis.

RESULTS OF FACTOR ANALYSIS

33

Component Matrixa

Component

1 2 3

not sure of product quality .964 -.004 .055

cannot bargain/negotiate -.161 -.721 .235

not sure of security of

transactions/credit card mis use.964 -.004 .055

need to touch and feel the

product.145 .211 .933

significant discounts are not

there-.024 .796 -.092

have to wait for delivery .728 -.165 -.284

Extraction Method: Principal Component Analysis.

a. 3 components extracted.

34

Rotated Component Matrixa

Component

1 2 3

not sure of product quality .953 .050 .152

cannot bargain/negotiate-.115

-.765.059

not sure of security of

transactions/credit card mis use.953 .050 .152

need to touch and feel the

product.046 .010 .966

significant discounts are not

there-.087 .793 .077

have to wait for delivery .762 -.048 -.236

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 4 iterations.

35

Component Transformation Matrix

Compon

ent 1 2 3

1 .992 .069 .103

2 -.089 .973 .213

3 -.085 -.220 .972

Extraction Method: Principal Component

Analysis.

Rotation Method: Varimax with Kaiser

Normalization.

36

Interpretation:

The principal component analysis is giving 78.065 as commutative % which is good enough

because data redundancy is less.

Three components have been extracted with eigen values more than 1 after principal component

analysis and rotated component analysis.

The output value shows that following factors can be safely extracted after factor analysis:

Not sure of product quality (Extracted from component 1)

Transactions/credit card misuse (Extracted from component 1)

Have to wait for delivery (Extracted from component 1)

Significant discounts are not there (Extracted from component 2)

37

CROSS TABS

1) BETWEEN TIME OF LAST PURCHASE AND METHOD OF PAYMENT

Interpretation:

The most common method of payment is by debit card/credit card for the purchase over internet

irrespective of the time of purchase of internet. Second most common method is cash on

delivery.

38

2) BETWEEN TIME OF LAST PURCHASE AND DECISION FACTOR FOR

SELECTING SITE FOR SHOPPING ONLINE

39

Interpretation:

The most common factor for making decision for online purchase is through information by

search engine. Also when people come across any special offer that helps in decision making for

online purchase.

3) BETWEEN TIME OF LAST PURCHASE AND AGE GROUP

40

Interpretation:

People below the age group of 40 are more actively involved in online shopping. That means

youngsters are getting attracted towards concept of online shopping.

4) BETWEEN TIME OF LAST PURCHASE AND MONTHLY INCOME

41

Interpretation:

People earning between Rs. 20,000-50,000 is more keen towards online shopping. This explains

the fact why online shopping is becoming popular amongst younger workforce earning between

20k-50k.

42

LIMITATIONS OF THIS STUDY

Limitation of the study is the selection of the existing studies. Owing to time limitation, only a

few number of journals were searched. This may leave some other prominent empirical studies

out. In addition, owing to the multidisciplinary nature of online shopping, it would be very

interesting to compare IS literature to other disciplines that study online shopping attitudes and

behavior.

IMPLICATIONS AND RECOMMENDATIONS FOR FUTURE

RESEARCH

As the proposed model indicates, three out of the five dependent variables (consumer attitudes,

intentions, and purchasing behavior) and three out of the five independent variables (perceived

usefulness, perceived ease of use, perceived enjoyment, information on online shopping, security

and privacy, quality of internet connection) receive the most attention. This seems to constitute

the main stream of research in this area. It is found that personal characteristics such as

vender/service/product characteristics and website quality significantly affect online shopping

attitudes, intention, and behavior.

The role of the external environment, demographics, online shopping decision making, and

consumer satisfaction are less well represented in the proposed model.. Any number of factors,

including vender/service/product characteristics, website quality, attitude towards online

shopping, intention to online shopping, online shopping decision making, and online purchasing,

may influence consumer’s satisfaction. More importantly, the extent to which customers are

43

satisfied is directly related to attitudes toward online shopping or toward specific Internet stores.

The relative importance of this factor in determining such consumer behavior as repeat purchases

suggests that further research on consumer satisfaction with online shopping needs to be

conducted.

