A Multi-Method Approach to Prioritize Locations of Labor Exploitation for Ground-Based Interventions
Ioannis Kougkoulos, M. Selim Cakir, Nathan Kunz, Doreen S. Boyd, Alexander Trautrims, Kornilia Hatzinikolaou, Stefan Gold
Production and Operations Management · 2021 · Volume 30 · Issue 12
Abstract
Recent estimates suggest that more than 40 million people worldwide are in situations of modern slavery and other forms of labor exploitation. UN Sustainable Development Goal 8.7 addresses this problem and urges stakeholders to take effective measures to end all forms of labor exploitation by 2030. Labor exploitation is often a direct consequence of forced migration, and humanitarian operations have a key role to play in tackling this issue worldwide. Academic research can facilitate this by providing the necessary decision-making tools to support antislavery practitioners in humanitarian organizations and governments. For effective resource allocation, these practitioners need tools to help them systematically identify and assess the risks of labor exploitation in an area. In this study, we develop a multi-method approach that combines various data sources to capture the issue's complex and multidimensional nature. Through satellite remote sensing, we first identify 50 informal settlements hosting migrant workers in the strawberry production area of Southern Greece. We then apply a multi-criteria decision analysis (MCDA) method to a subset of six informal settlements in order to evaluate their labor exploitation risks based on eight criteria. In addition to being practically implemented by a humanitarian organization and a government agency in Greece, our study advances research on humanitarian operations and labor exploitation by elucidating how a multi-method approach can be used for data-driven prioritization of interventions against labor exploitation. Our approach offers opportunities for other applications in the field of humanitarian operations.
Keywords
labor exploitation, multi-criteria decision analysis (MCDA), satellite remote sensing, sustainable development goals
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