Assessing the systemic effects of modern slavery mitigation strategies in supply chains
本研究构建了供应链中现代奴隶制的系统动力学模型，发现缓解策略组合实施长期效果最佳，并强调提高犯罪风险（如公众意识）是关键，但识别后缺乏明确应对措施。
Abstract According to recent estimates, around 50 million people worldwide are victims of modern slavery (MS), with approximately 28 million subjected to forced labour, much of which is linked to global supply chains. The United Nations Sustainable Development Goal 8.7 and various national legislations urge businesses and stakeholders to take proactive measures to eradicate MS and other severe forms of labour exploitation. MS in supply chains represents a complex socio-economic system. Adopting a systems perspective and drawing on situational crime prevention theory, this study presents one of the first system dynamics models of MS in supply chains. The model investigates the long-term effects of mitigation strategies and addresses the common issue of policy resistance in business-driven MS mitigation efforts. The model was developed in two stages: first, by deriving a causal loop diagram from the literature, and second, by extending it into a stock and flow diagram with mathematical formulations and calibrating it using empirical insights from a petrochemical supply chain in a developing country, which also served to confirm and refine the literature-based causal relationships. The results indicate that MS mitigation strategies are most effective in the long run when implemented together, supporting the configurational approach in social sustainable supply chain management research. Additionally, the findings highlight the critical role of increasing the risk of offending the MS crime for offenders, such as enhancing public awareness, as a key component of any combined policy aimed at significantly reducing MS. While mitigation strategies are valuable for detecting labour exploitation, the study highlights a persistent gap: the lack of clear, actionable responses once MS is identified. Finally, although digital platforms offer potential support, their high implementation costs may limit their feasibility for many supply chains.