Examining the Signaling Effect of E-tailers’ Return Policies

Zhang, Jie; Han, Li; Yan, Ruiliang; Johnston, Chuck

doi:10.1080/08874417.2016.1183989

Cited by 30 publications

(29 citation statements)

References 48 publications

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“…The impact of monetary leniency on consumer behavior is tested in 10 studies, using both primary and secondary data methods. For the CR classifier, several studies lend support to signaling theory by finding empirical evidence that monetary leniency signals product and service quality resulting in higher perceived value (Wang, ; Wood, ; Zhang et al, ). Moreover, research shows that monetary leniency positively influences perceived cost fairness (Bower & Maxham III, ) and policy fairness (Pei et al, ).…”

Section: Empirical Researchmentioning

confidence: 99%

“…For the AR classifier, research suggests that monetary leniency can stimulate liking toward a retailer's return policy (Posselt et al, ) and decrease postreturn regret (Bower & Maxham III, ). In general, there is strong empirical evidence that higher monetary leniency results in favorable customer behavioral intentions and actions from a retailer's perspective (Gelbrich et al, ; Lantz & Hjort, ; Pei et al, ; Zhang et al, ).…”

Section: Empirical Researchmentioning

confidence: 99%

“…With respect to the CR classifier, a consistent finding is that higher time leniency is associated with a higher willingness‐to‐pay for product and return option; however, the relationship shows a diminishing return to scale (Heiman et al, ; Rao et al, ; Suwelack et al, ; Wang, ). Research on signaling quality suggests that time leniency can signal retailer service quality but may not signal product quality (d'Astous & Guèvremont, ; Zhang et al, ). In terms of the AR classifier, research shows that time leniency can stimulate liking toward a retailer and reduce anticipated regret (Posselt et al, ; Suwelack et al, ).…”

Section: Empirical Researchmentioning

confidence: 99%

“…Section 5.2 focuses on the literature that resides at the intersection of RP and CB domains, in which the vast majority of the literature is concentrated. Section 5.3 is dedicated to the research in the intersection of return policy with PE and RM (2008), Bonifield et al (2010), Pei, Paswan, and Yan (2014), Rao, Lee, Connelly, and Iyengar (2018), Zhang, Li, Yan, and Johnston (2017), and Oghazi, Karlsson, Hellström, and Hjort (2018) Prospect (including endowment effect) Kahneman and Tversky (1979) Wood (2001), Wang (2009), andHeiman, Just, McWilliams, andZilberman (2015) Distributive (equity) and procedural justice Adams and Freedman (1976), Lind and Tyler (1988) Suwelack, Hogreve, and Hoyer (2011), Bower and Maxham III (2012), and Pei et al (2014) Attribution Kelley (1967) Bower and Maxham III (2012) Construal level Liberman and Trope (1998) Janakiraman and Ordóñez (2012) Norm Kahneman and Miller (1986) Kim and Wansink (2012) Cognitive dissonance Festinger (1957) Powers andJack (2013) domains. The complete classification of the empirical literature appears in Table A3.…”

Section: Empirical Researchmentioning

confidence: 99%

See 3 more Smart Citations

Taking stock of consumer returns: A review and classification of the literature

Abdulla

Ketzenberg

Abbey

2019

J of Ops Management

111

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Coincident with the rapid growth of consumer returns and their corresponding importance in the retail marketplace, academic interest in the area of consumer return policy design has significantly increased. In fact, the growth in academic publications has been tremendous, with almost half of the published works appearing within the past 6 years. The influx of new and evolving research spans across multiple disciplines and various methodologies. To provide clarity for the continued evolution of the field, we provide a comprehensive review and classification of the literature predicated on a holistic conceptual framework. The scope of the review includes all peer reviewed journal articles published prior to the end of 2018, along with any working papers cited therefrom, that specifically address (a) managerial decision‐making related to return policies or (b) consumer behavior in response to such decision‐making. Examining the state of the literature and practice on return policy design through the lens of a unified conceptual framework—a framework that spans both analytical and empirical research—reveals numerous managerial and theoretical opportunities for future research.

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Section: Empirical Researchmentioning

confidence: 99%

Section: Empirical Researchmentioning

confidence: 99%

Section: Empirical Researchmentioning

confidence: 99%

Section: Empirical Researchmentioning

confidence: 99%

See 2 more Smart Citations

Taking stock of consumer returns: A review and classification of the literature

Abdulla

Ketzenberg

Abbey

2019

J of Ops Management

111

View full text Add to dashboard Cite

show abstract

“…Towards addressing these problems, much research has focused on: (1) easy and efficient product returns as part of company customer service policies [14,15]; (2) consumer recycling programs [16][17][18]; (3) product reuse, reconditioning, and remanufacturing [19,20]; and (4) design of closed loop supply chain model (CLSC) with third party enterprises to manage the reverse function [21][22][23]. Song et al, for instance, constructed a CLSC model with a third-party dominating and managing the recycling market [24].…”

Section: Introductionmentioning

confidence: 99%

Dual Chains Competition under Two Recycling Modes Based on System Dynamics Method

et al. 2018

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Abstract:The fast-growing accumulation of electronic waste (e-waste) around the world is resulting in environmental pollution and adverse human health and, thus, has become a global area of concern. As the world's second largest producer of e-waste, China suffers significant pollution from e-waste because of inefficient recycling and management. This paper is a comparative systems dynamics study of two big home appliance manufacturers in China: Haier (Haier Group of Qingdao, China) and Gree (Gree Electric Appliances Inc. of Zhuhai, China). We used systems dynamics modeling to examine and compare the impact of closed-loop supply chain recycling and remanufacturing strategies on the total revenue of the supply chain and market shares of both manufacturers. Results show that an increase in third party service coverage and increased environmental awareness enhanced the total revenue of supply chain. Retailers showed more enthusiasm for recycling through contract development with manufacturers, thus resulting in reduced time of payment in closed-loop supply chains. We also found that an improvement of the recycling mechanism of retailers results in an increase in the share of the supply chain market. Hence, we propose a better supply chain mode.

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The impact of free returns on online purchase behavior: Evidence from an intervention at an online retailer

Patel

Baldauf

Karlsson

et al. 2021

J of Ops Management

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Whether free returns create economic value for online retailers is a question of increasing importance. Using order‐level data from an online fashion retailer in Sweden, we investigate the introduction of free returns for customers in Denmark starting November 1, 2017, but not for customers in Sweden, Norway, Finland, France, Germany, and the rest of Europe (the control group). Using difference‐in‐differences, with and without sample matching, the introduction of free returns increased the order bill by 54.95 Swedish Krona (SEK) (9.15%), product variety per order by 0.057 (8.74%), gross margin per order by 29.90 SEK (9.71%), and returns by 0.195 items per order (7.86%). This likelihood of increased returns was generally similar across different product categories. The findings are robust to parallel trends, event studies, placebo effects, alternative control groups (with Scandinavian countries, Sweden and Norway), country‐time trends, and correlations between outcome variables. Based on back‐of‐the‐envelope calculations, the cost of offering free returns is greater than the increase in gross profit driven by free returns. Though our results show that free returns may not be of short‐term benefit, retailers must also consider the long‐term strategic implications of free returns.

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Examining the Signaling Effect of E-tailers’ Return Policies

Cited by 30 publications

References 48 publications

Taking stock of consumer returns: A review and classification of the literature

Taking stock of consumer returns: A review and classification of the literature

Dual Chains Competition under Two Recycling Modes Based on System Dynamics Method

The impact of free returns on online purchase behavior: Evidence from an intervention at an online retailer

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