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Human Trafficking: Policy Intervention

Author

Listed:
  • John N. Mordeson

    (Department of Mathematics, Creighton University, Omaha, Nebraska 68178, USA)

  • Michel Mallenby

    (Department of Mathematics, Creighton University, Omaha, Nebraska 68178, USA)

  • Sunil Mathew

    (Department of Mathematics, National Institute of Technology, Calicut, 673601, Kerala, India)

  • Santanu Acharjee

    (Economics and Computational Rationality Group, Department of Mathematics, Debraj Roy College Golaghat 785621, Assam, India)

Abstract

In E. Lutz and R. Lotspich, sex markets and human trafficking: Cause–effect and policy interventions, The Protection Project Journal of Human Rights and Civil Society 2 (2009) 199–124, causal linkages between commercial sex and human trafficking were examined. A three-link chain of necessary conditions exists. All three are required for trafficking into commercial sex. Consequently, trafficking can be addressed by policy intervention at any link. Prospects for policy success at the three points of intervention were compared. It was shown that a strategy of suppressing sex markets is least likely to be successful in reducing the associated human trafficking. In this paper, we create a mathematical model of the work developed above. We use five methods to derive five different linear equations to measure the success of policy intervention. The methods are the analytical hierarchy process, the Guiasu method, the Dempster rule of combination method, the Yen method, and the set-valued statistical method. The equations are based on an expert’s opinion of the relative importance of the factors involved in sex trafficking. These equations are used to determine a measure of how well a particular state in the USA is doing in policy intervention.

Suggested Citation

  • John N. Mordeson & Michel Mallenby & Sunil Mathew & Santanu Acharjee, 2017. "Human Trafficking: Policy Intervention," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 341-358, November.
    • Handle: RePEc:wsi:nmncxx:v:13:y:2017:i:03:n:s1793005717400142
    DOI: 10.1142/S1793005717400142
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    References listed on IDEAS

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    1. Samuel Lee & Petra Persson, 2012. "Human Trafficking and Regulating Prostitution," Working Papers 12-07, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. John N. Mordeson & Terry D. Clark & Adam D. Grieser & Mark J. Wierman, 2007. "An Inductive Approach To Determining Causality In Comparative Politics: A Fuzzy Set Alternative," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 191-202.
    3. John N. Mordeson & Hilary C. Wething & Terry D. Clark, 2010. "A Fuzzy Mathematical Model Of Nuclear Stability," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 119-140.
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    Cited by:

    1. Santanu Acharjee & John N. Mordeson, 2017. "Soft Statistics with Respect to Utility and Application to Human Trafficking," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 289-310, November.

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