Knowledge that Transforms

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.

Traditional approaches in inventory control first estimate the demand distribution among a predefined family of distributions based on data fitting of historical demand observations, and then optimize the inventory control using the estimated distributions. These approaches often lead to fragile solutions whenever the preselected family of distributions was inadequate. In this article, we propose a minimax robust model that integrates data fitting and inventory optimization for the single‐item multi‐period periodic review stochastic lot‐sizing problem. In contrast with the standard assumption of given distributions, we assume that histograms are part of the input. The robust model generalizes the Bayesian model, and it can be interpreted as minimizing history‐dependent risk measures. We prove that the optimal inventory control policies of the robust model share the same structure as the traditional stochastic dynamic programming counterpart. In particular, we analyze the robust model based on the chi‐square goodness‐of‐fit test. If demand samples are obtained from a known distribution, the robust model converges to the stochastic model with true distribution under generous conditions. Its effectiveness is also validated by numerical experiments.

We analyze the market entry problem faced by startups that must integrate their service or product with one or more complementary technologies. The problem is especially challenging when the complementary technologies have uncertain cost reduction potentials. The entrepreneurship literature suggests that startups should pursue focused strategies for various reasons, including bounded rationality and budget constraints, but generally overlooks startups entering markets with complementary technologies. The advice for mature firms investing in complementary technologies is often to diversify investment across multiple complements to manage technological uncertainty. Given competing guidance, we seek to extend the entrepreneurship literature by modeling startups' entry decisions for markets in which complementary technologies exhibit strong learning effects. We find that, consistent with the extant entrepreneurship literature, startups generally achieve higher expected returns by channeling their integration investment to only one complementary technology. However, the mechanisms driving our results differ significantly by hinging on nonlinear feedback effects that occur when firms concentrate integration investment in only one complementary technology. Interestingly, this focused strategy often does not yield the highest market share or the lowest likelihood of bankruptcy. We characterize the situations under which each finding holds and describe the implications of these findings for theory, practice, and policy.

Recent years have witnessed the pervasive supply disruptions and their impacts on supply chain performance. In this study, we investigate the optimal procurement design with supply disruptions and heterogeneous beliefs between the buyer and the supplier. We examine the impact of information asymmetry on the supplier's belief, the control right of the backup production, and the verifiability of supply disruption. The belief heterogeneity creates speculative gains and losses because the buyer and the supplier hold different estimates of the disruption probability. We demonstrate that the buyer's incentive to exploit this belief heterogeneity leads to real production inefficiencies in different scenarios. The production efficiency is not necessarily improved with more transparent information. Moreover, a very pessimistic supplier may have no incentive to invest in improving the reliability even if this is costless, and the supplier may produce more when the expected production cost becomes higher. When the buyer sees some value in using the supplier's estimate to update his own belief, we find that the main results hold unless the buyer completely abandons his belief.

This research investigates the value of category captainship (a management practice in which a retailer relies on a manufacturer for recommendations regarding strategic category management decisions) in retail supply chains. We consider a setting where the scope of category management is limited to assortment decisions and demand enhancing activities. We assume that the retailer selects a category captain among multiple competing manufacturers with privately known capabilities for driving category traffic. First, we consider a benchmark scenario where the retailer is responsible for category management. Then, we consider the category captainship scenario where the retailer selects one of the manufacturers as a captain to manage the category. We find that captainship is more likely to emerge in categories where the cost of managing variety, the retail margins, and the competition for captainship are moderate and the captain is more capable of driving traffic compared to the retailer. In such categories the collaboration between the retailer and the captain ensures sufficient surplus for both parties. Finally, we show that captainship can also benefit the non‐captain manufacturers.

We consider the service parts end‐of‐life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phaseout returns. Phaseout returns happen when a customer replaces an old system platform with a next‐generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this study, we study the decision‐making complications as well as cost‐saving opportunities stemming from phaseout occurrence. We use a finite‐horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time‐varying threshold level for item repair. Furthermore, we study the value of phaseout information by extending the results to cases with an uncertain phaseout quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.

