EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 58 / No 3 (May-June 2024) RAIRO-Oper. Res., 58 3 (2024) 2507-2524 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 58, Number 3, May-June 2024
Page(s) 2507 - 2524
DOI https://doi.org/10.1051/ro/2024059
Published online 25 June 2024
  • C. Bonifield, C. Cole and R.L. Schultz, Product returns on the internet: a case of mixed signals. J. Bus. Res. 63 (2010) 1058–1065. [CrossRef] [Google Scholar]
  • L. Cabral and A. Hortaçsu, The dynamics of seller reputation: evidence from eBay. J. Ind. Econ. 58 (2010) 54–78. [CrossRef] [Google Scholar]
  • X.Y. Cai, J.B. Li, B. Dai and T. Zhou, Pricing strategies in a supply chain with multi-manufacturer and a common retailer under online reviews. J. Syst. Sci. Syst. Eng. 27 (2018) 435–457. [CrossRef] [Google Scholar]
  • L.V. Casaló, C. Flavián, M. Guinalíu and Y. Ekinci, Avoiding the dark side of positive online consumer comments: enhancing comments’ usefulness for high risk-averse travelers. J. Bus. Res. 68 (2015) 1829–1835. [CrossRef] [Google Scholar]
  • Y.B. Chen and J.H. Xie, Online consumer review: word-of-mouth as a new element of marketing communication mix. Manage. Sci. 54 (2008) 477–491. [CrossRef] [Google Scholar]
  • W. Chen, B. Gu, Q. Ye and K.X. Zhu, Measuring and managing the externality of managerial responses to online customer reviews. Inf. Syst. Res. 30 (2019) 1–16. [Google Scholar]
  • W.Y.K. Chiang, D. Chhajed and J.D. Hess, Direct marketing, indirect profits: a strategic analysis of dual-channel supply-chain design. Manage. Sci. 49 (2003) 120. [Google Scholar]
  • China Internet Network Information Center, The 51th statistical report on China’s internet development. Accessed date March 2, 2019. https://www3.cnnic.cn/NMediaFile/2023/0322/MAIN16794576367190GBA2HA1KQ.pdf (2023). [Google Scholar]
  • S. Davis, E. Gerstner and M. Hagerty, Money back guarantees in retailing: matching products to consumer tastes. J. Retail. 71 (1995) 7–22. [CrossRef] [Google Scholar]
  • P. De, Y. Hu and M.S. Rahman, Product-oriented web technologies and product returns: an exploratory study. Inf. Syst. Res. 24 (2013) 998–1010. [CrossRef] [Google Scholar]
  • A. Dimoka, Y. Hong and P.A. Pavlou, On product uncertainty in online markets: theory and evidence. MIS Q. 36 (2012) 395–426. [CrossRef] [Google Scholar]
  • S. Dixit, A.J. Badgaiyan and A. Khare, An integrated model for predicting consumer’s intention to write online reviews. J. Retail. Consum. Serv. 46 (2019) 112–120. [CrossRef] [Google Scholar]
  • B. Gu, J. Park and P. Konana, Research note – the impact of external word-of-mouth sources on retailer sales of high-involvement products. Inf. Syst. Res. 23 (2012) 182–196. [CrossRef] [Google Scholar]
  • S. Han and K.A. Chris, Customer motivation and response bias in online reviews. Cornell Hospitality Q. 61 (2020) 142–153. [CrossRef] [Google Scholar]
  • B.V. Helversen, K. Abramczuk and W. Kopeć, Influence of consumer reviews on online purchasing decisions in older and younger adults. Decis. Support Syst. 113 (2018) 1–10. [CrossRef] [Google Scholar]
  • L. Hsiao and Y.J. Chen, Returns policy and quality risk in E-business. Prod. Oper. Manage. 21 (2012) 489–503. [Google Scholar]
  • J. Hu, Y.L. Liu, T.W.W. Yuen, M.K. Lim and J. Hu, Do green practices really attract customers? The sharing economy from the sustainable supply chain management perspective. Res. Conserv. Recycl. 149 (2019) 177–187. [CrossRef] [Google Scholar]
  • Y.H. Huang, C.X. Li, J. Wu and Z. Lin, Online customer reviews and consumer evaluation: the role of review font. Inf. Manage. 55 (2018) 430–440. [CrossRef] [Google Scholar]
