Knowledge that Transforms

Problem definition: In an environment where consumers’ rising valuation of Instagrammable memories drives their spending from products to experiences, retailers offer experiences to attract consumers back to their stores. Yet, it is not obvious under which settings consumers can benefit from these experiences and raise retailers’ profits. Methodology/results: We use a random utility model for consumer choice in both monopoly and duopoly settings. For the latter, we pose a game-theoretic model to analyze the equilibrium prices, profits, and consumer welfare for various problem cases. We show that medium-quality experiences can lower the product sales and store traffic below the level when no experience is offered. Sufficiently low- or high-quality experiences overcome this issue, making the consumers better off. Yet, the former presents the only profitable option when a single retailer in the market offers an experience. In contrast, when both retailers adopt experiences, low-quality experiences may not be profitable, and the retailers would need to adopt even higher-quality experiences, which lead to a “win-win-win” outcome for the two retailers and consumers. A fee structure for the experience elevates retailer profits but can turn stores into outlets where consumers visit to purchase experiences and not products. When experiential retailing is the common practice in the market, it enables “win-win-win” outcomes when free experiences fail. Managerial implications: Being the first to study this new retail format, our results contribute to the ongoing debate on the settings under which experiential offerings are beneficial for the retailers and consumers and highlight that there is no one-size-fits-all strategy. Our results show that experiences affect main product sales in nonobvious ways, especially in competitive markets. In a (post-)pandemic world where retailers try to attract consumers back to stores, we offer insights that can guide retailers in the process.

Problem definition: Consumers often try a few varieties of an experience product before establishing a shopping routine. In retailing, a sample box typically refers to a package of multiple trial-sized varieties within a product category. Sample boxes potentially create value by helping consumers resolve their uncertainties regarding these varieties earlier and at a lower cost. In this paper, we study how firms and consumers share this added value under different market scenarios. We also derive the optimal pricing of sample boxes in product categories for which consumers make ongoing purchases over time. Academic/practical relevance: We thus extend the literature by proposing a framework that integrates sequential search and seller-induced learning. Methodology: We analyze a firm’s pricing decisions when consumers either purchase full-sized options sequentially or bypass that process via a sample box. We use dynamic programming to analyze consumers’ search problem (in the absence of a sample box) and nonlinear optimization to analyze the firm’s problem. Results: As anticipated, the informational value of a sample box yields an optimal price premium relative to the prices of individual products. Despite this price premium, we show that the firm’s expected profit may decrease because a sample box accelerates consumer learning, and thus, it may help consumers settle upon an outside option earlier. We establish that a firm can reverse the potential adverse profit impact of selling sample boxes by introducing an optimally specified future credit. Managerial implications: Offering sample boxes is a common practice in retailing. Contrasting the resulting expected profits with and without the sample box option, our results highlight that managers may be ill-advised to offer a sample box in the absence of the future credit mechanism. This study is the first to address the pricing of sample boxes and show the optimality of offering credit toward a subsequent purchase.

Problem definition: We consider the mechanism design problem of finding an optimal pay-as-bid mechanism in which a platform chooses an assortment of suppliers to balance the tradeoff between two objectives: providing enough variety to accommodate heterogeneous buyers, yet at low prices. Academic/practical relevance: Modern buying channels, including e-commerce and public procurement, often consist of a platform that mediates transactions. Frequently, these platforms implement simple and transparent mechanisms to induce suppliers’ direct participation, which typically results in pay-as-bid (or first-price) mechanisms where suppliers set their prices. Methodology: We introduce a novel class of assortment mechanisms that we call k-soft reserves (k-SRs): If at least k suppliers choose a price below the soft-reserve price, then only those suppliers are added to the assortment; otherwise, all the suppliers are added. Results: We show the optimality of k-SRs for a class of stylized symmetric models to derive the intuition behind these mechanisms. Then, through extensive numerical simulations, we provide evidence of the robustness of k-SRs in more general and realistic settings. Managerial implications: Our results give intuitive and simple-to-use prescriptions on how to optimize pay-as-bid assortment mechanisms in practice, with an emphasis on public procurement settings.

Problem definition: Kidney paired donation programs allow patients registered with an incompatible donor to receive a suitable kidney from another donor, as long as the latter’s co-registered patient, if any, also receives a kidney from a different donor. The kidney exchange problem (KEP) aims to find an optimal collection of kidney exchanges taking the form of cycles and chains. Methodology/results: We develop the first decomposition method that is able to consider long cycles and long chains for projected large realistic instances. Particularly, we propose a branch-and-price framework in which the pricing problems are solved (for the first time in packing problems in a digraph) through multivalued decision diagrams. We present a new upper bound on the optimal value of the KEP, obtained via our master problem. Computational experiments show superior performance of our method over the state of the art by optimally solving almost all instances in the PrefLib library for multiple cycle and chain lengths. Managerial implications: Our algorithm also allows the prioritization of the solution composition, for example, chains over cycles or vice versa, and we conclude, similar to previous findings, that chains benefit the overall matching efficiency and highly sensitized patients.

