This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.

This study focuses on the effectiveness of systematic approaches to achieve business success, through integrated digital marketing strategies with the use of mobile applications. Focused on contemporary digital markets, the research highlights the transformative potential of these strategies about improving the quality of services and products, while promoting business sustainability. The objective of this research is to develop and evaluate a mobile application, designed to optimize customer orders within communities on the move. Through a mixed approach that includes semi-structured interviews with community members and digital marketing experts, along with quantitative surveys, assessed user perceptions and effectiveness of the app. The results indicate great acceptance and effectiveness of this digital tool, facilitating direct interactions, and improving accessibility to the service despite physical and digital limitations, reducing digital gaps and promoting economic empowerment among marginalized communities.

PPGIS platforms have been widely used to map social actors since the emergence of open access webGIS platforms. This identification of citizen initiatives is based on the physical location, but is rarely combined with social networking. This research seeks to close that gap by using the platIC web-based mapping tool for citizen initiatives, together with their interrelationships. Therefore, a methodical procedure has been defined to construct a geolocalised graph by identifying and categorising linked nodes. Method steps have been tested in three case studies in the Malaga region: Malaga city, Benalmadena, and Valle del Genal. They were selected for a comparative analysis in three different urban and socio-economic scenarios, namely: a tourist destination with a high density of Spanish population and floating city users; a sun-and-beach destination with a significant presence of resident foreign population; and a rural area suffering from depopulation, respectively. Mapping reveals a higher density of citizen initiatives in central urban areas and with social conflicts. Social graphs show a wider interconnection of nodes in rural areas, but isolated nodes are spread more widely there. Monitoring active citizen initiatives could serve as a basis for local administration to involve the citizenry in the management of current issues in the urban and rural context. Future research may promote new plugins to improve participatory process through webGIS platforms.

Socrates argues that individuals can continue to behave morally when trying to explore virtue, distinguishing between copying a moral person’s actions and acting on the basis of virtue itself. This study proves the limitations of South Korea’s moral education, which values moral knowledge as a driver of moral behavior, by analyzing the art of measurement presented by Socrates as a method of recognizing virtue. Consequently, Protagoras was examined to identify the characteristics of the art of measurement, and “all pleasure is good” and “knowledge directly drives action” was problematized. The study concluded that moral knowledge is not a decisive factor in guiding moral behavior in the right direction.

Law Number 20 of 2003 on the National Education System states that citizens have the right to obtain basic education for children aged seven to fifteen years. In addition, it is also a commitment to the implementation of Grobogan district’s regional regulation No 5 of 2019 on education implementation, especially article 12 related to the obligation of local governments to ensure the implementation of basic education according to their authority. The purpose of this study is to determine the implementation of the basic education management program in Grobogan district; analyze the factors that support and hinder the implementation of the basic education management program in Grobogan district; formulate a model for implementing the basic education management program in Grobogan district. The method used in this research is qualitative. This method was used to analyse the phenomenon of policy implementation of the basic education management program in Grobogan district. The research site was in Grobogan district. The informants are policy actors who know a lot about the basic education program in Grobogan district. The results show that the implementation of the Grobogan district education office’s policy on basic education management consists of three areas, namely (1) equalization and expansion of access to education; (2) improvement of quality, relevance and competitiveness; (3) education governance and accountability. These three areas aim to achieve the national standards of education and the minimum service standards of education.

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.