project final report document

8/8/2019 Project Final Report Document

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CHAPTER 1

INTRODUCTION

1.1 INTRODUCTION TO INTERNET ADVERTISING

The Internet as a marketing medium offers many unique challenges to

marketers. To assist marketers in their venture on-line, comparisons and contrasts

to existing marketing theory have been used to build a conceptual understanding of

the current state of the Internet and its implications for consumer transactions. To

further understand the commercial possibilities of the Internet, several internet

usage surveys have been conducted to document consumers behavior online. Yet,

in terms of assessing the commercial effectiveness of the Internet and the value of

Internet advertising, most research has concentrated upon the companys rather

than consumers point of view. As a result, many decisions regarding Internet

advertising (IA) are being made with relatively little specific knowledge about

consumers attitudes toward IA and how the structure of these IA attitudes compare

to the structure of attitudes toward advertising in traditional media. The aim of the

current research is to examine consumers perceptions and judgments of IA.

Consumers attitudes toward advertising have been considered important to

track because they likely influence consumers exposure, attention, and reaction to

individual ads through a variety of cognitive and affective processes. One

fundamental difference between Internet and traditional advertising is the degree to

which the consumer versus the company has control over advertising exposure.

With traditional advertising, consumers play a relatively inactive role in exposure.

Advertisements interrupt or intercept consumers attention to other information

(e.g., a television program, a radio show, or traffic signs). In essence,

advertisements are pushed at them. With many forms of IA, however, the

consumer has a great deal of control over advertising exposure. The company may

request the consumers attention (e.g., through banner ads on others Web sites or

through hyperlinks), but it is up to the consumer to seek additional commercial

content. Consumers can select whether, when, and how much commercial content

they wish to view. That is, consumers pull for electronic advertising content.


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Because IA exposure is largely under the consumers volition, it is particularly

important to understand the valence and structure of one important driver of

advertising exposure: attitudes toward IA.

1.2 NEED FOR THE STUDY

Understanding consumer behavior and knowing customers are never simple.

Customers may say one thing but do another. They may not be in touch with their

deeper motivation. They may respond to influences that change their mind at the

last minute. The major propose of this study to understand the key influencing

factors and impact level of internet advertising on buyers buying decisions.

1.3 OBJECTIVE OF THE STUDY

The primary objective of the study to find out how much impact is really the internet

Advertising having on individual buying behaviours.

The other objectives are

To understand the Internet Users Attitude towards Internet advertising.

To understand Internet Ads dimensions underlie in Internet Advertising.

To understand level of implication of Internet Ads towards Internet Users

attitude.

1.4 SCOPE OF STUDY

Many have speculated about the current state of Internet advertising, how it

compares to advertising in general, and its implications for traditional marketing

models and practices. Although many estimates exist regarding who uses the

Internet as well as guidelines about how best to design IA, little is known about

Internet users attitudes toward IA, much less what characterizes these attitudes. To

test this, a l sample of over 200 participants with at least some exposure to the

Internet was surveyed. The results revealed no majority opinion of IA: approximately

a third of respondents liked, disliked, and felt neutrally toward IA, respectively. A

regression analysis indicated that enjoyment of looking at Internet advertisements,

its informativeness, and its utility for making behavioral (purchasing) decisions.


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1.5 LIMITATION OF THE STUDY

The study is conducted only in select part of Chennai and hence may not be

entirely representative of the entire population of the Chennai.

Thetotal sample size of 50 working peoples and 50 students are determined.Taking time and cost into consideration and no scientific method was used in

arriving at it.

CHAPTER 2

REVIEW OF LITERATURE

2.1 WHAT IS INTERNET ADVERTISING

According to consumers, IA includes many forms of commercial contentfromelectronic advertisements that are similar to traditional advertisements to formats

that are different from traditional advertisements, such as corporate Web sites.

Thus, it appears that there are idiosyncratic differences in consumers perceptions

of what constitutes IA such that any specific definition of IA is likely to be a bad fit

for measuring IA perceptions. Because the goal of the present research is to assess

consumer perceptions of IA, IA is described broadly as any form of commercial

content available on the Internet that is designed by businesses to inform

consumers about a product or service. Hence, IA can be delivered via any channel(e.g., video clip, print or audio), in any form (e.g., an e-mail message or an

interactive game), and provide information at any degree of depth (e.g., a corporate

logo or an official Web site).

