Segmenting Human Reliability Risks Through Employer Attractiveness: A Clustering Approach in the Military Context

This study explores human factors and reliability within the Lithuanian Armed Forces by analysing the alignment between employer value propositions and soldiers' expectations. Using five dimensions of employer attractiveness: Interest, Social, Economic, Development, and Application Value, the cluster analysis was applied to segment soldiers based on perceived organizational value. Intention to continue service (ICS), a key indicator of reliability and operational sustainability, was examined across these clusters. Three distinct clusters emerged through K-means clustering. Cluster 1, with low scores across all value dimensions, showed the lowest ICS (M=2.89), indicating high risk for disengagement and attrition. Cluster 2, scoring highly on all dimensions, demonstrated the strongest commitment (M=4.43), suggesting high reliability and resilience. Cluster 3 reflected moderate perceptions and ICS (M=3.65), marking it as a transitional group requiring attention. Significant differences in ICS across clusters confirmed the relevance of this segmentation for reliability assessment. Both linear and non-linear relationships between cluster membership and ICS highlight the complexity of motivationally conditioned human reliability risk dynamics in military contexts. Findings emphasize the importance of economic and developmental support in sustaining engagement. Risks such as communication breakdown, morale decline, and reduced mission readiness are most evident in Cluster 1. Practical implications include targeted counselling, development planning, and recognition strategies to strengthen reliability and organizational effectiveness.

Keywords: Human factors, human reliability, risk profiling, military personnel, employer attractiveness, cluster analysis.