A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Improving performance? The adoption and implementation of quality systems in U.K. nonprofits

There are increasing and multiple pressures on nonprofit organizations to demonstrate excellence in performance. Although there is a growing literature on the various approaches to performance improvement taken by nonprofits, little is known about the processes involved in the adoption and implementation of specific approaches. This article is about the adoption and use of one approach to performance improvement, “quality systems,” in the U.K. nonprofit sector. We report findings about factors that encourage nonprofits to adopt quality systems. We also analyze the distinctive challenges of implementing quality approaches in a nonprofit sector context and suggest critical success factors. The article concludes with a discussion of the organizational and policy implications of applying the management concepts of quality and performance to the nonprofit sector.     

Class analysis and its futures

Books reviewed in this articles:
Class and Stratification: An introduction to current debates R. Crompton
Class S. Edgell
Changing Classes: Stratification and Mobility in Post-Industrial Societies G. Esping-Anderson, (ed.)
Class and Inequality: Comparative Perspectives M. Hamilton and M. Hirszowicz
Class R. Scase     

Is Stakeholder Corporate Governance Appropriate in Russia?

Journal of Management and Governance - Alternative forms of disciplining the actionsof senior enterprise managers can becharacterized as shareholder or stakeholdergovernance. This paper analyzes...     

Two phase parametric and probabilistic NPV calculations, with possible deferral of disposal of UK nuclear waste as an example

This paper illustrates the value of several particular features of a first phase parametric approach to discounted cash flow (DCF) decision analysis when significant uncertainty is involved. It also illustrates the value of second phase probabilistic approaches to selected parameters for five quite different example reasons. The most controversial example reason concerns the discount rate. The particular example used to illustrate both phases may stimulate general interest because of the important issues involved, but it is argued that the two phase approach as a whole has a wide range of applications for decisions large and small.     

Academic Entrepreneurship: Time for a Rethink?

Academic entrepreneurship, which refers to efforts undertaken by universities to promote commercialization on campus and in surrounding regions of the university, has changed dramatically in recent years. Two key consequences of this change are that more stakeholders have become involved in academic entrepreneurship and that universities have become more ‘strategic’ in their approach to this activity. The authors assert that the time is ripe to rethink academic entrepreneurship. Specifically, theoretical and empirical research on academic entrepreneurship needs to take account of these changes, so as to improve the rigour and relevance of future studies on this topic. We outline such a framework and provide examples of key research questions that need to be addressed to broaden understanding of academic entrepreneurship.