GENERAL DISCUSSIONS

CHANGING ATTITUDE TOWARDS ONLINE SHOPPING:

Malls malls springing up everywhere and yet people are e-shopping! And not in small numbers

either. E-commerce figures are going through the roof, according to Assocham (Associated

Chambers of Commerce & Industry of India). Today (2008-09) the figures are touching Rs. 2200

crore, but are expected to increase by 150 percent by 2009-10 - to Rs 5,500 crores! And two

metros - Delhi and Mumbai are driving the growth:

LOGGING ONTO E-SALES

CITY Share in 08-09 Projection for 09-10

Mumbai 24% 40%

Delhi 20% 30%

44

Chennai 7% 11-12%

Kolkata 7% 10-11%

Bangalore 6% 9%

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?

Well, Assocham says that books are the hottest selling item on the internet. In fact most products

bought and sold off online are: books, electronic gadgets and railway tickets. However, people

are also buying clothes; gifts, computer and peripherals, and a few are buying home tools and

products, home appliances, toys, jewelry, beauty products and health and fitness products.

Traffic for e-commerce sites is mostly coming from the two metros of Delhi and Mumbai.

Here are few reasons for this:

1. Convenience

It is the major reason. Both the cities are spread out over a large area and the best stores in

both these cities are often concentrated in certain ‘posh’ areas. In Mumbai for example

there are certain items you get only in Crawford market which is at the other end of town in

South Mumbai. And demographics show that the population of Mumbai is now

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concentrated in the suburbs. Of course, huge malls have come up in the suburbs as well,

and India’s biggest mall Nirmal Lifestyle is in far-flung Mulund but often you find a better

choice of sizes and styles choice in other malls, say Phoenix (central Mumbai). And though

both Mumbai and Delhi have transport system, few people like to travel for two hours just

to get to a shop at the other end of town. Clearly the transport systems leave much to be

desired. In Delhi, safety is also an issue for women traveling alone in the evenings.

2. Literacy Rate and the Cities’ Internet Savvy Population

Most cities in India have a higher literacy rate as compared to the national average of 64.8

percent. In fact Mumbai has a highest literacy even amongst the cities (86 per cent). Delhi

too has a high literate population (81.2 per cent). Oddly, although Bangalore has a higher

literacy rate than Delhi, at 83 per cent, the city’s share of e-commerce is not very high.

Kolkatta too has a literacy rate (80.8 per cent) and so does Chennai (80.1 percent.) If one

compares these rates to literacy rates of cities like Patna (62.9 percent), Jaipur (67 percent),

Indore (72 percent) or Warangal (73 percent) its clear why its the metros which are going

to continue to lead e-shopping.

3 .Home delivery concept

In any case, home delivery is a concept that Indians are familiar with and love. The mall craze

has started only now. Earlier it was a choice between sweating it out in small crowded markets,

or asking a friendly neighbourhood kirana (grocer) to deliver groceries home and this system is

still thriving.

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4. Increase in the Internet users

Increasing penetration of Internet connectivity and PCs has led to an increase in the

Internet users across India. The demographic segments that have witnessed maximum

growth comprise college going students and young persons. These segments are the users

of advanced applications and technologies online and are most likely to be heavy E-

Commerce users.

5. Increase in the number of buyers and sellers

The success of a marketplace depends on the presence of a large number of buyers and a

large number of sellers. In addition to online buyers, many offline stores have begun to sell

their products in the online marketplace. The greater the number of sellers and buyers, the

faster the market grows.

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PRODUCT PREFERENCES CITY WISE

Bangalore loves to buy books, electronic gadgets, computer peripherals, gifts movies,

bookings, actually just about everything.

Well, Kolkatta prefers to buy music and movies online

Mumbai leads in all categories, except jewellery.

Delhites seem to prefer buying jewellery online as compared to any other city

Indian E-Comm. Report Finds Heavy Spenders Driving Sales

By Devin Comiskey

August 16, 2008

A Survey by Indian research organization Juxtconsult found that more and more Indian Internet

users are opening their wallets online. While such hurdles as limited broadband access and

security concerns remain, the report finds there are currently more than 10 million shoppers

online in India. While current trends point to increased e-commerce growth in India, the online

marketplace in the country of more than 1 billion people is still relatively small.

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Juxtconsult's survey found that 40 percent of all urban Internet users buy online, while 42

percent of the sales originate through just five percent of consumers. The survey was conducted

in April 2008and sampled more than 30,000 users.

"This section of buyers spends 5,000 rupees or more per month on the net," states the report. "It

is interesting to note that two out of every three heavy spenders are also 'netholics,' those who are

on the net for more than three hours per day...Of all those who buy online, only 25 percent are

spending more than 1,000 rupees per month while the (remaining) 75 percent bill less than 1,000

rupees per month." (1,000 Indian rupees is currently equal to approximately $23 US.)

