CHAPTER - 4 - Shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/45045/11/11_chapter4.pdf · The...

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CHAPTER – 4

ANALYSIS OF DATA

4.1 Introduction

This chapter provides the empirical findings on presenting the detailed analyses of

the data collected and the statistical results of the study. The chapter is divided into

three main sections.

The first section provides information on the profiles of the respondents and

descriptive statistics.

The second section provides preliminary analysis, which includes normality test,

reliability and validity.

The third section discusses hypothesis tests.

4.2 Profile of Respondents

Total 968 respondents were contacted. Data were collected from respondents in two

ways. They were requested to participate in the survey through a fill physical printout

of the questionnaire as well as questionnaire put online through online research

website. Sent request of online questionnaire through webpage link

by the way of

email and social networking website like Facebook, LinkedIn. The responses received

through online were 285 respondents (Annexture-3) were 19 responses were rejected

due to lack of sufficient information. The other approach was through a face-to-face

interview, approached 750 respondents and hence 702 respondents have accepted the

request and 48 have rejected the request. The reasons for rejecting the survey were

lack of interest, lack of time, lack of willingness etc. After collection of data, total 968

(702 Physical copy + 266 online) completely filled questionnaires were available for

the analysis. A detailed description of the respondents of this study is explained in

table 4.1.

In the questionnaire, six types of demographic information collected from the

respondents, namely, gender, age, education qualification, occupation and annual

family income. Out of the total respondents 55.3 % (535) were male and 44.7 percent

(433) were female. In case of age of respondents, 35 percent (339) of the respondents

Link for online questionnaire: https://qtrial.qualtrics.com/SE/?SID=SV_esuvSyJm4GGbzYp

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were in the age group of 12-18 years and 19-25 years, was followed by 43.7 percent

(423) respondents who were more than 26-35 years old, while 21.2 percent (206) of

the respondents were in the age group 36 -50 and more than 50 years. In terms of

annually family income out of 968 respondents, 10.1 percent (98) of respondents‟

family income were below ₹ 1 lac. Total 30.4 percent (294) respondents described

their income between ₹ 1 lac to ₹ 3 lac. Respondents whose family income between ₹

7 Lac to 12 Lac was 16.8 percent (163) from the sample. The remaining 4 percent

(39) of the respondents reported their annually family income as greater than ₹ 12 lac.

Table: 4.1 Demographic profiles of respondents

Profile of Respondents

Characteristics Measuring Variables Frequency Percentage

Gender

Male 535 55.3

Female 433 44.7

Total 968 100

Age

12 to18 years 29 3

19 to 25 years 310 32

26 to 35 years 423 43.7

36 to 50 years 193 19.9

More than 50 years 13 1.3

Total 968 100

Educational

Qualification

Up to HSC 121 12.5

Graduate 454 46.9

Post Graduate 372 38.4

Other 21 2.2

Total 968 100

Occupation

Business 88 9.1

Service 393 40.6

Professional 75 7.7

Student 226 23.3

Housewife 182 18.8

Other 04 0.4

Total 968 100

Annual Family

Income

Below Rs. 1 Lac 98 10.1

1 lac to 3 lac 294 30.4

3 Lac to 7 Lac 374 38.6

7 Lac to 12 Lac 163 16.8

More than 12 Lac 39 4.0

Total 968 100

Source: Primary data collected by the researcher

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In terms of education qualification, the majority of respondents had a

graduation and post graduation level degree. The sample consisted of 38.4 percent

(372) post graduate respondents. Total 46.9 percent (454) respondents were graduates,

whereas 12.5 percent (121) respondents had studied up to higher secondary and

hardly 2.2 percent (21) respondents had other qualification means the diploma holder,

I.T.I holder etc. The noticeable participation of graduate and post graduate

respondents was in this research.

In case of occupation, the 40.6 percent (393) of the respondents were

employees (Service) and 23.3 percent (226) were students of the total respondents. 9.1

percent (81) respondents were the occupation of business and seventy five (7.7%)

respondents were professionals. Whereas 18.8 % respondents (182) ware house wife

and merely four respondents were comes under another category means all are found

unemployed. The data were collected from major cities of Gujarat state. These cities

are Ahmedabad (250), Vadodara (175), Rajkot (175), Bhavnagar (90), Surat (160),

Mehsana (60), Himatnagar (58) etc.

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4.3 Source of information

Respondents were asked to source, where usually they got information regarding to

product or services. The question was asked in to multiple choice answers among

given various options.

Table: 4.2 Frequency of sources of information

Source of Information Frequency Percentage

Television 884 91.32

Magazine 355 36.67

Newspaper 733 75.72

Hoardings 408 42.15

Internet 556 57.44

In store display 262 27.07

Radio 167 17.25

Neighbor 194 20.04

Friend 538 55.58

Colleague 251 25.93

Direct mail 123 12.71

Social networking 353 36.47

Other 33 3.41


From above table 4.2, it has been found that 91.32% (884) respondents got

information from television while second most preferable source was newspaper.

Total thirteen sources were given, and among them four sources named television,

newspaper, internet and friends were playing a major role (more than 50%) for

accessing information. Here noticeable source is social media (36.47 %). Due to the

penetration and popularity of FM radio stations, out of the total 17.25% of

respondents got information, where as hoarding was 42.15 %. At last magazine

(36.67%) and neighbor (20.04%) identified as a source of information.

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4.4 Identification of Product categories endorsed by celebrities

Table: 4.3 Identification of Product categories endorsed by celebrity

FMCG

Category Product category Yes % No %

Household Care Detergent Powder/Soap 683 70.6 285 29.4

Home cleaning 517 53.4 451 46.6

Personal Care

Oral Care 731 75.5 237 24.5

Skin Care 796 82.2 172 17.8

Hair Care 807 83.4 161 16.6

Foods

Bakery products 575 59.4 393 40.6

Snack food 652 67.4 316 32.6

Chocolates 700 72.3 268 27.7

Beverages Tea 633 65.4 335 34.6

Soft drinks 712 73.6 256 26.4

Insurance Life Insurance 529 54.6 439 45.4


Respondents were asked to identify celebrity endorsement across various product

categories which were given in to tabular form in the questionnaire. If they remember

any of the celebrity endorsement in relevant product categories then ticks on „Yes‟

otherwise tick on „No‟. From the data interpretation, it is found that 83.4% (807)

respondents identify as celebrity endorsed Hair care related products. The major

categories identified by respondents were detergent powder/soap, oral care, skin care,

chocolates and soft drink.

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4.5 Identification of Product categories endorsed by non-celebrity

Table: 4.4 Identification of Product categories known by the respondents by

Non-celebrity

FMCG

Category Product category Yes % No %

Household Care Detergent Powder/Soap 574 59.6 394 40.7

Home cleaning 597 61.7 371 38.3

Personal Care

Oral Care 605 62.5 363 37.5

Skin Care 532 55.0 436 45.0

Hair Care 586 60.5 382 39.5

Foods

Bakery products 577 59.6 391 40.4

Snack food 623 64.4 345 35.6

Chocolates 642 66.3 326 33.7

Beverages Tea 591 61.1 377 38.9

Soft drinks 513 53.0 455 47.0

Insurance Life Insurance 663 68.5 305 31.5


In case of non-celebrity endorsement table 4.4, respondents were asked to identify

non-celebrity endorsement across various product categories given in to tabular form

in the questionnaire. If they remember any of the non-celebrity endorsement in

relevant category than tick on „Yes‟ otherwise „No‟. From data interpretation, it is

found that 68.5 (663) respondents identify as non-celebrity endorsed in the Insurance

category. The major categories identified by respondents were Home cleaning, Oral

care, Hair care, Snack food, chocolates, Tea and Insurance.

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4.6 Liking of advertisement endorsed by celebrity and Non-celebrity

Table: 4.5 Liking of advertisement of product categories

Category Advertisement Frequency Percentage

Detergent

powder/soap

Celebrity (Salman Khan) 380 39.3

Non Celebrity 588 60.7

Home cleaning Celebrity (Hussain) 590 61.0


Oral Care Celebrity (Shahrukh Khan) 471 48.7


Skin Care Celebrity (Aishwarya Rai) 666 68.8


Hair Care Celebrity (Katrina Kaif) 697 72.0


Bakery products Celebrity (Amitabh Bachchhan) 342 35.3


Snack food Celebrity (Parineeti Chopra) 694 71.7


Chocolates Celebrity (Katrina Kaif) 455 47.0


Tea Celebrity (Saif Ali Khan) 522 53.9


Soft drinks Celebrity (MS Dhoni) 684 70.7


Life Insurance Celebrity (Sachin Tendulkar) 342 35.3


Mobile Handset Celebrity (Priyanka Chopra) 674 69.6



Respondents have to give their choice for advertisement from the pair of

advertisement (celebrity and non-celebrity) for each product category. The selection

of advertisement for this research is based on screening of all the advertisements,

including print advertisements as well as a television commercial. The list of

advertisements given in annexture-1, from this pair, I have selected those

advertisements having a maximum frequency of appearance in the TVC and print

media. According to Sherman (1985), approximately 20 percent of all television

advertisements include famous people and approximately 10 percent of the money

spent on television advertisements are used on celebrity endorsements. Table 4.5,

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showing choice of advertisement from the pair of advertisement given in

questionnaire.

For non-celebrity endorsed products, Bakery products have highest liking of

64.7%, followed by life insurance (64.7%). Where as In the Detergent powder/soap

category 60.7 % responded likes. The celebrity advertisement likes by respondents

under categories of Home cleaning (61%, famous TV star Hussein endorse Harpic

brand toilet cleaner), Skin care (68.8%, Aishwarya Rai endorse L‟oreal skin cream).

Further Hair care category is highest for liking of celebrity endorsed advertisement

(72%, Ketrina Kaif endorse Pentene brand shampoo), Snack food (71.7%, Parneeti

Chopra endorse Kurkure), Tea (53.9%, Saif Ali khan endorse Tajmahal Tea), Soft

drink (70.7%, M.S. Dhoni endorse Pepsi) and Mobile handset (69.6%, Priyanka

Chopra endorse the Sony brand).

4.7 Descriptive Statistics

The mean and standard deviation were calculated for all the intervals scaled items.

These are reported in table 4.6 along with the skewness and kurtosis of these items.

The results indicated that the responses to the variables had a good dispersion on the

scales.

Table 4.6 Descriptive Statistics of celebrity and Non-celebrity’s characteristics

Constructs Items N Mean Std.

Deviation Skewness Kurtosis

Celebrity‟s

Physical

Attractiveness

Beautiful 968 6.01 1.410 -1.837 3.125

Elegant 968 5.36 1.367 -0.984 0.938

Sexy 968 5.22 1.748 -0.879 -0.183

Pleasant 968 5.50 1.528 -1.062 0.591

Celebrity‟s

Trustworthiness

Dependable 968 5.16 1.703 -0.924 0.122

Honest 968 5.42 1.725 -1.047 0.122

Reliable 968 5.40 1.595 -0.981 0.286

Sincere 968 5.32 1.661 -0.852 -0.025

Believable 968 5.21 1.747 -0.865 -0.242

Having A Good

Reputation 968 5.66 1.660 -1.296 0.812

Celebrity‟s

Expertise

Experienced 968 5.57 1.646 -1.190 0.644

Knowledgeable 968 5.50 1.612 -1.112 0.513

Qualified 968 5.26 1.577 -0.898 0.119

Skilled 968 5.47 1.508 -1.052 0.448

Professional 968 5.51 1.537 -1.111 0.769

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Constructs Items N Mean Std.


