Knowledge that Transforms

We experimentally study the role of reputation in procurement using two common mechanisms: price‐based and buyer‐determined auctions. While buyers are bound to buy from the lowest bidder in price‐based auctions, they can choose between bidders in buyer‐determined auctions. Only the latter buyers can consider the reputation of bidders. We find that bidders supply higher quality in buyer‐determined auctions leading to higher market efficiencies in these auctions. Accordingly, buyers prefer the buyer‐determined auction over the price‐based auction, while only half of the bidders do so. A more detailed analysis of buyers' and bidders' behavior and profits provides insights into their mechanism choice.

We consider a system of two service providers each with a separate queue. Customers choose one queue to join upon arrival and can switch between queues in real time before entering service to maximize their spot utility, which is a function of price and queue length. We characterize the steady‐state distribution for queue lengths, and then investigate a two‐stage game in which the two service providers first simultaneously select service rates and then simultaneously charge prices. Our results indicate that neither service provider will have both a faster service and a lower price than its competitor. When price plays a less significant role in customers’ service selection relative to queue length or when the two service providers incur comparable costs for building capacities, they will not engage in price competition. When price plays a significant role and the capacity costs at the service providers sufficiently differ, they will adopt substitutable competition instruments: the lower cost service provider will build a faster service and the higher cost service provider will charge a lower price. Comparing our results to those in the existing literature, we find that the service providers invest in lower service rates, engage in less intense price competition, and earn higher profits, while customers wait in line longer when they are unable to infer service rates and are naive in service selection than when they can infer service rates to make sophisticated choices. The customers’ jockeying behavior further lowers the service providers’ capacity investment and lengthens the customers’ duration of stay.

We study a hybrid push–pull production system with a two‐stage manufacturing process, which builds and stocks tested components for just‐in‐time configuration of the final product when a specific customer order is received. The first production stage (fabrication) is a push process where parts are replenished, tested, and assembled into components according to product‐level build plans. The component inventory is kept in stock ready for the final assembly of the end products. The second production stage (fulfillment) is a pull‐based assemble‐to‐order process where the final assembly process is initiated when a customer order is received and no finished goods inventory is kept for end products. One important planning issue is to find the right trade‐off between capacity utilization and inventory cost reduction that strives to meet the quarter‐end peak demand. We present a nonlinear optimization model to minimize the total inventory cost subject to the service level constraints and the production capacity constraints. This results in a convex program with linear constraints. An efficient algorithm using decomposition is developed for solving the nonlinear optimization problem. Numerical results are presented to show the performance improvements achieved by the optimized solutions along with managerial insights provided.

Supply contracts are used to coordinate the activities of the supply chain partners. In many industries, service level‐based supply contracts are commonly used. Under such a contract, a company agrees to achieve a certain service level and to pay a financial penalty if it misses it. The service level used in our study refers to the fraction of a manufacturer's demand filled by the supplier. We analyze two types of service level‐based supply contracts that are designed by a manufacturer and offered to a supplier. The first type of contract is a flat penalty contract, under which the supplier pays a fixed penalty to the manufacturer in each period in which the contract service level is not achieved. The second type of contract is a unit penalty contract, under which a penalty is due for each unit delivered fewer than specified by the parameters of the contract. We show how the supplier responds to the contracts and how the contract parameters can be chosen, such that the supply chain is coordinated. We also derive structural results about optimal values of the contract parameters, provide numerical results, and connect our service level measures to traditional service level measures. The results of our analyses can be used by decision makers to design optimal service level contracts and to provide them with a solid foundation for contract negotiations.

