Results 91 to 100 of about 3,645 (233)
Corporate ESG Greenwashing: Does Regulatory Proximity Matter?
ABSTRACT Environmental, social, and governance (ESG) greenwashing undermines sustainable development, yet the influence of regulatory proximity on oversight is understudied. By introducing the “distance decay effect” from geoeconomics into ESG misconduct research and using a sample of Chinese listed firms from 2009 to 2022, this study reveals a ...
Weiqi Zhao +4 more
wiley +1 more source
The parameters of a level-set flame model are inferred using an ensemble of heteroscedastic Bayesian neural networks (BayNNEs). The neural networks are trained on a library of 1.7 million observations of 8500 simulations of the flame edge, obtained using
Juniper, MP, Croci, ML, Sengupta, U, ,
core
ABSTRACT This study analyses the association between carbon emissions and financial performance in Latin American firms. The scientific literature on this topic is limited, with little evidence available in this geographical region. This study aims to address this research gap by testing hypotheses focused on analysing how Scope 1, 2 and 3 carbon ...
Ana Isabel Mendieta‐Callirgos +3 more
wiley +1 more source
Heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures
Lachos, Victor H. +2 more
core +1 more source
ABSTRACT The transition to a circular economy (CE) has become a strategic priority for firms, yet empirical assessments of corporate circularity remain fragmented and heavily dependent on structured indicators or self‐reported metrics. This paper proposes a novel, text‐based circularity index derived from mandatory non‐financial statements of large ...
Giuseppe Pernagallo +2 more
wiley +1 more source
Variable selection methods in both the frequentist and Bayesian frameworks are powerful techniques that provide prediction and inference in high-dimensional linear regression models.
Zgodic, Anja
core
Target Firm's ESG Engagement and Post–M&A Performance: The Mediating Role of Acquirer's CSR Strategy
ABSTRACT The paper examines whether the environmental, social and governance (ESG) performance of target firms influences both accounting‐based and market‐based corporate financial performance (CFP) within the merger and acquisition (M&A) context and whether this relationship is mediated by the acquirer's corporate social responsibility (CSR) strategy.
Francesco Gangi +4 more
wiley +1 more source
Internationalization and ESG Controversies: Do Foreign Directors on Corporate Boards Matter?
ABSTRACT This study examines the relationship between internationalization and environmental, social, and governance (ESG) controversies, focusing on whether foreign directors on corporate boards influence this relationship. Drawing on resource dependence theory, we argue that internationalization increases ESG controversies due to the complexity of ...
Mohamed Elsayed +4 more
wiley +1 more source
Gaussian process regression with heteroscedastic or non-Gaussian residuals
Gaussian Process (GP) regression models typically assume that residuals are Gaussian and have the same variance for all observations. However, applications with input-dependent noise (heteroscedastic residuals) frequently arise in practice, as do ...
Chunyi Wang, Radford M. Neal
core
ABSTRACT Despite the critical role that state‐owned enterprises (SOEs) can play in the green transition, relatively little is known about governments' environmental behavior as foreign shareholders. This study examines the effect of state ownership on domestic and foreign environmental performance.
Pablo Torres, Germà Bel, Marc Esteve
wiley +1 more source