Celebrity‟s

Likability

Familiar 968 5.60 1.514 -1.211 1.002

Similar 968 5.27 1.450 -0.973 0.648

I can relate 968 4.95 1.705 -0.764 -0.085

Appropriate 968 5.10 1.562 -0.762 -0.070

Logical 968 4.95 1.581 -0.589 -0.193

Non-celebrity‟s

Physical

Attractiveness

Beautiful 968 5.41 1.692 -0.990 -0.026

Elegant 968 5.07 1.635 -0.596 -0.029

Sexy 968 4.82 1.823 -0.460 -0.833

Pleasant 968 5.10 1.727 -0.655 -0.512

Non-celebrity‟s

Trustworthiness

Dependable 968 4.82 1.751 -0.645 -0.537

Honest 968 4.94 1.792 -0.591 -0.698

Reliable 968 4.80 1.798 -0.459 -0.825

Sincere 968 4.88 1.832 -0.491 -0.879

Believable 968 4.85 1.841 -0.492 -0.877

Having A Good

Reputation 968 4.82 1.841 -0.446 -0.967

Non-celebrity‟s

Expertise

Experienced 968 4.92 1.866 -0.589 -0.826

Knowledgeable 968 5.02 1.769 -0.565 -0.787

Qualified 968 4.86 1.707 -0.403 -0.836

Skilled 968 5.03 1.735 -0.537 -0.764

Professional 968 4.79 1.808 -0.424 -0.888

Non-celebrity‟s

Likability

Familiar 968 4.81 1.868 -0.556 -0.810

Similar 968 4.66 1.679 -0.492 -0.646

I can relate 968 4.44 1.751 -0.342 -0.849

Appropriate 968 4.64 1.680 -0.351 -0.796

Logical 968 4.51 1.728 -0.270 -0.956


Distribution of skewness is either symmetric or skewed. In a distribution, the values

on either side of the centre of the distribution are the same. The negative data

indicating a negative skew.

Kurtosis is measure of relative peakedness or flatness of the curve defined by

the frequency distribution. If the kurtosis is positive, than the distribution is more

peaked than a normal distribution. A negative value means that the distribution is

flatter than a normal distribution.

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Table 4.7 Descriptive Statistics of variables of effectiveness of celebrity.

Constructs Items

(Variables) N Mean

Std.


Celebrity

endorsement

effectiveness

(Q-7)

V1 968 4.30 0.933 -1.381 1.528

V2 968 3.20 1.210 -0.398 -0.751

V3 968 3.93 1.119 -0.807 -0.285

V4 968 3.40 1.263 -0.354 -0.872

V5 968 3.16 1.336 -0.259 -1.110

V6 968 3.23 1.259 -0.218 -0.955

V7 968 3.15 1.187 -0.305 -0.837

V8 968 3.25 1.083 -0.232 -0.446

V9 968 3.24 1.193 -0.220 -0.741

V10 968 2.93 1.317 0.058 -1.133

V11 968 3.80 1.184 -0.779 -0.254

V12 968 3.48 1.200 -0.487 -0.636

V13 968 3.58 1.138 -0.520 -0.472

V14 968 3.44 1.261 -0.561 -0.628

V15 968 3.39 1.336 -0.467 -0.926

V16 968 3.58 1.104 -0.413 -0.605

V17 968 2.77 1.328 0.010 -1.230

V18 968 3.09 1.295 -0.115 -1.034

V19 968 3.12 1.354 -0.127 -1.149

V20 968 3.29 1.307 -0.331 -0.959

V21 968 2.87 1.250 0.028 -0.953

V22 968 2.80 1.289 0.036 -1.036

V23 968 3.11 1.381 -0.187 -1.200

V24 968 3.78 1.155 -0.709 -0.367


The means of the sixty eight items were ranged satisfactorily from 6.01 to 2.77 with

standard deviations ranging from 0.933 to 1.868 on the 7-point and 5-point scales. As

it can be observed from the table 4.6, characteristics of celebrity, Non-celebrity and its

endorsement effectiveness are neutral. The one item under celebrity‟s physical

attractiveness has values greater than 6.0 which is the neutral value.

4.8 Measurement of Reliability and Validity

It is essential to examine the reliability and validity of the twenty four interval-scaled

items that measured the five constructs. The measurements of reliability and validity

are important steps in ensuring that the variables measure the relevant construct

exactly and accurately. The reliability is defined as an assessment of the degree of

consistency between multiple measurements of a variable (Hair et al., 2010).

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According to Sekaran (2003), the internal consistency of measures is an indication of

the homogeneity of the items which measure the same construct. The validity is the

extent to which a set of measuring variables accurately represents the concept of

interest (Hair et al., 2010). This test confirms if the multiple variables developed for a

construct rightly measure that construct. The measuring variables were developed and

tested in the literature. It remained necessary to test their reliability and validity,

especially in a new dataset. This might be helpful in validating the previous findings.

In this study reliability was tested using Cronbach‟s alpha and exploratory factor

analysis.

4.8.1 Reliability

Cronbach‟s alpha was used to test the reliability of the interval-scaled variables. It is

the most popular test of inter-item consistency, reliability, which is useful for

multipoint- scaled variables (Sekaran, 2003). The cutoff of reliability α is 0.70 (Hair

et al., 2010), hence the reliabilities ≥ 0.70 are acceptable. The results showed that all

eight constructs obtained acceptable reliabilities, which is more than 0.7, except one

case of celebrity‟s physical attractiveness had 0.673 which was accepted. The

constructs were described in the table 4.7 with the value of cronbach‟s alpha, which

indicates that the test of reliability approves the scale. From the below table 4.2 values

of cronbach‟s alpha it can be concluded that all the constructs of influencing

characteristics of celebrity and non-celebrity‟s Physical attractiveness,

Trustworthiness, Expertise and Likability were found reliable. The reliability of the

constructs also indicated that further analysis is possible.

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Table: 4.8 Reliability and Factor analysis for Celebrity and Non-celebrity.

Factor analysis for Celebrity

Constructs Items Cronbach’s Alpha Factor loading

Celebrity‟s

Physical

Attractiveness

Beautiful

0.673

0.780

Elegant 0.764

Sexy 0.610

Pleasant 0.708

Celebrity‟s

Trustworthiness

Dependable

0.873

0.575

Honest 0.856

Reliable 0.834

Sincere 0.823

Believable 0.818

Having A Good

Reputation 0.781

Celebrity‟s

Expertise

Experienced

0.858

0.753

Knowledgeable 0.860

Qualified 0.803

Skilled 0.852

Professional 0.729

Celebrity‟s

Likability

Familiar

0.833

0.757

Similar 0.791

I can relate 0.794

Appropriate 0.812

Logical 0.719

Factor analysis for Non-celebrity

Non-celebrity‟s

Physical

Attractiveness

Beautiful

0.840

0.822

Elegant 0.866

Sexy 0.775

Pleasant 0.830

Non-celebrity‟s

Trustworthiness

Dependable

0.917

0.732

Honest 0.876

Reliable 0.863

Sincere 0.876

Believable 0.861

Having A Good

Reputation 0.832

Non-celebrity‟s

Expertise

Experienced

0.911

0.819

Knowledgeable 0.892

Qualified 0.864

Skilled 0.873

Professional 0.853

Non-celebrity‟s

Likability

Familiar

0.894

0.795

Similar 0.856

I can relate 0.856

Appropriate 0.868

Logical 0.824


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4.8.2 Validity

A measurement scale has validity, if it measures what it is supposed to measure

(Aaker et al., 2009). Churchill et al., (2010) argue that at a minimum, a researcher

should establish that new measures developed have face validity, construct validity,

discriminant validity, convergent validity and nomological validity. Face validity is

the extent to which the content of the items is consistent with the construct definition,

based solely on the researcher‟s judgment. The face validity is invoked when it can be

argued that the measurement scale apparently reflects the content of the concept, it is

trying to measure (Aaker et al., 2009). In the pre-testing of the measures, the face

validity of the measurement scales was established. The construct validity is the

extent to which a set of measured variables actually represent the theoretical latent

construct they are designed to measure. It is made up of four components: convergent

validity, discriminant validity, nomological validity and construct reliability. The

convergent validity is the extent to which indicators of a specific construct “converge”

or share a high proportion of variance in common.

The discriminant validity establishes that a construct is truly distinct from

other constructs. The nomological validity is tested by examining whether or not the

correlations between the constructs in the measurement theory make sense. The

construct reliability is a measure of reliability and internal consistency based on the

square of the total of factor loadings for a construct (Churchill et al., 2010; Aaker et

al., 2009).

The factor analysis techniques can achieve their purposes from either an

exploratory or confirmatory perspective (Hair et al., 2010). The exploratory factor

analysis is an effective method to assess if the dimensions of a concept are strongly

associated with each other to represent that concept (Hair et al., 2010; Sekaran, 2003).

The exploratory factor analysis is often considered to be more appropriate and

conducted before confirmatory analysis. In this validity analysis, exploratory factor

analysis was adopted to confirm whether the different variables were loaded on the

right constructs. When applying exploratory factor analysis, there were three main

steps. The first step was to assess the appropriateness of applying this technique. The

second step was to conduct the factor extraction, while the third was to interpret factor

loadings among the multiple variables. In this study, four types of constructs/factors

(i) Celebrity‟s physical attractiveness, (ii) Trustworthiness, (iii) Expertise and (iv)

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Likability were tested with the help of total twenty items and using a 7 - point scale.

Therefore, factor analysis was conducted separately for all four main measurement

scales. Same scale was applicable to non-celebrity.

4.8.3 Exploratory Factor Analysis

Under descriptive analysis of research, the exploratory factor analysis was conducted

using the principal component method and Varimax rotation at the initial stage of

analysis using SPSS (Hair et al., 2010; Sekaran, 2003). The twenty items that derived

from the literature review and mentioned in chapter three, here table 4.9 showing

exploratory factor analyses. The exploratory factor analysis was applied first on

physical attractiveness, Trustworthiness, Expertise and Likability of celebrity.

In this study, the result of Bartlett‟s test of Sphericity (Chi-Square value 9565,

degree of freedom (df) 190, p value 0.000) and KMO (0.935) was found significant

and which indicate that the data were appropriate for factor analysis. In the analysis

only the factors having latent roots or eigenvalue greater than 1 were considered

significant. In this research, an orthogonal rotational method, namely, Varimax was

adopted. This method was chosen because, compared to other rotated methods, it is a

more useful means of reducing the variables to a smaller set of uncorrelated variables

for subsequent use in the regression technique, as well as to give a clearer separation

of the factors (Hair et al., 2010). According to Hair et al. (2010) the factor loadings

exceeding ±0.60 are considered practically significant.

As shown in table 4.9, each of the variables obtained a factor loading greater

than 0.6. The four factors were extracted during this stage of exploratory factor

analysis, accounted for 61.37 percent of the total variance. These four factors were

physical attractiveness, Trustworthiness, Expertise and Likability.

