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The effects of advertising credibility on consumer

buying behavior

1.AbstractCustomer buying behavior is usually reflected by the perception and attitude of

the customers towards company or a brand. The effects of advertising credibility on

customers is evaluated in this paper. Every customer interpret the advertising message in

his/her own way. The focus of this study is to determine the trend about online

purchasing. As online buying has different dimensions of benefits and threats at the same

time. The response of the customers will be measured through a 5 point likert scale and

the data will be analyzed empirically. The results of this study will help marketers to

devise appropriate strategies which will further boost up the online buying.

Key words

Internet, Social Networking Sites, eWOM, Customer buying behavior, Online

customer reviews, Source credibility.

1.1 Introduction

Advertising credibility refers to the perception of customers about an advertise

product. Advertisement through various medium have varying credibility depending upon

the interface of advertisement.


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In this era, due to changing trends new medium are getting more importance than

the traditional ones. So, this study is important due to the fact that the traditional

mediums are obsoleting.The future belongs to advertisement through social media.

Advertisement credibility includes the trust worthiness of websites has a direct

effects on consumers buying behavior. Each website has its own rating which is likely to

influence the consumer buying behavior. Advertisements which are based on false

information and ideas which are misrepresented by the marketers have negative effects

on consumer buying behavior. In Pakistan PEMRA is the regulatory advertising agency.

But due to the loop holes and grey areas there have not been effective implementations

on values and regulations.

According to Alessandro, Girardi and Tiangsoongnern (2012), online purchasing

comprises of great risk and people do not know each other personally and they are unable

to inspect the goods they are ordering in physical state and they are also unaware of the

service providers. With the advent of internet, it has become easy for people to purchase

online with much of ease and saving their and also can perform in depth analysis of the

product and also allows them to compare the prices of different brands. At the same time

they are also vulnerable to privacy risk theft which greatly reduces buying online.

Online shopping site such as e-bay encountered numerous problems in their early

days because of lack of confidence and trust from the consumers in online shopping.

Recent researches has shown that this is still a pretty much problem because as much as

6.25 percent on the average are subjected to fraud.


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To reduce the potential risk online consumers rely on the brands with high

credibility. Their policies regarding security, protection and the mechanism they have

devised to ensure the privacy. There has been different assurances from the online

retailers to the consumers regarding their privacy protection in order to gain the trust of

consumers.Advertisement campaigns also use celebrities to promote the products which

results in increased purchasing behavior. It also influence advertising effectiveness and

also to increase brand recognition, brand recall, purchase intentions and even purchase

behavior.Sometime marketers use celebrities which have negative effects on society

because they are widely followed by the fans and they try to imitate the celebrities.

1.2 Importance and Significance

There are many different channels for advertisement but in these days due to

dynamicalSly changing environment the use of e-commerce is becoming more popular.E-

commerce is contributing to get the global view of market. In addition to this shopping

has become much more easier and we are just a click away from global market.This study

will help us to identify the perceptions of online buyers and how the credibility of

different advertisements affect their purchasing behavior

According to Coulter and Roggeveen (2012), the increasing use of social

networks including Face book, My space, Meetup, Linkedin and Twitter has grown

rapidly in the past years and is changing the effects of WOM. Traditional WOM plays a

vital role in molding attitude of the consumers and increases the adoption of the product

than any other mass media channel. Because of the internet the environment in which

communication take place has not been changed.


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WOM does not take place in face to face involving two persons, it occurs

between number of public domains of online social portal.Due to this emerging trend,

marketers has started putting their efforts on the social networking web sites (for

example: My Space, Facebook, Linkedin and Twitter). In order to create awareness

regarding their brand, products, generating interest which will ultimately lead to

purchasing of the product. Now a days the typical strategic marketers are creating pages

on the social networks which is an attempt to understand the potential customers.

Traditional WOM has constructed models to explain the determinants of e-WOM

influence. Different social networking sites have different effects on consumer buying

because of their characteristics and popularity.

1.3 Research Questions

What is the initial perception of the customers regarding online purchasing?

How fraudulent activities are effecting the online buying behavior?

How the privacy of consumers is at stake?

How the level of trust can be regained in online buying behavior?

What are the factors relating to the credibility of advertising companies?

1.4 Objectives

To analyse the relationship between consumer perception and attitude towards

online shopping.

