Refund Amount Research Articles

Reduce, reuse, redeem: Deposit-refund recycling programs in the presence of alternatives

Understanding how consumers make recycling decisions is crucial in crafting sustainable recycling policies. We estimate consumer preferences and willingness to pay for current beverage container recycling methods, including curbside pick-up services, drop-off at government-subsidized recycling centers, and drop-off at non-subsidized centers. Using a representative online and telephone survey of California households, we estimate a revealed preference discrete choice model that identifies the key attributes explaining consumers’ beverage container disposal decisions, including the ability to receive a deposit refund (paid to consumers only if they recycle at drop-off centers) and the effort associated with bringing recyclable materials to recycling centers. Additionally, we use counterfactual policy analysis to show that increasing the refund amount increases overall household recycling rates. Infra–marginal households who are on the boundary between taking containers to recycling centers and recycling using curbside pick-up, namely white households and households with higher educational attainment, see the largest changes in consumer surplus generated by increasing refund payments. Conversely, we show that eliminating government-subsidized drop-off centers does not significantly alter consumer surplus for any major demographic group, and has little impact on whether a household chooses to recycle.

Behavioral multi‐lever decision‐making: A study of consumer return policy, price, and inventory decisions

AbstractConsumer return policies have been long recognized and studied by operations management scholars as an important managerial lever in a retail environment. Yet, the behavioral aspects of return policy decision‐making and interaction of return policy decisions with other common operational decisions have not been investigated to date. We present a behavioral analysis of return policy decision‐making in a retail environment with aggregate demand and individual product valuation uncertainties. Leveraging a generalized newsvendor context, we conduct a randomized behavioral experiment to understand how individuals make each of the three key retail decisions—refund amount, price, and order quantity—and the causal effect of salvage value on these decisions. We find that decision‐makers exhibit behavioral regularities in making decisions across the three levers and they react to changes in the operating conditions in a boundedly rational manner, suggesting the use of heuristics. Based on behavioral regularities that we observe in our data—that is, responses, time‐dependent effects, and decision dependencies—we develop a process theory based on behavioral decision‐making tenets that offers a new direction with testable hypotheses for future research. The process theory describes a conditional decision‐making heuristic that leads to a propagation of decision errors across different levers as well as lever‐specific decision biases.

Nonlinear Regression Model Based on Fractional Bee Colony Algorithm for Loan Time Series

High levels of nonperforming loans provide negative impacts on the growth rate of gross domestic product. Therefore, predicting the occurrence of nonperforming loans is a vital issue for the financial sector and governments. In this paper, an intelligent nonlinear model is proposed for describing the behavior of nonperforming loans. In order to find the optimal parameters of the model, a new fractional bee colony algorithm (BCA) based on fractional calculus techniques is proposed. The inputs of the nonlinear model are the loan type, approved amount, refund amount, and economic realm. The output of the regression model is that whether the current information is for a nonperforming loan or not. Consequently, the model is modified to detect the status of a loan. So, the modified model predicts the occurrence of a nonperforming loan and determines the loan status, i.e., current, overdue, and nonperforming. The proposed procedure is applied to data gathered from an economic institution in Iran. The findings of this study are helpful for the managers of banks, and financial sectors to forecast the future of the loans and, therefore, manage the budget for the upcoming loan requests.

Pricing of Complementary Products in Online Purchasing under Return Policy

In online purchasing, customers may return products due to dissatisfaction with the quality of the product, and receive a refund based on the return policy, which is determined by online distributors. Online distributors can offer generous policies to attract more customers, but at the cost of reducing total profits. In this paper, the effect of the pricing and quality of complementary products (products sold together with other items) in online selling under the return policy is investigated. For this purpose, a mathematical model is developed to obtain optimal values for selling price, refund amount, and quality of products. Based on analytical results, a solution algorithm is proposed to solve the numerical examples and perform sensitivity analysis. Findings reveal that, while increasing the sensitivity of demand with respect to the refund amount, the price, quality, and refund on returned products should be increased. In addition, the online distributor should increase the quality of products when customers are more sensitive to the quality of products. Among other results, the selling price is shown to be negatively affected by demand elasticity with respect to price. In this situation, the online distributor should reduce the quality level and the refund amount for returned products to avoid a sharp decline in profit. In addition, when the quality cost is high, the price and quality should be decreased and the refund amount unchanged.

