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CHAPTER 9

RESULTS

The results chapter is divided into four sections. The first section discusses the results of

manipulation checks, which ensured that the respondents perceived the stimuli in the way the

researcher wanted them to. The second section describes CFA/Measurement Model results

for the reliability and validity of the seven (7) constructs, which were used in the model.

Third section details about the SEM results and hypothesized model’s fit and fourth section

of results provide the findings of t-tests.

9.1. Manipulation Checks

There were two (2) manipulation checks for the study. The final data (N=480) was divided in

four groups. For each brand, there were two groups of responses (for congruent and

incongruent celebrity). Manipulation checks were conducted for the variables ‘Familiarity’

and ‘Celebrity Endorser-Brand Congruence’. Table-8 shows the results of the manipulation

checks for brand ‘Levi’s’ and Table-9 shows the results for the manipulation checks for brand

‘Nokia’.

Table-8. Results of Manipulation Checks (Levi’s Brand)

Variables Celebrities Mean t-value

Familiarity

Priyanka Chopra

Rani Mukherjee

6.00

5.91

0.532ns

Celebrity-Brand

Congruence

Priyanka Chopra

Rani Mukherjee

5.13

2.85

14.339**

**P<0.01, *P<0.05, ns = Not Significant

Table-9. Results of Manipulation Checks (Nokia Brand)

Variables Celebrities Mean t-value

Familiarity

Vijender Singh

Sresanth

5.34

5.25

0.438ns

Celebrity-Brand

Congruence

Vijender Singh

Sresanth

4.27

3.23

6.166**


Results of manipulation checks for both the brands show the successful manipulation

of variables ‘Familiarity’ and ‘Celebrity-Brand Congruence’. For ‘Levi’s’ brand, both the

celebrities Priyanka Chopra (mean = 6.00) and Rani Mukherjee (mean = 5.91) had similar

levels of perceived familiarity (t = 0.532, p > 0.05). Hence there won’t be any impact of

celebrity’s familiarity on consumer attitudes. Further, Priyanka Chopra (mean = 5.13) was

perceived significantly higher (t = 14.339, p < 0.05) than Rani Mukherjee (mean = 2.85) on

congruence with brand’s personality, satisfying the study’s assumptions of congruent and

incongruent celebrity. For ‘Nokia’ brand, Vijender Singh (mean = 5.34) and Sreesanth (mean

= 5.25) were perceived to be equally familiar to the participants (t = 0.438, p > 0.05). On

congruence with brand’s personality, Vijender Singh (mean = 4.27) was significantly higher

(t = 6.166, p < 0.05) than Sreesanth (mean = 3.23), again satisfying the study’s assumptions

on congruence.

9.2. Test of Construct Validity and Reliability for Latent Factors (Measurement Model)

This phase of results, discuss the various tests of reliability and construct validity for all

seven (7) factors used for the model. Construct validity is the extent to which a set of

observed variables/items actually reflects the theoretical latent construct those items are

designed to measure (Hair et al., 2009). Evidence of construct validity substantiate that the

item measures taken from a sample represent the actual true score of population. Construct

validity has four important components: Face validity, Convergent validity, Discriminant

validity and Nomological validity (Hair et al., 2009).

Face validity tests whether the items provide the same information related to its

constructs or not (Hair et. al, 2009). As mentioned earlier in chapters of research design and

questionnaire design, the items/questions to measure the constructs were adopted from the

past literature. And further, the questionnaires used in this study were shown to two experts

and they validated those questions. It satisfies the face validity of the constructs.

Convergent validity is established when the items of a specific construct converge or

share a high proportion of variance. There are several ways to check the convergent validity.

High factor loadings of items on its factor indicate that they converge on a single factor.

Various studies have suggested that the standardized factor loadings should be 0.5 or higher,

and ideally 0.7 or higher (Hair et al., 2009). Second measure to check convergent validity is

the ‘Average Variance Extracted (AVE)’. This value is calculated by dividing summation of

squares of all the factor loadings of items under a factor by number of items under that factor.

AVE value of 0.5 or higher suggests adequate convergence (Hair et al., 2009). The third

measure for convergent validity is the ‘Construct Reliability’. It is calculated by dividing

squared sum of factor loadings by sum of squared sum of factor loadings and the sum of error

variance. Its value of 0.7 or higher is construed as the good evidence of convergent validity.

