Increasing the environmental friendliness of production systems is largely dependent on the effective organization of waste logistics within a single enterprise or a system of interconnected market participants. The purpose of this article is to develop and test a methodology for evaluating a data-based waste logistics model, followed by solutions to reduce the level of waste in production. The methodology is based on the principle of balance between the generation and beneficial use of waste. The information base is data from mandatory state reporting, which determines the applicability of the methodology at the level of enterprises and management departments. The methodology is presented step by step, indicating data processing algorithms, their convolution into waste turnover efficiency coefficients, classification of coefficient values and subsequent interpretation, typology of waste logistics models with access to targeted solutions to improve the environmental sustainability of production. The practical implementation results of the proposed approach are presented using the production example of chemical products. Plastics production in primary forms has been determined, characterized by the interorganizational use of waste and the return of waste to the production cycle. Production of finished plastic products, characterized by a priority for the sale of waste to other enterprises. The proposed methodology can be used by enterprises to diagnose existing models for organizing waste circulation and design their own economically feasible model of waste processing and disposal.

The allocation of funds in the local budget is a matter of concern for the governments and economic scholars. The study examines the influence of local budget expenditures on the GRDP per capita of 63 provinces and municipalities in Vietnam from 2018 to 2022. Regression analysis of panel data reveals that capital expenditure has a positive correlation with local GRDP per capita, whereas current expenditure has a negative correlation with GRDP per capita. Furthermore, the analysis indicates that the percentage of individuals aged 15 and above who are employed and the percentage of urban citizens have an equivalent influence as the GRDP per capita. Conversely, the average age and local Gini coefficient have contrasting effects on GRDP per capita. The author suggests several policy alternatives to assist localities in boosting their GRDP per capita based on the findings of the study model.

Competition in the telecommunications market has significant benefits and impacts in various fields of society such as education, health and the economy. Therefore, it is key not only to monitor the behavior of the concentration of the telecommunications market but also to forecast it to guarantee an adequate level of competition. This work aims to forecast the Linda index of the telecommunications market based on an ARIMA time series model. To achieve this, we obtain data on traffic, revenue, and access from companies in the telecommunications market over a decade and use them to construct the Linda index. The Linda index allows us to measure the possible existence of oligopoly and the inequality between different market shares. The data is modeled through an ARIMA time series to finally predict the future values of the Linda index. The results show that the Colombian telecommunications market has a slight concentration that can affect the level of competition.

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.

This study addressed the procedural aspects of the claim for civil liability for nuclear damage in accordance with the newly promulgated Law on Civil Liability for Nuclear Damage No. 4 of 2012 of the United Arab Emirates and the Vienna Convention. The study was divided into two main investigators; the first main investigator examined the parties to the claim for nuclear damage, which, in turn, was split into two main sections: the first section examined the claimant, and the second section examined the defendant. The second main investigator of this paper examined civil liability for nuclear damage, which, in turn, was split into two main sections: the first of which addressed the jurisdiction in the claim for liability for nuclear damage, and the second of which dealt with the time to initiate proceeding. The study based its conclusions on several findings and recommendations, the most important of which was to propose amendments to the Civil Liability for Nuclear Damage Act in line with the general rules of civil liability and the Vienna Convention.