2.2 BACKGROUND ON INTERNET ADVERTISING

Despite the limited understanding of how consumers judge IA, there has been

substantial commercial growth on the Internet of many forms of advertising, Inaddition to anticipating the monetary growth of the Internet, the majority of on-line

businesses believe the Internet is here to stay and will generate sales in the future.

Furthermore, the adoption curve for the Internet is quite steep, especially in

comparison to other media introduced in this century (radio, television, cable;

Morgan Stanley Technology research cited in Internet Advertising Bureau, 1997).


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Thus, as many have predicted, investment in IA is likely to escalate into the billions

as we enter the next millennium. Studies of consumers reactions to IA typically

have quantified customers judgments of Web sites in terms of consumers

behavioral traces at the site (i.e., counting the number of clicks and hits. These

measures have been shown to both overestimate and underestimate the number of

visitors and exposures, however. Moreover, the indirect nature of these methods

makes it difficult to ascertain the meaning behind the results (e.g., whether clicking

on a link were an accident or intended behaviour and whether the loaded site

satisfied the consumers expectations). Coinciding with the growth in IA, there has

been a plethora of guidelines about how to best reach and persuade the consumer

market with the Internet. Many of these recommendations have been based upon

assumptions (rather than actual assessments) of how consumers react to Internet

Ads relative to General Ads. Relatively little is known about how consumers judge

Internet advertising and which components make up these attitudes.

2.3 ATTITUDES TOWARDS ADVERTISING IN GENERAL

The studies on advertising attitudes have varied widely in the types of samples used

and the data collection methods employed, they have focused upon many of the

same dimensions of judgment. Respondents typically have been asked not only

about their overall attitudes toward advertisements but also their perceptions of

advertisings trustworthiness, offensiveness, informativeness, entertainment value,

and effect on product prices and value, as well as attitudes toward regulatory

issues.

Early surveys of advertising attitudes yielded somewhat favorable, albeit mixed,

results. Found that a majority of their respondents generally liked advertising and

that most of those respondents liked it because they felt it was informative. They

also found that a majority of respondents preferred advertised products over

unadvertised products, although most also felt that advertising increased the cost of

things they buy. People held favorable attitudes toward advertising than

unfavorable attitudes and that a majority of respondents felt advertising was

essential. Still, a majority of their respondents felt that advertisements were


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misleading and that they resulted in higher prices and argued that, beginning in the

1970s, attitudes toward advertising were becoming increasingly negative

2.4 CONSUMER RESPONSE TO INTERNET ADVERTISING

Most of the direct-response measures administered to consumers have assessed

consumers perceptions and usage of the Internet and its services. Yet, relatively

less is known about consumers evaluations of IA specifically. In an important

exception assessed Internet users attitudes toward advertising on newsgroups and

through e-mail. Consumers held negative attitudes toward newsgroup and e-mail

advertising, even when the message was directly relevant to the special interests of

the group. However, their sample was limited to those who posted messages to the

group. Those who merely read messages were not included in the sample.

As a result, it is possible that these unfavorable attitudes are due to this vocal

samples perception that they are competing with electronic advertisements for the

groups attention. In addition, attitudes toward newsgroup/ e-mail advertising may

not generalize to all forms of IA, including less intrusive ads. Consequently, it is

unclear whether the results would generalize to the entire Internet populations

attitudes toward IA in its many forms. Web advertising to be generally informative

and entertaining, although more informative than entertaining.

For instance, because it is used primarily as an information- providing medium IA

might elicit attitudes that are mostly comprised of cognitive factorsespecially in

comparison with attitudes toward advertising in general. Such variations have

implications for how practitioners alter Internet ads (as opposed to traditional

advertising) in order to improve IA attitudes. Thus, one goal of the present research

is to determine which dimensions underlie and to what degree they explain variance

in attitudes toward IA.

2.5KEY FACTORS OF INTERNET ADVERTISING INFLUENCING THE CONSUMERBUYING DECESION

Online advertising facilitates the advertiser to reach an absolutely pinpointed

and targeted audience.


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Traditional advertising is usually a one-way mechanism there is no way for

customers to act on the information in the advertisements. On the Internet,

however, interested customers can click on a banner, learn more, and

actually make purchase on the spot.