Further, Reliability coefficient Cronbach’s α shows the internal consistency in responses to a

particular construct. Its value of 0.8 or higher suggests good reliability of that construct. A

series of CFAs were conducted to confirm the convergent validity of each factor. Results of

all these CFAs and Reliability coefficients are shown in tables for each factor.

9.2.1. Endorser Personality and Brand Personality Congruence (CONGR)

CFA results for the factor ‘CONGR’ showed a good fit of the model. Chi-square value (with

degrees of freedom 6) for this model was 8.263. Table-10 provides the indices for goodness

of fit for this construct with their recommended values.

Table-10. Model Fit Indices for CONGR

Fit Indices Recommended Value* Measurement Model

Chi-square to degree of

freedom ratio (CMIN/df) 3.000 or below 1.377

Root mean square of error

approximate (RMSEA) 0.070 or below 0.028

Standardized root mean

residual (SRMR) 0.070 or below 0.005

Comparative Fit Indices

(CFI) 0.900 or above 0.999

Tucker-Lewis Index (TLI) 0.900 or above 0.998

The statistical tool ‘Mplus’ doesn’t provide GFI and AGFI values (Byrne, 2012).

Other parameters are shown in Table-11.

* Browne and Cudeck, 1993; Hu & Bentler, 1999; Hair at al., 2009; and Byrne, 2012.

Table-11. CFA Results for CONGR

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 1: Endorser-Brand Congruence

Please indicate your opinion on the

appropriateness of the celebrity endorser as the

brand ambassador of Levi’s/Nokia based on

personality traits of both.

(a) Very Inappropriate-Very Appropriate

(b) Inconsistent-Consistent

(c) Very Unlikely Match-Very Likely Match

(d) Very Irrelevant-Very Relevant

(e) Doesn’t Match-Matches Very well

(f) Doesn’t Go Together-Goes Together

0.877**

0.819**

0.931**

0.927**

0.933**

0.916**

0.769**

0.670**

0.866**

0.859**

0.871**

0.840**


For this model, AVE was 0.812, construct reliability was 0.963 and Cronbach’s α was

0.964. CFA results show that the convergent validity and reliability of the construct

‘CONGR’ are good as each factor loading is more than 0.7; Variance explained by each item

is more than 0.5; AVE is more than 0.5; construct reliability is more than 0.7; and reliability

coefficient or Cronbach’s α is more than 0.8.

9.2.2. Endorser Suitability (ES)

CFA results for the factor ‘ES’ too showed a good fit of the model. Chi-square value (with



Table-12. Model Fit Indices for ES

Fit Indices Recommended Value Measurement Model








(CFI) 0.900 or above 1.000



Table-13. CFA Results for ES

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 3: Endorser Suitability

(a) I find this celebrity endorser suitable for any

advertising campaign.

(b) I recommend this celebrity endorser as an

endorser for ‘Levi’s/Nokia’ brand.

(c) I would pay more attention to an

advertisement if this celebrity endorser is in

it compared to other advertisements for

same brand ‘Levi’s/Nokia’.

(d) This advertisement would gain due to the

fact it used this celebrity as an endorser.

0.766**

0.928**

0.743**

0.858**

0.588**

0.861**

0.522**

0.751**



0.900. These results show that the convergent validity and reliability of the construct ‘ES’ are

good as each factor loading is more than 0.7; Variance explained by each item is more than

0.5; AVE is more than 0.5; construct reliability is more than 0.7; and reliability coefficient or

Cronbach’s α is more than 0.8.

9.2.3. Endorser Credibility (EC)

CFA results for the factor ‘EC’ showed a good fit of the model. Chi-square value (with

degrees of freedom 84) for this model was 189.137. Table-14 provides the indices for

goodness of fit for this construct with their recommended values.

Table-14. Model fit Indices for EC









(CFI) 0.900 or above 0.979


Other parameters are shown in Table-15. For this model, AVE was 0.634, construct

reliability was 0.768 and Cronbach’s α was 0.924. These results show that the convergent

validity and reliability of the construct ‘EC’ are good as almost all factor loadings are more

than 0.7; Variance explained by almost all items are more than 0.5; AVE is more than 0.5;

construct reliability is more than 0.7; and reliability coefficient or Cronbach’s α is more than

0.8.