To determine the frequency of fraudulent activities in online shopping.

To run the awareness campaign among customers regarding online shopping.

To look for various factors that are contributing to the image of online shopping.


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1.5 Problem Statement

Customers are avoiding from online buying.

1.6 Significance of the study

The world has become a global village and due to this, there has been a

tremendous rise in online shopping due to ease of access.This study endeavors to

determine those factors due to which customers are reluctant to go for online shopping.

This study will help to gain the attention of government to devise such policies which

will protect the online customers.

1.7 Delimitation

We limitised our study to certain sectors of Islamabad. Due to lack of time and funds.

2.0 Literature Review

According to Cheung, Lee and Rabjohn(2008), with the rapid growth of E-

commerce there is a huge amount of information which influences the customers.

Information usefulness have a strong and positive relation with the consumer decision

making and facilitates consumers to adopt information in online communities.

People make purchase decisions on the basis of information available over the

internetand rely on the OCRs to make decisions varying from medical purchase to online

movie purchase.

This study helps to identify the factors which help consumers for the adoption of

the information. Retailers are continuously looking to identify new market channels and

new segments where they can promote their products and services internet has provided


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huge opportunities for online business and has promoted eWOM such as online blogs,

review sites, social networking site eWOM allow consumers across different

geographical areas to share their interests, reviews and experiences regarding the use of

particular product or services. A recent study has shown that consumers play great trust

on online reviews because it creates a sense of trustworthiness. Consumers continue to

share their experiences in the cyber environment. Most of the studies have been

conducted that triggers the consumers to hear their product related experiences and

knowledge but little attention is paid to the factors which work as a driving force to

promote the usage of online customer reviews. eWOM also includes the factors which are

important for the information adoption.

Traditional WOM has been playing important role in the consumer buying

process. Previous researches have also proven that WOM is more effective advertising

tool and gains more customer attention than traditional means of marketing such as

personal selling. So by implementing these elements, marketers can increase their

advertising campaign. eWOM includes positive or negative opinion or views made by the

potential, current or former customers regarding the brand or company which helps

multiple people to gather relevant information regarding their product purchase through

the internet medium.

eWOM can also be considered extension of traditional interpersonal

communication which has now entered into the era of cyber space. Marketers and

consumer research places great importance and analyze how eWOM modifies and

influences buying pattern. Researchers are also looking for factors that promote eWOM


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and how they provide information to the marketers to understand the consumer

perception regarding buying. Although eWOM carries basic general information but this

information is perceived differently among different persons.

Information quality has also been an underlying factor which influence the buying

process. In the context of end user the information embedded in the advertising message

is evaluated on the basis of information format accuracy and timelines with the increase

and advent of internet shopping researchers are working to extent information quality

dimensions. Source credibility also reflects the advertising message is complete and

trustworthy.

The good source credibility was found to alter the purchase direction of the

consumer as compare to low credibility source. The adoptability of the message depends

on the positive attributes, reliability of the message and thereby facilitates knowledge

transfer.

Recent researches have shown that consumers buying behavior is likely to be

influenced by the online reviews suggested by the other consumers.Online customer

reviews contains the information about the target product and it also provides the

recommendations and suggestions from a consumers point of view. Word of mouth is

the powerful communication tool used by the marketers which influences the opinions

and purchase intentions of the customers.

By understanding the communication tools such as electronic word of mouth

marketerscan influence the purchase decision of the customers.Advertisement which are

based on false information irritate the customers.If the customer is unsatisfied with the


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product orservice this will result in negative WOM and loosing of the customers base

unless the issue is resolved.This study will also help web developers to design websites

that provide better information to the customers.

According to Karakaya and Barnes (2010), information based websites like

Amazon.com help customers in making decisions or change their perception regarding a

particular brand or product. eWOM refers to the change of information and knowledge

between consumers over the internet. There is a positive relationship between customer

loyalty and eWOM which affects the overall image of the company. Therefore eWOM is

being valued by the organizations. Researchers have been focusing on all the sales of the

company will be increasing by promoting positive WOM and also comparing influence

of WOM with other marketing channels.

