An interdependent network interdiction model for disrupting sex trafficking networks

• 成果类型: Article
• 署名作者: Xie, Xiaodan; Aros-Vera, Felipe
• 署名单位: Procter & Gamble; University System of Ohio; Ohio University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13713
• 发表日期: 2022
• 页码: 2695-2713
• 关键词: interdependent networks; network interdiction; sex trafficking; supply chain

摘要

We map the organized sex trafficking networks (STNs) into a network flow model and develop an interdependent network interdiction model (NIM) to disrupt such networks. Our model considers the interdependence between the information and physical victim networks and reformulates the problem using duality theory. Our NIM provides a clear strategy for interdicting STNs. Namely, it determines when to monitor (i.e., gather information) or arrest the criminals to maximize the impact of the interdiction operation and cripple the network. We tested our NIM using three federally prosecuted sex trafficking cases in the United States of different sizes and structural properties: hybrid, international transactional, and Tenancingo models. Our experiments show promising results regarding the effectiveness of our NIM in all network types. In addition to that, we tested our model with an increasingly higher fraction of missing information to account for the inherently hidden nature of illicit networks. Our study provides analytical insight regarding (1) the importance of building the case prior to the arrests of criminals in illicit networks and (2) deploying a holistic strategy to improve interdiction and enhance the fight against sex trafficking.