Return shipping insurance: Free versus for-a-fee?

Return shipping insurance (RSI) has been widely adopted by retailers on major online platforms such as Taobao.com and JD.com to compensate online consumers for their return shipping fee. There are two types of RSI, namely free RSI (f-RSI), under which the retailer covers the RSI premium, and for-a-fee RSI (faf-RSI), under which consumers pay the premium. We study the optimal f-RSI and faf-RSI strategies for a monopolistic online retailer as well as the impact RSI on the retailer's returns policy. First, we find that RSI is complementary to the partial-refund returns policy as it further increases the retailer's profit. Specifically, the retailer adopts the RSI strategy if and only if the RSI premium is relatively small; in addition, the RSI strategy is more appealing with a higher RSI compensation and product salvage value, and a smaller return shipping cost. Second, we find that under the f-RSI strategy, the retailer does not change its refund price, i.e., the refund amount equals the product salvage value; while, under the faf-RSI strategy, the retailer changes its refund price strategically according to the RSI premium, compensation, and number of RSI-sensitive consumers. Third, we find that the f-RSI strategy dominates the faf-RSI strategy from the profit and social welfare perspectives; whereas, the faf-RSI may lead to a “win-win” situation for the retailer and consumers.

Differential Game Model of a Fresh Dual-Channel Supply Chain Under Different Return Modes

The freshness of fresh products will directly affect consumers’ purchase behavior, and returns of fresh products will cause considerable waste. This paper investigates the differential game between a fresh e-tailer and a supplier with chain supermarkets in a dual-channel supply chain. We compare and analyze optimal equilibrium strategies under different return modes (refund mode and exchange purchase mode) of the fresh e-tailer. We also discuss the impact of fresh e-tailers (the advantage of fresh-keeping technology) sharing fresh-keeping technology with suppliers in the dual-channel fresh supply chain. Our results show the following: (1) The high sensitivity of consumers to freshness can improve the fresh-keeping efforts of the supply chain to a certain degree, thereby reducing product loss. (2) The refund amount and exchange purchase cost have a significant impact on the optimal equilibrium strategies under the two return modes. For suppliers, the exchange purchase model is the most advantageous. For fresh e-tailers, the choice is affected by the exchange cost and the relationship between the wholesale price and refund amount. (3) Under certain conditions, fresh e-tailers sharing fresh-keeping technology can improve the fresh-keeping efforts and profits of the supply chain.

Managing consumer returns with technology-enabled countermeasures

This paper examines retail return abuse with respect to both opportunistic and fraudulent consumer behavior. The decisions of interest are the retailer’s price for purchases and refund amount for returns. Our analysis provides managerial insight into how a retailer makes these decisions to mitigate return abuse. Including both forms of return abuse in a base model, we find that there is an interaction effect that meaningfully changes a retailer’s optimal decisions and profit, from what would be observed if only opportunism was present. We also evaluate two innovative technology-enabled countermeasures designed to mitigate return abuse: customer profiling and product tracking. A customer profiling system identifies opportunistic customers by using their personal identification and transaction history. In contrast, a product tracking system identifies fraudulent returns by recording each transaction of a product through the use of unique identifiers. We develop prescriptive models for these technologies and investigate the value of making such investments. Our analyses demonstrate the conditions in which it is advantageous to adopt these technologies and when such investments should be avoided. We find that when a retailer is able to charge restocking fees, it is well equipped to mitigate opportunism and fraud with only its price and refund decisions. Hence, the value of consumer profiling and product tracking technologies is limited. However, when a retailer is constrained to offer a full refund due to market dynamics, employing these technologies may hold significant value. Our analysis details the determinants of value, model sensitivity, and comparisons between models. We also address how these countermeasures impact a retailer’s profitability, demand structure, and decisions with respect to price and refund amount.

