Matching Managers to Strategy: Further Tests of the Miles and Snow Typology

This paper integrates prior research on strategic leadership by building on the concept of alignment to explain the performance impact of top managers. Using the Miles and Snow (1978) typology as a theoretical framework, several hypotheses are tested on a sample drawn from three distinct industries. The results show that organizations that are able to achieve an alignment between managerial characteristics and strategic direction perform better than firms where such an alignment is absent. Further, it was found that the strategy-manager match explains a greater proportion of variance in performance than industry membership, organizational age and firm size. Taken together, these findings provide persuasive evidence about the impact that an organization's leaders exert in driving performance outcomes and demonstrates the validity of the administrative dimension of the Miles and Snow typology.     

A simulation analysis of the impact of family configuration on virtual cellular manufacturing

Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.     

Social security in a globalizing world

The main burden of the paper is to argue for enlarging both the concept and the coverage of social security, especially in developing countries, to address the twin problems of "deficiency" and "adversity". The two parts of this enlarged concept of social security are Basic Social Security (BSS) and Contingent Social Security (CSS). To strengthen the argument, lessons have been highlighted from the historical experience of Western countries, where the State played a leading role. Having argued for the extension of BSS, the paper also deals with the extension of CSS. This is best done through the informal economy, which employs a large majority of workers in developing countries. While the primacy of the State has been highlighted, the paper develops a typology of various social security models that could be used to study and understand the existing arrangements as well as the potentialities for extension.     

Hierarchical bayes quality measurement plan

Quality Measurement Plan (QMP) as developed by Hoadley (1981) is a statistical method for analyzing discrete quality audit data which consist of the expected number of defects given the standard quality. The QMP is based on an empirical Bayes (EB) model of the audit sampling process. Despite its wide publicity, Hoadley's method has often been described as heuristic. In this paper we offer an hierarchical Bayes (HB) alternative to Hoadley's EB model, and overcome much of the criticism against this model. Gibbs sampling is used to implement the HB model proposed in this paper. Also, the convergence of the Gibbs sampler is monitored via the algorithm of Gelman and Rubin (1992).     

Tissue Dosimetry, Pharmacokinetic Modeling, and Interspecies Scaling Factors

Interspecies scaling factors (ISFs) are numbers used to adjust the potency factor (for example, the q1* for carcinogens or reference doses for compounds eliciting other toxic endpoints) determined in experimental animals to account for expected differences in potency between test animals and people. ISFs have been developed for both cancer and non-cancer risk assessments in response to a common issue: toxicologists often determine adverse effects of chemicals in test animals and then they, or more commonly risk assessors and risk managers, have to draw inferences about what these observations mean for the human population. This perspective briefly reviews the development of ISFs and their applications in health risk assessments over the past 20 years, examining the impact of pharmacokinetic principles in altering current perceptions of the ISFs applied in these health risk assessments, and assessing future directions in applying both pharmacokinetic and pharmacodynamic principles for developing ISFs.     

The generalized exponential cure rate model with covariates

In this article, we consider a parametric survival model that is appropriate when the population of interest contains long-term survivors or immunes. The model referred to as the cure rate model was introduced by Boag 1 Boag, J. W. 1949. Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J. R. Stat. Soc. Ser. B, 11: 15–53.  [Google Scholar] in terms of a mixture model that included a component representing the proportion of immunes and a distribution representing the life times of the susceptible population. We propose a cure rate model based on the generalized exponential distribution that incorporates the effects of risk factors or covariates on the probability of an individual being a long-time survivor. Maximum likelihood estimators of the model parameters are obtained using the the expectation-maximisation (EM) algorithm. A graphical method is also provided for assessing the goodness-of-fit of the model. We present an example to illustrate the fit of this model to data that examines the effects of different risk factors on relapse time for drug addicts.     

On the joint distribution of placement statistics under progressive censoring and applications to precedence test

In reliability and survival analysis, comparison of two or more populations is an important problem. For example, while comparing a treatment group with a control group, one may be interested in determining whether the observations in the treatment group have a longer lifetime than those from the control group, that is, whether the treatment is effective or not. In such a study, it would be extremely valuable to make a decision based on early failures. In this paper, we consider independent progressively Type-II censored random samples from two populations with cumulative distribution function's (cdf) F(·)$F(·)$ and G(·)$G(·)$ respectively, and discuss a precedence test for testing the equality of the two distributions based on placements. For this purpose, we derive the joint distribution of the first l   placement statistics from the progressively censored sample from F(·)$F(·)$. We then derive the exact null distribution of the precedence test statistic which is simply the sum of the placements. We provide the rejection regions for fixed levels of significance and various sample sizes and different progressive censoring schemes.     

A comparison of ordinal logistic regression models using Classical and Bayesian approaches in an analysis of factors associated with diabetic retinopathy

Estimating the risk factors of a disease such as diabetic retinopathy (DR) is one of the important research problems among bio-medical and statistical practitioners as well as epidemiologists. Incidentally many studies have focused in building models with binary outcomes, that may not exploit the available information. This article has investigated the importance of retaining the ordinal nature of the response variable (e.g. severity level of a disease) while determining the risk factors associated with DR. A generalized linear model approach with appropriate link functions has been studied using both Classical and Bayesian frameworks. From the result of this study, it can be observed that the ordinal logistic regression with probit link function could be more appropriate approach in determining the risk factors of DR. The study has emphasized the ways to handle the ordinal nature of the response variable with better model fit compared to other link functions.     

A Dynamic Perspective on Diverse Teams: Moving from the Dual-Process Model to a Dynamic Coordination-based Model of Diverse Team Performance

The existing literature on diverse teams suggests that diversity is both helpful to teams in making more information available and encouraging creativity and damaging to teams in reducing cohesion and information sharing. Thus the extant literature suggests that diversity within teams is a double-edged sword that leads to both positive and negative effects simultaneously. This literature has not, however, fully embraced the increasing calls in the broader groups literature to take account of time in understanding how groups function [e.g. Cronin, M. A., Weingart, L. R., &; Todorova, G. (2011). Dynamics in groups: Are we there yet? The Academy of Management Annals, 5, 571–612]. We review the literature on diverse teams employing this lens to develop a dynamic perspective that takes account of the timing and flow of diversity's effects. Our review suggests that diversity in groups has different short-term and long-term effects in ways that are not fully captured by the currently dominant double-edged sword metaphor. We identify an emerging perspective that suggests a tropical depression metaphor—that has the potential, over time, to develop either into a dangerous hurricane or diffuse into a rainstorm that gives way to sunshine, as more apt to capture the dynamic effects of diversity in teams. We conclude by outlining an agenda for redirecting future research on diverse teams using this more dynamic perspective.     

Some nonparametric precedence-type tests based on progressively censored samples and evaluation of power

In this paper, we consider the problem of testing the equality of two distributions when both samples are progressively Type-II censored. We discuss the following two statistics: one based on the Wilcoxon-type rank-sum precedence test, and the second based on the Kaplan–Meier estimator of the cumulative distribution function. The exact null distributions of these test statistics are derived and are then used to generate critical values and the corresponding exact levels of significance for different combinations of sample sizes and progressive censoring schemes. We also discuss their non-null distributions under Lehmann alternatives. A power study of the proposed tests is carried out under Lehmann alternatives as well as under location-shift alternatives through Monte Carlo simulations. Through this power study, it is shown that the Wilcoxon-type rank-sum precedence test performs the best.