Table-15. CFA Results for EC

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 2: Source Credibility

Please indicate your opinion about the celebrity

endorser on the following items. The last five

items should be considered with respect to the

brand advertised.

1. Attractiveness

(a) Unattractive-Attractive

(b) Not Classy-Classy

(c) Ugly-Handsome/Beautiful

(d) Plain-Ugly

(e) Not Sexy-Sexy

2. Trustworthiness

(f) Untrustworthy-Trustworthy

(g) Undependable-Dependable

(h) Dishonest-Honest

(i) Unreliable-Reliable

(j) Insincere-Sincere

3. Expertise

(k) Not an Expert-Expert

(l) Inexperienced-Experienced

(m) Unknowledgeable- Knowledgeable

(n) Unqualified-Qualified

(o) Unskilled-Skilled

0.917**α

0.864**

0.832**

0.798**

0.842**

0.802**

0.727**α

0.710**

0.513**

0.739**

0.868**

0.772**

0.731**α

0.801**

0.846**

0.872**

0.832**

0.809**

0.840**β

0.747**

0.692**

0.636**

0.710**

0.644**

0.528**β

0.505**

0.263**

0.546**

0.753**

0.596**

0.534**β

0.641**

0.716**

0.761**

0.693**

0.654**


9.2.4. Advertisement Believability (ABL)

Results related to the CFA conducted for the construct ‘ABL’ are shown in Table-16

α Factor loadings of second order construct EC on first order constructs Attractiveness, Trustworthiness and

Expertise

β Variance explained by first order constructs Attractiveness, Trustworthiness and Expertise

Table-16. CFA Results for ABL

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 4: Believability/Credibility of

Advertisement

Indicate your opinion on the

believability/credibility of the advertisement

shown.

(a) Highly Unbelievable-Highly Believable

(b) Highly Incredible-Highly Credible

0.806**

0.769**

0.650**

0.592**


For this model, AVE was 0.621, construct reliability was 0.765 and Correlation

coefficient was 0.886. These results show that the convergent validity and reliability of the

construct ‘ABL’ are good as each factor loading is more than 0.7; Variance explained by each

item is more than 0.5; AVE is more than 0.5; construct reliability is more than 0.7; and

correlation coefficient is more than 0.8. The construct ‘ABL’ had only two items therefore

the correlation coefficient is better indicator for the internal consistency than Cronbach’s

alpha.

9.2.5. Attitude toward Advertisement (AA)

CFA results for the factor ‘AA’ showed a good fit of the model. Chi-square value (with



Table-17. Model Fit Indices for AA









(CFI) 0.900 or above 0.998



Table-18. CFA Results for AA

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 5: Attitude toward Advertisement

Rate your attitude toward the advertisement

using the following scales.

(a) Unpleasant-Pleasant

(b) Not likeable-likeable

(c) Unfavourable-Favourable

(d) Bad-Good

0.865**

0.921**

0.909**

0.912**

0.749**

0.848**

0.827**

0.832**



0.945. These results show that the convergent validity and reliability of the construct ‘AA’

too are good as each factor loading is more than 0.7; Variance explained by each item is more

than 0.5; AVE is more than 0.5; construct reliability is more than 0.7; and reliability


9.2.6. Attitude toward Brand (AB)

CFA results for the factor ‘AB’ showed a good fit of the model. Chi-square value (with



Table-19. Model Fit Indices for AB









(CFI) 0.900 or above 1.000



Table-20. CFA Results for AB

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 6: Attitude toward the Brand

Rate your attitude toward the

Levi’s/Nokia using the following scales.

(a) Unpleasant-Pleasant

(b) Not likeable-likeable

(c) Unfavourable-Favourable

(d) Bad-Good

0.816**

0.919**

0.890**

0.881**

0.665**

0.844**

0.792**

0.777**



0.932. These results show that the convergent validity and reliability of the construct ‘AB’

are good as each factor loading is more than 0.7; Variance explained by each item is more

than 0.5; AVE is more than 0.5; construct reliability is more than 0.7; and reliability


9.2.7. Purchase Intention (PI)

Results related to the CFA conducted for the construct ‘PI’ is shown in Table-21.

