On the introduction of return window to supply chains with online channel

doi:10.1016/j.cie.2022.108623

Computers & Industrial Engineering

Volume 172, Part A, October 2022, 108623

https://doi.org/10.1016/j.cie.2022.108623 Get rights and content

Highlights

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Return window is introduced to the supply chain with online channel.
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Pricing and channel strategies are derived in centralized and decentralized systems.
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The return window is longer in a centralized system than in a decentralized one.
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Introducing return window limits the supplier to choose a dual-channel strategy.

Abstract

In the E-commerce era, many firms offer return policy in the form of return window, allowing consumers to return for a full refund within a specific time, which has an important effect on supply chain operations. Motivated by practical observations, we explore a supplier’s distribution channel strategy when introducing return window in both centralized and decentralized supply chain systems. A game-analytical model is developed to study the interaction between channel strategy and return window. The equilibrium channel strategies, return windows, and prices in the two systems are derived. We find that a long return window always tends to be offered by the supplier when the direct channel is open (in a dual-channel or single direct-channel strategy) since it expands potential market demand. Also, the supplier provides a shorter return window in the decentralized than the centralized system as the existence of double marginalization, which enriches existing results. We prove that introducing return window always restricts the supplier to choose a dual-channel strategy, but it incentivizes (restricts) the supplier to choose a single retail-channel strategy in the decentralized (centralized) system in response to changing cost pressures. Our theoretical findings provide insights for managing supply chains when introducing return window as a market strategy.

Introduction

Consumer returns are becoming universal in business (Shulman et al., 2010). According to a report by the National Retail Federation and Appriss Retail, U.S. consumers returned products worth approximately $428 billion to retailers in 2020, accounting for about 10.6 % of total US retail sales.¹ This mainly results from firms’ various return policies (Nageswaran et al., 2020). While return policy has attracted much attention in business (Mukhopadhyay & Setoputro, 2005), since it highly affects consumer purchasing behavior (Letizia et al., 2018, Padmanabhan and Png, 1997, Seo et al., 2016, Wood, 2001), and determines the seller’s performance (Su, 2009), the impact of return window has been ignored. Return window, allowing consumers to obtain full refunds for returns within a specific time, is an essential part of return policies. Ma et al. (2020) suggest that return windows are more crucial than refund policies, as many firms increasingly use full-refund policies with different return windows.

Return windows are varying for firms with different product categories. For example, the return window is 30 days for Adidas,² but 14 days for Apple³ and 90 days for LEGO.⁴ It is noted that even for the same product, the return window may be diverse in different supply chain systems. In a centralized supply chain, Apple allows consumers to return Apple products in Apple stores within 14 days. In a decentralized supply chain, however, Suning (a retailer) only provides consumers with a 7-day return window for Apple products.⁵ More importantly, return windows also vary according to different selling channels of supply chains. In the garment industry, YISHION, selling products only through a traditional brick-and-mortar (retail) channel, provides a 7-day return window, while Uniqlo, Nike, and Adidas, selling products through a dual-channel strategy (including a retail channel and an online channel), offer a 30-day return window for their products sold in both channels. These practical examples motivate us to explore why firms set different return windows in different supply chain systems, that is, the centralized and decentralized systems, and how to decide the optimal return window when they sell products through different channel strategies?

With the rapid development of E-commerce, many firms, such as aforementioned Adidas, Suning, Apple, and LEGO, have adopted a dual-channel strategy in their supply chains. The dual-channel strategy is universal in supply chain operations, especially in the post-pandemic era, which induces many firms to shut down their retail channels as required by the epidemic prevention and control policies. Compared with retail channels, there may induce more prevalent returns in online channels, because consumers cannot experience and evaluate products personally before receiving them. It has been reported that approximately 5 % to 10 % of in-store purchases are returned, but that rate rises from 15 % to 40 % for online purchases.⁶ This practical difference in product return rates largely determines firms’ profitability of different types of channels, further impacting their channel strategies and associated operational strategies. Intuitively, offering a longer return window (an easy return policy) can directly reduce the shopping risk of consumers, thus improving their utility. Therefore, the return window policy plays an important role in consumers’ purchasing channel decision, which in turn affects the firm’s optimal channel and pricing strategies. A lot of academic studies have suggested that a firm’s dual-channel strategy is affected by return policies (Ertekin and Agrawal, 2021, Li and Jiang, 2019, Nageswaran et al., 2020). However, the return window decision and its effect on dual-channel strategies are ignored. To the best of our knowledge, there is no research focusing on how the return window decision affects the channel strategy in different supply chain systems and the corresponding price decisions. Therefore, we are inspired by the question that whether the optimal pricing and channel decisions of the supply chain in previous studies are still valid when return window is introduced.

