Results 81 to 90 of about 15,975 (254)
Does the CEO's Attention Affect How Well the Firm Performs Environmentally?
Business Strategy and the Environment, EarlyView.ABSTRACT This study explores whether CEOs' environmental attention (CEA) enhances firms' environmental performance. Drawing on attention‐based and upper echelons theories, which emphasize that executives' cognitive focus shapes organizational outcomes, we argue that CEOs who devote greater attention to environmental issues are more likely to integrate ...
Salah Aldain Abdullah Alshorman +2 more
wiley +1 more source
European Journal of Personality, EarlyView., 2020 Abstract Personality can be described at different levels of abstraction. Whereas the Big Five domains are the dominant level of analysis, several researchers have called for more fine‐grained approaches, such as facet‐level analysis. Personality facets allow more comprehensive descriptions, more accurate predictions of outcomes, and a better ...
Daniel Danner +4 more
wiley +1 more source
Variational Bayes under Model Misspecification
CoRR, 2019 Variational Bayes (VB) is a scalable alternative to Markov chain Monte Carlo (MCMC) for Bayesian posterior inference. Though popular, VB comes with few theoretical guarantees, most of which focus on well-specified models. However, models are rarely well-specified in practice. In this work, we study VB under model misspecification.
Yixin Wang 0002, David M. Blei
openaire +3 more sources
Business Strategy and the Environment, EarlyView.ABSTRACT ESG ratings, and in particular environmental scores (E‐scores), are becoming increasingly relevant for financial stability and capital allocation decisions. This paper investigates the relationship between corporate environmental performance and market risk, as measured through value at risk (VaR) and expected shortfall (ES), the key metrics ...
Matilda Shini +3 more
wiley +1 more source
Robust Portfolio Optimization with Environmental, Social, and Corporate Governance Preference
RisksThis study addresses the crucial but under-explored topic of ambiguity aversion, i.e., model misspecification, in the area of environmental, social, and corporate governance (ESG) within portfolio decisions.
Marcos Escobar-Anel, Yiyao Jiao
doaj +1 more source
Generalized Bayes approach to inverse problems with model misspecification. [PDF]
Inverse Probl, 2023 Baek Y, Aquino W, Mukherjee S.
europepmc +1 more source
Measuring the Burden of Choice: Development and Validation of a Choice Overload Scale
Journal of Consumer Behaviour, EarlyView.ABSTRACT Excessive choice imposes substantial cognitive demands on consumers, impairs decision‐making, and generates negative consumer responses—a phenomenon widely known as the choice overload effect. Despite its conceptual prominence in consumer research and its enduring relevance in today's consumer markets, existing approaches to measuring choice ...
Jennifer Musial
wiley +1 more source
Copula‐based joint modelling of emergency department visits with time‐varying dependence
Canadian Journal of Statistics, EarlyView.Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley +1 more source
Canadian Journal of Statistics, EarlyView.Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen +3 more
wiley +1 more source
Vine copula knockoffs for variable selection in gene expression studies
Canadian Journal of Statistics, EarlyView.Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina +3 more
wiley +1 more source