Results 151 to 160 of about 25,725,996 (279)

Responsible leadership and sustainability performance in health systems: evidence from health and sanitation projects. [PDF]

Front Health Serv
Kyambade M, Mwesigwa R, Alinda K, Tumwine S, Lwanga F.   +4 more
europepmc   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Bridging the gaps in innovation research: A bibliometric analysis and multi-level framework integrating meso-perspectives and well-being. [PDF]

PLoS One
Elsamani Y, Mejia C, Kajikawa Y.
europepmc   +1 more source

Cross‐Sectoral AI Integration Is Essential to Tackling Food Waste and Food Insecurity: A Roadmap for Developing Resilient Food Systems

Advanced Intelligent Systems, EarlyView.
As food insecurity and global food demands surge, artificial intelligence (AI)‐based technologies offer promising opportunities to reduce food loss and waste. In this perspective, current AI adoption across the food supply chain is assessed using various academic, industry, and policy sources.
Akansha Prasad, Hannah Mann, Lubna Najm, Shadman Khan, Carlos D. M. Filipe, Tohid F. Didar   +5 more
wiley   +1 more source

Towards the development of a framework for monitoring and evaluating the multidimensional sustainability of healthcare organisations: a scoping review protocol. [PDF]

BMJ Open
Pain GCF, Chaves RLP, Zhao W, Haren MT, Gartner JB, Bergeron F, Côté A.   +6 more
europepmc   +1 more source

How Organizations Learn and Innovate to Institutionalize Generative AI: Trust, Feedback Loops, and Cultural Friction

AI &Innovation, EarlyView.
ABSTRACT This study examines how organizations advance in their use of Generative AI (GenAI) tools after initial adoption with particular attention to the dynamics of trust, cultural resistance, and feedback mechanisms. Grounded in organizational learning theory and institutional theory, we propose a framework that captures the factors influencing how ...
Surajit Bag, Gautam Srivastava, Santosh Kumar Shrivastav, Daniel Rees   +3 more
wiley   +1 more source

The impact of big data capabilities and business model innovation on new venture performance. [PDF]

PLoS One
Xiong X.
europepmc   +1 more source

AI Dependence as a Longitudinal Governance Problem

AI &Innovation, EarlyView.
ABSTRACT Artificial intelligence governance typically focuses on whether people rely on AI appropriately during individual decisions. This Perspective addresses a different question: whether repeated AI use changes the capabilities and alternatives available to users and organisations over time.
Yiran Du
wiley   +1 more source

The role of AI capabilities and entrepreneurial competency in SME performance: the mediating role of strategic intelligence. [PDF]

Front Artif Intell
Alsenan S, Al-Rahmi WM, Alyoussef IY, Dahri NA.   +3 more
europepmc   +1 more source

Causal analysis of trade loss from pathogens: A global study of foot and mouth disease impacts on meat exports

American Journal of Agricultural Economics, EarlyView.
Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman, Thomas L. Marsh   +1 more
wiley   +1 more source