Social Capital and Turnover. Towards a Theoretically Informed Model for Social Capital in Turnover Research: Applications to the U.S. Military

Abstract

In the United States and around the world, social capital is becoming an intriguing antidote for a declining sense of community and community trust. This increased focus on social capital in empirical studies may play an important role in U.S. public policy, as policy changes focused on increasing social capital may decrease turnover. Yet, according to researchers, not enough empirical measures of social capital have been validated. It is possible that combining several existing measures could provide a theoretically informed measurement of social capital for turnover research in the U.S. military. This thesis incorporated survey responses into a predictive model of intent to turnover. Social scientists have yet to expand upon the study of the social capital variable in an empirically sound and theoretically informed manner that leads to a clearly defined and universally accepted definition. If being universally accepted is a necessary component of employee turnover models, the social capital variable will require the beta coefficients for the classic antecedents to be re-evaluated. The author takes the first step towards this goal by adding about 1 percent to the variance explained, above the variance explained by classic turnover antecedents.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA469287

Entities

People

  • Frederic W. Lunas

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Cyber
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Business Administration
  • Data Mining
  • Data Science
  • Employment
  • Enlisted Personnel
  • Factor Analysis
  • Information Science
  • Knowledge Management
  • Management Personnel
  • Organizational Structure
  • Personnel Management
  • Public Policy
  • Regression Analysis
  • Statistical Analysis
  • Surveys
  • United States

Fields of Study

  • Economics

Readers

  • Computational Modeling and Simulation
  • Economics
  • Organizational Psychology.