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Research on E-Commerce Platforms’ Return Policies Considering Consumers Abusing Return Policies

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  • Huixin Liu

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Feng Du

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

Abstract

Currently, major e-commerce platforms are competing to improve their return services, while merchants are suffering from consumers abusing return policies. We developed a dual oligopoly model consisting of two e-commerce platforms, one offering a lenient return policy and the other enforcing a stringent one, to investigate the effectiveness of lenient return policies in the presence of opportunistic consumers. We examine the impact of the proportion of opportunistic consumers, cross-network effects, gains from dishonest returns, and penalties on the scale of users and profits for both platforms. The findings indicate that: (1) As the proportion of opportunistic consumers increases, multi-homing merchants tend to be single-homing on a platform with a stringent return policy. This reduces the number of consumers on a platform with a lenient return policy and lowers the platform’s profit. Moreover, increased gains from dishonest returns worsen the situation. (2) Network effects on merchants from the consumer side significantly affect the effectiveness of lenient return policies. (3) Enforcement of penalties for dishonest returns could prevent an exodus of consumers and merchants from platforms that offer lenient return policies. However, it does not raise profits. In other words, its impact on the success of lenient return policies is limited.

Suggested Citation

  • Huixin Liu & Feng Du, 2023. "Research on E-Commerce Platforms’ Return Policies Considering Consumers Abusing Return Policies," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13938-:d:1243511
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    References listed on IDEAS

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    1. Xiaoyao Li & Bing Jiang & Xueying Meng & Yang Bai, 2025. "Refining waste and elevating customer service: assessing the efficacy of reverse logistics strategies for product returns management," Journal of Combinatorial Optimization, Springer, vol. 49(5), pages 1-31, July.

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