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: brajeshbolia@hotmail.com


Sumi Jha PhD

Associate Professor of General Management

NITIE, Mumbai, India

E-mail: sumijha05@gmail.com


Manoj K Jha PhD

Professor of General Management

NITIE, Mumbai, India

E-mail: manojkjha40@yahoo.co.in



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; Fünfgeld & 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.

2. Literature Review

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).

3. Research Methodology

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


"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


"Have we spent more" - Participant 1 FGD 2


"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


"Feel frustrated"- Participant 9 FGD 2


Feel dissatisfied"- Participant 9 FGD 2


"Blame self " - Participant 1 FGD 1


"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   à Male 56% Female 44%

Average Age / Max Age / Minimum Age / Mode Age à 28.30 / 44 / 23 (Years)

Education – Post Graduate & Graduates à 97%

Employment  à 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  à Male 57.6% Female 42.4%

Average Age / Max Age / Minimum Age à 28/ 44 / 23 (Years)

Education – Post Graduate & Graduates à 98.4%

Employment à90.4% 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





































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.”


4.1 Emotional 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.


4.2 Achievement

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).


4.3 Decision Concern

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”.


4.4 Emotional Gain

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.


4.5 Financial Concern

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-Setälä & 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.


4.6 Managerial Implications

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 longterm 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.


5. Limitations & Future Directions

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 with age might give an insight regarding differences in perception among different generation respondents.



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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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