Effectiveness of product return-prevention instruments: Empirical evidence
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RESEARCH PAPER
Effectiveness of product return-prevention instruments: Empirical evidence Gianfranco Walsh 1 & Michael Möhring 1,2
Received: 31 July 2016 / Accepted: 8 May 2017 # Institute of Applied Informatics at University of Leipzig 2017
Abstract The convenience and ease of online shopping reduce consumers’ risk perceptions, which encourages the continued growth of online retailing but also may force online retailers to deal with expensive and excessively high product return rates. Despite efforts by e-commerce management practitioners and scholars to identify determinants of customer product return behavior, scarce research investigates the effectiveness of instruments designed explicitly to reduce customers’ actual return rates. Drawing on risk theory, this article tests the influence of three important instruments on product return prevention. Three separate field experiments among customers of a well-known European online retailer reveal, unexpectedly, that the use of a money-back guarantee increases product returns, whereas product reviews decrease the product return rate. The provision of free return labels has no influence on customer product return behavior. This article concludes with some managerial and theoretical implications of these results. Keywords E-commerce . Money-back guarantee . Online shopping . Prevention instruments . Product returns . Product reviews Responsible Editor: Hans-Dieter Zimmermann * Michael Möhring [email protected] Gianfranco Walsh [email protected] 1
Wirtschaftswissenschaftliche Fakultät, Lehrstuhl für Allgemeine Betriebswirtschaftslehre / Marketing, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, 07743 Jena, Germany
2
Munich University of Applied Sciences, Faculty of Computer Science and Mathematics, Lothstr. 64, DE-80335 Munich, Germany
JEL classification L81 . M31
Introduction Electronic retailing continues to grow at a faster rate than conventional retailing (MacKenzie et al. 2013; RetailMeNot 2015), especially in apparel product categories (Ben-Shabat et al. 2016). For the U.S. apparel sector, online business captured $60 billion in 2015 (eMarketer 2015), and the growth trends are upward. Yet online retailers of apparel and other popular online products (e.g., consumer electronics) face a major concern: product returns (Rao et al. 2014; Walsh et al. 2016; Zhou and Hinz 2016). In the U.S., the average return rate is 30% for clothing online (Shah 2014). Moreover, it was estimated that in the U.S. in the pre-Christmas months of November and December of 2015, $20 billion worth of products bought online were returned (Maple 2015). Consumers may return non-defective products that do not fit their preferences (Shulman et al. 2010), especially those they order online. In contrast with offline shopping, online customers cannot evaluate the product before purchase by touching, smelling, or trying it on (Ofek et al. 2011; Shulman et al. 2010). For an online retailer, returns lead to costs and perhaps unsatisfied customers, even though most returned pr
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