Dark Patterns in Indian E-Commerce Interfaces and Consumer Purchase Regret
DOI:
https://doi.org/10.31305/rrjss.2025.v05.n01.052Keywords:
Dark patterns, consumer purchase regret, e-commerce, consumer protection, deceptive designAbstract
Dark patterns are user-interface designs that are designed to trick users into making a purchase or giving up their data that they would not have made otherwise. On 30 November 2023, India introduced them within the framework of the law through the Central Consumer Protection Authority's notification of the Guidelines for Prevention and Regulation of Dark Patterns, which declared thirteen practices as being unfair trade practices under the Consumer Protection Act, 2019. This paper explores the prevalence of these practices in the Indian Digital Commerce landscape and the routes via which these practices elicit purchase regret in the consumers. The study relied solely on the secondary sources of the regulatory instrument and its taxonomy, prevalence studies published by the ASCI Academy and Parallel study (12,000 screens across 53 Indian apps), international benchmark studies (11,000 shopping sites and 240 mobile apps), and the enforcement orders of the Central Consumer Protection Authority. The results have shown that deceptive design is almost ubiquitous with 52 of the 53 examined applications featuring at least one deceptive pattern, and the e-commerce sector had 5.3 patterns per application as compared to the average of 2.7 across all examined sectors. The four patterns (namely: privacy deception, drip pricing, interface interference and false urgency) represent 78 per cent of all events recorded. These can be mapped to the components of regret theory and it seems that the latter mainly causes process regret, which comes from a wrong decision procedure, and not outcome regret, which comes from a bad product. The paper suggests that this distinction is relevant to the regulation, as process harms cannot be measured in satisfaction-based consumer metrics and recommends disclosure-based remedies, implementation of an interface audit protocol and the creation of an enforcement system suited to the scale of the problem.
References
Advertising Standards Council of India (ASCI) Academy and Parallel (2024). Conscious Patterns: A Study of Deceptive Patterns in Top Indian Apps. Mumbai: ASCI Academy. Available at: https://www.ascionline.in
Bell, D.E. (1982). Regret in decision making under uncertainty. Operations Research, 30(5), 961–981. https://doi.org/10.1287/opre.30.5.961
Bhoot, A.M., Shinde, M.A. and Mishra, W.P. (2020). Towards the identification of dark patterns: An analysis based on end-user reactions. In Proceedings of the 11th Indian Conference on Human-Computer Interaction (IndiaHCI ’20). New York: ACM, 24–33. https://doi.org/10.1145/3429290.3429293
Bongard-Blanchy, K., Rossi, A., Rivas, S., Doublet, S., Koenig, V. and Lenzini, G. (2021). "I am definitely manipulated, even when I am aware of it. It’s ridiculous!" Dark patterns from the end-user perspective. In Proceedings of the 2021 ACM Designing Interactive Systems Conference (DIS ’21). New York: ACM, 763–776. https://doi.org/10.1145/3461778.3462086
Brignull, H. (2010). Dark Patterns: Deceptive Design. Available at: https://www.deceptive.design
Brignull, H. (2023). Deceptive Patterns: Exposing the Tricks Tech Companies Use to Control You. Testimonium Ltd.
Central Consumer Protection Authority (CCPA) (2023). Guidelines for Prevention and Regulation of Dark Patterns, 2023. Notified 30 November 2023 under Section 18 of the Consumer Protection Act, 2019. New Delhi: Department of Consumer Affairs, Government of India.
Cialdini, R.B. (2009). Influence: Science and Practice, 5th edn. Boston: Pearson Education.
