Handling data uncertainties in event tree analysis

Event tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.     

Utility estimates of job performance as related to the Data,People, and Things parameters of work

The purpose of this study was to investigate the applicability of the Schmidt–Hunter global estimation method of assessing utility across a broad range of jobs. Ninety-five industrial/organizational psychologists estimated the utility of performance in 24 carefully selected jobs. The utility estimates were compared to the Data, People, and Things worker function parameters from the Dictionary of Occupational Titles. The majority of jobs (62.5 per cent) produced significantly positively skewed distributions of dollar-valued job performance. The Data, People, and Things parameters accounted for 46 per cent of the variance in the non-symmetry of the utility distributions and 33 per cent of the variance in the inter-rater reliability of the utility estimates. The implications of the results were discussed for utility assessment, and explained from a decision theoretic perspective. © 1998 John Wiley & Sons, Ltd.     

The role of perceived system knowledge in predicting appraisal reactions,job satisfaction,and organizational commitment

There is a very large research base in Applied Psychology on the importance of affective reactions on organizational functioning. Likewise, performance appraisal has been a heavily researched area within the field. The present field studies attempt to bridge our understanding of these two areas by studying the relationship between performance appraisal process variables and employee affective reactions. In particular, the current studies examine the effects of a relatively new performance appraisal variable, Perceived System Knowledge (Williams and Levy, 1992), on appraisal reactions and job attitudes. In both studies, there was a strong relationship between employees' levels of perceived system knowledge and their appraisal reactions and job attitudes. In Study 1, when controlling for performance rating, PSK was positively related to appraisal reactions, job satisfaction, and organizational commitment. The findings from Study 1 were replicated in the second study which employed a longitudinal design. In addition, Study 2 found a relationship between PSK and fairness perceptions. Implications for these results and suggestions for approaching performance appraisal from an organizational perspective are proposed. © 1998 John Wiley & Sons, Ltd.