Partial Refund Research Articles

Price markdowns to induce customers to opt out of free returns

With consumers increasingly relying on online shopping, returns have become a considerable issue in the retail e-commerce industry. Major e-retailers typically impose either “free returns” or a “partial refund” policy. This article studies a flexible return policy in which customers get to self-select return options. We consider a setting where, alongside the conventional free return (FR) option, consumers are offered an additional return alternative called opt-out of free return (FO). Choosing FR allows consumers to return items within a grace period for a full refund. Alternatively, selecting FO gives them a price markdown, but involves paying a fixed and variable penalty if they choose to return the product. We aim to derive managerial insights on when offering FO would be beneficial to firms and, if so, how to set the optimal markdown level. We find that the uncertainty level in the consumers’ valuation distribution has a subtle impact on the profitability of providing the FO option alongside the FR. While conventional wisdom suggests that offering the FO option is more likely to be beneficial as customers’ uncertainty about the product’s valuation pre-purchase increases, we show that the opposite could be true. Specifically, we show that if the product’s expected valuation is high (low), higher (lower) uncertainty in the valuation distribution makes it more likely that offering FO alongside FR is advantageous to the firm.

Intraconsumer Price Discrimination with Credit Refund Policies

Consumers often receive a full or partial refund for product returns or service cancellations. Much of the existing literature studies cash refunds, where consumers get the money back minus a fee upon a product return or service cancellation. However, not all refunds are issued in cash. Sometimes consumers receive credit that can be used for future purchases, oftentimes with an expiration term after which the credit is forfeited. We study the optimal design of credit refund policies. Different from models that consider cash refunds, we explicitly model repeated interactions between the seller and consumers over time. We assume that consumers’ valuation for the product/service varies over time and that there is an exogenous probability for product returns. Several interesting results emerge. First, a credit refund policy facilitates intraconsumer price discrimination for a single type of consumers with stochastic valuation. Second, an optimal policy often involves an intermediate credit expiration term, under which a consumer with a high product valuation always makes a purchase, whereas a consumer with a low product valuation may be induced to make a purchase as the credit approaches expiration, leading to a demand induction effect. Finally, a credit refund policy can be more profitable than a cash refund policy and can lead to a win-win outcome for both the firm and consumers under certain conditions. We also consider several extensions to check the robustness of our findings. This paper was accepted by Jeannette Song, operations management. Funding: Y. Liu was substantially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU15502420). Y. Liu was also supported by a grant from NSFC [72293564/72293560]. Supplemental Material: The data and online appendices are available at https://doi.org/10.1287/mnsc.2020.03042 .

Behavior-based optimal refund policy under advance selling: an analysis of the impact of loss fairness concerns

Buying and returning products can result in losses for both transaction parties, and a partial refund policy affects the loss difference. If consumers feel the policy is unfair, they can easily trigger their inequity aversion to loss. This study analyzes the effects of consumers’ loss fairness concerns on a two-period partial refund policy in advance selling. We develop a mathematical framework in which a firm sells products to consumers in advance, and consumers decide when to buy. The firm allows pre-purchased consumers to return the products in the spot period, resulting in potential losses for both parties. Considering fair-minded consumers, we first show how the firm responds to loss fairness concerns to make an optimal partial refund policy. We then discuss whether the firm is affected by loss fairness concerns. We find that when the degree of fairness concern exceeds a certain threshold, consumers’ loss fairness concerns negatively affect the firm. Besides, we propose a fairness-mitigating mechanism to relieve the negative effect on the firm, which might benefit both parties. Our analysis and results first provide management insights into the importance of incorporating loss fairness concerns in advance selling and the influence on partial refund policy.

