IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v308y2022i1d10.1007_s10479-020-03602-y.html
   My bibliography  Save this article

Impact of artificial intelligence adoption on online returns policies

Author

Listed:
  • Guangyong Yang

    (Xiamen University)

  • Guojun Ji

    (Xiamen University)

  • Kim Hua Tan

    (Nottingham University Business School)

Abstract

The shift to e-commerce has led to an astonishing increase in online sales for retailers. However, the number of returns made on online purchases is also increasing and have a profound impact on retailers’ operations and profit. Hence, retailers need to balance between minimizing and allowing product returns. This study examines an offline showroom versus an artificial intelligence (AI) online virtual-reality webroom and how the settings affect customers’ purchase and retailers’ return decisions. A case study is used to illustrate the AI application. Our results show that adopting artificial intelligence helps sellers to make better returns policies, maximize reselling returns, and reduce the risks of leftovers and shortages. Our findings unlock the potential of artificial intelligence applications in retail operations and should interest practitioners and researchers in online retailing, especially those concerned with online returns policies and the consumer personalized service experience.

Suggested Citation

  • Guangyong Yang & Guojun Ji & Kim Hua Tan, 2022. "Impact of artificial intelligence adoption on online returns policies," Annals of Operations Research, Springer, vol. 308(1), pages 703-726, January.
    • Handle: RePEc:spr:annopr:v:308:y:2022:i:1:d:10.1007_s10479-020-03602-y
    DOI: 10.1007/s10479-020-03602-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-020-03602-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-020-03602-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Elie Ofek & Zsolt Katona & Miklos Sarvary, 2011. ""Bricks and Clicks": The Impact of Product Returns on the Strategies of Multichannel Retailers," Marketing Science, INFORMS, vol. 30(1), pages 42-60, 01-02.
    2. Fei Gao & Xuanming Su, 2017. "Online and Offline Information for Omnichannel Retailing," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 84-98, February.
    3. Santiago Gallino & Antonio Moreno, 2018. "The Value of Fit Information in Online Retail: Evidence from a Randomized Field Experiment," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 767-787, October.
    4. Adrian Alexandrescu & Cristian Nicolae Butincu & Mitică Craus, 2017. "Recommending Products and Services Belonging to Online Businesses Using Intelligent Agents," Service Science, INFORMS, vol. 9(4), pages 338-348, December.
    5. Mabel C. Chou & Chee-Khian Sim & Xue-Ming Yuan, 2020. "Policies for inventory models with product returns forecast from past demands and past sales," Annals of Operations Research, Springer, vol. 288(1), pages 137-180, May.
    6. David R. Bell & Santiago Gallino & Antonio Moreno, 2018. "Offline Showrooms in Omnichannel Retail: Demand and Operational Benefits," Management Science, INFORMS, vol. 64(4), pages 1629-1651, April.
    7. Bing Jing, 2018. "Showrooming and Webrooming: Information Externalities Between Online and Offline Sellers," Marketing Science, INFORMS, vol. 37(3), pages 469-483, May.
    8. V. Kumar & Nita Umashankar & Kihyun Hannah Kim & Yashoda Bhagwat, 2014. "Assessing the Influence of Economic and Customer Experience Factors on Service Purchase Behaviors," Marketing Science, INFORMS, vol. 33(5), pages 673-692, September.
    9. Paolo Letizia & Morteza Pourakbar & Terry Harrison, 2018. "The Impact of Consumer Returns on the Multichannel Sales Strategies of Manufacturers," Production and Operations Management, Production and Operations Management Society, vol. 27(2), pages 323-349, February.
    10. Mehmet Sekip Altug & Tolga Aydinliyim, 2016. "Counteracting Strategic Purchase Deferrals: The Impact of Online Retailers’ Return Policy Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 18(3), pages 376-392, July.
