Mapping of Online Shopping behaviour: A Dark Triad Approach

Shweta Shivani ., Dr. Benny J. Godwin .


The main purpose of this study is to examine a probable association between personality factors and the online shopping behavior of a consumer. A design of descriptive research is found to be suitable for carrying out the analysis for the framed objectives. A questionnaire with 3 sections is devised, consisting of demographic factors, dark triad of personality, and online shopping behavior. A multi-stage random sampling technique was utilized for the research. The paper focuses on the determination of impact of personality factors with respect to Dark triad in formulating the online shopping behavior of an online consumer. This is in lieu of the correlation of the concepts of Marketing and psychology. The results obtained cannot be generalized for the entire customer segment. The limitations are also possible because of the fact that the analysis is based on the responses obtained on the basis of questionnaire distributed to the respondents. The present study mainly deals with the consumer behavior aspect of an individual. It takes into account the personality of a person in an individual way that affects his/her choices over an online e-commerce platform. Thus, it will result in understanding the needs and preferences of probable customers who are surfing items over online domain. The research will provide insight over the basis of decision making of an online consumer based on his/her individual personality traits which will lead to him/her ordering a product online.


Dark Triad of Personality, Online Shopping Behavior, Demographic Factors and Personality Factors.

Full Text:



Ahmeda, R. A., Shehaba, M. E., Morsya, S., & Mekawiea, N. (2015). Performance Study of Classification Algorithms for Consumer Online Shopping Attitudes and Behavior Using Data Mining. 2015 Fifth International Conference on Communication Systems and Network Technologies. doi:10.1109/csnt.2015.50

Boyu, K. (2012). The Empirical Study of Motivators for Online Shopping Demand Based on Behavior Analysis. 2012 Second International Conference on Business Computing and Global Informatization. doi:10.1109/bcgin.2012.65

Chynal, P., Sobecki, J., Rymarz, M., & Kilijanska, B. (2016). Shopping behavior analysis using eyetracking and EEG. 2016 9th International Conference on Human System Interactions (HSI). doi:10.1109/hsi.2016.7529674

Devkishin, K. R., Rizvi, A. H., & Akre, V. L. (2013). Analysis of factors affecting the online shopping behavior of consumers in U.A.E. 2013 International Conference on Current Trends in Information Technology (CTIT). doi:10.1109/ctit.2013.6749507

Garibaldi, J., Ferguson, E., & Aickelin, U. (2014). A Data Mining Framework to Model Consumer Indebtedness with Psychological Factors. 2014 IEEE International Conference on Data Mining Workshop. doi:10.1109/icdmw.2014.148

Godwin, B. J. (2013). Experiencing the experience: Psychodynamics of customer citizenship behavior (CCB).

Gu, H. (2011). An Empirical Study on Inexperienced Online Consumer's Window Shopping Behavior in China: A Trust Analysis Model. 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing. doi:10.1109/wicom.2011.6040647

Hanyang Luo, Yanan Yu, Xinwei Han, & Yanhua Zhang. (2016). The effect of online shops' unexpected services on Costumer Citizenship Behaviors. 2016 13th International Conference on Service Systems and Service Management (ICSSSM). doi:10.1109/icsssm.2016.7538538

Hsieh, J., & Liao, P. (2011). Antecedents and Moderators of Online Shopping Behavior in Undergraduate Students. Social Behavior and Personality: an international journal, 39(9), 1271-1280. doi:10.2224/sbp.2011.39.9.1271

Jonason, P. K., & Webster, G. D. (2010). The dirty dozen: A concise measure of the dark triad. Psychological Assessment, 22(2), 420-432. doi:10.1037/a0019265

Krejcie, R. V., & Morgan, D. W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30(3), 607-610. doi:10.1177/001316447003000308

Lee, K., Ashton, M. C., Wiltshire, J., Bourdage, J. S., Visser, B. A., & Gallucci, A. (2012). Sex, Power, and Money: Prediction from the Dark Triad and Honesty-Humility. European Journal of Personality, 27(2), 169-184. doi:10.1002/per.1860

Liangfang Huang, & Lingling Wang. (2011). Research on the application of 4Ps marketing theory based on Chinese Consumer Psychology. 2011 International Conference on Business Management and Electronic Information. doi:10.1109/icbmei.2011.5916956

Liao, S., & Chung, Y. (2011). The effects of psychological factors on online consumer behavior. 2011 IEEE International Conference on Industrial Engineering and Engineering Management. doi:10.1109/ieem.2011.6118142