  • N. Janakiraman, H.A. Syrdal and R. Freling, The effect of return policy leniency on consumer purchase and return decisions: a meta-analytic review. J. Retail. 92 (2016) 226–235. [CrossRef] [Google Scholar]
  • D.B. Kenneth and B. Eric, Information and its impact on consumers’ reactions to restrictive return policies. J. Retail. Consum. Serv. 21 (2014) 415–423. [CrossRef] [Google Scholar]
  • D.S. Kostyra, J. Reiner, M. Natter and D. Klapper, Decomposing the effects of online customer reviews on brand, price, and product attributes. Int. J. Res. Marketing 33 (2016) 11–26. [CrossRef] [Google Scholar]
  • Y. Kwark, J. Chen and S. Raghunathan, Online product reviews: implications for retailers and competing manufacturers. Inf. Syst. Res. 25 (2014) 93–110. [CrossRef] [Google Scholar]
  • M. Li and Y. Liu, Beneficial product returns in supply chains. Prod. Oper. Manage. 30 (2021) 3849–3855. [CrossRef] [Google Scholar]
  • M.X. Li, L.Q. Huang, C.H. Tan and K.K. Wei, Helpfulness of online product reviews as seen by consumers: source and content features. Int. J. Electron. Commerce 17 (2013) 101–136. [CrossRef] [Google Scholar]
  • X.L. Li, C.J. Wu and F. Mai, The effect of online reviews on product sales: a joint sentiment-topic analysis. Inf. Manage. 56 (2019) 172–184. [CrossRef] [Google Scholar]
  • Y.G. Liu and S.Z. Dong, Rebate strategy to stimulate online customer reviews. Int. J. Prod. Econ. 204 (2018) 99–107. [CrossRef] [Google Scholar]
  • P.D. Liu and F. Teng, Probabilistic linguistic TODIM method for selecting products through online product reviews. Inf. Sci. 485 (2019) 441–455. [CrossRef] [Google Scholar]
  • B. Lu and Z. Chen, Live streaming commerce and consumers’ purchase intention: an uncertainty reduction perspective. Inf. Manage. 58 (2021) 103509. [CrossRef] [Google Scholar]
  • F.J. Martínez-López, C. Feng, Y. Li and M.S. Mata, Restoring the buyer–seller relationship through online return shipping: the role of return shipping method and return shipping fee. Electron. Commerce Res. App. 54 (2022) 101170. [CrossRef] [Google Scholar]
  • A. Minnema, T.H.A. Bijmolt, S. Gensler and T. Wiesel, To keep or not to keep: effects of online customer reviews on product returns. J. Retail. 92 (2016) 253–267. [CrossRef] [Google Scholar]
  • S. Mohammad and J.K. Dan, Predicting the Performance of online consumer reviews: a sentiment mining approach to big data analytics. Decis. Support Syst. 81 (2016) 30–40. [CrossRef] [Google Scholar]
  • E. Moretti, Social learning and peer effects in consumption: evidence from movie sales. Rev. Econ. Stud. 78 (2011) 356–393. [CrossRef] [Google Scholar]
  • S.M. Mudambi and D. Schuff, What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Q. 34 (2010) 185–200. [CrossRef] [Google Scholar]
  • S.K. Mukhopadhyay and R. Setaputra, Reverse logistics in e-business: optimal price and return policy. Int. J. Phys. Distrib. Logistics Manage. 34 (2004) 70–89. [CrossRef] [Google Scholar]
  • J. Narayan, A.S. Holly and F. Ryan, The effect of return policy leniency on consumer purchase and return decisions: a meta-analytic review. J. Retail. 92 (2016) 226–235. [CrossRef] [Google Scholar]
  • E. Ofek, Z. Katona and M. Sarvary, “Bricks and clicks”: the impact of product returns on the strategies of multi-channel retailers. Marketing Sci. 30 (2011) 42–60. [CrossRef] [Google Scholar]
  • P. Oghazi, S. Karlsson, D. Hellström and K. Hjort, Online purchase return policy leniency and purchase decision: mediating role of consumer trust. J. Retail. Consum. Serv. 41 (2018) 190–200. [CrossRef] [Google Scholar]
