The Effect of Lead Time Uncertainty on Safety Stocks

The pressure to reduce inventory investments in supply chains has increased as competition expands and product variety grows. Managers are looking for areas they can improve to reduce inventories without hurting the level of service provided. Two areas that managers focus on are the reduction of the replenishment lead time from suppliers and the variability of this lead time. The normal approximation of lead time demand distribution indicates that both actions reduce inventories for cycle service levels above 50%. The normal approximation also indicates that reducing lead time variability tends to have a greater impact than reducing lead times, especially when lead time variability is large. We build on the work of Eppen and Martin (1988) to show that the conclusions from the normal approximation are flawed, especially in the range of service levels where most companies operate. We show the existence of a service‐level threshold greater than 50% below which reorder points increase with a decrease in lead time variability. Thus, for a firm operating just below this threshold, reducing lead times decreases reorder points, whereas reducing lead time variability increases reorder points. For firms operating at these service levels, decreasing lead time is the right lever if they want to cut inventories, not reducing lead time variability.     

The Role of Clinical and Process Quality in Achieving Patient Satisfaction in Hospitals

Managers constantly struggle with where to allocate their resources and efforts in managing the complex service delivery system called a hospital. In the broadest sense, their decisions and actions focus on two important aspects of health care—clinical or technical medical care that emphasizes “what” the patient receives and process performance that emphasizes “how” health care services are delivered to patients. Here, we investigate the role of leadership, clinical quality, and process quality on patient satisfaction. A causal model is hypothesized and evaluated using structural equation modeling for a sample of 202 U.S. hospitals. Statistical results support the idea that leadership is a good exogenous construct and that clinical and process quality are good intermediate outcomes in determining patient satisfaction. Statistical results also suggest that hospital leadership has more influence on process quality than on clinical quality, which is predominantly the doctors' domain. Other results are discussed, such as that hospital managers must be mindful of the fact that process quality is at least as important as clinical quality in predicting patient satisfaction. The article concludes by proposing areas for future research.     

On the Rank-Based Selection Strategy for the Group Interview Problem*

For the so-called group interview problem in which several groups of choice alternatives are presented sequentially to the decision maker, the optimal selection strategy is derived that minimizes the expected rank of the selected choice or purchased product. For the case in which the sequence of groups can be rearranged by the decision maker, a simple heuristic procedure is proposed for obtaining a near-optimal sequence of groups, and the performance of the heuristic procedure in a Monte Carlo simulation is accessed. According to the heuristic procedure, the consumer is advised to visit smaller stores first and then move to larger stores later to increase the likelihood of finding a better product. Finally, the optimal selection strategy and the heuristic procedure are compared with those proposed by Chun, Moskowitz, and Plante (1993) and the problem of locating a new store in an area where there are several competing stores is discussed. The optimal selection strategy and the heuristic procedure can be applied to many sequential decision problems such as the consumer search and purchase process.     

Business patterns within telecommunications

The global telecommunications changed from a number of co-operating national monopolies offering a restricted range of services to a competitive, growing market with players of many types and sizes, offering a large range of services. How can vertically integrated incumbents align themselves and their systems to best compete in this environment? Business patterns and enterprise modelling offer a tool to model a large organization as a number of smaller enterprises that can compete with and co-operate with smaller specialist players in the market. In order to identify enterprises, this paper proposes that there are only a limited number of types of enterprise (manufacturer, service supplier, reseller, that these enterprise types can only interact in a limited number of ways (component supply, aggregation supply, resell supply, trading, end-supply and commission). With the use of examples, this paper illustrates these types of enterprise and enterprise relationships, and how they can be combined to build both internal and external supply chains, and discusses some of the conclusions that can be drawn from this analysis.     

A Bicriterion Maximal Covering Location Formulation Which Considers the Satisfaction of Uncovered Demand

There have been many applications of the maximal covering location problem (MCLP). An underlying assumption of the MCLP is that demand not covered (i.e., not within a prespecified maximal distance of a facility) is not served. This may be an unrealistic assumption in many location planning scenarios, especially in the public sector. For example, in cases such as fire protection or ambulance service, calls not technically covered will still be serviced. The MCLP, however, does not consider the distances or travel times necessary to service such demand. This paper presents a bicriterion locational covering model which explicitly considers the travel distance or time necessary to service demand not within the maximal covering distance of a facility. The model may be used to generate noninferior (Pareto optimal) siting configurations which demonstrate the inherent trade-offs between a siting scheme designed to maximize total coverage and one designed to minimize total travel time for uncovered demand to reach its nearest facility. In addition, it is shown that for any particular weighting scheme on the two objectives, the problem can be solved as a p-median problem; a problem for which several efficient solution methods exist.     

Necessary and Sufficient Conditions of Unacceptable Solutions in LP Discriminant Analysis*

Characterization of unacceptable solutions for linear programming (LP) discriminant models have been discussed in the literature and the results presented so far are not satisfactory. This paper establishes necessary and sufficient conditions of unacceptable solutions for a number of LP models, addresses the practical implications of these conditions, and discusses the relationship between unacceptable solutions and multiple solutions.     

Solving the Classification Problem in Discriminant Analysis Via Linear and Nonlinear Programming Methods*

This paper demonstrates the feasibility of applying nonlinear programming methods to solve the classification problem in discriminant analysis. The application represents a useful extension of previously proposed linear programming-based solutions for discriminant analysis. The analysis of data obtained by conducting a Monte Carlo simulation experiment shows that these new procedures are promising. Future research that should promote application of the proposed methods for solving classification problems in a business decision-making environment is discussed.     

Development of a Prediction Model for Hospital Closure Using Financial Accounting Data*

Numerous research studies have examined the use of financial accounting data in the prediction of corporate bankruptcy. Partly due to a lack of available data, however, little work has been done in developing a closure prediction model specifically for hospitals. Using cost reports from the Health Care Financing Administration and a sample of 71 closed hospitals and a matched sample of 71 open hospitals, the current study examines the relationship between 21 financial accounting ratios and hospital closure. Univariate logit results indicate that hospital closure is significantly related to 17 of the 21 ratios one year prior to closure. Results are also presented using a multivariate model, and for the relationships two years prior to closure. The current study provides information helpful to users in identifying financial variables which may be important indicators of hospital closure.     

FIRM EXPANSION THROUGH FRANCHISING: A MODEL AND SOLUTION PROCEDURES

This paper presents a practical model for firm expansion through franchising. The model allows the possibility of opening both company-owned and franchised stores. The objective is to maximize the expected returns to the franchisor from both types of stores, subject to the total capital outlay budget and the excess capacity available at each warehouse. A relaxation for this problem is studied and a heuristic solution procedure that makes use of this relaxation is developed. Experimental results over a wide range of problem structures show this solution methodology to be very effective, with gaps between feasible solution values and upper bounds generally in the 0 to 1 percent range. An efficient branch-and-bound code also is developed. This code is tested on problems with up to 100 potential store locations and 20 regions. It is found to be at least two orders of magnitude faster than a state-of-the-art commercial integer programming package.