The Internet as a medium knows no demographic boundaries and gives the

advertiser a huge audience to tap and build brand image if not sell products.

Internet's interactive nature allows for greater flexibility than traditional

media in the type of information transmitted and the method of transmission.

Online advertisement can facilitate purchase decision.

Enhance customer company relationship.

Protection of environment.

CHAPTER 3

METHODOLGY

3.1 Research Design:

Though the primary objective of the study is to understand how much impact is

really the internet having on individual buying behaviors. Exploratory research

design is applied to the study to portray the characteristics of a group or individual

as a situation. It includes surveys and fact finding enquiries of different kinds. The

purpose of exploratory research is description of the state of affairs as it exists at

present.

A sample design is a definite plan for obtaining a sample from a given

population. It refers to the

technique or the procedure would adopt in selecting items from the sample. Since

the population size is infinite sample size for the study was taken as 100

respondents in which 50 samples were of the working people and 50 samples were


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of the students. Population of study includes all the samples in and around Chennai

cities of Tamil Nadu.

3.2 Sources of Data Collection:

The study consists of the application of both primary and secondary data. Primary

data was collected by administering questionnaire cum interview schedules to

Working peoples and students. The secondary data was collected through websites

and from various journals and magazines.

3.3 Sampling Procedure:

The Sample Type used is Simple Random Sampling.

3.3.1 Simple random sampling

Simple random sampling is the technique in which sample is go drawn that

each and every unit in the population has an equal and independent chance of

being included in the sample. If the unit selected in any draw is not replace in the

population before making the next draw, then it is known as simple random

sampling without replacement and if it is replaced back before making the next

draw, then the sampling plan is called Simple random sampling, with replacement

and is amounts to sampling from an infinite population, even through the population

is finite.

3.3.2 Benefit of Simple random sampling

1. It gives each element in the population an equal probability of getting

into the sample; and all choices are independent of one another

2. It gives each possible combination of equal probability of being chosen.

3.4 Research Instrument:

A structured Questionnaire was prepared to extract the required data.

A Structured Questionnaire is chosen because it produces more reliable

results than the unstructured ones.


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3.5 Communication Method:

The data collection is by Direct interviewing.

This method is chosen because further explanation can be requested, if

desired.

3.6 Tools used for data interpretation

3.6.1 Average Method:

The average method is used for interpretation of data. The formula used

for this is,

No of favorable response

= ---------------------------------- X 100

Total no of respondents

3.6.2 Weight Average Method:

The term weight stands for the relative importance of the different items.

The formula for

computing weighted average is

Weighted average = Wi Xi N

Where,

Xi - represents the variable values.

Wi represents the weights attached to the variable values.

3.6.3 Chi-Square Test

The real world data of a system follow some distribution depending on thecharacteristic of the system. After collecting data from the system of interest, the

essential step is to fit the data to the nearest distribution, which represents the

data, more meaning fully for future analysis. Such fitting of data to the nearest

distribution is done using the goodness of fit test. The goodness of fit of a given set


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of data is performed using chi-square test. The combination of hypothesis for this

situation is

H0: The given data follow an assumed distribution

H1: The given data do not follow an assumed distribution

Chi Square Test formula:

Where

Aij = actual frequency in the i-th row, j-th column.

Eij = expected frequency in the i-th row, j-th column.

r = number or rows.

c = number of columns.

Degree of Frequency = (r 1)*(c 1)

Chapter 4

Data Analysis and Interpretation

4.1 DEMOGRAPHIC PROFILE OF THE RESPONDENTS:

Table No: 4.1.1


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Table Name: Respondents Age.

S.I No Age (In Yrs) No of Respondents Percentage

1 Below than 20 2 2 %

2 20 29 78 78 %3 30 39 16 16 %4 40 49 4 4 %5 Greater than 50 0 0 %

Total 100 100 %

Inference:

The above table shows that 78% of respondents are under the age group of 20-29,

16% of respondents are under 30-39, 4% of respondents are under 40-49, 2% of

respondents are under Below than 20 age group and 0% are under Greater than 50group.

Figure No: 4.1.1

Figure Name: Respondents Age.

Table No: 4.1.2Table Name: Respondents Gender.

