IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v22y2022i3d10.1007_s10660-020-09406-3.html
   My bibliography  Save this article

Modelling and prioritizing the factors for online apparel return using BWM approach

Author

Listed:
  • Vineet Kaushik

    (Indian Institute of Management)

  • Ashwani Kumar

    (Jaipuria Institute of Management)

  • Himanshu Gupta

    (Indian institute of Technology-Indian School of Mines)

  • Gaurav Dixit

    (Indian Institute of Technology)

Abstract

Online apparel industry is suffering from a major issue of return, with a high rate of return for apparels that are sold online it becomes necessary to investigate the probable reasons of return in online apparel industry. The objective of the study is to develop a multi-criterion approach for evaluation of various factors that are responsible for the return of apparels purchased online in context of India. A total of 34 factors were identified through literature review and discussion with experienced experts from the fashion domain. In this study, best–worst method has been employed to prioritize and rank the factors for online return more effectively. Sensitivity analysis has been carried out to check the robustness of the proposed model of the study. The findings of the study show that fit and size variation, defects, found a better product (wisdom of purchase), wrong product delivery, lenient return policy and value for money were identified as crucial factors for online apparel return. The present study provides valuable research implications which can be used for retail policy improvements and also to online selling strategy.

Suggested Citation

  • Vineet Kaushik & Ashwani Kumar & Himanshu Gupta & Gaurav Dixit, 2022. "Modelling and prioritizing the factors for online apparel return using BWM approach," Electronic Commerce Research, Springer, vol. 22(3), pages 843-873, September.
  • Handle: RePEc:spr:elcore:v:22:y:2022:i:3:d:10.1007_s10660-020-09406-3
    DOI: 10.1007/s10660-020-09406-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-020-09406-3
    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/s10660-020-09406-3?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. Liu, Jian & Mantin, Benny & Wang, Haiyan, 2014. "Supply chain coordination with customer returns and refund-dependent demand," International Journal of Production Economics, Elsevier, vol. 148(C), pages 81-89.
    2. Gupta, Himanshu, 2018. "Evaluating service quality of airline industry using hybrid best worst method and VIKOR," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 35-47.
    3. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    4. 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.
    5. Janakiraman, Narayan & Syrdal, Holly A. & Freling, Ryan, 2016. "The Effect of Return Policy Leniency on Consumer Purchase and Return Decisions: A Meta-analytic Review," Journal of Retailing, Elsevier, vol. 92(2), pages 226-235.
    6. Greatorex, M. & Mitchell, V. W., 1994. "Modelling consumer risk reduction preferences from perceived loss data," Journal of Economic Psychology, Elsevier, vol. 15(4), pages 669-685, December.
    7. 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.
    8. Xuanming Su, 2009. "Consumer Returns Policies and Supply Chain Performance," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 595-612, March.
    9. Li, Yongjian & Xu, Lei & Li, Dahui, 2013. "Examining relationships between the return policy, product quality, and pricing strategy in online direct selling," International Journal of Production Economics, Elsevier, vol. 144(2), pages 451-460.
    10. Shaina Singh & Rajesh Kumar Singh & Nitin Seth, 2017. "Ranking of critical success factors for online retailing by TOPSIS approach," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 21(3), pages 359-374.
    11. Jyrki Wallenius & James S. Dyer & Peter C. Fishburn & Ralph E. Steuer & Stanley Zionts & Kalyanmoy Deb, 2008. "Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead," Management Science, INFORMS, vol. 54(7), pages 1336-1349, July.
    12. Oghazi, Pejvak & Karlsson, Stefan & Hellström, Daniel & Hjort, Klas, 2018. "Online purchase return policy leniency and purchase decision: Mediating role of consumer trust," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 190-200.
    13. Govindan, Kannan & Kaliyan, Mathiyazhagan & Kannan, Devika & Haq, A.N., 2014. "Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 555-568.
    14. Mukhopadhyay, Samar K. & Setaputra, Robert, 2007. "A dynamic model for optimal design quality and return policies," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1144-1154, August.
    15. Dailey, Lynn C. & Ülkü, M. Ali, 2018. "Retailers beware: On denied product returns and consumer behavior," Journal of Business Research, Elsevier, vol. 86(C), pages 202-209.
