The Economic Benefits of Predicting Job Performance: Volume 1: Selection Utility

Designed as a comprehensive text for advanced courses in personnel selection and classification, the three volumes that comprise The Economic Benefits of Predicting Job Performance take a different approach than that taken in most previous works on the subject. While most texts focus on selection and psychological measurement to the exclusion of classification, these volumes summarize the major theories and research findings in both areas and provide a thorough treatment of classification processes. This is the first text providing more than a chapter on classification since Cronbach and Gleser's historic work in 1965. Joseph Zeidner and Cecil D. Johnson discuss the central topics involved in the practical prediction of job performance, including validity and utility models and research strategies and designs. Based on their analysis, they introduce a new theory, the differential assignment theory, and illustrate the mathematical principles that govern its use in personnel classification. Throughout, the authors are concerned with the realistic applications of specific procedures to maximize both selection and classification efficiency.

This volume begins with an overview describing the major issues, important findings, and conclusions. Focusing on selection utility, it covers the analysis of major validation studies and the development of current decision theoretic selection utility models. Volume 1 includes a glossary and list of references.

JOSEPH ZEIDNER is Professor of Administrative Sciences and of Psychology at The George Washington University. He authored Scientific Selection of Personnel and Guide to Psychological Tests (1963), coauthored Behavioral Science in the Army: A Corporate History of the Army Research Institute (1988), and edited Human Productivity Enhancement, Volumes 1 and 2 (Praeger, 1987 and 1988).

CECIL D. JOHNSON is a Research Consultant to The George Washington University, with more than 30 years of experience in personnel research.