Results 41 to 50 of about 5,672 (172)
ABSTRACT Environmental, social, and governance (ESG) is pivotal for firms and their stakeholders, highlighting the importance of organizational authenticity (OA) in mitigating information asymmetry between signalers and receivers, thereby enhancing effective communication of social strategies.
Jihun Choi, Young‐Kyu Kim, Taewoo Roh
wiley +1 more source
Too Old to Bother: CEO Age and Corporate Stakeholder Engagement
ABSTRACT We examine how CEO age, a key demographic attribute, affects corporate stakeholder engagement. Drawing on Upper Echelons Theory, we argue that older CEOs are less responsive to stakeholder concerns because of heightened conservatism, shorter time horizons, and greater risk aversion.
Mehwish Yousaf, Pascal Nguyen
wiley +1 more source
Sensegiving, ESG, and Firm Value: Mitigating Interpretive Uncertainty in South Korea
ABSTRACT As environmental, social, and governance (ESG) becomes central to corporate strategy, firms must navigate the tension between meeting stakeholder expectations and avoiding overinvestment. This study examines how interpretive uncertainty—arising from stakeholders' divergent cognitive frames—produces a nonlinear relationship between ESG ...
Yanghee Kim +3 more
wiley +1 more source
Recombining Knowledge for Climate Innovation: Evidence From US Energy Incumbents
ABSTRACT As the climate crisis intensifies, energy incumbents must strategically transform their fossil‐fueled legacies to remain competitive and sustainable. Yet, little is known about how internal knowledge architectures and external industry positions jointly shape their capacity for climate innovation.
Kyung‐Baek Min +2 more
wiley +1 more source
Internalization of Management Systems and Eco‐Product Innovation: The More the Better?
ABSTRACT Environmental challenges demand urgent and strategic responses from firms. Eco‐product innovation (EPI) is a key approach to reducing environmental impact while preserving competitiveness. This research analyses the relationship between EPI and the internalization of management system (MS) certifications, focusing on ISO 9001, ISO 14001, and ...
Alfonso Hernandez‐Vivanco +2 more
wiley +1 more source
Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley +1 more source
ABSTRACT This paper presents a quantitative assessment of Spanish companies' commitment to the United Nations Global Compact (UNGC) and the Sustainable Development Goals (SDGs). Analyzing over 1000 participating firms, we identify prioritization patterns and examine structural factors influencing SDG adherence.
Juan Laborda, Juan Pérez
wiley +1 more source
Plasmakristall‐4 Experiment: 10 Years of Operation in Orbit
ABSTRACT Plasmakristall‐4 (PK‐4) is a microgravity complex plasma laboratory operated for 10 years on board the International Space Station. Its main purpose is the particle‐resolved investigation of generic condensed matter phenomena using strongly coupled suspensions of microparticles immersed in low‐pressure gas‐discharge plasmas.
M. Pustylnik +3 more
wiley +1 more source
Flexible methods for species distribution modeling with small samples
Species distribution models (SDMs) predict where species live or could potentially live and are a key resource for ecological research and conservation decision‐making. However, current SDM methods often perform poorly for rare or inadequately sampled species, which include most species on earth, as well as most of those of the greatest conservation ...
Brian S. Maitner +4 more
wiley +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source

