This study investigates the relationship between individual differences and the incidence of workplace aggression in a sample of employees from a transportation company and a public school system. Hierarchical multiple regression analysis indicated that measures of trait anger, attribution style, negative affectivity, attitudes toward revenge, self-control, and previous exposure to aggressive cultures accounted for 62% of the variance in the participants' self-reported incidence of workplace aggression. Further research on workplace aggression is advocated, focusing on the role of individual differences and their interactions with organizational and group-level variables.

Over the past decade, there has been an increase in attention to counterproductive workplace behaviors including violence, stealing, dishonesty, volitional absenteeism, drug and alcohol abuse, and aggression, many of which have been addressed in this special issue. Accompanying the attention to these specific types of behaviors has been a proliferation of theories developed to explain, understand, and manage counterproductive behavior. While these theories have addressed many apparently divergent types of behaviors, many similarities exist between and among these various perspectives. In this article, we integrate these various perspectives into a causal reasoning framework, proposing that individuals' attributions about the causal dimensions of workplace events are a primary factor motivating both the emotions and behaviors that result in counterproductive workplace behaviors.

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There is considerable scholarly writing about the theory and application of public value concepts, but this article explores why there is, by contrast, so little empirical research on public value. The article then goes on to provide a framework and a research agenda for inspiring and guiding new empirical research, based on three different conceptualizations of public value, with researchers needing to be explicit about which approach they are using in order to avoid confusion. While case studies have been used as a research method, the authors suggest a much wider array of potential research methods (depending on the research question) covering both quantitative and qualitative approaches and with a wider variety of designs, including comparative analysis. It is suggested that empirical research is undertaken with a more diverse range of stakeholders of public value, breaking out of the public manager-centric approach. This is an exciting agenda for research, though the paper warns that public value may fade from view unless empirical research is undertaken to test, challenge and extend the scholarly contributions.

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Multichannel deconvolution and equalization is an important task for numerous applications in communications, signal processing, and control. In this paper, w e extend the efficient natural gradient search method in [I] to d e r i v e a set of on-line algorithms for combined multichannel blind source separation and time-domain deconvolution/equalization of additive, convolved signal mixtures. We prove that the doubly-infinite multichannel equalizer based on the maximum entropy cost function w i t h natural gradient possesses the so-called "equivariance p r o p e r t y " such that its asymptotic performance depends on the normalized stochastic distribution of the soursce signals and not on the characteristics of the u n k n o w n channel. Simulations indicate the ability of the algorithm to perform efficient simultaneous multichannel signal deconvolution and source separatiam.