Message direction shows whether the message produces favorable or unfavorable

results which effects product attitude and purchase intention. As WOM has more

credibility than commercial advertisement. It also generates favorable results by

promoting customers to buy a particular productive service. Whether the message has

emotional or rational appeal it is likely to have some sort of persuasive effect on the

message receivers to devise an appropriate marketing strategy. Marketers need to

understand the message source credibility and the nature of message influence the effects

of eWOM. Involvement in terms of risk associated with purchase as perceived by the

consumer. If there is low risk in regarding a purchase, there will be low involvement and

vice versa. When consumers evaluate a product on the basis of their attributes they are in

a state of confusion and uncertainty about purchasing of the product because of the


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perceived risk.The influences of eWOM message appeal and message source credibility

on brand attitude.

Source credibility is an important indicator which influences the consumer

buying behavior to increase the message credibility. Marketers are employing celebrities

and expert opinion in their advertising campaigns to prove the credibility of their

message. Senders image and expertise have a direct influence on consumer perception

regarding the source credibility. It has been seen that consumers go for online reviews for

making a product purchase. With the increase in online shopping there has also been

increase in reviews and opinion sides which allows the consumers to test their purchase

decisions by comparing it from the customers who have experiences in the past with the

particular product or services. If the information source is trustworthy and reliable only

then the customers follow it.

There are number of online sites such as Amazon.com which provides the reviews

for customers to assist them and their buying decision. The frequency of visiting websites

also influences consumer decisions regarding purchase. Previous studies have been

focusing on influence consumers decision making but little work has been done

regarding the customer care provided by the companies. Source credibility, customer

opinions and the level of consumer usage or all inter-related and they promote the use of

a product or service. A study conducted by researchers concluded that web blogs are

considered to be more credible than traditional resources such as personal selling. The

customers rank their preferences and credibility of the blogs on the basis of the usage. As


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blogs are providing credible information, it would be interesting to analyze and look for

other information sources to see whether they are meeting the same level of trust or not.

There are factors that facilitates consumers and making their search while there

are some factors which can frustrate them.

According to Hadija, Barnes and Hair (2012), it is a general perception that social

networks are easy inexpensive and attractive way of combining the people around the

world who share similar interests. Social network divides people in the form of

community where they can express themselves.Online networks can help friends and

families to connect anywhere in the world, find friends and co-workers to work as a team.

Social networks are offering free services and sign ups because of the huge advertising in

their virtual space. Advertising over the internet is picking up pace day by day and is

expected to surpass the figure of 29 billion in 2010. So because of this advertising plays

an integral part in every social networking site and there has been a dedicated space for

the advertisers for the promotion of the products. The reason behind providing space to

the advertisers benefits both the only social networks and advertising agency themselves

it not only helps social networks to increase their popularity but also helps advertisers to

identify the segments and market their target audience.

Advertisers are using push strategy in online networks where they are posting

their advertisements and attracting their customers but this trend is slowly changing as

advertisers are moving from push medium to a pull strategy. The question that still

remains that advertisements that influences customers does have any effect on their

buying behavior and consumption patterns.


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Most of the users rely on online friends advise and trust when the question of

advertising and brands take place in minds. In order to gain better understanding of the

consumer perceptions regarding the online buying we must focus on the basic principles

of web advertising. Some authors are of the opinion although a website with attractive

contents create positive feelings and attitude, it does not have strong influence as

television.

Moreover users are likely to give a positive response to the advertisement that

focuses their needs otherwise they will ignore them. There are number of questions that

still remains to be unanswered regarding the right target population and how consumer

views the advertisements placed in online social networks.

According to Demangeot and Broderack (2006), experience plays a crucial role in

the life of consumers as they help to improve the past experiences and alter their buying

behavior as well. Mostly people shop to fulfill their basic needs, analyze the market,

gathering information regarding the products and also for the purpose of gaining

pleasure.

Besides the primary motives, entertainment and fun are the secondary motives of

shopping. Shopping experiences take place when shoppers are involved in buying activity

and exposed to environmental cues. Experiences which takes place during shopping

reflects the consumers future attitude and perception regarding a particular brand or

company positive experiences also favors the company and help them to shape the

consumer attitudes, moods and behavior. Today, consumers are unable to differentiate

among product and services because of number of companies operating so the only way


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consumers can differentiate among the products and services as on the basis of their

experiences.

Pleasure and sense of ease during the journey of online shopping increases

satisfaction. Sites with interactive interface increases user involvement and intention to

purchase. Experiences which occur during online environments are smaller threats that

they can be tackled easily by employing some technological skills.

