This study investigates the relationship between corporate social responsibility (CSR), capital structure, and financial distress in Jordan’s financial services sector. It tests the mediating effect of capital structure on the CSR-distress linkage. Utilizing a panel data regression approach, the analysis examines a sample of 35 Jordanian banks and insurance firms from 2015–2020. CSR is evaluated through content analysis of sustainability disclosures. Financial distress is measured using Altman’s Z-score model. The findings reveal an insignificant association between aggregated CSR engagement and bankruptcy risk. However, capital structure significantly mediates the impact of CSR on financial distress. Specifically, enhanced CSR enables higher leverage capacity, subsequently escalating distress risk. The results advance academic literature on the nuanced pathways linking CSR to financial vulnerability. For practitioners, optimally balancing CSR and financial sustainability is recommended to strengthen resilience. This study provides novel empirical evidence on the contingent nature of CSR financial impacts within Jordan’s understudied financial services sector. The conclusions offer timely insights to inform policies aimed at achieving sustainable and stable financial sector development.

This study examines the relationship between board diversity (in term of percentage of female board members, educational qualification, independent directors, interlocking directorship, and financial literacy) and earnings quality of listed insurance companies in Nigeria. The study used secondary data from the stock exchange fact books and audited financial statements of the selected companies. We adopted a quantitative research design in which data were analyzed using descriptive and inferential statistics. Three variants of regression model, namely pooled ordinary least square, fixed effects and random effects models were estimated. Results revealed that significant differences exist in board diversity and earnings quality across the listed insurance companies in Nigeria. Also, the impact of board diversity on earnings quality is positive and strong. That is, the higher the company’s board diversity the better the ability to generate quality earnings. The results suggest than insurance companies with large number of women on the board are more likely to generate higher quality earning than those dominated by men. The paper draws the attention of management of listed insurance companies to the need to comply with the code of corporate governance on board diversity to increase the number of women on the board and ensure that the board consists of educationally qualified members, and financial literate members. The study also draws the attention of Nigeria Stock Exchange Group (NSGG) and other regulatory authorities to the need for regulation that will make disclosure of directors’ personal information a regulatory disclosure.

Objectives: This research aimed to empirically examine the transformative impacts of Artificial Intelligence (AI) adoption on financial reporting quality in Jordanian banking, with internal controls as a hypothesized mediation mechanism. Methodology: Quantitative survey data was collected from 130 bank personnel. Multi-item reflective measures assessed AI adoption, internal controls, and financial reporting quality—structural equation modelling analysis relationships between constructs. Findings: The research tested four hypotheses grounded in agency and contingency theories. Confirmatory factor analysis demonstrated sound measurement models. Structural equation modelling revealed that AI adoption significantly transformed financial reporting quality. The mediating effect of internal controls on the AI-quality relationship was supported. Specifically, the path from AI adoption to quality was significant, indicating a positive impact. Despite internal controls strongly predicting quality, its mediating effect significantly shaped the degree of transformation driven by AI adoption. The indirect effect of AI on quality through internal controls was also significant. Findings imply a growing diffusion of AI applications in core financial reporting systems. Practical implications: Increasing AI applications focus on holistically transforming systems, reflecting committing adoption. Jordanian banks selectively leverage controls to moderate AI-induced transformations. Originality/value: This study provides essential real-world insights into how AI is adopted and impacts the Jordanian banking sector, a key player in a fast-evolving developing economy. By examining the role of internal controls, it deepens our understanding of how AI works in practice and offers practical advice for integrating technology effectively and improving information quality. Its mixed methods, unique context, and focus on AI’s impact on organizations significantly enrich academic literature. Recommendations: Banks should invest in integrated AI architectures, strategically strengthen critical controls to steer transformations, and incrementally translate AI innovations into core processes.

Village Finance System (SISKEUDES) is a village financial reporting application policy. The application of the SISKEUDES is as a form of accountability to be accessible and known by the community. However, communication problems, resources, knowledge and limited internet networks in many regions still cause problems in reporting process. The research used a qualitative descriptive method by conducting in-depth interviews and document analysis of Mamala Negeri SISKEUDES. The policy implementation model according to George Edward III was used as an analysis tool. This research was designed to be carried out for 5 (five) months to explore various data from various information regarding this research problem. The research findings are that the provision of facilities and infrastructure for Mamala Negeri supporting human resources is still limited, making it difficult to apply the SISKEUDES 2.0 application. Besides, the village also needs more systematic transaction planning, which allows each transaction to be recorded completely both planning and realization.

The presence of a crisis has consistently been an inherent aspect of the Supply Chain, mostly as a result of the substantial number of stakeholders involved and the intricate dynamics of their relationships. The objective of this study is to assess the potential of Big Data as a tool for planning risk management in Supply Chain crises. Specifically, it focuses on using computational analysis and modeling to quantitatively analyze financial risks. The “Web of Science—Elsevier” database was employed to fulfill the aims of this work by identifying relevant papers for the investigation. The data were inputted into VOS viewer, a software application used to construct and visualize bibliometric networks for subsequent research. Data processing indicates a significant rise in the quantity of publications and citations related to the topic over the past five years. Moreover, the study encompasses a wide variety of crisis types, with the COVID-19 pandemic being the most significant. Nevertheless, the cooperation among institutions is evidently limited. This has limited the theoretical progress of the field and may have contributed to the ambiguity in understanding the research issue.