Cognitive Dissonance amongst Youth of Jalandhar City for Purchase of Online Apparels

 

Dr. Ritu Sehgal

Assistant Professor, DAV Institute of Engg & Technology, Jalandhar

 

ABSTRACT:

Cognitive dissonance as a state which comes into existence when a person gets confused between two cognitions (thoughts), which cannot exist together and hence create tension for him, Festinger, 1957. In this paper an attempt has been made by the researcher to find out the factors affecting cognitive dissonance amongst youth for purchase of apparels. Along with an attempt has also been made to analyze the relation between gender and dissonance in online purchase of apparels amongst youth. It has been found that there is no significant association between Gender and Customer Satisfaction. After applying the factor analysis, nine factors titled ‘Timely Delivery, Value, Psychological Cost, Easeness for Search, Impulsive Buying, User Friendliness, Reasonable Price, Convenience and Reliability’ have been extracted. The study has been done on 100 respondents of age group between 18-24 years of Jalandhar city.

 

 

 

INTRODUCTION:

Cognitive Dissonance is an integral part of the Consumer Behaviour. As per Festinger, 1957, describes cognitive dissonance as a psychological phenomenon that occurs when there exists a discrepancy between what a person believes in and the outcome which questions a person’s belief. Sweeney, Hausknecht and Soutar, 2000 describes that a consumer is bound to be dissonant if there is a discrepancy between the satisfaction levels he had expected from a product and between the satisfactions; he actually received from the product. It has also been argued that cognitive dissonance not only comprises of cognitive elements but emotional elements as well. Elliot and Devine, 1994 “many researchers have argued that cognitive dissonance is mainly experienced through psychological discomfort”.

 

This study is about cognitive dissonance amongst youth in online purchase of apparels and various variables like quality, price, impulsive buying, personality of an individual, friends and family influences have been discussed in this paper.

 

LITERATURE REVIEW:

Jessica Santos J. and Boote J. (2003) in their paper named “A theoretical exploration and model of consumer expectations, post-purchase affective states and affective behaviour” presented a theoretical model exploring the interrelationship between expectations, affective post-purchase states and affective behaviour.

 

Awa H. O. and Nwuche C.A. (2010) in their paper titled “Cognitive Consistency in Purchase Behaviour: Theoretical and Empirical Analyses” analysed and synthesized the major theoretical and empirical body of knowledge of the three theories with a view to proffering a tripartite approach (involving the consumers, the organizations and the governments) to solving inconsistency among cognitive elements (e.g.; values, beliefs, knowledge and attitudes). Kumar V. and Sharma R. (2010) in their paper named “Impact of Cognitive Dissonance on Consumer Behaviour” have explored the factors which affect the consumer buying behaviour and analysed post purchase consumer behaviour. Bose T.K. and Sarker S. (2012) in their paper named “Cognitive Dissonance Affecting Consumer Buying Decision Making: A study Based on Khulna Metropolitan Area” have examined 10 variables in the form of: belief, norms, customs, family status, political ideology, emotional reaction, personal performance, culture, religious value and peer group influence. The results of the study showed that these factors do impact the cognitive dissonance amongst customers. Costanzo P.J. (2013) in his paper “Revisiting Cognitive Dissonance Theory: Pre-Decisional Influences and the Relationship to the Consumer Decision-Making Model” examined pre-decisional dissonance as a motivating factor in consumer decisional-making. Sharma M.K. (2014) in his paper named “The Impact on Consumer Buying Behaviour: Cognitive Dissonance” has explored the factors creating cognitive dissonance such as family status, religious believes, customs. Kyhe S. (2015) in his paper named “Cognitive dissonance and its influence on online reviewers” provided a thorough examination of signs of CD in reviewers, and offers a negative result in terms of how the reviews reflect Apple’s attempts to counter dissonance. Brajesh Bolia B., Jha S. et al. (2016) in their paper named “Cognitive Dissonance: A Study of Post Purchase Behaviour of Consumers in the Context of Financial Products” found that there was no significant difference in the levels of Cognitive Dissonance due to Demographic Factors such as Age, Gender, Education, while it was observed that students felt high and medium levels of cognitive dissonance after purchasing a financial product.

 

RESEARCH METHODOLOGY:

Research Objectives:

1     To extract the factors influencing cognitive dissonance amongst youth in online purchase of apparels.

2     To analyze the relation between gender and dissonance in online purchase of apparels amongst youth.

 

Hypotheses:

There is no significant relation between Gender and dissonance amongst youth.

 

Sample Size:

Sample size of 100 respondents had been taken due to time and money constraints.

 

Research Methodology:

Apposite with the objectives of the present study, the relevant data has been obtained from secondary as well as primary sources. The various secondary information sources used for the present research include various journals and magazines. The primary data was collected from 100 respondents who are college students. A well-structured questionnaire was prepared and distributed to the customers who shop online Jalandhar City of Punjab. Convenience and judgment sampling techniques were adopted in the selection of the respondents. Data was collected in the months of March 2017. For analyzing the data, chi-square and factor analysis has been applied. The data was analyzed using Statistical Package for the Social Sciences (SPSS). The data collected through survey was analyzed for accomplishment of the stated objectives.

