RETURN POLICY AS A RISK REDUCTION MECHANISM IN E-COMMERCE: INTEGRATING SIGNALLING THEORY WITH PRE AND POST-PURCHASE PERSPECTIVES
DOI:
https://doi.org/10.35631/AIJBES.829048Keywords:
Consumer Behaviour, E-commerce, Perceived Risk, Return Policy, Signalling TheoryAbstract
Uncertainty about product quality and transaction risk remains a major obstacle to e-commerce, which relies on indirect evaluation before purchase. Although return policies are widely regarded as an important mechanism for reducing consumers' perceived risk, the existing literature shows theoretical fragmentation and inconsistent empirical results regarding their effectiveness. Most previous studies have treated return policies unidimensionally, such as lenient vs strict, and rarely explicitly integrate them with the psychological and informational mechanisms underlying risk perception. To address this gap, this study uses a theory-based narrative review to present an integrative theoretical synthesis of the e-commerce return policy literature, explaining how various theoretical perspectives conceptualise the role of return policy in shaping perceived risk, post-purchase evaluation, and advanced consumer behaviour across the stages of the decision-making process. This study synthesises the fragmented literature on e-commerce return policies. By combining signalling theory, consumer risk theory, expectation disconfirmation theory, dissonance theory, procedural justice theory, and transaction cost economics, this study explains how return policy is conceptualised differently and how these theories complement one another in explaining consumer perceptions and behaviours. From a managerial perspective, this study highlights the importance of designing a balanced return policy that balances consumer-side risks with the sustainability of the company's operations.
Downloads
References
Ahmed, W., Huma, S., & Ali, S. U. (2023). Influence of return convenience on young buyers’ repurchase intentions. Young Consumers, 25(2), 149–169.
Ahsan, K., & Rahman, S. (2022). A systematic review of e-tail product returns and an agenda for future research. Industrial Management & Data Systems, 122(1), 137–166.
Akturk, M. S., Ketzenberg, M., & Yıldız, B. (2021). Managing consumer returns with technology-enabled countermeasures. Omega, 102, 102337. https://doi.org/10.1016/j.omega.2020.102337
Al-Adwan, A. S., & Yaseen, H. (2023). Solving the product uncertainty hurdle in social commerce: The mediating role of seller uncertainty. International Journal of Information Management Data Insights, 3(1). https://doi.org/10.1016/j.jjimei.2023.100169
Amirtha, R., Sivakumar, V. J., & Hwang, Y. (2020). Influence of Perceived Risk Dimensions on E-Shopping Behavioural Intention Among Women—A Family Life Cycle Stage Perspective. Journal of Theoretical and Applied Electronic Commerce Research, 16(3), 320–355. https://doi.org/10.3390/jtaer16030022
Babnik, K., Staresinic, C., & Lep, Ž. (2022). Some of the Workforce Face Post COVID After the Acute Phase of the Illness: The Employer’s Supportive Role. Human Systems Management, 41(2), 257–275. https://doi.org/10.3233/hsm-220003
Chen, J., Yu, B., Chen, B., & Liu, Z. (2023a). Lenient vs. stringent returns policies in the presence of fraudulent returns: The role of customers’ fairness perceptions. Omega, 117, 102843. https://doi.org/10.1016/j.omega.2023.102843
Chen, J., Yu, B., Chen, B., & Liu, Z. (2023b). Lenient vs. stringent returns policies in the presence of fraudulent returns: The role of customers’ fairness perceptions. Omega, 117, 102843. https://doi.org/10.1016/j.omega.2023.102843
Chen, W. K., Chen, C. W., & Lin, Y. C. (2023). Understanding the influence of impulse buying toward consumers’ post-purchase dissonance and return intention: An empirical investigation of apparel websites. Journal of Ambient Intelligence and Humanized Computing, 14(11), 14453–14466. https://doi.org/10.1007/s12652-020-02333-z
