Nashat Ali Almasria

The introduction of autonomous AI agents as active participants in the institutions is a qualitative change in the governance requirements facing organisations in the public sector, financial services and critical infrastructure. In contrast to the earlier generations of decision-support systems, AI agents do not simply enlighten human choices; they take consequential actions, coordinate multi-step work processes, and increasingly act in distributed multi-agent systems that decentralize responsibility and make it harder to monitor. The chapter states that the governance of AI agents is not appropriate to be addressed through compliance-oriented, checklist-driven approaches that are designed to be applicable to the systems that are static and rule-based

This study examines the association between environmental, social, and governance (ESG) rating divergence and firm value among Chinese A‐share firms. Using six ESG providers and a final fixed‐effects sample of 3532 firm‐year observations from 2019 to 2023, we find that greater ESG rating divergence is positively associated with log market capitalization. The association remains robust when alternative measures of divergence are used, winsorization, provider‐coverage restrictions, and additional financial and governance controls, and is concentrated in social‐rating divergence. Results are outcome‐sensitive: market‐to‐book remains positive and significant, whereas Tobin's Q measures are not statistically significant. These findings indicate that ESG rating divergence is associated with market capitalization but should not be interpreted as a universal valuation premium. The study highlights valuation measurement, provider coverage, and ESG heterogeneity as important boundary conditions in assessing the market relevance of ESG rating disagreement and the economic consequences of ESG rating.

Environmental, social, and governance (ESG) disclosure quality remains constrained by fragmented data, limited verifiability, and inconsistent reporting practices. This study examines whether artificial intelligence and blockchain are associated with perceived ESG disclosure quality and whether financial regulation conditions the artificial intelligence relationship while stakeholder engagement conditions the blockchain relationship. A cross-sectional survey produced 250 usable responses from professionals involved in finance, sustainability reporting, compliance, and corporate governance. Partial least squares structural equation modeling was conducted using SmartPLS 3. Artificial intelligence (β = 0.297, p < 0.001), blockchain (β = 0.142, p = 0.001), financial regulation (β = 0.190, p = 0.008), and stakeholder engagement (β = 0.340, p < 0.001) showed positive direct associations with ESG disclosure quality. Financial regulation positively moderated the relationship between artificial intelligence and ESG disclosure quality (β = 0.069, p = 0.020). The blockchain–stakeholder engagement interaction was not supported because its bias-corrected confidence interval included zero. The model explained 86.6% of the variance in ESG disclosure quality (R² = 0.866), while blindfolding indicated positive predictive relevance (Q² = 0.613). However, elevated construct-level collinearity and HTMT values require caution in interpreting the structural effects.

Information Systems (IS) play a critical role in managing and optimizing core business processes and financial operations within small and medium-sized enterprises (SMEs). Specifically, Cloud-based Accounting Information Systems (CAIS) represent a significant digital innovation that is reshaping accounting practices and financial management in SMEs. Despite growing adoption, limited empirical evidence exists on the organizational and governance factors influencing CAIS implementation in developing economies. This paper conducts empirical research primarily examining how organizational culture, organizational structure, and organizational support shape the effective adoption and usage of CAIS among SMEs in Jordan. In particular, the study explores the moderating role of Information Technology Governance (ITG) in the relationships between these organizational factors and CAIS usage. Drawing on the Information Systems and digital accounting literature, this study employs quantitative research design using PLS-SEM. An adapted model is derived from the Technology–Organization–Environment perspectives in adoption technological and contextual factors. Data was collected through a structured questionnaire from 397 Jordanian SME professionals across various managerial and accounting roles. The findings reveal that organizational culture exerts the strongest positive influence on CAIS adoption (β = 0.537, p < 0.001), followed by organizational structure (β = 0.296, p < 0.001) and organizational support (β = 0.226, p < 0.001). ITG also demonstrates a significant direct effect on CAIS adoption (β = 0.218, p < 0.001). Mediation analysis indicates that ITG significantly strengthens the relationship between organizational support and CAIS adoption (β = 0.089, p = 0.035), while its moderating effects on organizational culture and structure are not statistically significant. This research contributes to the digital accounting and Information Systems literature by providing nuanced insights into the conditional role of ITG in CAIS adoption, moving beyond traditional direct-effect models. From an empirical perspective, the findings recommend that policymakers and SME managers must priorities IT governance frameworks alongside organizational support mechanisms to facilitate effective CAIS implementation in emerging markets. Furthermore, prior studies have largely focused on technological determinants or direct effects of organizational factors, while providing limited insight into how IT governance shapes the relationship between organizational capabilities and CAIS adoption within SMEs in emerging economies.

