The goal of this paper is to describe, model, and optimize inventory in a reverse logistics system that supports the warranty returns and replacements for a consumer electronic device. The context and motivation for this work stem from a collaboration with an industrial partner, a Fortune 100 company that sells consumer electronics. The reverse logistics system is a closed-loop supply chain: failed devices are returned for repair and refurbishing; this inventory is then used to serve warranty claims or sold through a side sales channel. Managing inventory in this system is challenging because of the short life cycle of these devices and the rapidly declining value for the inventory. We examine an inventory model that captures these dynamics. We characterize the structure of the optimal policy for this problem for stochastic demand and introduce an algorithm to calculate optimal sell-down levels. We also provide a closed-form policy for the deterministic version of the problem, and we use this policy as a certainty-equivalent approximation to the stochastic optimal policy. Finally, using numerical experiments, we analyze the sensitivity of this system to changes in various parameters, and we also evaluate the performance of the certainty-equivalent approximation using data from our industrial partner. The online appendix is available at https://doi.org/10.1287/msom.2017.0622 .

We consider the problem of a newsvendor that is served by multiple suppliers, where any given supplier is defined to be either perfectly reliable or unreliable. By perfectly reliable we mean a supplier that delivers an amount identically equal to the amount desired, as is the case in the most basic variant of the newsvendor problem. By unreliable, we mean a supplier that with some probability delivers an amount strictly less than the amount desired. Our results indicate the following effects of unreliability: From the perspective of the newsvendor, the aggregate quantity ordered is higher than otherwise would be ordered if the newsvendor’s suppliers were completely reliable. From the perspective of end customers, however, the service level provided is lower than otherwise would be provided if the newsvendor’s suppliers were completely reliable. From the perspective of the suppliers, although reliability affects how much is ordered from a selected supplier, cost generally takes precedence over reliability when it comes to selecting suppliers in the first place. Even perfect reliability is no guarantee for qualification since, in an optimal solution, a given supplier will be selected only if all less-expensive suppliers are selected, regardless of the given supplier’s reliability level. Nevertheless, the relative size of a selected supplier’s order depends on its reliability.

Online purchases constitute about one-tenth of U.S. retail sales. The supply chains that support online retailing are fundamentally different from those that support traditional brick-and-mortar stores. Traditional solutions are not always appropriate to solve online retailing’s operations problems; thus, there is an opportunity to understand and improve these novel supply chains. One key characteristic of the inventory systems for online retailing is demand spillover, whereby a stockout at a fulfillment center (FC) results in demand spilling over to another FC. For this context we examine how to allocate inventory to the FCs under a periodic-review joint-replenishment policy, with an objective to minimize outbound shipping costs for a fixed amount of inventory. We first show how traditional decentralized allocation policies may perform suboptimally and induce dynamics (whiplash) that result in costly spillover. We find that this phenomenon increases with the prevalence of local stockouts and with the level of inventory imbalance. We then describe that inventory imbalance occurs in online retailing because of operational realities and provide evidence based on real data. Finally, we propose a heuristic to allocate inventory accounting for possible spillover during the lead time. We test the heuristic by a simulation and show that it performs better than the status quo policy, is robust to operational realities, and captures over 90% of the possible improvement as compared to a pseudo-optimal policy. The online appendix is available at https://doi.org/10.1287/msom.2016.0614 .

Problem definition: It is common practice for firms to deploy strategies based on customer segmentation (by clustering customers into different segments) and price discrimination (by offering different prices to different customer segments). Price discrimination, although seemingly beneficial, can hurt firms in competitive environments. Academic/practical relevance: It is thus critical for firms to understand when to engage in price discrimination and how to support discriminatory pricing practices with appropriate inventory management strategies. This paper tackles this overarching question through operational lenses by studying the joint impact of price discrimination and the allocation of limited inventory across customer segments. Methodology: We develop a Bertrand competition game featuring capacity restrictions, quality differentiation, and customer heterogeneity. Results: We characterize (pure- or mixed-strategy) Nash equilibria for a single-stage game reflecting uniform pricing and for a two-stage inventory-price game reflecting discriminatory pricing along with endogenous inventory allocation. Managerial implications: We identify three sources of market friction in price competition enabling firms to earn higher profits: capacity limitations, quality differentiation, and customer heterogeneity. Price discrimination eliminates the market frictions from customer heterogeneity, but strategic inventory allocation restores (or strengthens) the market frictions from capacity limitations. As such, price discrimination is only beneficial when combined with optimal inventory allocation across segments. We discuss relevant real-world examples featuring regional price discrimination along with strategic inventory allocation, including fast fashion and vaccines. Otherwise, uniform pricing may outperform discriminatory pricing. Our results thus underscore the critical role of inventory allocation in the design of competitive pricing strategies. Funding: This research was partially supported by the National Natural Science Foundation of China [Grant 71821002]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1146 .