Chen, Y., Pang, T.-T., & Kuslina, B. H. (2023). The Effect of Price Discrimination on Fairness Perception and Online Hotel Reservation Intention. Journal of Theoretical and Applied Electronic Commerce Research, 18(3), 1320–1337. https://doi.org/10.3390/jtaer18030067
Choi, J., & Yoo, D. (2021). The Impacts of Self-Construal and Perceived Risk on Technology Readiness. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1584–1597. https://doi.org/10.3390/jtaer16050089
Church, E. M., DaSouza, R. O., & Awe, O. A. (2024). Examining the Antecedents of Return Policy Leniency in eCommerce. Journal of Electronic Commerce in Organizations, 22(1), 1–19. https://doi.org/10.4018/jeco.337362
Confente, I., Russo, I., Peinkofer, S., & Frankel, R. (2021). The challenge of remanufactured products: The role of returns policy and channel structure to reduce consumers’ perceived risk. International Journal of Physical Distribution and Logistics Management, 51(4), 350–380. https://doi.org/10.1108/IJPDLM-03-2020-0089
Ferraz, R. M., Veiga, C. P. d., Cássia Rita Pereira da Veiga, Furquim, T. S. G., & Silva, W. V. d. (2023). After-Sales Attributes in E-Commerce: A Systematic Literature Review and Future Research Agenda. Journal of Theoretical and Applied Electronic Commerce Research, 18(1), 475–500. https://doi.org/10.3390/jtaer18010025
García‐Dastugue, S. J., Nilakantan, R., Wallenburg, C. M., & Rao, S. (2023). On Merchandise Return Policy, Entrepreneurial Internet Retail, and Customer Reviews – Insights From an Observational Study. Journal of Business Logistics, 45(1). https://doi.org/10.1111/jbl.12342
García-Dastugue, S. J., Nilakantan, R., Wallenburg, C. M., & Rao, S. (2024). On merchandise return policy, entrepreneurial internet retail, and customer reviews – Insights from an observational study. Journal of Business Logistics, 45(1), e12342. https://doi.org/10.1111/jbl.12342
Gorton, M., Marek-Andrzejewska, E., Pang, G., Andrzejewski, W., & Lin, Y. (2024). Users’ processing of online marketplace listings for high and low involvement goods. Electronic Commerce Research and Applications, 65, 101382. https://doi.org/10.1016/j.elerap.2024.101382
Green, B. N., Johnson, C. D., & Adams, A. (2006). Writing narrative literature reviews for peer-reviewed journals: Secrets of the trade. Journal of Chiropractic Medicine, 5(3), 101–117. https://doi.org/10.1016/S0899-3467(07)60142-6
Han, X., Wang, F., Lv, S.-X., & Han, W. (2021). Mechanism Linking AR-Based Presentation Mode and Consumers’ Responses: A Moderated Serial Mediation Model. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 2694–2707. https://doi.org/10.3390/jtaer16070148
Jones, A. L., Miller, J. W., Whipple, J. M., Griffis, S. E., & Voorhees, C. M. (2023). The effect of perceptions of justice in returns on satisfaction and attitudes toward the retailer. International Journal of Physical Distribution & Logistics Management, 54(1), 40–60. https://doi.org/10.1108/IJPDLM-01-2022-0007
Ketzenberg, M., Abbey, J. D., Heim, G. R., & Kumar, S. (2020). Assessing Customer Return Behaviors Through Data Analytics. Journal of Operations Management, 66(6), 622–645. https://doi.org/10.1002/joom.1086
Li, M., Choudhury, A. H., & Du, J. (2026). Impact of impulse buying on product return in online shopping. Journal of Retailing and Consumer Services, 89, 104608. https://doi.org/10.1016/j.jretconser.2025.104608
Li, X., Ma, B., & Chu, H. (2021). The impact of online reviews on product returns. Asia Pacific Journal of Marketing and Logistics, 33(8), 1814–1828. https://doi.org/10.1108/APJML-02-2020-0074
Li, Y., Sheng, F., & Sun, Q. (2024). Embrace Uncertainty. Journal of Global Information Management, 32(1), 1–26. https://doi.org/10.4018/jgim.352521
