1. PLEASE NOTE
ALL THE EMBOLDEND LETTERS IN RED INDICATE INFORMATION WHICH IS NOT
PROVIDED IN THIS VERSION OF THE REPORT.
NPF IS “NON PRODUCT FACTOR” OR “EMOTIONAL ASSOCIATION”
PF IS “PRODUCT FACTOR”
MAINAK BAG

2. ABSTRACT
This study attempts to find the relationship of brand attitude and how it is comprised with inputs
from consumer perceptions about products attributes and non product attributes, which are largely
a felt response of emotional acknowledge of a brand. In essence it is peek into the making of
brand attitude through a two way interaction of product attributes and perceived emotional
benefits.
2

3. INTRODUCTION
The key to marketing, always, has been understanding the consumers. A greater realization is the
simple one of recognizing the consumer as a human being. This recognition can lead as all the
way to understanding the customer from a holistic perspective.
A human being is essentially a thinking – feeling being. The Stanford Encyclopedia of
Philosophy states: “No aspect of our mental life is more important to the quality and meaning of
our existing than emotion”.
Important studies have been done in marketing and psychology affirming this.
Brand attitude has been described by Keller as the “overall evaluation of the brand in terms of its
quality and the satisfaction it generates”. Richard Elliot and Larry Percy have said “People who
think about brands…often talk in terms of things like value, perceived quality and image. What
all this comes down to is a brand attitude, the association in memory linked to the brand.”
Brand awareness Brand salience Brand attitude Brand equity
Learning Associations build Preference
Attitude is considered example of affect by some (Bagozzi). Cohen and Areni, 1991 described
affect as “valenced feeling states”. There are others who opine that emotions are evaluative
judgments or in other words cognitive appraisals (Eagly and Chaiken, 1993). Martin Fishbein and
Icek Agezen (1975) have arguably regarded affect “as isomorphic with evaluation itself” (Eagly
and Chaiken, 1993).
But there are studies that have worked on arguing that attitude is a function of two different and
highly correlated components: Affect and cognition (Bagozzi & Burnkrant 1997, Batra and Ahtol
1990). But it is also noted that the terms attitude, emotion, affect, mood have been used
inconsistently in marketing literature (Bagozzi). Below is described the relationship between
affect, emotions mood and attitude.
Attitude (Bagozzi & Burkrant, Batra & Ahtol)
Affective Cognitive
(Affect) (“Valenced feeling state” (“Evaluative judgments or a
- Cohen & Areni) Appraisals” – Eagly & Chaiken ’93)
Emotion Mood
(Intense, accompanied by physical (Longer lasting, diffused, non-action
expression, action oriented, a mental state oriented – Frijda 1993)
of readiness – (Bagozzi, Gopinath, Iyer)
Emotions are a mental state of readiness and often are a cognitive appraisal of events and
thoughts which act as referents prompting an evaluative judgment and thus give rise to a
3

4. particular action/ reaction oriented response often accompanied with physical expression
(Bagozzi, Gopinath, Iyer).
The process is shown below.
Events
“THE FULL HUMAN
IMPACT OF EMOTIONS
IS ONLY REALIZED
WHEN THEY ARE Cognitive Processing
SENSED, WHEN THEY
BECOME FEELING AND
WHEN THOSE FEELINGS Emotion Leraning
ARE FELT. THAT IS
WHEN THEY BECOME
KNOWN” Feeling
(Damasio, 1999, Quoted in
Elliot and Percy.) Attitude
Action
Importantly, there has been agreement that biological system dealing with emotions in the human
brain can operate separately storing information without involving cognitive processing (Eliot
and Percy). The ‘Prefrontal cortex’ and ‘Amygdala’ process emotion and they engage the
declarative memory system (Eichendaun, 2002). The declarative memory system is responsible
for cognitive processing (Eliot and Percy). What this implies is that although emotional
processing is done by a separate system (‘Prefrontal cortex’ and ‘Amygdala’), it influences and
overlaps with cognitive processing.
A measure of emotional involvement is trust (Rempel et al, 1985), which moves in stages from
predictability to dependability, to trust and then to faith, representing a hierarchy of emotional
involvement.
Trust requires a move from reliance on rational cognitions to reliance on emotion and sentiment
(Rempel et al, 1985, P13).
The scope of this study is limited to finding contribution and importance of non product attributes
based and emotion oriented factors to brand attitude.
Research Methodology:
Sampling frame: Students of a business school
Sampling units: Both male and female students,
Sampling elements: Users of the three product used for the study
Three products were arbitrarily chosen to find out their product level of involvement.* Seven
variables were used to find the levels of involvement.
4

