The aim of our systematic review was to inspect the recently published literature on decentralized governance systems and integrate the insights it articulates on blockchain technology and smart contracts by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Throughout January and May 2022, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out, with search terms including “city” + “blockchain technology”, “smart contracts”, and “decentralized governance systems”. As the analyzed research studies were published between 2016 and 2022, only 371 sources satisfied the eligibility criteria. A Shiny app was harnessed for the PRISMA flow diagram to include evidence-based acquired and handled data. Analyzing the most recent and relevant sources and leveraging screening and quality assessment tools such as AMSTAR, Dedoose, Distiller SR, ROBIS, and SRDR, we integrated the core outcomes and robust correlations related to smart urban governance. As data visualization tools, for initial bibliometric mapping dimensions were harnessed, together with layout algorithms provided by VOSviewer. Future research should investigate smart contract governance of blockchain applications and infrastructure using decision-making tools and spatial cognition algorithms.

The global renewable energy landscape is changing rapidly. Green energies reduce greenhouse gas emissions, diversify the energy supply, and lower dependence on volatile and uncertain fossil fuel markets. The future looks promising for green energy sources, which are taking on an increasingly important role, especially in the current context, as governments are trying to identify viable solutions to the energy crisis and reduce dependence on fossil fuels. Worldwide, there is a growing interest in and support for green energy sources, a factor that could help accelerate the current energy transition. Despite these positive developments, much remains to be done globally to make the energy transition a reality. In this respect, the European Union member states have committed to a wide neutrality target by establishing an increase in the total share of energy from renewable sources to 55% (by 2030) and, at the same time, reducing the net greenhouse gas effect emissions by at least 55% until 2030 to reach the neutrality target by 2050. Green energy sources are essential for long-term efforts to mitigate climate change and will play an important role in improving energy security and accessibility. The efforts of every country to strengthen the energy sector through the development of green energies will reduce geopolitical risks and disproportionate external costs for society. The large-scale use of green energies will contribute to sustainable development. The objective of our research is to review the literature on green energy in the context of sustainable development by analyzing research conducted by various authors and international organizations on these topics. The period considered for this study is 2011–2020. Our research focused on the EU 27, but the review also took into account the results obtained by other countries worldwide, such as China, the USA, Norway, and Iceland. The main research method used was the analysis of scientific papers, studies developed by international organizations, and a wide set of agreements and political commitments assumed by different states for developing green energy as a solution for sustainable development. The obtained results show an interesting international debate about green energies and how they can contribute to sustainable development. This paper’s results also show that in 2019 at the global level, low-carbon energy sources, including nuclear power and renewable energy, accounted for 15.7% of primary energy (solar, wind, hydropower, bioenergy, geothermal and wave and tidal), while in 2021, for the EU 27, the share of energy from renewable sources reached 22%. According to international statistics, more than 90% of the governments of many countries are making investments to efficiently capitalize on green energy sources and to design new models of sustainable economic and social development, in order to lower pollution levels, reduce the dependence on fossil fuel imports and limit the climate change impact.

Relevant research has investigated how predictive modeling algorithms, deep-learning-based sensing technologies, and big urban data configure immersive hyperconnected virtual spaces in digital twin cities: digital twin modeling tools, monitoring and sensing technologies, and Internet-of-Things-based decision support systems articulate big-data-driven urban geopolitics. This systematic review aims to inspect the recently published literature on digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks. We integrate research developing on how blockchain-based digital twins, smart infrastructure sensors, and real-time Internet of Things data assist urban computing technologies. The research problems are whether: data-driven smart sustainable urbanism requires visual recognition tools, monitoring and sensing technologies, and simulation-based digital twins; deep-learning-based sensing technologies, spatial cognition algorithms, and environment perception mechanisms configure digital twin cities; and digital twin simulation modeling, deep-learning-based sensing technologies, and urban data fusion optimize Internet-of-Things-based smart city environments. Our analyses particularly prove that virtual navigation tools, geospatial mapping technologies, and Internet of Things connected sensors enable smart urban governance. Digital twin simulation, data visualization tools, and ambient sound recognition software configure sustainable urban governance networks. Virtual simulation algorithms, deep learning neural network architectures, and cyber-physical cognitive systems articulate networked smart cities. Throughout January and March 2023, a quantitative literature review was carried out across the ProQuest, Scopus, and Web of Science databases, with search terms comprising “sustainable urban governance networks” + “digital twin simulation tools”, “spatial cognition algorithms”, and “multi-sensor fusion technology”. A Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow diagram was generated using a Shiny App. AXIS (Appraisal tool for Cross-Sectional Studies), Dedoose, MMAT (Mixed Methods Appraisal Tool), and the Systematic Review Data Repository (SRDR) were used to assess the quality of the identified scholarly sources. Dimensions and VOSviewer were employed for bibliometric mapping through spatial and data layout algorithms. The findings gathered from our analyses clarify that Internet-of-Things-based smart city environments integrate 3D virtual simulation technology, intelligent sensing devices, and digital twin modeling.