This review is a critical analysis of 29 peer-reviewed articles that investigate the application of Artificial Intelligence (AI) and Natural Language Processing (NLP) innovations to transform financial decision-making using social media data. A systematic review and subsequent study selection was in connection with PRISMA scheme using relevancy to sentiment analysis, predictive modeling, fraud detection, and sustainability in financial ecosystems to select studies between 2021 and 2025. Using unstructured social media data, AI and NLP can greatly improve sentiment analysis, risk forecasting, and personalized financial services. Nevertheless, there are still fears of algorithmic secrecy, data bias, ethical responsibility, and privacy theft. The literature demands explainable AI (XAI), models that are fair, and solid governance structures that can guarantee transparency and trust. The review is a synthesis of developing evidence regarding the potential of AI-NLP to incorporate social media signals into finance to provide insights into sustainable, transparent, and ethical financial innovation.

Artificial Intelligence (AI), Blockchain, and Cloud Computing (CC) are key technologies to improve financial automation and risk management of developing countries in particular. The purpose of this research is to explore the combined impact of AI, Blockchain, and CC on financial automation and how it, in turn, affects improved risk management in financial institutions in Oman. This study adopted a quantitative method by conducting questionnaires with 201 financial and IT experts in banks and fintech firms in Oman using convenience and snowball sampling methods. The respondents were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) based on Technology-Organization-Environment (TOE) and Innovation Diffusion Theory (IDT). Results indicate that Blockchain (β = 0.561) and AI (β = 0.264) have a strong impact on financial automation, with a moderate positive influence observed for CC (β = 0.173). Financial automation has a significant positive effect on improved risk management (β = 0.827, R² = 0.81) and regulatory compliance, market responsiveness, and technology access. This research is novel in its integrated empirical model, which brings together three frontier technologies in one model and empirically validates their impact on financial performance and risk management in a developing country, offering practical insights for policymakers and financial practitioners.

This review summarises the research conducted towards practical application of Quality 4.0 in the supply chains by defining theoretical framework and models aimed at bridging the gap between Industry 4.0 technologies and already known quality management practises. The research comprehensively analyses the existing state of the art with regard to Quality 4.0 integration. Based on the previous studies review the Findings shows that adoption of quality 4.0 faces several challenges in supply chain context, the interaction between quality 4.0 and supply chain determined by organisational readiness, workforce competencies and leadership commitment become critical enablers while technological complexity and limited resource allocations provided hindrances to successful implementation.. The review calls for rigorous empirical validation and development of cross-sectoral frameworks which will help to develop intelligent and adaptive quality management systems in digitally transformed supply chains.

Integrated reporting (IR) has become a groundbreaking model that connects both financial and non-financial reporting in order to promote corporate transparency and value generation. Nonetheless, variations in implementation, governance frameworks, and digital integration constrain its effectiveness. This paper seeks to review the current trends in IR in the framework of the convergence of environmental, social, and governance (ESG), digital transformation, and Industry 5.0. Major academic databases were used to analyse 48 studies on the PRISMA method that were published between 2024 and 2025. It is found that technologies like artificial intelligence (AI), natural language processing (NLP), and blockchain can considerably enhance reporting accuracy and timeliness, but add ethical, regulatory, and standardisation issues. Quality of governance, diversity of boards, and ethical responsibility turn out to be key forces behind IR credibility. The paper concludes that IR is shifting from a symbolic tool of compliance to a strategic governance tool that is in line with stakeholder-centric and sustainability-oriented models. The study is an addition in that it incorporates digital ethics and governance innovation into the IR debate and provides policy-makers and organisations with harmonized and transparent reporting systems.

This study presents a bibliometric analysis of the evolving research landscape at the intersection of digital technology, corporate reporting, and disclosure practices. Analysing data from Web of Science, Scopus, and Dimensions (2015–2024), this study maps the intellectual structure of the field through citation, co-citation, and co-authorship networks, as well as keyword co-occurrence. Our findings reveal a significant academic shift toward digital themes, yet a persistent dominance of traditional domains such as financial reporting and governance. Notably, critical areas such as digital transformation, data analytics, risk management, and stakeholder engagement remain markedly underrepresented. This disconnect suggests a misalignment between scholarly focus and the practical challenges corporations face. The key implication of this work is that a significant realignment of research priorities is urgently needed to address critical practical challenges and ensure the relevance of academic output in the digital age. This study provides a comprehensive map of the field’s evolution and issues an urgent call for research to bridge the identified gap. The objective of this future work must be to transform corporate disclosures, making them resilient, technologically advanced (e.g., via interactive dashboards and blockchain audit trails), and directly responsive to a diverse array of stakeholders.