A Meta-Analysis of the Antecedents of Voluntary Turnover in Studies Involving Active Duty Military Member Populations

Studies have explored the antecedents to turnover in the military; however, results vary. This research used a meta-analytic method to evaluate reported correlations between antecedents of turnover intent and turnover in an effort to understand the true relationship between them and offer insight to leaders as to where they can affect turnover within their organizations. Included studies reported a military sample and were published between 1973 and 2009. The meta-analysis revealed no correlation between OPTEMPO and turnover intent. Not enough studies were included to evaluate the relationship between OPTEMPO and turnover. Varying definitions and measurements of OPTEMPO raised concern. Additional primary research is needed with consistent definition and measurement of OPTEMPO. This study did validate that turnover intent and turnover had the strongest positive relationship with an 80% credibility range of 0.43 to 0.58. Organizational commitment and turnover had the strongest negative relationship with an 80% credibility range of -0.49 to -0.34. For the dependent variable turnover intent, job search had the strongest positive relationship with an 80% credibility range of 0.41 to 0.56. Organizational commitment also had the strongest negative relationship with turnover intent. The 80% credibility interval was -0.65 to -0.50. Leaders should focus their efforts on organizational commitment to influence subordinates’ turnover decisions

Determining the Optimized Distribution Fielding Plan for Next Generation Automatic Test Systems

Abstract Due to a lack of regulation regarding United States Army Automatic Test Equipment (ATE), the number and variety of these ATEs has proliferated to the point that supporting the many varieties of non-standard ATE has become extremely burdensome. Additionally, the inventory of ATE is aging, causing supportability and performance problems. In order to combat these issues, the Next Generation Automatic Test System (NGATS) was developed. There are currently 28 NGATS projected for fielding to the various Army Depots and ATE-Test Program Set (TPS) Centers located throughout the United States by fiscal year 2019. The authors developed an optimization model to best determine a distribution fielding plan that maximizes the efficient use of these machines. The model utilized Multi-Objective Decision Analysis (MODA) principles to capture competing priorities for the equipment. The resultant fielding plan will help the Army distribute the NGATS in a way that minimizes costs to the Army and maximizes productivity