The report also found that buying and search patterns among Indians differ between genders.

"While 43 percent of male users buy online, only 31 percent of urban female users are consumers

as well. Women tend to search more. Defying their more common attitude towards shopping,

women are more guarded when it comes to the online market," says Juxtconsult.

"Depending on the product type, nine percent to 25 percent are buying online, whereas 33 to 47

percent are searching the net for product information," it says.

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SECURITY FEARS PERSIST

Juxtconsult says the motivation for Indian users to make purchases online varies, but users fear

compromised personal information is still a great risk when it comes to e-commerce.

"The single biggest motivation for buying online for net users is saving time. Thirty-two percent

of them look to shop online with this purpose. Convenience of shopping '24x7' and home

delivery are other major incentives," says the report. "However, the concern of possible misuse

of credit car or personal information is extremely significant among online buyers, with almost

55 percent of them voicing their concern. Clearly, tackling and countering the issue of online

safety figures as an imminent challenge for net marketers."

Books, CDs Top the List

The products that are purchased most online in India, according to Juxtconsult, are books and

CDs - making up 25 percent of all online purchases.

"Ironically, computer hardware and software, despite having the home advantage are among one

of the least bought products online, with only 13 percent buying them," says the report.

"In sum, the online market in India is blossoming but is yet to take off in a considerable way.

The Internet is still being used more for searching than buying products and services. Though a

noticeable proportion of net users are also net consumers, essentially, at present only a small

tribe among them is driving online shopping momentum," says Juxtconsult.

LATEST

A new trend in this space is that of Meta search engines. Ixigo and Ezeego are two

players in this space. A Meta search engine searches all the online travel sites (including

the airlines sites as well) and displays the best deals for the user.

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Travel websites, such as Make My Trip India Pvt. Ltd and Yatra Online Pvt. Ltd, are

battling to win over India’s Rs16,000 crore ($400 million) religious travel market

Opportunity in Online Travel Industry: $2billion

Online travel company MakeMyTrip (MMT) has recorded sales of Rs. 1000 crore for the

financial year ending March 2008, as per a release.

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CHAPTER-6

CONCLUSION & SUGGESTIONS

CONCLUSION:

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

savviness see more and more Indians shopping online. .

BARRIERS TO GROWTH OF ONLINE MARKET

Consumer Bias

Consumers often display a bias for brands that they know well and have had a good experience

in the past. Thus products of brands with a favorable bias will score over the products of less

popular brands. A few would risk buying expensive jewelry from an unknown jeweler online.

Lack of ‘Touch –Feel-Try’ Experience

The customer is not sure of the quality of the product unless it is delivered to him and post

delivery of the product, it is sometimes a lengthy process to get a faulty or the unsuitable product

changed. Thus, unless the deliverables are as per the customers expectations, it is hard to infuse

more credibility in the e-Tailing market.

Mounting Competitive Pressures

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To attract customers, the competing online players are adopting all means to provide products

and services at the lowest prices. This has resulted in making the consumers choice-spoilt, who

in turn surf various websites to spot the lowest price for the product. Thus, although the number

of transactions is increasing, the value of the products sold is continuously falling owning to high

competition and leaner margins.

Seasonality

E-Tailing Market is faced by seasonal fluctuations. As told by an Industry player, “August to

February is the peak seasons for sale, while March to July is the dry seasons for sale”. During the

peak season, occasions that drive the sales are Diwali, Rakhi, Valentines Day, New Year,

Christmas, Mother’s Day, Friendship Day etc are. On these occasions younger generations

prefers buying and sending gifts online.

Credibility in Payment System

Online frauds and breach are the biggest barriers to online sales. As a result, prospective buyers

prefer staying away from revealing their credit card and bank details.

Untimely Delivery of Products

It might take a few minutes to search, book and pay for products and services online, but the

delivery of the product may take unreasonable time.

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.

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RECOMMENDATIONS:

The companies need to reduce the risks related to consumer incompetence by tactics such as

making purchase websites easier to navigate, and introducing Internet kiosks, 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.