S.I No Gender No of Respondents Percentage

1 Male 54 54 %

2 Female 46 46 %


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Total 100 100 %

Inference:

The above table shows that 54% of respondents are male and remaining 46% ofrespondents are female.

Figure No: 4.1.2

Figure Name: Respondents Gender.

Table No: 4.1.3

Table Name: Respondents Educational Background.

S.I No Educational BackgroundNo of

RespondentsPercentage

1 Secondary School 0 0 %

2 Bachelor Degree 36 36 %3 Master Degree 60 60 %


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4 Doctoral Degree 4 4 %5 Others 0 0 %

Total 100 100 %

Inference:

The above table shows that 60% of respondents are under Master Degree, 36 % of

respondents are under Bachelor Degree, 4% of respondents are under Doctoral

Degree and 0 % of respondents are under Secondary and Others Category.

Figure No: 4.1.3

Figure Name: Respondents Educational Background.

Table No: 4.1.4

Table Name: Respondents Profession.

S.I No Profession No ofRespondents

Percentage

1 Banking / Finance 12 12 %

2 Advertising / Marketing 8 8 %3 Computer / Electronics 68 68 %

4Manufacturing /

Production6 6 %


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5 Others 6 6 %Total 100 100 %

Inference:

The above table shows that 68% of respondents are under Computer / Electronics,

12 % of respondents are under Banking / Finance, 8% of respondents are under

Advertising / Marketing and 6 % of respondents are under Manufacturing /

Production and Others Category.

Figure No: 4.1.4

Figure Name: Respondents Profession

Table No: 4.1.5

Table Name: Respondents Income (Per Month).

S.I No

Income (Per

Month) No of Respondents Percentage

1Lesser than

1500036 36 %

2 15001 -25000 38 38 %3 25001 35000 12 12 %4 35001 45000 6 6 %5 45001 and Above 8 8 %


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Total 100 100 %

Inference:

The above table shows that 38% of respondents are under 15001 -25000, 36 % of

respondents are under Lesser than 15000, 12% of respondents are under 25001 35000, 8 % of respondents are under 45001 and Above and 6% of respondents are

under 35001 45000.

Figure No: 4.1.5

Figure Name: Respondents Income (Per Month)

4.2 HOW MUCH IMPACT IS REALLY THE INTERNET HAVING ON INDIVIDUAL

BUYING BEHAVIORS

Table No: 4.2.1

Table Name: Frequency of Transactions.

S.I NoFrequency of

Transactions

No of


1Lesser than once in

month20 20 %

2 1 2 times/month 20 20 %


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3 2 5 times/month 32 32 %4 6 9 times/month 16 16 %5 > 10 times/month 12 12 %

Total 100 100 %

Inference:The above table shows that 32% of respondents are under 2 5 times/month, 20 %

of respondents are under Lesser than once in month and 1 2 times/month, 16% of

respondents are under 6 9 times/month, 12 % of respondents are under > 10

times/month.

Figure No: 4.2.1

Figure Name: Frequency of Transactions.

Table No: 4.2.2

Table Name: Amount Spent.

S.I No Amount SpentNo of


1 Lesser than 1000 28 28 %

2 1001 10000 44 44 %3 10001 20000 12 12 %4 20001 30000 8 8 %


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Inference:

The above table shows that 28% of respondents are under E-banking services, 24 %

of respondents are under Household's Items & Books and Computer Equipment,

16% of respondents are under Food Items, 8 % of respondents are under

Automobile.

Figure No: 4.2.3

Figure Name: Product or Services Purchased.

4.3 INTERNET USERS ATTITUDE TOWARDS INTERNET ADVERTISING

4.3.1 ATTITUDE

Table No: 4.3.1.1

Table Name: You like or dislike advertising

S.INo

Opinion No of Respondents (Xi)

Rating Factors(Wi)

WeightedMean(XiWi)

1 Extremely Like 18 5 902 Like 52 4 2083 Neutral 26 3 784 Dislike 2 2 45 Extremely

Dislike2 1 2

Total 100 382


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WiXiWeighted Average = ---------

N

382= ---------

100

= 3.82Inference:

The above table shows that 52 respondents are like the online advertising, 26

respondents are neutral, 18 respondents are extremely like the Internet Advertising,

4 respondents are dislike and extremely dislike the Internet Advertising.

