Results 181 to 190 of about 115,144,832 (243)

A Meta‐Analytic Review of Board Characteristics and Carbon Emission Disclosure: The Moderating Effect of Contextual Factors

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT The relationship between board governance and corporate carbon emission disclosure remains persistently inconsistent across the empirical literature, despite decades of accumulated evidence. Drawing on agency, stakeholder, legitimacy, institutional, and upper echelons perspectives within a single analytical framework, we conduct a three‐level ...
Mohamed Hegazy   +2 more
wiley   +1 more source

Environmental Transparency Through Digital Transformation: Evidence on Carbon Disclosure Quality From China's Heavy‐Polluting Firms

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT The rise of digital transformation (DT) has become an important driver of transparency in corporate environmental disclosure. Whether and how DT is related to the improvement of carbon information disclosure quality, particularly in heavily polluting firms that may have both information and symbolic roles, is still controversial.
Ruixiang Xue   +2 more
wiley   +1 more source

Detection and evaluation of clusters within sequential data. [PDF]

open access: yesData Min Knowl Discov
Van Werde A   +3 more
europepmc   +1 more source

The Virial Expansion of the Hydrogen Equation of State in Comparison to PIMC Simulations: The Quasiparticle Concept, IPD, and Ionization Degree

open access: yesContributions to Plasma Physics, EarlyView.
ABSTRACT The properties of plasmas in the low‐density limit are described by virial expansions. Analytical expressions are known for the lowest virial coefficients from Green's function approaches. Recently, accurate path‐integral Monte Carlo (PIMC) simulations were performed for the hydrogen plasma at low densities by Filinov and Bonitz (Phys. Rev.
Gerd Röpke   +3 more
wiley   +1 more source

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

open access: yesDeep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang   +3 more
wiley   +1 more source

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