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The impact of online reviews in the presence of customer returns

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  • Sun, Miao
  • Chen, Jing
  • Tian, Ye
  • Yan, Yufei

Abstract

We develop a duopoly model to examine how online reviews influence the decisions of two competing online sellers who sell products of differentiated quality under different returns policies. We derive the competing sellers' optimal decisions on price and returns policy with and without online reviews, and we find that online reviews have greater impact on the high-quality seller than on the low-quality seller. If the salvage value of the product is relatively low, the seller has less opportunity to benefit from online reviews when it offers an MBG, as compared to a no-refund policy. The impact of online reviews on the competition between the two sellers has a “symmetric effect area,” where reviews may either weaken or intensify the price competition between the two sellers when they both offer a no-refund policy, but always intensify the competition if they both offer an MBG. We have identified the conditions under which online reviews lead to a win-win, or benefit one seller, or present a prisoner's dilemma for the two online sellers. We also show that MBGs at both sellers help mitigate the prisoner's dilemma if the net salvage value at both sellers is sufficiently high.

Suggested Citation

  • Sun, Miao & Chen, Jing & Tian, Ye & Yan, Yufei, 2021. "The impact of online reviews in the presence of customer returns," International Journal of Production Economics, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:proeco:v:232:y:2021:i:c:s092552732030284x
    DOI: 10.1016/j.ijpe.2020.107929
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    6. Chen, Zhongwei & Fan, Zhi-Ping & Zhu, Stuart X., 2023. "Extracting values from consumer returns: The role of return-freight insurance for competing e-sellers," European Journal of Operational Research, Elsevier, vol. 306(1), pages 141-155.
    7. Fan, Huirong & Khouja, Moutaz & Gao, Jie & Zhou, Jing, 2023. "Incorporating social learning into the optimal return and pricing decisions of online retailers," Omega, Elsevier, vol. 118(C).
    8. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    9. Rezaei Kalantary, Mina & Hejazi, Seyed Reza & Khosroshahi, Hossein, 2023. "Pricing for different return policies in an online marketplace considering appeasement during a post-return out-of-stock," International Journal of Production Economics, Elsevier, vol. 266(C).
    10. Bingsheng Liu & Wenwen Zhu & Yinghua Shen & Yuan Chen & Tao Wang & Fengwen Chen & Maggie Wenjing Liu & Shi‐Hao Zhou, 2022. "A study about return policies in the presence of consumer social learning," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2571-2587, June.

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