To fill this research gap, we develop a game-analytical supply chain model consisting of one upstream supplier and one downstream retailer to study the interaction between the supplier’s return window decision and channel strategy. With the introduction of return window, the supplier provides a full-refund policy with a return window to consumers, within which consumers are allowed to return their products with a full refund. At the same time, the supplier decides its channel strategy, that is, selling products through a retail channel, a direct channel, or a dual channel. This study aims to provide theoretical and managerial implications for dual-channel supply chain operations when introducing return window by examining the following research questions:

How should the supplier and retailer determine their optimal channel strategies, return windows, and pricing decisions in the presence of return window? Should they use differentiated optimal strategies under centralized and decentralized supply chain systems?
How does the supplier’s channel strategy affect its optimal return window decision in centralized and decentralized systems? How does the introduction of return window impact the supplier’s channel strategy and the corresponding pricing strategies in both systems?
Are the existing results of optimal return window decision and pricing strategy still valid when considering the interaction of the firm’s channel strategies and return window decisions?

This study contributes to the literature from the following three aspects.

First, this study contributes to the literature by providing a novel perspective on explaining why many firms offer different return window policies in different supply chain structures and systems. We find that in both centralized and decentralized systems, compared with a single retail-channel strategy, the supplier tends to offer a longer return window if direct channel is introduced (whether in a dual-channel or single direct-channel strategy). This result implies that the firm’s channel strategy and return window actually interplay. Specifically, opening direct channel can significantly attract some consumers to purchase from the direct channel, who may exit the market in the absence of direct channel. Therefore, with the introduction of direct channel, the supplier is motivated to offer a longer return window to enjoy the benefits of direct channel in expanding potential market demand, thus further attracting more consumers. This is not only beneficial to the welfare of consumers, but also to the profit of the entire supply chain.

Second, we complement the current supply chain operations literature by focusing on how the introduction of return window affects the supplier’s channel strategy, thus providing a new method to examine the interaction between a supplier’s return window decision and channel strategy. While previous studies examine these two issues independently, this study, motivated by practical business cases, develops an analytical model to combine the two. Compared with previous studies without considering the return window decision, this study investigates the impact of introducing return window on optimal pricing decision and channel strategy. Interestingly, we find that although the introduction of return window always reduces the willingness of the supplier to choose a dual-channel strategy in both centralized and decentralized systems, it has an opposite effect on the adoption of a single retail-channel strategy in different systems. Specifically, introducing return window lowers the supplier’s willingness to choose the single retail-channel strategy in the centralized system. The introduction of return window usually increases the cost pressure of processing returned products. In a centralized system, the supplier can alleviate this cost pressure by seeking a more effective way to sell products, for example, by opening a direct channel (choosing a dual-channel or single direct-channel strategy). However, in a decentralized system, it is difficult for the supplier to do this due to double marginalization, so the supplier is more likely to choose a single retail-channel strategy.

Third, this study contributes to the literature by obtaining some novel results. Different from the result in Ma et al. (2020), who show that the firm will set a longer return window in the decentralized system than in the centralized system, we find that the supplier, bearing the cost of product returns, does not always set a longer return window in the decentralized supply chain. Our result is closer to reality and the reason behind is as follows. On the one hand, the supplier in a centralized system can enjoy all the benefits of improved demand resulting from offering a longer return window. While in a decentralized system, these benefits are partially captured by the retailer. On the other hand, compared with a centralized system, double marginalization in a decentralized system leads the return window to be less effective in improving product demand. Accordingly, the supplier is restrained to set a shorter return window in a decentralized system relative to a centralized system. In addition, the well-known result shows that in the centralized system (without introducing return window), the supplier charges the same sales price in the single retail-channel and dual-channel strategies (Chiang et al., 2003, Guo et al., 2020). However, we find that when introducing return window, adopting a dual-channel strategy induces the supplier to set higher retail prices, which implies that it is unwise for the supplier to keep retail price consistency and the supplier should strategically adjust sales price with the introduction of return window. Alternatively, when the supplier always chooses a dual-channel strategy in both systems, we reveal that with the improvement of direct channel efficiency, the prices in both channels increase in the centralized system, but decrease in the decentralized system.

