BALTIMORE, MD, May 24, 2025 – Most anti-human trafficking efforts focus on breaking up sex sales; however, new research in the INFORMS journal Manufacturing & Service Operations Management is turning its attention to where trafficking truly begins – recruitment. Using machine learning to analyze millions of online ads, researchers at the University of Pennsylvania have uncovered patterns that link deceptive job offers to sex trafficking networks. By mapping the connections between recruitment and sales locations, the study reveals a hidden supply chain – one that can now be exposed and interrupted earlier in the trafficking process.
Drugs being explicitly developed to treat rare diseases are getting more expensive.
Old technology is behind the recent ongoing delays and cancellations at Newark Liberty International Airport, but newer technology will be an important part of the solution.
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Testing and vaccination for monkeypox became available in all Georgia health districts last week, according to the state health department.
Over the past two-plus years, global supply chains have been stretched beyond recognition. Yet stretched is not broken, and covid-19 may serve as the launch pad to create a new and improved global supply chain model.
The Biden administration’s response has made key mistakes in handling the emerging threat. We hope this situation serves as a wake-up call to rethink and re-tool emergency response policies and practices.
In the middle of the ongoing coronavirus pandemic, we're facing a second global, viral crisis: monkeypox.
If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? In times that continue to defy our ability to predict them, the words of famous statistician George Box have never been more right: “All models are wrong, but some are useful.” So what can we do to make models more useful? Artificial intelligence and machine learning (AI/ML) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves. For supply chains to get more use from their models, we need to “trust the box;” recognize that models are not the holy grail; and remember that a forecast is an input into making better decisions, not an end in and of itself.
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