Lin, J. D., Keinan, A., Chang, H. H., & Lehmann, D. R. (2025). The Robin Hood Effect in Transgressions Against Firms: How Political Ideology Shapes Consumer Justifications. Journal of Consumer Research. https://doi.org/10.1093/jcr/ucaf053
Lu, H., & Wung, Y.-S. (2021). Applying Transaction Cost Theory and Push-Pull-Mooring Model to Investigate Mobile Payment Switching Behaviors With Well-Established Traditional Financial Infrastructure. Journal of Theoretical and Applied Electronic Commerce Research, 16(2), 1–21. https://doi.org/10.4067/s0718-18762021000200102
Magano, J., Turčínková, J., Santos, M. C. dos, Correia, R., & Serebriannikov, M. (2024). Exploring Apparel E-Commerce Unethical Return Experience: A Cross-Country Study. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 2650–2672. https://doi.org/10.3390/jtaer19040127
Martinez, L. F., Martínez‐López, F. J., & Westland, J. C. (2023). Introduction: Special Issue on Digital Marketing and eCommerce. Electronic Commerce Research, 23(3), 1359–1360. https://doi.org/10.1007/s10660-023-09751-z
Martínez-López, F. J., Feng, C., Li, Y., & Sansó Mata, M. (2022). Restoring the buyer–seller relationship through online return shipping: The role of return shipping method and return shipping fee. Electronic Commerce Research and Applications, 54, 101170. https://doi.org/10.1016/j.elerap.2022.101170
Phau, I., Akintimehin, O., Shen, B., & Cheah, I. (2022). “Buy, Wear, Return, Repeat”: Investigating Chinese Consumers’ Attitude and Intentions to Engage in Wardrobing. Strategic Change, 31(3), 345–356. https://doi.org/10.1002/jsc.2503
Shao, B., Cheng, Z., Wan, L., & Yue, J. (2021). The impact of cross border E-tailer’s return policy on consumer’s purchase intention. Journal of Retailing and Consumer Services, 59, 102367. https://doi.org/10.1016/j.jretconser.2020.102367
Tai, Y.-N., & Chi, T. (2025). Unveiling the Factors Influencing U.S. Consumer Adoption of the Apparel Digital Retail Theater. Journal of Theoretical and Applied Electronic Commerce Research, 20(2), 60. https://doi.org/10.3390/jtaer20020060
Tueanrat, Y., Papagiannidis, S., & Alamanos, E. (2021). A Conceptual Framework of the Antecedents of Customer Journey Satisfaction in Omnichannel Retailing. Journal of Retailing and Consumer Services, 61, 102550. https://doi.org/10.1016/j.jretconser.2021.102550
Tzavlopoulos, Ι., Gotzamani, K., Andronikidis, A., & Vassiliadis, C. (2019). Determining the impact of e-commerce quality on customers’ perceived risk, satisfaction, value and loyalty. International Journal of Quality and Service Sciences, 11(4), 576–587. https://doi.org/10.1108/IJQSS-03-2019-0047
Ülkü, M. A., & Gürler, Ü. (2018). The impact of abusing return policies: A newsvendor model with opportunistic consumers. International Journal of Production Economics, 203, 124–133. https://doi.org/10.1016/j.ijpe.2018.05.016
Wang, Y., Anderson, J., Joo, S.-J., & Huscroft, J. R. (2020). The leniency of return policy and consumers’ repurchase intention in online retailing. Industrial Management & Data Systems, 120(1), 21–39. https://doi.org/10.1108/IMDS-01-2019-0016
Yang, X., Ma, Y., & Han, J. (2023). Product Information the More The better? A Moderated Mediation model to Explain Consumer Purchasing Intention In cross-Border E-Commerce. Asia Pacific Journal of Marketing and Logistics, 35(11), 2601–2620. https://doi.org/10.1108/apjml-08-2022-0723
Yang, Y., Ma, Y., Wu, G., Guo, Q., & Xu, H. (2022). The Insights, “Comfort” Effect and Bottleneck Breakthrough of “E-Commerce Temperature” During the COVID-19 Pandemic. Journal of Theoretical and Applied Electronic Commerce Research, 17(4), 1493–1511. https://doi.org/10.3390/jtaer17040075
Zhang, Y., Ikonen, I., Eelen, J., & Sotgiu, F. (2025). One size does not fit all: Optimizing size-inclusive model photography mitigates fit risk in online fashion retailing. Journal of the Academy of Marketing Science, 53(2), 643–672.
