The paper examines the motivations, financing, expansion and challenges of the Belt and Road Initiative (BRI). The BRI was initially designed to address China’s overcapacity and promote economic growth in both China and in countries along the “Belt” and “Road” through infrastructure investment and industrial capacity cooperation. It took into account China’s strategic transition in its opening-up policy and foreign policy to pay more attention to the neighboring countries in Southeast Asia and Central and West Asia when facing greater strategic pressure from the United States in East Asia and the Pacific region. More themes have been added to the initiative’s original framework since its inception in 2013, including the vision of the BRI as China’s major solution to improve international economic cooperation and practice to build a “community of shared future for mankind”, and the idea of the Green Silk Road and the Digital Silk Road. Chinese state-owned enterprises and policy and commercial banks have dominated investment and financing for BRI projects, which explains the root of the problems and risks facing the initiative, such as unsustainable debt, non-transparency, corruption and low economic efficiency. Measures taken by China to tackle these problems, for example, mitigating the debt distress and improving debt sustainability, are unlikely to make a big difference anytime soon due to the tenacity of China’s long-held state-driven investment model.

Cross-border ecological cooperation is always a challenging issue. Ecological cooperation in the Guangdong-Hong Kong-Macao Greater Bay Area has its own uniqueness as it is cross-border cooperation under “One Country, Two Systems”, which is different from multinational cooperation or regional collaboration within one country. This paper analyses the cooperation documents of Guangdong, Hong Kong and Macao, official reports and academic literature, and then summarises the unique pattern of ecological cooperation in the Greater Bay Area under “One Country, Two Systems”. It outlines four characteristics: different priorities in ecological management of each side, case by base cooperation, government-dominated cooperation with low public participation, and huge institutional gap between three sides. This article also identifies several problems and causes: lack of common ecological targets for each side and effective cross-border regulative measures, cumbersome coordination in cross-border cooperation. Finally, four feasible recommendations have been put forwarded: creating new institutional arrangements under the context of “One Country, Two Systems”, establishing the efficient decision-making platform for the inter-city cooperation, introducing the market-based resource allocation, and encouraging public participation in ecological monitoring.

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.

Bibliometric analysis is a commonly used tool to assess scientific collaborations within the researchers, community, institution, regions and countries. The analysis of publication records can provide a wealth of information about scientific collaboration, including the number of publications, the impact of the publications, and the areas of research where collaborations are most common. By providing detailed information on the patterns and trends in scientific collaboration, these tools can help to inform policy decisions and promote the development of effective strategies to support and enhance scientific collaborations between countries. This study aimed to analyze and visualize the scientific collaboration between Japan and Russia, using bibliometric analysis of collaborative publications from the Web of Science (WoS) database. The analysis utilized the bibliometrix package within the R statistical program. The analysis covered a period of two decades, from 2000 to 2021. The results showed a slight decrease in co-authored publications, with an annual growth rate of −1.26%. The keywords and thematic trends analysis confirmed that physics is the most co-authored field between the two countries. The study also analyzed the collaboration network and research funding sources. Overall, the study provides valuable insights into the current state of scientific collaboration between Japan and Russia. The study also highlights the importance of research funding sources in promoting and sustaining scientific cooperation between countries. The analysis suggests that more efforts in government funding are needed to increase collaboration between the two countries in various fields.

Purpose: The paper aims to study the methodology and functional of Internal Audit (IA) during the transition to remote working methods necessitated by the COVID-19 pandemic crisis period. Design/methodology/approach: Data are collected over a sample of 352 internal audit departments in retail SMEs distributed in the Gulf Cooperation Council (GCC) region. The six variables are measured using a reflective model. An exploratory factor analysis is applied to gauge the measurement model’s validity and reliability. Findings: The research findings revealed that internal auditing within the Kingdom of Saudi Arabia (KSA) and the Qatari retail sector is not sufficiently advanced. The focus of internal auditing primarily revolves around compliance audits rather than performance audits, thereby limiting their degree of agility and strategy which negatively affects the IA methodology. Conversely, for the United Arab Emirates (UAE) retail companies the research hypotheses were validated showing an IA functions evolution, an IA reassurance and IA agility that are conducted throughout a remote working and a strategic design that affect positively IA working methodology. Originality: The originality impregnates by the fact that reviews of traditional audit working methods were updated and shaped according to the deficiencies that couldn’t be identified during a pre COVID-19 period. A traditional audit plan may not work in this situation. The originality of the study consists of estimating IA methodological review through an agile approach that provides internal reassurance and risk attenuation.

Cross-border infrastructure projects offer significant economic and social benefits for the Asia-Pacific region. If the required investment of $8 trillion in pan-Asian connectivity was made in the region’s infrastructure during 2010–2020, the total net income gains for developing Asia could reach about $12.98 trillion (in 2008 US dollars) during 2010–2020 and beyond, of which more than $4.43 trillion would be gained during 2010–2020 and nearly $8.55 trillion after 2020. Indeed, infrastructure connectivity helps improve regional productivity and competitiveness by facilitating the movement of goods, services and human resources, producing economies of scale, promoting trade and foreign direct investments, creating new business opportunities, stimulating inclusive industrialization and narrowing development gaps between communities, countries or sub-regions. Unfortunately, due to limited financing, progress in the development of cross-border infrastructure in the region is low.

This paper examines the key challenges faced in financing cross-border projects and discusses the roles that different stakeholders—national governments, state-owned enterprises, private sector, regional entities, development financing institutions (DFIs), affected people and civil society organizations—can play in facilitating the development of cross-border infrastructure in the region. In particular, this paper highlights the major risks that deter private sector investments and FDIs and provides recommendations to address these risks.