EARLY ATTRITION WITHIN THE FIRST SIX MONTHS IN THE GERMAN MILITARY: IMPLICATIONS FOR RECRUITMENT AND PERSONNEL RETENTION

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Authors
Schwandt, Robert
Subjects
attrition
personnel retention
German Armed Forces
Bundeswehr
statistical analysis
logistic regression
survival analysis
difference-in-differences analysis
demographic factors
basic training
operational readiness
educational attainment
commuting distance
notice periods
personnel management
force retention
Advisors
Seagren, Chad W.
Ahn, Sae Young
Date of Issue
2025-03
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
Since the suspension of conscription in 2011 and the transition to a volunteer army, the German Armed Forces (Bundeswehr) has faced significant recruitment challenges in a fiercely competitive applicant market. A particularly problematic issue is the high dropout rate within the first six months, which now reaches up to 30%. This thesis investigates the reasons for Early Attrition of service and analyzes the extent to which the commuting distance between the place of residence and the workplace plays a role. By enriching existing personnel data with geographic information and incorporating actual measured distances via an application programming interface, the hypothesis that long travel distances are a crucial factor for early termination is tested.Methodologically, this study combines descriptive statistics with heatmaps and density plots to visualize the geographical data, as well as regression analyses to identify correlations between commuting distances and the dropout rate. Additionally, a Difference-in-Differences analysis is conducted to assess the effects of a new Withdrawal Policy introduced in 2024, which had the aim to decrease the Early Attrition Rate.The results indicate that commuting distance has a significant, non-linear impact on early termination and that the new policy is only effective in specific areas. Recommendations for the future include deepening of analyses using advanced methods such as survival analysis and improvement of data collection.
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Thesis
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Distribution Statement A. Approved for public release: Distribution is unlimited.
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