Who should pay for the return freight in e-commerce? Platforms, retailers or consumers

In the realm of e-commerce, various return freight modes are available, such as platform-bearing return freight (PP strategy), retailer-bearing return freight (RP strategy), and consumer-bearing return freight (CP strategy). The return freight strategy adopted by platforms plays a crucial role in responding to consumer behaviors. To analyze how platforms determine the optimal return freight strategies, we examine a supply chain comprising a platform, a retailer, and heterogeneous consumers, employing a Stackelberg game model to capture their decision dynamics. Our findings suggest that the platform should opt for the PP strategy only when the product profit margin is relatively low. If the platform refuses to adopt the PP strategy, then the RP strategy is preferable when consumers face extremely high consumer return freight costs; otherwise, the CP strategy is the equilibrium result. We also prove that the selection of the return freight strategies leads to changes in the property of the equilibrium. Under the CP strategy, how the product fit probability affects the optimal price depends on the procurement cost; while under the RP and PP strategies, the optimal price decreases with the fit probability. Moreover, under the PP strategy, an increase in the product fit probability does not always benefit the platform. Further, our analysis reveals that, while the PP strategy can reduce the retailer’s risk, it might negatively impact supply chain performance, which implies that cost sharing in the supply chain does not necessarily lead to a higher channel profit. We also investigate how the platform’s return freight strategies affect consumer surplus and identify regions for Pareto improvement where all parties benefit from the PP strategy. Finally, by exploring extensions like positive salvage values, partial refunds, platform competition, and differentiated return freight costs, we confirm the robustness of our findings and unveil new insights.

Evaluation of the Generic Drug User Fee Act (GDUFA) Program for Fiscal Years 2013-2022.

The effectiveness of the regulatory initiatives, strategies, and incentives put forth in the first two authorizations of the Generic Drug User Fees Act (GDUFA) were evaluated using factors including the number of Abbreviated New Drug Application (ANDA) withdrawals and first-cycle approvals. GDUFA was originally authorized in 2012 for FY 2013-2017 (GDUFA I) and reauthorized for FY 2018-2022 (GDUFA II). ANDA approvals were analyzed from the Drugs @ FDA database covering 2013-2022. From the applications, the approval time, dosage form and route of administration (ROA), product indication, market status of the product, first generic status, company and company size filing the ANDA were noted. Despite the COVID pandemic, there was more than a 40% increase in ANDA approvals during GDUFA II relative to GDUFA I. Oral and parenteral drugs were the two leading categories of approved generics during both iterations of GDUFA. There was more than a 120% increase in withdrawn applications during GDUFA II, which reflects the partial refund that is now offered to incentivize companies to withdraw inadequate applications prior to review. This also appears to have contributed to an increase in the number of first-cycle approvals, which increased by 100% between GDUFA I and II. Due to the COVID-19 public health emergency, there was a decrease in activity within the generic drug program and market. Therefore, it is important to consider this impact when observing actual trends from this study.

Managing consumer bracketing purchases: Optimal return policy analysis

This paper investigates the optimal pricing and return policies of an online retailer selling a product with multiple versions to consumers facing valuation uncertainty. Consumers resolve their uncertainty through bracketing, a practice wherein they purchase multiple versions with the intention of keeping the best fit and returning the rest. By establishing a Stackelberg game between the retailer and consumers, we investigate two return policies: one offering full refunds with purchase limits, and the other offering partial refunds (Q or R) under exogenous and endogenous pricing (N or P), yielding four scenarios: NQ, PQ, NR, PR. Our study provides key insights into optimal return policies for retailers, demonstrating that stringent return policies may not necessarily be more profitable compared to lenient ones when dealing with consumer bracketing. In the case of exogenous pricing, retailers providing convenient returns are better off charging return fees, while those facing cumbersome returns should offer full refunds under certain conditions. When jointly leveraging pricing, retailers have the flexibility to choose between the full-refund and partial-refund policies. We obtain several interesting findings. First, as the mismatch probability increases, retailers tend to charge higher return fees in Scenario PR, while adjusting optimal decisions (i.e., refund under the partial-refund policy and purchase limit under the full-refund policy) non-monotonically in other scenarios. Second, consumers receive nonnegative expected utility in the exogenous pricing scenario, whereas zero in the endogenous pricing scenario. Third, when returns become sufficiently convenient, retailers adopting the partial-refund policy under endogenous pricing shift toward offering full refunds. In addition, when considering heterogeneous consumers, we discover that in some cases, retailers can benefit from consumer bracketing.