According to Martinez-Lopez, Rodriguez-Ardura, Gazquez-Abad, Sanchez-

Franco and Cabal (2010), information regarding products can also be obtained through

recommendation which is a vital information source, and helps consumers to direct their

decision processes. Sometimes recommendations also create lack of understanding with

certain products and services because of un-trusted sources. Consumers provided by a

variety of choices create positive relations. In these days, advertising markets have

become increasingly saturated and consumers rely on recommendations to go for a

particular brand or a product. If advertising message is providing with too much choices

this could confuse the customers which results in stress and anxiety and ultimately de-

tracking the consumer without closing the purchase process. To address this problem,

company running online businesses analyze the consumer profiles their needs and

demands, their preferences and attributesthey value and then provide them with the right

product. Recommendation system is becoming a very integral tool in online advertising

which helps to build long term customer relation which also shows that recommendation

regarding accurate product results in good transaction and meets customer satisfaction.

Therefore this recommendation should be properly designed and targeted towards the


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market. According to Wang and Sun (2010), the attitudes and beliefs of consumers

towards online advertising plays a significant role in their buying decision. Studies have

shown that effectiveness of the advertising can be measured through attitudes towards

online advertising. Studies have been conducted regarding the relationship between

culture and advertising focusing traditional media but little work has been done in online

context. By understanding the cultural differences marketers can gain useful insights by

developing ads focusing the particular needs of a segment.

2.1 Research Gaps

How much customers gethelp from the shopping websites also how they get

Persuadedto shop online. Electronic Word of Mouth can be positive or negative so future

research can look into the persuasion effects of negative or even neutral eWOM and

compare the results with positive eWOM. Future research can also manipulate factors

that may affect eWOM message source credibility

2.3 Description of Variables

Credit card fraud is a wide-ranging term fortheft and fraud committed using

a credit card or any similar payment mechanism as a fraudulent source of funds in a

transaction. The purpose may be to obtain goods without paying, or to obtain

unauthorized funds from an account. Credit card fraud is also an adjunct to identity theft.

This model shows that factors such as fraudulent purchases and misrepresentation

etc. influence attitude towards online buying which in turn affects online behavior and

intention to buy. This model also depicts that trust influences belief factors or attitude

towards online buying behavior.
http://en.wikipedia.org/wiki/Thefthttp://en.wikipedia.org/wiki/Fraudhttp://en.wikipedia.org/wiki/Credit_cardhttp://en.wikipedia.org/wiki/Identity_thefthttp://en.wikipedia.org/wiki/Identity_thefthttp://en.wikipedia.org/wiki/Credit_cardhttp://en.wikipedia.org/wiki/Fraudhttp://en.wikipedia.org/wiki/Theft


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2.4 Hypotheses

H1: Positive source credibility will increase the costumer buying behavior.

H2: Privacy of personal information will negatively affect the online shopping.

H3: Positive online brand image will enhance the costumer buying behavior.

3.0 Conceptual Model

Online Brand

Image

Source

Credibility

Privacy

Concerns

Customer Buyin

Behavior


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4.0 Research Methodology

As we are working with the attitude of people, we are going to measure the

preference of customers about online buying which is of primary interest. The data

collected for this purpose will be of primary nature. We will consider the customers who

are experiencedso they will provide us the most reliable data.The instrument that will be

used for this purpose will be 5 point Likertscale, because some of the independent

variables are qualitative in nature.

4.1 Population

The internet users of Islamabad will be the population of our study.

4.2 Sample

The individuals and households of sector I-8, Islamabad.

4.3 Sample Size

The sample size will be of 100 people.

4.4 Sample Characteristics

The age group includes the customers that ranges between 20 to 40. The

customers will be university students, job holders.

4.5 Data Type

The data will be of primary nature.

4.6 Instrument

Our instrument is adopted questionnaire. It is based on 5 point lickert scale


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4.7 Demographic Analysis:

Demographic table shows the frequencies of gender, age, education and marital

status. Gender table shows that males are 54% and females are 46% out of 100

respondents. The maximum number of respondents lies in age group of up to 21 to 25

years. Comprising 58% of all respondents, 32% of the respondents lies in age group 26-

30. 2% lies in 31-35 age group. 2% lies in age group of 36-40 and the remaining 6% lies

in the age group of above 40. The education table shows that 52% of the respondents are

of graduate level and 42% of the respondents are of post-graduate level and 6% of the

respondents are of Ph.D level.