  • X. Pan, L. Hou, K.C. Liu and H. Niu, Do reviews from friends and the crowd affect online consumer posting behaviour differently? Electron. Commerce Res. App. 29 (2018) 102–112. [CrossRef] [Google Scholar]
  • D. Proserpio and G. Zervas, Online reputation management: estimating the impact of management responses on consumer reviews. Marketing Sci. 36 (2017) 645–665. [CrossRef] [Google Scholar]
  • N. Sahoo, C. Dellarocas and S. Srinivasan, The impact of online product reviews on product returns. Inf. Syst. Res. 29 (2018) 723–738. [CrossRef] [Google Scholar]
  • H. Tang and X. Lin, Curbing shopping cart abandonment in C2C markets – an uncertainty reduction approach. Electron. Markets 29 (2019) 533–552. [CrossRef] [Google Scholar]
  • P. Vana and A. Lambrecht, The effect of individual online reviews on purchase likelihood. Marketing Sci. 40 (2021) 708–730. [CrossRef] [Google Scholar]
  • Z. Wang and Q. Chen, Monitoring online reviews for reputation fraud campaigns. Knowl.-Based Syst. 195 (2020) 105685. [CrossRef] [Google Scholar]
  • X.H. Wang, Q.L. Zhang and H. Du, The effect of online customer reviews on product sales: moderating effect of brand strength and category maturity. J. Ind. Eng. Eng. Manage. 32 (2018) 9–18. [Google Scholar]
  • W.C. Wang, F. Li and Z.L. Yi, Scores vs. stars: a regression discontinuity study of online consumer reviews. Inf. Manage. 56 (2019) 418–428. [CrossRef] [Google Scholar]
  • Y. Wang, V. Ramachandran and O.R. Liu Sheng, Do fit opinions matter? The impact of fit context on online product returns. Inf. Syst. Res. 32 (2021) 268–289. [CrossRef] [Google Scholar]
  • K. Warut, K. Karthik and G. Hossein, Extrinsic versus intrinsic rewards for contributing reviews in an online platform. Inf. Syst. Res. 29 (2019) 871–892. [Google Scholar]
  • K.L. Xie, Z.L. Zhang and Z.Q. Zhang, The business value of online consumer reviews and management response to hotel performance. Int. J. Hospitality Manage. 43 (2014) 1–12. [CrossRef] [Google Scholar]
  • L. Xu, Y. Li, K. Govindan and X. Xu, Consumer returns policies with endogenous deadline and supply chain coordination. Eur. J. Oper. Res. 242 (2015) 88–99. [CrossRef] [Google Scholar]
  • D. Yin, S. Mitra and H. Zhang, Research note – When do consumers value positive vs. negative reviews? An empirical investigation of confirmation bias in online word of mouth. Inf. Syst. Res. 27 (2016) 131–144. [CrossRef] [Google Scholar]
  • D. Yin, T. de Vreede, L.M. Steele and G.J. de Vreede, Decide now or later: making sense of incoherence across online reviews. Inf. Syst. Res. 34 (2023) 1211–12127 [CrossRef] [Google Scholar]
  • Y. Yu and H.S. Kim, Online retailers’ return policy and prefactual thinking: an exploratory study of USA and China e-commerce markets. J. Fashion Marketing Manage.: Int. J. 23 (2019) 504–518. [Google Scholar]
  • J. Zhang, H. Li, R. Yan and C. Johnston, Examining the signaling effect of e-tailers’ return policies. J. Comput. Inf. Syst. 57 (2017) 191–200. [Google Scholar]
  • X.M. Zhao and S.H. Hu, Online retailers return freight policy in the e-commerce context. Chin. J. Manage. Sci. 27 (2019) 53–62. [Google Scholar]
  • X. Zhao, S. Hu and X. Meng, Who should pay for return freight in the online retailing? Retailers or consumers. Electron. Commerce Res. 20 (2020) 427–452. [CrossRef] [Google Scholar]
  • P. Zhi, P. Audhesh and R.L. Yan, E-tailer’s return policy, consumer’s perception of return policy fairness and purchase intention. J. Retail. Consum. Serv. 21 (2014) 249–257. [CrossRef] [Google Scholar]
  • W. Zhou and O. Hinz, Determining profit-optimizing return policies – a two-step approach on data from taobao.com. Electron. Markets 26 (2016) 103–114. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.