Table: 4.9 Exploratory Factor Analyses for celebrity

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. 0.935

Bartlett's Test of

Sphericity

Approx. Chi-Square 9565.550

df 190

Sig. 0.000

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Celebrity Attitude Factor Loadings Factor

Beautiful 0.780 PHYSICAL

ATTRACTIVENESS

Elegant 0.764

Sexy 0.610

Pleasant 0.708

Dependable 0.575

TRUSTWORTHINESS

Honest 0.856

Reliable 0.834

Sincere 0.823

Believable 0.818

Having A Good Reputation 0.781

Experienced 0.753

EXPERTISE

Knowledgeable 0.860

Qualified 0.803

Skilled 0.852

Professional 0.729

Familiar 0.757

LIKABILITY

Similar 0.791

I can relate 0.794

Appropriate 0.812

Logical 0.719


The second exploratory factor analysis was conducted for non-celebrity, comprising

of four constructs/items and twenty variables same as celebrity. As shown in table

4.10 the result of Bartlett‟s test of sphericity (Chi Square value 14760, df 190, p value

0.000) and KMO (0.965) were found significant and which indicated that the data

were appropriate for further factor analysis. The eigenvalue greater than 1 was

considered significant, and varimax rotation was conducted which resulted in factor

loadings greater than ±0.60. Total four factors were extracted during this stage of

exploratory factor analysis, accounted for 63.81 percent of the total variance.

Table: 4.10 Exploratory Factor Analyses for Non-celebrity.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. 0.965

Bartlett's Test of

Sphericity

Approx. Chi-Square 14760.125

df 190

Sig. 0.000

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Non-celebrity Attitude Factor Loadings Factor

Beautiful 0.822 PHYSICAL

ATTRACTIVENESS

Elegant 0.866

Sexy 0.775

Pleasant 0.830

Dependable 0.732

TRUSTWORTHINESS

Honest 0.876

Reliable 0.863

Sincere 0.876

Believable 0.861

Having A Good Reputation 0.832

Experienced 0.819

EXPERTISE

Knowledgeable 0.892

Qualified 0.864

Skilled 0.873

Professional 0.853

Familiar 0.795

LIKABILITY

Similar 0.856

I can relate 0.856

Appropriate 0.868

Logical 0.824


4.9 Multiple Regression Analysis of Factors affecting Celebrity Endorsement and

Celebrity Endorsement Effectiveness

In reference of first objective of research, the multiple regression analysis was

employed. Hypotheses developed regarding consumer perception for celebrity

endorsements in advertisements .The first four hypotheses designed with respect to

means score of twenty four statements related to effectiveness of celebrity

endorsement in advertisement (Question-7) as a dependent variable, the analysis

firstly investigates whether the data have met basic assumptions for applying multiple

regression analysis. Then presents the multiple regression analysis for celebrity‟s

characteristics. These are physical attractiveness, trustworthiness, expertise and

likability. Hair et al. (2010) considered linearity of relationships, constant variance of

residuals, and the normality of residual distribution essential assumptions underlying

multiple regression analysis, which can ensure that the results obtained from multiple

regression analysis are truly representative of the sample and that the best results are

deemed to be obtained. The partial regression plots and the constant variance support

the linearity. All these assumptions were all satisfactorily confirmed. The assumptions

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of linearity, constant variance and normality were statistically supported to employ

multiple regression analysis.

Dependent variable (Y): Effectiveness of celebrity endorsement in advertisement

Independent Variables (X): Factors affecting Celebrity Endorsement / Celebrity‟s

characteristics

For independent variables Physical Attractiveness, Trustworthiness, Likability and

expertise are taken one by one for regression analysis

According to Churchill et al. (2010) and Aaker et al. (2009) the equation in multiple

regression analysis has the following form:

Y = α + β1X1 + β2X2 + … + βnXn + ε

Where,

Y = the level of the dependent, or predicted, variable

α = the intercept or constant

β1 = the slope coefficient of the independent variable X1

X1 = the level of the independent variable X1

β2 = the slope coefficient of the independent variable X2

X2 = the level of the independent variable X2

βn = the slope coefficient of the independent variable Xm

Xn = the level of the independent variable Xm

n = the number of independent variables in the equation

ε = the random error associated with the prediction of Y

4.9.1 Hypothesis testing for celebrity endorsement effectiveness

H01a: There is no significant relationship between physical attractiveness of celebrity

and mean score of celebrity endorsement effectiveness.

H01b: There is no significant relationship between trustworthiness of celebrity and

mean score of celebrity endorsement effectiveness.

H01c: There is no significant relationship between expertise of celebrity and celebrity

mean score of endorsement effectiveness.

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H01d: There is no significant relationship between likability of celebrity and celebrity

mean score of endorsement effectiveness.

H01e: There is no significant relationship between physical attractiveness of non-

mean score of celebrity and celebrity endorsement effectiveness.

H01f: There is no significant relationship between trustworthiness of non-celebrity

and mean score of celebrity endorsement effectiveness.

H01g: There is no significant relationship between expertise of non-celebrity and


H01h: There is no significant relationship between likability of non-celebrity and


As shown in table 4.11 under the title of analysis of variance, this percentage was

statistically significant (F = 11.662, p<0.05). There was no threat of multicollinearity

among the predictor variables as the value of tolerance for each of the independent

variables was more than 0.2 and the VIF (Variance Inflation Factor) was less than 5

(Churchill et al., 2010).

Table: 4.11 Analysis of variance for celebrity endorsement effectiveness

Sum of

Squares Df

Mean

Square F

Sig.

(p value)

Regression 17.307 8 2.163

11.662 0.000 Residual 177.902 959 0.186

Total 195.210 967


As seen in the table 4.12, the intercept (identified as the constant) was significant at

the level of 0.05 (B=2.285; t=22.088). From all eight factors, only one regression

coefficients was statistically not significant (p < 0.05). This coefficient implied that

there is a significant relationship exists among celebrity‟s likability characteristics.

91

Table 4.12: Regression analyses for celebrity endorsement effectiveness

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.795 32.046 0.000 2.795

Celebrity's Physical

Attractiveness

0.017 0.042 1.182 0.238 0.764 1.308

Celebrity's

Trustworthiness

-0.022 -0.063 -1.277 0.202 0.386 2.592

Celebrity's Expertise -0.023 -0.064 -1.325 0.186 0.411 2.435

Celebrity's Likability 0.132 0.356 7.773 0.000 0.453 2.206

Non-celebrity's

Physical

Attractiveness

-0.015 -0.046 -1.095 0.274 0.533 1.875

Non-celebrity's

Trustworthiness

0.000 -0.001 -0.010 0.992 0.247 4.049

Non-celebrity's

Expertise

0.020 0.069 1.073 0.284 0.233 4.296

Non-celebrity's

Likability

-0.006 -0.020 -0.364 0.716 0.303 3.302

So, the hypothesis is there is a significant relationship between celebrity‟s likability

and means score of celebrity endorsement effectiveness. The positive beta shows

positive relationship.

4.9.2 Summary of Multiple Regression Analysis.

Table 4.13 Summary of hypotheses for celebrity endorsement effectiveness

Hypothesis statement Result

H01a

There is no significant relationship between physical

attractiveness of celebrity and mean score of celebrity

endorsement effectiveness.

Not rejected

H01b

There is no significant relationship between trustworthiness

of celebrity and mean score of celebrity endorsement

effectiveness.

Not rejected

H01c

There is no significant relationship between expertise of

celebrity and mean score of celebrity endorsement

effectiveness.

Not rejected

H01d

There is no significant relationship between likability of


effectiveness.

Rejected

92

Summary of multiple regression from above table 4.13, it is concluded that weather

celebrity or non-celebrity endorsement, Physical attractiveness, Trustworthiness and

Expertise characteristics might not play very important role but in case of celebrity‟s

likability was significantly influence the overall effectiveness of endorsement.

H01e

There is no significant relationship between physical

attractiveness of non-celebrity and mean score of celebrity


Not rejected

H01f

There is no significant relationship between trustworthiness

of non-celebrity and mean score of celebrity endorsement

effectiveness.

Not rejected

H01g

There is no significant relationship between expertise of non-


effectiveness.

Not rejected

H01h

There is no significant relationship between likability of non-


effectiveness.

Not rejected

93

4.10 t-Tests for effectiveness of celebrity on product preferences

t- Test is used to test a hypothesis stating that the mean scores on some variable will

be significantly different for two independent samples or groups. It is used when the

number of observations (sample size) is small and the population standard deviation is

unknown (Zikumnd pp. 506). Compares the means of one variable for two groups of

cases. Descriptive statistics for each group and Levene‟s test for equality of variances

are provided, as well as both equal- and unequal-variance t-values and a 95%

confidence interval for the difference in means. Here, t-test applied for celebrity and

non-celebrity endorser‟s characteristics and mean score of celebrity endorsement

effectiveness. The hypothesis test for the variables were conducted using t statistics

examination in case of two categorical groups (Churchill et al., 2010) and one way

ANOVA employed in case of more than two category groups (Malhotra, 2007;

Churchill et al., 2010). The hypothesis test for Gender, Age group, Education

qualification, Occupation and Family monthly income were conducted for

characteristics of celebrity and non-celebrity. The t test was conducted for gender and

one way ANOVA was employed by Age Group, Education, Qualification,

Occupation and Family monthly income.

4.10.1 Hypothesis for effectiveness of celebrity on product preferences

H02a: There is no significant difference between likening advertisement of fabric care

product and mean score of celebrity endorsement effectiveness.

Table 4.14: t-test for likening advertisement of fabric care product and mean

score of celebrity endorsement effectiveness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value

Equal variances assumed 0.140 0.709 1.299 966 0.194

Equal variances not assumed 1.282 772.910 0.200


As shown in Table 4.14: the t-test results indicate that there is no significant

difference found in likening of celebrity and non-celebrity endorser for advertisement

of fabric care product. Under the title of Levene‟s test for equality variances, the F

94

value was 0.140 with a Significance value of 0.709. The p value was not significant at

0. 194, indicating the perceived difference of celebrity endorsement effectiveness and

likening advertisement of fabric care product was not significant (p > 0.05). Thus,

hypothesis H02a was not rejected.

H02b: There is no significant difference between likening of advertisement of home

care product and mean score of celebrity endorsement effectiveness.

Table 4.15: t-test for likening advertisement of home care product and mean


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of home care product. Under the title of Levene‟s test for equality variances, the F


0.336, indicating the perceived difference of celebrity endorsement effectiveness and

likening advertisement of home care product was not significant (p > 0.05). Thus,

hypothesis H02b was not rejected.

H02c: There is no significant difference between likening advertisement of oral care


Table 4.16: t-test for likening advertisement of oral care product and mean score

of celebrity endorsement effectiveness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value




95



of oral care product. Under the title of Levene‟s test for equality variances, the F



likening advertisement of oral care product was not significant (p > 0.05). Thus,

hypothesis H02c was not rejected.

H02d: There is no significant difference between likening advertisement of skin care


Table 4.17: t-test for likening advertisement of skin care product and mean score


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of skin care product. Under the title of Levene‟s test for equality variances, the F


0.567, indicating the perceived difference of mean score of celebrity endorsement

effectiveness and likening advertisement of skin care product was not significant (p >

0.05). Thus, hypothesis H02d was not rejected.

96

H02e: There is no significant difference between likening advertisement of hair care


Table 4.18: t-test for likening advertisement of hair care product and mean score


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value

Equal variances assumed 2.239 0.135 -1.971 966 0.049

Equal variances not assumed 1.811 965.809 -2.034


As shown in Table 4.18: the t-test results indicate that there is a significant difference

found in likening of celebrity and non-celebrity endorser for advertisement of hair

care product. Under the title of Levene‟s test for equality variances, the F value was

2.239 with a Significance value of 0.135. The p value was significant at 0.049,

indicating the perceived difference of celebrity endorsement effectiveness and

likening advertisement of hair care product was significant (p < 0.05). Thus,

hypothesis H02e was rejected.