Marital status table shows that 32% of the respondents are married while the

remaining 68%

4.8 Descriptive Analysis

Descriptive statistics comprising the value of the maximum, minimum, mean, standard

deviation, skewness and curtosis. The values of skewness and curtosis from the table of

descriptive statistics are used to find out normality of data the acceptable range of skewness is

between -2 and +2 and the ideal range is between -1 and +1. From the table we find out that value

of skewness for most of the variables lies between the ideal range of -1 to +1 and the value of

Source credibility and Privacy concerns lies in an acceptable range of -2 to +2. So with respect to

skewness data is normal.


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Table 1

Gender

Frequency Percent Valid Percent

Cumulative

Percent

Valid 1.00 54 54.0 54.0 54.0

2.00 46 46.0 46.0 100.0

Total 100 100.0 100.0

Table 2

Age


Cumulative

Percent

Valid 21-25 58 58.0 58.0 58.0

26-30 32 32.0 32.0 90.0

31-35 2 2.0 2.0 92.0

36-40 2 2.0 2.0 94.0

Above 40 6 6.0 6.0 100.0

Total 100 100.0 100.0


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Table 3

Education L evel


Cumulative

Percent

Valid Phd 6 6.0 6.0 6.0

post graduate level 42 42.0 42.0 48.0graduate level 52 52.0 52.0 100.0

Total 100 100.0 100.0

Table 4

Marital StatusFrequency Percent Valid Percent

Cumulative

Percent

Valid Married 32 32.0 32.0 32.0

Single 68 68.0 68.0 100.0

Total 100 100.0 100.0

Reliability Analysis:

In reliability analysis the value of Cronbachs alpha is analyzed to ensure the intern item

consistency for each variable. The value of Cronbach alpha should be greater than 0.6. In


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our analysis the value of Cronbachs alpha for all of the variables is greater than 0.6

which shows that all the variables are reliable

Table 5

Source Credibil ity

Cronbach's

Alpha N of Items

.558 5

Table 6

Online Brand Image

Cronbach's

Alpha N of Items

.731 5

Table 7

Pri vacy ConcernsCronbach's

Alpha N of Items

.822 5


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Table 8

Customer Buying

BehaviorCronbach's

Alpha N of Items

.655 5

Results and Discussions:

Independent Sample t Test:

Levenes test shows that the significance value is greater than .05 which means that thedata is normal. It is applied when the variables has two categories. So we are applying it

on gender which has two categories of male and female. So the significance value that we

calculated in it is less than .05 so significant relation exist.

Table 9

Levene's Test for Equali ty of Var iances

t-test for Equality of Means

95%ConfidenceInterval of the

Difference

F Sig. t df

Sig.(2-

tailed)

Mean

Difference

Std. Error

Difference Lower Upper

D Equalvariances

assumed

.778 .380 -1.520

98 .132 -.19630 .12914 -.45258

.05998

Equal

variancesnot assumed

-

1.530

97.410 .129 -.19630 .12827 -

.45086

.05827


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One-Way ANOVA

In our study, marital status, age and education level have more than 2 categories. So we

will apply one way ANOVA. Our table shows that marital status does not have any effecton customer buying behavior as the significance value is greater than .05 which means

the relation is insignificant so the null hypothesis will be accepted. Whereas each table

shows that the relation is significant as the significance value is less than .05 so we will

accept alternate hypothesis. Education level has a significant effect on customer buying

behavior as its significance value is less than .05.

Table 10

ANOVASum of

Squares df Mean Square F Sig.

Between Groups .008 1 .008 .018 .893

Within Groups 41.549 98 .424

Total 41.556 99

Table 11

ANOVA

Sum of


Between Groups 2.577 2 1.289 3.207 .045


Total 41.556 99


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Table 12

ANOVASum of


Between Groups 3.032 4 .758 1.869 .122


Total 41.556 99

Measure of Association

Regression Analysis

With a one unit change in IV, there is a increase or decrease in unit of DV. In regression

table the main focus is on significance value. In our table the significance value is 0.000.

So now we will move towards coefficient table in which we will look at the value of t, it

this is greater than 2 then we will accept the alternate hypothesis.