Table-21. CFA Results for PI

Factors/Items

Std. Factor

Loading

Variance

Explained

Factor 7: Purchase Intention

(a) I would inquire about the brand

‘Levi’s/Nokia’.

(b) I would consider purchasing the

brand ‘Levi’s/Nokia’.

(c) I would actually purchase the brand

‘Levi’s/Nokia’.

0.574**

0.986**

0.819**

0.329**

0.972**

0.670**



0.820. These results show that the convergent validity and reliability of the construct ‘PI’ are

good as each factor loading is more than 0.5; AVE is more than 0.5; construct reliability is

more than 0.7; and reliability coefficient or Cronbach’s α is more than 0.8.

Thus for each construct, convergent validity was confirmed. Another component of

construct validity is ‘discriminant validity’. Discriminant validity is the extent to which a

construct is distinct from other constructs. High levels of the discriminant validity ensure that

constructs are unique and capture those measures, which other constructs don’t (Hair et al.,

2009). One of the ways to test for the discriminant validity for a particular factor is to ensure

the AVE of that factor would be higher than squared inter-factors correlations. Result related

to the discriminant validity has been shown in Table-22.

Table-22. AVE and Covariance Matrix

CONGR EC ES ABL AA AB PI

CONGR 0.812

EC 0.565 0.637

ES 0.652 0.543 0.680

ABL 0.546 0.571 0.609 0.621

AA 0.403 0.471 0.516 0.576 0.814

AB 0.014 0.017 0.018 0.026 0.036 0.782

PI 0.003 0.004 0.004 0.006 0.009 0.254 0.657

From Table-22, it could be observed that ‘Average Variance Extracted (AVE)’ for

each construct (diagonally in bold letters) is more than the squared inter-construct

correlations. Hence, the discriminant validity of all seven constructs has been confirmed.

Nomological validity and predictive validity are confirmed by examining whether the

construct is significantly correlated to the other related constructs or not (Hair et al., 2009).

This validity got confirmed through the significant relationships between constructs in the

structural model shown in next section. Thus the construct validity of all the constructs has

been confirmed.

9.3. The Structural Model Results

‘Structural Equation Modeling’ with the help of ‘Mplus version 6.12’ was performed to test

the hypothesized relationships shown in Figure-1. The model fit parameters given by Mplus

output have been provided in Table-23.

Table-23. Model Fit Parameters

MODEL FIT INFORMATION

Number of Free Parameters 139

Chi-Square Test of Model Fit

Value 1123.387

Degrees of Freedom 640

CMIN/df 1.755

P-Value 0.0000

RMSEA (Root Mean Square Error Of

Approximation)

Estimate 0.040

90 Percent C.I. 0.036 0.043

Probability RMSEA <= .05 1.000

CFI/TLI

CFI 0.971

TLI 0.968

SRMR (Standardized Root Mean Square

Residual) Value 0.037

The structural model suggested in this study (Figure-1) was tested using the maximum

likelihood method with Mplus 6.12. The results showed an acceptable fit of the proposed

structural model with χ2 (480) = 1123.387, df = 640, p = .00, CMIN/df = 1.755, RMSEA =

.040, CFI = .971, TLI = .968, and SRMR = .037 (Hair et al., 2009; Hu and Bentler, 1999;

Browne and Cudeck, 1993). Mplus doesn’t provide the GFI and AGFI values (Byrne, 2012).

The standardized model path coefficients and their corresponding p-values have been

provided in Table-24.

Table-24. Parameter Estimates

Hypotheses

Path/Relationship Estimate

Two-Tailed

P-Value

H-1 Congruence Endorser Suitability 0.584 0.000

H-2 Congruence Endorser Credibility 0.752 0.000

H-3 Endorser Credibility Endorser Suitability 0.298 0.000

H-4 Endorser Suitability Believability of the

Advertisement 0.551 0.000

H-5 Endorser Credibility Believability of the

Advertisement 0.392 0.000

H-6 Believability of the Advertisement

Attitude toward Advertisement 0.859 0.000


Attitude toward Brand 0.150 0.233


Purchase Intention 0.031 0.779

H-9 Attitude toward Advertisement Attitude

toward Brand 0.321 0.007

H-10 Attitude toward Brand Purchase Intention 0.497 0.000

H-11 Attitude toward Advertisement

Purchase Intention 0.015 0.888

A pictorial presentation of these results is shown in Figure-2. Results in Table-24 and

their pictorial presentation in Figure-2 clearly show the significant impact of celebrity

endorser personality and brand personality congruence on celebrity endorser’s suitability and

his/her credibility. Further these results also show the significant effect of these source

characteristics (endorser suitability and credibility) on believability of the advertisements.