H02f: There is no significant difference between likening advertisement of bakery


Table 4.19: t-test for likening advertisement of bakery product and mean score


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of bakery product. Under the title of Levene‟s test for equality variances, the F value

97

was 0.102 with a Significance value of 0.750. The p value was not significant at


likening advertisement of bakery product was not significant (p > 0.05). Thus,

hypothesis H02f was not rejected.

H02g: There is no significant difference between likening advertisement of snack

food product and mean score of celebrity endorsement effectiveness.

Table 4.20: t-test for likening advertisement of snack food product and mean


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of snack food product. Under the title of Levene‟s test for equality variances, the F



likening advertisement of snack food product was not significant (p > 0.05). Thus,

hypothesis H02g was not rejected.

H02h: There is no significant difference between likening advertisement of chocolate


Table 4.21: t-test for likening advertisement of chocolate product and mean score


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value




98



of chocolate product. Under the title of Levene‟s test for equality variances, the F



likening advertisement of chocolate product was not significant (p > 0.05). Thus,

hypothesis H02h was not rejected.

H02i: There is no significant difference between likening advertisement of tea and


Table 4.22: t-test for likening advertisement of tea and mean score of celebrity


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of tea. Under the title of Levene‟s test for equality variances, the F value was 0.257

with a Significance value of 0.613. The p value was not significant at 0.277,


likening advertisement of tea was not significant (p > 0.05). Thus, hypothesis H02i

was not rejected.

99

H02j: There is no significant difference between likening advertisement of soft drink


Table 4.23: t-test for likening advertisement of soft drink product and mean


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value






of soft drink product. Under the title of Levene‟s test for equality variances, the F



likening advertisement of soft drink product was not significant (p > 0.05). Thus,

hypothesis H02j was not rejected.

H02k: There is no significant difference between likening advertisement of life

insurance and mean score of celebrity endorsement effectiveness.

Table 4.24: t-test for likening advertisement of life insurance and mean score of

celebrity endorsement effectiveness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





found in likening of celebrity and non-celebrity endorser for advertisement of life

insurance. Under the title of Levene‟s test for equality variances, the F value was

0.038 with a Significance value of 0.846. The p value was significant at 0.010,

100


likening advertisement of life insurance was significant (p < 0.05). Thus, hypothesis

H02k was rejected.

H02l: There is no significant difference between likening advertisement of mobile

handset and mean score of celebrity endorsement effectiveness.

Table 4.25: t-test for likening advertisement of mobile handset and mean score of


Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





found in likening of celebrity and non-celebrity endorser for advertisement of mobile

handset. Under the title of Levene‟s test for equality variances, the F value was 0.853

with a Significance value of 0.356. The t value was significant at 0.022, indicating the

perceived difference of celebrity endorsement effectiveness and likening

advertisement of mobile handset was significant (p < 0.05). Thus, hypothesis H02k

was rejected.

101

4.10.2 Summary of effectiveness of celebrity on product preferences

Table 4.26: Summary of effectiveness of celebrity on product preferences.


Hypothesis statement F-value P value Result

H02a There is no significant difference between likening

advertisement of fabric care product and mean score of


0.140 0.194 Not

Rejected

H02b There is no significant difference between likening of

advertisement home care product and mean score of


7.355 0.336 Not

Rejected

H02c There is no significant difference between likening

advertisement of oral care product and mean score of


0.748 0.071 Not

Rejected

H02d There is no significant difference between likening

advertisement of skin care product and mean score of


0.762 0.567 Not

Rejected

H02e There is no significant difference between likening

advertisement of hair care product and mean score of


2.239 0.049 Rejected.

H02f There is no significant difference between likening

advertisement of bakery product and mean score of


0.102 0.079 Not

Rejected

H02g There is no significant difference between likening

advertisement of snack food product and mean score of


0.622 0.097 Not

Rejected

H02h There is no significant difference between likening

advertisement of chocolate and mean score of celebrity


9.546 0.068 Not

Rejected

H02i There is no significant difference between likening

advertisement of tea and mean score of celebrity


0.257 0.277 Not

Rejected

H02j There is no significant difference between likening

advertisement of soft drink product and mean score of


0.038 0.118 Not

Rejected

H02k There is no significant difference between likening

advertisement of life insurance and mean score of

celebrity endorsement effectiveness

3.745 0.010 Rejected.

H02l There is no significant difference between likening

advertisement of mobile handset and mean score of


0.853 0.022 Rejected.

102

4.11 t-Tests for Demographic Factors

H03a: There is no significance difference between gender group and celebrity‟s

physical attractiveness.

Table: 4.27 t-test for gender group and celebrity’s physical attractiveness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value


Equal variances not assumed -1.195 958.328 0.232


As shown in Table 4.27 the t-test results indicate that there is no significant difference

between a gender of the respondents and celebrity‟s physical attractiveness. Under the

title of Levene‟s test for equality variances, the F value was 3.257 with a Significance

value of 0.071. This value indicated that the variances of celebrity‟s physical

attractiveness were not equally distributed both groups of male and female. The t

value (-1.180) was not significant at 0.238, indicating the mean difference between

the male and female groups by celebrity‟s physical attractiveness was not significant

(p > 0.05). Thus, hypothesis H03a was not rejected.

H03b: There is no significance difference between gender group and celebrity‟s

trustworthiness.

Table: 4.28 t-tests for gender group and celebrity’s trustworthiness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value




As shown in Table 4.28 the t-test results indicate that there is a significant difference

between a gender of the respondents and celebrity‟s trustworthiness. Under the title of

Levene‟s test for equality variances, the F value was 3.073 with a Significance value

of 0.080. The t value (-4.451) was significant at 0.000, indicating the mean difference

103

between the male and female groups by celebrity‟s trustworthiness was significant (p

< 0.05). It indicates that the respondents view regarding celebrity‟s trustworthiness

was associated by gender wise. Thus, hypothesis H03b was rejected.

H03c: There is no significance difference between gender group and celebrity‟s

expertise.

Table: 4.29 t-tests for gender group and celebrity’s expertise.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





between a gender of the respondents and celebrity‟s expertise. Under the title of


of 0.130. This value indicated that the variances of celebrity‟s expertise were not

equally distributed both groups of male and female. The t value (0.130) was

significant at 0.000, indicating the mean difference between the male and female

groups by celebrity‟s expertise was significant (p < 0.05). It indicates that the

respondents view regarding celebrity‟s expertise was associated by gender wise. Thus,

hypothesis H03c was rejected.

H03d: There is no significance difference between gender group and celebrity‟s

likability.

Table: 4.30 t-test for Gender and celebrity’s likability.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value




104


between a gender of the respondents and celebrity‟s likability. Under the title of


of 0.408. This value indicated that the variances of celebrity‟s likability were not

equally distributed both groups of male and female. The t value (-4.448) was


groups by celebrity‟s likability was significant (p < 0.05). It indicates that the

respondents view regarding celebrity‟s likability was associated with gender. Thus,

hypothesis H03d was rejected.

H03e: There is no significance difference between gender group and non-celebrity‟s


Table: 4.31 t-test for Gender group and non-celebrity’s physical attractiveness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





between a gender of the respondents and non-celebrity‟s physical attractiveness

characteristics. Under the title of Levene‟s test for equality variances, the F value was

1.428 with a Significance value of 0.232. This value indicated that the variances of

non-celebrity‟s physical attractiveness were not equally distributed both groups of

male and female. The t value (-2.215) was significant at 0.027, indicating the mean

difference between the male and female groups by non-celebrity‟s physical

attractiveness was significant (p < 0.05). It indicates that the respondents view

regarding non-celebrity‟s physical attractiveness was associated gender wise. Thus,

hypothesis H03e was rejected.

105

H03f: There is no significance difference between gender group and non-celebrity‟s

trustworthiness.

Table: 4.32 t-test for Gender group and non-celebrity’s trustworthiness.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





between a gender of the respondents and non-celebrity‟s trustworthiness. Under the

title of Levene‟s test for equality variances, the F value was 6.539 with a Significance

value of 0.011. This value indicated that the variances of non-celebrity‟s

trustworthiness were not equally distributed both groups of male and female. The t

value (-2.034) was significant at 0.042, indicating the mean difference between the

male and female groups by non-celebrity‟s trustworthiness was significant (p <

0.05).n Thus, hypothesis H03f was rejected.

H03g: There is no significance difference between gender group and non-celebrity‟s

expertise.

Table: 4.33 t-test for Gender group and Non-celebrity’s expertise.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





between a gender of the respondents and non-celebrity‟s expertise. Under the title of


of 0.000. This value indicated that the variances of non-celebrity‟s expertise were

equally distributed both groups of male and female. The t value (-1.588) was not


groups by Non-celebrity‟s expertise was not significant (p > 0.05). It indicates that the

106

respondents view regarding non-celebrity‟s expertise was not associated gender wise.

Thus, hypothesis H03g was not rejected.

H03h: There is no significance difference between gender group and non-celebrity‟s

likability.

Table: 4.34 t-test for Gender group and non-celebrity’s likability.

Levene's Test for

Equality of

Variances

Sig. t-test

value Df p value





between a gender of the respondents and non-celebrity‟s likability characteristics.

Under the title of Levene‟s test for equality variances, the F value was 9.295 with a

Significance value of 0.002. This value indicated that the variances of non-celebrity‟s

likability were equally distributed both groups of male and female. The t value (-

1.040) was not significant at 0.299, indicating the mean difference between the male

and female groups by non-celebrity‟s likability was not significant (p > 0.05). It

indicates that the respondents view regarding non-celebrity‟s likability was not

associated with gender wise. Thus, hypothesis H03h was not rejected.

107

4.11.1 Summary of t-Tests for Demographic Factors by celebrity and non-

celebrity’s characteristics:

The hypothesis test of the gender demographic variable and celebrity / non-celebrity‟s

characteristics and factor of effectiveness in the advertisement was concluded.

Table: 4.35 Summary of t-Tests for demographic factors by celebrity and non-

celebrity’s characteristics.

Hypothesis statement F-value P value Result

H03a There is no significance difference between gender

group and celebrity‟s physical attractiveness. 3.257 0.238

Not

Rejected

H03b There is no significance difference between gender

group and celebrity‟s trustworthiness. 3.073 0.000 Rejected

H03c There is no significance difference between gender

group and celebrity‟s expertise. 2.296 0.000 Rejected

H03d There is no significance difference between gender

group and celebrity‟s likability. 0.686 0.000 Rejected

H03e There is no significance difference between gender

group and non-celebrity‟s physical attractiveness. 1.428 0.027 Rejected

H03f There is no significance difference between gender

group and non-celebrity‟s trustworthiness. 6.539 0.042 Rejected

H03g There is no significance difference between gender

group and non-celebrity‟s expertise. 20.185 0.113

Not

Rejected

H03h There is no significance difference between gender

group and non-celebrity‟s likability. 9.295 0.299

Not

Rejected

108

4.12 ANOVA test for Age group and celebrity / non-celebrity’s characteristics

H04a: There is no significance difference in mean scores of different age group in

case of celebrity‟s physical attractiveness.

Table 4.36: ANOVA test for age groups and celebrity’s physical attractiveness.

ANOVA

Sum of Squares df Mean Square F Sig.

Between Groups 31.062 4 7.766

6.817 0.000 Within Groups 1097.016 963 1.139

Total 1128.079 967


The results of the one-way ANOVA are shown in table 4.36, The F value with a

significance value of 0.000 indicated mean differences among the age groups were

significant (p < 0.05). Thus, hypothesis H04a was not accepted for given dataset. This

shows age group wise different perception among celebrity‟s physical attractiveness.

H04b: There is no significance difference in mean scores of different age group in

case of celebrity‟s Trustworthiness.

