Alcohol Use and Prior Substance Abuse Treatment in Relation to Gambling Problem Severity and Gambling Treatment Outcome

Recent research has made it clear that problematic gambling is often accompanied by problematic alcohol use. Unfortunately, little is known about the nature of this association, especially as it relates to gambling treatment outcome. The purpose of this study is to explore the effect of current alcohol use level and previous substance abuse treatment on the symptoms of a large cohort of pathological gamblers as well as on their response to treatment for pathological gambling. The sample included 464 men and 301 women recruited at six gambling treatment programs in Minnesota. Gambling treatment patients were assessed on a number of gambling problem severity and related clinical variables using the Gambling Treatment Outcome Monitoring System (GAMTOMS). Patients with frequent alcohol use had greater gambling involvement at baseline than infrequent alcohol users. Patients with a previous history of substance abuse treatment had more severe psychosocial problems, ostensibly resulting from their gambling behavior, than patients without past substance abuse treatment. A MANOVA with repeated measures showed that neither pretreatment alcohol use, nor past substance abuse treatment exerted significant effects on gambling treatment outcome. While the level of pretreatment alcohol use and a history of substance abuse treatment are markers for greater gambling problem severity, treatment outcome for pathological gambling was not adversely impacted by these variables.     

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.     

Mass Customization in the Automotive Industry: Comparing Interdealer Trading and Reconfiguration Flexibilities in Order Fulfillment

Mass customization has been viewed as desirable but difficult to achieve in the volume automotive sector. Here we consider flexibility in automotive order fulfillment systems to enhance the ability to satisfy customers with their desired vehicle variants within acceptable delivery lead times. Two types of flexibility are compared in a Virtual‐Build‐to‐Order system—reconfiguration in the planning pipeline and interdealer trading. A representative simulation model is used to investigate the impact of the two types of flexibility across a wide spectrum of product variety levels. The impacts on major stakeholders in the system—the producer, dealers, and customers—are considered. The study shows that both types of flexibilities can bring significant benefits in terms of reductions in lead time and inventory holding. The level of product variety strongly influences the observed effects—an important finding in the mass customization context. Upstream reconfiguration flexibility brings greater benefits than downstream trading flexibility. Reconfiguration tends to dominate trading as a fulfillment mechanism when both are in operation. The findings have implications for the design and management of automotive order fulfillment systems in improving their ability to offer mass customization. The study has relevance for companies in other sectors with high levels of variety that seek to combine efficiency, speed, and flexibility in order fulfillment.     

Strategies for Addressing the Nursing Shortage: Coordinated Decision Making and Workforce Flexibility

In this article, we present strategies to help combat the U.S. nursing shortage. Key considerations include providing an attractive work schedule and work environment—critical issues for retaining existing nurses and attracting new nurses to the profession—while at the same time using the set of available nurses as effectively as possible. Based on these ideas, we develop a model that takes advantage of coordinated decision making when managing a flexible workforce. The model coordinates scheduling, schedule adjustment, and agency nurse decisions across various nurse labor pools, each of differing flexibility levels, capabilities, and costs, allowing a much more desirable schedule to be constructed. Our primary findings regarding coordinated decision making and how it can be used to help address the nursing shortage include (i) labor costs can be reduced substantially because, without coordination, labor costs on average are 16.3% higher based on an actual hospital setting, leading to the availability of additional funds for retaining and attracting nurses, (ii) simultaneous to this reduction in costs, more attractive schedules can be provided to the nurses in terms of less overtime and fewer undesirable shifts, and (iii) the use of agency nurses can help avoid overtime for permanent staff with only a 0.7% increase in staffing costs. In addition, we estimate the cost of the shortage for a typical U.S. hospital from a labor cost perspective and show how that cost can be reduced when managers coordinate.     