Supporting results of various studies on attitude, these results show the significant

relationships between consumers’ attitude toward advertisement to their attitude toward brand

and attitude toward brand to purchase intention of consumers’. However, paths from

advertisement believability to attitude toward brand (H-7) and purchase intention (H-8) as

well as path from attitude toward advertisement to purchase intention (H-11) of consumers

have been found insignificant. SEM results of the insignificant relationships have been shown

in Table-24 in bold letters. The possible reasons for these insignificant relationships have

been discussed in next chapter. The model comprising only significant relationships has been

shown in Figure-3.

Figure-2. Parameter Estimates for the Hypothesized Model


Model Fit Parameters:

Chi-square test = 1123.387 (degrees of freedom = 640), RMSEA = 0.040, SRMR = 0.037, CFI = 0.971, TLI = 0.968

Endorser Personality and

Brand Personality Congruence

Endorser Suitability

Endorser Credibility

Believability of the

Advertisement

Attitude toward Advertisement

Attitude toward Brand

Purchase Intention

0.031ns

0.752**

0.298**

0.392**

0.551** 0.584**

584

0.150ns

0.859** 0.321**

0.497**

0.015ns

Figure-3. Model after removing Insignificant Relationships

**P<0.01, *P<0.05

Model Fit Parameters:

Chi-square test = 1125.884 (degrees of freedom = 643), RMSEA = 0.040, SRMR = 0.037, CFI = 0.971, TLI = 0.968

Endorser Personality and

Brand Personality Congruence

Endorser Suitability

Endorser Credibility

Believability of the

Advertisement

Attitude toward Advertisement

Attitude toward Brand

Purchase Intention

0.752**

0.298**

0.392**

0.551** 0.584**

584

0.859** 0.321**

0.497**

9.4. Results of t-tests

A series of t-tests were conducted to compare means of variables ‘Believability of the

Advertisement (ABL)’; ‘Attitude toward Advertisement (AA)’; ‘Attitude toward Brand (AB)’

and ‘Purchase Intention (PI)’ across congruent and incongruent groups for each brand. For

Levi’s brand, congruent celebrity was Priyanka Chopra and incongruent celebrity was Rani

Mukherjee. For Nokia, the congruent celebrity was Vijender Singh and incongruent celebrity

was Sreesanth. The t-tests were conducted to check whether there is any significant difference

between the congruent and incongruent pairs of brand and celebrity on the above-mentioned

dependent variables. The results of t-tests for brand ‘Levi’s’ and for brand ‘Nokia’ have been

shown in Table-25 and Table-26 respectively.

Table-25. t-test Results for Levi’s Brand

Hypotheses

Variables

t-test for Equality of Means

t df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

H-12 ABL 7.741 238 .000 2.642 .341

H-13 AA 8.547 238 .000 5.725 .670

H-14 AB 1.229 238 .220 .633 .515

H-15 PI 1.088 238 .278 .558 .513

Table-26. t-test Results for Nokia Brand

Hypotheses

Variables

t-test for Equality of Means

t df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

H-12 ABL 5.367 238 .000 1.850 .345

H-13 AA 4.399 238 .000 3.075 .699

H-14 AB .256 238 .798 .167 .650

H-15 PI 1.731 238 .085 1.008 .582

The t-values for both the brands show the significant difference between congruent and

incongruent pairs of celebrity endorser and brand for dependent variables ‘Attitude toward

advertisement (AA)’ and ‘Believability of the Advertisement (ABL)’. However, for both the

brands, there was no significant difference found between congruent and incongruent pairs of

celebrity endorser and brand for ‘Attitude toward Brand (AB)’ and ‘Purchase Intention (PI)’.

These conclusions were the same whether variances were assumed to be equal or unequal. Hence

hypotheses H-12 and H-13 were supported while hypotheses H-14 and H-15 were not supported.

chapter 9 results - shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/27412/14/14_ chapter...

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