Li, F., & Liu, Z. (2010). Study on the Main Influencing Factors on the Online Shopping Behavior of the Undergraduate. 2010 International Conference on Management and Service Science. doi:10.1109/icmss.2010.5576582

Li, S., & Liang, L. (2011). An Empirical Study of College Students' Online Shopping Behaviors. 2011 International Conference on Computer and Management (CAMAN). doi:10.1109/caman.2011.5778903

Miller, J. D., Dir, A., Gentile, B., Wilson, L., Pryor, L. R., & Campbell, W. K. (2010). Searching for a Vulnerable Dark Triad: Comparing Factor 2 Psychopathy, Vulnerable Narcissism, and Borderline Personality Disorder. Journal of Personality, 78(5), 1529-1564. doi:10.1111/j.1467-6494.2010.00660.x

Miller, J. D., & Lynam, D. R. (2015). Psychopathy and Personality: Advances and Debates. Journal of Personality, 83(6), 585-592. doi:10.1111/jopy.12145

Mohammadinejad, A., Farahbakhsh, R., & Crespi, N. (2016). Employing Personality Feature to Rank the Influential Users in Signed Networks. 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom). doi:10.1109/bdcloud-socialcom sustaincom.2016.59

Muris, P., Meesters, C., & Timmermans, A. (2013). Some Youths have a Gloomy Side: Correlates of the Dark Triad Personality Traits in Non-Clinical Adolescents. Child Psychiatry & Human Development, 44(5), 658-665. doi:10.1007/s10578-013-0359-9

O'Boyle, E. H., Forsyth, D. R., Banks, G. C., Story, P. A., & White, C. D. (2014). A Meta-Analytic Test of Redundancy and Relative Importance of the Dark Triad and Five-Factor Model of Personality. Journal of Personality, 83(6), 644-664. doi:10.1111/jopy.12126

Qiao, Y., Zhang, Y., Lindgren, A., & Yang, J. (2016). Understanding online shopping and offline mobility behavior in urban area from the view of multilayer networks. 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC). doi:10.1109/icnidc.2016.7974608

Sheng-Chin Yu, & Fu, F. (2010). Investigating customer needs and evaluation behavior in online shopping. 2010 IEEE International Conference on Advanced Management Science (ICAMS 2010). doi:10.1109/icams.2010.5553124

Shi, B., Li, S., Zhang, X., & Zhang, D. (2017). Social- versus personal-oriented purchases: impacts of worry versus sadness on young consumers. Journal of Consumer Marketing, 34(7), 566-576. doi: 10.1108/jcm-02-2017-2117

Social Changes Provide Valuable Clues to Consumer Behavior in the Marketplace. (1984).

Wang, C., & Sie, C. (2012). A Study of Consumers' Trust in Online Shopping between Pick-up Goods Behavior in the Convenience Stores. 2012 26th International Conference on Advanced Information Networking and Applications Workshops. doi:10.1109/waina.2012.7

Yang, N. (2010). Consumer Behavior in Electronic Commerce.

Yi, F., & Fan, G. (2011). An Empirical Study on Consumer Purchase Intention Affecting Online Shopping Behavior. 2011 International Conference on Management and Service Science. doi:10.1109/icmss.2011.5998965

Yuan, K. (2005). Fit Indices Versus Test Statistics. Multivariate Behavioral Research.

Yu, W., Yan, C. G., Ding, Z., Jiang, C., & Zhou, M. (2016). Modeling and Verification of Online Shopping Business Processes by Considering Malicious Behavior Patterns. IEEE Transactions on Automation Science and Engineering, 13(2), 647-662. doi:10.1109/tase.2014.2362819

Zeigler-Hill, V., & Vonk, J. (2015). Dark Personality Features and Emotion Dysregulation. Journal of Social and Clinical Psychology, 34(8), 692-704. doi:10.1521/jscp.2015.34.8.692

Zhang, L., Li, Z., & Azamat, B. (2012). A Study of University Students' On-line Shopping Behavior Traits and Influencing Factors. 2012 Fifth International Conference on Business Intelligence and Financial Engineering. doi:10.1109/bife.2012.141

Zhuo, D., & Xiaoting, Z. (2010). An Empirical Study on Factors which Affect Consumers' Online Shopping Behavior. 2010 International Conference on E-Business and E-Government. doi:10.1109/icee.2010.556


  • There are currently no refbacks.

Editorial Office:

Educational Research Multimedia & Publications,
S.N. 21, Plot No 24, Mirza Ghalib Road Malegaon Nasik,
Maharashtra India - 423203.
+919764558895 (whatsapp),,

Copyrights © 2010-2020 - ERM Publications, India     

This work is licensed under