    16. Hong, Ilyoo B. & Cha, Hoon S., 2013. "The mediating role of consumer trust in an online merchant in predicting purchase intention," International Journal of Information Management, Elsevier, vol. 33(6), pages 927-939.
    17. Davis, Scott & Hagerty, Michael & Gerstner, Eitan, 1998. "Return policies and the optimal level of "hassle"," Journal of Economics and Business, Elsevier, vol. 50(5), pages 445-460, September.
    18. Anil Kumar & Manoj Kumar Dash, 2016. "Using DEMATEL to construct influential network relation map of consumer decision-making in e-marketplace," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 21(1), pages 48-72.
    19. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    20. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    21. Jeffrey D. Shulman & Anne T. Coughlan & R. Canan Savaskan, 2011. "Managing Consumer Returns in a Competitive Environment," Management Science, INFORMS, vol. 57(2), pages 347-362, February.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Hao-Wei, 2023. "Improving supply quality through the store-initiated returns in wholesale supply chains," International Journal of Production Economics, Elsevier, vol. 261(C).
    2. 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).
    3. Xu, Lei & Li, Yongjian & Govindan, Kannan & Xu, Xiaolin, 2015. "Consumer returns policies with endogenous deadline and supply chain coordination," European Journal of Operational Research, Elsevier, vol. 242(1), pages 88-99.
    4. Urvashi Tandon & Amit Mittal & Sridhar Manohar, 2021. "Examining the impact of intangible product features and e-commerce institutional mechanics on consumer trust and repurchase intention," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 945-964, December.
    5. Zhang, Juzhi & Xu, Qingyun & He, Yi, 2018. "Omnichannel retail operations with consumer returns and order cancellation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 308-324.
    6. Ülkü, M. Ali & Gürler, Ülkü, 2018. "The impact of abusing return policies: A newsvendor model with opportunistic consumers," International Journal of Production Economics, Elsevier, vol. 203(C), pages 124-133.
    7. 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).
    8. Lin, Jiaxin & Zhang, Juliang & Cheng, T.C.E., 2020. "Optimal pricing and return policy and the value of freight insurance for a retailer facing heterogeneous consumers with uncertain product values," International Journal of Production Economics, Elsevier, vol. 229(C).
    9. Necati Ertekin & Jeffrey D. Shulman & Haipeng (Allan) Chen, 2019. "On the Profitability of Stacked Discounts: Identifying Revenue and Cost Effects of Discount Framing," Marketing Science, INFORMS, vol. 38(2), pages 317-342, March.
    10. Huseyn Abdulla & James D. Abbey & Michael Ketzenberg, 2022. "How consumers value retailer's return policy leniency levers: An empirical investigation," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1719-1733, April.
    11. Leela Nageswaran & Soo-Haeng Cho & Alan Scheller-Wolf, 2020. "Consumer Return Policies in Omnichannel Operations," Management Science, INFORMS, vol. 66(12), pages 5558-5575, December.
    12. Necati Ertekin & Anupam Agrawal, 2021. "How Does a Return Period Policy Change Affect Multichannel Retailer Profitability?," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 210-229, 1-2.
    13. 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.
    14. Wang, Chong & Chen, Jing & Chen, Xu, 2019. "The impact of customer returns and bidirectional option contract on refund price and order decisions," European Journal of Operational Research, Elsevier, vol. 274(1), pages 267-279.
    15. Khouja, Moutaz & Ajjan, Haya & Liu, Xin, 2019. "The effect of return and price adjustment policies on a retailer’s performance," European Journal of Operational Research, Elsevier, vol. 276(2), pages 466-482.
    16. 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.
    17. 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.
    18. Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.
    19. Shujun Yang & Ivan Kai Wai Lai & Huajun Tang, 2022. "Pricing and Contract Coordination of BOPS Supply Chain Considering Product Return Risk," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
    20. Rokonuzzaman, Md & Iyer, Pramod & Harun, Ahasan, 2021. "Return policy, No joke: An investigation into the impact of a retailer's return policy on consumers' decision making," Journal of Retailing and Consumer Services, Elsevier, vol. 59(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:elcore:v:22:y:2022:i:3:d:10.1007_s10660-020-09406-3. 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.