Pia Ramchandani

Pia Ramchandani
  • Doctoral Candidate

Contact Information

  • office Address:

    533.3 Jon M. Huntsman Hall
    3730 Walnut Street
    Philadelphia, PA 19103

Research

  • Pia Ramchandani, Hamsa Bastani, Emily Wyatt (Under Review), Unmasking Human Trafficking Risk in Commercial Sex Supply Chains with Machine Learning.

    Abstract: The covert nature of sex trafficking provides a significant barrier to generating large-scale, data-driven insights to inform law enforcement, policy and social work. We leverage massive deep web data (collected globally from leading commercial sex websites) in tandem with a novel machine learning framework to unmask suspicious recruitment-to-sales pathways, thereby providing the first global network view of trafficking risk in commercial sex supply chains. This allows us to infer likely recruitment-to-sales trafficking routes of criminal entities, deceptive approaches used to recruit victims, and regional variations in recruitment vs. sales pressure. These insights can help law enforcement agencies along trafficking routes better coordinate efforts, as well as target local counter-trafficking policies and interventions towards exploitative behavior frequently exhibited in that region.

  • Pia Ramchandani, Hamsa Bastani, Ken Moon (Under Revision), Responsible Sourcing: The First Step Is the Hardest.

    Abstract: Responsible sourcing is a priority for companies and consumers concerned with corporate social responsibility (CSR) in global supply chains. Most brands' product lines contain just a few products certified by third parties- which suggests that brands limit their efforts at ensuring that suppliers behave responsibly. In this paper, we examine a previously under-appreciated role of certifications: that certifications enable brands to learn about how to source responsibly. By successfully certifying even a single product, the certifying brand may enjoy positive, knowledge-based spillovers encouraging responsible sourcing throughout its product line. Using data on the responsible sourcing decisions of coffee brands in the $48B US consumer market, we find that certifying brands' rates of CSR violations (adjusted for disparities in production volume and detection) are similarly low regardless of whether the brand's portfolio is 3% certified or 100% certified- consistent with learning-based spillover effects. Certifying brands' violation rates are an estimated 61-78% lower than for comparable brands that make no CSR claims. While we find that brands making their own uncertified, on-packaging CSR claims also exhibit low CSR violation rates, their low violation rates are nearly entirely explained by the countries from which they source. In contrast, certifying brands appear uniquely able to source responsibly even from within "high-risk" countries. Our work novelly suggests that prevalent dual-sourcing may surprisingly amplify, rather than limit, responsible sourcing in supply chains, and that certified sourcing valuably develops the pool of responsible suppliers in high-risk countries.

Awards and Honors

  • People‚Äôs Choice Award, Early-Career Sustainable OM Workshop, 2020