The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

With the rapid development of modern AI painting, Chinese university fine arts education is facing numerous challenges and opportunities. This paper analyzes the impact of modern AI painting on traditional art creation and its implications for student skill development. Additionally, it explores the key areas where Chinese university fine arts education needs to transform, including curriculum, teaching methods, and teacher training, while proposing corresponding strategies.

With the implementation of China’s national strategy of “Culture Going-out”, it is important to translate Qingdao folk culture well in order to promote the effective communication of Qingdao folk culture worldwide. However, the uniqueness of folk culture poses certain difficulties for translation. Skopos theory can effectively guide the translation of Qingdao folk culture. From the perspective of this theory, the author analyzes the principles and strategies of English translation of Qingdao folk culture and proposes four translation methods, such as literal translation with notes, equivalent translation, phonetic translation with notes and free translation. Translators can choose the appropriate translation methods according to specific translation purposes.

This study analyzes the studies on project finance (PF) and renewable energy (RE) arena, employing a comprehensive scientometric analysis to illuminate the current research landscape, identify prominent scholars, and uncover emerging trends. Encompassing several analyses, we have charted the evolution of this domain from 1993 to March 2024 and showed the way for further research. We analyzed 80 studies selected from several databases by means scientometric tools. Despite decent citation rates, research in this relatively young field is surprisingly scarce. While geographically diverse, research leadership stems from the UK, USA, Australia, and Germany. Interestingly, a significant portion of the studies originates from broad energy and sustainability areas, highlighting a potential knowledge gap in finance and economics areas. Additionally, the prevalence of case studies points to a strong connection between theory and practice. The research also revealed prominent topics like the interplay between PF and RE, various renewable resources, infrastructure development, financial considerations, risk management, among others. While many themes exist, areas like technological advancements, diverse cost approaches, valuation methodologies, and policy considerations remain underexplored. Other results unveiled an unexpected finding: limited evidence of large-scale collaborations, with individual or small-group research efforts currently dominating the field. However, existing collaborative networks promise future advancements through the emergence of more formalized research groups, which can perform future research endeavors with a wide spectrum of unexplored topics.

Design and procurement integration strategies in construction projects play an important role and have an impact on the overall project cycle. Integrated design and procurement will increase productivity and reduce waste. This research aims to provide a guide to good design and procurement integration strategies in Design and Build (DB) projects in government projects. This research uses qualitative and quantitative methods in the form of a schematic literature review followed by a Focus Group Discussion (FGD) with the Delphi method to formulate integrated design and procurement that improve project performance. In-depth interviews were conducted with 90 respondents to explore the implementation of the design and procurement strategy on the project used as a case study. The results of this research are recommendations for an integrated design and procurement strategy which can be used as a Standard Operating Procedure (SOP) in DB projects on government projects so that it can provide added value from the start of the project being designed through tenders. This research can be utilized by project stakeholders, academics and anyone who will develop project performance through the integrated design and procurement in the long term.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.