REFERENCES

Consumer online shopping attitudes and behavior: an assessment of research ,by: Na Li

and Ping Zhang ,Syracuse University

Consumer attitudes toward shopping venues affect marketing strategies .By Susan

McGinley

The State of E-Commerce: Online Shopping Trends,By James Maguire

Journal of Electronic Commerce Research, VOL. 6, NO.2, 2005

Research report by IMNAI & Pinstrom

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Research report By: Thijs L. J. Broekhuizen ,University of Groningen, The Netherlands

Framework for consumers’ intentions to shop online, research by Emerald

Research report By: IAMAI

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ANNEXURE 1

Questionnaire

1. Have you ever made a purchase over the Internet? a. Yes b. No

2. When was the last time you made a purchase over the Internet?

a. One month ago b. Two months ago c. More than two months ago

3. In the past 3 months what items have you purchased on the Internet?

a. Books b. Videos / DVDs / Games

c. Airline Tickets / Reservations d. Clothing / Accessories / Shoes

e. Music f. Electronic Equipment

g. Computer Hardware h. Tours / Hotel Reservations

i. Event Tickets j. Computer software

k. Cosmetics / Nutrition Supplies l. Groceries

m. Sporting Goods n. other items

4. Which method (or methods) of payment did you use to make your last purchases over the

Internet in the past 3 months?

a. Credit /Debit Card b. Bank Transfer c. Cash on Delivery

d. Money Transfer e. Other Method

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5. What helps you decide which site to use for shopping online?

a. Search engine b. Personal recommendation c. Special offer I saw

d. Online Advertising e. Same store I buy from offline

f. TV/print or other advertising

6. Do you have enough information about online products and services?

Totally disagree Totally agree

7. Online shopping is useful:

Totally disagree Totally agree

8. Online shopping is easy to do:

Totally disagree Totally agree

9. Online shopping is enjoyable:

Totally disagree Totally agree

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10. Online shopping is secure:

Totally disagree Totally agree

11. Quality of internet connection is good:

Totally disagree Totally agree

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12. For each of the following, please tell if these concern you when you are making a

purchase over the Internet.

Great deal Fair amount A little Not at all

a) Not sure of product quality

b) Cannot bargain/Negotiate

c) Not sure of security of transactions

/Credit card misuse

d) Need to touch and feel the product

e) Significant discounts are not there

f) Have to wait for delivery

NAME:

AGE: below 23 yrs

23 yrs- 40 yrs

40 yrs-55yrs

55yrs and above

GENDER: Male/ Female

MONTHLY INCOME: below Rs. 20,000

Rs. 20,000-50,000

Rs. 50,000 and above

CONTACT NO:

EMAIL ID:

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ANNEXURE:2

Different models of consumer attitude towards online shopping

By:Mary Ann Eastlick

This chart shows how consumer attitude toward online shopping can lead either to approach

coping (wanting to shop online) or to avoidance coping (deciding not to search or shop online).

Someone who is optimistic toward the benefits of online shopping will develop approach coping.

A person who is pessimistic toward online shopping will think of the drawbacks to it and decide

to purchase in physical stores instead, which is avoidance coping.

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ANNEXURE:3

FRAMEWORK FOR CONSUMERS’ INTENTIONS TO SHOP ONLINE

Source: research by Emerald

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ANNEXURE:4

By: Thijs L. J. Broekhuizen

University of Groningen, The Netherlands

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ANNEXURE:5

Marketing Trends in India Online Travel Industry

Searches by Indians every month Over 1 billion

Searches by Indians that result in sponsored links shown,

every month

308 million

Total clicks on sponsored links by Indian users in a month Over 4.8 million

Number of advertisers targeting Indians web-users Over 40,000

Total annualized spend by all advertisers targeting Indian

users

Rs.236 crores (US $ 52 m)

Total annualized spend by Indian advertisers targeting Indian

users

Rs.72 crores (US $ 16 m)

Most amount spent by one advertiser Rs.9.7 crores (US $ 2.2 m)

All brands that spend more than Rs.10 lakhs a year in India 291

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Indian brands that spend more than Rs.10 lakhs a year in

India

90

Average number of key words bought by a brand 42

Most key words bought by a brand 89,377

Most clicks bought by a brand in a month 599,968

Average cost per click paid by advertiser in India Rs.16.20 ($ 0.36)

Highest cost per click paid by advertiser in India Rs.266 ($ 5.92)

Average search campaign click-through rate 0.62%

ANNEXURE:6

Top Online Travel Industry using Search Engine Marketing and their annual spend in

Rupees.

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Keywords Portfolio: Online Travel India Firms

Source: IMNAI & Pinstrom

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.

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