Table 4.37: ANOVA test for age group and celebrity’s trustworthiness.

ANOVA



1.596 0.173 Within Groups 1660.776 963 1.725

Total 1671.784 967




not significant (p > 0.05). Thus, hypothesis H04b was accepted for dataset. This shows

age group wise perception for celebrity‟s trustworthiness was same.

109

H04c: There is no significance difference in mean scores of different age group in

case of celebrity‟s Expertise.

Table 4.38: ANOVA test for age group and celebrity’s expertise.

ANOVA



1.184 0.316 Within Groups 1527.661 963 1.586

Total 1535.176 967




not significant (p > 0.05). Thus, hypothesis H04c was accepted for given dataset. This

shows age group wise perception for celebrity‟s expertise was same.

H04d: There is no significance difference in mean scores of different age group in

case of celebrity‟s Likability.

Table 4.39: ANOVA test for age group and celebrity’s likability.

ANOVA



2.118 0.077 Within Groups 1405.486 963 1.459

Total 1417.851 967




not significant (p > 0.05). Thus, hypothesis H04d was accepted for given dataset. This

shows age wise perception for celebrity‟s likability was same.

110

H04e: There is no significance difference in mean scores of different age group in

case of non-celebrity‟s physical attractiveness.

Table 4.40: ANOVA test for age group and non-celebrity’s physical

attractiveness.

ANOVA



0.893 0.468 Within Groups 1925.744 963 2.000

Total 1932.886 967




not significant (p > 0.05). Thus, hypothesis H04e was accepted for given dataset. This

shows age group wise perception for non-celebrity‟s physical attractiveness was

same.

H04f: There is no significance difference in mean scores of different age group in case

of non-celebrity‟s Trustworthiness.

Table 4.41: ANOVA test for age group and non-celebrity’s trustworthiness.

ANOVA



1.810 0.125 Within Groups 2220.915 963 2.306

Total 2237.610 967




not significant (p > 0.05). Thus, hypothesis H04f was accepted for given dataset. This

shows age group wise perception for non-celebrity‟s trustworthiness was same.

111

H04g: There is no significance difference in mean scores of different age group in

case of non-celebrity‟s Expertise.

Table 4.42: ANOVA test for age group and non-celebrity’s expertise.

ANOVA



1.205 0.307 Within Groups 2245.429 963 2.332

Total 2256.663 967




not significant (p > 0.05). Thus, hypothesis H04g was accepted for given dataset. This

shows age group wise perception for non-celebrity‟s expertise was same.

H04h: There is no significance difference in mean scores of different age group in

case of non-celebrity‟s Likability.

Table 4.43: ANOVA test for age group and non-celebrity’s likability.

ANOVA



2.703 0.029 Within Groups 2041.226 963 2.120

Total 2064.140 967




significant (p < 0.05). Thus, hypothesis H04h was not accepted for given dataset. This

shows age group wise different perception among non-celebrity‟s likability.

112

4.13 ANOVA test for Educational groups and Celebrity / non-celebrity’s

characteristics.

H05a: There is no significance difference in mean scores of different educational

group in case of celebrity‟s physical attractiveness.

Table 4.44: ANOVA test for educational groups and celebrity’s physical

attractiveness.

ANOVA



8.240 0.000 Within Groups 1099.876 964 1.141

Total 1128.079 967



significance value of 0.000 indicated mean differences among the educational groups

were significant (p < 0.05). Thus, hypothesis H05a was not accepted for given dataset.

This shows educational groups wise perception for celebrity‟s physical attractiveness

was different.

H05b: There is no significance difference in mean scores of different educational

group in case of celebrity‟s Trustworthiness.

Table 4.45: ANOVA test for educational groups and celebrity’s trustworthiness.

ANOVA



7.338 0.000 Within Groups 1634.460 964 1.695

Total 1671.784 967




were significant (p < 0.05). Thus, hypothesis H05b was not accepted for given dataset.

This shows educational groupd wise perception for celebrity‟s trustworthiness was

different.

113

H05c: There is no significance difference in mean scores of different educational

group in case of celebrity‟s Expertise.

Table 4.46: ANOVA test for educational groups and celebrity’s expertise.

ANOVA



10.898 0.000 Within Groups 1484.819 964 1.540

Total 1535.176 967




were significant (p < 0.05). Thus, hypothesis H05c was not accepted for given dataset.

This shows educational groups wise perception for celebrity‟s expertise was different.

H05d: There is no significance difference in mean scores of different educational

group in case of celebrity‟s Likability.

Table 4.478: ANOVA test for educational groups and celebrity’s likability.

ANOVA



1.991 0.114 Within Groups 1409.118 964 1.462

Total 1417.851 967




were not significant (p > 0.05). Thus, hypothesis H05d was accepted for given dataset.

This shows educational group wise perception for celebrity‟s likability was not

different.

114

H05e: There is no significance difference in mean scores of different educational

group in case of non-celebrity‟s physical attractiveness.

Table 4.48: ANOVA test for educational groups and non-celebrity’s physical

attractiveness.

ANOVA



0.810 0.489 Within Groups 1928.028 964 2.000

Total 1932.886 967




were not significant (p > 0.05). Thus, hypothesis H05e was accepted for given dataset.

This shows educational group wise perception for non-celebrity‟s physical

attractiveness was not different.

H05f: There is no significance difference in mean scores of different educational

group in case of non-celebrity‟s Trustworthiness.

Table 4.49: ANOVA test for educational groups and non-celebrity’s

trustworthiness.

ANOVA



1.358 0.254 Within Groups 2228.194 964 2.311

Total 2237.610 967




were significant (p > 0.05). Thus, hypothesis H05f was accepted for given dataset.

This shows educational group wise perception for non-celebrity‟s trustworthiness was

not different.

115

H05g: There is no significance difference in mean scores of different educational

group in case of non-celebrity‟s Expertise.

Table 4.50: ANOVA test for educational groups and non-celebrity’s expertise.

ANOVA



0.696 0.554 Within Groups 2251.782 964 2.336

Total 2256.663 967




were not significant (p > 0.05). Thus, hypothesis H05g was accepted for given dataset.

This shows educational group wise perception for non-celebrity‟s expertise was not

different.

H05h: There is no significance difference in mean scores of different educational

group in case of non-celebrity‟s Likability.

Table 4.51: ANOVA test for educational groups and non-celebrity’s likability.

ANOVA


Between Groups .742 3 0.247

0.116 0.951 Within Groups 2063.398 964 2.140

Total 2064.140 967




were not significant (p > 0.05). Thus, hypothesis H05h was accepted for given dataset.

This shows educational group wise perception for non-celebrity‟s likability was not

different.

116

4.14 ANOVA test for occupational groups and Celebrity / non-celebrity’s

characteristics.

H06a: There is no significance difference in mean scores of different occupational

group in case of celebrity‟s physical attractiveness.

Table 4.52: ANOVA test for occupational groups and celebrity’s physical

attractiveness.

ANOVA



4.870 0.000 Within Groups 1100.230 962 1.144

Total 1128.079 967



significance value of 0.000 indicated mean differences among the occupational

groups were significant (p < 0.05). Thus, hypothesis H06a was not accepted for given

dataset. This shows occupational group wise perception for celebrity‟s physical

attractiveness was different.

H06b: There is no significance difference in mean scores of different occupational

group in case of celebrity‟s Trustworthiness.

Table 4.53: ANOVA test for occupational groups about celebrity’s

trustworthiness.

ANOVA



6.452 0.000 Within Groups 1617.542 962 1.681

Total 1671.784 967




groups were significant (p < 0.05). Thus, hypothesis H06b was not accepted for given

dataset. This shows occupational group wise perception for celebrity‟s trustworthiness

was different.

117

H06c: There is no significance difference in mean scores of different occupational

group in case of celebrity‟s Expertise.

Table 4.54: ANOVA test for occupational groups and celebrity’s expertise.

ANOVA



5.560 0.000 Within Groups 1492.061 962 1.551

Total 1535.176 967




groups were significant (p < 0.05). Thus, hypothesis H06c was not accepted for given

dataset. This shows occupational group wise perception for celebrity‟s expertise was

different.

H06d: There is no significance difference in mean scores of different occupational

group in case of celebrity‟s Likability.

Table 4.55: ANOVA test for occupational groups and celebrity’s likability.

ANOVA



4.134 0.001 Within Groups 1388.029 962 1.443

Total 1417.851 967




groups were significant (p < 0.05). Thus, hypothesis H06d was not accepted for given

dataset. This shows occupational group wise perception for celebrity‟s likability was

different.

118

H06e: There is no significance difference in mean scores of different occupational

group in case of non-celebrity‟s physical attractiveness.

Table 4.56: ANOVA test for occupational groups and non-celebrity’s physical

attractiveness.

ANOVA



1.471 0.197 Within Groups 1918.219 962 1.994

Total 1932.886 967




groups were not significant (p > 0.05). Thus, hypothesis H06e was accepted for given

dataset. This shows occupation wise perception for non-celebrity‟s physical

attractiveness was not different.

H06f: There is no significance difference in mean scores of different occupational

group in case of non-celebrity‟s Trustworthiness.

Table 4.57: ANOVA test for occupational groups and non-celebrity’s

trustworthiness.

ANOVA



1.762 0.118 Within Groups 2217.304 962 2.305

Total 2237.610 967




groups were not significant (p > 0.05). Thus, hypothesis H06f was accepted for

dataset. This shows occupation wise perception for non-celebrity‟s trustworthiness

was not different.

H06g: There is no significance difference in mean scores of different occupational

group in case of non-celebrity‟s Expertise.

119

Table 4.58: ANOVA test for occupational groups and non-celebrity’s expertise.

ANOVA



1.531 0.177 Within Groups 2238.846 962 2.327

Total 2256.663 967




groups were not significant (p > 0.05). Thus, hypothesis H06g was accepted for

dataset. This shows occupation wise perception for non-celebrity‟s expertise was not

different.

H06h: There is no significance difference in mean scores of different occupational

group in case of non-celebrity‟s Likability.

Table 4.59: ANOVA test for occupational groups and non-celebrity’s likability.

ANOVA



1.537 0.176 Within Groups 2047.781 962 2.129

Total 2064.140 967




groups were not significant (p > 0.05). Thus, hypothesis H06h was accepted for given

dataset. This shows occupational group wise perception for non-celebrity‟s likability

was not different.

120

4.15 ANOVA test for Income groups and Celebrity / non-celebrity’s

characteristics.

H07a: There is no significance difference in mean scores of different income group in

case of celebrity‟s physical attractiveness.

Table 4.60: ANOVA test for income groups and celebrity’s physical

attractiveness.

ANOVA



4.863 0.001 Within Groups 1105.741 963 1.148

Total 1128.079 967



significance value of 0.001 indicated mean differences among the income groups

were significant (p < 0.05). Thus, hypothesis H07a was not accepted for given dataset.

This shows income group wise perception for celebrity‟s physical attractiveness was

different.

H07b: There is no significance difference in mean scores of different income group in

case of celebrity‟s Trustworthiness.

Table 4.61: ANOVA test for income groups and celebrity’s trustworthiness.

ANOVA



7.717 0.000 Within Groups 1619.861 963 1.682

Total 1671.784 967




were significant (p < 0.05). Thus, hypothesis H07b was not accepted for given dataset.

This shows income group wise perception for celebrity‟s trustworthiness was

different.

H07c: There is no significance difference in mean scores of different income group in

case of celebrity‟s Expertise.

121

Table 4.62: ANOVA test for income groups and celebrity’s expertise.