4.3.2 ADVERTISING UTLITIY

Table No: 4.3.2.1

Table Name: Most advertising is informative

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)

1 Strongly Agree 18 5 902 Agree 56 4 2243 Uncertainty 18 3 544 Disagree 8 2 165 Strongly

Disagree0 1 0

Total 100 384


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N

384

= --------- 100

= 3.84

Inference:

The above table shows that 56 respondents are agree that most advertising is

informative, 18 respondents are strongly agree and uncertainty, 8 respondents are

disagree with advertising is informative.

Table No: 4.3.2.2

Table Name: I like to look at most advertisements that I am exposed to

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree0 1 0

Total 100 372


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20


N

372

= --------- 100

= 3.72

Inference:

The above table shows that 62 respondents are like to look at most advertisements

that they exposed more, 18 respondents are uncertainty, 10 respondents are

strongly agree and 10 respondents are disagree.

Table No: 4.3.2.3

Table Name: Online Advertising helps you to make your purchase decision.

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree2 1 2

Total 100 360


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N

360

= --------- 100

= 3.60

Inference:

The above table shows that 44 respondents are agree that online advertising helps

to make their purchase decisions, 20 respondent are uncertainty, 18 respondents

are strongly agree, 16 respondents are disagree and 2 respondents are strongly

disagree.

Table No: 4.3.2.4

Table Name: Internet Ads informative to make purchase decision.

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree0 1 0

Total 100 354


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N

354= ---------

100

= 3.54

Inference:

The above table shows that 52 respondents are agree that IA information make

impact on their purchase decision, 26 respondents are uncertainty, 14 respondents

are disagree and 8 respondents are strongly agree.

4.3.3 INDIGNITY

Table No: 4.3.3.1

Table Name: Most advertising insults my intelligence.

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree2 1 2

Total 100 312


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N

312= ---------100

= 3.12

Inference:

The above table shows that 32 respondents are disagree with the statement that

most advertising insults my intelligence, 30 respondents are uncertainty, 24

respondents are agree, 12 respondents are strongly agree and 2 respondents are

strongly disagree.

Table No: 4.3.3.2

Table Name:You feel offended by advertisements

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree0 1 0

Total 100 318


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N

318= ---------100

= 3.18

Inference:

The above table shows that 34 respondents are uncertainty that they feel offended

by Internet Advertising, 30 respondents are feel agree, 28 respondents are feel

disagree, 8 respondents are strongly agree.

Table No: 4.3.3.3

Table Name:You felt misled by advertisements

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)

1 Strongly Agree 8 5 40

2 Agree 22 4 883 Uncertainty 40 3 1204 Disagree 24 2 485 Strongly

Disagree6 1 6

Total 100 302


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N

302

= --------- 100

= 3.02

Inference:

The above table shows that 40 respondents are felt misled by advertisements, 24

respondents are felt disagree, 22 respondents are felt agree, 8 respondents are felt

strongly agree and 6 respondents are felts strongly disagree.

4.3.4 TRUST

Table No: 4.3.4.1

Table Name:You feel you can trust Internet advertising.

WiXi

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree2 1 2

Total 100 340


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Weighted Average = ---------N

340= ---------

100

= 3.40

Inference:

The above table shows that 36 respondents are agree that they can trust internet

advertising, 34 respondents are uncertainty, 16 respondents are disagree with the

statement that they can trust the Internet Ads, 12 respondents are strongly agree

and 2 respondents are strongly disagree.

Table No: 4.3.4.2

Table Name: Comfort to purchase thru web ads

WiXi

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)

1 Highly comfort 16 5 802 Comfort 56 4 2243 Uncertainty 8 3 244 Discomfort 20 2 405 Highly

Discomfort0 1 0

Total 100 368


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Weighted Average = ---------N

368= ---------

100

= 3.68

Inference:

The above table shows that 56 respondents are comfort with purchasing an item

directly through a web address in an advertisement, 20 respondents are discomfort,

16 respondents are highly comfort and 8 respondents are uncertainty.

