Operations & Supply Chain Management

This work examines the impact of discharge decisions under uncertainty in a capacity-constrained high risk setting: the intensive care unit (ICU). New arrivals to an ICU are typically very high priority patients and, should the ICU be full upon their arrival, discharging a patient currently residing in the ICU may be required to accommodate a newly admitted patient. Patients so discharged risk physiologic deterioration which might ultimately require readmission; models of these risks are currently unavailable to providers.

The fields of statistics and econometrics have developed powerful methods for testing the validity (specification) of a model based on its fit to underlying data. Unlike statisticians, managers are typically more interested in the performance of a decision rather than the statistical validity of the underlying model. We propose a framework and a statistical test that incorporates decision performance into a measure of statistical validity. Under general conditions on the objective function, asymptotic behavior of our test admits a sharp and simple characterization.

The authors test methods, based on cognitively simple decision rules, that predict which products consumers select for their consideration sets. Drawing on qualitative research, the authors propose disjunctions-of-conjunctions (DOC) decision rules that generalize well-studied decision models, such as disjunctive, conjunctive, lexicographic, and subset conjunctive rules. They propose two machine-learning methods to estimate cognitively simple DOC rules. They observe consumers' consideration sets for global positioning systems for both calibration and validation data.

Recent theoretical work predicts that an important margin of adjustment to deregulation or trade reforms is the reallocation of output within firms through changes in their product mix. Empirical work has accordingly shifted its focus towards multi-product firms and their product mix decisions. Existing studies have however focused exclusively on the U.S.

Economics is the study of how scarce resources are allocated. Operations research studies how to accomplish goals in the least costly manner. These fields have much to offer each other in terms of challenging problems that need to be solved and the techniques to solve them. This was the case after World War II, partly because the individuals who went on to be the leading scholars in economics and operations research worked together during WWII. In fact, the two fields share many early luminaries, including Arrow, Dantzig, Holt, Kantorovich, Koopmans, Modigliani, Scarf, and von Neumann.

Hospital ambulance diversions are prevalent and increasing nationwide as emergency departments experience growing congestion. Using negative binomial regressions, this paper links the number of acute myocardial infarction (AMI) deaths to the level and extent of diversion in the five boroughs of New York City. The results indicate that both high levels of ambulance diversion and simultaneous diversion across hospitals are associated with increasing numbers of deaths from AMI.

Automobile manufacturers in the U.S. supply chain exhibit significant differences in their days-of-supply of finished vehicles (average inventory divided by average daily sales rate). For example, from 1995 to 2004, Toyota consistently carried approximately 30 fewer days-of-supply than General Motors. This suggests that Toyota's well-documented advantage in manufacturing efficiency, product design and upstream supply chain management extends to their finished-goods inventory in their downstream supply chain from their assembly plants to their dealerships.

We study a capacity sizing problem in a service system that is modeled as a single-class queue with multiple servers and where customers may renege while waiting for service. A salient feature of the model is that the mean arrival rate of work is random (in practice this is a typical consequence of forecasting errors). The paper elucidates the impact of uncertainty on the nature of capacity prescriptions, and relates these to well established rules-of-thumb such as the square root safety staffing principle.