Knowledge that Transforms

Small‐to‐medium‐sized enterprises (SMEs), including many startup firms, need to manage interrelated flows of cash and inventories of goods. In this study, we model a firm that can finance its inventory (ordered or manufactured) with loans in order to meet random demand which in general may not be time stationary. The firm earns interest on its cash on hand and pays interest on its debt. The objective is to maximize the expected value of the firm's capital at the end of a finite planning horizon. The firm's state at the beginning of each period is characterized by the inventory level and the capital level measured in units of the product, whose sum represents the “net worth” of the firm. Our study shows that the optimal ordering policy is characterized by a pair of threshold parameters as follows. (i) If the net worth is less than the lower threshold, then the firm employs a base stock order up to the lower threshold. (ii) If the net worth is between the two thresholds, then the firm orders exactly as many units as it can afford, without borrowing. (iii) If the net worth is above the upper threshold, then the firm employs a base stock order up to the upper threshold. Further, upper and lower bounds for the threshold values are developed using two simple‐to‐compute myopic ordering policies which yield lower bounds for the value function. We also derive an upper bound for the value function by considering a sell‐back policy. Subsequently, it is shown that policies of similar structure are optimal when the loan and deposit interest rates are piecewise linear functions, when there is a maximal loan limit and when unsatisfied demand is backordered. Finally, further managerial insights are provided with extensive numerical studies.

Debris generated by disasters can hinder relief efforts and result in devastating economic, environmental, and health problems. In this study, we present a decision‐support tool employing analytical models to assist disaster and waste management officials with decisions regarding collection, transportation, reduction, recycling, and disposal of debris. The tool enables optimizing and balancing the financial and environmental costs, duration of the collection and disposal operations, landfill usage, and the amount of recycled materials. In addition to post‐disaster operational decisions, the tool can also support the challenging task of developing strategic plans for disaster preparedness. We illustrate the applicability and effectiveness of the tool with a disaster scenario based on Hurricane Andrew.

The practice of diverting genuine products to unauthorized gray markets continues to challenge companies in various industries and creates intense competition for authorized channels. Recent industry surveys report that the abuse of channel incentives is a primary reason for the growth of gray market activities. Therefore, it is crucial that companies take the presence of gray markets into consideration when they design contracts to distribute products through authorized retailers. This issue has received little attention in the extensive literature on contracting and supply chain coordination. In this study, we analyze the impacts of gray markets on two classic contracts, wholesale price and quantity discount, in a supply chain with one manufacturer and one retailer when the retailer has the opportunity to sell to a domestic gray market. Our analysis provides interesting and counterintuitive results. First, a classic quantity‐discount contract that normally coordinates the supply chain can perform so poorly in the presence of a gray market that the supply chain would be better off using a wholesale price contract instead. Second, the presence of gray market can also degrade the performance of the wholesale price contract; therefore, a more sophisticated contract is needed for coordinating the supply chain. We show that contracts that solely depend on retailer's order quantity cannot coordinate the supply chain, and provide the conditions for coordinating the supply chain with price‐dependent quantity discount contracts. We also provide comparative statics and show that when there is a gray market, coordinating the supply chain enhances total consumer welfare.

The research domain Industry Studies and Public Policy (IS&PP) seeks to further our understanding of industrial practices and managerial challenges by explicitly considering contextual details in the design and interpretation of research studies. These details can be vital considerations when shaping public policies. This article reviews a sample of IS&PP publications and analyzes the content of 180 selected papers—85 papers published in the Production and Operations Management (POM) journal and 95 papers published in related journals between 1992 and 2014. Our analysis of the sample dataset and examination of exemplar papers provide four findings. First, studies in different industries emphasize different themes of operational decisions. This difference in emphasis reveals potential research opportunities, especially for conducting inter‐industry studies. Second, our analysis reveals a shift in focus over time. Earlier studies contain a mix of benchmarks and inter‐industry comparisons, while later studies tend to be context‐specific, intra‐industry studies. Third, we report on empirics → analytics → empirics cycles that reveal gaps for building novel theories. Finally, we observe that the relationship between POM decisions and public policy is bi‐directional. This highlights the need to jointly examine operational decisions with policy considerations, especially in information goods, healthcare, sustainable operations and high‐tech manufacturing industries.

We investigate retailers’ dynamic pricing decisions in a stylized two‐period setting with possible supply constraints and demand from both myopic and strategic consumers. We present an analytical model and then test its predictions in a behavioral experiment in which human subjects played the role of pricing managers. We find that the fraction of strategic consumers in the market systematically moderates the optimal pricing structure. When this fraction exceeds a certain threshold, the retailer offers relatively small late season markdowns to discourage strategic consumers from waiting and to incentivize them to buy during the early season; otherwise, the retailer offers relatively large markdowns to divert all strategic consumers to the late season, where the majority of revenue is made. Our model analyses suggest that the latter policy is optimal under fairly broad conditions. Our experiment shows that after some significant learning, aggregate behavior is able to approximate the key qualitative predictions from our model analysis, with one notable deviation: in the presence of a mixture of myopic and strategic consumers, subjects act somewhat myopically – they underprice and oversell in the main selling season, which significantly limits their ability to generate revenue in the markdown season.

