In this comprehensive Encyclopedia, Matthijs Bal brings together over 190 international experts to present fresh perspectives on key concepts, theories and research in organizational psychology. Entries cover central topics in the field, such as performance and work family balance, as well as upcoming …

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Purpose This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations …

From September 2024 onwards we will start the development of an educational innovation for Dutch primary schools to design a dynamic school day (a school day in which sedentary learning is regularly interrupted by moments of physical activity) for their local context. A number of Dutch primary schools …

In the era of exponential technology growth, one unexpected guest has claimed a seat in classrooms worldwide, Artificial Intelligence. Generative AI, such as ChatGPT, promises a revolution in education, yet it arrives with a double-edged sword. Its potential for personalized learning is offset by issues …

This paper presents a Python script that automates the estimation of Yang & Zhang’s stock realized volatility proxy for univariate and multivariate cases. Yang & Zhang’s realized volatility is a stock volatility proxy commonly used by financial researchers and practitioners due to its unbiasedness in …

BACKGROUND: Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider …

This study proposes a novel loss function for neural network models that explores the topological structure of stock realized volatility (RV) data by adding Wasserstein Distance (WD). The study shows that the proposed loss statistically significantly improves the forecast accuracy of neural network models …

This paper addresses the challenge of assessing Energy Transition Readiness levels in businesses. It identifies gaps in existing literature concerning energy transitions and readiness levels. To tackle this, the paper employs organizational learning theory as its foundational model and introduces a new …

The role of central banks in addressing the emerging challenges posed by climate change has garnered significant attention from practitioners and academics alike. Through meticulous bibliometric analysis, this article reveals the fundamental themes and dynamic trends within this research field. Simultaneously, …