Extending the job component validity (JCV) model to include personality predictors

The ultimate goal of personnel selection research is to identify and validate predictors that will differentiate good performers from poor performers (Hunter & Schmidt, 1998). Historically, the most effective means of identifying top performers has been via the use of general cognitive ability predictors. During the last 15 to 20 years there has been a revival in using personality inventories as predictors of occupational success (Barrick, et al., 2001) due to the development and near global acceptance of the Five Factor Model of Personality (also known as the FFM or Big Five).; Validation studies have traditionally been accomplished through criterion-related or content-oriented validation. However, such studies are often not feasible because of issues like small sample sizes, time constraints, budget concerns, and other contemporary barriers. Fortunately, alternate methods of establishing validity, such as job component validity (JCV) have been developed. JCV, a synthetic validity approach, is the process of statistically demonstrating that if two different jobs (receptionist vs. secretary) have similar job components, then a single predictor can be used for both jobs (McCormick, Jeanneret, & Mecham, 1979). The JCV model incorporated in the Position Analysis Questionnaire (PAQ), a worker oriented job analysis, (PAQ; McCormick, Mecham, and Jeanneret, 1972) has been effective in applications such as predicting mean test scores on cognitive ability batteries, predicting observed validity coefficients, and in guiding establishment of cut scores (Hoffman, Holden, and Gale, 2000).; Job analysis reports from the PAQ provide 13 overall job dimension scores and 32 divisional job dimension scores useful for job comparison purposes. Using job dimension scores as predictors, the PAQ's JCV model has successfully predicted mean scores job incumbents should attain on cognitive ability tests such as the Wonderlic and GATB (McCormick et al., 2001). The PAQ also produces 76 secondary attribute scores that can also be utilized for analysis as predictors.; The goal of this research was to begin preliminary work toward evaluating the feasibility of using PAQ job dimension scores and/or PAQ attribute scores as predictors for estimating mean FFM personality scores as measured by the Hogan Personality Inventory (HPI). This research seeks to extend the JCV model to determine if the PAQ can also be successfully used to predict mean scores on personality constructs to increase the utility of the JCV model.; PAQ Services provided job analysis data for this study, while Hogan Assessment Services provided data from validity studies using the HPI. All data used in this study were archival and were aggregated at the job or DOT code level. Results were mixed, but significant regression models were obtained for each of the seven HPI scales suggesting the JCV model can be extended to include personality predictors.