Management and Operations Commons^™

Segmentation Of Severe Occupational Incidents In Agribusiness Industries Using Latent Class Clustering, Fatemeh Davoudi Kakhki, Steven Freeman, Gretchen Mosher

Faculty Publications

One of the principle objectives in occupational safety analysis is to identify the key factors that affect the severity of an incident. To identify risk groups of occupational incidents and the factors associated with them, statistical analysis of workers’ compensation claims data is performed using latent class clustering, for the segmentation of 1031 severe occupational incidents in agribusiness industries in the Midwest region of the United States between 2008–2016. In this study, severe incidents are those with workers’ compensation costs equal to or greater than $100,000 (USD). Based on the latent class clustering results, three risk groups are identified with …