Why Do Consumers Return Products in E-Commerce? Evidence from Online Review Analysis

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, SI1 (2026), pp. 01–10
Proceedings of Selected Papers from the
National Conference on Emerging Trends in Commerce and Management
NCETCM-2K26
2026-03-30 to 2026-03-31
Vijayawada, Andhra Pradesh, India
Organized by Andhra Loyola College, Vijayawada, India
eISSN: 3107-9075

This work is licensed under a Creative Commons Attribution 4.0 International License .

Why Do Consumers Return Products in E-Commerce? Evidence from Online Review Analysis

Sunil Kumar Chokkandla, Venkata Srinivas Kumar Daruri

School of Management Studies, University of Hyderabad, Telangana, India

Abstract

Product returns have become a critical challenge in e-commerce, affecting operational efficiency, costs, and customer satisfaction. This study adopts a data-driven approach to examine the drivers of product returns using consumer-generated online reviews. A publicly available dataset was filtered to identify return-related reviews, from which 400 samples were analyzed. The study employs thematic analysis to identify key return drivers and complements it with sentiment analysis based on review ratings. The findings reveal five primary drivers of product returns: defective or damaged products, size and fit issues, expectation mismatch, poor product quality, and return/refund process-related concerns. The results highlight that return behaviour is influenced by both operational inefficiencies and perceptual gaps between expectations and actual product performance. Sentiment analysis indicates a strong dominance of negative emotions associated with return experiences. The study provides actionable insights for e-commerce firms to reduce return rates through improved product representation, quality control, and return policy design.

Keywords: E-commerce returns, Product return behaviour, Online reviews, Thematic analysis, Sentiment analysis.

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DOI: 10.66710/ijersem.v2si1.1

Open Access • Peer Reviewed Article

References

  1. C. Verhoef, P. K. Kannan, and J. J. Inman, “From Multi-Channel Retailing to Omni-Channel Retailing,” Journal of Retailing, vol. 91, no. 2, pp. 174–181, Jun. 2015. https://doi.org/10.1016/j.jretai.2015.02.005
  2. V. F. Yu, L. N. H. Vinh, P.-H. Hsu, and S.-W. Lin, “The cold chain vehicle routing problem in omni-channel retailing,” Expert Systems With Applications, p. 132564, Apr. 2026. https://doi.org/10.1016/j.eswa.2026.132564
  3. R. Manandhar and L. K. Siebeneck, “Information management and the return-entry process: Examining information needs, sources, and strategies after Superstorm Sandy,” International Journal of Disaster Risk Reduction, vol. 53, p. 102015, Dec. 2020. https://doi.org/10.1016/j.ijdrr.2020.102015
  4. K. Hjort and B. Lantz, “The impact of returns policies on profitability: A fashion e-commerce case,” Journal of Business Research, vol. 69, no. 11, pp. 4980–4985, Nov. 2016. https://doi.org/10.1016/j.jbusres.2016.04.064
  5. S. M. Mudambi and D. Schuff, “What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.Com,” MIS Quarterly, vol. 34, no. 1, pp. 185–200, Mar. 2010. https://doi.org/10.2307/20721420
  6. D. S. Rogers, D. M. Lambert, K. L. Croxton, and S. J. García‐Dastugue, “The returns management process,” The International Journal of Logistics Management, vol. 13, no. 2, pp. 1–18, Jul. 2002. https://doi.org/10.1108/09574090210806397
  7. J. C. Sweeney, D. R. Hausknecht, and G. Soutar, “Cognitive dissonance after purchase: A multidimensional scale,” Psychology & Marketing, May 2000. https://doi.org/10.1002/(SICI)1520-6793(200005)17:53.3.CO;2-7
  8. D. W. Rook and R. J. Fisher, “Normative Influences on Impulsive Buying Behavior,” Journal of Consumer Research, vol. 22, no. 3, p. 305, Dec. 1995. https://doi.org/10.1086/209452
  9. B. Verplanken and A. Herabadi, “Individual differences in impulse buying tendency: feeling and no thinking,” European Journal of Personality, vol. 15, no. 1_suppl, pp. S71–S83, Nov. 2001. https://doi.org/10.1002/per.423
  10. M. Tsiros and V. Mittal, “Regret: A Model of Its Antecedents and Consequences in Consumer Decision Making,” Journal of Consumer Research, vol. 26, no. 4, pp. 401–417, Mar. 2000. https://doi.org/10.1086/209571
  11. B. Syam Sundar, “The Rise of Quick Commerce and Its Business Implications,” International Journal of Emerging Research in Science Engineering and Management, vol. 2, no. si1, pp. 360–366, May 2026. https://doi.org/10.66710/ijersem.v2si1.46
  12. K. Floyd, R. Freling, S. Alhoqail, H. Y. Cho, and T. Freling, “How Online Product Reviews Affect Retail Sales: A Meta-analysis,” Journal of Retailing, vol. 90, no. 2, pp. 217–232, Jun. 2014. https://doi.org/10.1016/j.jretai.2014.04.004
  13. S. Chandra, S. Muniraj, S. Y. Reddy, V. Raju, B. R. Kumar, and S. K. Katta, “Blockchain and AI Integration in Fintech: Securing Financial Transactions and Ensuring Transparency,” 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC), GB Nagar, Gwalior, India, pp. 257–261, 2025. https://doi.org/10.1109/AIC66080.2025.11212004
  14. B. R. Kumar, S. Rajesh, N. A. K. Chowdari, and T. S. Lakshmi, “Digital Transformation in rural Governance: a case study,” International Journal of Emerging Research in Science Engineering and Management, vol. 1, no. 1, pp. 15–21, Jul. 2025. https://doi.org/10.58482/ijersem.v1i1.3
  15. Ganesh Babu M. P, “Consumer adoption of digital payment systems in Tier-2 and Tier-3 Indian Cities: A Technology Acceptance Model (TAM) approach,” International Journal of Emerging Research in Science Engineering and Management, vol. 1, no. 5, pp. 13–18, Nov. 2025. https://doi.org/10.58482/ijersem.v1i5.3
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This article is part of Volume 2, Special Issue 1 (May 2026)

2026-05-14