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Investigating the influential factors of return channel loyalty in omni-channel retailing

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  • Xu, Xun
  • Jackson, Jonathan E.

Abstract

The ever-evolving omni-channel retail environment provides customers with a variety of channels to select from when making purchases and returns. Despite the growing number of product returns, there is limited research that focuses on customers' perception of the return process in an omni-channel retail environment. To fill this gap, via an empirical analysis, this paper examines the influential factors on customers' return channel loyalty. Our structural equation modeling results found that perceived risk, purchase-return channel consistency, monetary cost, and hassle cost influence customers' return channel loyalty. Comparatively, perceived risk has the highest impact on customers' return channel loyalty. Additionally, hassle cost has more influence than monetary cost on customers' return channel loyalty. We also found that both internal (ambiguity tolerance, patience, and familiarity) and external (return policy flexibility) factors influence customers' perceived risk. Comparatively, channel familiarity has a higher influence on reducing customers' perceived risk compared with patience and the channel's return policy flexibility. Understanding customers' perceptions of a return channel is the first step in the implementation of an effective return management strategy in an omni-channel retail environment. This first step will provide retailers with opportunities to better understand the needs of targeted customers, offer improved post-sales services, and optimize their handling of product returns.

Suggested Citation

  • Xu, Xun & Jackson, Jonathan E., 2019. "Investigating the influential factors of return channel loyalty in omni-channel retailing," International Journal of Production Economics, Elsevier, vol. 216(C), pages 118-132.
  • Handle: RePEc:eee:proeco:v:216:y:2019:i:c:p:118-132
    DOI: 10.1016/j.ijpe.2019.03.011
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    5. Amir Heiman & Bruce P. McWilliams & David Zilberman, 2022. "Adoption of Innovations: Comparing the Imitation and the Threshold Models," Foundations and Trends(R) in Marketing, now publishers, vol. 17(1), pages 1-57, June.
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    7. Anthony Boyd Stevenson & Julia Rieck, 2024. "Investigating Returns Management across E-Commerce Sectors and Countries: Trends, Perspectives, and Future Research," Logistics, MDPI, vol. 8(3), pages 1-37, August.
    8. Xu, Xun & Zeng, Shuo & He, Yuanjie, 2021. "The impact of information disclosure on consumer purchase behavior on sharing economy platform Airbnb," International Journal of Production Economics, Elsevier, vol. 231(C).
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    10. Sonia Bendimerad & Oussama El Khalil & Asma Khelifi, 2023. "E-commerce and returns management: the other side of the show [E-commerce et gestion des retours : l'envers du décor]," Post-Print hal-04413401, HAL.
    11. Kong, Ruixiao & Luo, Li & Chen, Liuxin & Keblis, Matthew F., 2020. "The effects of BOPS implementation under different pricing strategies in omnichannel retailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
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    13. Ahmed Dabees & Mahmoud Barakat & Sahar Sobhy Elbarky & Andrej Lisec, 2023. "A Framework for Adopting a Sustainable Reverse Logistics Service Quality for Reverse Logistics Service Providers: A Systematic Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    14. 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.
    15. Kamarin Merritt & Shichao Zhao, 2020. "An Investigation of What Factors Determine the Way in Which Customer Satisfaction Is Increased through Omni-Channel Marketing in Retail," Administrative Sciences, MDPI, vol. 10(4), pages 1-24, October.
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