The research addresses the importance of ethics in public administration, focusing on public servants in the municipality of Rionegro, Colombia. Ethics is presented as an essential element to promote transparency and combat corruption in public management. Despite the fact that the 1991 Constitution establishes ethical principles, their application in practice remains a challenge, with a high level of immorality in public service. The study highlights the diversity of professional profiles in public servants, which hinders consistent ethical management. In addition, it mentions that many civil servants lack political training and understanding of the importance of their role, which contributes to corruption. Ethics, according to the authors, is a key tool for strengthening institutions and regaining public trust. The research evaluated the impact of a professional ethics training program on public servants, finding significant improvements in their ethical knowledge and behavior. It concludes that, although ethics will not solve all corruption problems, it is an indispensable component for strengthening accountability and justice in public administration. It underscores the need to implement continuous training programs that promote ethical values as part of a strategy to improve efficiency and transparency in public institutions.

The purpose of this study is to analyze how the entrepreneurial mindset, social context, and entrepreneurial ambitions of university students in the United Arab Emirates (UAE) have progressed over time in terms of starting their businesses. The research aims to investigate the evolution of the entrepreneurship mindset, considering the implementation of educational and governmental policies over the past decade to promote entrepreneurship among UAE university graduates. To collect primary data and evaluate the impact of the studied variables on the dependent variable “entrepreneurial ambitions,” a self-created questionnaire was used. The results reveal a positive correlation between personal context variables and entrepreneurial ambitions, as well as between personality traits and entrepreneurial ambitions. Furthermore, the study demonstrates the constructive effect of education, government policies, and capital availability on fostering entrepreneurial ambitions in the UAE.

The aim of this study was to analyze scientific production on accounting strategies for the management of sporting events over the last 20 years. The methodology used was mixed, combining the quantitative perspective of bibliometric analysis and the qualitative perspective of the case study, to deepen the analysis of the data set. Using bibliometrics, the number of scientific papers on this topic was quantified. For the study, 853 papers from Scopus and Google Scholar were considered that met the inclusion criteria in terms of relevance and keywords in English (accounting strategies, financial strategies and sporting events). Between 2021 and 2024, scientific production increased significantly (n = 376; 44.1%), with the United States being the largest contributor, with 21.7%. In addition, Plos One was the most important source, with 22 publications. The most cited author was Crawford (333 citations). Most of the publications (81%) were scientific articles, with 37% focused on medicine and 12% focused on social sciences. It is concluded that the literature on accounting strategies for sport event management has been the subject of research, with a wide variety of authors, topics, countries, and resources in general. Thus, financial planning, cost control, proper revenue recognition, tax compliance, all these strategies enable the organization of a sporting event to be profitable, efficient and sustainable. As a result, there is a complete picture of the global influence, perception and importance of research on this topic, which lays the groundwork for future research in this field. The value of the research lies in its ability to provide evidence-based solutions to improve the financial efficiency and sustainability of sporting events.

Nowadays, urban ecosystems require major transformations aimed at addressing the current challenges of urbanization. In recent decades, policy makers have increasingly turned their attention to the smart city paradigm, recognizing its potential to promote positive changes. The smart city, through the conscious use of technologies and sustainability principles, allows for urban development. The scientific literature on smart cities as catalysts of public value continues to develop rapidly and there is a need to systematize its knowledge structure. Through a three-phase methodological approach, combining bibliometric, network and content analyses, this study provides a systematic review of the scientific literature in this field. The bibliometric results showed that public value is experiencing an evolutionary trend in smart cities, representing a challenging research topic for scholars. Network analysis of keyword co-occurrences identified five different clusters of related topics in the analyzed field. Content analysis revealed a strong focus on stakeholder engagement as a lever to co-create public value and a greater emphasis on social equity over technological innovation and environmental protection. Furthermore, it was observed that although environmental concerns were prioritized during the policy planning phase, their importance steadily decreased as the operational phases progressed.

In this paper, a study developed at the University of Seniors in Aragón is presented. The Sono-libro, used as an innovative resource, is assessed in the proposal with an educational and pedagogical purpose. The aim is to understand the motivational and learning perception variation after the incorporation of the Sono-libro in the sample. In this quantitative longitudinal design study, the listening habits of the participants are comparatively analyzed at two moments: The first data collection took place before the implementation of the proposal, and the second collection occurred after the proposal. The sample consists of 116 subjects, with 64.16% being women and an average age of 66 years of age. Data was obtained through a validated ad hoc questionnaire judged by experts. The results of the data collections showed an increase in both motivation and perception of the learning obtained, indicating the benefits of incorporating digital resources into contexts of adult students.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.