Media Coverage

Adoption of telemedicine in emergency departments leads to better quality of care and patient satisfaction, according to a new study published in the INFORMS Journal Information Systems Research. Emergency room telemedicine adoption shortened average length of stay and wait time significantly based on New York emergency room data from 2010 to 2014. This is a crucial finding as emergency departments face overcrowding and critical shortages of emergency care physicians, particularly as COVID-19 stresses hospital capacity across the country.

Social media has forever changed our society and how people do business. A 2013 report by J.D. Power found nearly two-thirds of customers have used a company's social media site to connect with customer service. New research in the INFORMS journal Information Systems Research finds businesses that use Twitter as a social care channel are seeing a 19% increase in customer satisfaction.

It’s almost impossible for humans to draw unbiased maps, even when they’re trying. A new mathematical method developed by Cornell researchers can inject fairness into the fraught process of political redistricting – and proves that it takes more than good intent to create a fair and representative district. The two-step method, described in the paper, “Fairmandering: A Column Generation Heuristic for Fairness Optimized Political Districting,” first creates billions of potential electoral maps for each state, and then algorithmically identifies a range of possibilities meeting the desired criteria for fairness.

During JD's fourth annual tech summit JD Discovery (JDD) held on November 25^th in Beijing, JD has shared plans to build a digital and intelligent supply chain. JD-Y, JD's supply chain R&D unit (focused on supply chain innovation) shared a relevant breakthrough and application regarding its self-built industry-leading end-to-end replenishment model (E2E model).

In developing COVID-19 policies and managing supply chains the constant drumbeat is “data-driven decisions” where the new high priests are data scientists. Data by itself is not sufficient, the missing critical success factor is “models” to project the impact of decisions. One critical area for COVID-19 public policy is understanding the impact of different group sizes on the spread of COVID-19. This blog will provide a few examples of being “COVID-19 data adrift without operations management” and illustrate that a simple model that can be coded in a few hours provides more insight than is possible with just data for the group size question.