Results 131 to 140 of about 16,203 (295)
Breadth at the Helm: Generalist CEOs and Corporate ESG Performance‐Evidence From China
ABSTRACT Drawing on the Upper Echelons Theory and the Imprinting Theory, this study conjectures that generalist CEOs may have a stronger tendency to pursue environmental, social and governance (ESG) goals. We perform multiple regression analyses with observations of Shanghai and Shenzhen A‐share listed companies from 2010 to 2023 in order to explore ...
Shanmei Luo +4 more
wiley +1 more source
Seats at the Table, Shifts in the Actions: Board Gender Diversity and Climate Activism
ABSTRACT As regulatory and stakeholder pressures intensify, firms are increasingly expected to move beyond symbolic sustainability commitments towards corporate climate activism. This concept refers to the active institutionalisation of climate‐focused mechanisms such as external assurance, board oversight and climate‐linked incentives.
Md Tanvir Hamim, Rasim Simsek
wiley +1 more source
ABSTRACT Public organisations often experience a discrepancy between improvements in technical efficiency and stakeholders' perceptions of integrity and performance. This study analyses the mechanisms that may underlie this efficiency–perception discrepancy in Spanish Defence Delegations during 2020–2023.
José Solana‐Ibáñez +1 more
wiley +1 more source
Abstract This study evaluates the potential of a new organic fertilizer derived from porcine intestinal mucosa (designated BHE), a by‐product of the heparin extraction process, as a sustainable nitrogen (N) source for agriculture. The work was conducted in two stages: (i) chemical and spectroscopic characterization of BHE compared with poultry litter ...
Aline Zanquetti +3 more
wiley +1 more source
Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus +7 more
wiley +1 more source
Variational Mode Decomposition and Linear Embeddings are What You Need For Time-Series Forecasting [PDF]
Time-series forecasting often faces challenges due to data volatility, which can lead to inaccurate predictions. Variational Mode Decomposition (VMD) has emerged as a promising technique to mitigate volatility by decomposing data into distinct modes ...
Yudistira, Novanto +2 more
core +1 more source
ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei +2 more
wiley +1 more source
This review highlights non‐thermal extraction technologies for seaweed proteins, emphasizing their mechanisms, impacts on protein structure and functionality, and sustainability potential. Key limitations related to species dependence, extract complexity, and scale‐up are discussed to guide future industrial and biorefinery applications.
Rahat Mahmud +3 more
wiley +1 more source
This study compares oxidative stability, fatty acid profiles, volatile compounds, and sensory attributes of four Xinjiang seed oils. Distinct aldehyde‐driven aroma patterns and compositional differences were revealed, providing a scientific basis for quality evaluation and valorization of underutilized plant seed oils in food applications.
Yilai Wan +4 more
wiley +1 more source
Forecasting With Dynamic Factor Models Estimated by Partial Least Squares
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley +1 more source

