In order to meet the Sustainable Development Goals (SDGs) of the United Nations and address the growing global concern for ecologically responsible activities, this study examines the role that French financial institutions play in financing a green future and promoting sustainable development (SD). Through semi-structured interviews with twelve participants from banks and Fintech companies, the research investigates their familiarity with green financing commitments to international organizations and associations, their views on the growth potential of green finance, and the provision of green finance products. Additionally, it explores the connection between green finance and its positive influence on SD. Data analysis was performed using NVivo 12. The findings highlight a strong commitment to green finance and sustainable practices among these institutions, emphasizing the significance of integration and utilization of green finance products across various sectors. This research emphasizes the crucial role of financial institutions in France in driving a greener and more sustainable future through green finance.

The main objective of the study is to discuss the application of a participatory approach that involves the community of a small rural area in Italy to develop and maintain a sustainable local food system based on a very ancient and high-quality typical local bean. The efficacy of the approach in terms of the active involvement of local actors (farming communities, local administration, social associations, and civil society) and knowledge transfer for preserving the local food culture has been demonstrated. Possible improvements to the approach through digital technologies for stimulating the effective engagement of teenagers have also been discussed.

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.

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.