Debnath, A. and Singh, S. (2024). Evaluating India’s dark patterns guidelines — advocating a comprehensive approach. Law School Policy Review. Available at: https://lawschoolpolicyreview.com
Di Geronimo, L., Braz, L., Fregnan, E., Palomba, F. and Bacchelli, A. (2020). UI dark patterns and where to find them: A study on mobile applications and user perception. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–14. https://doi.org/10.1145/3313831.3376600
Gray, C.M., Kou, Y., Battles, B., Hoggatt, J. and Toombs, A.L. (2018). The dark (patterns) side of UX design. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–14. https://doi.org/10.1145/3173574.3174108
Gray, C.M., Santos, C., Bielova, N., Toth, M. and Clifford, D. (2021). Dark patterns and the legal requirements of consent banners: An interaction criticism perspective. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–18. https://doi.org/10.1145/3411764.3445779
Gunawan, J., Pradeep, A., Choffnes, D., Hartzog, W. and Wilson, C. (2021). A comparative study of dark patterns across web and mobile modalities. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), Article 377, 1–29. https://doi.org/10.1145/3479521
Inman, J.J. and Zeelenberg, M. (2002). Regret in repeat purchase versus switching decisions: The attenuating role of decision justifiability. Journal of Consumer Research, 29(1), 116–128. https://doi.org/10.1086/339925
Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
Lee, S.H. and Cotte, J. (2009). Post-purchase consumer regret: Conceptualization and development of the PPCR scale. Advances in Consumer Research, 36, 456–462.
Liao, C., Lin, H.-N., Luo, M.M. and Chea, S. (2017). Factors influencing online shoppers’ repurchase intentions: The roles of satisfaction and regret. Information & Management, 54(5), 651–668. https://doi.org/10.1016/j.im.2016.12.005
Loomes, G. and Sugden, R. (1982). Regret theory: An alternative theory of rational choice under uncertainty. The Economic Journal, 92(368), 805–824. https://doi.org/10.2307/2232669
Luguri, J. and Strahilevitz, L.J. (2021). Shining a light on dark patterns. Journal of Legal Analysis, 13(1), 43–109. https://doi.org/10.1093/jla/laaa006
Mathur, A., Acar, G., Friedman, M.J., Lucherini, E., Mayer, J., Chetty, M. and Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), Article 81, 1–32. https://doi.org/10.1145/3359183
Mathur, A., Kshirsagar, M. and Mayer, J. (2021). What makes a dark pattern… dark? Design attributes, normative considerations, and measurement methods. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–18. https://doi.org/10.1145/3411764.3445610
Moser, C., Schoenebeck, S.Y. and Resnick, P. (2019). Impulse buying: Design practices and consumer needs. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–15. https://doi.org/10.1145/3290605.3300472
Narayanan, A., Mathur, A., Chetty, M. and Kshirsagar, M. (2020). Dark patterns: Past, present, and future. Communications of the ACM, 63(9), 42–47. https://doi.org/10.1145/3397884
Nouwens, M., Liccardi, I., Veale, M., Karger, D. and Kagal, L. (2020). Dark patterns after the GDPR: Scraping consent pop-ups and demonstrating their influence. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York: ACM, 1–13. https://doi.org/10.1145/3313831.3376321
Organisation for Economic Co-operation and Development (2022). Dark Commercial Patterns. OECD Digital Economy Papers No. 336. Paris: OECD Publishing. https://doi.org/10.1787/44f5e846-en
Roese, N.J. and Summerville, A. (2005). What we regret most… and why. Personality and Social Psychology Bulletin, 31(9), 1273–1285. https://doi.org/10.1177/0146167205274693
Sunstein, C.R. (2016). Fifty shades of manipulation. Journal of Marketing Behavior, 1(3–4), 213–244. https://doi.org/10.1561/107.00000014
Thaler, R.H. and Sunstein, C.R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. New Haven: Yale University Press.
Tsiros, M. and Mittal, V. (2000). Regret: A model of its antecedents and consequences in consumer decision making. Journal of Consumer Research, 26(4), 401–417. https://doi.org/10.1086/209571
Utz, C., Degeling, M., Fahl, S., Schaub, F. and Holz, T. (2019). (Un)informed consent: Studying GDPR consent notices in the field. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security. New York: ACM, 973–990. https://doi.org/10.1145/3319535.3354212
Waldman, A.E. (2020). Cognitive biases, dark patterns, and the privacy paradox. Current Opinion in Psychology, 31, 105–109. https://doi.org/10.1016/j.copsyc.2019.08.025
Zagal, J.P., Björk, S. and Lewis, C. (2013). Dark patterns in the design of games. In Proceedings of the 8th International Conference on the Foundations of Digital Games (FDG 2013). Chania: Society for the Advancement of the Science of Digital Games, 39–46.
Zeelenberg, M. and Pieters, R. (2007). A theory of regret regulation 1.0. Journal of Consumer Psychology, 17(1), 3–18. https://doi.org/10.1207/s15327663jcp1701_3