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Fuzzy Indices with Applications to Human Trafficking

Author

Listed:
  • John N. Mordeson

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

  • Aimee Schwab-McCoy

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

  • Sunil Mathew

    (#x2020;Department of Mathematics, National Institute of Technology, Calicut 673601, Kerala, India)

  • M. Binu

    (#x2020;Department of Mathematics, National Institute of Technology, Calicut 673601, Kerala, India)

Abstract

We develop indices that can be used to measure the susceptibility of a route to human trafficking. The susceptibility is based on data providing a measure of a country’s vulnerability for and its government response to human trafficking. The data was normalized and the Pearson correlation coefficient was used to determine the correlation between five types of government response and five types of vulnerability. It was determined that comparing government response values with vulnerability values yielded a negative correlation. Four routes through the Americas to the United States were examined. The indices of two of the measures agree on all four routes.

Suggested Citation

  • John N. Mordeson & Aimee Schwab-McCoy & Sunil Mathew & M. Binu, 2019. "Fuzzy Indices with Applications to Human Trafficking," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 411-425, November.
    • Handle: RePEc:wsi:nmncxx:v:15:y:2019:i:03:n:s1793005719500236
    DOI: 10.1142/S1793005719500236
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