Hussam Musa is professor of the Department of Finance and Accounting, at the Faculty of Economics, Matej Bel University in Banská Bystrica, Slovakia. His research is focused on the responsible and sustainable behaviour of businesses on the circular economy and ESG agenda. He specializes in financial health and performance of enterprises. He is a lecturer of Corporate Finance, International Finance and Financial Management in bachelor´s, master´s, and PhD. degree. He has published research papers in various journals indexed in Web of Science and Scopus. He is the author or co-author of articles and books, including the Handbook of Corporate Finance, Corporate Financial Accounting a management with application IAS/IFRS, International Finance, Islamic Finance and Banking, Financial tools in management of small and medium-sized enterprises. His research activities include/included cooperation in several projects of international and national importance (Internationalization of Accounting Education in Slovakia, European project LEONARDO, FINAC, VEGA, APVV, NISPAcee).

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Introduction

This section explores how environmental, social and governance (ESG) principles and artificial intelligence (AI) are shaping sustainable business and influencing economic performance and financial decision-making.
The section welcomes theoretical, empirical and methodological contributions from economics, finance, econometrics and business economics, across all sectors and regions. Topics include, but are not limited to, ESG measurement, disclosure and rating divergence, double materiality, AI-enabled sustainability analysis, responsible AI and its governance, sustainable investment and green finance instruments, corporate governance, responsible finance, climate and social risks, greenwashing and “AI-washing”, sustainable supply chains, the impact of AI on employment and skills, and sustainable business practices. Contributions may also investigate how regulation, technology and market conditions affect firms’ sustainability transitions, AI adoption and long-term competitiveness.
Papers applying econometric methods to assess relationships between ESG performance, AI adoption and financial or economic outcomes are particularly welcome. Studies using cross-country comparisons, sectoral analyses, case studies and novel data sources (e.g. textual, satellite, synthetic, AI-generated or other alternative data) are equally encouraged. We also invite papers examining AI’s potential to improve forecasting, resource allocation, climate risk assessment and sustainability reporting, alongside concerns about bias, transparency, explainability, accountability, data governance and the reliability of AI-generated sustainability information and synthetic data.
By bringing together multidisciplinary perspectives, this section aims to advance understanding of how ESG integration and responsible AI can support resilient economies and sound decision-making in the context of the green and digital transition. It welcomes evidence-based insights relevant to academics, business leaders and policymakers concerned with responsible growth, investment and corporate strategy, as well as practical recommendations for organizations seeking to strengthen accountability, innovation and long-term value creation.

Related topics for this special session (but not limited to):

• Economic and Financial Performance;
• International Economics Relationships, Behavioural Economics and Decision Making;
• Tax;
• Industry 4.0;
• Circular Economic, Corporate Social Responsibility, Econometrics;
• Business Economics;
• Finance; Sustainable Business Practices; Responsible AI;
• ESG Measurement and Reporting.