 

Test Applied:

Factor Analysis and Chi Square test has been applied under this study.

 

Data Analysis and Interpretation:

Demographic profile of the respondents:

Table No. 1 shows that in the gender response rate of survey, male respondents are (60%) and female respondents are (40%). The sample taken was between the age of 18 and 24 years as it is classified as youth by UN norms. In the sample of respondents 52% are Graduates, 32% are Post Graduates, 13% are High School Graduates and left 3% are pursuing some other courses.

 

Table No. 1: Demographic profile of respondents who purchase apparels online

Demographic Variables		Respondents (%)
Gender	Male	60
	Female	40
	Total	100
Age	18-24	100
	Total	100
Education	SSC	13
	Graduation	52
	Post-Graduation	32
	Other	3
	Total	100

 

An Analysis of Gender of Respondents with Cognitive Dissonance

In this section, relationship of gender with satisfaction level of online purchases amongst youth has been analysed. Table No. 2 describes the cross tabulation between age and satisfaction level of customers.

 

Table No. 2: Cross Tabulation between Gender and Satisfaction Level

	Customer Satisfaction
Gender	Yes (%)	No (%)	Total
Male	50	10	60
Female	28	12	40
Total	78	22	100

Table No. 2 reveals that highest percentages of satisfied customers are male (50%). In category of male, 50% customers are satisfied and 10% are unsatisfied. In case of female, 28% customers are satisfied and 12% are unsatisfied.

 

Table No. 3: Chi Square for Gender and Satisfaction Level

	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	2.486	1	.115
Likelihood Ratio	2.445	1	.118
Linear-by-Linear Association	2.462	1	.117
N of Valid Cases	100

 

It has been found from the Table No. 3 that in online purchasing, the Pearson chi square calculated value is .115 which is greater than .05(p > .05). Hence, null hypothesis is accepted. It means that there is no significant association between Gender and Satisfaction Level.

 

An Analysis of the Factors Influencing Cognitive Dissonance of Online Purchasers of Apparels:

Factor loading represents the magnitude of factors which explains the variables. High loading indicates that factors strongly influence the variables. Factor analysis has been applied to investigate the relationship among the variables which were supposed to determine or affect consumers’ perspectives on Online Shopping Services. 30 statements were framed in the final questionnaire which contains most of the statements in assertive form. These statements were evaluated on 5-point Likert scale by the respondents. Data collected through questionnaire provided inputs for factor analysis. For analysis, first of all Kaiser-Meyer-Olkin measure of sampling adequacy was calculated to test the sampling adequacy and it was 0.799. Table No. 4 shows the Kaiser-Meyer-Olkin measure of sampling adequacy.  It indicates that the sample is good enough for sampling. The overall significance of correlation matrix was tested with Bartlett test of sphericity (chi-square= 1.35923 and significant at 0.000).  This supports the validity of applying the factor analysis.

 

Table No. 4: KMO and Bartlett's Test of Sphericity

 

 

Table No. 5: Total Variance Explained

	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
Component	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	8.426	28.086	28.086	8.426	28.086	28.086	4.727	15.757	15.757
2	2.260	7.532	35.617	2.260	7.532	35.617	2.560	8.533	24.290
3	2.014	6.715	42.332	2.014	6.715	42.332	2.469	8.229	32.519
4	1.846	6.153	48.485	1.846	6.153	48.485	2.334	7.780	40.299
5	1.529	5.095	53.581	1.529	5.095	53.581	2.031	6.769	47.068
6	1.362	4.542	58.122	1.362	4.542	58.122	1.847	6.156	53.224
7	1.244	4.147	62.269	1.244	4.147	62.269	1.760	5.865	59.089
8	1.200	3.999	66.268	1.200	3.999	66.268	1.686	5.620	64.708
9	1.113	3.711	69.979	1.113	3.711	69.979	1.581	5.271	69.979
10	.854	2.846	72.825
11	.808	2.694	75.519
12	.775	2.582	78.101
13	.722	2.408	80.510
14	.687	2.291	82.801
15.	.626	2.086	84.887
16.	.522	1.740	86.627
17.	.494	1.646	88.273
18.	.418	1.393	89.666
19.	.411	1.368	91.034
20.	.374	1.247	92.281
21.	.330	1.100	93.381
22.	.311	1.037	94.418
23.	.268	.893	95.311
24.	.261	.869	96.180
25.	.247	.823	97.002
26.	.233	.776	97.778
27.	.197	.658	98.436
28.	.177	.589	99.025
29.	.166	.555	99.580
30.	.126	.420	100.000

 

 

 

Table No. 6: Factors extracted after Factor Analysis

 