Problem definition: Our objective is to design a defibrillator-enabled drone network that augments the existing emergency medical services (EMS) system to rapidly respond to out-of-hospital cardiac arrest (OHCA). Academic/practical relevance: OHCA claims more than 400,000 lives each year in North America and is one of the most time-sensitive medical emergencies. Drone-delivered automated external defibrillators (AEDs) have the potential to be a transformative innovation in the provision of emergency care for OHCA. Methodology: We develop an integrated location-queuing model that incorporates existing EMS response times and is based on the p-median architecture, where each base constitutes an explicit [Formula: see text] queue (i.e., Erlang loss). We then develop a reformulation technique that exploits the existing EMS response times, allowing us to solve real-world instances to optimality using an off-the-shelf solver. We evaluate our solutions using a tactical simulation model that accounts for the effects of congestion and dispatching, and we use a machine-learning model to translate our response-time reductions into survival estimates. Results: Using real data from an area covering 26,000 square kilometers around Toronto, Canada, we find that a modest number of drones are required to significantly reduce response times in all regions. An objective function that minimizes average response time results in drone resources concentrated in cities, with little impact on the tail of the distribution. In contrast, optimizing for the tail of the response-time distribution produces larger and more geographically dispersed drone networks that improve response-time equity across the regions. We estimate that the response-time reductions achieved by the drone network are associated with between a 42% and 76% higher survival rate and up to 144 additional lives saved each year across the geographical region we consider. Managerial implications: Overall, this paper provides a realistic framework that can be leveraged by system designers and/or EMS personnel seeking to investigate design questions associated with a drone network. An objective function focused on improving the tail of the response-time distribution is well-suited for use in practice because the model provides equitable solutions that reduce the entire response-time distribution and corresponds to the real-world metrics, on which EMS systems are most commonly evaluated.

Problem definition : We examine a dynamic assignment problem faced by a large wireless service provider (WSP) that is a Fortune 100 company. This company manages two warranties: (i) a customer warranty that the WSP offers its customers and (ii) an original equipment manufacturer (OEM) warranty that OEMs offer the WSP. The WSP uses devices refurbished by the OEM as replacement devices, and hence their warranty operation is a closed-loop supply chain. Depending on the assignment the WSP uses, the customer and OEM warranties might become misaligned for customer-device pairs, potentially incurring a cost for the WSP. Academic/practical relevance : We identify, model, and analyze a new dynamic assignment problem that emerges in this setting called the warranty matching problem. We introduce a new class of policies, called farsighted policies, which can perform better than myopic policies. We also propose a new heuristic assignment policy, the sampling policy, which leads to a near-optimal assignment. Our model and results are motivated by a real-world problem, and our theory-guided assignment policies can be used in practice; we validate our results using data from our industrial partner. Methodology : We formulate the problem of dynamically assigning devices to customers as a discrete-time stochastic dynamic programming problem. Because this problem suffers from the curse of dimensionality, we propose and analyze a set of reasonable classes of assignment policies. Results : The performance metric that we use for a given assignment policy is the average time that a replacement device under a customer warranty is uncovered by an OEM warranty. We show that our assignment policies reduce the average uncovered time and the expected number of out-of-OEM-warranty returns by more than 75% in comparison with our industrial partner’s current assignment policy. We also provide distribution-free bounds for the performance of a myopic assignment policy and of random assignment, which is a proxy for the WSP’s current policy. Managerial implications : Our results indicate that, in closed-loop supply chains, being completely farsighted might be better than being completely myopic. Also, policies that are effective in balancing short-term and long-term costs can be simple and effective, as illustrated by our sampling policy. We describe how the performance of myopic and farsighted policies depend on the size and length of inventory buildup.

Problem definition: We develop a framework for studying the impact of voluntary ecolabels and mandatory environmental regulation on green product development among competing firms. Academic/practical relevance: We contribute to the academic literature on environmental quality competition by explicitly accounting for the credibility of environmental claims made by firms, and by exploring the implications for society of two mechanisms used to remedy credibility-related consumer discounting of firms’ self-declared environmental qualities. We draw parallels between our findings and instances of environmental labeling and regulation from industry to highlight the practical implications of our study. Methodology: We use a game-theoretic framework to analyze a consumer-driven model of green product development. Results: Credibility asymmetry drives product differentiation between two competing firms. The less credible firm always adopts external certification, while the more credible firm does so only if its credibility is sufficiently low. Credibility may also determine whether or not the government should intervene. In the absence of an external certifier, the regulator should intervene by imposing a mandatory environmental standard that is decreasing in stringency as the credibility of the more credible firm increases. In the presence of a certifier, the regulator should intervene if neither firm is sufficiently credible, or if consumers do not value environmental stewardship highly. Managerial implications: We identify how and when government should (and should not) intervene to stimulate green product development when competing firms can use self-labels or external certifications to communicate their environmental performance to consumers. We also determine the optimal strategies for the competing firms and external certifiers.

