AI in Social Worker Recruitment and Training for Bullying Intervention DOI

Yvonne-Yvette Maota,

Tshepo Maota

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 30

Published: Feb. 21, 2025

Bullying in South African schools is a pervasive issue that requires comprehensive intervention strategies. This study explores the potential role of AI-powered technologies enhancing recruitment and training social workers for school-based bullying programs. The examines current state work practices Africa, identifying technological gaps opportunities AI-driven solutions. While various sectors have increasingly adopted AI, its integration into remains limited, according to findings. We provide recommendations policymakers, educators, technology developers bridge identified utilize AI enhance efficiency effectiveness

Language: Английский

Artificial intelligence, corporate information governance and ESG performance: Quasi-experimental evidence from China DOI
Xiaoyong Zhou, Gaochao Li, Qunwei Wang

et al.

International Review of Financial Analysis, Journal Year: 2025, Volume and Issue: unknown, P. 104087 - 104087

Published: March 1, 2025

Language: Английский

Citations

2
Can artificial intelligence technology reduce carbon emissions? A global perspective DOI
Qingfeng Cao, Chi Chen,

Junjie Shan

et al.

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108285 - 108285

Published: Feb. 1, 2025

Language: Английский

Citations

1
Unveiling Greenwashing: Analyzing the interaction of factors discouraging ESG Greenwashing through TISM and MICMAC DOI

Shikha Daga,

Kiran Yadav,

Dharmendra Singh

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124850 - 124850

Published: March 12, 2025

Language: Английский

Citations

1
Can artificial intelligence improve enterprise environmental performance: Evidence from China DOI

Junkai Wang,

Andong Wang,

Kaijie Luo

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 123079 - 123079

Published: Oct. 30, 2024

Language: Английский

Citations

6
Integrating AI in Food Contaminant Analysis: Enhancing Quality and Environmental Protection DOI Creative Commons
Kuppusamy Sathishkumar, Meivelu Moovendhan‬‬‬‬‬‬‬‬,

Loganathan Praburaman

et al.

Journal of Hazardous Materials Advances, Journal Year: 2024, Volume and Issue: unknown, P. 100509 - 100509

Published: Oct. 1, 2024

Language: Английский

Citations

4
Artificial intelligence and enterprise pollution emissions: From the perspective of energy transition DOI

Youcai Yang,

Xiaotong Niu,

Changgui Lin

et al.

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108349 - 108349

Published: March 1, 2025

Language: Английский

Citations

0
AI capability and environmental sustainability performance: Moderating role of green knowledge management DOI

Sachin Kumar,

Vinod Kumar, Ranjan Chaudhuri

et al.

Technology in Society, Journal Year: 2025, Volume and Issue: unknown, P. 102870 - 102870

Published: March 1, 2025

Language: Английский

Citations

0
Improving Corporate Environmental Performance Through Big Data Analytics Implementation: The Role of Industry Environment DOI Open Access

Ahmed Alyahya,

Gomaa Agag

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 2928 - 2928

Published: March 26, 2025

Big data analytics (BDA) has recently received significant public interest and is widely considered as a transformative technology set to improve organizations’ environmental performance. However, prior empirical studies have yielded inconsistent findings. Based on organizational learning theory, our paper utilized longitudinal approach understand the relationships between big implementation corporate This project also investigates role of industry environment in influencing these relationships. employed from 172 firms covering 2408 firm-year observations Fortune 200 firms. We “the generalized method moments (GMMs) technique” test study assumptions. Our analysis shows that one-unit improvement BDA leads to, average, 2.8% performance (CEP). In addition, impact CEP greater more complex dynamic settings. offers meaningful implications for scholars managers influence across various Moreover, this provides refined comprehension ramifications BDA, consequently addressing essential enquiries how when can

Language: Английский

Citations

0
Suppliers’ AI adoption and customers’ carbon emissions: firm-level evidence from China DOI
Feng Han, Qin Qi, Shengjie Zhou

et al.

Applied Economics, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 15

Published: March 27, 2025

Using panel data of Chinese listed firms from 2010 to 2021, we investigate whether and how suppliers' artificial intelligence (AI) adoption affects their customers' carbon emissions. We find that increased AI by supplier reduces emissions, this result is robust various tests. The main mechanisms are the innovation chain (measured green patents) capital (based on trade credit). Cross-sectional analyses reveal negative impact more pronounced for customers boasting higher ESG score, better absorptive capacity, lower resource endowments, or stronger coordination with suppliers. also show as adopt AI, own emissions rise, but downstream across multiple tiers fall. Our findings suggest a firm's position in supply determines positively negatively impacts its

Language: Английский

Citations

0
AI in Social Worker Recruitment and Training for Bullying Intervention DOI

Yvonne-Yvette Maota,

Tshepo Maota

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 30

Published: Feb. 21, 2025

Bullying in South African schools is a pervasive issue that requires comprehensive intervention strategies. This study explores the potential role of AI-powered technologies enhancing recruitment and training social workers for school-based bullying programs. The examines current state work practices Africa, identifying technological gaps opportunities AI-driven solutions. While various sectors have increasingly adopted AI, its integration into remains limited, according to findings. We provide recommendations policymakers, educators, technology developers bridge identified utilize AI enhance efficiency effectiveness

Language: Английский

Citations

0