Understanding Cognitive Dissonance of Indian Customers for Financial
Products: A Multi-Dimensional Scale Development Approach
Brajesh Bolia PhD
Assistant Professor of Marketing
K J Somaiya Institute of Management Studies &
Research, Mumbai, India
E-mail: [email protected]
Sumi Jha PhD
Associate Professor of General Management
NITIE, Mumbai, India
E-mail: [email protected]
Manoj K Jha PhD
Professor of General Management
NITIE, Mumbai, India
E-mail: [email protected]
Abstract
The aim of the
study was to understand the dynamics of cognitive dissonance in the context of
financial product purchase. A mixed methodology research approach was
undertaken to explore the attitudinal and behavioural dimensions (qualitative)
and subsequent empirical validation (quantitative) with a sample of customers
of financial products. Qualitative research was conducted through focus group
discussions to arrive at a pool of 99 items which were then pruned and
validated with the help of academic and industry experts. The items were
empirically tested and validated with the help of appropriate statistical tools
to arrive at a �5 factor and 25 items� measurement scale for cognitive
dissonance. The study found two factors �Emotional Gain� & �Financial
Concern� as distinguishing factors emerging out as key findings. The
arousal of cognitive dissonance after the purchase decision taken by consumer
can be a major concern for marketers as it might result in order cancellations,
loss of trust for the brand as well as loss of loyal customers. Measuring
dissonance in financial product context post purchase can help marketers devise
appropriate strategies to reduce dissonance, thereby retaining and attracting
customers.
Keywords: Cognitive dissonance,
Mixed Method, Financial Product, Purchase Decision.������������������������������������������������������������������
1. Introduction
The term cognitive dissonance (Festinger,
1957) has been researched exhaustively since
its inception. With declining focus during 1970s-80s, it regained the attention
of the researchers during 1990s (Aronson, 1992). Cognitive dissonance (Festinger, 1957) post-purchase in services (Hill,
1977) has been marketers� subject of
curiosity and importance, as it directly affected the post-purchase behavior of
the customer. Marketers have used the theory of cognitive dissonance (Festinger, 1957) mainly to investigate the dissonance
experienced by customers� post-purchase of a product (Seger-Guttmann, Vilnai-Yavetz, Wang & Petruzzellis, 2018; Telci,
Maden & Kantur, 2011; Wilkins, Butt & Heffernan, 2018). Cognitive dissonance has been primarily studied by western
researchers (Aronson, 1992; Brehm & Cohen, 1962;
Cooper, 2007; Cooper & Fazio, 1984; Cummings & Venkatesan, 1976; Egan,
Santos & Bloom, 2007; Harmon-Jones & Harmon-Jones, 2007; Hinojosa,
Gardner, Walker, Cogliser & Gullifor, 2017; Hunt, 1970; O'Neill &
Palmer, 2004; Kim, 2011; Oshikawa, 1968; Powers & Jack, 2013; Wilkins,
Beckenuyte & Butt, 2016) with very few Indian
studies reported (Bawa & Kansal, 2008; George & Edward,
2009; Viswesvaran & Deshpande, 1996; Viswesvaran, Deshpande & Joseph,
1998). India being an emerging economy and
going through extreme market changes regarding
customers� product choice, the gap between customer perception regarding a
product and producer�s imagination of product is widening. Hence, the Indian customers who are learning
from their western counterparts are becoming more and more demanding (Gupta, 2013; Jaiswal, 2008). While
there had been enough research in customer behavior in consumer goods with
respect to cognitive dissonance (Charron & Redondo,
2018; Telci et al., 2011) ever
since the Festinger came up with his theory of cognitive dissonance, little
research had been done on the application of cognitive dissonance to the
service industry (Kim, 2011).
Service sector comprises almost 70% of GDP in developed countries and more than
50% of the GDP in India and other developing countries (Services-Report, September, 2019). The
services sector of India remains the engine of growth for India�s economy and
contributed 54.17 percent of India�s gross value added in 2018-19 and the
sector grew at 12.75 percent growth in 2018-19 (Services-Report,
September, 2019). The growth in services (Gopalan & Singhi, 2015) had
generally not been due to marketing developments in the service industries, but
rather to the maturation of economy and rising living standards. Service
industry making a huge impact on today�s economy calls for a more intense
research in the field of cognitive dissonance in service industry especially
the financial sector. The rate of growth and the size of the financial services
sector as a proportion of the economy (Gross National Savings as percentage of
GDP is 30% as on March 2018) was a good reason to single out the sector for
special consideration (Arnold et al., 2016;
Financial-Services-Report, September, 2019).
�There
seems to be a wide difference in the treatment of financial products in the
Indian market and western market (Costanzo & Ashton,
2006; F�nfgeld & Wang, 2009; Gait & Worthington, 2008; Vyas & Raitani,
2014). Indian customers being more
conservative in financial matters, therefore, might feel more dissonance post-purchase (Bawa
& Kansal, 2008). The study attempted to develop a scale
on cognitive dissonance capturing concerns of Indian customers from emerging
market context. A mixed method approach (using qualitative methods as well as
quantitative methods) was used to develop and validate the measurement scale.
The
concept of cognitive dissonance was introduced by Festinger (1957; 1962) who stated that if
an individual holds two cognitions/cognitive elements (�knowledge� about
himself, his environment, his opinions, his attitudes and his past behavior)
that are inconsistent with one another, the individual will experience dissonance
and will try to reduce it in one of the three ways: remove dissonant
cognitions, add new consonant cognitions, or reduce the importance of dissonant
cognitions. The cognitive dissonance theory assumes a drive like motivation to
maintain consistency among the relevant thoughts and actions. The theory of
cognitive dissonance is one of the groups of cybernetic theories called
consistency theories, all of which begin with the same premise: people are more
comfortable with consistency than inconsistency (Heider,
1946). The evolution of the theory of
cognitive dissonance seems to have developed with the notion that people are
more comfortable with consistency than inconsistency and try to resist, avoid
or change the contradictory information and knowledge.
�The literature review
suggested that enough research had been carried out and published since Festinger (1957) formulated the theory of cognitive
dissonance (Aronson, 1992; Bolia et al., 2016;
Brehm & Cohen, 1962; Cummings & Venkatesan, 1976; Egan et al., 2007;� Gbadamosi, 2009; Harmon-Jones & Harmon-Jones,
2007; Hinojosa et al., 2017; Hunt, 1970; Kim, 2011; Liao, 2017; O'Neill
& Palmer, 2004; Oshikawa, 1968; Oshikawa, 1972; Powers & Jack, 2013;
Shahin & Rahim, 2014; Soutar & Sweeney, 2003; Sweeney et al., 2000;
Telci et al., 2011; Yamaguchi & Abe, 2016; Wilkins et al., 2016;
Wilkins et al., 2018). Researchers have
used the theory of cognitive dissonance in the marketing
area extensively to address post-purchase
behavior of the customers at various stages as how it was controlled or reduced
(Cao & Just, 2010; Gbadamosi, 2009; Hunt, 1970; Liao, 2017; Soutar
& Sweeney, 2003; Wilkins et al., 2016; Yamaguchi & Abe, 2016). Post-purchase
communications affected the customers either ways (Hunt, 1970); hence organizations must carefully
choose the type of post-purchase
communication mode to connect with the customers. The customer�s decision of
purchase should get strengthened rather than create a doubt in mind due to the post-purchase communications (Hunt, 1970). Researchers also studied assurance from celebrities, local
opinion leaders and reputed citizens which caused strengthening of attitudes
towards a brand thereby ensuring the customers did not feel regret post-purchase (Dzisah
& Ocloo, 2013). Researchers attempted to devise
measures for cognitive dissonance in past (Bell, 1967; Hawkins,
1972; Hunt, 1970; Korgaonkar & Moschis, 1982), while (Montgomery & Barnes, 1993; Sweeney et
al., 2000) developed the measure with a higher number of items through a thorough literature review and proper empirical
validation. Montgomery & Barnes (1993) developed a measure of
ten items and validated the same by
assessing content validity, predictive validity and construct validity. The
scale was named as POSTDIS by the
researcher which was explained by two factors � �Correctness of Decision� (An
individual�s concern if he has taken the right
decision and not got influenced by the salesperson)
and �Support� (An individual looking for reinforcing its decision by supportive
information and actions in favor of the decision). The scale was not used by many researchers (Bose & Sarker 2012; Sweeney et al., 2000). A 22-item
scale for assessing cognitive dissonance, felt immediately after purchase, was
developed by Sweeney et al., (2000) conceptualizing the constructs recognizing that dissonance
was not only cognitive, but also had an
emotional component, consistent with Festinger�s early description of
dissonance as a psychologically uncomfortable state. Researchers concluded with a three dimensional model having following
constructs ��Emotional� (A
person�s psychological discomfort subsequent to the purchase decision), �Wisdom of Purchase� (A person�s
recognition after the purchase has been made that they may not have needed the
product or may not have selected the appropriate one) and �Concern over the
deal� (A person�s recognition after the purchase has been made that they may
have been influenced against their own beliefs by sales staff). The
scale had been used by various
researchers in their studies (Bolia et al., 2016; Soutar &
Sweeney, 2003; Sweeney et al., 2000; Kim, 2011). The theory of cognitive dissonance (Festinger, 1957) was widely accepted, however the
measurement had been an issue in services sector in the Indian context where
the significance of post purchase decision carries high importance due to
increasing purchasing power of customers (Country forecast India
August, 2018). Financial products� purchase might be
associated with high dissonance and higher confusion due no clear differences
between competing brands and customers� involvement is higher (Assael, 2005).
The
systematic way to develop and validate a construct, following predetermined
principles and procedures, is known as scale development (Farooq, 2016). The study conducted a research
methodology that combined both the perspectives, qualitative and quantitative,
known as the mixed methodology (Sreejesh & Mohapatra, 2013; Teddlie &
Tashakkori, 2011). The mixed methodology research was
undertaken to explore the attitudinal and behavioral dimensions (qualitative),
and their empirical validation (quantitative) and these two approaches were
applied in sequential form (first qualitative followed by quantitative). The
central premise of the study was to understand the concept of cognitive
dissonance, an idea which had strong literature support, however, required empirical
validation of the scale in the Indian financial sector context. The study
started with extensive literature review on cognitive dissonance. This
understanding helped the researchers in categorizing the scale development
process into three different phases. Phase �I was a qualitative study (focused
group discussion) that explored the attitudes and feelings of customers just
after making a purchase decision, the findings were subjected to face validity.
Phase-II looked at empirical scale development using quantitative techniques
(factor analysis) to arrive at a suitable measure for cognitive dissonance.
Phase �III comprised of validation of the measure derived from Phase-II using
quantitative techniques (Factor analysis). All the three phases and their
sampling details are explained in the subsequent sections.
3.1 Phase-I - Scale Development (Qualitative Research)
Four
Focus group discussions (FGD) were conducted as a part of qualitative research
of phase I. The FGDs (Bryman & Bell, 2011) were conducted with different groups of students as well as
working individuals to understand the concept of cognitive dissonance, its
causes, and subsequent effects. The data obtained from the focus group
discussions were analyzed using attribution analysis, a part of the semantic
content analysis (Janis, 1965).
Authors examined the frequency with which certain characterizations or
descriptors were used. It was a simple counting exercise, but the emphasis was
on adjectives, adverbs, and descriptive phrases. The quotes from the
participants were used to extract 99 important words from the analysis of the
focus group discussions (Table 1). The pool of important words was converted
into items for the development of questions. The questionnaire developed based
on these items, was subjected to face validity by taking inputs from experts in
the field of behavioral science and marketing, both from academia as well as
industry. Total seven expert opinions were considered, three were from
academia, and four were from industry. Their suggestions based on the
relevance, repetition, framing of statements, appropriateness for cognitive
dissonance, were incorporated and the item list was reduced to 53.
� Table 1. Important Quotes from
Focus Group Discussions
|
QUOTES of Participants |
Imp Words |
|
"When I do some
purchase, then it feels like the task has been
accomplished, my to do list is reducing and feeling of
satisfaction" - Participant 7 FGD 4 |
Accomplishment,
satisfaction |
|
"When I purchase
anything which I wanted to buy for a long time it gives a kick, feel happy and
emotionally uplifted. Also, there is a
feeling of concern about the performance of the product like in
electronics" - Participant 8 FGD 4 |
Happy, kick, emotionally
uplifted, |
|
"Am I making the
right choice in the view of several brands which are available in the market
"- Participant 8 FGD 4 |
Right choice |
|
" Soon after
purchase decision again we compare if the decision was right" -
Participant 9 FGD 3 |
Compare |
|
"After taking the decision to purchase, seek review
and suggestions about the deal" - Participant 1 FGD 3 |
Review, suggestions |
|
"Think of resale of
exchange"- Participant 6 FGD 3 |
Resale, exchange |
|
"Was it a paisa vasool or good value for money?"-
Participant 3 FGD 3 |
Value for money |
|
"Flaunt the product
after taking the decision to
purchase" - Participant 2 FGD 3 |
Flaunt |
|
"Have we spent
more" - Participant 1 FGD 2 |
Spend |
|
"Have I got a bad
deal" - Participant 3 FGD 2 |
Bad, deal |
|
"Regret after
purchasing a premium product" - Participant 8 FGD 2 |
Premium product, regret |
|
"After impulse
buying feeling of regret comes if done right or not "- Participant 6 FGD
2 |
Impulse, regret, buying |
|
" Feel cheated
sometimes"- Participant 8 FGD 2 |
Cheating, |
|
"Feel
frustrated"- Participant 9 FGD 2 |
Frustration |
|
Feel dissatisfied"-
Participant 9 FGD 2 |
Dissatisfied |
|
"Blame self " -
Participant 1 FGD 1 |
Blame |
|
"When stressed out,
looking for stress busters and just roaming around and ended up buying
something then it gives enjoyment" - Participant 10 FGD 4 |
Stress Buster, enjoyment |
|
"If buying a
personal care thing for me, kids and family then I feel very happy but when I
buy for others than it is ok�like a neutral feeling" - Participant 11
FGD 4 |
Happy, ok |
|
"Price plays role value for money - companion in
shopping affects no feeling of a wrong
decision, but with family, a thought
comes if the decision was right or not" -
Participant 5 FGD 4 |
Price, value for money,
wrong decision, thought, right, wrong |
����������������������������������������������������������������������������������������
3.2 Phase-II - Scale Development
(Quantitative Analysis)
Questionnaire
for cognitive dissonance, based on the 53 items obtained from focus group
discussions and face validation analysis (Phase �I), was floated to respondents
who had bought any financial product in the past. The questionnaire was
self-administered and was also distributed through a web-based form, and the
research used 135 responses for analysis. Purposive sampling method was used,
and the sample was chosen based on a judgmental basis. All respondents were
either working executives or earning members and had bought some financial
product in the past.�
|
Sample
Characteristics � Phase-II - Scale Development (Quantitative Analysis) |
|
Gender�� � Male 56% Female 44% Average Age / Max Age /
Minimum Age / Mode Age � 28.30 / 44 / 23 (Years) Education � Post Graduate
& Graduates � 97% Employment� � 84% Private Sector Employees |
� Exploratory factor
analysis was conducted on initial 53 items of cognitive dissonance. Missing
value treatment was done for three items by replacing the missing values with a
mean of the series method (Figure 1 & Appendix). Principal component
analysis method and the rotated component extraction method were used to
extract five factors containing 25 items with the criterion of Eigenvalues
greater than 1. These five factors containing 25 items explained 71.395% of the
variance which was above the desired levels of 60% (Malhotra & Dash, 2014). The
statistics associated with sample adequacy were also satisfactory with KMO
Value as 0.906 and Bartlett�s Test of Sphericity value as 0.000 (Hair Jr, Black, Babin & Anderson, 2013). The
result obtained from the exploratory factor analysis was subjected to
confirmatory factor analysis (CFA) to confirm the latent structure (Figure 1).
Factor 1 had nine items and explained 24.397% of the variance. This factor
explained the feelings of discomfort and concerns (Gregory-Smith, Smith & Winklhofer, 2013) like �I felt horrible,� �I felt cheated.�� Factor 2 consisted of 8 items explaining
21.68 % of the variance. This factor explained about the sense of
accomplishment and achievement (Heckhausen, 2013) with items constituting this factor like �I felt relieved,�
�I felt satisfied.�� Factor 3 had four
items explaining 12.467 % of the variance. The items constituting this factor
�I should have waited,� �I should have sought suggestions� explained the
dilemma and the regret about the wisdom of the decision. Customers are often
faced with thoughts of uncertainties, and lack of knowledge (Berger, 2013) about the purchase and hence after
thoughts may pop up post-purchase decision. Factor 4 comprised of two items
explaining 6.604% of the variance.� The
items explaining this factor �It was a stress buster� and �I felt emotionally
uplifted� showed the sense of emotional gratification (Cassotti et al., 2012) the
individual obtained after deciding consonance with thinking and feeling. Factor
5 was comprised of 2 items explaining 6.385% of the variance. The items under
this factor �I paid a higher price� and �I spent more� explained the concerns
about the financial wisdom (Klontz, Sullivan, Seay & Canale, 2015) of the customer after purchase decision was made.
��
While reviewing the fit indices for confirmatory factor analysis, we
observed that the hypothesized scale was well- fitting as indicated by value of
Normed Chi-Square as 1.539 (Segars & Grovers, 1993), CFI value of 0.942, TLI value of 0.934, RMSEA value of
0.063, RMR value was 0.040, which were well within the recommended range of
acceptability (Byrne, 2013; Hair et al., 2013). Construct Reliability (Hair et al., 2013) was found appropriate (Factor 1= 0.95, Factor 2= 0.92,
Factor 3= 0.86, Factor 4= 0.78 & Factor 5= 0.64).� The statistics associated with goodness of
fit appeared to be explaining the well-fitting scale. Hence, the model with
five factors and 25 items was accepted for further validation.
Figure 1. CFA - Scale Development
(Phase- II)
Note- The nomenclature for the Observed
& Latent items are being explained in
Appendix
3.3 Phase-III � Scale Validation
(Quantitative Analysis)
This phase considered validation of the scale developed in
the phase-II analysis. A questionnaire based on the 25 items obtained after Phase-II
analysis was administered to the respondents from various fields in person and
through web-based forms. The questionnaire
was again administered to respondents who
had bought any financial product in the past.�
Purposive sampling method was used; the sample was chosen on a judgmental basis and forms were sent to individuals
who were earning members and had bought some financial product in the past. Total 125 respondents were considered for analysis for the validation
of the measure.
|
Sample
Characteristics � Phase-III - Scale Validation (Quantitative Analysis) |
|
Gender� � Male 57.6% Female 42.4% Average Age / Max Age /
Minimum Age � 28/ 44 / 23 (Years) Education � Post Graduate
& Graduates � 98.4% Employment �90.4% Salaried |
�
�
Confirmatory factor analysis was performed on the 25 items obtained in
the Phase-II analysis; principal component method and the rotated component
matrix were used. The extraction method used was forced factor method keeping
the 5-factor structure. Forced factor method of extraction was performed as the
scale developed in the previous phase with five factors and 25 items needed
validation (Hair et al., 2013). All the items could be retained based on the confirmatory
factor analysis (CFA) with 25 items and five factors explaining 71.831% of the
variance (Figure 2). Construct Reliability (Hair et al., 2013) was measured for all the factors obtained after validation
and was found appropriate (F1CD=0.95, F2CD=0.93, F3CD=0.86, F4CD=0.79 &
F5CD=0.64). The statistics associated with Factor Analysis indicated the
appropriateness of the data. The KMO value found was 0.900 which indicated
sampling adequacy appropriateness (Values should be above 0.50). Bartlett�s
Test of Sphericity was performed and the significance value found was 0.000
(should be less than 0.05) which indicated significant correlations among the
variables being tested (Hair et al., 2013). While reviewing these fit indices, it was observed that the
scale was well- fitting as indicated by value of Normed Chi-Square as 1.664 (Segars & Grovers, 1993), CFI value of 0.923, TLI value of
0.913, RMSEA value of 0.073 and RMR value of 0.044, which were well within the
recommended range of acceptability (Byrne, 2013; Hair et
al., 2013). The statistics associated with goodness
of fit appeared to be explaining the well-fitting model with five factors and
25 items (Appendix). The five factor measurement model values showed better
model fit in comparison to 3 factors (combining factors 5, 4, and 3) and 4
factors (combining factors 4 & 5) (Table 2). The emerged five factors were
named as emotional concern, achievement, decision concern, emotional gain and
financial concern. �The underlying
philosophy behind naming and retaining factor has been mentioned in discussion
section.
�
Table 2. Comparative Models � Scale Validation � Phase-III (CD)
|
CFA Analysis |
3 Factor Model |
4 Factor Model |
5 Factor Model |
|
Normed Chi-Square |
2.172 |
1.837 |
1.664 |
|
CFI |
0.860 |
0.902 |
0.923 |
|
GFI |
0.740 |
0.773 |
0.794 |
|
AGFI |
0.689 |
0.724 |
0.746 |
|
RMR |
0.070 |
0.085 |
0.044 |
|
RMSEA |
0.097 |
0.082 |
0.073 |
|
TLI |
0.846 |
0.890 |
0.913 |
|
ECVI |
5.618 |
4.891 |
4.529 |
Figure 2. CFA - Scale Validation
(Phase- III)
Note- The nomenclature for the Observed
& Latent items are being explained in
Appendix
4. Discussion and
Contribution
There had
been very few focused studies on scale development for the concept of cognitive
dissonance. This study aimed to develop a scale for measurement of the concept
of cognitive dissonance in the context of the Indian financial sector.� This study used the mixed method (Sreejesh & Mohapatra, 2013; Teddlie & Tashakkori, 2011) approach to arrive at a final measure consisting of 25
items covered under 5 distinguishing factors in confirmation with the existing
literature (Montgomery & Barnes, 1993; Sweeney et
al., 2000) as well as emphasizing on the 2
aspects of �emotional gain� and �financial concern� relevant to the Indian
financial sector context. The statistics related to the model provided a very
good explanation for a fit model specifying factors within desirable limits to
satisfy the suitability of the model explaining cognitive dissonance. The
research proposed five factors based on the empirical scale building and
validation exercise. These are �Emotional Concern,� �Achievement,� �Decision
Concern,� �Emotional Gain� and �Financial Concern.�
Research
in emotions has witnessed an increase in numbers suggesting that emotions
played an integral role in organizational efforts to connect with their
customers. It has also been demonstrated that understanding of emotions, both
self, and others, played an important role in the organization�s life, in how
people communicated, how people motivated others to do what they wanted (Berman & Brooks, 2002). Buyers
do not like to be duped as feeling duped produces an aversive self � conscious
emotional response with peril of self-blame (Vohs et al., 2007).
Lakomski & Evers (2010) proposed a substantial revision in
Herbert Simon's modified model of rational choice that sharply demarcates
emotions and values from rationality and rational decision making (Simon, 1955), and concluded that emotion has a
central role to play in rational decision making. A negative emotion after
purchase decision which violates one�s values and norms might result in
consumer guilt (Burnett & Lunsford, 1994) and frustration (Kandra et al., 2004). Therefore, �Emotional Concern� formed an important factor
for marketers to respond to customer needs and the first factor consisted of 9
items explaining 24.02% of the variance. This factor elucidated the feelings of
discomfort and concerns (Gregory-Smith et al., 2013) such as �I was fooled,� �I felt cheated,� and �I felt
guilty� etc.
The
second factor �Achievement� consisted of 8 items explaining 22.085% of the
variance explaining the sense of accomplishment and achievement (Heckhausen, 2013). The items
constituting this factor were �I felt relieved,� �I felt satisfied,� and �I
felt happy� in congruence with what was suggested by Woodruff et al., (1983) and Walters & Bergiel (1989) that
customers anticipated and expected satisfaction out of a planned purchase.
However, Woodruff et al. (1983) also stated that both satisfaction (cognitive evaluations)
and feelings (emotions) could be anticipated. Past research also indicated the
importance of anticipated satisfaction or the utility of the purchase before
consumption (Modigliani & Brumberg, 1954); however, marketing academicians have neglected the same to
a larger extent. Research has emphasized the importance of a sense of feel and
experience as a feeling of accomplishment (Tomkins & Eatough, 2013) and the association of utilitarian and hedonic shopping
values resulting in satisfaction, repeat buying intentions, loyalty for a brand
and word of mouth activities (Vieira et al., 2018).
Customers
also felt dissonant if the thoughts of uncertainty occurred due to doubts about
the transaction process such as procuring the product in good physical shape
and from, legally compliant and in the right time as per the specified features
expected. Anderson et al., (2015) referred
transaction uncertainty as �easy-to-use procedures for doing business,
processing orders accurately, and providing reliable and timely deliveries.�
Customers are also exposed to dilemma and regret due to uncertainties and lack
of knowledge (Berger, 2013)
about the wisdom of the decision taken, causing concerns about the purchase
decision taken. Participants in the focus group quoted �Soon after purchase
decision again we compare if the decision was right" - Participant 9 FGD
3� and �After taking the decision to purchase, seek review and suggestions
about the deal" - Participant 1 FGD 3� thereby strengthening the premise
that customers might feel concerned about the purchase decision is made.
Customers might also experience dissonance due to counterfactual thinking post
purchase decision (Mannetti et al., 2007). This study proposed the factor �Decision Concern� as third
factor that explained 12.502% of the variance and consisted of 4 items as �I
should have waited more�, �I felt incongruence with the decision�, �I felt like
reviewing my purchase decision� and �I felt I should have sought suggestion�.
�
The
fourth factor �Emotional Gain� explained the sense of emotional gratification (Cassotti et al., 2012) the
individual got after deciding consonance with thinking and feeling. This factor
explained 6.804% of the variance and comprised of 2 items as �It was a stress
buster� and �I felt emotionally uplifted.� Post-purchase and pre-consumption
experience of customers has attracted many researchers in recent years (Kim & Mattila, 2010; Menon & Dube, 2007; Weber & Sparks,
2009), thereby indicating strong explanation
for the factor �Emotional Gain� experienced by customers after making a
purchase decision. A focus group respondent expressed a feeling of joy after
making a purchase ("When I purchase anything which I wanted to buy for a
long time it gives a kick, feel happy and emotionally uplifted and there is a
feeling of concern about the performance of the product like in
electronics" - Participant 8 FGD 4) (Table 1). Customers indulged in
impulse buying (Hausman, 2000)
might feel a sense of emotional fulfillment (Meadows, 2013) after purchase. Various factors could contribute, towards
customers feeling a sense of emotional victory and emotional satisfaction after
taking a purchase decision, such situation such as discount availed, the
ambience of the store, emotional attachment to a product, being the first to
buy, and peer influence (Mishra, 2012). According
to Mattila & Enz (2002), understanding of customers� emotional expressions during
the purchase transaction could also help sales and service personnel to
customize their products to the target segments.
�
The fifth
factor �Financial Concern� depicted the psychology of Indian customers as
suggested by Kopalle & Lindsey-Mullikin (2003) that when customers experienced unexpected price encounter,
they adopted one of the three methods of reducing dissonance such as; engaging
in biased or filtered information to support prior belief; search for
information about other retailers and substitute products that are consistent
with their state; re-evaluate the price in relation to the external reference
prices. Customers are also influenced by competitors� prices (Wagner, 1987), price knowledge (Aalto-Set�l� & Raijas, 2003), and price perception (Munnukka, 2008) which might affect the post-purchase
feelings about the pricing concerns in the form of spend and price comparison (Jung et al., 2014; McMahon, 2005). One of the focus group participants expressed a feeling of
concern �Have we spent more" - Participant 1 FGD 2� and another stated
�Was it a �paisa vasool� or good value for money?"- Participant 3 FGD 3�,
which confirms the presence of financial concern and interest among Indian
customers. This factor explained 6.42 % of the variance and was comprised of 2
items as �I paid a higher price� and �I spent more� explaining the concerns
about the financial wisdom (Klontz et al., 2015) of the customer.
� Being conservative,
customers in India take extra precautions while choosing any financial
products. Extending the research of (Sweeney et al., 2000) the study contributes
to understanding the dissonance Indian customers are facing in dealing with
financial products. Indian customers being more traditional and believe in
taking calculated risk in financial matters, might feel more dissonance
post-purchase. The research contributes to the aspects of �emotional gain� and
�financial concern� relevant for Indian context. Previous studies noted the
role of emotions, concern for deal and wisdom of purchase in facing dissonance (Sweeney et al., 2000). This
study contributes with reference to financial concerns and emotional gain as
distinguishing factors of cognitive dissonance.
The study
could help managers evaluate their sales customer interface dynamics and look
for improvements towards higher customer orientation (Mukerjee, 2013). The ability to provide superior
customer experience is essential while making efforts to establish and sustain
long‐term customer relationships (Berry
et al., 2002). Customers in search to make buying and
consuming tasks simpler, improve information processing, shrink perceived
risks, and maintain cognitive uniformity and a state of psychological ease look
for assurance during the sales �customer interface (McColl-Kennedy et al., 2015).
The willingness and ability of marketers to engage with customers and provide
assurance during the sales-customer interface can help reduce post-purchase
dissonance, increase customer satisfaction and positive word of mouth for the
brand.� The scale would help managers in
identifying specific areas where organization shall focus given a set of
customers. If the concern is emotional the sales person will take decisions to
enhance emotional gains. If the concern is financial, the sales personnel will
focus the discussion on providing sufficient justification to satisfy financial
concerns. Measuring dissonance post-purchase could help marketers devise
appropriate strategies to retain and attract customers. Financial product sales
are largely dependent on sales personnel and customer interface if not
purchased online (Easingwood & Storey, 1991). Financial product sales require the sales personnel to be
more focused towards an understanding of the product details of self as well as
competitor products, to assure and help the customer take the right decision
and reducing dissonance.
The
purpose of the study was to develop a scale for cognitive dissonance in the
Indian context. Factors proposed in this study covered all the aspects of the
cognitive dissonance measures developed by previous authors and provided a
valuable explanation by expanding the role played by emotions in a purchase
decision. The scale also captured the price-sensitive Indian customer mind-set
by extracting a factor financial concern. The factors emerged in the study also
explained and corroborated with the existing factors in literature such as
�Correctness of Decision� & �Support� (Montgomery & Barnes,
1993), �Emotional parameters�, and �Wisdom of
purchase� and �Concern for Deal� (Sweeney et al., 2000). While the study brought the important aspects of emotional
gains and financial concerns, the scale could be further validated by
conducting similar studies on different samples. The suitability for the scale
could be empirically tested with products other than financial products like;
shopping and specialty goods (Kaish, 1967). A
study involving self-employed segment may be conducted for understanding the
robustness of the scale in a variety of sample. Though cross-sectional studies
provide valuable insights (Liu & Wang, 2016) a longitudinal study covering changes in dissonance levels
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Appendix
Final Scale Items �
Cognitive Dissonance
|
F1CD = Emotional Concern CD 25 - I felt my purchase
decision was horrible� CD 27 - I felt I was fooled CD 28 - I felt I was cheated CD 29 - I felt frustrated CD 46 - I cursed myself CD 47 - I felt guilty CD 48 - I felt withdrawing my
purchase decision CD 50 - I tried to forget the
purchase decision CD 53 - I felt it was not my
taste F2CD = Achievement CD 6 - I felt relieved CD 7 - I felt happy CD 8 - I liked what I bought CD 9 - I felt satisfied CD 10 - I felt positive CD 11_1 - I felt I took the
right decision CD 17_1 - I accomplished what I
wanted CD 31_1 - I felt confident F3CD = Decision Concern CD 33 - I felt some incongruence
with the decision CD 34 - I felt I should have
waited for more before making a purchase decision��� CD 35 - I felt like reviewing my
purchase decision CD 36 - I felt I should have
sought suggestion before making a purchase decision F4CD = Emotional Gain CD 51 - It was a stress buster CD 52 - I was emotionally
uplifted F5CD = Financial Concern CD 1 - I felt I paid higher
price CD 4 - I felt I spent more |
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