Justifying wrongful employee behavior: The role of personality in organizational sabotage

The role that personality plays in the justification of organizational sabotage behavior was examined. In a two phase study, 120 business students were first surveyed to create a list of 51 methods of sabotage. In the second phase, 274 other business students rated justifiability of the 51 methods and completed Machiavellian and hostility scales. A factor analysis of the justification ratings yielded four factors: (1) methods of sabotaging company profits and production, (2) informational sabotage, (3) violent and illegal methods, and (4) traditional labor methods of sabotage. A 2 (high versus low Machiavellianism) ×2 (high versus low hostility) ANOVA upon factor scores for justifiability revealed significant main effects for hostility and significant interactive effects on Factors 1 and 2. Results were discussed in terms of differences in management and blue collar methods of sabotage and in terms of a self-presentational approach to justification of sabotage. Robert A. Giacalone is currently Assistant Professor of Management Systems at the E. Claiborne Robins School of Business, University of Richmond. Dr. Giacalone has published a variety of articles in the areas of organizational impression management, organizational sabotage and business ethics. His book, Impression Management in the Organization, co-edited with Paul Rosenfeld, is due out in 1989.Stephen B. Knouse is currently Associate Professor of Management at the University of Southwestern Louisiana. Dr. Knouse has published numerous articles on the letter of recommendation and impression management.     

A forecasting comparison of some var techniques

Higher dimensional multivariate time series models suffer from the problem of over-parametrisation which impairs their forecasting performance. Starting from such unrestricted vector autoregressive models the paper discusses two ways to cope with this difficulty. The first approach reduces the number of free parameters by applying a subset modelling strategy. The second approach takes a Bayesian point of view by formulating ‘priors’ which are then combined with sample information, but leaving the original specification unaltered. Using Austrian quarterly macroeconomic time series a comparative study is undertaken by running alternative forecasting exercises. Both methods improve out-of-sample forecasting performance substantially at the cost of some bias in ex-post simulations. Comparing the ex-ante predictions of the two approaches, the former does better at short horizons whereas the latter gains as the forecast horizon lengthens.