Risk sharing rule and safety loading in a peer to peer cooperative insurance model

AbstractThe evolution of digital technologies is reshaping consumer habits and needs, driving process automation, and giving rise to innovative business models like Insurtech. Peer-to-peer (P2P) insurance is emerging as part of this trend. P2P involves purchasing an insurance policy by sharing the risk with a group of peers. This group transparently monitors real-time savings and tracks claims filed by its members. At the policy’s expiration, if the actual risk is lower than anticipated, the peers receive a partial refund of their premium. This paper introduces a model to determine the entry price in a broker-based P2P scheme using a cooperative game approach. We employ the Shapley Value method to distribute the risk among participants. Numerical examples are included for illustration and discussion.

Impact of consumer foresight on efficient overselling

AbstractOverselling is commonly adopted in the travel and hospitality sectors where a good or service is sold in excess of actual supply. We examine the impact of consumer foresight on efficient overselling when there are two dimensions of uncertainty, namely, early consumers are uncertain about their service valuations and the seller is uncertain about late demand arrival. We show that when consumers are naïve and have no foresight to anticipate future events, the seller resorts to the use of partial refunds and involuntary cancellation when the mandatory compensation for seller‐initiated cancellation is low, resulting in efficiency loss. When consumers are sophisticated and have perfect foresight on future events, efficiency is achieved when the seller sells the entire capacity in advance and relies solely on voluntary cancellation to re‐sell units when late demand warrants it. Refund complements overselling both by improving allocation efficiency in involuntary cancellation and by mitigating the cost of overselling when consumers have limited foresight. Unlike the social planner, the seller may suffer from consumer foresight. Our findings pinpoint the mandatory compensation in involuntary cancellation as a strategic tool for the social planner to tilt the seller's preference in the seller‐initiated cancellation policy to achieve efficient overselling.

Pricing decisions through O2O commerce in a closed-loop green supply network and logistics under return and cooperative advertising policies

Our current societal practices of excessive consumption and disposal pose a significant threat to the environment, necessitating the implementation of appropriate policies and strategies to mitigate these destructive factors. Recycling used products can play a crucial role in preserving the environment. In this study, we propose a closed-loop green supply network (CLGSN) that consists of a manufacturer and a retailer who produce and sell green products through both offline and online channels. The Stackelberg approach is employed, with the manufacturer serving as the leader and the retailer as the follower. A revenue sharing policy is established between these members. To encourage customers to return their used products, we introduce four return policies under four scenarios for both offline and online channels. These policies are designed to drive customer engagement with sustainable practices while also promoting revenue growth for all network members. The present study investigates various return policies through dual channels, with the aim of identifying the most effective approach. The first scenario considers a Return & Loyalty Refund policy for offline channels, while a Return & Discount approach is evaluated for online channels. The second policy defines the Return & Loyalty Refund and Return & Loyalty Discount policies for offline and online channels, respectively. In the third scenario, a Return & Partial Refund policy is examined for offline channels, while a Return & Discount policy is studied for online channels. Finally, the fourth scenario explores a Return & Partial Refund policy in an offline channel and a Return & Loyalty Discount policy in an online channel. By comparing these different policies, this research aims to identify the optimal approach for managing returns across multiple channels. Overall, this research aims to provide insights into the effectiveness of different return policies in both offline and online channels, while also considering environmental sustainability. Ultimately, this research will help us improve customer satisfaction, increase profitability, and reduce waste. In fact, in this study we find that: (1) under the fourth scenario, the total profit chain has the highest value; (2) due to the practical return policies, more customers are convinced to return their used products and hence, more used products will be recycled and then remanufactured. So, as the results show, it improves the total profit chain; (3) the proposed return policies can both conserve the environment and coordinate the total profit chain. a numerical analysis is implemented to represent the relations clearly. We also evaluate how different parameters affect decision variables and profit chains by providing an analytical sensitivity.