Table 13

ANOVAb

Model

Sum of


1 Regression 16.130 3 5.377 20.301 .000a

Residual 25.426 96 .265

Total 41.556 99

a. Predictors: (Constant), C, B, Ab. Dependent Variable: D


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Table 14

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 1.534 .340 4.515 .000

A .961 .152 1.210 6.328 .000

B .090 .071 .104 1.272 .207

C -.673 .168 -.770 -4.003 .000

a. Dependent Variable: D

Assumptions of Regression

Normality of data: It is checked through skewness and curtosis. In our case the

independent variables A and C have the skewness value of -1.068 and -1.283 respectively

while the independent variable B has a value of -0.890. The value of our DV is -0.042.

Descri ptive Statistics

N Minimum Maximum Mean

Std.

Deviation Skewness Kurtosis

Statistic Statistic Statistic Statistic Statistic Statistic

Std.

Error Statistic

Std.

Error

A 100 1.60 4.80 3.6880 .81616 -1.068 .241 .132 .478

B 100 2.00 5.00 3.8140 .75170 -.890 .241 -.261 .478

C 100 1.40 4.80 3.7500 .74094 -1.283 .241 1.417 .478D 100 1.20 4.40 2.8940 .64789 -.042 .241 -.464 .478

Valid N

(listwise)

100


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Outliers: There is not much dispersion in data and majority of the data is appeared Inclusters.


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Normal distribution of error: Normal distribution of error is checked through histogram.

In our case the data is normally distributed.

Auto-Correlation: There will be no auto correlation when the value will bebetween 1.5-2.5, in our case Durbin Watson value is 1.910 so there is no auto

correlation.


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Table 15

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Durbin-

Watson

1 .623a

.388 .369 .51464 1.910

a. Predictors: (Constant), C, B, A

b. Dependent Variable: D

Homoscedasticity: In our case the data in not on the same line, it is little bit dispersed so

it is hetroscedasticitic data.


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Linearity is checked through correlation analysis. Within IVs the value should notbe greater than 0.8.

Table 16

CorrelationsA B C D

A Pearson Correlation 1 .192 .909**

.531**

Sig. (2-tailed) .055 .000 .000

N 100 100 100 100


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B Pearson Correlation .192 1 .219*

.168

Sig. (2-tailed) .055 .029 .094

N 100 100 100 100

C Pearson Correlation .909** .219* 1 .352**

Sig. (2-tailed) .000 .029 .000

N 100 100 100 100

D Pearson Correlation .531**

.168 .352**

1

Sig. (2-tailed) .000 .094 .000

N 100 100 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Multicollinearity:

It is checked through variance influence factor and tolerance value should not be less

than 0.25 and variance influence factor should not be greater than 4. And the value of t

should be greater than 2. In our case IVs Source Credibility and Online Brand Image,

have a tolerance value less than 0.25 and VIF greater than 4, so multicollinearity exist but

the value of t for IV Source Credibility and Online Brand Image is greater than 2 so we

need not to worry about it.

Table 17

ANOVAb

Model

Sum of


1 Regression 16.130 3 5.377 20.301 .000a

Residual 25.426 96 .265

Total 41.556 99

a. Predictors: (Constant), C, B, A

b. Dependent Variable: D


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Table 18

Co-efficientsa

Model

UnstandardizedCoefficients

StandardizedCoefficients

t Sig.

CollinearityStatistics

B Std. Error Beta Tolerance VI

1 (Constant) 1.534 .340 4.515 .000

A .961 .152 1.210 6.328 .000 .174 5

B .090 .071 .104 1.272 .207 .952 1

C -.673 .168 -.770 -4.003 .000 .172 5

a. Dependent Variable: D

Factor Analysis:

The purpose is to obtain the most parsimonious set of factors related to each variable. Factor

analysis is an iterative process that is repeated again and again till we obtain the desired results.

Factor analysis has some assumptions:

KMO value should not be less than 0.5 Bartletts test of sphericity should be less than .05 It can only be performed on cross sectional data There must be five items for each variables Two or more items have correlation greater than 0.3 KMO test is performed to check whether sample is adequate or not if greater than 0.8-1

it is called outstanding level, if it is less than 0.8 and or greater than 0.7 then it is called

average level. If it is less than 0.7 or greater than 0.6 it is called miserable level. If less

than 0.5 then we cannot perform factor analysis.