ANOVA



6.424 0.000 Within Groups 1495.276 963 1.553

Total 1535.176 967




were significant (p < 0.05). Thus, hypothesis H07c was not accepted for given dataset.

This shows income group wise perception for celebrity‟s expertise was different.

H07d: There is no significance difference in mean scores of different income group in

case of celebrity‟s Likability.

Table 4.63: ANOVA test for income groups and celebrity’s likability.

ANOVA



7.426 0.000 Within Groups 1375.424 963 1.428

Total 1417.851 967




were significant (p < 0.05). Thus, hypothesis H07d was not accepted for given dataset.

This shows income group wise perception for celebrity‟s likability was different.

H07e: There is no significance difference in mean scores of different income group in

case of non-celebrity‟s physical attractiveness.

Table 4.64: ANOVA test for income groups and non-celebrity’s physical

attractiveness.

ANOVA



0.258 0.905 Within Groups 1930.817 963 2.005

Total 1932.886 967




122

were not significant (p >0.05). Thus, hypothesis H07e was accepted for given dataset.

This shows income group wise perception for non-celebrity‟s physical attractiveness

was not different.

H07f: There is no significance difference in mean scores of different income group in

case of non-celebrity‟s Trustworthiness.

Table 4.65: ANOVA test for income groups and non-celebrity’s trustworthiness.

ANOVA



1.505 0.199 Within Groups 2223.707 963 2.309

Total 2237.610 967




were not significant (p >0.05). Thus, hypothesis H07f was accepted for given dataset.

This shows income group wise perception for non-celebrity‟s trustworthiness was not

different.

H07g: There is no significance difference in mean scores of different income group in

case of non-celebrity‟s Expertise.

Table 4.66: ANOVA test for income groups and non-celebrity’s expertise.

ANOVA



1.159 0.327 Within Groups 2245.847 963 2.332

Total 2256.663 967




were not significant (p >0.05). Thus, hypothesis H07g was accepted for given dataset.

This shows income group wise perception for non-celebrity‟s expertise was not

different.

123

H07h: There is no significance difference in mean scores of different income group in

case of non-celebrity‟s Likability.

Table 4.67: ANOVA test for income groups and non-celebrity’s likability.

ANOVA



1.832 0.121 Within Groups 2048.553 963 2.127

Total 2064.140 967




were not significant (p >0.05). Thus, hypothesis H07h was accepted for given dataset.

This shows income group wise perception for non-celebrity‟s likability was not

different.

Table 4.68: Summary of ANOVA test.

Hypothesis statement F P value Result

H04a

There is no significance difference in mean scores of

different age group in case of celebrity‟s physical

attractiveness.

6.817 0.000 Not

Accepted

H04b There is no significance difference in mean scores of

different age group in case of celebrity‟s Trustworthiness 1.596 1.730 Accepted

H04c There is no significance difference in mean scores of

different age group in case of celebrity‟s Expertise. 1.184 0.316 Accepted

H04d There is no significance difference in mean scores of

different age group in case of celebrity‟s Likability. 2.118 0.077 Accepted

H04e


different age group in case of non-celebrity‟s physical

attractiveness.

0.893 0.468 Accepted

H04f


different age group in case of non-celebrity‟s

Trustworthiness.


H04g There is no significance difference in mean scores of

different age group in case of non-celebrity‟s Expertise. 1.205 0.307 Accepted

124

H04h There is no significance difference in mean scores of

different age group in case of non-celebrity‟s Likability. 2.703 0.029

Not

Accepted

H05a


different educational group in case of celebrity‟s physical

attractiveness.

8.240 0.000 Not

Accepted

H05b


different educational group in case of celebrity‟s

Trustworthiness.

7.338 0.000 Not

Accepted


different educational group in case of celebrity‟s Expertise. 10.898 0.000

Not

Accepted

H05d There is no significance difference in mean scores of

different educational group in case of celebrity‟s Likability. 1.991 0.114 Accepted

H05e


different educational group in case of non-celebrity‟s



H05f



Trustworthiness.


H05g



Expertise.


H05h



Likability.


H06a


different occupational group in case of celebrity‟s physical

attractiveness.

4.870 0.000 Not

Accepted

H06b


different occupational group in case of celebrity‟s

Trustworthiness.

6.452 0.000 Not

Accepted


different occupational group in case of celebrity‟s Expertise. 5.560 0.000

Not

Accepted

125


H06d There is no significance difference in mean scores of different

occupational group in case of celebrity‟s Likability. 4.134 0.001

Not

Accepted

H06e

There is no significance difference in mean scores of different

occupational group in case of non-celebrity‟s physical

attractiveness.


H06f There is no significance difference in mean scores of different

occupational group in case of non-celebrity‟s Trustworthiness. 1.762 0.118 Accepted

H06g There is no significance difference in mean scores of different

occupational group in case of non-celebrity‟s Expertise. 1.531 0.177 Accepted

H06h There is no significance difference in mean scores of different

occupational group in case of non-celebrity‟s Likability. 1.537 0.176 Accepted

H07a There is no significance difference in mean scores of different

income group in case of celebrity‟s physical attractiveness. 4.863 0.001

Not

Accepted

H07b There is no significance difference in mean scores of different

income group in case of celebrity‟s trustworthiness. 7.717 0.000

Not

Accepted

H07c There is no significance difference in mean scores of different

income group in case of celebrity‟s Expertise. 6.424 0.000

Not

Accepted

H07d There is no significance difference in mean scores of different

income group in case of celebrity‟s Likability. 7.426 0.000

Not

Accepted

H07e

There is no significance difference in mean scores of different

income group in case of non-celebrity‟s physical

attractiveness.


H07f There is no significance difference in mean scores of different

income group in case of non-celebrity‟s Trustworthiness. 1.505 0.199 Accepted

H07g There is no significance difference in mean scores of different

income group in case of non-celebrity‟s Expertise. 1.159 0.327 Accepted

H07h There is no significance difference in mean scores of different

income group in case of non-celebrity‟s Likability. 1.832 0.121 Accepted

126

4.16 Multiple Regression Analysis for Purchase Behavior and characteristics of

celebrity and non-celebrity:

The previous section tested the hypothesis for demographic variables by

characteristics of celebrity and non-celebrity. This part of the analysis presents the

process of the multiple regression analysis on purchase behavior across different

product categories. Multiple regression analysis was employed to examine the

relationships in the hypotheses developed regarding celebrity and non celebrity‟s

physical attractiveness, trustworthiness, expertise and likability characteristics.

Another hypothesis relating to purchase behavior and advertisement effectiveness.

The products are Detergent, Home cleaning, Oral care, Skin care, Hair care, Bakery

products, Snack food, Chocolates, Tea, Soft drink and Life insurance.

4.16.1 Hypothesis test for purchasing behavior and Celebrity’s factors

H08a: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of detergent products.

Dependent Variable (Y): Purchasing behavior of products.

Independent Variable (X): Factors affecting celebrity endorsement.

For purchasing behavior of detergent products, as shown in the table 4.69 under the

title of analysis of variance, this percentage was statistically significant (F = 4.623,

p<0.05). There was no threat of multicollinearity among the predictor variables as the

value of tolerance for each of the independent variables was more than 0.2 and the

VIF (Variance Inflation Factor) was less than 5 (Churchill et al.,2010).

Table: 4.69 Analysis of variance for detergent products.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


4.623 0.001 Residual 688.397 963 0.715

Total 701.616 967



the level of 0.05 (B = 2.480; t = 15.388). From all four, only one regression

127

coefficients were statistically significant (p < 0.05). This coefficient implied that there

is a significant relationship exists between celebrity‟s expertise characteristics.

Table: 4.70 Regression analysis of detergent products.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.480 15.388 0.000


Attractiveness 0.030 0.038 1.064 0.287 0.784 1.275

Celebrity's

Trustworthiness 0.018 0.028 0.562 0.574 0.398 2.510


Celebrity's Likability 2.480 -0.004 -0.095 0.924 0.475 2.106


The standardized coefficient β (beta) can be used to compare directly the relative

effect of each independent variable on the dependent variable (Hair et al., 2010).

Among the four factors, likability had the highest beta score (β = 0.030, p >0.05),

which is not signifying. While, trustworthiness is not significant characteristics. (β = -

0.004, p >0.05). The negative beta of likability indicated that these construct had a

negative relationship with purchasing behavior of detergent product.

H08b: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of home cleaning products.

For purchasing behavior of home cleaning products, as shown in the table 4.71 under

the title of analysis of variance, this percentage was statistically significant (F=1.997,

p>0.05). There was a threat of multicollinearity among the predictor variables as the


VIF (Variance Inflation Factor) was less than 5 (Churchill et al., 2010).

Table: 4.71 Analysis of variance for home cleaning products.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


1.997 0.093 Residual 620.288 963 0.644

Total 625.434 967


128


the level of 0.05 (B=2.5460; t=16.643). From all four factors, none of regression

coefficients were statistically significant (p > 0.05). These coefficients implied that

there is no significant relationship exists between celebrity‟s characteristics. So, the

entire hypothesis was not rejected.

Table: 4.72 Regression analysis of home cleaning product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.546 16.643 0.000


Attractiveness 0.015 0.020 0.563 0.573

0.784 1.275

Celebrity's

Trustworthiness -0.018 -0.030 -0.586 0.558

0.398 2.510


Celebrity's Likability -0.012

-0.018 -0.378 0.706 0.475 2.106




Among the four constructs are not signifying.

H08c: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of oral care products.

For purchasing behavior of oral care products, as shown in the table 4.73 under the

title of analysis of variance, this percentage was statistically significant (F = 3.142,




Table: 4.73 Analysis of variance for oral care products.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


3.142 0.014 Residual 763.163 963 0.792

Total 773.124 967


129


the level of 0.05 (B=2.551; t=15.038). From all four characteristics, only one

regression coefficients were statistically significant (p < 0.05). This coefficient

implied that there is a significant relationship exists between celebrity‟s

trustworthiness characteristic. So, the hypothesis that the celebrity‟s only one

characteristic having relationship.

Table: 4.74 Regression analysis of oral care products.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.551 15.038 0.000


Attractiveness -0.002 -0.003 -0.078 0.938 0.784 1.275

Celebrity's

Trustworthiness -0.073 -0.108 -2.120 0.034 0.398 2.510






Among the four constructs, likability had the highest beta score (β = 0.006, p >0.05),

not signifying, on the purchasing behavior of the oral care product. While

Trustworthiness is signifying construct (β = -0.073, p <0.05). The negative beta of

likability indicated that these construct had a negative relationship with the oral care

product.

H08d: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of skin care products.

For purchasing behavior of skin care products, as shown in the table 4.75 under the

title of analysis of variance, this percentage was statistically significant (F=5.257,




130

Table: 4.75 Analysis of variance for skin care product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


5.257 0.000 Residual 823.727 963 0.855

Total 841.715 967




regression coefficients were statistically significant (p < 0.05). These coefficients

implied that there is a significant relationship exists between celebrity‟s

trustworthiness characteristics.

Table: 4.76 Regression analysis of skin care product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.645 15.005 0.000


Attractiveness 0.005 0.005 0.149 0.882 0.784 1.275

Celebrity's



Celebrity's Likability -0.001 -0.002 -0.037 0.970 0.475 2.106




Among the four factors, physical attractiveness had the highest beta score (β= 0.005, p

>0.05), which was not signifying and not influenced purchasing behavior of skin care

product. While Trustworthiness is signifying construct (β = -0.095, p <0.05). The

negative beta of likability indicated that these characteristic had a negative

relationship with the skin care product.

