The shift away from fossil fuels can bring cleaner air, new jobs and major climate benefits. However, a new CMCC study finds that ensuring a just transition also requires giving affected communities a meaningful voice and respecting their identities, histories and ways of life. “The evidence shows that climate and environmental policies can deliver major benefits, but their costs and benefits may not affect everyone in the same way,” says CMCC researcher and lead author of the study Ireri Hernandez Carballo.

Unethical behavior inside organizations is often less sudden than companies assume. New research from ESMT Berlin shows how employees can collectively drift into misconduct as groups gradually reshape what they perceive as ethical or acceptable. 

New research from Texas A&M University examines what those competing effects mean for companies trying to manage demand through pricing, particularly for digital services where additional usage carries real costs.

The solution, Gupta found, is to tweak pay incentives. By rewarding doctors for prioritized follow-ups, healthcare systems can make them easier to get — and improve the systems’ own bottom lines.

“They’re able to ensure continuity of care, as opposed to letting the patient call two or three weeks later,” Gupta says. “If patients try to book an appointment with the same doctor, and they can’t, they might go to a different clinic or health system.”

University of Phoenix College of Doctoral Studies scholars affiliated with the Center for Educational and Instructional Technology Research (CEITR) have published a peer-reviewed study examining how higher education institutions can support graduate employability as workplace skill demands continue to change. Published in the International Journal of Innovative Business Strategies, as the article, “Graduate Employability in a Changing World,” the mixed-methods study draws on the perspectives of 380 graduates of U.S. colleges and universities and found strong agreement that employability is supported when academic learning is intentionally connected to careers, practical applications and opportunities to develop adaptable skills.

Executives increasingly turn to generative AI to help evaluate strategic decisions, from ranking business models to weighing competing options — but new research published in Strategic Management Journal cautions that no single AI-generated evaluation should be trusted at face value. The study finds that individual generative AI evaluations of strategic decisions are inconsistent and often biased, simply by the order in which two options are presented — but aggregating many evaluations across different prompts, roles, and models produces judgments that closely resemble those of human experts.

The research team of Anil R. Doshi of University College London, J. Jason Bell of the University of Oxford, and Emil Mirzayev and Bart Vanneste, both of University College London, tested large language models by having them rank 60 business models through pairwise comparisons, repeated across multiple models, ten assumed roles — including journalist, strategy professor, and industry expert — and two prompting strategies. No human expert panel evaluates the same option set that many ways, giving the researchers a rare way to measure where AI’s judgment holds up, and where it doesn’t.