We consider a firm's sourcing problem from one reliable supplier and one unreliable supplier in two price‐setting scenarios. In the committed pricing scenario, the firm makes the pricing decision before the supply uncertainty is resolved. In the responsive pricing scenario, the firm's pricing decision is made after the supply uncertainty is resolved. For the committed pricing scenario, we develop a condition on supply uncertainty that guarantees the unimodality of the firm's objective function. By comparing the firm's optimal diversification decisions in the two pricing scenarios, we examine the interplay of supply diversification strategy and responsive pricing strategy in mitigating supply uncertainty. While both strategies are effective in mitigating supply uncertainty, we show that they are not necessarily substitutes. The relationship between these two strategies depends on two adverse effects caused by supply uncertainty: the lost‐revenue effect and the lost‐goodwill effect. More specifically, when the lost‐revenue effect dominates the lost‐goodwill effect, these two strategies are complements; otherwise, they are substitutes. Furthermore, we examine the impact of market size, price sensitivity, supplier reliability, and failure rebate on the interplay between these two strategies, and discuss the implications of our results. Finally, we extend our analysis to the case of two unreliable suppliers and show that the insights regarding the interplay between diversification and pricing continue to hold.

This thought piece represents an opportunity to integrate creativity and operations management (OM) research, and in particular the management of technology (MOT), to stimulate thinking and drive research across disciplines. Specifically, we discuss how there is an inherent tension when considering how work is organized and performed given that the majority of today's jobs require a certain degree of following routinized procedures, while some level of creativity is desirable as well. Therefore, there is the need to balance standardization with the desire for creativity, and this represents an inherent paradox. Here, we propose applying a creativity lens to the work categories used in OM, and discuss the implications of considering creativity as a process and an outcome that ranges along a continuum from incremental to radical. Our goal is to start a conversation that integrates the organizational creativity literature with OM and the MOT, and in doing so leads to future research and new developments in each of these literatures.

During the last 25 years, the ecosystem of knowledge creation and dissemination in operations and supply chain management has improved remarkably. We now see OM as a vibrant community and an ecosystem in steady state. Yet, there are many opportunities ahead to revitalize our field and to expand our influence. In the spirit of continuous improvement, we propose that we focus our major efforts on accelerating the following four developments: First, having greatly expanded the domain of operations management, we should continue to expand its boundaries. Second, after a visible increase in exploratory studies, our community should accelerate our pursuit of such research. Third, we encourage OM faculty to develop programs that enable Ph.D. students to carry out part of their work in actual organizational settings. Fourth, we should further strengthen our interactions with the business community and create mechanisms to systematically disseminate our research to its members.

We consider a system in which two competing servers provide customer‐intensive services and the service reward is affected by the length of service time. The customers are boundedly rational and choose their service providers according to a logit model. We demonstrate that the service provider revenue function is unimodal in the service rate, its decision variable, and show that the service rate competition has a unique and stable equilibrium. We then study the price decision under three scenarios with the price determined by a revenue‐maximizing firm, a welfare‐maximizing social planner, or two servers in competition. We find that the socially optimal price, subject to the requirement that the customer actual utility must be non‐negative, is always lower than the competition equilibrium price which, in turn, is lower than the revenue‐maximizing monopoly price. However, if the customer actual utility is allowed to be negative in social optimization, the socially optimal price can be higher than the other two prices in a large market.

Can peer‐to‐peer (P2P) marketplaces benefit traditional supply chains when consumers may experience valuation risk? P2P marketplaces can mitigate consumers' risk by allowing them to trade mismatched goods; yet, they also impose a threat to retailers and their suppliers as they compete over consumers. Further, do profit‐maximizing marketplaces always extract the entire consumer surplus from the online trades? Our two‐period model highlights the effects introduced by P2P marketplaces while accounting for the platform's pricing decisions. We prove that with low product unit cost, the P2P marketplace sets its transaction fee to the market clearing price, thereby extracting all of the seller surplus. In this range of product unit cost, the supply chain partners are worse off due to the emergence of a P2P marketplace. However, when the unit cost is high, the platform sets its transaction fee to be less than the market clearing price, intentionally leaving money on the table, as a mechanism to stimulate first period demand for new goods in expectation for some of them to be traded later, in the second period, via the marketplace. It is not until the surplus left with the sellers is sufficiently high that the supply chain partners manage to extract some of this surplus, ultimately making them better off due to a P2P marketplace. We further analyze the impact of a P2P marketplace on consumer surplus and social welfare. In addition, we consider model variants accounting for a frictionless platform and consumer strategic waiting.