Towards Evidence-Based Migration Governance: A Novel Fuzzy Multi-Criteria Approach to Problem Prioritization

Migration has become a multidimensional policy challenge for host countries, as migrants face economic, social, political, and psychological problems that hinder both their well-being and their potential contribution to social and economic development. A fundamental problem in this context is the absence of a clear prioritization of these diverse challenges, which limits the effectiveness of policy interventions. Although the literature extensively examines individual migrant related problems, comparative analyses that determine which problems are the most critical remain limited, creating an important gap in migration research. The aim of this study is to address this gap by identifying and prioritizing the most critical problems experienced by migrants in host countries through a comprehensive analytical framework. To this end, a novel fuzzy multi criteria decision making model is proposed, integrating a distance-based experts’ weighting approach, the author developed COWEB technique for criteria weighting, and behavioral leadership fuzzy sets to capture expert heterogeneity and judgment behavior. The model evaluates fourteen problem criteria based on assessments from ten experts. The findings reveal that wage inequality and underemployment are the most critical challenges, highlighting the central role of labor market dynamics in migrant vulnerability. The results are validated through comparative analysis, correlation tests, and scenario-based robustness checks. The study contributes to the literature by offering an original and robust prioritization framework and addressing a key methodological gap. From a policy perspective, the findings suggest that strategies focusing on fair wage enforcement, skill recognition, and inclusive labor market policies are essential for effective migration governance.