Public-Private Partnerships (PPPs) are mostly presented as a means to introduce efficient procurement methods and better value for money to taxpayers. However, the complexity of the PPP mechanism, their lack of transparency, accounting rules and implicit liabilities make it often impossible to perceive the amount of public expenditure involved and the long-run impact on taxpayers, providing room for fiscal illusion, i.e., the illusion that PPPs are much less expensive than traditional public investments. This psaper, thanks to a systematic review of the literature on the EU countries experience, tries to unveil the sources of this illusion by looking at the reasons behind the PPPs’ choice, their real costs, and the sources of fiscal risks. The literature suggests that PPPs are more costly than public funding, especially when contingent liabilities are not taken into account, and are employed as mechanisms to circumvent budgetary restrictions and to spend off-balance. The paper concludes that the public sector should share more risks with private sectors by reducing the amount of guarantees, and should prevent governments from operating through a sleight of hand that deflects attention away from off-balance financing, by applying a neutral fiscal recording system.

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

This article presents a bibliographic review on the evolution of Geographic Information Systems (GIS) and their integration in the social sciences, which is important because the interrelation of these areas contributes to the knowledge of the people. In this sense, the objective was to contribute to the university academic knowledge, through the compilation, classification, analysis and synthesis of scientific works according to the subject treated. For this purpose, the historical, synthetic, dialectical, and analytical methods were used, with a descriptive and documentary type of research, obtaining as a result that the GIS are very useful in different fields of social sciences, ranging from archeology to sociology, including specific topics such as economics and criminology.

Business model innovation (BMI) has garnered substantial academic and corporate attention in recent decades. Researchers have not yet agreed on the most complicated BMI practices in the high-tech startups (HTS). Despite being the second-biggest economy in the world today, China has done little research on the practice of business model innovation in China’s high-tech startups. This study addresses the factors that impact the business model innovation of high-tech startups in China. Our study aims to fill the research gap by visualising and analysing, using systematic literature review (SLR) analyses and reviewing 36 in-depth articles, from 688 academic literature sources. Relevant publications from Scopus, Springer, ScienceDirect, Web of Science, IEEE Xplore, and the JDM e-library expose the current research status from 2013 to December 2023 without bias. We conducted a literature-based investigation to identify essential insights on the BMI factors in the literature and derived a high-tech startup’s BMI critical factor. Our study shows that three main factors affect the innovation of business models in high-tech startups in China. The findings raise managers’, entrepreneurs’, and executives’ knowledge of corporate resource bricolage and cognitive style constraints in business model innovation and their pros and cons. The findings will help Chinese academics understand enterprises’ institutional environment and resource bricolage as final suggestions and proposals for corporates, regulators, and policymakers are presented.

Rapid urban expansion gives rise to smart cities which pose immense logistical and supply chain challenges. The COVID-19 pandemic transformed the holistic system identified by Zhao et al. in 2021. The system encompasses logistics and supply chain integral to the concept of smart cities, with a focus on sustainability. This transformation requires an in-depth study on challenges of a common framework of policies for smart cities in countries comprising the Organisation for Economic Cooperation and Development (OECD). The study employs an extensive literature analysis for the period 2020–2022. an approach which contextualizes the model. The model identifies the causes, impact, and spillovers of new trends in logistics and supply, including the sustainability of adopted technologies. The study includes the variables involved, and barriers to creating a shared model. The results reveal that the two elements affecting the supply chain and transport in smart cities are Industry 4.0 and 5.0 technologies supporting specific sectors. The resilience of small and medium-sized enterprises positively impacts the sustainability of large urban centres. The study presents both factors that help and hinder the adoption of environmental, social, and economic sustainability technologies.

In recent years, the construction of Jiafeng (家风)has become an important research topic in the field of street-level governance. A systematic literature review method is used to review 504 journal articles sourced from China National Knowledge Infrastructure (CNKI). The research overview is presented from the perspectives of overall research characteristics, highly cited literature, theoretical foundations, and research methods. The research systematically elaborates on the results of literature analysis from the perspective of the connotation and extension of Jiafeng, the practical mechanisms and related suggestions for Jiafeng construction. The research has found that the practical mechanisms of Jiafeng construction includes institutional support mechanism, theoretical consolidation mechanism, collaborative mechanism, social education mechanism, application innovation mechanism, and efficiency evaluation mechanism. On the basis of constructing a framework for the study of Jiafeng, this article provides prospects for future research: consolidating the theoretical foundation of Jiafeng construction, defining the connotation and extension of Jiafeng, refining the practical mechanism of Jiafeng construction, enriching the research methods of Jiafeng and measuring tools for governance effectiveness.