5. Projective techniques and laddering techniques were used to find out the relevant variables of
brand attitude from ten subjects. The most occurring variables were used to framing the
questionnaire.
The resultant variables were used to find the brand attitude scores for each of the three brands,
using a slightly modified “Expectancy Value Model” developed by Martin Fishbein and Icek
Ajzen.
The formula used is Ai = Wi │Ii - bi│
When Ai = Attitude on variable i
Wi = Importance or weight of variable i.
I = Ideal performance on variable i.
bi = Actual performance on variable i
Respondents were asked ideal level of performance on each variable
Wi = {Mean of I for variable i/ ∑ Mean of I} *100, where I = Ideal performance
The variables were reduced to two factors by factor analysis.
A two dimensional brand trust scale, developed and validated by Ellena Delgado- Ballester,
Jose Luis Munuera –Aleman and Maria Jesus Yague-Guillen (published in “International
Journal of Marketing Research”, 2003, Vol. 45 Quarter1) was used to find the reliability trust,
intention trust and composite trust.
The definition of brand trust as proposed by Ballester, Aleman and Guillen reflects two distinct
components: (1) brand reliability, and (2) brand intentions. Brand reliability has a competence of
technical nature in other words, it concerns the perception that the brand fulfils or satisfies the
consumer's needs. Brand intention describes the consumer's belief that the brand's behaviour is
guided or motivated by favourable and positive intentions towards the consumer's welfare and
interests.
Then a Trust: Involvement ratio was calculated for each respondent. This ratio can show the trust
per unit of perceived risk as perceived risk is represented by product involvement level. The T/I
ratio will show us how much positive emotional association [represented by trust] the brand in
question has been able to generate for the perceived risk it carries. This concept is supported by
the following statement: “trust is required in situations of high perceived risks” (Elliot and Percy,
P 30)
T/I = Trust Score / Involvement Level
The scores were categorized as below:
0 to 1.32 – Low T/I.
1.32 to 3 --- medium T/I.
>= 3 – high T/I.
* Consumer involvement comes from three sources: i) Consumer, ii) Product
and iii) Situation. Product source of involvement was chosen because firstly consumer
profiling would have been an elaborate process which may not have been met with limited
time, money and access, secondly, to find the right consumer at their purchasing time is, in
more than one way, difficult, lengthy and, for the purpose of study, impractical.
5

6. All the product features were analyzed to find out their Principal Components. The Principal
Components could be easily categorized into Product and Service Efficiency Related
Components and Non Product and Service Efficiency Related Components, henceforth referred to
as PF and NPF respectively.
Univariate analysis of covariance (ANCOVA) was done first with interaction between
involvement levels* NPF & involvement levels* PF and then with interactions between T/I* PF
and T/I *NPF.
The dependent variable was attitude scores, category factors were involvement levels and T/I
scores and covariates were NPF and PF.
To understand the degree and the direction of the influence of PF and NPF on Brand Attitude
regression analysis was executed.
The direction of the influence of PF and NPF on Brand Attitude found by the regression analysis
is again substantiated by Chao Test.
RESULTS:
Cadbury Mean Attitude: 44.05, Trust score (reliability): 4.12,
Trust score (Intention): 3.32 Trust score (all): 3.43
Axe Mean Attitude: 90.74, Trust score (reliability): 3.48,
Trust score (Intention): 3.13 Trust score (all): 3.30
Compaq Mean Attitude: 86.23, Trust score (reliability): 3.61,
Trust score (Intention): 3.37 Trust score (all): 3.49
Descriptive Statistics (COMPAQ)
Std.
Mean Deviation N
ATTITUD
E OF
86.2318 52.76146 32
EACH
PERSON
Descriptive Statistics (CADBURY)
Std.
Mean Deviation N
ATTITUD
E OF
44.0550 31.83615 34
EACH
PERSON
6

