Research networks organized around a particular topic are built as knowledge is produced and socialized. These are parts of a seminal or initial production, to which new authors and subtopics are added until research and knowledge networks are formed around a particular area. The purpose of the research was to find this type of relationship or network between authors, institutions, and countries that have contributed to the issue of the circular economy and specifically its relationship with sustainability. This allows those interested in the said object of study to know the research advances of the network, enter their research lines, or create new networks according to their interests or needs. The study used a bibliometric-type descriptive quantitative approach using the Scopus scientific database, the R Studio data analytics application, and the Bibliometrix library. The results were found to determine a relationship building from 2006, which makes it an emerging topic. However, the growth it has achieved in recent years of more than 31% shows a strong interest in the subject. Of the subtopics that have been addressed, sustainability, recycling, solid waste, wastewater, and renewable energy. Similarly, sectors such as construction, the automotive industry, tourism, cities, the agricultural sector, the chemical industry, and the implementation of technologies 4.0 and 5.0 in their processes stood out. The most prominent country in the scientific approach to this area is Italy. The most prominent author for his citations is Molina-Moreno, the source of knowledge that stands out for his contributions is the University of Granada and different networks have been built around their knowledge.

This study aims to investigate the effectiveness of community involvement in waste management through participatory research. Its objective is to bridge the theoretical underpinnings of participatory research with its practical implementation, particularly within the realm of waste management. The review systematically analyzes global instances where community engagement has been incorporated into waste management initiatives. Its principal aim is to evaluate the efficacy of participatory strategies by scrutinizing methodologies and assessing outcomes. To achieve this, the study identified 74 studies that met rigorous criteria through meticulous search efforts, encompassing various geographical locations, cultural contexts, and waste management challenges. In examining the outcomes of participatory research in waste management, the study explores successful practices, shortcomings, and potential opportunities. Moving beyond theoretical discourse, it provides a detailed analysis of real-world applications across various settings. The evaluation not only highlights successful engagement strategies and indicators but also critically assesses challenges and opportunities. By conducting a comprehensive review of existing research, this study establishes a foundation for future studies, policy development, and the implementation of sustainable waste management practices through community engagement. The overarching goal is to derive meaningful insights that contribute to a more inclusive, effective, and globally sustainable approach to waste management. This study seeks to inform policymaking and guide future research initiatives, emphasizing the importance of community involvement in addressing the complexities of waste management on a global scale.

Introduction/Main objectives: This study aims to test the influence of the application of the concept of value for money on regional government financial management at the quality level of regional development, which is determined by the level of foreign and domestic investment in local governments. Background problems: State the problem or economic/business phenomena studied in this paper and specify the research question(s) in one sentence. Novelty: This study has a research model that has yet to be widely carried out in Indonesia, namely, a moderated model regression analysis of the value concept for money on the quality of regional development with investment as a moderating variable. Research methods: This study uses data on financial performance, domestic and foreign investment levels, and human development index of 34 provincial governments from 2017 to 2021. This research data comes from the website of the Directorate General of Fiscal Balance, Ministry of Finance and the Central Bureau of Statistics. The data collected in this study is then analyzed using moderated regression analysis (MRA) with the SPSS ver 23.0 application. Findings/Results: The findings in the research show that the application of value for money ( economics, efficiency, and effectiveness ) from local government financial governance can influence the quality of regional development in Indonesia’s provinces in 2017–2021. In addition, the existence of foreign and domestic investment in the provincial government also strengthens the influence of value-for-money financial governance on the quality level of regional development in the provincial government. Conclusion: Based on existing research, local government financial management applies the concept that value for money needs to be increased to create optimal public services to improve the quality of human development in the regions. Regional governments are also expected to be able to encourage the level of capital investment both domestically and abroad to support the creation of development that can strengthen the quality of regional development in the regions.

This article presents the validation of a virtue-based leadership development questionnaire (LID). Leadership is defined as the human action of guiding others toward a common good, which requires the exercise of personal competencies and virtues. The theoretical and factorial structure of LID has three domains: intellectual, relational and performative. The LID was administered to a sample of 1759 university students from Mexico and Spain for factor analysis. Subsequently, it was applied to a sample of 1906 students from a Mexican university for confirmatory factor analysis and to 171 Mexican students for a convergent validity study with the Socially Responsible Leadership Scale (SRLS). Psychometric analyses indicate that the questionnaire is reliable and valid. Confirmatory factor analysis indicates that the questionnaire fits the theoretical model and has convergent validity with the SRLS. This questionnaire aims to contribute to the leadership education of university students.

This study conducts research on retailers’ behavioral intentions and behavior in adopting e-commerce platforms (ECPs) and uses the unified theory of acceptance and use of technology (UTAUT2) model as well as add other factors such as Personalization Platform, Seamless Interaction. The findings show that Effort Expectancy, Social Influence, Hedonic Motivation, Retailers’ Capacity, Integration Strategies have a positive impact on retailers’ behavioral intention of adopting ECPs and Performance Expectancy has a negative impact on retailers’ behavioral intention of adopting ECPs. At the same time, Behavioral Intention, Facilitating Conditions have a positive impact on retailers’ behavior adopting ECPs and Seamless Interaction has a negative impact on retailers’ behavior adopting ECPs. With important implications, these findings are proposed to relevant parties, helping retailers and ECPs suppliers identify factors affecting retailers’ behavioral intention and behavior in adopting ECPs in Vietnam.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.