In summary, to the best of our knowledge, this paper is the first study that explores the supplier’s channel strategy with return policy from the perspective of return window, which provides an analytical method to investigate the interaction between channel strategy and return window decision. Based on this study, some managerial implications of return window for channel operations management can be derived to guide supply chain participants and provide insights for decision-makers.

The remainder of this paper is as follows. Section 2 depicts the related literature. In Section 3, we present the model and relevant assumptions. The equilibrium results in the centralized and decentralized systems are characterized in 4 Centralized system, 5 Decentralized system, respectively. The comparative analysis and numerical experiments are presented in Section 6. 7 Managerial implications, 8 Conclusions present managerial implications and conclusions, respectively.

Section snippets

Literature review

This work complements studies that examine the effect of return policy on the channel strategy by considering return window (see Table 1). A growing body of literature has explored the return problem in the supply chain from traditional brick-and-mortar models and dual-channel strategy perspectives (Chen and Bell, 2013, Mukhopadhyay and Setoputro, 2005, Radhi and Zhang, 2018, Saha et al., 2016, Shulman et al., 2010, Su, 2009, Yang et al., 2022, Yue and Raghunathan, 2007). For instance, Yue and

Model description and assumptions

In this section, we develop a game-analytical supply chain model to examine the interaction between a supplier’s channel strategy and return window decision. The supply chain consists of one upstream supplier and one downstream retailer, in which the supplier sells products to consumers through the retailer. Additionally, the supplier can open an online direct channel to consumers by providing products directly. To lower the shopping risk of consumers obtaining mismatched products, consumers

Centralized system

In the centralized system, the supplier first decides the return window $T^{c}$ and then sets the retail price $p_{r}^{c}$ and direct price $p_{o}^{c}$ (if introducing direct channel), under which the supplier will account for all related costs, such as the unit cost of two channels and the cost of handling returned products. We can easily derive the profit of the supplier in the centralized dual-channel strategy as $π^{c} = \sum_{i = r, o} ((1 - \bar{α} T^{c}) (p_{i}^{c} - c_{i}) - \bar{α} T^{c} (c_{i} - s^{c})) d_{i}^{c} - \frac{\bar{α} {(T^{c})}^{2}}{2}$

In the above profit function, it is intuitive that in each

Decentralized system

In the decentralized system, the supplier and retailer make decisions independently by pursuing their respective profit maximizations in a Stackelberg game. Consequently, their profits are

$π_{r}^{d} = (1 - \bar{α} T^{d}) (p_{r}^{d} - w) d_{r}^{d}$ and $π_{s}^{d} = (w - c_{r} - \bar{α} T^{d} (w - s^{d})) d_{r}^{d} + (p_{o}^{d} - c_{o} - \bar{α} T^{d} (p_{o}^{d} - s^{d})) d_{o}^{d} - \frac{\bar{α} {(T^{d})}^{2}}{2}$

Backward induction is adopted to examine equilibrium decisions. We first explore the retailer’s optimal response and then derive the supplier’s optimal pricing, return window, and channel strategies.

Comparison and numerical analysis

We first explore how the introduction of return window affects the supplier’s channel strategy in both systems. It is easy to verify that when $α = 1$ , the results in Propositions 1 and 2 are the same as those of Chiang et al. (2003), under which return window is not considered. Therefore, recalling Corollaries 1 and 3, we can explore the impact of return window on the channel selection as follows.

Proposition 3

With the introduction of return window, the supplier’s willingness to choose a dual-channel strategy

Managerial implications

Based on the main results of this study, we can elaborate the following practical insights into supply chain and enterprise operations management.

First, we find two effective ways to motivate companies to provide a longer return window, which can be used by supply chains in practice, namely opening a direct channel to operate dual-channel supply chain, or implementing supply chain integration to avoid the negative effect of double marginalization. The analytical results show that in both

Conclusions

While various return policies have received wide attention in practice and academia, the issue of setting the return window, which is easy to encounter in practice, has been ignored. In the E-commerce era, many companies, operating in dual-channel supply chains, provide return policies in the form of return windows, which allow consumers to return goods for a full refund within a certain period of time. Therefore, it is important to explore the interaction between the return window decision and

CRediT authorship contribution statement

Zhenyang Pi: Conceptualization, Methodology, Software, Visualization, Writing - original draft, Writing - review & editing. Weiguo Fang: Supervision, Project administration, Writing - review & editing. Qiuhong Zhao: Supervision, Project administration, Writing - review & editing. Baofeng Zhang: Supervision, Methodology, Funding acquisition, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.