7. Descriptive Statistics (AXE)
Std.
Mean Deviation N
ATTITU
DE OF
90.7385 59.52077 34
EACH
PERSON
FACTOR ANALYSIS:
CADBURY Total Variance Explained
Extraction Sums of Rotation Sums of
Initial Eigenvalues Squared Loadings Squared Loadings
% of Cumul % of Cumul % of Cumul
Comp Varian ative Varian ative Varian ative
onent Total ce % Total ce % Total ce %
1 5.091 46.286 46.286 5.091 46.286 46.286 3.135 28.497 28.497
2 1.190 10.821 57.108 1.190 10.821 57.108 2.517 22.885 51.382
3 1.097 9.971 67.079 1.097 9.971 67.079 1.727 15.697 67.079
4 .913 8.296 75.374
5 .807 7.333 82.707
6 .623 5.662 88.369
7 .486 4.422 92.792
8 .325 2.955 95.747
9 .239 2.169 97.916
10 .125 1.140 99.056
11 100.00
.104 .944
0
Extraction Method: Principal Component Analysis.
Rotated Component Matrix (a)
Component
PF NPF 3
MIKY .700 Extraction Method: Principal
TASTY .881 Component Analysis. Rotation
SMOOTH .519 Method: Varimax with Kaiser
SWEET .846 Normalization.
LOVE .646 a Rotation converged in 6
CELEB .677 iterations.
FRNDS .667
KIDS .760
YOUNG .667
PAMP .831
COLR .657
7

8. KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .738
Bartlett's Test of Approx. Chi-Square 185.364
Sphericity df 55
Sig. .000
Reliability Coefficients 5 items FOR FACTOR PF (ONE)
Alpha = .8878 Standardized item alpha = .8901
Reliability Coefficients 3 items FOR FACTOR NPF (TWO)
Alpha = .69 Standardized item alpha = .6921
Reliability Coefficients 2 items FOR FACTOR 3 (THREE)
Alpha = .3662 Standardized item alpha = . 3772
AXE
Rotated Component Matrix (a)
Component
PF NPF
VAR .807
SKIN .748
STYL .773
YOUNG .814
SEX .713
ELIT .868
XFAC .778
MYSTRE
.605
Y
TRND .595
FASHIO
.846
N
FUN .808
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization.
a Rotation converged in 3 iterations.
8

9. Correlations
MYS FAS
SKI STY YOU XFA TRE TRN HIO
VAR N L NG SEX ELIT C Y D N FUN
VAR 1.00
.629 .673 .540 .292 .214 .575 .344 .404 .653 .236
0
SKI 1.00
.629 .560 .600 .417 .280 .587 .318 .583 .666 .379
N 0
Sig. ATO
(1- FEA
.030 .028 .000 .001 .002 .000 .000 .002 .041 .019 .023
tailed CH
)
VAR . .000 .000 .000 .047 .112 .000 .023 .009 .000 .090
SKI
.000 . .000 .000 .007 .054 .000 .033 .000 .000 .013
N
Total Variance Explained
Extraction Sums of Squared Rotation Sums of Squared
Initial Eigenvalues Loadings Loadings
% of % of % of
Compo Varianc Cumula Varianc Cumula Varianc Cumula
nent Total e tive % Total e tive % Total e tive %
1 5.971 54.282 54.282 5.971 54.282 54.282 4.733 43.031 43.031
2 1.359 12.356 66.638 1.359 12.356 66.638 2.597 23.607 66.638
3 .948 8.620 75.258
4 .581 5.279 80.537
5 .498 4.523 85.060
6 .430 3.905 88.966
7 .361 3.279 92.245
8 .272 2.473 94.718
9 .225 2.042 96.760
10 .209 1.896 98.656
11 .148 1.344 100.000
Extraction Method: Principal Component Analysis.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .881
Bartlett's Test of Approx. Chi-Square 209.189
Sphericity Df 55
Sig. .000
9

