论文标题

通过数据包络分析估算识别人口贩运的有效性

Estimating Effectiveness of Identifying Human Trafficking via Data Envelopment Analysis

论文作者

Dimas, Geri L., Khalkhali, Malak El, Bender, Alex, Maass, Kayse Lee, Konrad, Renata, Blom, Jeffrey S., Zhu, Joe, Trapp, Andrew C.

论文摘要

过境监测是一种预防方法,用于在剥削前或在越过边界之前识别可能的人口贩运病例。过境监控通常是由非政府组织(NGO)进行的,他们培训员工以识别和拦截可疑活动。 Love Justice International(LJI)是一家公认的非政府组织,在多个监测站沿着尼泊尔 - 印度边境进行了多年的过境监测。与LJI合作,我们开发了一种系统,该系统使用数据包络分析(DEA)来帮助LJI决策者评估这些站点的绩效,以拦截潜在的人口贩运的受害者,鉴于可用的资源数量(例如,员工等)可用和组成的特定运营建议。我们的模型由来自13个季度的7个站点的91个决策单位(DMU)组成,并考虑了三个输入,四个输出和3个同质性标准。使用此模型,我们确定了有效的站点,比较了站点性能的排名以及提高效率的建议策略。据我们所知,这是DEA在反人类贩运领域中的第一个应用。

Transit monitoring is a preventative approach used to identify possible cases of human trafficking prior to exploitation while an individual is in transit or before one crosses a border. Transit monitoring is often conducted by non-governmental organizations (NGOs) who train staff to identify and intercept suspicious activity. Love Justice International (LJI) is a well-established NGO that has been conducting transit monitoring for years along the Nepal-India border at multiple monitoring stations. In partnership with LJI, we developed a system that uses data envelopment analysis (DEA) to help LJI decision-makers evaluate the performance of these stations at intercepting potential human-trafficking victims given the amount of resources (e.g. staff, etc.) available and make specific operational improvement recommendations. Our model consists of 91 decision-making units (DMUs) from 7 stations over 13 quarters and considers three inputs, four outputs, and 3 homogeneity criteria. Using this model we identified efficient stations, compared rankings of station performance, and recommended strategies to improve efficiency. To the best of our knowledge, this is the first application of DEA in the anti-human trafficking domain.

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