This study analysed the behaviour of both economic and financial profitability of credit unions belonging to segment 1 in Ecuador, as well as its determinants. For this purpose, data from the financial statements of a sample of 30 credit unions between 2016 and 2022 were used by means of a multiple linear regression methodology using panel data with fixed effects after applying the Hausman test. The findings of this research showed that current liquidity and non-performing loans have a negative and significant effect on both economic and financial profitability while the past due portfolio has a positive and significant impact on the generation of profitability of the financial institutions under study. In addition, it was revealed that the rate of outflow absorption has a negative relationship with economic profitability but a positive relationship with financial profitability. Unlike previous research in the Ecuadorian context, this research is pioneering in presenting results that indicate that the determinants traditionally considered for nonfinancial institutions and banks are also valid for credit unions, even though they are organisations with different characteristics from the rest.

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.

The objective of this study was to examine the impact of utilizing smart algorithms on enhancing the operational performance of sports facilities in the Kingdom of Saudi Arabia. These algorithms, based on principles and concepts of artificial intelligence, aim to achieve functions such as learning, decision-making, data analysis, pattern recognition, planning, and problem-solving. The study aimed to identify the extent to which smart algorithms are utilized in sports facilities, assess the level of operational performance, explore the correlation between the use of smart algorithms and operational performance, and predict the level of operational performance based on the use of smart algorithms. The study employed a descriptive approach, specifically utilizing a survey study method. Participants included chairmen and members of boards of directors, executive directors, sports directors, administrators, specialists, and members of various committees. The study sample was intentionally selected from different categories within the study population. Two questionnaires were used to collect data from 325 participants. The findings revealed a lack of utilization of smart algorithms in sports facilities in the Kingdom of Saudi Arabia, indicating a low level of operational performance. Additionally, a correlation was observed between the use of smart algorithms and operational performance, suggesting that the level of operational performance can be predicted based on the utilization of smart algorithms. The study concludes that the implementation of intelligent algorithms can enhance the operational performance of sports facilities in the Kingdom of Saudi Arabia. It provides valuable insights into the effects of utilizing smart algorithms on improving operational performance.

This research aims to do the assessing the feasibility of the Public-Private Partnership project in investing in the construction of the Palu-Parigi By-pass road through a PPP financing scheme, thereby providing opportunities for the private sector to participate in the provision of special road infrastructure. In this context, experimental criteria for determining Value for Money (VFM) are applied using the PPP model, to evaluate projects. The main objective also emphasizes the provision of greater VFM Goods through private financing, through conventional methods that are economical, efficient and effective. Furthermore, financial performance measurement reports apply several methods, including Payback Period (PP), Net Present Value (NPV), and Internal Rate of Return (IRR) which determine the feasibility and time required for returns on invested capital. The previous Economic Feasibility Study of the Palu-Parigi By-pass Road Construction project also showed an EIRR value of 20.1% in 2014, illustrating the economic development of this work. In connection with the limitations currently faced by the Regional Budget Agency of Central Sulawesi Province, the next PPP scheme is recommended for road construction by prioritizing infrastructure completion after the 28 September 2018 earthquake and the COVID-19 pandemic. The DBFMT (Design–Build–Finance–Maintenance–Transfer) model was also applied to the project, with GCA responsible for design, construction, financing, periodic maintenance and transfer at the end of the collaboration agreement.

This research investigates the relationship between Generative Artificial Intelligence (GAI), media content, and copyright laws. As GAI technologies continue to evolve and permeate various aspects of the media landscape, questions regarding the creation and protection of intellectual property have become paramount. The study aims to highlight the impact of GAI generated content, and the challenge it poses to the traditional copyright framework. Furthermore, the research addresses the evolving role of copyright laws in adapting to the dynamic landscape shaped by artificial intelligence. It investigates whether existing legal frameworks are equipped to handle the complexities introduced by GAI, or if there is a need for legislative and policy reforms. Ultimately, this research contributes to the ongoing discourse on the intersection of GAI, media, and copyrights, providing insights that can guide policymakers, legal practitioners, and industry stakeholders in navigating the evolving landscape of intellectual property in the age of artificial intelligence.