10. R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) FOR FACTOR 1 (ONE)
Reliability Coefficients 8 items
Alpha = .9136 Standardized item alpha = .9145
Reliability Coefficients FOR FACTOR 2(TWO) 3 items
Alpha = .7911 Standardized item alpha = .7910
COMPAQ
Rotated Component Matrix(a)
Component
1 2 3
BATTER
.428
Y
SPEAK .825
SOUND .753
LCD .523
MOVI .856
MUSIC .688
ENTERT .645
ATTRAC
.799
T
STYL .832
FEELBET
.878
T
LOGO .736
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization.
a Rotation converged in 12 iterations.
10

11. Total Variance Explained
Extraction Sums of Rotation Sums of Squared
Initial Eigenvalues Squared Loadings Loadings
% of Cumul % of Cumul % of Cumul
Compo Varian ative Varian ative Varian ative
nent Total ce % Total ce % Total ce %
1 5.109 46.448 46.448 5.109 46.448 46.448 3.241 29.465 29.465
2 1.486 13.511 59.959 1.486 13.511 59.959 2.867 26.062 55.528
3 1.183 10.755 70.714 1.183 10.755 70.714 1.670 15.186 70.714
4 .914 8.309 79.023
5 .728 6.620 85.643
6 .533 4.842 90.486
7 .336 3.058 93.544
8 .296 2.689 96.232
9 .190 1.725 97.957
10 .155 1.407 99.365
11 100.00
.070 .635
0
Extraction Method: Principal Component Analysis.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .778
Bartlett's Test of Approx. Chi-Square 194.454
Sphericity Df 55
Sig. .000
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) FOR FACTOR 1 (ONE)
Reliability Coefficients 4 items
Alpha = .8728 Standardized item alpha = .8812
Reliability Coefficients FOR FACTOR 2 (TWO) 5 items
Alpha = .7715 Standardized item alpha = .7722
Reliability Coefficients FOR FACTOR 3 (TWO) 2 items
Alpha = .7316 Standardized item alpha = .7372
11

