Legalistic organizational responses to catastrophic illness: The effect of stigmatization on reactions to HIV/AIDS

The HIV/AIDS epidemic has focused increased attention on catastrophic illnesses in the workplace, and because of the stigmas associated with HIV/AIDS, it raises three primary concerns for organizations: (1) organizational avoidance of legal sanctions and litigation; (2) the maintenance of organizational legitimacy; and (3) organizational protection of employee rights. Although many organizations adopt legalistic responses to cope with these concerns, the analysis presented in this article suggests that while legalistic approaches function well to protect organizational interests in terms of both legal liability and legitimacy, the are only partially able to protect employee rights. Drawing upon the limited literature on HIV/AIDS in the workplace, this article presents an agenda for future research on organizational responses to HIV/AIDS.     

Distribution-free tests for comparing several treatments with a control

Abstract  In this paper we propose distribution-free treatments versus control tests for the one- and two-way classifications. The null distribution properties are shown to be equivalent to those of well-known statistics for which critical values have been extensively tabled. Asymptotic relative efficiencies with respect to corresponding normal theory competitors are derived and optimal designs for the allocation of experimental units to the treatments and control are obtained.     

Inferences about the parameters of a time series model with changing variance

Summary We consider the problem of making inferences about the parameters of a time series model when there is the possibility of a discrete variance change at an unknown time point. For this we obtain the posterior distributions of the parameters and of the variance ratio.     

Are robust estimation methods useful in the structural errors-in-variables model?

Summary In this paper it is investigated whether robust estimation procedures for the parameters of a regression model are also applicable when the observations are generated by the errors-in-variables model. Specifically, attention is paid to bounded-influence estimators, i.e. estimators that are constructed in such a way that the influence of a single observation on the outcome of the estimator is bounded. Both the classical errors-in-variables model and models with contaminated observational errors are considered.The authors are indebted to a referee for his valuable comments on an earlier version of this paper.     

The occurrence of outliers in the explanatory variable considered in an errors-in-variables framework

Summary The problem of estimating the slope of a linear relationship between two jointly normally distributed random variables is considered when outliers may occur in the explanatory variable. It will be studied as a special case of an errors-in-variables problem where the explanatory variable is measured which a nonnormally distributed error. In this more general model and under certain conditions a consistent estimator can be given with a normal limiting distribution. Applications to cases of outliers in the explanatory variable will be presented.     

Speaking Up in the Operating Room: How Team Leaders Promote Learning in Interdisciplinary Action Teams

ABSTRACT This paper examines learning in interdisciplinary action teams. Research on team effectiveness has focused primarily on single-discipline teams engaged in routine production tasks and, less often, on interdisciplinary teams engaged in discussion and management rather than action. The resulting models do not explain differences in learning in interdisciplinary action teams. Members of these teams must coordinate action in uncertain, fast-paced situations, and the extent to which they are comfortable speaking up with observations, questions, and concerns may critically influence team outcomes. To explore what leaders of action teams do to promote speaking up and other proactive coordination behaviours – as well as how organizational context may affect these team processes and outcomes – I analysed qualitative and quantitative data from 16 operating room teams learning to use a new technology for cardiac surgery. Team leader coaching, ease of speaking up, and boundary spanning were associated with successful technology implementation. The most effective leaders helped teams learn by communicating a motivating rationale for change and by minimizing concerns about power and status differences to promote speaking up in the service of learning.     

Sources of Sectoral Growth in an Economy Wide Context: The Case of U.S. Agriculture

Growth in U.S. agriculture is linked to the non-farm economy through domestic terms of trade and factor market adjustments. With almost stable input growth, the relatively large contributions from growth in Total Factor Productivity (TFP) are passed on to intermediate and final consumers in the form of declining real prices for primary farm products. The resulting net growth in the real value of farm output (GDP) is relatively low (0.25% per annum). The decomposition of TFP suggests that public agricultural stock of knowledge and infrastructure are robustly associated with TFP growth, while spill-overs from private agricultural and economy wide research and development (R and D) are positive but, relatively small.     

Unlocking the potential of advanced manufacturing technologies

This research examines whether investments in advanced manufacturing technologies (AMTs) such as flexible manufacturing systems (FMS), computer aided design (CAD), computer aided manufacturing (CAM), robotics, etc., are more likely to lead to improved performance if they are supported by improvements in the manufacturing infrastructure of the company. This question is evaluated using data gathered from 202 manufacturing plants chosen from industries generally considered to have relatively high investments in technology.Multiple item scales are developed and adapted from sources in the literature to measure investments in technology, infrastructure, and the performance of the plant. Evidence supporting the reliability and validity of these scales is provided. Hierarchical regression is used to analyze the relationship between technology, infrastructure, and performance. The results suggest that there is an important interaction between the adoption of advanced manufacturing technologies and investments in infrastructure. Firms that invest in both AMTs and infrastructure perform better than firms which only invest in one or the other. Separate analyses on sub-samples of firms with the highest and lowest investments in AMTs show that infrastructural investments have a stronger relationship with performance in the high investment group. Thus, the data indicate that infrastructural investments provide a key to unlocking the potential of advanced manufacturing technologies.