Media Coverage

“This book on men has a vital message and a model to follow,” Mitch Daniels’s Jan. 4 op-ed on the recent reissuance of the book, “Men Without Work: America’s Invisible Crisis,” was thoughtful. But he violated his own message of considering various perspectives without declaring certainty in his main example regarding the Great Barrington Declaration signers. His conclusion that “the condemnation they incurred was profoundly anti-intellectual and anti-scientific” was defensible, but his declaration that pandemic lockdown policies were unequivocally a “net negative” was not, as it was implicitly predicated on how objectives are weighted.

By imposing one of its largest penalties, the CPSC is sending 'is a loud and clear warning to companies who continue to sell dangerous products.

Returns have been growing year over year, creating millions of pounds of waste and needless emissions from shipping. Major retailers are starting to charge for returns, which could have a positive impact on the environment.

New Year’s resolutions are not commitments to change. If a person is committed to make positive and constructive changes, a specific date such as Jan. 1 is not necessary. Any day can do.

A new research in the INFORMS journal Manufacturing & Service Operations Management finds that Medicare Advantage (MA), the largest healthcare capitation program in the U.S., unintentionally incentivises health plans to cherry-pick profitable patients from traditional Medicare (TM). The study, “Can Big Data Cure Risk Selection in Healthcare Capitation Program? A Game Theoretical Analysis,” shows that even if the current MA risk adjustment design became informationally perfect through increased availability of big data, incentives would continue to persist for risk selection, primarily because of the way the current risk adjustment model is designed. Co-author SMU Assistant Professor of Operations Management Zhaowei She said, “No generic risk adjustment algorithm can solve the strategic prediction problem in risk adjustment without explicitly taking into account the underlying mechanism in healthcare capitation programs.” The study calls for practitioners and policymakers to change their views of seeing risk adjustment as a pure statistical and machine learning problem and to look more comprehensively at the human impact.