H08e: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of hair care products.

For purchasing behavior of hair care products, as shown in the table 4.77 under the

title of analysis of variance, this percentage was statistically significant (F=4.942,


131



Table: 4.77 Analysis of variance for hair care product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


4.942 0.001 Residual 809.883 963 0.841

Total 826.508 967





there is no significant relationship exists between celebrity‟s all four characteristics.

So all the four hypothesis were not rejected

Table: 4.78 Regression analysis of hair care product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.476 14.168 0.000


Attractiveness 0.045 0.053 1.473 0.141 0.784 1.275

Celebrity's







Among the four factors, physical attractiveness had the highest beta score (β = 0.045,

p >0.05), and not signifying, while Trustworthiness, expertise and likability were also

not signifying construct (β = -0.050, -0.031, -0.049 p >0.05). The negative beta of

likability indicated that these construct had a negative relationship with the hair care

product.

H08f: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of bakery products.

132

For purchasing behavior of bakery product, as shown in the table 4.79 under the title

of analysis of variance, this percentage was statistically significant (F = 3.484,



VIF (Variance Inflation Factor) was less than 5.

Table: 4.79 Analysis of variance for bakery product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


3.484 0.008 Residual 726.788 963 0.755

Total 737.306 967



the level of 0.05 (B = 2.352; t = 14.203). From all four factors, only one regression

coefficients were statistically significant (p < 0.05). This coefficient implied that there

is a significant relationship exists between celebrity‟s likability characteristics.

Table: 4.80 Regression analysis of bakery product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.352 14.203 0.000


Attractiveness 0.053 0.066 1.822 0.069 0.784 1.275

Celebrity's


Celebrity's Expertise 0.037 0.054 1.093 0.275 0.427 2.343





Among the four characteristics, physical attractiveness had the highest beta score (β =

0.053, p >0.05), this was not signifying and not influenced purchasing behavior of the

bakery products. While likability is signifying construct (β = -0.071 p <0.05). The

negative beta of likability indicated that this characteristic had a negative relationship

with the bakery product.

133

H08g: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of snack food.

For purchasing behavior of snack product, as shown in the table 4.81 under the title of

analysis of variance, this percentage was statistically not significant (F=2.326,

p>0.05). There was a threat of multicollinearity among the predictor variables as the


VIF (Variance Inflation Factor) was less than 5.

Table: 4.81 Analysis of variance for snack food.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.326 0.055 Residual 703.270 963 0.730

Total 710.065 967





there is no significant relationship exists between celebrity‟s factors. So all the four

hypotheses were not rejected

Table: 4.83 Regression analysis for snack food.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.519 15.468 0.000


Attractiveness 0.003 0.003 0.095 0.925 0.784 1.275

Celebrity's







Among the four characteristics, expertise characteristic had highest beta score (β =

0.003, p >0.05), which was not signifying and not influenced on purchasing behavior

of snack food. While Trustworthiness, and likability were also not signifying

134

characteristics (β = -0.044, -0.031 p >0.05). The negative beta indicated that these

construct had a negative relationship with the snack food.

H08h: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of chocolate product.

For purchasing behavior of chocolate product, as shown in the table 4.83 under the

title of analysis of variance, this percentage was statistically not significant

(F=1.554, p>0.05). There was a threat of multicollinearity among the predictor

variables as the value of tolerance for each of the independent variables was more

than 0.2 and the VIF (Variance Inflation Factor) was less than 5.

Table: 4.83 Analysis of variance for chocolate product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


1.554 0.185 Residual 664.898 963 0.690

Total 669.190 967





there is no significant relationship exists between celebrity‟s characteristics. So all the

four hypotheses were not rejected.

Table: 4.84 Regression analysis for chocolate product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.338 14.762 0.000


Attractiveness -0.019 -0.024 -0.665 0.506 0.784 1.275

Celebrity's







135

Among the four characteristics, expertise characteristic had the highest beta score

(β=0.023, p >0.05) which was not signifying and not influenced on purchasing

behavior of chocolate product. While Trustworthiness, expertise and likability were

also not signifying construct (β = -0.044, -0.018 p >0.05). The negative beta indicated

that these construct had a negative relationship with the chocolate product.

H08i: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of tea.

For purchasing behavior of tea, as shown in the table 4.85 under the title of analysis of

variance, this percentage was statistically significant (F=2.587, p<0.05).

Table: 4.85 Analysis of variance for tea product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.587 0.036 Residual 788.760 963 0.819

Total 797.236 967



the level of 0.05 (B = 2.192; t = 12.708). From all four factors, two of regression

coefficients were statistically significant (p<0.05). These coefficients implied that

there is significant relationship exists between celebrity‟s physical attractiveness and

expertise characteristics. So, two hypotheses were not rejected.

Table: 4.86 Regression analyses for tea product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.192 12.708 0.000


Attractiveness 0.064 0.076 2.110 0.035 0.784 1.275

Celebrity's








136

0.064, p<0.05) which was signifying and influenced on purchasing behavior of tea.

While Trustworthiness, and likability were not signifying characteristics (β = -0.035,

0.060 p >0.05).

H08j: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of soft drink.

For purchasing behavior of soft drink, as shown in the table 4.87 under the title of

analysis of variance, this percentage was statistically significant (F=2.547, p<0.05).

There was no threat of multicollinearity among the predictor variables as the value of

tolerance for each of the independent variables was more than 0.2 and the VIF

(Variance Inflation Factor) was less than 5.

Table: 4.87 Analysis of variance for soft drink product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.547 0.038 Residual 880.452 963 0.914

Total 889.768 967



the level of 0.05 (B=2.611; t=14.329). From all four characteristics, none of

regression coefficients were statistically significant (p >0.05). These coefficients

implied that there were no significant relationship exists between celebrity‟s all

characteristics. So all hypothesis were not rejected.

Table: 4.88 Regression analysis of soft drink product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.611 14.329 0.000


Attractiveness -0.002 -0.002 -0.054 0.957 0.784 1.275

Celebrity's





137



Among the four characteristics, likability characteristic had the highest beta score (β =

0.044, p>0.05), which was not signifying and not influenced on purchasing behavior

of soft drink.

H08k: There is no significant relationship between purchasing behaviors and

celebrity‟s characteristics in case of life insurance.

For purchasing behavior of life insurance, as shown in the table 4.89 under the title of

analysis of variance, this percentage was statistically significant (F=1.554, p<0.05).

There was a threat of multicollinearity among the predictor variables as the value of

tolerance for each of the independent variables was more than 0.2 and the VIF

(Variance Inflation Factor) was less than 5 (Churchill et al.,2010).

Table: 4.89 Analysis of variance for insurance.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


4.878 0.001 Residual 943.817 963 0.980

Total 962.942 967



the level of 0.05 (B=2.858; t=15.147). From all four characteristics, none of

regression coefficients were statistically significant (p > 0.05). These coefficients

implied that there is no significant relationship exists between celebrity‟s

characteristics. So all the four hypotheses were not rejected

Table: 4.90 Regression analysis for life insurance.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.858 15.147 0.000


Attractiveness 0.063 0.068 1.895 0.058 0.784 1.275

Celebrity's





138



Among the four factors, physical attractiveness had the highest beta score (β = 0.063,

p >0.05) which was not signifying and not influenced on purchasing behavior of life

insurance. While other characteristics were also not signifying (β = -0.005, -0.060, -

0.074 p >0.05). The negative beta indicated that these construct had a negative

relationship with the insurance.

4.16.2: Hypothesis test for purchasing behavior and non-celebrity’s

characteristics:

H09a: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of detergent product.

For purchasing behavior of detergent product for non-celebrity, as shown in the table

4.91 under the title of analysis of variance, this percentage was statistically not

significant (F = 0.802, p>0.05).

Table: 4.91 Analysis of variance for detergent product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)

Regression 4 0.582

0.802 0.524 Residual 699.287 963 0.726

Total 701.616 967



the level of 0.05 (B = 2.220; t = 20.226). From all four characteristics, none of the


implied that there is no significant relationship exists between non-celebrity‟s

characteristics. So the hypothesis that all the non-celebrity‟s characteristics were not

rejected.

139

Table: 4.92 Regression analyses for detergent product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.220 20.226 0.000

Non-celebrity's

Physical Attractiveness 0.021 0.034 0.787 0.431 0.552 1.813

Non-celebrity's


Non-celebrity's

Expertise -0.034 -0.061 -0.935 0.350 0.240 4.160

Non-celebrity's

Likability -0.008 -0.014 -0.252 0.801 0.317 3.153





0.021, p >0.05) which was not signifying and not influenced on purchasing behavior

of detergent. While Trustworthiness, expertise and likability were also not signifying

characteristics.

H09b: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of home cleaning product.

For purchasing behavior of home cleaning product for non-celebrity, as shown in the

table 4.93, under the title of analysis of variance, this percentage was not statistically

significant (F = 1.29, p>0.05). There was no threat of multicollinearity among the

predictor variables as the value of tolerance for each of the independent variables was

more than 0.2 and the VIF (Variance Inflation Factor) was less than 5 (Churchill et

al.,2010).

Table: 4.93 Analysis of variance for home cleaning product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


1.729 0.141 Residual 620.975 963 0.645

Total 625.434 967




140

regression coefficients was statistically significant (p < 0.05). This coefficient implied

that there is a significant relationship exists among non-celebrity‟s expertise

characteristic.

Table: 4.94 Regression analyses for home cleaning product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.285 22.088 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.082 -0.155 -2.368 0.018 0.240 4.160

Non-celebrity's

Likability 0.022 0.040 0.707 0.480 0.317 3.153


H09c: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of oral care product.

For purchasing behavior of oral care product for non-celebrity, as shown in the table





al.,2010).

Table: 4.95 Analysis of variance for oral care product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


0.539 0.707 Residual 771.396 963 0.801

Total 773.124 967



the level of 0.05 (B=2.558; t=19.589). From all four characteristics, none of the



characteristics. So, the entire hypotheses were not rejected.

141

Table: 4.96 Regression analysis for oral care product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.258 19.589 0.000

Non-celebrity's Physical

Attractiveness 0.001 0.001 0.025 0.980 0.552 1.813

Non-celebrity's


Non-celebrity's

Expertise -0.007 -0.011 -0.172 0.863 0.240 4.160

Non-celebrity's

Likability 0.004 0.006 0.110 0.912 0.317 3.153




Among the four characteristics, likability had the highest beta score (β = 0.004, p

>0.05), which was not signifying and not influenced on purchasing behavior of an

oral care product.

H09d: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of skin care product.

For purchasing behavior of skin care product for non-celebrity, as shown in the table

4.97 under the title of analysis of variance, this percentage was not statistically

significant (F = 1.251, p>0.05). There was a threat of multicollinearity among the



al.,2010).

Table: 4.97 Analysis of variance for skin care product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


1.251 0.288 Residual 837.365 963 0.870

Total 841.715 967



the level of 0.05 (B=2.215; t=18.441). From all four characteristics, none of the


142


characteristics. So, the entire hypotheses were not rejected.

Table: 4.98 Regression analyses for skin care product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.215 18.441 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.028 -0.046 -0.702 0.483 0.240 4.160

Non-celebrity's

Likability 0.048 0.075 1.310 0.190 0.317 3.153


H09e: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of hair care product.

For purchasing behavior of hair care product for non-celebrity, as shown in the table

4.99 under the title of analysis of variance, this percentage was statistically significant

(F=2.509, p<0.05). There was no threat of multicollinearity among the predictor


than 0.2 and the VIF (Variance Inflation Factor) was less than 5 (Churchill et

al.,2010).

