Lowering Inventory Systems Costs by Using Regression-Derived Estimators of Demand Variability*

Scientific techniques for inventory management typically are applied to systems containing many items. Such techniques require an estimation of the demand variance (and mean) of each item from historical data. This research demonstrates a significant potential for improvement in system cost performance from using least-squares regression fits of a variance-to-mean functional relation instead of the standard statistical variance estimate. Even when there is a moderate degree of heterogeneity among items and when the form of the variance-to-mean relation is misspecified, substantial cost savings may be realized. The cost of statistical uncertainty may be reduced by half. The research also provides evidence that system cost is fairly insensitive to the number of items used to fit the regression. This paper provides the underlying reason why a regression-derived variance estimator yields lower cost: it is less variable than the usual individual item variance estimator.     

Time Series Models for Count or Qualitative Observations

Time series sometimes consist of count data in which the number of events occurring in a given time interval is recorded. Such data are necessarily nonnegative integers, and an assumption of a Poisson or negative binomial distribution is often appropriate. This article sets ups a model in which the level of the process generating the observations changes over time. A recursion analogous to the Kalman filter is used to construct the likelihood function and to make predictions of future observations. Qualitative variables, based on a binomial or multinomial distribution, may be handled in a similar way. The model for count data may be extended to include explanatory variables. This enables nonstochastic slope and seasonal components to be included in the model, as well as permitting intervention analysis. The techniques are illustrated with a number of applications, and an attempt is made to develop a model-selection strategy along the lines of that used for Gaussian structural time series models. The applications include an analysis of the results of international football matches played between England and Scotland and an assessment of the effect of the British seat-belt law on the drivers of light-goods vehicles.     

Doing Gender Well and Differently in Dirty Work: The Case of Exotic Dancing

This article explores how a group of exotic dancers do gender and manage the stigma associated with their work and identities. We draw upon stigma management strategies from the dirty work literature and illuminate the doing of gender in these strategies. We also contribute to the debate that gender can be done well and differently through simultaneous, multiple enactments of femininity and masculinity. We consider the experiences of 21 exotic dancers working in a chain of UK exotic dancing clubs and conclude that in order to be good at their job, exotic dancers are expected to do gender well, that is, perform exaggerated expressions of femininity. However, we also theorize that for some dirty workers, specifically exotic dancers as sex workers, doing gender well will not be enough to reposition bad girls (bad, dirty work) into good girls (good, clean work). Finally, we propose that doing gender well will have different consequences in different types of work, thereby extending our findings to other dirty work occupations and organizations in general.     

Longitudinal predictors of reading achievement among at-risk children

Early exposure to multiple risk factors is related to an elevated risk for academic difficulty. Thus, it is important to promote academic resilience as early as possible and to identify factors that support resilience. Given the positive relation between early literacy skills and later academic outcomes, examining resilience in reading is important. This study examined, first, whether the reading gap widens or narrows for below-average and above-average, at-risk children during the first four years of school; and, second, what protective factors predict reading achievement over time from kindergarten through the end of third grade. Results indicated that as a group, low-achieving children made smaller gains in reading than high-achieving children over the first four years of school. In addition, participation in center-based prekindergarten care, plus more access to books in the home, better interpersonal skills, and fewer poor physical conditions immediately surrounding elementary schools served as protective factors for at-risk children's early literacy development.     

The impact of seating and positioning on the development of repetitive strain injuries of the upper extremity in wheelchair athletes

The population of people who use wheelchairs has been increasing due to technological advances. With this increase, there has also been an increase in participation in wheelchair sports. The incidence of upper extremity injury in wheelchair users has been reported to be between 31 and 73% [2,13,23,26,29]. Wheelchair athletes may be at an increased risk for upper extremity injury due to increased upper extremity use with sport. The purpose of this paper is to ascertain whether proper seating and positioning have an impact on the prevention of repetitive strain injuries (RSI) of the soft tissues, including peripheral nerve entrapments and muscle injury, of the upper extremity in wheelchair athletes. A review of current research on wheelchair propulsion and RSI revealed several hazards for wheelchair athletes to develop RSI's. These include duration of impairment, muscle imbalance, awkward positioning, inadequate rest breaks, repetition of muscle use in daily activities and in sport participation, the degree of force needed for propulsion, and fatigue. Current research does not provide conclusive information on optimal seating. Suggestions of preventative measures are given including suggestions with regard to positioning in the wheelchair.