Quality disclosure strategy in a decentralized supply chain with consumer returns

AbstractWe study the quality disclosure strategy of a manufacturer/retailer in a supply chain with consumer returns for new products. In particular, we explicitly model the effect of quality disclosure on the reduction of the returns rate. We identify the condition in which the manufacturer/retailer should reveal product quality in the presence of consumer returns. We find that (1) the manufacturer/retailer has an incentive to choose quality disclosure strategy when the disclosure quality is above a lower bound; (2) if the returns rate of new products is low, the retailer‐disclosure scenario leads to reveal more quality information than that of the manufacturer‐disclosure scenario; otherwise, the manufacturer‐disclosure scenario leads to reveal more quality information; and (3) the manufacturer prefers to reveal a higher level of product quality in the supply chain with a higher refund amount or a lower salvage value per unit of returned product.

An applicability test of the use of deposit-refund system for managing water-sachet litter in Ilorin, Nigeria

This study used both quasi-experiment and contingent valuation survey to explore the applicability of deposit-refund system (DRS) to water-sachet litter management in Nigeria. In the experiment, a DRS was established to incentivize the participants to return emptied sachets of water. A contingent valuation survey of 454 sachet-water consumers selected using quasi-systematic sampling technique was conducted. Experimental results showed that the number of sachets returned by the experimental group – those subjected to DRS – was significantly greater than that of the comparison group – those not subjected to DRS. Logit regression results showed that refund size increased the odds of returning sachets by 42.0%. Increasing the redemption time decreased the odds of turning in sachets by about 16.0%. A one-minute increase in the time spent on redemption would result in about 2.4% decrease in the probability that participants would comply. Income decreased the odds of compliance by about 31.0%, while age reduced the odds of compliance by about 2.2%. These results imply that the DRS reduced water-sachet littering in the study area, and that income, refund amount, redemption time, age and perceived effectiveness of DRS influenced consumers’ compliance with DRS. Hence, an appropriate motivating DRS would reduce litter and its attendant problems, such as hygiene, plastic pollution, flooding, aesthetic loss, non-naturally degradable toxic compounds, degradation of natural habitat ant its endangered species. The government should, therefore, implement a DRS and set up recycling plants, or encourage private recycling firms, in order to accommodate used sachets that would end up piling up.

The Impact of Consumer Loss Aversion on Returns Policies and Supply Chain Coordination

Product return is a common after-sale service. Existing literature has assumed loss neutral consumers, while in practice consumers are often more sensitive to utility losses than gains, i.e., customers are often loss averse. In this paper, we study the impact of such loss aversion on the retailer's optimal pricing and returns policies. We analyze three scenarios where the seller offers no refund, full refund and partial refund for the returned products. Under each scenario, the seller determines the optimal price, quantity, and refund amount (under partial refund case) in order to maximize the expected profit. Our results demonstrate that consumer loss aversion leads a no-refund retailer to charge lower price and order smaller quantity, has no impact on a full-refund retailer, and results in a more lenient returns policy for a partial-refund retailer. We also find contracts that coordinate supply chains selling to loss averse consumers. Therefore, this article sheds some lights on how the management of returns policies should be adapted when consumers are loss averse.

Buyback contract in a risk-averse supply chain with a return policy and price dependent demand

This paper examines a two-stage supply chain where a retailer offers a return policy with partial refund to end customers, and a manufacturer offers a buyback contract for all unsold and returned items to the retailer to share the risk. Customer demand is stochastic and price dependent. Key performance measure is the utility of profit, a function of the mean and variance of profit. Supply chain members are risk averse. Optimal buyback price, wholesale price, and retailer's order quantity are determined for the supply chain under coordination. A computational study is conducted to investigate the impacts of the members' risk attitudes, refund amount, and retail price on the optimal decisions. Further analysis shows break-even points among utility values at different retail prices as the risk attitude parameters and refund amount change. These break-even points provide a guideline for the retailers to adjust the price to maximise the utility of profit.

