The Bini people of Edo State, located in the Edo South senatorial district, have been the focus of a study investigating the impact of international migration on Nigerian infrastructure. The study employed a descriptive-qualitative approach, using a survey research methodology and structured questionnaires to gather data from 401 respondents. The study used regression and thematic analysis to examine the collected data, focusing on the connection between migration and the advancement of infrastructure. The findings suggest that low incomes, job insecurity, and the development of domestic infrastructure contribute to the momentum behind international migration movements. The study suggests that remittances from migrants and investments are needed to alleviate the situation, highlighting the need for a more inclusive and sustainable approach to addressing the challenges faced by the Bini people in Edo State.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

“Global South” is undoubtedly a broad term that typically refers to developing countries with varying degrees of economic, cultural and political influence. The rise of the Global South signifies the importance of reassessing the existing international order. In terms of international relations theory, this should be an innovative, progressive and reflective field of study. However, this research is predominantly led by the Western mainstream international relations theories. This often neglects the internal and external factors in the development processes of other countries, the formation of relationship frameworks, foreign policy formulation, and the need of foreign relations. Despite the ongoing and intense debate over the innovation of international relations theory, it is difficult to see it keeping pace with contemporary developments. Various schools and thoughts frequently innovate only within their foundational frameworks. Therefore, for Global South countries, there is the need for international relations theories that can reflect their specific needs and actual conditions. This does not only require breaking away from the westcentric theoretical framework, but ensuring that the innovation process is aligned with practical realities that recognize mutual interests and encompass both local and global perspectives. This approach should involve a comprehensive reflection on international relations, allowing innovation of international relations theories to genuinely “enter” the Global South countries.

This article examines the overseas corporate social responsibility (CSR) patterns of Chinese international contractors (CICs). Adopting an institutional and political economy approach, a unique dataset is constructed with country-specific contents drawn from CSR-related reports and website information of 50 top CICs. This dataset provides a foundation for systematic content analysis of CICs’ overseas CSR practices, revealing that both political legitimacy-seeking and strategic competitiveness-seeking motivations drive CICs’ CSR activities abroad, characterized by the prioritization of customer and community engagement. The findings highlight the coexistence of the exogenous pressures for the national image-building purpose and the endogenous awareness of CSR strategic importance for corporate internationalization. The hybridization of political and economic rationales is presented as the defining feature of CICs’ current overseas CSR patterns, with the balance between them being determined by stakeholder type and internal business needs influenced by corporate internationalization experience.

This research explores the relationship between the independent variables (need for achievement, risk-taking, family support, economic factors, and the dependent variable of women’s enterprises’ success) and examines the moderating influence of socio-cultural factors. A survey-based methodology was adopted. One hundred sixty-nine small and medium-sized enterprises (SMEs) in the Palestinian West Bank were surveyed using structured questionnaires. Structural equation modeling (SEM) was conducted by using the Smart-PLS program. The results indicate that women entrepreneurs’ success in SMEs is positively and significantly impacted by the need for achievement as an internal factor and economic factors and family support as external factors. Furthermore, sociocultural factors did not show any significant moderating influence. By gaining knowledge about the relationship between internal and external factors and the success of women-owned SMEs, this study adds to the body of literature already in existence. These factors can be considered in the success of these enterprises, particularly in an environment full of political and economic fluctuations. Furthermore, the research is said to be the first of its type in Palestine, particularly concerning SMEs run by women. It also supports entrepreneurs by providing them with resources that might aid in the growth and success of their businesses.

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.