Development of a Dose‐Response Model for SARS Coronavirus

In order to develop a dose‐response model for SARS coronavirus (SARS‐CoV), the pooled data sets for infection of transgenic mice susceptible to SARS‐CoV and infection of mice with murine hepatitis virus strain 1, which may be a clinically relevant model of SARS, were fit to beta‐Poisson and exponential models with the maximum likelihood method. The exponential model (k= 4.1 × l0²) could describe the dose‐response relationship of the pooled data sets. The beta‐Poisson model did not provide a statistically significant improvement in fit. With the exponential model, the infectivity of SARS‐CoV was calculated and compared with those of other coronaviruses. The does of SARS‐CoV corresponding to 10% and 50% responses (illness) were estimated at 43 and 280 PFU, respectively. Its estimated infectivity was comparable to that of HCoV‐229E, known as an agent of human common cold, and also similar to those of some animal coronaviruses belonging to the same genetic group. Moreover, the exponential model was applied to the analysis of the epidemiological data of SARS outbreak that occurred at an apartment complex in Hong Kong in 2003. The estimated dose of SARS‐CoV for apartment residents during the outbreak, which was back‐calculated from the reported number of cases, ranged from 16 to 160 PFU/person, depending on the floor. The exponential model developed here is the sole dose‐response model for SARS‐CoV at the present and would enable us to understand the possibility for reemergence of SARS.     

The Potential for Cannibalization of New Products Sales by Remanufactured Products*

The potential for cannibalization of new product sales by remanufactured versions of the same product is a central issue in the continuing development of closed‐loop supply chains. Practitioners have no fact‐based information to guide practice at firms and academics have no studies available to use as the basis for assumptions in models. We address the cannibalization issue by using auctions to determine consumers’ willingness to pay (WTP) for both new and remanufactured products. The auctions also allow us to better understand the potential impact of offering new and remanufactured products at the same time, which provides us insights into the potential for new product cannibalization. Our results indicate that, for the consumer and commercial products auctioned, there is a clear difference in WTP) for new and remanufactured goods. For the consumer product, there is scant overlap in bidders between the new and remanufactured products, leading us to conclude that the risk of cannibalization in this case is minimal. For the commercial product, there is evidence of overlap in bidding behavior, exposing the potential for cannibalization.     

Temptation and Taxation

We study optimal taxation when consumers have temptation and self‐control problems. Embedding the class of preferences developed by Gul and Pesendorfer into a standard macroeconomic setting, we first prove, in a two‐period model, that the optimal policy is to subsidize savings when consumers are tempted by “excessive” impatience. The savings subsidy improves welfare because it makes succumbing to temptation less attractive. We then study an economy with a long but finite horizon which nests, as a special case, the Phelps–Pollak–Laibson multiple‐selves model (thereby providing guidance on how to evaluate welfare in this model). We prove that when period utility is logarithmic, the optimal savings subsidies increase over time for any finite horizon. Moreover, as the horizon grows large, the optimal policy prescribes a constant subsidy, in contrast to the well known Chamley–Judd result.     

How Does Product Recovery Affect Quality Choice?

We study the impact of product recovery on a firm's product quality choice, where quality is defined as an observable performance measure that increases a consumer's valuation for the product. We consider three general forms of product recovery: (i) when product recovery reuses (after reprocessing) quality inducing components or material (e.g., remanufacturing), (ii) when product recovery does not reuse quality inducing components or material but it is overall profitable (e.g., cell phone recycling), and (iii) when product recovery is costly (but mandated by legislation, e.g., recycling of small appliances in the European Union). Using a stylized economic model, we show that the form of product recovery, recovery cost structure, and the presence of product take‐back legislation play an important role in quality choice. Generally speaking, product recovery increases the firm's quality choice, except for some instances of recovery form (ii). In addition, we find that product take‐back legislation can lead to higher quality choice as opposed to voluntary take‐back. We further demonstrate that both the firm and the consumers benefit from recovery form (ii), while both are worse off with recovery form (iii). However, environmental implications of the three recovery modes differ from their impact on consumer surplus and firm profit. While recovery forms (i) and (iii) reduce consumption and increase environmental benefits, the same is not true with recovery form (ii), which can increase consumption, potentially resulting in higher environmental impact.     

Fixed‐Effects Dynamic Panel Models,a Factor Analytical Method

We consider the estimation of dynamic panel data models in the presence of incidental parameters in both dimensions: individual fixed‐effects and time fixed‐effects, as well as incidental parameters in the variances. We adopt the factor analytical approach by estimating the sample variance of individual effects rather than the effects themselves. In the presence of cross‐sectional heteroskedasticity, the factor method estimates the average of the cross‐sectional variances instead of the individual variances. The method thereby eliminates the incidental‐parameter problem in the means and in the variances over the cross‐sectional dimension. We further show that estimating the time effects and heteroskedasticities in the time dimension does not lead to the incidental‐parameter bias even when T and N are comparable. Moreover, efficient and robust estimation is obtained by jointly estimating heteroskedasticities.