12. INTERPRETATION:
In case of Cadbury factor one can be named ‘product feature’ factor as it contains variables taste,
smoothness and sweetness, all of which convey quality of the product.
Milky has low correlation with other three qualitative factors (.289, .406 and .287 for taste,
smoothness and sweetness respectively). Factor one has an alpha of .8878 which is great.
Factor two represents friendship, childhood and the feeling of being pampered. We call it the
‘childhood factor’. It has a relatively low alpha at .69, which borders the acceptance level of .70.
We accept the factor.
Factor three represents love and colour and we call it the ‘romance factor’. But it has a very low
alpha value of .3662 implying that this factor may be measuring multidimensionality.
In case of Axe factor one can be named the ‘product feature’ factor as it contains variables variety
and skin care both of which convey quality of the product. But it also contains variables like style,
youth, fashion, and x factor, which are non product attribute related. However correlation among
them is high and significant meaning these emotional qualities have been strongly associated and
identified with the two product factors. This factor has high alpha value of .9136.
The second factor, again, is measuring the emotional benefits like the feeling of being elite or a
class feeling, fashionable, and fun. This non-attribute factor can be called ‘fashion factor’. This
factor has an alpha value of .7911
Compaq also yields two factors the first of which relates to the emotional benefits like feeling
competent, attraction, and style. It has an alpha value of.8728.
The second factor is clearly a ‘product attribute factor’ measuring sound, battery, speaker and
LCD screen. It has an alpha score of .7715.
The third factor measures entertainment value and contains movie and music variables.
The third factor has an alpha value of .7316.
Bartlett's Test of Sphericity has been done to test for the reliability of the factor.
Bartlett's Test of Sphericity tests the null hypothesis that the intercorrelation matrix comes from a
population in which the variables form an identity matrix. If it is an identity matrix it would
extract as many factors as variables, since each variable would be its own factor. And Kaiser-
Meyer-Olkin Measure of Sampling Adequacy test has also been done.
If two variables share a common factor with other variables, their partial correlation (aij) will be
small, indicating the unique variance they share.
If aij ≅ 0.0
The variables are measuring a common factor, and KMO ≅ 1.0
If aij ≅ 1.0
The variables are not measuring a common factor, and KMO ≅ 0.0
For all three factor analysis done the Bartlett's Test of Sphericity is significant at .000.
And the KMO scores are .738, .881, and .778 for Cadbury, Axe and Compaq repectivly.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO)
12

13. KMO Value Degree of Common Variance
0.90 to 1.00 Marvelous
0.80 to 0.89 Meritorious
0.70 to 0.79 Middling
0.60 to 0.69 Mediocre
0.50 to 0.59 Miserable
0.00 to 0.49 Don't Factor
ANCOVA:
Univariate Analysis of Variance
MODEL 1
Between-Subjects Factors
Value Label N
INVOLVEM 1
Low
ENT 34
involvement
LEVELS
2 Medium
34
involvement
3 High
32
involvement
Tests of Between-Subjects Effects
Dependent Variable: ATTITUDE
Type III Sum
Source of Squares df Mean Square F Sig.
Corrected Model 133273.412(a) 8 16659.176 10.233 .000
Intercept 542359.443 1 542359.443 333.143 .000
INVOLVEM 44768.606 2 22384.303 13.750 .000
NPF 53447.047 1 53447.047 32.830 .000
PF 11874.539 1 11874.539 7.294 .008
INVOLVEM *
14657.975 2 7328.988 4.502 .014
NPF
INVOLVEM * PF 9322.060 2 4661.030 2.863 .062
Error 148148.718 91 1628.008
Total 820530.360 100
Corrected Total 281422.130 99
a R Squared = .474 (Adjusted R Squared = .427)
13

14. MODEL 2
Between-Subjects Factors
Value
Label N
Trus 1 Low
t trust 51
ratio ratio
2 Medium
n trust 23
ratio
3 High
trust 26
ratio
Tests of Between-Subjects Effects
Dependent Variable: Attitude
Type III Sum
Source of Squares df Mean Square F Sig.
Corrected Model 125745.942(a) 8 15718.243 9.188 .000
Intercept 328536.855 1 328536.855 192.045 .000
TRUSTRAT 41607.309 2 20803.655 12.161 .000
PF 3873.284 1 3873.284 2.264 .136
NPF 18441.985 1 18441.985 10.780 .001
TRUSTRAT *
5272.548 2 2636.274 1.541 .220
PF
TRUSTRAT *
16792.134 2 8396.067 4.908 .009
NPF
Error 155676.187 91 1710.727
Total 820530.360 100
Corrected Total 281422.130 99
a R Squared = .447 (Adjusted R Squared = .398)
Model one shows that there is significant interaction between NPF and involvement level, which
means the influence of the covariate take into account the value or the category of the factor
(level of involvement). But there is no significant interaction between PF and involvement at 5
percent significance level.
However the main effects show NPF and involvement level to have the highest influence.
If we wanted to get a “semipartial R-square” for just the effects of NPF, after controlling for these
other two variables, we would look at the Type III SS for NPF, and compare it to the “corrected
total” Type III SS.
14

