Search

Research has demonstrated that management influences the performance of public organizations, but almost no research has explored how the success or failure of a public organization influences the decisions of those who manage it. Arguing that many decisions by public managers are analogous to risky choice, the authors use a well-validated model of relative risk aversion to understand how such choices are influenced by managers' perceptions of organizational performance. They theorize that managers will be less likely to encourage innovation or give discretion to employees when they are just reaching their goals relative to other performance conditions. Analyses of responses to the 2011 and 2013 Federal Employee Viewpoint Surveys provide considerable support for these assertions. The findings have significant implications for our understanding of the relationship between management and performance in public organizations. [ABSTRACT FROM AUTHOR]

The initial examination of validity generalization in the Army Selection and Classification Project used data from a concurrent validation sample of 4,039 job incumbents drawn from a representative sample of nine jobs. The available data consisted of 24 predictor scores and five job performance factor scores on each individual. The major objectives were to determine (a) the degree of validity generalization across the major components of performance, with the job held constant, and (b) the degree of validity generalization across jobs within each major performance factor. After reducing the predictor set by eliminating variables that added no information, a modified confirmatory analysis was used to test the hypotheses that one equation would fit the data from all performance components and that one equation would fit the data from all jobs, given a particular performance component. The major findings were that different predictor equations were needed for each of the five criterion factors. For generalization across jobs, within each criterion factor, one equation fit the data for four of the five performance components. Different prediction equations were required for the component that reflects proficiency on the technical tasks specific to each job. [ABSTRACT FROM AUTHOR]

The goal of criterion development in Project A was to construct multiple measures of the major components of job performance such that the total performance domain for a representative sample of the population of entry-level enlisted positions in the U.S. Army was covered. These measures were to be used as criteria against which to validate both experimental and existing predictors of job performance. The initial model specified that performance is multidimensional within two major categories of dimensions designated as organization-wide and job specific. The development strategy involved describing the total domain of job content via extensive task analyses and critical incident analyses, generating the critical performance dimensions that constitute it, constructing measures for each dimension, and evaluating each measure using expert judgment and field test data. The specific measures developed consisted of rating scales, tests of job knowledge, hands-on job samples, and archival records. The major steps in the job analyses, content sampling, instrument construction, and instrument evaluation are described, and the final array of criterion measures is presented. [ABSTRACT FROM AUTHOR]