    11. Michele Samorani & Aydın Alptekinoğlu & Paul R. Messinger, 2019. "Product Return Episodes in Retailing," Service Science, INFORMS, vol. 11(4), pages 263-278, December.
    12. Xuanming Su, 2009. "Consumer Returns Policies and Supply Chain Performance," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 595-612, March.
    13. Necati Ertekin, 2018. "Immediate and Long†Term Benefits of In†Store Return Experience," Production and Operations Management, Production and Operations Management Society, vol. 27(1), pages 121-142, January.
    14. Fei Gao & Xuanming Su, 2017. "Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 84-98, February.
    15. Lei Li & Ting Chi & Tongtong Hao & Tao Yu, 2018. "Customer demand analysis of the electronic commerce supply chain using Big Data," Annals of Operations Research, Springer, vol. 268(1), pages 113-128, September.
    16. Tiaojun Xiao & Jing Shi, 2016. "Consumer returns reduction and information revelation mechanism for a supply chain," Annals of Operations Research, Springer, vol. 240(2), pages 661-681, May.
    17. Kaiquan Xu & Jason Chan & Anindya Ghose & Sang Pil Han, 2017. "Battle of the Channels: The Impact of Tablets on Digital Commerce," Management Science, INFORMS, vol. 63(5), pages 1469-1492, May.
    18. Keith J. Crocker & Paolo Letizia, 2014. "Optimal Policies for Recovering the Value of Consumer Returns," Production and Operations Management, Production and Operations Management Society, vol. 23(10), pages 1667-1680, October.
    19. Jeffrey D. Shulman & Anne T. Coughlan & R. Canan Savaskan, 2009. "Optimal Restocking Fees and Information Provision in an Integrated Demand-Supply Model of Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 577-594, December.
    20. Thanh Tran & Haresh Gurnani & Ramarao Desiraju, 2018. "Optimal Design of Return Policies," Marketing Science, INFORMS, vol. 37(4), pages 649-667, August.
    21. Saraswathi Sivamani & Jongsun Choi & Yongyun Cho, 2018. "A service model for nutrition supplement prediction based on Fuzzy Bayes model using bigdata in livestock," Annals of Operations Research, Springer, vol. 265(2), pages 257-268, June.
    22. Pauwels, Koen & Neslin, Scott A., 2015. "Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment," Journal of Retailing, Elsevier, vol. 91(2), pages 182-197.
    23. Anthony Dukes & Yi Zhu, 2019. "Why Customer Service Frustrates Consumers: Using a Tiered Organizational Structure to Exploit Hassle Costs," Marketing Science, INFORMS, vol. 38(3), pages 500-515, May.
    24. Xing Hu & Zhixi Wan & Nagesh N. Murthy, 2019. "Dynamic Pricing of Limited Inventories with Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 501-518, July.
    25. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    26. Guangzhi Shang & Bikram P. Ghosh & Michael R. Galbreth, 2017. "Optimal Retail Return Policies with Wardrobing," Production and Operations Management, Production and Operations Management Society, vol. 26(7), pages 1315-1332, July.
    27. Anantaram Balakrishnan & Shankar Sundaresan & Bo Zhang, 2014. "Browse-and-Switch: Retail-Online Competition under Value Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 23(7), pages 1129-1145, July.
    28. Samuel Fosso Wamba & Andrew Edwards & Shahriar Akter, 2019. "Social media adoption and use for improved emergency services operations: the case of the NSW SES," Annals of Operations Research, Springer, vol. 283(1), pages 225-245, December.
    29. Ganesh Iyer & Dmitri Kuksov, 2012. "Competition in Consumer Shopping Experience," Marketing Science, INFORMS, vol. 31(6), pages 913-933, November.
    30. Youngsoo Kim & Ramayya Krishnan, 2015. "On Product-Level Uncertainty and Online Purchase Behavior: An Empirical Analysis," Management Science, INFORMS, vol. 61(10), pages 2449-2467, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Xiaoping & Wang, Yuting & Cheng, T.C.E. & Choi, Tsan-Ming, 2024. "Should live broadcasting platforms adopt artificial intelligence? A sales effort perspective," European Journal of Operational Research, Elsevier, vol. 318(3), pages 979-999.
    2. Wang, Qiang & Ji, Xiang & Zhao, Nenggui, 2024. "Embracing the power of AI in retail platform operations: Considering the showrooming effect and consumer returns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Guangyong & Ji, Guojun, 2022. "The impact of cross-selling on managing consumer returns in omnichannel operations," Omega, Elsevier, vol. 111(C).
    2. Lin, Jiaxin & Choi, Tsan-Ming & Kuo, Yong-Hong, 2023. "Will providing return-freight-insurances do more good than harm to dual-channel e-commerce retailers?," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1225-1239.
    3. Park, YoungSoo & Sim, Jeongeun & Kim, Bosung, 2022. "Online retail operations with “Try-Before-You-Buy”," European Journal of Operational Research, Elsevier, vol. 299(3), pages 987-1002.
    4. Jian Liu & Xinyue Sun & Yanyan Liu, 2022. "Products pricing and return strategies for the dual channel retailers," Operational Research, Springer, vol. 22(4), pages 3841-3867, September.
    5. Zhong, Yuyun & Shen, Wenjing & Ceryan, Oben, 2023. "Information provision under showrooming and webrooming," Omega, Elsevier, vol. 114(C).
    6. Sun, Yanhong & Wang, Zihan & Han, Xiaohua, 2020. "Supply chain channel strategies for online retailers: Whether to introduce web showrooms?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    7. Chen, Xiaohong & Tan, Lixia & Wang, Fuqiang, 2024. "Managing consumer bracketing purchases: Optimal return policy analysis," International Journal of Production Economics, Elsevier, vol. 275(C).
    8. Konur, Dinçer, 2021. "Keep your enemy close? Competitive online brands’ expansion with individual and shared showrooms," Omega, Elsevier, vol. 99(C).
    9. Mandal, Prasenjit & Basu, Preetam & Saha, Kushal, 2021. "Forays into omnichannel: An online retailer’s strategies for managing product returns," European Journal of Operational Research, Elsevier, vol. 292(2), pages 633-651.
    10. Li, Yanran & Li, Bo & Zheng, Wei & Chen, Xue, 2021. "Reveal or hide? Impact of demonstration on pricing decisions considering showrooming behavior," Omega, Elsevier, vol. 102(C).
    11. Buqing Ma & Chenchen Di & Lu Hsiao, 2020. "Return Window Decision in A Distribution Channel," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2121-2137, September.
    12. Kaiying Cao & Tsan‐Ming Choi, 2022. "Optimal Trade‐in Return Policies: Is it Wise to be Generous?," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1309-1331, March.
    13. Khouja, Moutaz & Hammami, Ramzi, 2023. "Optimizing price, order quantity, and return policy in the presence of consumer opportunistic behavior for online retailers," European Journal of Operational Research, Elsevier, vol. 309(2), pages 683-703.
    14. Yan Liu & Ningyuan Chen, 2022. "Dynamic Pricing with Money‐Back Guarantees," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 941-962, March.
    15. Ratchford, Brian & Soysal, Gonca & Zentner, Alejandro & Gauri, Dinesh K., 2022. "Online and offline retailing: What we know and directions for future research," Journal of Retailing, Elsevier, vol. 98(1), pages 152-177.
    16. Yang, Lu & Li, Xiangyong & Xia, Ye & Aneja, Y.P., 2023. "Returns operations in omnichannel retailing with buy-online-and-return-to-store," Omega, Elsevier, vol. 119(C).
    17. Jena, Sarat Kumar & Meena, Purushottam, 2022. "Shopping in the omnichannel supply chain under price competition and product return," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    18. Qian Tang & Mei Lin & Youngsoo Kim, 2021. "Inter‐Retailer Channel Competition: Empirical Analyses of Store Entry Effects on Online Purchases," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2547-2563, August.
    19. Jin, Delong & Caliskan-Demirag, Ozgun & Chen, Frank (Youhua) & Huang, Min, 2020. "Omnichannel retailers’ return policy strategies in the presence of competition," International Journal of Production Economics, Elsevier, vol. 225(C).
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:308:y:2022:i:1:d:10.1007_s10479-020-03602-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.