Price Adjustment Policy with Partial Refunds

Have you ever purchased an item only to notice a short while later that its price was reduced? Many retailers offer to refund customers the full price difference as long as the discount occurred within a short period of time after the original purchase. Such policy looks attractive to consumers as it shields them from future price fluctuations. But can this policy be advantageous for the retailer?In this paper we investigate the price difference refund policy (commonly referred to as price adjustment) and demonstrate how it can result in a higher profit even if all consumers request and receive a price adjustment.Further, the existing literature and practice both assume that if a price adjustment policy is employed, the consumers should get the full price difference refunded. In this paper we endogenize the refund amount, allowing the retailer to determine the optimal percentage of the price difference to be returned to consumers. We fully characterize the conditions under which it is optimal to offer a partial or greater than full price adjustment to customers as well as the optimal refund percentage. Additionally, we demonstrate that the practice of limiting the price adjustment option to a short period after the purchase incident is not necessarily in the best interest of retailers.

Pricing, refund, and coordination optimization in a two stages supply chain of green and non-green products under hybrid production mode

In this research, a joint pricing and refund optimization problem under cooperative and non-cooperative strategies in a two-stage supply chain consists of a supplier and a manufacturer who produces two types of product; green and non-green is developed. The features of both products in usage and functional are same but in price and environmentally aspect are different. Moreover refund policy is considered for both products that can affect on customers’ decision. We explore and analyze the system performance under both non-cooperative and cooperative strategies. The Stackelberg game in cooperative and Rubinstein bargaining in non-cooperative environments are applied respectively. Results show the cooperation of members increase their profits and products demand for both types of products. By increasing the value of potential demand, refund amount of green product and profits in cooperative and non-cooperative cases are increased and refund amount of non-green product is decreased. Changes of utility level sensitivity to the refund amount of green and non-green products have direct relations with refund amount and system profits, unless the utility level sensitivity to the refund amount of non-green product has contrariwise relationship with the refund amount of non-green products.

P.3.b.035 - Risk of psychiatric disorders in siblings of patients diagnosed with schizophrenia or affective disorders

Return shipping insurance (RSI) has been widely adopted by retailers on major online platforms such as Taobao.com and JD.com to compensate online consumers for their return shipping fee. There are two types of RSI, namely free RSI (f-RSI), under which the retailer covers the RSI premium, and for-a-fee RSI (faf-RSI), under which consumers pay the premium. We study the optimal f-RSI and faf-RSI strategies for a monopolistic online retailer as well as the impact RSI on the retailer's returns policy. First, we find that RSI is complementary to the partial-refund returns policy as it further increases the retailer's profit. Specifically, the retailer adopts the RSI strategy if and only if the RSI premium is relatively small; in addition, the RSI strategy is more appealing with a higher RSI compensation and product salvage value, and a smaller return shipping cost. Second, we find that under the f-RSI strategy, the retailer does not change its refund price, i.e., the refund amount equals the product salvage value; while, under the faf-RSI strategy, the retailer changes its refund price strategically according to the RSI premium, compensation, and number of RSI-sensitive consumers. Third, we find that the f-RSI strategy dominates the faf-RSI strategy from the profit and social welfare perspectives; whereas, the faf-RSI may lead to a “win-win” situation for the retailer and consumers.

The Role of Refund Expectations in Savings: Evidence from Volunteer Income Tax Preparation Programs in the United States

Millions of households in the United States receive federal income tax refunds annually, many for substantial amounts. Consumers can use the proceeds of income tax refunds for spending and saving, but tests of prior programs to encourage savings show low take-up rates. This field study shows that the majority of tax filers make no estimate of their refund amount in advance, but that consumers who are able to estimate their refund in advance of completing their tax returns tend to be reasonably accurate in their estimates. Moreover, taxpayers who estimate their refunds before filing their taxes are more likely to save their refunds than those who do not. These results highlight the importance of expectations and planning with respect to savings decisions.

