Objective:

Kermanshah Province has experienced considerable demographic changes over recent decades due to persistent unemployment, regional disparities, and structural changes in agricultural activities. Understanding the spatial structure of migration flows and the socioeconomic factors influencing them is essential for effective regional planning. Accordingly, this study aims to explain the migration network among the counties of Kermanshah Province by examining the role of unemployment, agricultural activities, and educational characteristics within a social network analysis framework.

Methods:

This study is descriptive–analytical and is based on secondary data obtained from the 2016 National Population and Housing Census of Iran. A migration matrix was constructed for the fourteen counties of Kermanshah Province to represent inter-county migration flows. Network analysis was conducted using UCINET and NetDraw software. Pearson correlation analysis was subsequently applied to examine the relationships between migration network indicators and selected socioeconomic and agricultural variables, including unemployment rate, agricultural producers, agricultural land area, irrigated fallow land, educational status of agricultural operators, and heavy livestock producers.



Findings:

The results indicate that Kermanshah County occupies the dominant position in the provincial migration network, recording the highest values of in-degree, out-degree, betweenness, and eigenvector centrality. Correlation analysis revealed a significant negative relationship between out-migration and the number of heavy livestock producers (r = −0.540), and the number of illiterate agricultural producers (r = −0.544). In contrast, irrigated fallow land exhibited a significant positive relationship with in-migration (r = 0.732), indicating that counties with greater agricultural production potential tend to attract more migrants.

Conclusion:

The migration network of Kermanshah Province exhibits a centralized structure in which population movements are concentrated toward counties with stronger economic and service capacities. The results highlight the importance of strengthening productive agriculture, expanding sustainable employment opportunities, and reducing spatial inequalities to promote balanced regional development and mitigate undesirable migration flows.