Recognition of overlap graphs

Overlap graphs occur in computational biology and computer science, and have applications in genome sequencing, string compression, and machine scheduling. Given two strings \(s_{i}\) and \(s_{j}\) , their overlap string is defined as the longest string \(v\) such that \(s_{i} = uv\) and \(s_{j} = vw\) , for some non empty strings \(u,w\) , and its length is called the overlap between these two strings. A weighted directed graph is an overlap graph if there exists a set of strings with one-to-one correspondence to the vertices of the graph, such that each arc weight in the graph equals the overlap between the corresponding strings. In this paper, we characterize the class of overlap graphs, and we present a polynomial time recognition algorithm as a direct consequence. Given a weighted directed graph \(G\) , the algorithm constructs a set of strings that has \(G\) as its overlap graph, or decides that this is not possible.     

Role of Random Capacity Risk and the Retailer in Decentralized Supply Chains with Competing Suppliers

This research considers a supply chain under the following conditions: (i) two heterogeneous suppliers are in competition, (ii) supply capacity is random and pricing is endogenous, (iii) consumer demand, with and without an intermediate retailer, is price dependent. Specifically, we examine how uncertainty in supply capacity affects optimal ordering and pricing decisions, supplier and retailer profits, and the incentives to reduce such uncertainty. When two suppliers sell through a monopolistic retailer, supply uncertainty not only affects the retailer's diversification strategy for replenishment, but also changes the suppliers’ wholesale price competition and the incentive for reducing capacity uncertainty. In this dual‐sourcing model, we show that the benefit of reducing capacity uncertainty depends on the cost heterogeneity between the suppliers. In addition, we show that a supplier does not necessarily benefit from capacity variability reduction. We contrast this incentive misalignment with findings from the single‐supplier case and a supplier‐duopoly case where both suppliers sell directly to market without the monopolistic retailer. In the latter single‐supplier and duopoly cases, we prove that the unreliable supplier always benefits from reducing capacity variability. These results highlight the role of the retailer's diversification strategy in distorting a supplier's incentive for reducing capacity uncertainty under supplier price competition.     

Price Incentives and Coordination in a Two‐Product Decentralized Supply Chain

We investigate pricing incentives for competing retailers who distribute two variants of a manufacturer's product in a decentralized supply chain. Under a two‐dimensional Hotelling model, we derive decentralized retailers' prices for the products, and distortions in pricing when compared to centrally optimal prices. We show that price distortions decrease as consumers' travel cost between retailers increases, due to less intense competition. However, price distortions do not change monotonically in consumers' switching cost between products within stores. To fix decentralized retailers' price distortions, we construct a two‐part pricing contract that coordinates the supply chain. We show that the coordinating contract is Pareto‐improving and analyze increase in the supply chain profit under coordination.     

Partially Flexible Operating Rooms for Elective and Emergency Surgeries

In hospitals, the management of operating rooms faces a trade‐off between the need to be responsive to emergency surgeries and to conduct scheduled elective surgeries efficiently. Operating rooms can be configured as flexible and handle both electives and emergencies, or as dedicated to focus on either electives or emergencies. With flexible rooms, the prioritization of emergencies over scheduled electives can lead to schedule disruptions. Focused rooms can lead to imbalances between capacity and surgery workload. Whereas hospital administrators typically handle this trade‐off by employing either flexible rooms (complete flexibility) or dedicated rooms (complete focus), we investigate whether a combination of flexible and dedicated rooms (partial flexibility) could be a preferable alternative. The ensuing question is what is the right combination of flexible and dedicated rooms? A versatile simulation model is developed to evaluate different resource allocation policies under various environmental parameters and performance metrics, including patient wait time, staff overtime, and operating room utilization. The main result is that partial flexibility configurations outperform both complete flexibility and complete focus policies by providing solutions with improved values of expected wait time for both emergency and elective patients.     

