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.

In today’s fast-moving, disrupted business environment, supply chain risk management is crucial. More critically, Industry 4.0 has conferred competitive advantages on supply chains through the integration of digital technologies into manufacturing and logistics, but it also implies several challenges and opportunities regarding the management of these risks. This paper looks at some ways emerging technologies, especially Artificial Intelligence (AI), help address pressing concerns about the management of risk and sustainability in logistics and supply chains. The study, using a systemic literature review (SLR) backed by a mapping study based on the Scopus database, reveals the main themes and gaps of prior studies. The findings indicate that AI can substantially enhance resilience through early risk identification, optimizing operations, enriching decision-making, and ensuring transparency throughout the value chain. The key message from the study is to bring out what technology contributes to rendering supply chains resilient against today’s uncertainties.

The technological development and the rise of artificial intelligence are driving a significant transformation of the labor market. The technological unemployment predicted by Keynes poses challenges for the global labor market that require new solutions. Basic income research has become a significant field of study, attracting attention from various disciplines such as political science, law, economics, and sociology. The aim of this paper is to explore on the basis of a literature review, what factors influence the support for basic income among the population. A systematic literature review based on the Web of Science and Scopus databases, after screening 2623 publications, identified 23 articles that contained findings relevant to the research question. A significant number of authors (12/23) analyzed data from the same source, the European Social Survey 2016 (ESS Round 8, 2020), conducted in 2016, first published in 2017 and updated several times since then. The paper shows that the study of the topic has a strong European focus. The social, economic, social and cultural diversity of European countries makes these studies important from a European and EU perspective, but from an international perspective, further research on the topic is needed.

Infrastructure decision-making has traditionally been focused on the use of cost-benefit analysis (CBA) and multicriteria decision analysis (MCDA). Nevertheless, there remains no consensus in the infrastructure sector regarding a favored approach that comprehensively integrates resilience principles with those tools. This review focuses on how resilience has been evaluated in infrastructure projects. Initially, 400 papers were sourced from Web of Science and Scopus. After a preliminary review, 103 papers were selected, and ultimately, the focus was narrowed down to 56 papers. The primary aim was to uncover limitations in both CBA and MCDA, exploring various strategies for amalgamating them and enhancing their potential to foster resilience, sustainability, and other infrastructure performance aspects. Results were classified based on different rationalities: i) objectivist, ii) conformist, iii) adjustive, and iv) reflexive. The analysis revealed that while both CBA and MCDA contribute to decision-making, their perceived strengths and weaknesses differ depending on the chosen rationality. Nonetheless, embracing a broader perspective, fostering participatory methods, and potentially integrating both approaches seem to offer more promising avenues for assessing the resilience of infrastructures. The goal of this research proposal is to devise an integrated approach for evaluating the long-term sustainability and resilience of infrastructure projects and constructed assets.