Modeling Demand For Unionization With Nontraditional Data Analysis Methods

Upon reviewing the extant literature on determinants of unionism, it becomes clear that many areas that have had a plethora of research attention do not converge upon singularly directional findings. This study explores a potential cause of such an apparent anomaly: nonlinearity of data. An exploratory examination of correlation coefficients among typical union determinant variables seems to show different patterns of relationships at different levels of union demand. Thus, a break from traditional linear data analysis techniques is explored in the interest of explaining more variance with typical, theoretically derived variables by using neural network analysis. Results of analyses on industry level data reveal that using neural network analysis to model union demand explained over four times as much variance as multiple regression analysis.     

A PROFIT-MAXIMIZATION MODEL FOR A RETAILER'S STOCKING DECISIONS ON PRODUCTS SUBJECT TO SUDDEN OBSOLESCENCE

A product has been formally denned as being subject to sudden obsolescence if its lifetime is negative exponentially distributed. Using an approximate model, Masters suggested that the traditional method of incorporating obsolescence cost as a component of inventory holding costs in the economic order quantity (EOQ) model was appropriate-for products subject to sudden obsolescence, provided that the obsolescence cost component was computed properly. Unfortunately, current practice of the EOQ model seriously underestimates the costs of sudden obsolescence. An exact model demonstrating that Masters' model also underestimated true lifetime costs and overestimated the optimal order quantity has been presented. Neither of these models addressed quantity discounts. Furthermore, with their cost-minimization focus, these models fail to identify situations when minimized costs exceed expected revenues. We extend Joglekar and Lee's model to focus on maximizing profits, rather than minimizing costs. This model answers such questions as whether to stock the product at all, whether to accept a quantity discount offer, and what order quantity to use. Numerical examples and sensitivity analyses suggest that Masters' model provides a significant improvement over the traditional model in moving toward true optimality. However, they also illustrate situations where both the traditional and the Masters' model accept a quantity discount that deserves to be rejected and stock a product that should not be stocked. In such situations, it seems important that a retailer uses the profit-maximization model presented here.     

An Evaluation of Capacity Sensitive Order Review and Release Procedures in Job Shops

We investigate the performance of capacity-sensitive order review and release (ORR) procedures in job shop environments that have not been previously explored. Previous research has ignored the case of job shops which must perform to very tight due-dates because of time-sensitive customers. We propose and test a new capacity sensitive ORR procedure called path based bottleneck (PBB) in such environments, along with the modified infinite loading (MIL) procedure which has been shown to work well in several studies. We compare the performance of these two controlled release rules with that of immediate release rule under different conditions of capacity utilization and customer specified exogenous duedates. Our results indicate that PBB performs well in lowering total costs when due-dates are tight, while MIL is a better procedure with relatively loose to medium due-dates. We also show that in many cases, the shortest processing time (SPT) dispatching rule is a superior performer than a due-date based rule like critical ratio (CR); a conclusion which is contrary to the existing research in this area. In addition, the shop floor control policies recommended are shown to be sensitive to the cost structure of the firm. The managerial implications of this research in providing effective shop floor control in job shops operating under tight due-date conditions are also discussed.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

Risk attitudes and digit ratio (2D:4D): Evidence from prospect theory

Journal of Risk and Uncertainty - Prenatal androgens have organizational effects on brain and endocrine system development, which may have a partial impact on economic decisions. Numerous studies...     

Capturing temporal dynamics of fear behaviors on a moment‐to‐moment basis

Identifying patterns of fearful behaviors early and accurately is essential to identify children who may be at increased risk for psychopathology. Previous work focused on the total amount of fear by using composites across time. However, considering the temporal dynamics of fear expression might offer novel insights into the identification of children at risk. One hundred and twenty‐five toddlers participated in high‐ and low‐fear tasks. Data were modeled using a novel two‐step approach. First, a hidden Markov model estimated latent fear states and transitions across states over time. Results revealed children's behavior was best represented by six behavioral states. Next, these states were analyzed using sequence clustering to identify groups of children with similar dynamic trajectories through the states. A four‐cluster solution found groups of children varied in fear response and regulation process: “external regulators” (using the caregiver as a regulation tool), “low reactive” (low reaction to stimulus), “fearful explorers” (managing their own internal state with minimal assistance from the caregiver), and “high fear” (fearful/at‐caregiver state regardless of task). The combination of analytic tools enabled fine‐grained examination of the processes of fearful temperament. These insights may help prevention programs target behaviors that perpetuate anxious behavior in the moment.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.     

The Popular Kids Don't Matter: Centrality and Influence on Adolescent Behavior

This study examines the widely held belief that socially central individuals are disproportionately influential in their networks. Using data from the National Longitudinal Study of Adolescent Health, it models the association between four behavioral outcomes and two distinct specifications of the behaviors' relationship to network prominence. This study finds little evidence that sociometrically central individuals are more influential than randomly chosen peers from the same network when predicting drinking, smoking, and sports participation. Students resemble their peers in systematic ways, but it is unlikely that this is because central students serve as a reference for the group or because students adjust their actions based on the social rewards that they observe given their position in a social network.     

Methods for spatial and temporal land use and land cover assessment for urban ecosystems and application in the greater Baltimore-Chesapeake region

Understanding contemporary urban landscapes requires multiple sets of spatially and temporally compatible data that can integrate historical land use patterns and disturbances to land cover. This paper presents three principal methods: (1) core analysis; (2) historic mapping; and (3) gradient analysis, to link spatial and temporal data for urban ecosystems and applies their use in the Baltimore-Chesapeake region. Paleoecological evidence derived from the geochronology of sediment cores provides data on long-term as well as recent changes in vegetative land cover. This information, combined with contemporary vegetation maps, provides a baseline for conducting trend analyses to evaluate urbanization of the landscape. A 200-year historical land use database created from historical maps, census data, and remotely sensed data provides a spatial framework for investigating human impacts on the region. A geographic information system (GIS) integrates core analyses with historic data on land use change to yield a comprehensive land use and land cover framework and rates of change. These data resources establish the regional foundation for investigating the ecological components of an urban ecosystem. Urban-rural gradient analyses and patch analyses are proposed as the most appropriate methods for studying the urban ecosystem as they link ecological and social patterns and processes for varying degrees of urbanization.     

Stigmatized Identities: Too Muslim to Be American,Too American to Be Muslim

In the United States today, Muslim identity is highly stigmatized. Much of this can be attributed to an increasing climate of Islamophobia. The current study finds that some Muslim Americans are confronted with another source of stigma: other Muslims. Using interview data with 23 Muslim Americans in and around Houston, TX, this study examines the intersection of religious out‐group and in‐group stigma in the lives of Muslim Americans. Findings suggest that stigma comes not only from non‐Muslims, but also from other Muslims. Some Muslim Americans are especially vulnerable to religious in‐group stigma. Those who are most acculturated to non‐Muslim, Western culture often face criticism from Muslim communities, be they inside or outside the United States. These Muslim Americans find that they are not perceived as fully Muslim or fully American, and therefore denied the full benefits of either status while simultaneously bearing the burden of both. This paper articulates the multiple dimensions of stigma faced by Muslims in America.