Problem definition: Fashion retailers are increasingly implementing take-back programs to reduce textile waste and prevent used clothing from being landfilled. To increase participation, retailers must decide how much and what type of information to provide to consumers, how to collect the used clothing, and how much of a financial reward to offer. However, the effectiveness of different types of information, convenience, and reward levels on consumer participation is not well understood, and participation rates in take-back programs remain low. Methodology/results: We examine the effect of different information levels (i.e., none, generic, and different types of specific information) and convenience levels on the reward required by consumers to return their used clothing through four experiments involving over 5,200 subjects. Across all experiments, we find that providing generic information that collected items will be diverted from the landfill significantly decreases the reward required by consumers to return their used clothing. However, we find that providing information about a specific circular economy strategy does not necessarily help. When the collected clothing will be recycled (either as open-loop or as closed-loop), consumers’ required reward is not significantly different from when the clothing will just be diverted from the landfill. Moreover, we find that when collected clothing will be resold, consumers’ required reward is significantly higher. We show that the negative response to resale is due to the consumers’ aversion to the retailer explicitly profiting from the returned clothing. We also find that making the return process more convenient lowers the reward required by consumers. Managerial implications: Our results offer several managerial insights. We find that information can be an effective lever to increase consumers’ participation in take-back programs, but only if used judiciously. If a retailer intends to resell collected clothing, it may consider offering a higher reward or making the return process more convenient. Even though a more convenient return process may be more costly for the retailer, those additional costs may be offset by the lower reward required by the consumers. Funding: A. Sáez de Tejada Cuenca’s research was partially supported by the Spanish Ministry of Science and Innovation [ref. SFJC1900I042215XV0]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0561 .

Problem definition: We study a shipper transporting and selling a short life-cycle product to a destination market via two competing transportation service providers (i.e., carriers). The two carriers offer distinct speeds and competing freight rates, whereas customers in the destination market obtain higher utility if they receive the product earlier and their time preferences are heterogeneous. Academic/practical relevance: Perishable products are commonly shipped via multiple means of transport. The faster the mode of transport, the more expensive it is, but speed enables the product to reach the market with higher quality. In addition to the trade-off between speed and cost, the competition between carriers can also influence the shipper's transportation procurement strategies. Our model highlights the implications of carrier competition in a dual sourcing problem. Methodology: We analyze a two-stage game in which carriers first compete on freight rates, and then the shipper determines the shipping quantities. Results: We show that the shipper may benefit from product differentiation via dual-mode shipping, in which the shipment that arrives earlier is sold at a premium price. In equilibrium, the shipper's profit can be U-shaped in the speed difference between carriers. Dual sourcing may be inferior to simply restricting a single shipping service in a winner-take-all fashion. Managerial implications: This study reveals an underlying trade-off between the operational advantage from product differentiation and the cost advantage from carrier competition. To benefit from either of these advantages, a shipper should use two carriers with either very distinct or very similar speeds. Single sourcing may bring an additional cost advantage that outweighs the value of production differentiation through dual sourcing.

Problem definition E-tailers face a dilemma in addressing the bracketing behaviour, where consumers purchase multiple versions of a product to try at home and return the unsatisfactory ones. While this practice reduces product fit uncertainty, it also results in a surge of returns. Academic/practical relevance Despite this dilemma, how to manage bracketing remains largely under-explored in academic research, particularly in leveraging monetary leniency. Methodology We develop a game-theoretic framework, where the monopoly e-tailer incorporates consumers’ best purchase and return responses into its pricing and return service fee decisions. Results Surprisingly, despite the high reverse logistics cost, the e-tailer can still benefit from bracketing. Managing bracketing involves tailoring pricing and return strategies to product and consumer attributes. Some of these strategies run counter to traditional operations. Specifically, even if the reverse logistics cost is zero, it may still be optimal to charge for returns to extract profit from bracketing or deter bracketing. In addition, the reverse logistics cost should sometimes be incorporated into the price and not, as often, into the return fee, even if it hurts all the consumers. Finally, mitigating fit uncertainty, despite appearing beneficial, could reduce the e-tailer’s overall profit, even if it is costless. Managerial implications Our results offer actionable insights for managing bracketing. First, e-tailers banning bracketing across the board (e.g., Amazon) or applying the same return strategy for most products (e.g., Uniqlo) should develop customised strategies, targeting bracketers, non-bracketers, or both, while offering a partial or full refund and allowing or disallowing returns. Second, e-tailers encouraging bracketing through lenient return policies (e.g., Zappos) could render this practice explicit through mechanisms such as try-on schemes, while strategically employing return fees or pricing to internalise the associated costs. Finally, e-tailers striving to reduce fit uncertainty (e.g., Lululemon) should remain cautious about this practice.