Predicting Enlistment for Recruiting Market Segments

Abstract

This Note examines the relationships between geodemographic information and individual (micro) models of enlistment decisionmaking. Although geodemographic systems can identify groups with varying enlistment rates, they provide limited information on the factors underlying enlistment. Given the apparent advantages of the micro models, the authors undertook to determine whether (1) differences in enlistment rates among the geodemographic groups are attributable to the types of factors included in the micro models; (2) including geodemographic information in the individual-level models improves the prediction of enlistment decisionmaking; and 3) the factors predicting enlistment vary by geodemographic groupings distinguish areas with different enlistment rates, they could be used in efforts such as targeting the mailing of recruiting literature and allocating recruiters or recruiting goals. At the same time, the authors found that enlistment decisionmaking micro models capture much of the same information. Finally, the research shows that the micro models are superior to the geodemographic information in predicting individuals' enlistment decisions and that the inclusion of geodemographic information in the micro models has little meaningful impact on enlistment behavior predictions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1989
Accession Number
ADA214487

Entities

People

  • Bruce R. Orvis
  • James R. Hosek
  • Martin Gahart

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Business Administration
  • Data Centers
  • Databases
  • Education
  • Employment
  • Enlisted Personnel
  • Families (Human)
  • High Density
  • Information Processing
  • Information Science
  • Manpower
  • Recruiting
  • Regression Analysis
  • Schools
  • Standards
  • Students
  • Surveys

Readers

  • Computational Modeling and Simulation
  • Electrochemical Surface Science
  • Psychometric Testing or Psychological Assessment.