4.3.5 PRICE PERCEPTION

Table No: 4.3.5.1

Table Name: Cyber advertising results in lower prices

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)

1 Strongly Agree 8 5 40

2 Agree 16 4 643 Uncertainty 44 3 1324 Disagree 28 2 565 Strongly

Disagree4 1 4

Total 100 296


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N

296

= --------- 100

= 2.96

Inference:

The above table shows that 44 respondents are uncertainty that cyber advertising

results in lower prices for the products, 28 respondents are disagree, 16

respondents are agree, 8 respondents are strongly agree and 4 respondents are

strongly disagree with the statement.

Table No: 4.3.5.2

Table Name: Money value for the advertised brands products

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree4 1 4

Total 100 352


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29


N

352= ---------100

= 3.52

Inference:

The above table shows that 50 respondents are positive going with that they will

usually get better value for their money in advertised brands, 20 respondents are

uncertainty, 14 respondents are disagree, 12 respondents are strongly agree and 4

respondents are strongly disagree with the statement.

Table No: 4.3.5.3

Table Name: Online advertising has effect on the prices of advertised products.

S.INo Opinion No of Respondents (Xi) Rating Factors(Wi) WeightedMean(XiWi)


Disagree0 1 0

Total 100 386


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30


N

386= ---------

100

= 3.86

Inference:

The above table shows that 56 respondents are accepts that Online advertising has

effect on the prices of advertised products, 20 respondents are strongly agree, 14

respondents are uncertainty, 10 respondents are disagree.

4.3.6 REGULATION

Table No: 4.3.6.1

Table Name: I think the government should put less effort into regulating thecontent of advertising I

see

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree2 1 2

Total 100 338


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N

338= ---------

100

= 3.38

Inference:

The above table shows that 46 respondents are uncertainty with the government

should put less effort into regulating the content of advertising, 20 respondents are

agree, 18 respondents are strongly agree, 14 respondents are disagree and 2


Table No: 4.3.6.2

Table Name: Advertising regulation should be done by the advertising industrythrough its member associations rather than by the government

S.INo Opinion No of Respondents (Xi) Rating Factors(Wi) WeightedMean(XiWi)


Disagree4 1 4

Total 100 340


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N

340= ---------

100

= 3.40

Inference:

The above table shows that 36 respondents are uncertainty with the Advertising

regulation should be done by the advertising industry through its member

associations rather than by the government, 30 respondents are agree, 16

respondents are strongly agree, 14 respondents are disagree and 4 respondents are

strongly disagree with the statement.

Table No: 4.3.6.3

Table Name: Amount of regulation which the government currently places onadvertising

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree10 1 10

Total 100 312


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33


N

312= ---------100

= 3.12

Inference:

The above table shows that 42 respondents are uncertainty with the Amount of

regulation which the government currently places on advertising, 22 respondents

are agree, 14 respondents are disagree, 12 respondents are strongly agree and 10


Table No: 4.3.6.4

Table Name: Online advertising transform consumer marketing in the same waythat general advertising practice four or five decades ago

S.INo


Rating Factors(Wi)

WeightedMean(XiWi)


Disagree2 1 2

Total 100 334


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34


N

334= ---------

100

= 3.34

Inference:

The above table shows that 48 respondents are uncertainty with that online

advertising transform consumer marketing in the same way that general advertising

practice four or five decades ago, 26 respondents are agree, 12 respondents are

Strongly agree, 12 respondents are disagree and 2 respondents are strongly

disagree with the statement.

4.5 CHISQUARE ANALYSIS

To analyze how much impact is really the internet advertising having on individual

buying behaviors.

Response StronglyAgree

Agree

Uncertainty

Disagree

StronglyDisagree

Total

Lesser than once/month 6 14 4 6 0 30

1 2 times/month 1 9 6 6 0 22

2 5 times/month 0 18 6 4 2 30

6 9 times/month 1 1 0 0 0 2


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Greater than 10time/month

4 8 4 0 0 16

Total 12 50 20 16 2 100

4.5.1 Null Hypothesis: Ho

Internet Advertising really has impact on the individual purchase decisions.

4.5.2 Alternate Hypothesis: H1

Internet Advertising doesnt have any impact on the individual purchase decisions.

