Cross-Level Inferences of Job Satisfaction in the Prediction of Intent to Leave

Abstract

An emerging literature has demonstrated that proportionately more dissatisfied employees intend to leave their employing organization while proportionately more satisfied employees intend to remain. The purpose of the present study was to apply criteria for aggregation of individual-level data to the group-level using a measure of job satisfaction in the prediction of aggregated group-level intent to leave. Data collected from 5,586 employees of the Federal Aviation Administration provided partial support for aggregation. These results have general implications for the use of individual-level job satisfaction scores as predictors of group-level intent to leave.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1991
Accession Number
ADA242779

Entities

People

  • Chan M. Hellman
  • L. A. Witt

Organizations

  • Federal Aviation Administration

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Air Traffic
  • Air Traffic Controllers
  • Applied Psychology
  • Aviation Medicine
  • Education
  • Equations
  • Human Resources
  • Information Processing
  • Information Science
  • Job Satisfaction
  • New York
  • Organizational Structure
  • Personnel Management
  • Political Science
  • Psychology
  • Regression Analysis
  • United States

Readers

  • Maritime Combat Support and Expeditionary Logistics.
  • Naval Personnel Management
  • Theoretical Analysis.

Technology Areas

  • AI & ML