Results 221 to 230 of about 31,007 (299)
ABSTRACT This study investigates how directors with environmental protection (EP) backgrounds influence corporate biodiversity concern (BIO) among Chinese A‐share listed firms from 2008 to 2023. Drawing on Upper Echelons Theory, we argue that directors' environmental expertise shapes firms' biodiversity strategies.
Chengming Huang +2 more
wiley +1 more source
ABSTRACT This study investigates the way sustainable innovation, conceptualized as a second‐order construct integrating sustainable orientation and innovation culture, impacts triple bottom line (TBL) performance. It also examines the mediating roles of product, process, organizational, and marketing innovations.
Nuno Fernandes Crespo +1 more
wiley +1 more source
Data-driven p-norms for estimating transmission loss coefficients in power systems. [PDF]
Montoya OD +2 more
europepmc +1 more source
ABSTRACT This study examines how digital strategic orientation (DSO) and environmental practices (EP) interact to shape innovation and performance among Chilean SMEs. Using survey data from 271 firms (February–May 2022), we estimate a generalized structured component analysis (GSCA) model that accommodates a nonrecursive relationship between DSO and EP.
Constanza Caicha‐Caroca +2 more
wiley +1 more source
Selected Methods for Designing Monetary and Fiscal Targeting Rules Within the Policy Mix Framework. [PDF]
Przybylska-Mazur A.
europepmc +1 more source
Abstract Applying a single parameter set to describe complex mammalian kinetics often is too simplistic, as it fails to capture sensitive cell‐to‐environment interactions that may be exploited to optimize production performance. To resolve this time dependency, intra‐experimental parameter shifts as part of design of dynamic experiments (DoDE) can be ...
Samuel Kienzle +7 more
wiley +1 more source
Reinforcement learning-based optimal control for stochastic opinion dynamics. [PDF]
Chen Y, Gao H, Mazalov VV, Liu Y.
europepmc +1 more source
Implementation of Machine Learning Models to Predict Functionality of Pea Flour From Its Composition
ABSTRACT Background and Objectives The goal of this research was to examine the relationship between the composition and functionality of pea flour using the following machine learning algorithms: linear regression, partial least squares regression (PLSR), Gaussian process regression (GPR), support vector regression, gradient‐boosted decision trees ...
Colten N. Nickerson +7 more
wiley +1 more source