4.5.3 Chi Square Test formula:

where

Aij = actual frequency in the i-th row, j-th column

Eij = expected frequency in the i-th row, j-th column

r = number or rows

c = number of columns

4.5.4 CALCULATION TABLE:

S.INo

Observed(A)

Excepted(E) (A - E) (A - E)2 (A - E)2 /E (A - E)2 /E

1 6 3.6 2.4 5.76 1.6 1.6

2 14 15 -1 1 0.066666667 0.07

3 4 6 -2 4 0.666666667 0.67


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4 6 4.8 1.2 1.44 0.3 0.3

5 0 0 0 0 0 0

6 1 0.34 0.66 0.4356 1.281176471 1.29

7 9 11 -2 4 0.363636364 0.37

8 6 6 0 0 0 0

9 6 3.52 2.48 6.1504 1.747272727 1.7510 0 0 0 0 0 0

11 0 0 0 0 0 0

12 18 15 3 9 0.6 0.6

13 6 6 0 0 0 0

14 4 4.8 -0.8 0.64 0.133333333 0.14

15 2 0.6 1.4 1.96 3.266666667 3.27

16 1 0.24 0.76 0.5776 2.406666667 2.41

17 1 1 0 0 0 0

18 0 0 0 0 0 0

19 0 0 0 0 0 0

20 0 0 0 0 0 0

21 4 1.92 2.08 4.3264 2.253333333 2.26

22 8 8 0 0 0 0

23 4 3.2 0.8 0.64 0.2 0.2

24 0 0 0 0 0 0

25 0 0 0 0 0 0

Total 14.93

4.5.5 DEGREE OF FREQUENCY:

Degree of Frequency = (r 1)*(c 1)

= (5 1)*(5-1)

= 16

4.5.6 TABULATED VALUE:

Tabulated Value = 26.300, At D.F 16 and 5% level of Significance.

4.5.7 CALCULATED VALUE:


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Calculated Value = 14.93

4.5.8 DECISION:

The tabulated value of X2 at 16 level of d.f, 5% is 26.300. The observed value of

X2 is 14.93 less than tabulated value (26.300). Thus accept the H0 and conclude

that Internet Advertising really has impact on the individual purchase decisions.

CHAPTER 5

CONCLUSIONS

5.1 SUMMARY OF FINDINGS

Among the respondents 78 % of respondents are under the age group of 20

-29 and 0 % of respondents are under the age group of Greater than 50.


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Among the respondents 54 % of respondents are male and 46 % of

respondents are female.

Among the respondents 60 % of respondents are Master degree qualification,

36 % of respondents are Bachelor degree and 4 % of respondents are female.

Among the respondents 68 % of respondents are computer/Electronics

professional and 6 % of respondents are related to manufacturing/Production.

Among the respondents 38 % of respondents are in 15001 25000 salary

range and 6 % of respondents are in 35001 45000 salary range.

Among the respondents 32 % of respondents are 2 5 times frequency of

transaction per month and 12 % of respondents are > 10 times frequency of

transaction per month.

Among the respondents 44 % of respondents are spent almost 1001 to 10000

on online purchasing per month and 8 % of respondents are spent more than

40000.

Among the respondents 28 % of respondents are render the E-banking

services and 8 % of respondents are purchased automobile products.

52 respondents like the Internet advertisement and 2 respondents are

extremely dislike the IA.

56 respondents are agreeing that IA is more informative and 8 respondents

are disagreeing with the statement.

62 respondents are agreeing that they look more advertisement which

exposed them more and 10 respondents are disagreeing with the statement.

44 respondents are agreeing that online ads help in their purchase decisions

and 2 respondents are disagreeing with the statement.

24 respondents are disagreeing with the statement that they misled by IA

and 22 respondents are agree with the statement.


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36 respondents are trust the internet Ads and 2 respondents are strongly

disagree.

56 respondents are comfort with purchasing an item directly through a web

address in an advertisement.

28 respondents are disagreeing with the statement that cyber ads results in

lowering the price of the product/services and 16 respondents are agreeing

the statement.

50 respondents agree that they get better value for their money in advertised

brands of product and 4 respondents strongly disagree with the statement.

26 respondents agree that online advertising transform consumer marketing

in the same way that general advertising practice four or five decades ago.


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5.2 SUGGESTIONS AND RECOMMENDATIONS

Indeed, current commercial Web sites appear to include features that would

allow users to benefit from the information richness of the medium while

ignoring those features that would engage the consumer (e.g., role-playing

and interactivity).

