Bayes Estimation of Intraclass Correlation Coefficients Under Unequal Family Sizes

Bayesian inference for the intraclass correlation ρ is considered under unequal family sizes. We obtain the posterior distribution of ρ and then compare the performance of the Bayes estimator (posterior mean of ρ) with that of Srivastava's (1984) estimator through simulation. Simulation study shows that the Bayes estimator performs better than the Srivastava's estimator in terms of lower mean square error. We also obtain large sample posteriors of ρ based on the asymptotic posterior distribution and based on the Laplace approximation.     

Bayes Prediction for a Stratified Regression Superpopulation Model Using Balanced Loss Function

We consider the stratified regression superpopulation model and obtain Bayes predictor of the finite population mean under Zellner's two-criterion balanced loss function (BLF). BLF predictor simplifies to a linear combination of the sample and predictive means. Furthermore, it reduces to some of the well-known classical and Bayes predictors. Relative losses and relative savings loss are obtained to investigate loss robustness of the BLF predictor. It is found to perform better than the usual sample mean as well as the predictive mean in the minimal Bayes predictive expected loss sense.     

Testing Homogeneity of Gini Indices Against Simple-Ordered Alternative

Gini index is one of the most popular indices employed for measuring inequality in income and wealth. In this article, we propose a multi-sample test for testing Gini indices against simple-ordered alternatives. The exact critical points through simulation were computed for the proposed test in case of two-parameter exponential distribution; however, the proposed test can be applied even in case of other distributions like Pareto, Weibull, etc. Construction of simultaneous one-sided confidence intervals (SOCIs) was proposed along with an illustration. Power of the test is computed and some power comparisons are also made.     

The Conventions of Management Research and their Relevance to Management Practice

This paper recognizes the failure of management research to communicate with practitioners, and speculates over the reasons why this may be the case. It is possible that the researchers’ interests may not always coincide with management practitioners’; however, even when such interests are congruent, it seems that relatively little management research is published in practitioner journals. We suggest that this is because academic research is written in a style that tends to alienate most practitioners. This paper isolates the stylistic conventions associated with research targeted to academics (typically published in academic journals) and research targeted to practitioners (typically published in practitioner‐oriented journals). Such stylistic differences are illustrated through a study of organizational change whose findings have been published in both academic and practitioner format, namely in the Administrative Science Quarterly and the Harvard Business Review. We suggest that the gap between these two types of research could be narrowed through processes of translation (i.e. academic jargon could be translated in practitioner language). In addition we might consider greater use of Mode 2 research over Mode 1 research (academic). Mode 2 research presupposes that teams of academics and practitioners assemble to define the research problem and methodology in terms appropriate to a particular context and in a way that accounts for all existing interests so that translation processes are seamless. However, Mode 2 creates its own gap in that the knowledge is more contextual and may not reach a wide audience.     

Use of a case study in sequencing/scheduling research

This paper describes a study of an industrial sequencing/scheduling problem. The study contains the definition of the problem, data requirements and examination of solution technique. Definition of the problem is discussed from the aspect of uniqueness of the specific system. Discussion of data requirements includes availability and accuracy, while examination of solution technique considers limitation of time, computer capacity, etc., as well as the possibility of imbedding available algorithms into the solution procedure. Conclusions are presented relative to the use of the case study approach in sequencing/scheduling research.     

Using review articles to address societal grand challenges

We introduce a special issue of International Journal of Management Reviews that demonstrates how to use review articles to address societal grand challenges—complex, large-scale issues facing humankind, such as climate change, inequality and poverty. First, we argue that review articles possess unique features that make them particularly useful for addressing societal grand challenges. Second, we discuss three distinct but related roles of review articles in addressing societal grand challenges: (1) advancing theoretical knowledge; (2) advancing methodological knowledge; and (3) advancing practical knowledge. We conclude by providing future directions to enhance contributions of review articles for addressing societal grand challenges further by: (a) spanning disciplinary boundaries; (b) engaging practitioners; and (c) using alternative review approaches.     

Multilocus linkage analysis by blocked Gibbs sampling

The problem of multilocus linkage analysis is expressed as a graphical model, making explicit a previously implicit connection, and recent developments in the field are described in this context. A novel application of blocked Gibbs sampling for Bayesian networks is developed to generate inheritance matrices from an irreducible Markov chain. This is used as the basis for reconstruction of historical meiotic states and approximate calculation of the likelihood function for the location of an unmapped genetic trait. We believe this to be the only approach that currently makes fully informative multilocus linkage analysis possible on large extended pedigrees.     

Sensitivity of Bayesian sampling inspection schemes to a non-normal prior distribution

summary In this paper we derive the predictive density function of a future observation under the assumption of Edgeworth-type non-normal prior distribution for the unknown mean of a normal population. Fixed size single sample and sequential sampling inspection plans, in a decisive prediction framework, are examined for their sensitivity to departures from normality of the prior distribution. Numerical illustrations indicate that the decision to market the remaining items of a given lot for a fixed size plan may be sensitive to the presence of skewness or kurtosis in the prior distribution. However, Bayes'decision based on the sequential plan may not change though expected gains may change with variation in the non-normality of the prior distribution.