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The purpose of this paper is to systematically review how agency and stakeholder theories are integrated within corporate governance and environmental disclosure practices in the UAE, highlighting their relevance and adaptation to a distinct economic and regulatory environment.

Using a comprehensive qualitative methodology, this study synthesises a broad spectrum of existing theoretical and empirical research to explore the dynamics of corporate governance mechanisms regarding environmental sustainability. This approach enables a detailed examination of how agency theory’s focus on principal–agent relationships complements stakeholder theory’s broader view of corporate responsibilities.

This research uncovers significant insights into corporate conduct and responsibility, emphasising the need to balance shareholder objectives with broader stakeholder interests. It identifies key challenges in this integration, such as managing the complexities and potential conflicts between different stakeholder demands. The findings underscore the crucial role of specialised governance mechanisms, like board characteristics and committees, in enhancing environmental transparency and accountability.

This study contributes to the academic discourse by shedding light on the interplay between corporate governance frameworks and environmental disclosure practices within the UAE. It offers fresh insights into applying established theories in a non-Western context. These insights are precious for academics, practitioners and policymakers interested in refining corporate governance and promoting environmental responsibility. The practical implications drawn from the findings empower stakeholders to implement effective strategies that can enhance a firm’s reputation, legitimacy and long-term viability.

The purpose of this paper assess the impact of the green finance pilot reform on corporate green innovation, leveraging the establishment of the China green finance pilot reform in 2018 as a quasi-natural experiment.

This study investigates the effects of environmental policies on green innovation, utilising a substantial data set from Chinese A-share listed firms over the 2015–2019 period. Employing both double and triple difference models, it focuses on how tax reforms influence green patent filings among these firms.

The study confirms that environmental tax policies and green finance initiatives significantly boost green patent filings in pollution-intensive industries. Findings from the regression analysis show robust positive effects from these policies, supporting the idea that stringent environmental regulations can spur innovation by offsetting regulatory costs. Financial health indicators like asset logs and return on assets positively correlated with innovation, emphasising the importance of financial stability. In addition, increased RandD spending is linked to enhanced green innovation, highlighting that financial investment in research is crucial for overcoming innovation barriers. These insights are crucial for shaping policies that integrate sustainability into corporate practices.

This research contributes to the literature by highlighting traditional views on the economic burden of environmental taxes and demonstrating their role as significant drivers of innovation. It deepens insights into strategically optimising fiscal tools to promote environmentally sustainable economic activities. In addition, it offers a practical framework for policymakers to improve ecological outcomes through effective fiscal strategies.

The purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.

This study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.

The study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.

The study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.

The results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.

This paper aims to investigate the adoption of International Financial Reporting Standards (IFRS) and International Public Sector Accounting Standards (IPSAS) and their impact on financial transparency, public sector accountability and economic performance across 173 jurisdictions from 2000 to 2022.

A robust quantitative approach using econometric panel data analysis with fixed- and random-effects models evaluates the effects of IFRS and IPSAS adoption. This study compares 69 adopting countries with 104 non-adopting or partially adopting nations, examining cross-country and temporal dynamics.

This paper provides compelling evidence that adopting IFRS and IPSAS significantly improves financial transparency and public sector accountability. Countries adopting these standards, mainly developed economies, experience increased foreign direct investment and improved sovereign credit ratings. The impact is more pronounced in nations with solid institutional frameworks while developing countries benefit from enhanced governance and reduced corruption, though to a lesser extent. These findings contribute to the literature by demonstrating how international accounting standards enhance governance quality and economic performance.

The study’s limitations include the availability and reliability of financial data in jurisdictions with weaker institutional systems. Future research should include longitudinal case studies and stakeholder analyses to explore the nuanced effects of IFRS and IPSAS adoption in different regions.

The results emphasise the need for tailored implementation strategies, especially for developing countries. Strengthening institutional frameworks, investing in capacity-building programmes and enhancing financial literacy are essential to maximising the benefits of IFRS and IPSAS adoption. Policymakers can leverage these standards to improve transparency, attract investment and promote economic stability.

By improving financial transparency and accountability, IFRS and IPSAS foster better governance, reduce corruption and promote more equitable resource distribution. These reforms have a particularly positive impact on developing countries, enhancing public trust, supporting social equity and encouraging sustainable economic development.

This paper provides a unique contribution to the discourse on global financial standards. It offers a comprehensive quantitative analysis of IFRS and IPSAS adoption over 23 years and valuable insights for policymakers and financial regulators seeking to strengthen governance and promote global economic integration.

The purpose of this paper is to provide a theoretical framework that integrates the endogenous growth and functions of financial markets and institutions theory in order to investigate how the financial market and the banking sector develop indicators that affect economic growth in these countries.

This paper is an empirical analysis of the relationship between financial development and economic growth for 42 emerging markets, over 12 years, using endogenous growth model.

First, the results suggest that stock market development has a significant effect on economic growth, and this effect remains strong even after the influence of banking sector and other control variables using a growth model. Second, the research findings largely support the view that there is a stable, long‐term equilibrium relationship between the evolution of the stock market and the evolution of the economy.

The evidence supports the view that the relation between stock market development and economic growth in emerging economies is bi‐directional. The findings describe that the stock market and the banking sector in emerging economy are complementary rather than substitutes in providing financial services to the economy.