Time-sensitive cancellation refund in advance booking: Effect of online-to-offline marketing policy

Due to heightened competition, current selling approaches are rapidly advancing as firms aim to enhance customer satisfaction to increase their market share and extend their customers’ zone. As an efficient advertising method, the online-to-offline (O2O) marketing strategy is extensively used by most of the competing vendors who tend to sell their commodities via advertisement in both virtual and traditional stores. By doing it this way, they can reach both online and offline-oriented customers, who prefer to buy the required commodities from online stores and real shopping centres respectively. In this research, we study the behaviour of two complementary firms in the airline and hotel industry using an advance booking policy. Here, it is supposed that cancellation is allowed and customers can enjoy a partial refund paid by the firms selling their products via both online and offline stores. The principal goal of this study is to investigate the behaviour of the partners of firms with/without an O2O strategy where the firms use partial refund for cancelled orders under time-sensitive cancellation rates. The optimal selling prices of commodities in advance and in a spot selling period are the decision variables, whose values are examined by numerical examples and are assessed using sensitivity analyses.

Improving supply chain transparency with blockchain technology when considering product returns

AbstractBlockchain technology is commonly used in many industries. One current application is that providing supply chain transparency, sellers can disclose product information to consumers for authentication and certification. To examine the supply chain blockchain based transparency‐level strategy and its interact with different refund policies, in a two‐echelon supply chain, we consider a supplier decides on the transparency level and wholesale price, and a retailer decides on retail price and provides full refund (policy F), or partial refund (policy P), or no refund (policy N) policy to consumers. We find the refund policy choice and the transparency‐level strategy have a mutual influence. A lenient refund policy (a higher refund) can generate more demand, which makes the supplier to provide a high transparency level, whereas a high consumer's transparency awareness also promotes the retailer to choose a more lenient refund policy. We find Pareto improvement exists under a cost‐sharing strategy, and the retailer is willing to share part of the adoption cost only when the efficiency of improving the transparency level is moderate. Otherwise, the retailer adopts blockchain technology only when there is no cost sharing. Further, different shipping cost bearers can change the sensitivity of refund policy choice, and the supplier prefers to provide a high transparency level when the retailer covers the shipping cost. When the retailer becomes more socially responsible, the supplier is more willing to provide a higher transparency level, and the retailer is more willing to provide a partial refund policy.

Information disclosure, consumer returns, and operational costs in omnichannel retailing

AbstractIn the online retailing, consumers are commonly uncertain about the product's quality and fitness. To resolve these uncertainties, many pure e‐tailers adopt various omnichannel strategies to provide tactile product information for consumers. We build a model to investigate a pure e‐tailer's decision on whether to adopt an omnichannel strategy. Our result indicates that when the cost for each physical store is sufficiently low, the e‐tailer always adopts the omnichannel strategy regardless of the product quality. Moreover, the low‐quality e‐tailer's willingness to adopt the omnichannel strategy is nonmonotonic with the fitness probability when the travel cost factor is high. In contrast, if the cost for each physical store is moderate, the e‐tailer adopts the omnichannel strategy if and only if the product quality is above a threshold. The quality threshold may increase with the fitness probability. Higher fitness probability means a lower return rate and fewer benefits brought by the omnichannel strategy. Thus, the threshold of the quality is increased to guarantee a sufficiently large price increase when choosing the omnichannel strategy. Furthermore, when the cost for each physical store is high, the e‐tailer with a high‐quality product would abandon the omnichannel strategy if the fitness probability is moderate. Finally, we consider the scenarios in which the e‐tailer can endogenously determine the number of physical stores or provide a partial refund policy.

The over-ordering problem in trade credit: Role of return policies

This paper explores the role of return policies on trade credit offered by suppliers to retailers. Traditional trade credit agreements, wherein a supplier extends a short-term loan to a retailer, can lead to over-ordering by the retailer even though she is financially constrained (FC), and this can affect supply chain efficiency. With ever-increasing product-handling costs, such over-ordering can have a severe impact on the supply chain profit. Motivated by our work with an industry partner, we design a game-theoretic model to evaluate optimal stocking decisions and wholesale prices in an FC supply chain, analyze the traditional trade credit model, and establish the reasons for over-ordering by the retailer when trade credit is deployed. We then examine how product returns, prevalent in the industry, can be used to control over-ordering. We design three different mechanisms incorporating returns in a trade credit model: quantity-limit-based returns, partial refund based returns, and marginal refund based returns. We find that returns-based policies improve profits for all members of the supply chain by driving inventory reduction and reducing over-ordering when trade credit is used. We also perform numerical analysis to quantify the impact of key parameters on the optimal decision variables. Our paper contributes by suggesting easy-to-implement mechanisms for improving trade credit deployment in supply chains and provides useful insights to decision makers to incorporate returns in trade credit policies.

Optimization of two‐dimensional warranty policy for repairable products based on age and usage, applicable to lemon law conditions

AbstractThis paper proposes a new two‐dimensional warranty policy based on two factors—age and usage—that simultaneously incorporates both the warranty period and the refund period for a repairable product with an increasing failure rate. In this policy, the product is warranted by taking into account both its age and usage, and the warranty expires when the product reaches a specified age or a specified usage, whichever comes first. One unique framework of the policy presented in this work is that, under a specific type of lemon law, it defines a refund period during which the manufacturer must either replace the purchased product or offer a full or partial refund to the buyer if the product fails in such a way that meets certain conditions involving either the number of failures or the length of each repair time. The refund period is generally assumed to be shorter than the warranty period, and each failure that occurs after the refund period is only minimally repaired until the termination of the warranty. In this article, we consider both age and usage in warranting a product and we define an age‐based univariate warranty period based on the usage rate. Under a specified cost structure, we evaluate the expected total warranty cost during the age‐based warranty period and determine an optimal age‐based warranty period from the manufacturer's perspective. We also suggest a heuristic method that can be used to obtain an optimal warranty premium for the two‐dimensional warranty policy considered in this study. Finally, relevant numerical examples are provided to analyze the proposed warranty policy.

Reducing the regressivity of indirect taxation in Brazil through a personalized value-added tax

ICMS is a value-added tax and the most important tax in Brazil in terms of revenue. This paper investigates the technical feasibility and impact of a reform to ICMS. The aim of the reform is twofold, on the one hand, to modernize the tax and redress some current flaws in terms of neutrality, simplicity and transparency and, on the other, to reduce its regressivity, increase redistribution, reduce poverty and impact positively on social welfare (without a loss in the tax revenue). A static behavioral microsimulation model was purpose-constructed to study the proposed reform. The new tax simplifies the current system by introducing a single general tax rate and an increased rate for alcoholic beverages and tobacco, without exemptions, combining this with a total or partial refund for the poorest families. The empirical results show that the new tax is superior to the current one, both in terms of efficiency and equity.

Whether to adopt “buy online and return to store” strategy in a competitive market?

This study attempts to examine whether it is beneficial to introduce the “buy online and return to store” (BORS) strategy in a competitive market. We consider two competing dual-channel retailers, and investigate conditions under which it is optimal for one or both of the retailers to offer the BORS strategy. We first assume that a partial refund is offered for online returns and then consider the important case of a full refund. We show that whether both retailers adopt this strategy significantly depends on the return rate and cross-selling profit. Specifically, if the return rate is sufficiently low (high), at least one retailer (both retailers) will adopt this strategy when the unit cross-selling profit is relatively high. Nonetheless, both retailers will fall into the prisoner's dilemma under certain conditions. Interestingly, the return rate and proportion of consumers with a high hassle cost associated with BORS returns significantly influence the equilibrium channel strategy and the existence of the prisoner's dilemma. We further find that, when both retailers implement the BORS strategy, they both benefit from offering a full refund return policy when the number of online-type consumers is large enough and the unit cross-selling profit is relatively small, but should provide a partial refund otherwise. When only one retailer adopts the BORS strategy, a partial refund return policy is preferable.

Optimal warranty policy design for deteriorating products with random failure threshold

With the rapid development of technologies and increasing availability of degradation data, the design of appropriate warranty policy for products subject to performance deterioration has hitherto received more attention in boosting profits and improving the competition of enterprises. In most existing works, a product is considered to have failed and trigger a warranty service when the degradation level exceeds the constant failure threshold. However, the stochastic nature of failure threshold exists in many applications. In this study, firstly, two truncated distributions are employed to model the random failure threshold. Then we propose three types of warranty policies-free replacement, full refund and partial refund, that take into account the random failure threshold based on the degradation model. Under the first policy, the manufacturer’s total expected profit is maximized to determine the optimal price and warranty period, besides these, the prescribed maintenance times can also be obtained under the other two policies. We further compare these warranty policies under random failure threshold characterized by different distributions. Finally, a numerical example is presented along with sensitivity analysis to illustrate and compare the proposed warranty policies, showing that the parameters of degradation model and random failure threshold can lead to different expected profits.

The Impact of Employee Empathy on Brand Trust in Organizational Complaint Response Emails: A Closer Look at Linguistic Realization

This study investigates the effect of linguistic realizations of employee empathy (LREE) on brand trust in email responses to customer complaints. We explore possible mediating effects of perceived empathy and perceived complaint handling quality and we look into moderation effects of compensation (Study 1) or customer’s acceptance of blame (Study 2). Our aim is to find out if LREE have a negative or positive impact on the customer in cases of partial refunds, either because LREE are being perceived as insincere or as genuine expressions of concern. The results of two experiments show that LREE positively influence brand trust through higher perceived empathy and perceived complaint handling quality. However, the expected negative effect is not found, as LREE are more effective in a low versus high compensation condition. The effectiveness itself is not influenced by the acceptance of blame when a partial refund is offered.

Pricing and Return Policies in a Competitive Market: A Consumer-Valuation Based Analysis with Valuation Uncertainties

In this study, we develop a series of consumer-valuation-based models to investigate the pricing and return policies of the sellers in a competitive e-commerce market. Differing from the competition models in literature, a novel two-dimensional valuation structure is built, which considers the valuations of a consumer on two products and the valuation differentiation of all consumers on each product. We consider both monopoly and duopoly (competitive) markets. In each market, two models are respectively developed, one with and one without the return policies. We derive the solutions for the four models, and conduct some analytical and numerical investigations. The results show that return policy with a partial refund is always chosen by the sellers in both monopoly and duopoly markets. Return policy benefits the seller in a monopoly market, but may not benefit the sellers in a duopoly market. In the duopoly models, one seller can be considered as a monopoly seller who meets a new competitor. Our results show that the monopoly seller will reduce its price by no more than 20% when there comes a competitor, and, counter-intuitively, it will meanwhile adopt a severer return policy to the consumers.

Partial refunds as a strategic price commitment device in advance selling in a service industry

Over the past decade, consumers’ strategic waiting behavior in anticipation of a price markdown has become increasingly common when advance selling is used. Recently, studies in the durable goods industry show that a partial refund strategy can activate the price-commitment mechanism to counter consumers’ strategic waiting, which is primarily driven by both consumers’ and retailers’ behaviors that discount the future. In this research, we investigate the possibility of using this partial refund strategy in a service industry context in which demand uncertainty and consumption state uncertainty act as major influential factors.We study analytical models that consider the demand uncertainty of later arrivals and the consumption state uncertainty of early arrivals over two selling periods (advance and spot selling). Our results show a consistent pattern reflecting that a partial refund strategy in which the cancellation fee acts as a price-commitment mechanism is capable of emerging as the optimal strategy. Other than the strategic commitment mechanism, the cancellation fee paid by the advance buyers who choose to cancel their advance purchase also plays a profit-enhancer role. Combining these two mechanisms, a partial refund strategy dominates both a price-matching strategy and a dynamic pricing strategy, and they are only special cases of that type of strategy. Finally, comparative statistical analyses are conducted and reveal the impacts of demand-related parameters on the optimality of the partial refund strategy. These results provide instructive guidance for sellers when utilizing the partial refund strategy in their marketing practices.