Defining Problems Fast and Slow: The U‐shaped Effect of Problem Definition Time on Project Duration

This study examines how time spent in problem definition affects problem solving in projects such as Six Sigma projects. Our hypotheses are tested using data collected from 1558 Six Sigma projects in a company. The results show evidence of a U‐shaped relationship between the amount of time spent in the Define phase and project duration. This finding suggests that spending too little time on problem definition potentially causes poor problem formulation, which leads to deficient problem solving and lengthens overall project time. On the other hand, too much time spent on problem definition can lead to unneeded delays in project completion due to diminishing returns on problem definition efforts. Furthermore, the optimal balance between spending too little and too much time depends on prior project experience and project complexity. Prior project experience reduced project completion time and weakened the U‐shaped effect. Conversely, complex projects took longer and appeared to show some evidence of a stronger U‐shaped effect; this suggests balancing the time spent in the Define phase was more challenging for complex projects. Our study also underscores the importance of managing project duration, as projects that were completed faster tended to be associated with higher project savings.     

Linking Process Quality and Resource Usage: An Empirical Analysis

Motivated by an increasing adoption of evidence‐based medical guidelines in the delivery of medical care, we examine whether increased adherence to such guidelines (typically referred to as higher process quality) is associated with reduced resource usage in the course of patient treatment. In this study, we develop a sample of US hospitals and use cardiac care as our context to empirically examine our questions. To measure a patient's resource usage, we use the total length of stay, which includes any additional inpatient stay necessitated by unplanned readmissions within thirty days after initial hospitalization. We find evidence that higher process quality, and more specifically its clinical (as opposed to its administrative) dimensions, are associated with a reduction in resource usage. Moreover, the standardization of care that is achieved via the implementation of medical guidelines, makes this effect more pronounced in less focused environments: higher process quality is more beneficial when the cardiac department's patient population is distributed across a wider range of medical conditions. We explore the implications of these findings for process‐oriented pay‐for‐performance programs, which tie the reimbursement of hospitals to their adherence to evidence‐based medical guidelines.     

The Impact of Worker and Establishment‐level Characteristics on Male–Female Wage Differentials: Evidence from Danish Matched Employee–Employer Data

Abstract. This paper uses matched employer–employee data from Denmark to examine how gender segregation at the level of occupation, industry, establishment, and job‐cell impacts the gender wage differential of full‐time, private‐sector salaried and manual workers. Wage effects of gender segregation at the above four levels are estimated through fixed effects or through controls for the proportion females within these structures. We find that occupation has a much larger role than industry or establishment in accounting for the gender gap for salaried but not manual workers, and that for both groups there is a significant within‐job‐cell gender wage differential.     

Using the End‐User Computing Satisfaction (EUCS) Instrument to Measure Satisfaction with a Web Site

The purpose of this study is to revise and revalidate the End‐User Computing Satisfaction (EUCS) instrument to measure satisfaction with a Web site from a usability perspective. This study is especially important given the increased significance of the Web and the uniqueness of the Web as a computing environment. A total of 176 students participated in a lab simulation that involved a usability evaluation of the Lands' End Web site ( http://www.landsend.com ). Students were asked to complete a set of tasks, record their answers, and then complete the EUCS instrument. Confirmatory factor analysis and invariance analyses were conducted to test the reliability, validity, and generalizability of the revised EUCS. The results show that the EUCS is a valid and robust instrument in the Web environment but that one of the subfactors, timeliness, will need further refinement in the future. Usability practitioners can use the EUCS to measure end‐user satisfaction with a Web site and use the feedback for improving Web‐site design. We describe a case study of an actual usability application that utilized the revised EUCS effectively to support the design of building supply Web sites involving two types of end users, homeowners and contractors. We also propose a typology that researchers can use as a starting point to judge when it is necessary to revalidate an instrument like the EUCS. Finally, we discuss the limitations of our study and present avenues for future research.     

Managing Demand Risk in Tactical Supply Chain Planning for a Global Consumer Electronics Company

We consider the problem of managing demand risk in tactical supply chain planning for a particular global consumer electronics company. The company follows a deterministic replenishment‐and‐planning process despite considerable demand uncertainty. As a possible way to formally address uncertainty, we provide two risk measures, “demand‐at‐risk” (DaR) and “inventory‐at‐risk” (IaR) and two linear programming models to help manage demand uncertainty. The first model is deterministic and can be used to allocate the replenishment schedule from the plants among the customers as per the existing process. The other model is stochastic and can be used to determine the “ideal” replenishment request from the plants under demand uncertainty. The gap between the output of the two models as regards requested replenishment and the values of the risk measures can be used by the company to reallocate capacity among different products and to thus manage demand/inventory risk.