Purpose: Digitalization has been the driving change in creating jobs and increasing economic growth in recent years. However, the digitalization of countries and sectors is uneven. The paper focuses on various factors that have an impact on the economic development and well-being in EU countries. Its purpose is to show the evolution of EU countries in terms of digital transformation and how other indicators, such as e-government, human development index, labour productivity, and economic growth influenced the well-being in EU countries in 2019–2021.Design/methodology/approach: The dataset consists of 15 numerical indicators extracted from Eurostat and World Bank databases. We apply principal component analysis and cluster analysis.Findings and Practical Implications: The main research results show that the first dimension – named the impact of innovation on well-being – is dominated by e-government, the percentage of ICT specialists in total, internet use by individuals, the Human Development Index, the Digitalization Index, the Happiness Indicator, human capital, and the integration of digital technology. The second dimension is characterized by government expenses and productivity. Finally, the third dimension is dominated by the GDP growth rate. 77.67% of the total variance is explained by the first three principal components.Originality: Four clusters have been identified by means of the K-Means clustering algorithm. All four clusters are well determined, with cluster 1 including the three Nordic countries ranking first, followed by cluster 3 of well-developed countries and cluster 4 containing mainly emerging economies.

In the new contemporary pandemic paradigm, higher education in public administration and beyond knows challenges, barriers, and opportunities for the academic process. Shocks, environmental changes and physical distancing in recent years have led to the implementation of efficient solutions in educational services, based on artificial intelligence (AI). Thus, in the global academic landscape, many international universities have adopted a ‘chatbot’, a digital interface designed to stimulate conversation with people. Modern algorithmic communications have effects, such as: increasing the number of enrollments in public administration programs, improving academic experience and active student participation, while reducing administrative tasks on university staff. This paper aims to provide a glimpse on the perceptions of the potential impact of conversational artificial intelligence on public administration (PA) programs from universities and to reflect on its implications for university leaders and staff work and also on students’ engagement. The paper will focus on how AI tools will help university programs to be more effective, and how technology will support the limited human resources in this sector. In order to gather the data for this research, the interview was used as well as case studies from international universities that have implemented a chatbot. The research findings capture technological and digital advances that will continue to shape the higher education landscape and its curricula, especially in PA programs. As a result, leaders will need to monitor how artificial intelligence, in particular conversational agents, influences universities’ images; attraction and retention for students in PA programs and other important partners; staff productivity, and how to be more proactive in initiating pilot projects. This is one of the few publications that looks at the expectations for conversational AI in higher education today. In this sense, implementing a chatbot can be a competitive advantage in a market where modern technologies weigh heavily and make a difference.

Too little has been published on emotional intelligence in the public sector, despite the scientific literature’s increased interest in the concept in recent years. The present research aim is to analyze whether and how public employees’ emotional intelligence (EI) has an influence on their job stress (JS) level and willingness to deliver quality and performant public services (WDQS). In order to investigate the hypotheses, the study used a quantitative methodology and a conceptual deductive research technique based on a conceptual framework. For statistical analysis, we used the SPSS Statistics 22.0 program. This made it possible for us to build descriptive analyses and run several parametric tests to achieve the primary goal of our study. The findings showed that the employees of the National Agency for Public Procurement from Romania (ANAP) registered an average to above average EI level (M = 4.99), with no relevant significant influence on their stress level, and with a weak influence on their willingness to deliver quality public services. The study’s respondents, although they register a high level of job stress (M = 5.44), demonstrated an average desire to deliver qualitative services to different stakeholders (M = 4.89), with low to average impact on the provided public services’ performance (M = 3.19). From all the main sample characteristics, only the occupied position in the organization (independent variable) had a positive significant influence on employees’ EI and JS level. In order to allow for comparisons of the results with those of the current study, future research should combine various methods of measuring emotional intelligence, job stress and public employees’ willingness to provide quality and performant public services.