Problem definition: Revenue management in railways distinguishes itself from that in traditional sectors, such as airline, hotel, and fashion retail, in several important ways. (i) Capacity is substantially more flexible in the sense that changes to the capacity of a train can often be made throughout the sales horizon. Consequently, the joint optimization of prices and capacity assumes genuine importance. (ii) Capacity can only be added in discrete “chunks” (i.e., coaches). (iii) Passengers with unreserved tickets can travel in any of the multiple trains available during the day. Further, passengers in unreserved coaches are allowed to travel by standing, thus giving rise to the need to manage congestion. Motivated by our work with a major railway company in Japan, we analyze the problem of jointly optimizing pricing and capacity; this problem is more-general version of the canonical multiproduct dynamic-pricing problem. Methodology/results: Our analysis yields four asymptotically optimal policies. From the viewpoint of the pricing decisions, our policies can be classified into two types—static and dynamic. With respect to the timing of the capacity decisions, our policies are again of two types—fixed capacity and flexible capacity. We establish the convergence rates of these policies; when demand and supply are scaled by a factor [Formula: see text], the optimality gaps of the static policies scale proportional to [Formula: see text], and those of the dynamic policies scale proportional to [Formula: see text]. We illustrate the attractive performance of our policies on a test suite of instances based on real-world operations of the high-speed “Shinkansen” trains in Japan and develop associated insights. Managerial implications: Our work provides railway administrators with simple and effective policies for pricing, capacity, and congestion management. Our policies cater to different contingencies that decision makers may face in practice: the need for static or dynamic prices and for fixed or flexible capacity.

Problem definition: Although in-kind donations contribute to charity’s triple bottom line (i.e., generating additional revenue for the charity, contributing to social welfare, and reducing environmental waste through rechanneling used items), inappropriate material donations impose additional costs to sort, process, or discard them. Minimizing the amount of undesired in-kind donations, however, is a challenge given charities’ sensitive relationship with their donors. This paper examines the effectiveness of behavioral interventions on improving the quality of in-kind donations gifted by individuals. Methodology/results: We conducted a field experiment to implement interventions motivated by two well-established behavioral mechanisms: information disclosure and social norm. We studied the reaction of 763 donors who were scheduled to make an in-kind donation at a local charity between October 31 and November 11, 2020. Our results show that using the social norm intervention effectively improved the quality of in-kind donations, whereas information disclosure, which is commonly used in practice as the industry standard intervention, was ineffective. We also conducted two postexperiment analyses. First, we collected additional data on 1,301 in-kind donations whose donors had received the social norm intervention during February 2021. Results show that the impact of the social norm intervention is stable over different time periods. Second, we studied the spillover effect of these interventions for a period of 12 months and did not find a negative long-term impact on in-kind donations. Managerial implications: A conservative estimation shows that implementing the social norm intervention reduced the junk donations received by 50% without having a negative spillover effect on donors’ in-kind donations or imposing any direct operating cost. Consequently, this field evidence provides an effective, cost-efficient, and scalable solution for charities to address the quality problem of in-kind donations. In addition, our results challenge the industry conventional practice of incorporating information disclosure in their communications with donors.

Problem definition: We study a repeated interaction between a manufacturer and a retailer, where the retailer may share with the manufacturer past sales information. In our model, such information cannot improve the latter’s predictive capabilities of future demand, but it does allow him to infer past demand. Academic/practical relevance: Our main research questions are under what conditions the retailer and the manufacturer benefit from sharing such past sales information and how dynamic interaction and past sales information affect the efficiency of the distribution channel. Methodology: We model a repeated relationship between a manufacturer and a retailer, where demand fluctuates in an independent and identically distributed manner between periods. In each period, the retailer privately observes the current demand, and the manufacturer offers a menu of contracts to elicit the retailer to reveal its private information. The manufacturer may observe sales information that reveals past demand at the end of each period if the retailer chooses to share such information. Results: We find that even without sharing sales information, repeated interaction by itself enhances efficiency and profits for both firms. Past sales information further improves the channels’ efficiency and increases the manufacturer’s expected profit. Yet, past sales information increases (decreases) the retailer’s per-period expected profit when the retailer places a low (high) value on its future profits. Managerial implications: Our results provide a new strategic reasoning for sharing past sales information—as a way to increase trust in repeated vertical relationships. Furthermore, when the retailer can share a noisy signal regarding past demand, this may facilitate the exchange of sales information. We also consider the case of a financially constrained retailer and demonstrate that financial constraints may benefit the retailer as they limit the market power of the manufacturer. In contrast, the manufacturer and the channel’s efficiency are always worse off when the retailer is financially constrained.

