Exploring Constraints and Sport Experiences: A Case Study of Adult Workers in Singapore.

Although rapid economic growth can produce various positive outcomes, the fast-paced society that inevitably accompanies it often results in longer working hours and higher stress levels, leading to reduced participation in sport activities among employees. To better understand this phenomenon, we aimed to explore the constraints and experiences of adult workers. We collected data from adult workers in Singapore who desired to participate in sport activities but were unable to do so due to various constraints.

"Extending the Technology Acceptance Model (TAM) to Predict University Students' Intentions to Use Metaverse-Based Learning Platforms".

Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy.

Impacts of the COVID-19 pandemic on household food waste behaviour: A systematic review.

Food waste has adverse economic, social, and environmental impacts and increases the prevalence of food insecurity. Panic buying at the beginning of the COVID-19 outbreak raised serious concerns about a potential rise in food waste levels and higher pressure on waste management systems. This article aims to investigate the impact of COVID-19 on food waste behaviour and the extent to which it occurs using the systematic review method.

People's expectations and experiences of big data collection in the Saudi context.

Big data and machine learning technologies facilitate various business intelligence activities for businesses. However, personal data collection can generate adverse effects on consumers. Big data collection can compromise people's sense of autonomy, harming digital privacy, transparency and trust.

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis.

In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency.