Striking the right balance: Customising return policy leniency for managing customer online return proclivity and satisfaction

E-commerce retailers (e-tailers) commonly adopt generous return policies which not only act as a guarantee to protect the customer's purchase but also help in maintaining their satisfaction. However, this strategy can backfire by encouraging impulsive purchasing behaviour and resulting in a surge of product returns. This creates what is termed the product return policy leniency dilemma. To address that, this paper aims to empirically discover the relationships between product return policy leniency dimensions (time, monetary, effort, scope, and exchange) and two output variables – customer return proclivity and satisfaction. We develop a hybrid method combining machine learning-based data extraction and logistic regression, using a large empirical dataset comprising return policies and reviews from Walmart. The results show that three leniency dimensions – monetary, effort and scope drive customer return proclivity and satisfaction. Time only drives the satisfaction but not proclivity while exchange is in reverse. Our findings imply that customers are amenable to reasonable restrictions in return policies regarding time, effort, and exchange. However, overly lenient return policy terms may fail to adequately address the return policy dilemma. Additionally, partial refund/restocking fees are acceptable for customers with return proclivity if they perceive the initial purchasing cost heavily. Allowing some hazardous/bulky products to be returned under condition may also be seen as a generous term from prospective returners. Overall, e-tailers should display flexibility by incorporating different levels of leniency across five dimensions to balance return satisfaction and intention. This study provides e-retailers a guidance to design an appropriate bespoke return policy. • Return policy signals affect customers' return proclivity and satisfaction. • Monetary, effort, and scope dimensions impact returns at varying leniency levels. • Customers accept certain restrictions on time, effort, and exchange conditions. • Medium leniency levels can balance return proclivity and customer satisfaction. • Retailers can use these findings to design bespoke return policy strategies.

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Publication Details

Journal
Journal of Retailing and Consumer Services
Published
2025-05-09
DOI
https://doi.org/10.1016/j.jretconser.2025.104315
Citations
5
Primary Topic
Consumer Retail Behavior Studies
Type
article
Field-Weighted Citation Impact
10.36
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article

Striking the right balance: Customising return policy leniency for managing customer online return proclivity and satisfaction

Li Zhou, Quang Huy Duong, Tiep Duy Nguyen, Meng Meng et al.
5 citations
Journal of Retailing and Consumer Services
Consumer Retail Behavior Studies
10.36
article

Striking the right balance: Customising return policy leniency for managing customer online return proclivity and satisfaction

Li Zhou, Quang Huy Duong, Tiep Duy Nguyen, Meng Meng, Le Thuy An Dang
article en
5 citations

Abstract

E-commerce retailers (e-tailers) commonly adopt generous return policies which not only act as a guarantee to protect the customer's purchase but also help in maintaining their satisfaction. However, this strategy can backfire by encouraging impulsive purchasing behaviour and resulting in a surge of product returns. This creates what is termed the product return policy leniency dilemma. To address that, this paper aims to empirically discover the relationships between product return policy leniency dimensions (time, monetary, effort, scope, and exchange) and two output variables – customer return proclivity and satisfaction. We develop a hybrid method combining machine learning-based data extraction and logistic regression, using a large empirical dataset comprising return policies and reviews from Walmart. The results show that three leniency dimensions – monetary, effort and scope drive customer return proclivity and satisfaction. Time only drives the satisfaction but not proclivity while exchange is in reverse. Our findings imply that customers are amenable to reasonable restrictions in return policies regarding time, effort, and exchange. However, overly lenient return policy terms may fail to adequately address the return policy dilemma. Additionally, partial refund/restocking fees are acceptable for customers with return proclivity if they perceive the initial purchasing cost heavily. Allowing some hazardous/bulky products to be returned under condition may also be seen as a generous term from prospective returners. Overall, e-tailers should display flexibility by incorporating different levels of leniency across five dimensions to balance return satisfaction and intention. This study provides e-retailers a guidance to design an appropriate bespoke return policy. • Return policy signals affect customers' return proclivity and satisfaction. • Monetary, effort, and scope dimensions impact returns at varying leniency levels. • Customers accept certain restrictions on time, effort, and exchange conditions. • Medium leniency levels can balance return proclivity and customer satisfaction. • Retailers can use these findings to design bespoke return policy strategies.

Journal of Retailing and Consumer ServicesVol. 85
University of Bath (GB), University of Greenwich (GB)
Openalex Percentile: Top 2%
Consumer Retail Behavior Studies
10.36
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