Table: 4.99 Analysis of variance for hair care product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.509 0.041 Residual 817.985 963 0.849

Total 826.508 967



the level of 0.05 (B=2.218; t=18. 681). From all four, none of regression coefficients

were statistically significant (p > 0.05). These coefficients implied that there is no

significant relationship exists between non-celebrity‟s characteristics. So all the four


143

Table: 4.100 Regression analysis for hair care product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.218 18.681 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.044 -0.072 -1.101 0.271 0.240 4.160

Non-celebrity's

Likability 0.014 0.022 0.384 0.701 0.317 3.153





0.043, p >0.05), While Trustworthiness, expertise and likability were also not

signifying characteristics (β = -0.051, -0.044, -0.014 p >0.05). The negative beta of

likability indicated that these construct had a negative relationship with the hair care

product.

H09f: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of bakery product.

For purchasing behavior of bakery product for non-celebrity, as shown in the table





al.,2010).

Table: 4.101 Analysis of variance for bakery product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


1.896 0.109 Residual 731.543 963 0.760

Total 737.306 967


144


the level of 0.05 (B = 2.328; t = 20.739). From all four, two regression coefficients

were statistically significant (p < 0.05). This coefficient implied that there is a

significant relationship exists between celebrity‟s expertise and likability

characteristics.

Table: 4.102 Regression analyses for bakery product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.328 20.739 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise 0.080 0.140 2.137 0.033 0.240 4.160

Non-celebrity's

Likability -0.068 -0.114 -2.006 0.045 0.317 3.153




Among the four characteristics, expertise factor had the highest beta score (β = 0.080,

p<0.05) which was signifying and influenced on purchasing behavior of the bakery

products. While likability factor is also signifying constructs (β = -0.068 p<0.05). The

negative beta of likability indicated that this factor had a negative relationship with

the bakery product.

H09g: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of snack food product.

For purchasing behavior of snack food products for non-celebrity, as shown in the

table 4.103 under the title of analysis of variance, this percentage was statistically

significant (F = 3.639, p<0.05). There was a threat of multicollinearity among the



al.,2010).

145

Table: 4.103 Analysis of variance for snack food.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


3.639 0.006 Residual 699.493 963 0.726

Total 710.065 967



the level of 0.05 (B=2.442; t=22.245). From all four, only one regression coefficients

were statistically significant (p < 0.05). This coefficient implied that there is a

significant relationship exists between non-celebrity‟s likability characteristic.

Table: 4.104 Regression analyses for snack food.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.442 22.245 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise 0.041 0.072 1.107 0.268 0.240 4.160

Non-celebrity's

Likability -0.070 -0.120 -2.114 0.035 0.317 3.153




Among the four characteristics, expertise factor had the highest beta score (β = 0.041,

p <0.05), which was signifying and influenced on purchasing behavior of snack food.

While physical attractiveness, Trustworthiness, and likability were also not signifying

characteristics (β = 0.012, -0.046, -.070 p >0.05). The negative beta indicated that

these factors had a negative relationship.

H09h: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of chocolate.

For purchasing behavior of chocolate products for non-celebrity, as shown in the table

4.105 under the title of analysis of variance, this percentage was statistically

significant (F = 2.769, p<0.05). There was a threat of multicollinearity among the

146



al.,2010).

Table: 4.105 Analysis of variance for chocolate products.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.769 0.026 Residual 661.581 963 0.687

Total 669.190 967



the level of 0.05 (B=2.279; t=21.345). From all four, none of regression coefficients


significant relationship exists between non-celebrity‟s constructs. So all the four


Table: 4.106 Regression analyses for chocolate product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.279 21.345 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.013 -0.024 -0.368 0.713 0.240 4.160

Non-celebrity's

Likability -0.033 -0.059 -1.033 0.302 0.317 3.153





0.022, p >0.05), While Trustworthiness, expertise and likability have beta score β = -

0.029, -0.013, -0.033. The negative beta indicated that these construct had a negative

relationship with the chocolate product.

147

H09i: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of tea.

For purchasing behavior of tea products for non-celebrity, as shown in the table 4.107

under the title of analysis of variance, this percentage was statistically not significant

(F = 2.017, p>0.05). There was no threat of multicollinearity among the predictor


than 0.2 and the VIF (Variance Inflation Factor) was less than 5 (Churchill et

al.,2010).

Table: 4.107 Analysis of variance for tea product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


2.017 0.090 Residual 790.613 963 0.821

Total 797.236 967




coefficients were statistically significant (p <0.05). These coefficients implied that

there is a significant relationship exists between non-celebrity‟s characteristics. So all

hypothesis were not rejected.

Table: 4.108 Regression analyses for tea product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.490 21.334 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.020 -0.034 -0.521 0.602 0.240 4.160

Non-celebrity's

Likability -0.050 -0.080 -1.402 0.161 0.317 3.153




148


0.018, p>0.05).

H09j: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of soft drink.

For purchasing behavior of soft drink products for non-celebrity, as shown in the table


significant (F=2.275, p>0.05). There was no threat of multicollinearity among the



al.,2010).

Table: 4.109 Analysis of variance for soft drink product.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


0.617 0.650 Residual 887.492 963 0.922

Total 889.768 967



the level of 0.05 (B = 2.371; t = 19.174). From all four characteristics, none of

regression coefficients were statistically significant (p >0.05). These coefficients

implied that there no significant relationship exists between non-celebrity‟s all

characteristics. So all hypothesis were not rejected.

Table: 4.110 Regression analyses for soft drink product.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.371 19.174 0.000

Non-celebrity's Physical

Attractiveness 0.006 0.009 0.209 0.835 0.552 1.813

Non-celebrity's


Non-celebrity's

Expertise -0.036 -0.057 -0.870 0.385 0.240 4.160

Non-celebrity's

Likability 0.009 0.014 0.238 0.812 0.317 3.153


149



Among the four characteristics, likability had the highest beta score (β = 0.009,

p>0.05).

H09k: There is no significant relationship between purchasing behaviors and non-

celebrity‟s characteristics in case of life insurance.

For purchasing behavior of Life insurance for non-celebrity, as shown in the table

4.111 under the title of analysis of variance, this percentage was statistically

significant (F=3.617, p<0.05). There was a threat of multicollinearity among the



al.,2010).

Table: 4.111 Analysis of variance for Life insurance.

Sum of

Squares Df

Mean

Square F

Sig.

(p value)


3.617 0.006 Residual 948.691 963 0.985

Total 962.942 967



the level of 0.05 (B=2.859; t=22.365). From all four, none of regression coefficients


significant relationship exists between non-celebrity‟s characteristics. So all the four


150

Table: 4.112 Regression analysis for Life insurance.

Regression

Coefficients

B Beta

Standardized

Coefficients β

Beta

t value p

value

Collinearity

Statistics

Tolerance

VIF

(Constant) 2.859 22.365 0.000

Non-celebrity's


Non-celebrity's


Non-celebrity's

Expertise -0.024 -0.036 -0.559 0.576 0.240 4.160

Non-celebrity's

Likability -0.036 -0.052 -0.915 0.360 0.317 3.153





0.011, p >0.05).

Table 4.113: Summary of Regression analysis for hypothesis between product

categories among characteristics of celebrity / non-celebrity.

Hypothesis statement Result

H08a

There is no significant relationship between purchasing

behaviors and celebrity‟s characteristics in case of detergent

product.

Partially

supported

H08b


behaviors and celebrity‟s characteristics in case of home

cleaning product.

Not rejected

H08c


behaviors and celebrity‟s characteristics in case of oral care

product.

Partially

supported

H08d


behaviors and celebrity‟s characteristics in case of skin care

product.

Partially

supported

151

H08e


behaviors and celebrity‟s characteristics in case of hair care

product.

Not rejected

H08f


behaviors and celebrity‟s characteristics in case of bakery

product.

Partially

supported

H08g


behaviors and celebrity‟s characteristics in case of snack food

product.

Not rejected

H08h There is no significant relationship between purchasing

behaviors and celebrity‟s characteristics in case of chocolate. Not rejected

H08i There is no significant relationship between purchasing

behaviors and celebrity‟s characteristics in case of tea.

Partially

supported

H08j There is no significant relationship between purchasing

behaviors and celebrity‟s characteristics in case of soft drink. Not rejected

H08k


behaviors and celebrity‟s characteristics in case of life

insurance.

Not rejected

H09a


behaviors and non-celebrity‟s characteristics in case of

detergent product.

Not rejected

H09b


behaviors and non-celebrity‟s characteristics in case of home

cleaning product.

Partially

supported

H09c


behaviors and non-celebrity‟s characteristics in case of oral

care product.

Not rejected

H09d


behaviors and non-celebrity‟s characteristics in case of skin

care product.

Not rejected

152


H09e


behaviors and non-celebrity‟s characteristics in case of hair

care product.

Not rejected

H09f


behaviors and non-celebrity‟s characteristics in case of bakery

product.

Partially

supported

H09g


behaviors and non-celebrity‟s characteristics in case of snack

food product.

Not rejected

H09h


behaviors and non-celebrity‟s characteristics in case of

chocolate.

Not rejected

H09i There is no significant relationship between purchasing

behaviors and non-celebrity‟s characteristics in case of tea. Not rejected

H09j


behaviors and non-celebrity‟s characteristics in case of soft

drink.

Not rejected

H09k


behaviors and non-celebrity‟s characteristics in case of life

insurance.

Not rejected

153

4.17 Cross tabulation of Gender and Likening of advertisement by endorsers’

type.

Table: 4.114 Cross tabulation of Gender and Likening of advertisement.

Product category Likening of Endorser in advertisement Male Female

Fabric care Celebrity endorsement 35.9 43.4

Non-celebrity endorsement 64.1 56.6

Home cleaning Celebrity endorsement 62.8 58.7


Oral care Celebrity endorsement 48.8 48.5


Skin care Celebrity endorsement 70.5 66.7


Hair care Celebrity endorsement 71.2 73.0


Bakery product Celebrity endorsement 37.0 33.3


Snack food Celebrity endorsement 66.5 78.1


Chocolate Celebrity endorsement 44.5 50.1


Tea Celebrity endorsement 51.8 56.6


Soft drink Celebrity endorsement 71.0 70.2


Life insurance Celebrity endorsement 36.3 34.2


Mobile handset Celebrity endorsement 72.2 66.8



Above table 119, depicts the result of cross tabulation of likening of advertisement for

different product categories. The pair of advertisements was given to respondents

including celebrity and non-celebrity endorser. In the above table gender wise

likening were given. For celebrity endorser advertisement for various product

154

categories, the difference were observed on fabric care, home cleaning, snack food

and chocolate, where as for non-celebrity endorsement the difference on gender wise

observed on fabric care, home cleaning, bakery product, chocolate and mobile

handset. The soft drink is one product in which there was less difference observed.

4.18 Conclusion:

This chapter started with a presentation of the descriptive statistic relevant to each

hypotheses of this study. The inferential statistics were then shown and the results of

independent sample t- test ANOVA and multiple regression analysis conducted to test

the study‟s hypotheses were presented. The next chapter discusses the result

discussion and findings of the study based data analysis.

155

References:

Churchill G. A., Lacobucci D. & Israel D. (2010). Marketing Research A South

Asian Perspective, (4th ed.). Delhi: Cengage Learning.

Sherman, S. P. (1985, August 19). When you wish upon a star. Fortune, 66-71

Zikmund W., Barry Babin, Jon Carr, Mitch Griffi “Business Research Methods”, Cengage

Learning, 2013.

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