Suggesting that on-line businesses should invest increating sites that

consumers enjoy visiting, just as they invest in creating traditional

advertisements that are enjoyable.

Internet advertisements should not include more features that have been

found to be entertaining in the mass media (e.g., attractive visuals, humor),

but rather features that have been found to be entertaining on the Internet.

Such features include those unique to the Internet such as interactive product

demonstrations.

Contributing nearly as much as perceived informativeness to IA attitudes isthe perceived behavioral (purchasing) utility of advertising.


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5.4 Questionnaires:

Demographic profile of the respondents:

1. Age (in Yrs)

Below than 20

20 29.

30 39.

40 49.

Greater than 50

2. Gender.

Male.

Female.

3. Educational Background

Secondary school

Bachelor degree.

Masters degree.

Doctoral degree.


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Others (please specify)

4. Profession.

Banking/ Finance

Advertising/ Marketing

Computers/ Electronics Manufacturing/Production

Others

5. Income (Per Month).

Lesser than 15000

15001 25000

25001 35000

35001 - 45000

45001 and Above

Objective 1: Primary objective of the study to find out how much impact is reallythe internet having on individual buying behaviors.

6. Frequency of transactions with the Internet Retailer in the past twelve

months.

Lesser than once/month

1 2 times/month

2 5 times/month

6 9 times/month

> 10 times/month

7. Amount spent with the Internet retailer in the past twelve months.

Lesser than 1000

1001 - 10000

10001 20000

20001 - 30000

Above than 40000

8. Indicate the product/services categories that purchased within the last six

months.


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E-banking services

Households items & Books

Computer equipment

Foods items

Auto (Bike & Car etc.)

Objective 2: To understand the Internet Users Attitude towards online advertising.

Attitude:

9. You like or dislike advertising.

Extremely like

Like

Neutral

Dislike

Extremely Dislike

10.Most advertising is informative.

Strongly Agree

Agree

Uncertainty

Disagree

Strongly Disagree

11.I like to look at most advertisements that I am exposed to

Strongly Agree

Agree

Uncertainty

Disagree

Strongly Disagree

12.Online Advertising helps you to make your purchase decision.

Strongly Agree

Agree

Uncertainty Disagree

Strongly Disagree

13.Confident do you generally feel using information you see in an ad to make apurchase decision.

Strongly Agree

Agree


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Uncertainty

Disagree

Strongly Disagree

Indignity

14.Most advertising insults my intelligence.

Strongly Agree

Agree

Uncertainty

Disagree

Strongly Disagree

15.You feel offended by advertisements.

Strongly Agree

Agree

Uncertainty

Disagree Strongly Disagree

16.You felt misled by advertisements.

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Trust

17.You feel you can trust advertising.

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

18.Comfort ability about purchasing an item directly through an web address inan advertisement.

Highly Comfort

Comfort

Uncertainty

Discomfort

Highly Discomfort

Price Perceptions


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Objective 3: Might it transform consumer marketing in the same way that networktelevision revolutionized consumer culture and commercial practice four or fivedecades ago.

25.Online advertising transform consumer marketing in the same way that

network television revolutionized consumer culture and commercial practicefour or five decades ago.

Strongly disagree

Disagree

Neutral

Agree

Strongly agree


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5.5 REFERENCE

Gordon, M. E. & De Lima-Turner, K. (forthcoming).Consumer Attitudes Toward

Internet Advertising: A Social Contract Approach. International Marketing

Review.

GVU (1999). GVUs WWW User Surveys. http://www.cc.gatech.edu/gvu/user_surveys.

Hammonds, K. H. (1997). Whos Doing What On-Line.http://www.businessweek.com/1997/18/b352514.htm.

Hawkins, D. T. (1994, March). Electronic Advertising: On Online InformationSystems. Online, 2639. Hoffman, D. L., Kalsbeek, W. D. & Novak, T. P.(1996).

Schlosser, A., and Kanfer, A. (1999a). Current advertising on the Internet: The

benefits and usage of mixed-media advertising strategies. In D. Schumann &

E. Thorson (Eds.), Advertising and the World Wide Web. Mahwah, NJ:

Lawrence Erlbaum Associates.
http://www.cc/http://www.cc/

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