Pricing strategy, return policy and coordination in a two-stage supply chain

ABSTRACTIn this paper, pricing, return and coordination policies in a two-stage supply chain, consisting of a manufacturer and a supplier are investigated. We propose a new return policy that depends on refund amount and selling price of product. Also, we develop and analyse a joint optimisation problem of pricing and return policies where both cooperative and non-cooperative games are used. In non-cooperative game, we use the Stackelberg game theory model where the supplier acts as leader and manufacture is follower, and in cooperative game, we use the Rubinstein bargaining model. Result shows that the system performance in cooperative game is always better than non-cooperative game, and cooperative game based on Rubinstein bargaining and return policy can ensure more than 31% increase in profits of the two-stage supply chain system.

Price Drop Protection Policy with Forward Looking Consumers

Have you ever purchased an item only to notice a short while later that its price was reduced? Many retailers now offer to refund customers the full price difference as long as the price discount occurred within a specified short period of time after the original purchase (e.g. Amazon, Walmart, Neiman Marcus). Such price difference refund policy looks very attractive to consumers as it shields them from future price fluctuations. But can this policy be advantageous for the retailer who has to refund the money if prices drop? Despite the recent popularity of such policies, the existing research on the topic is scarce. In this paper we investigate the price difference refund policy (commonly referred to as price adjustment) and demonstrate how it can improve retailer's profits. We show that contrary to common belief, price adjustment can result in higher profits even if all consumers request and receive the refund.Further, the existing literature and practice both assume that if price adjustment policy is employed, the consumers should get the full price difference back. In this paper we consider a generalized price adjustment policy where we endogenize the refund amount, allowing the retailer to determine the optimal percentage of price difference to be returned to consumers. We fully characterize the conditions under which it is optimal to offer only a partial refund to customers as well as the optimal refund fraction. Additionally, we demonstrate that the practice of limiting the price adjustment option to a short period after the purchase is not necessarily in the best interest of retailers.

Consumer returns policies with endogenous deadline and supply chain coordination

This paper considers returns policies under which consumers’ valuation depends on the refund amount they receive and the length of time they must wait after the item is returned. Consumers face an uncertain valuation before purchase, and the realization of that purchase's value occurs only after the return deadline has passed. Depending on the product lifecycle length and magnitude of return rate, a retailer decides on strategies for that product's return deadline, including return prohibition, life-cycle return, and fixed return deadline. In addition, the influence of the return deadline on consumers’ behavior and the pricing and inventory policies of the retailer are systematically investigated. Moreover, based on the analysis of consumer return behavior on a traditional buy-back contract, we present a new differentiated buy-back contract, contingent on return deadline, to coordinate a supply chain consisting of an upstream manufacturer and a downstream retailer. Finally, extensions on some specific behavioral factors such as moral hazard, inertia return, and external effect are investigated.

When to Carry Eccentric Products? Optimal Retail Assortment under Consumer Returns

To understand whether retailers should consider consumer returns when merchandising, we study how the optimal assortment of a retailer is influenced by its return policy. The retailer selects its assortment from an exogenous set of horizontally differentiated products. Consumers make purchase and keep/return decisions in nested multinomial logit fashion. Our main finding is that the optimal assortment has a distinct structure for relatively strict return policies: it is optimal to offer a mix of the most popular and most eccentric products when the refund amount is sufficiently low, which can be viewed as a form of risk sharing between the retailer and consumers. In contrast, if the refund is sufficiently high or when returns are disallowed, the optimal assortment is composed of only the most popular products (a common finding in the literature). We provide preliminary empirical evidence for one of the key drivers of our results: more eccentric products have higher probability of return—conditional on purchase. In light of our analytical findings and managerial insights, we conclude that retailers should take returns into account when merchandising.

Supply chain coordination with customer returns and refund-dependent demand

This paper examines a supply chain consisting of a single manufacturer and a single retailer, who faces with demand uncertainty. We investigate how customer returns influence the retailer's ordering decision as well as the profits of the manufacturer and the retailer. When the refund amount is exogenous, the supply chain can be coordinated by the buyback contract. We then treat the refund amount as a decision variable and show that in that case the buyback contract generally cannot coordinate the supply chain. We numerically illustrate and measure the profit loss to the supply chain due to this lack of coordination.