After applying factor analysis, the researcher has come up with nine factors named Timely Delivery, Value, Psychological Cost, Easeness for Search, Impulsive Buying, User Friendliness, Reasonable Price, Convenience and Reliability which are shown under Table No.6. Factor “Timely Delivery” contains statement “The product is delivered on time”. It states that the time factor influences the level of dissonance amongst customers. The factor loading is 69.979% in this factor. The second factor is “Value” which has statements “The purpose of buying the clothes was important” and “The purpose for buying clothes online was served properly”. The factor loading is 64.708%. The third factor is “Psychological Cost” which represents statements “Shopping clothes online saves time” and “Customer compares the same type of apparels from different websites”. The factor loading in this is 59.89%. The fourth factor is “Easeness for search” and the statement is “Customer searches for clothes online with my family and friends”. The factor loading is 53.224 %. The fifth factor is “Impulsive Buying” which has statement “Customer spends too much money on shopping clothes online”. The factor loading is 47.068%. The sixth factor is “User Friendliness” which contains statements “Customer spends significant time for shopping online” and “It is easy to search for clothes online”. The factor loading is 40.299%. The seventh factor is “Reasonable Price” and the statements are “The online prices of apparels are better than the prices of physical retail shops” and “The discounts available online are worth considering”. The factor loading is 32.519 %. The eighth factor is “Convenience” and the statements are “The return/replace policy of the online websites is convenient” and “The return/replace policy of the online website saves time. The factor loading is 24.290 %. The ninth factor is “Reliability” and has five statements that are “Customer never regrets her/his decision after buying clothes online”, “Online websites for shopping clothes are safe”, “The clothes match with their description provided online”, “The clothes looked same as they were shown on the website” and “Transactions for payments are accurate and reliable when buying clothes online”. The factor loading is 15.575%.

 

DISCUSSION:

Thus, there is no significant association between Gender and Customer Satisfaction. After applying the factor analysis, nine factors titled ‘Timely Delivery, Value, Psychological Cost, Easeness for Search, Impulsive Buying, User Friendliness, Reasonable Price, Convenience and Reliability’ have been extracted. These factors played a very crucial role in affecting cognitive dissonance. Though the cognitive dissonance is less amongst youth but the number could be improved further by providing better services to the customers. It may include better guidance and accountability by the service providers. Online purchasing trend in clothes are increasing in small towns like Jalandhar.

 

REFERENCES:

1.     Cummings W. H. and Venkatesan M. (1976), “Cognitive Dissonance and Consumer Behaviour: A Review of the Evidence”, Journal of Marketing Research, Vol. XIII, pp. 303-308.

2.     Jessica Santos J. and Boote J. (2003), “A theoretical exploration and model of consumer expectations, post-purchase affective states and affective behaviour”, Journal of Consumer Behaviour, Vol. 3, Issue 2, pp. 142–156

3.     Awa H. O. and Nwuche C.A. (2010), “Cognitive Consistency in Purchase Behaviour: Theoretical and Empirical Analyses”, International Journal of Psychological Studies, Vol. 2, No. 1, pp. 44-54

4.     Kumar V. and Sharma R. (2010), “Impact of Cognitive Dissonance on Consumer Behaviour”, International Journal of Latest Trends in Engineering and Technology, Vol. (8), Issue (1), pp.132-139

5.     Hasan U and Nasreen R (2012), “Cognitive Dissonance and Its Impact On Consumer Buying Behaviour”, IOSR Journal of Business and Management (IOSRJBM), Volume 1, Issue 4, pp. 07-12

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9.     Costanzo P.J. (2013), “Revisiting Cognitive Dissonance Theory: Pre-Decisional Influences and the Relationship to the Consumer Decision-Making Model”, Atlantic Marketing Journal Volume 2, Issue 1, pp. 42-49

10.   Sharma M.K. (2014), “The Impact on Consumer Buying Behaviour: Cognitive Dissonance”, Global Journal of Finance and Management, Volume 6, Number 9, pp. 833-840

11.   Hasan U. and Nasreen R. (2014), “The Empirical Study of Relationship between Post Purchase Dissonance and Consumer Behaviour”, Journal of Marketing Management June 2014, Vol. 2, No. 2, pp. 65-77

12.   Nordvall A.C. (2014), “Consumer Cognitive Dissonance Behaviour in Grocery Shopping”, International Journal of Psychology and Behavioral Sciences 2014, Vol. 4(4), pp.128-135

13.   Kyhe S. (2015), “Cognitive dissonance and its influence on online reviewers (A study of dissonance in people who recently wrote a review of Apple on Trustpilot.com)”, Bachelor’s Thesis, pp.1-79

14.   Pandey A.C. and Jamwal M. (2015), “Realizing the Impact of Cognitive Dissonance in Predicting Consumer Behaviour”, Journal of Social Sciences 2016, Vol.12 (1), pp. 36-41

15.   Brajesh Bolia B., Jha S. et al. (2016), “Cognitive Dissonance: A Study of Post Purchase Behaviour of Consumers in the Context of Financial Products”, International Journal of Innovative Research and Development, Vol 5, Issue 3, pp. 148-153

 

 

 

 

Received on 15.07.2017                Modified on 12.08.2017

Accepted on 22.09.2017            ©A&V Publications All right reserved