In this article, we study the price partitioning decisions of online retailers regarding shipping and handling (S&H) fees. Specifically, we analyze two partitioning formats used by retailers in this context. In the first scenario, retailers present customers with a price that is partitioned into a product price and a separate S&H surcharge (the PS strategy ); in the second, customers are offered free shipping through a non‐partitioned format where the product price already includes the shipping cost (the ZS strategy ). We first develop a stylized game‐theoretic model that captures the competitive dynamics between (and within) these two formats. Analysis of the model provides insights into how both firm and product level characteristics drive a retailer's strategic choice regarding which partitioning format to adopt and, hence, determines the equilibrium market structure in terms of proportion of ZS and PS retailers. Subsequently, we conduct empirical analyses , based on product and S&H prices data for two different product categories (digital cameras and printers) collected from online retailers, to validate all the results of our theoretical model. We establish that PS retailers charge lower product prices than ZS ones, but the total price (product + S&H) charged is higher for the first group. The S&H charge for PS retailers can be significant—it is, on average, 5.4% (printers) and 3.0% (digital cameras) for our two product categories. Furthermore, retailers which are popular and/or face risky cost environment are more likely to opt for the ZS strategy, while retailers whose portfolio mostly includes large or heavy products with high cost (S&H)‐to‐price ratios usually choose the PS strategy. Lastly, our empirical study also illustrates that the price adjustment behavior of retailers is affected by their shipping‐fee policies—for example, ZS retailers change their product prices almost 1.5 times more frequently than PS ones.

Despite the spread of cost‐driven outsourcing practices, academic research cautions that suppliers' cost advantage may weaken manufacturers' bargaining positions in negotiating outsourcing agreements, thereby hurting their profitability. In this study, we attempt to further understand the strategic impact of low‐cost outsourcing on manufacturers' profitability by investigating the contractual form of outsourcing agreements and the industry structure of the upstream supply market. We consider a two‐tier supply chain system, consisting of two competing manufacturers, who have the option to produce in‐house or to outsource to an upstream supplier with lower cost. To reach an outsourcing agreement, each manufacturer engages in bilateral negotiation with her supplier, who may be an exclusive supplier or a common supplier serving both manufacturers. Our analysis shows that wholesale‐price contracts always mitigate the competition between manufacturers regardless of whether they compete with price or quantity. In contrast, two‐part tariffs intensify the competition when the manufacturers compete with quantity, but soften it when they compete with price. As a result, when outsourcing with two‐part tariffs, the manufacturers may earn lower profits than they would from in‐house production, although the suppliers are more cost efficient. This suggests that managers have to be wary about the downside of using coordinating contracts such as two‐part tariffs when pursuing low‐cost outsourcing strategies. Our analysis also sheds some light on the profitability of using an exclusive supplier for outsourcing. When outsourcing with wholesale‐price contracts, the competing manufacturers are better off outsourcing to an exclusive supplier. However, when outsourcing with two‐part tariffs, the manufacturers may earn higher profits by outsourcing to a common supplier than to an exclusive one when the manufacturers' bargaining power is sufficiently strong (weak) under quantity (price) competition.

This article examines the choice of pricing policy (posted pricing or negotiation) toward end customers in a supply chain. Many retailers actively decide whether or not to encourage negotiation on the shop floor. Of course, the retailer's pricing policy influences not only the retailer's profit, but also the profits of the manufacturers who sell through the retailer. However, little is known about the forces that shape the pricing policy when two self‐interested parties interact in a supply chain. We consider two alternative models depending on who has the power to decide the pricing policy: the manufacturer or the retailer. We find that an increase in the wholesale price weakens the retailer's ability to price discriminate through negotiation. Therefore, the retailer prefers negotiation at lower wholesale prices and posted pricing at higher wholesale prices. We also find that whenever the retailer prefers negotiation, the manufacturer does too. Therefore, the retailer's discretion over the pricing policy causes friction only when the retailer wants to use posted pricing, while the manufacturer wishes the retailer to use negotiation. We show that such friction arises only when product availability or the cost of negotiation is moderate. In this case, we show that the manufacturer may offer a substantial discount to persuade the retailer to negotiate. Surprisingly, in this region of friction, a decrease in the supply chain's capacity or an increase in negotiation costs (both of which are typically considered as worsening the retailer's business environment) translates into higher profit for the retailer.

With the growing influence of online social media, firms increasingly take an active role in interacting with consumers in social media. For many firms, their first step in online social media is management responses, where the management responds to customers' comments about the firm or its products and services. In this article, we measure the impact of management responses on customer satisfaction using data retrieved from a major online travel agency in China. Applying a panel data model that controls for regression toward the mean and heterogeneity in individual preference for hotels, we find that online management responses are highly effective among low satisfaction customers but have limited influence on other customers. Moreover, we show that the public nature of online management responses introduces a new dynamic among customers. Although online management responses increase future satisfaction of the complaining customers who receive the responses, they decrease future satisfaction of complaining customers who observe but do not receive management responses. The result is consistent with the peer‐induced fairness theory.