EurekAlert! News by Subject: Business & Economics - News by Subject: Business & Economics

Business & Economics

Updates every hour. Last Updated: 26-Dec-2025 13:11 ET (26-Dec-2025 18:11 GMT/UTC)

23-Jul-2025

California Latino GDP surges past $1 trillion, as Latinos help power state economy

University of California - Los Angeles
Reports and Proceedings

Earlier this year, the latest U.S. Latino GDP Report from UCLA and Cal Lutheran revealed that the direct economic output of the country’s Latino population exceeded $4 trillion for the first time. Now, new findings from the research team that a quarter of that came from Latinos in one state: California. The California Latino GDP Report shows that the state’s Latino GDP surpassed $1 trillion in 2023.

22-Jul-2025

Greenhouse gas accounting procedures in low carbon fuel policies overlook the spatial variability of miscanthus-derived sustainable aviation fuel

University of Illinois at Urbana-Champaign Institute for Sustainability, Energy, and Environment

Low carbon fuel policies are intended to reduce greenhouse gas (GHG) emissions from transportation. However, rigid carbon intensity (CI) accounting procedures in current policies may limit CI responsiveness across candidate sites and facilities. This study examines how low carbon fuel programs capture or overlook spatial variability and net electricity production in biofuel carbon intensity, influencing crediting outcomes and fuel selling prices.

Journal: ACS Sustainable Resource Management
Funder: DOE/US Department of Energy

22-Jul-2025

Hotel revenues are reaching a new high in Colorado

Virginia Tech
Peer-Reviewed Publication

A new Virginia Tech study highlights the impact of marijuana legalization on hotels.

Journal: Production and Operations Management

22-Jul-2025

Pusan National University researchers reveal new calibration framework for digital twins

Pusan National University
Peer-Reviewed Publication

Digital twins for automated material handling systems (AMHSs) of semiconductor and display fabrication industries suffer from parameter uncertainty and discrepancy. This leads to inaccurate predictions, ultimately affecting performance. To address this, researchers have developed a new Bayesian calibration framework that simultaneously accounts for both parameter uncertainty and discrepancy, improving the prediction accuracy of digital twin models. This innovative framework holds great potential for enhancing digital twin applicability across diverse industries.