In our first IV i.e. source credibility, the KMO value is greater than 0.5 and barttlets test

significance -value is less than 0.05. So we can move further in anti-image matrices table the anti-

image correlation values should not be less than 0.4 or 0.5. In our case all of the values are above

than 0.4 and 0.5.

In communality table all of the values should be greater than 0.5. One of our extraction values is

less than 0.5, so we remove this factor and perform the test again.


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Table 19

KMO and Bar tlett's TestKaiser-Meyer-Olkin Measure of SamplingAdequacy.

.657

Bartlett's Test of

Sphericity

Approx. Chi-Square 61.433

df 3

Sig. .000

Table 20

Anti-image MatricesPEMRA is

widely known

as a

regulatory

body among

general public

Source plays

an important

part in online

shopping?

The

description of

products

shown on the

web sites are

very accurate,

Anti-image

Covariance

PEMRA is widely

known as a regulatory

body among general

public

.786 -.179 -.153

Source plays an

important part in online

shopping?

-.179 .632 -.308

The description of

products shown on the

web sites are very

accurate,

-.153 -.308 .645

Anti-image

Correlation

PEMRA is widely


body among general

public

.751a

-.255 -.215


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Source plays an


shopping?

-.255 .626a

-.483

The description ofproducts shown on the

web sites are very

accurate,

-.215 -.483 .634a

a. Measures of Sampling Adequacy(MSA)

Table 21

Total Vari ance ExplainedComp

onent

Initial Eigenvalues Extraction Sums of Squared Loadings

Total

% of

Variance Cumulative % Total

% of

Variance Cumulative %

1 1.929 64.313 64.313 1.929 64.313 64.313

2 .641 21.361 85.674

3 .430 14.326 100.000

Extraction Method: Principal Component Analysis.

Table 22

Component M atrixa

Component

1

PEMRA is widely


body among general

public

.734

Source plays an


shopping?

.839


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The description of

products shown on the

web sites are very

accurate,

.829

Extraction Method: Principal

Component Analysis.

a. 1 components extracted.The iteration process has been

repeated 2 times.

In our second variable i.e. Privacy Concerns, the KMO value is greater than 0.5 and barttlets test

value is less than 0.05. The anti-image correlation value are also greater than 0.4 and 0.5, the

communality table shows that all of the values are above 0.5. In component matrix table one ofthe factor has value less then 0.5 so we will remove that factor and perform the process again.

Table 23

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.807

Bartlett's Test of

Sphericity


df 6

Sig. .000


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Table 24

Anti-image MatricesRisk of loss

of privacy

while

shopping

online

While

shopping

online, I

hesitate to

give my credit

card number

Online

shopping is as

secure as

traditional

shopping

The role of

consumer court

is satisfying

with regard to

online

shopping

Anti-image

Covariance

Risk of loss of

privacy while

shopping online

.591 -.154 -.047 -.099

While shopping

online, I

hesitate to give

my credit card

number

-.154 .428 -.082 -.171

Online

shopping is as

secure as

traditional

shopping

-.047 -.082 .516 -.186

The role of

consumer court

is satisfying

with regard toonline shopping

-.099 -.171 -.186 .377

Anti-image

Correlation

Risk of loss of

privacy while

shopping online

.865a

-.306 -.085 -.209


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While shopping

online, I

hesitate to give

my credit cardnumber

-.306 .799a

-.174 -.425

Online

shopping is as

secure as

traditional

shopping

-.085 -.174 .827a

-.422

The role of

consumer court

is satisfying

with regard to

online shopping

-.209 -.425 -.422 .763a



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Table 25

CommunalitiesInitial Extraction

Risk of loss of privacy while

shopping online

1.000 .611

While shopping online, I hesitate

to give my credit card number

1.000 .753

Online shopping is as secure as

traditional shopping

1.000 .666

The role of consumer court is

satisfying with regard to online

shopping

1.000 .791


Table 26


onent


Total

% of


% of



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1 2.821 70.525 70.525 2.821 70.525 70.525

2 .536 13.400 83.926

3 .375 9.367 93.292

4 .268 6.708 100.000


Table 27

Component M atrixa

Component

1Risk of loss of privacy

while shopping online

.782

While shopping online, I

hesitate to give my

credit card number

.868

Online shopping is as

secure as traditional

shopping

.816

The role of consumercourt is satisfying with

regard to online

shopping

.889


Component Analysis.

a. 1 components extracted.

