Two-Group Classification Using Neural Networks*

Artificial neural networks are new methods for classification. We investigate two important issues in building neural network models; network architecture and size of training samples. Experiments were designed and carried out on two-group classification problems to find answers to these model building questions. The first experiment deals with selection of architecture and sample size for different classification problems. Results show that choice of architecture and choice of sample size depend on the objective: to maximize the classification rate of training samples, or to maximize the generalizability of neural networks. The second experiment compares neural network models with classical models such as linear discriminant analysis and quadratic discriminant analysis, and nonparametric methods such as k-nearest-neighbor and linear programming. Results show that neural networks are comparable to, if not better than, these other methods in terms of classification rates in the training samples but not in the test samples.     

Master Scheduling in Assemble-To-Order Environments: A Capacitated Multiobjective Lot-Sizing Model

Basic characteristics of an assemble-to-order environment make effective master scheduling extremely difficult. Limited resource capacities and dynamic customer end-item demand contribute to the complexity of the master production scheduling problem. To gain flexibility and responsiveness within this system, the master production schedule (MPS) focuses at the component level. This research proposes a master scheduling technique for manufactured components which combines a multiobjective capacitated multi-item/multi-stage lot-sizing model with an interactive multiple objective optimization solution procedure. To evaluate the model's performance as a realistic and practical master scheduling tool, this study focuses on the National Cash Register (NCR) electronics manufacturing facility in Columbia, South Carolina.     

Marketing Communication Intensity Across Industries

Marketing communication intensity (i.e., the ratio of advertising and promotional expenditures to sales) has been an important topic for both business managers and academics. Here, we investigate cross-sectional and time-series variation of communication intensity due to: type of offering (product versus service) and type of market (consumer versus industrial). Overall, we find that both of these factors affect variation of communication intensity across industries and over time. However, the effect of market type is much more dramatic than the effect of offering type. Such knowledge about patterns in communication intensity levels helps managers make decisions about how much to spend on advertising and promotion.     

The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers: A Comment*

Joglekar and Tharthare [6] presented an alternate approach for minimizing total inventory carrying and ordering costs of a vendor and the purchaser(s). This approach permits the vendor and the purchaser(s) to rationally select their operating policies. Joglekar and Tharthare claimed that their approach is more economical than the joint lot-size approach. In this note we identify some conceptual issues in their approach and demonstrate the superiority of the joint lot-size approach with the help of an example.     

ANALYSIS OF ALTERNATIVE SCHEDULING POLICIES FOR HOSPITAL NURSES

The persistent shortage of nurses adversely affects the productivity, quality of care, and operating costs in most acute care hospitals. Aggravating the shortage are high nurse turnover rates, approaching 200% in some institutions. Policies to ensure adequate staffing levels and provide more attractive work schedules are alleged to improve nurse retention. However, their cost is seldom discussed. We compared expected nursing expense and workforce requirements to staff eight medical and surgical nursing units of a large hospital for 1 month, under 12 different scheduling policies alleged to improve turnover. Using simulation and an integrated staffing and scheduling methodology, we found that the expected nursing wages and workforce requirements for some policies differed by as much as 33%. In this hospital, the expected labor costs for certain policies could erode the benefits expected from improved retention. In contrast, other policies appear to allow high utilization of nursing resources, enhancing the expected benefits of reduced turnover with significant reductions in expenses for labor, recruiting, training, and fringe benefits.     

Discretionary Use of Computers: An Empirically Derived Explanatory Model*

This study identifies variables that explain variations in computer use. Factor analysis of data gathered from 422 business administration faculty reveal eight themes among the independent variables. Seven of these factors significantly discriminate among non, minimal, and high users. These results suggest an empirical model for future studies and provide policy insights for decision makers seeking to stimulate computer usage. Additionally, the study shows that there is much commonality between the previously separate organizational innovation and information systems implementation streams. It also demonstrates that motivation theory may be a valid framework within which to study computer use.     

When Restrictive Constraints Are Nonbinding: Illustrations and Implications

For convex and concave mathematical programs restrictive constraints (i.e., their deletion would change the optimum) will always be binding at the optimum, and vice versa. Less well-known is the fact that this property does not hold more generally, even for problems with convex feasible sets. This paper demonstrates the latter fact using numerical illustrations of common classes of problems. It then discusses the implications for public policy analysis, econometric estimation, and solution algorithms.     

Factors enhancing adaptive coping and mental health in lesbian youth: a review of the literature

Mental health practitioners who find themselves working with lesbian youth have a limited knowledge base by which to guide them in the helping process. This article explores, examines, and synthesizes current literature in an attempt to uncover factors that serve to enhance adaptive coping strategies for lesbian youth.     

Foreign-born emigration: A new approach and estimates based on matched CPS files

The utility of postcensal population estimates depends on the adequate measurement of four major components of demographic change: fertility, mortality, immigration, and emigration. Of the four components, emigration, especially of the foreign-born, has proved the most difficult to gauge. Without "direct" methods (i.e., methods identifying who emigrates and when), demographers have relied on indirect approaches, such as residual methods. Residual estimates, however are sensitive to inaccuracies in their constituent parts and are particularly ill-suited for measuring the emigration of recent arrivals. Here we introduce a new method for estimating foreign-born emigration that takes advantage of the sample design of the Current Population Survey (CPS): repeated interviews of persons in the same housing units over a period of 16 months. Individuals appearing in a first March Supplement to the CPS but not the next include those who died in the intervening year, those who moved within the country, and those who emigrated. We use statistical methods to estimate the proportion of emigrants among those not present in the follow-up interview. Our method produces emigration estimates that are comparable to those from residual methods in the case of longer-term residents (immigrants who arrived more than 10 years ago), but yields higher--and what appear to be more accurate--estimates for recent arrivals. Although somewhat constrained by sample size, we also generate estimates by age, sex, region of birth, and duration of residence in the United States.