Knowledge that Transforms

This paper focuses on the proactive planning of a partial switch of a prescription (Rx) drug brand to over‐the‐counter (OTC) status within the former's patent‐protected life. The planning issues are whether and when to make this switch from the “single‐status” Rx drug phase to the “dual‐status” Rx+OTC phase with or without the grant of a 3‐year market exclusivity period for the OTC drug by the US Food and Drug Administration. We formulate an optimal control problem that leads to a two‐phase optimization problem with finite‐time horizon involving switching time‐dependent switching cost and terminal value. Applying a variational approach, we establish the conditions under which it can be optimal to make the partial switch. Counter to conventional thinking, the grant of market exclusivity is neither necessary nor sufficient for a partial switch before the Rx drug's patent expiry. Further, we show in a functionally specified model‐based illustration, involving varying combinations of plausible ratios of OTC and Rx version margins and potential market sizes, that denial of OTC market exclusivity can imply that the firm should advance rather than delay the partial switch, and yield greater savings for Rx drug consumers. Implications for pharmaceutical Rx–OTC switch planners and policymakers are discussed.

We analyze the dynamic strategic interactions between a manufacturer and a retailer in a decentralized distribution channel used to launch an innovative durable product (IDP). The underlying retail demand for the IDP is influenced by word‐of‐mouth from past adopters and follows a Bass‐type diffusion process. The word‐of‐mouth influence creates a trade‐off between immediate and future sales and profits, resulting in a multi‐period dynamic supply chain coordination problem. Our analysis shows that while in some environments, the manufacturer is better off with a far‐sighted retailer, there are also environments in which the manufacturer is better off with a myopic retailer. We characterize equilibrium dynamic pricing strategies and the resulting sales and profit trajectories. We demonstrate that revenue‐sharing contracts can coordinate the IDP's supply chain with both far‐sighted and myopic retailers throughout the entire planning horizon and arbitrarily allocate the channel profit.

This paper establishes a critically important positive role for operations management practices and financial hedging. We show that operations management decisions and financial hedging are intertwined, and we advance a framework that can identify their combined effects on investors' wealth. We show that: (a) firms (publicly traded corporations) will optimally hold adequate riskless working capital (e.g., cash) to minimize the cost of obtaining non‐financial inputs, and the magnitude of this cash holding depends on operating details, and (b) operations management and financial hedging can lower firms' cash requirements, and boost productivity, defined as the wealth created in the firm per dollar of invested capital. Productivity‐enhancing practices—by “freeing up” some of the firm's cash—can maximize the investors' wealth. We show that these results obtain because firms' contracts with many of the providers of non‐financial inputs are not traded, and because investors can invest not just in public corporations but also in businesses “outside the markets” (e.g., proprietorships, partnerships, and private equity).

We study a “Forecast‐Commitment” contract motivated by a manufacturer's desire to provide good service in the form of delivery commitments in exchange for reasonable forecasts and a purchase commitment from the customer. The customer provides a forecast for a future order and a guarantee to purchase a portion of it. In return, the supplier commits to satisfy some or all of the forecast. The supplier pays penalties for shortfalls of the commitment quantity from the forecast, and for shortfalls of the delivered quantity from the customer's final order (not exceeding the commitment quantity). These penalties allow differential service among customers. In Durango‐Cohen and Yano (2006), we analyzed the supplier's problem for a given customer forecast. In this paper, we analyze the customer's problem under symmetric information, both when the customer is honest and when he strategically orders more than his demand when doing so is advantageous. We show that the customer gains little from lying, so the supplier can use his control over the contract parameters to encourage honesty. When the customer is honest, the contract achieves (near‐)coordination of the supply chain in a great majority of instances, and thus provides both excellent performance and flexibility in structuring contracts.

A framework for the analysis of manufacturing systems operating under a production authorization card (PAC) system is outlined. The PAC system provides a single model, which encompasses a broad variety of control strategies, including Kanban and CONWIP. This paper describes a framework for the performance analysis and comparison of both specific and families of control strategies. The framework starts with system performance measures estimated by simulation. These simulations in turn provide training data for neural network metamodels. The metamodels allow for a variety of analysis and optimization approaches, including the construction of optimal policy curves, which can provide considerable insight into the systems under study.

Driven by market pressures, financial service firms are increasingly partnering with independent vendors to create service networks that deliver greater profits while ensuring high service quality. In the management of call center networks, these partnerships are common and form an integral part of the customer care and marketing strategies in the financial services industry. For a financial services firm, configuring such a call center service network entails determining which partners to select and how to distribute service requests among vendors, while incorporating their capabilities, costs, and revenue‐generating abilities. Motivated by a problem facing a Fortune 500 financial services provider, we develop and apply a novel mixed integer programming model for the service network configuration problem. Our tactical decision support model effectively accounts for the firm's costs by capturing the impact of service requirements on vendor staffing levels and seat requirements, and permits imposing call routing preferences and auxiliary service costs. We implemented the model and applied it to data from an industry partner. Results suggest that our approach can generate considerable cost savings and substantial additional revenues, while ensuring high service quality. Results based on test instances demonstrate similar savings and outperform two rule‐based methods for vendor assignment.