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An interdependent network interdiction model for disrupting sex trafficking networks

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  • Xiaodan Xie
  • Felipe Aros‐Vera

Abstract

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.

Suggested Citation

  • Xiaodan Xie & Felipe Aros‐Vera, 2022. "An interdependent network interdiction model for disrupting sex trafficking networks," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2695-2713, June.
    • Handle: RePEc:bla:popmgt:v:31:y:2022:i:6:p:2695-2713
    DOI: 10.1111/poms.13713
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    References listed on IDEAS

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    1. Nail Orkun Baycik & Thomas C. Sharkey & Chase E. Rainwater, 2018. "Interdicting layered physical and information flow networks," IISE Transactions, Taylor & Francis Journals, vol. 50(4), pages 316-331, April.
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    6. Burcu B. Keskin & Gregory J. Bott & Nickolas K. Freeman, 2021. "Cracking Sex Trafficking: Data Analysis, Pattern Recognition, and Path Prediction," Production and Operations Management, Production and Operations Management Society, vol. 30(4), pages 1110-1135, April.
    7. Maass, Kayse Lee & Trapp, Andrew C. & Konrad, Renata, 2020. "Optimizing placement of residential shelters for human trafficking survivors," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    8. Konrad, Renata A. & Trapp, Andrew C. & Palmbach, Timothy M. & Blom, Jeffrey S., 2017. "Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications," European Journal of Operational Research, Elsevier, vol. 259(2), pages 733-745.
    9. András Kővári & Erik Pruyt, 2014. "A Model-Based Exploration and Policy Analysis Related to Prostitution and Human Trafficking," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 3(4), pages 36-64, October.
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    Cited by:

    1. Xiang, Yin, 2023. "Minimizing the maximal reliable path with a nodal interdiction model considering resource sharing," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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