We performed the iteration process 1 times.


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In our third IV i.e. Online Brand Image the KMO value was less than 0.5 so this was the violation

of assumption and we could not perform the factor analysis further.

In our DV i.e. Customer Buying Behavior, the KMO value is greater than 0.5 and barttlets value

is less than 0.05. The anti-image correlation values are also greater than 0.4 or 0.5. Thecommunality table shows that all of the values are greater than 0.5 except for 1. So we will

remove it and perform the process again.

Table 28

KMO and Bar tlett's TestKaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.500

Bartlett's Test of

Sphericity


df 1

Sig. .000

Table 29

Anti-image MatricesReputation of

thecompany/bran

d has a strong

linkage with

your buying

preferences

Your

friends/relativ

es opinionschange your

perception

regarding a

particular

brand

Anti-image

Covariance

Reputation of the

company/brand has a

strong linkage with

your buying preferences

.676 -.385

Your friends/relatives

opinions change your

perception regarding a

particular brand

-.385 .676


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Anti-image

Correlation

Reputation of the

company/brand has a

strong linkage with


.500a

-.569




particular brand

-.569 .500a


Table 30

CommunalitiesInitial Extraction

Reputation of the

company/brand has a

strong linkage with


1.000 .785




particular brand

1.000 .785


Table 31


onent


Total

% of


% of


1 1.569 78.473 78.473 1.569 78.473 78.473

2 .431 21.527 100.000



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Table 32

Component M atrixa

Component

1

Reputation of the

company/brand has a

strong linkage with


.886




particular brand

.886


Component Analysis.

a. 1 components extracted.

For this variable we have performed the iteration process 1 time.

Discussion

The objective of the study is to study and examine th effects of different factors

like source credibility, privacy concerns and online brand image on customer buying

behavior.


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Hypothesis H1:

Positive source credibility will increase the consumer buying behavior is accepted

in our study which is aligned with the previous literature on the basis of which hypothesis

H1 is developed (Cheung, Lee, Ravjohn 2008).

Hypothesis H2:

Privacy of personal information will negatively affect the online shopping is

accepted. According to previous literature, the more privacy concerns customers perceive

they buy less through online shopping (Alessandro, Girardi, Tiangsoongnern 2012).

Hypothesis H3:

Positive online brand image will enhance the consumer buying behavior, this

hypothesis is rejected on the basis of regression analysis as the value to t is less than 2

and significance value is greater than .05. So we will accept null hypothesis (Ku 2012).

Managerial Implications:

As there is an increasing trend towards online shopping now a days and our study

being focused on consumer buying behavior will help marketing managers to develop

appropriate strategies that will enhance the consumer buying behavior.

Source credibility and privacy concerns appear to have a direct effect on customer

buying behavior so the marketing managers should use sources that are trustworthy and

reliable. They must develop a sophisticated security system to ensure the safe buying

through internet.


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Limitations of the research:

As our study is an empirical study so it have many limitations. First of all the

sample size is very small due to lack of resources. Also the samples chosen are from only

some sectors of Islamabad city. So it does not represent the whole population effectively.

In order to get better and verified results the study should be conducted in other cities as

well.

Recommendation for future study:

The future researchers should include the moderating variables in the current

model to better understand the customer buying behavior. Also increase the number of

IVs.

Research Gap:

Future research can look into the persuasion effects of negative or neutral eWOM

and compare the result with positive electronic word of mouth. Also future research can

look into those factors which effects the source credibility.

Conclusion:

Source credibility and Privacy concerns are the factors that are effecting

significantly on the online customer buying behavior. Keeping in view these factors the

marketing managers should take actions to provide credible and trustworthy sources to

customers so that they can buy online without hesitation and also their privacy should

also be maintained.

The quantitative approach has been used for the correction of data by using the

instrument that is questionnaire. We applied descriptive analysis, one way ANOVA,


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Independent Sample t test, Regression and Correlation tests to determine the relation

between our IVs and DV. The results show that Source Credibility and Privacy Concerns

have deep effect on online buying behavior and Online brand image has no significant

effect on online buying behavior.

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