Problem definition: Mobile money systems—platforms built and managed by mobile network platform operators (MMPOs) to allow money to be stored as digital currency—connect millions of poor and “unbanked” people to the formal financial system. Unfortunately, low service levels because of the suboptimal management of cash and digital currency (e-float) inventory impede the development of these ecosystems. Accordingly, we seek to answer the question of how agents should manage inventories of cash and e-float. Academic/practical relevance: This paper extends inventory theory to the mobile money context, unique in that sales of cash generate inventory of e-float and vice versa. In doing so, we address a key pain point for an emerging sector that improves lives at the base of the pyramid. Methodology: We develop an analytical heuristic to determine initial stocking levels for cash and e-float and analyze its performance on simulated and actual data. Results: By partnering with an MMPO, we tested the performance of the heuristic inventory policy with data from more than 35 million transactions. The heuristic captured 99.9998% of the optimal profit on simulated data and, on actual data, we found that following the recommendations could increase agents’ profits by an average of 15.4%. Managerial implications: We develop a pragmatic inventory policy that performs nearly optimally. We also analyze under which conditions the performance deteriorates and examine heterogeneity among agents with respect to the heuristic’s impact on their performance. Thus, we equip MMPOs with guidance as to whom to target and how. By contributing to service level and profit improvements, this work can make mobile money a more effective financial inclusion tool in the developing world as well as improve the livelihoods of agents.

Problem definition: Social media has become an indispensable platform for disseminating quality information to consumers across various service sectors. Recently, it has extended its influence to healthcare services, which traditionally relied on government report cards to disclose standardized quality information to the public. This article explores the impact of social media on consumer demand for healthcare services and compares its effectiveness with government report cards. Methodology/results: We analyze quality ratings of U.S. nursing homes collected from two information channels: (1) consumer ratings on Yelp and (2) government ratings on Nursing Home Compare, both of which adopt a five-star quality rating scale and are accessible on the Internet. We employ the method of difference-in-differences with continuous treatment intensity and instrumental variables to analyze the data. Using nursing home resident admissions as a proxy for consumer demand, we find that higher Yelp ratings led to higher consumer demand, particularly among Medicare-covered consumers. Furthermore, the effect of Yelp ratings was primarily driven by extreme ratings (one-star or five-star), as opposed to neutral ratings. We also find that Yelp ratings exerted a stronger effect on consumer demand than government ratings. This dominance of Yelp ratings over government ratings was observed primarily in markets with high Yelp penetration or markets with low and medium consumer education levels. Although higher Yelp ratings were associated with increased net incomes, we find little evidence that nursing homes made quality improvement in response to their Yelp ratings. Managerial implications: We recommend that the Centers for Medicare and Medicaid Services recognize social media platforms as valuable sources of information and collaborate with reputable platforms, such as Yelp, to promote public awareness of government report cards like Nursing Home Compare. Moreover, we advise nursing home operators to proactively manage their reputation on social media by promptly addressing consumer complaints and implementing quality improvement measures.

Problem definition: Strategic inventory refers to the inventory held by firms purely out of strategic considerations other than operational reasons (e.g., economies of scale). In this paper, we investigate the roles of strategic inventory in a system with two parallel supply chains under both full bargaining and partial bargaining, which differ in whether inventory is included in the bargaining terms. Methodology/results: (i) Under full bargaining, horizontal competition can induce an asymmetric equilibrium, whereby only one of the chains carries strategic inventory and benefits from it when the holding cost is small. The whole system, however, is worse off. (ii) Under partial bargaining, regardless of whether there is horizontal competition, the retailer in a supply chain always carries inventory when his bargaining power is small and the inventory holding cost is low. Furthermore, with horizontal competition, inventory hurts (improves) the system performance when the inventory holding cost is small (above a threshold and not too big). (iii) Full bargaining can be inferior to partial bargaining when there is horizontal competition. Managerial implications: The conventional wisdom about strategic inventory should be taken with caution. Specifically, the traditional role of strategic inventory empowering the retailer in a supply chain is completely dominated by the full bargaining framework, yet it is still present if inventory is not bargained. The inventory driven by horizontal competition plays a different strategic role of signaling to the competitor to avoid an otherwise adverse quantity competition if both retailers carried high inventory. Furthermore, despite the full cooperation nature of the full bargaining framework, it is not always in the retailer’s interest to give up the decision power on inventory (partial bargaining) and include it in the negotiation process (full bargaining).