arXiv subjects

Geri L. Dimas

Publications and source records attributed to Geri L. Dimas.

6 recordsLinked to original sources

arXiv2022

Perspectives on How To Conduct Responsible Anti-Human Trafficking Research in Operations and Analytics

Human trafficking, the commercial exploitation of individuals, is a gross violation of human rights and harms societies, economies, health and development. The related disciplines of Operations Management (OM), Analytics, and Operations Research (OR) are uniquely positioned to support trafficking prevention and intervention efforts by efficiently evaluating a plethora of decision alternatives, and providing quantitative, actionable insights. As operations and analytical efforts in the counter-trafficking field emerge, it is imperative to grasp subtle yet distinctive nuances associated with human trafficking. This note is intended to inform those practitioners working in the field by highlighting key features of human trafficking activity. We grouped nine themes around three broad categories: (1) representation of human trafficking, (2) consideration of survivors and communities, and (3) analytics related. These insights are derived from our collective experience in working in this area and substantiated by domain expertise.

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arXiv2022

On the Optimization of Benefit to Cost Ratios for Public Sector Decision Making

Decision making in the public sector centers on delivering resources and services for the common good, emphasizing an expansive set of objectives such as equity and efficiency, beyond immediate short term returns to reflect the broader cares of society and public beneficiaries. Cost-benefit analysis is a prevailing decision-making framework in the public sector that often uses the benefit to cost ratio (BCR) to compare viable alternatives, yet no systematic framework exists for evaluating many alternatives beyond the status quo of doing nothing. We propose a new framework to maximize the BCR for public sector decisions, seeking the largest improvement per marginal deployment of capacity. Requiring a status quo representable through (constrained) decision variables, the framework is generally applicable and useful to a broad set of decision contexts that involve maximizing the BCR for marginal deployments of resources. We demonstrate the applicability of our framework on a compelling case study for the New York City runaway and homeless youth shelter system, an area of high societal need. We represent this problem as a mixed integer linear fractional program (MILFP) and employ Dinkelbach's algorithm that converts the MILFP to a series of linearized mixed-integer optimization problems, making our approach tractable for fairly large problem instances. Our optimization-based algorithmic framework yields data-informed recommendations for making New York City shelter expansion decisions to better serve runaway and homeless youth, and generalizes to reveal managerial insights for optimizing the BCR. More broadly, our algorithmic decision making framework allows for iteration and comparison across multiple potential constraints ensuring action away from the status quo, thereby empowering effective assessment of marginal deployment of additional resources.

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arXiv2022

Improving Access to Housing and Supportive Services for Runaway and Homeless Youth: Reducing Vulnerability to Human Trafficking in New York City

Recent estimates indicate that there are over 1 million runaway and homeless youth and young adults (RHY) in the United States (US). Exposure to trauma, violence, and substance abuse, coupled with a lack of community support services, puts homeless youth at high risk of being exploited and trafficked. Although access to safe housing and supportive services such as physical and mental healthcare is an effective response to youths vulnerability towards being trafficked, the number of youth experiencing homelessness exceeds the capacity of available housing resources in most US communities. We undertake a RHY-informed, systematic, and data driven approach to project the collective capacity required by service providers to adequately meet the needs of homeless youth in New York City, including those most at risk of being trafficked. Our approach involves an integer linear programming model that extends the multiple multidimensional knapsack problem and is informed by partnerships with key stakeholders. The mathematical model allows for time-dependent allocation and capacity expansion, while incorporating stochastic youth arrivals and length of stays, services provided in a periodic fashion, and service delivery time windows. Our RHY and service provider-centered approach is an important step toward meeting the actual, rather than presumed, survival needs of vulnerable youth, particularly those at-risk of being trafficked.

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arXiv2022

Discrete Event Simulation to Evaluate Shelter Capacity Expansion Options for LGBTQ+ Homeless Youth

The New York City (NYC) youth shelter system provides housing, counseling, and other support services to runaway and homeless youth and young adults (RHY). These resources reduce RHYs vulnerability to human trafficking, yet most shelters are unable to meet demand. This paper presents a Discrete Event Simulation (DES) model of a crisis-emergency and drop-in center for LGBTQ+ youth in NYC, which aims to analyze the current operations and test potential capacity expansion interventions. The model uses data from publicly available resources and interviews with service providers and key stakeholders. The simulated shelter has 66 crisis-emergency beds, offers five different support services, and serves on average 1,399 LGBTQ+ RHY per year. The capacity expansion interventions examined in this paper are adding crisis-emergency beds and psychiatric therapists. This application of DES serves as a tool to communicate with policymakers, funders, and service providers potentially having a strong humanitarian impact.

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arXiv2022

Estimating Effectiveness of Identifying Human Trafficking via Data Envelopment Analysis

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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arXiv2022

Operations Research and Analytics to Combat Human Trafficking: A Systematic Review of Academic Literature

Human trafficking is a widespread and compound social, economic, and human rights issue occurring in every region of the world. While there have been an increasing number of anti-human trafficking works from the Operations Research and Analytics domains in recent years, no systematic review of this literature currently exists. We fill this gap by providing a systematic literature review that identifies and classifies the body of Operations Research and Analytics research related to the anti-human trafficking domain, thereby illustrating the collective impact of the field to date. We classify 142 studies to identify current trends in methodologies, theoretical approaches, data sources, trafficking contexts, target regions, victim-survivor demographics, and focus within the well-established 4Ps principles. Using these findings, we discuss the extent to which the current literature aligns with the global demographics of human trafficking and identify existing research gaps to propose an agenda for Operations Research and Analytics researchers.

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