Unmasking Human Trafficking Risk in Commercial Sex Supply Chains with Machine Learning
Published Online:18 Mar 2025https://doi.org/10.1287/msom.2022.0304
- Cited by
- 17 December 2025 | Manufacturing & Service Operations Management, Vol. 28, No. 2
- 12 February 2026 | Operations Research, Vol. 0, No. 0
- International Journal of Information Management, Vol. 86
- 29 September 2025 | Journal of Human Trafficking, Vol. 49
Volume 27, Issue 3
May-June 2025
Pages iv-xx, 679-992, C2
Article Information
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- Received:June 22, 2022
- Accepted:December 08, 2024
- Published Online:March 18, 2025
Copyright © 2025, INFORMS
Cite as
Pia Ramchandani; , Hamsa Bastani; , Emily Wyatt (2025) Unmasking Human Trafficking Risk in Commercial Sex Supply Chains with Machine Learning. Manufacturing & Service Operations Management 27(3):700-719.
https://doi.org/10.1287/msom.2022.0304
Keywords
The authors are grateful to Chris Dickson and Danielle Smalls of Uncharted Software for assistance with curating and contextualizing the core deep web dataset, as well as Carolina Holderness and Pierre Griffith of the Human Trafficking Response Unit at the Manhattan District Attorney’s Office for providing invaluable domain insights. The authors also thank Tsai-Hsuan Chung for collecting auxiliary data in support of this work, and David Jonker for helpful comments on an earlier draft.