Many people in developing countries do not have access to effective vaccines, medicines, and other life‐saving health technologies. Shortage of health care workers, severe financial constraints, and lack of awareness are some of the major obstacles that prevent higher access. However, ineffective and poorly designed supply chains for purchasing and distributing the medicines, vaccines, and health technologies are one of the most important barriers to increasing access. We argue that the ineffectiveness of the global health supply chain can be attributed largely to: coordination problems across multiple stakeholders with widely divergent objectives, lack of careful supply chain design, and use of myopic operational objectives and metrics. The operations management research community can contribute to improving this by applying existing knowledge to the field of global health delivery and by researching new frameworks of analysis which would then become the cornerstones for policy advice to those who design, operate, or finance these supply chains.

We study the stock market reaction to announcements of global green vehicle innovation over a 14‐year time span (1996–2009) using the event study methodology. We document that the stock market generally reacts positively to automakers' announcements of environmental innovations, consistent with prior research on the wealth effects of innovation announcements. Our results indicate that crucial green product development decisions such as innovation type and market segment choices exert direct influence on a firm's market value. These results hold after controlling for firm size, leverage, profitability, R&D intensity, and oil price changes.

Protecting throughput from variance is the key to achieving lean. Workload control (WLC) accomplishes this in complex make‐to‐order job shops by controlling lead times, capacity, and work‐in‐process (WIP). However, the concept has been dismissed by many authors who believe its order release mechanism reduces the effectiveness of shop floor dispatching and increases work center idleness, thereby also increasing job tardiness results. We show that these problems have been overcome. A WLC order release method known as “LUMS OR” (Lancaster University Management School order release) combines continuous with periodic release, allowing the release of work to be triggered between periodic releases if a work center is starving. This paper refines the method based on the literature (creating “LUMS COR” [Lancaster University Management School corrected order release]) before comparing its performance against the best‐performing purely periodic and continuous release rules across a range of flow directions, from the pure job shop to the general flow shop. Results demonstrate that LUMS COR and the continuous WLC release methods consistently outperform purely periodic release and Constant WIP. LUMS COR is considered the best solution in practice due to its excellent performance and ease of implementation. Findings have significant implications for research and practice: throughput times and job tardiness results can be improved simultaneously and order release and dispatching rules can complement each other. Thus, WLC represents an effective means of implementing lean principles in a make‐to‐order context.

Slack can act as a double‐edged sword. While it can buffer against environmental threats to help ensure business continuity, slack can also be costly and reduce profitability. In this study we focus on operational slack, the form related to the firm's production processes. We investigate the role of operational slack on firm survival during its venture stage when its survival is significantly challenged by environmental threats. Specifically, we explore how change in three types of environmental uncertainty, namely dynamism, complexity, and lack of munificence, affect the relationship between operational slack and venture survival. Results suggest that with an increase in environmental uncertainty, operational slack lowers the likelihood of venture failure.

The problem of no‐shows (patients who do not arrive for scheduled appointments) is particularly significant for health care clinics, with reported no‐show rates varying widely from 3% to 80%. No‐shows reduce revenues and provider productivity, increase costs, and limit patient access by reducing effective clinic capacity. In this article, we construct a flexible appointment scheduling model to mitigate the detrimental effects of patient no‐shows, and develop a fast and effective solution procedure that constructs near‐optimal overbooked appointment schedules that balance the benefits of serving additional patients with the potential costs of patient waiting and clinic overtime. Computational results demonstrate the efficacy of our model and solution procedure, and connect our work to prior research in health care appointment scheduling.

Some retailers of seasonal products adopt weather‐conditional rebate programs to induce early sales and increase profits. In such promotions, customers who buy the product in an advance preselling period are offered rebates if a pre‐specified weather condition is realized during the later normal selling season. We investigate the potential benefits of these programs for retailers. We show that the weather‐conditional rebate program can increase sales by price discriminating among a customer's post‐purchase states. Taking advantage of the early sales, it can also reduce the inventory holding cost and ordering cost, and hence can increase the retailer's expected profits. In addition, we numerically investigate the sensitivity of the rebate program's effectiveness to the model parameters and illustrate its advantages over an advance‐discount policy.