15. Semipartial R^2 for “NPF” = Type III SS for NPF/“corrected total” Type III SS
= 53447.047/281422.130 = 0.1899177 or 19%
Semipartial R^2 for “involvement” = 44768.606/281422.130 = 15.907%
Semipartial R^2 for “PF” = 11874.539/281422.130 = .0421947 or 4.219%
Semipartial R^2 for “involvement*NPF” = 14657.975/281422.130 = 0.052085 or 5.208%
Model two, again, shows significant interaction between Trust and NPF. And Trust and NPF has
much higher main effects than PF. PF does not have significant main effect at 5% significance.
Semipartial R^2 for “NPF” = 18441.985/281422.130 = 6.553%
Semipartial R^2 for “Trust*NPF” = 16792.134/281422.130 = 5.966%
Semipartial R^2 for “Trust” = 41607.309/281422.130 = 14.784%
IMPLICATIONS:
From ANCOVA we find that the influence of emotion (NPF) make significant differences in
brand attitude and that the extent of this influence is mediated by both trust and involvement level.
But even without interactions the main effects of emotion (NPF) is quite palpable. In other words
the extent of influence of emotion on brand attitude depends on how involved the product
requires the consumer to be to consume it and how much the consumer trusts the band.
But, as has been mentioned, emotion has large individual influence on brand attitude as well,
regardless of trust and involvement level.
In conflict with some of the theories*, emotion has been found to be intruding where, by
common perception, rationality only should reign. For different products with different
involvement levels, emotion has been found to be making a significant difference in the
formation of brand attitude.
To understand the degree and the direction of the influence of emotion regression analysis is
helpful. The following are the information from that effort.
Beta:
For Cadbury (low involvement):
PF = -.086, NPF = -.204
For Axe (medium involvement)
PF = -.415, NPF = -.484
For Compaq (high involvement)
PF = -.109, NPF= -.666
15

16. Emotion is making continuously larger impact on brand attitude, as for higher involvement level
products the slope (beta) is continuously increasing. It has to be seen whether higher involvement
means larger impact of emotion on brand attitude or not. A Chow test has been done to test
whether this increase holds true for the population or not.
The Chow test basically sees if slope for two or more groups are similar or not or in other words
if two regression lines are different from one another. It was originally designed
to analyze the same variables obtained in two different data sets to determine if they were similar
enough to be pooled together.
The test is run in SPSS. As it cannot be done with GUI, Paste (command) was used.
Tests of Between-Subjects Effects
Dependent Variable: ATTITUDE
Source Type III Sum of Squares DF Mean Square F Sig.
INVOLVEM * NPF 14657.985 2 7328.993 3.282 .042
INVOLVEM * PF 9322.044 2 4661.022 1.721 .184
It shows that emotion (NPF) significantly differs in different involvement levels. And we can
infer that emotion contributes more for higher involvement level products as it shown by the
regression slopes.
Conclusion*:
Based on what we have found here, we can safely say that the brand and product manager has
more scope and elbow space to position the brand on emotional parameters and not restrict
themselves to exploring only the product attribute, price based positioning. Acceptance of the fact
that emotion is a supremely powerful gift of the mind, can lead us to yet unexplored facets of
marketing. Advertising can, for example, take a lot from this realisation and go for creatives that
address the emotions more.
The rational and thinking area of the FCB grid is invaded strongly by emotion from the emotional
and feeling area. When feeling becomes heavily important, then it has to be explored, tested and
proved how much of thinking really happens and when and for what exactly.
*THIS CONCLUSION IS NOT EXHAUSTIVE.
YOUR CONTRIBUTION IN COMMENTS AND CRITICISM IS HEARTILY WELCOM.
16

17. REFERENCES:
17