This study analyzes the potential of making Uzbekistan’s taxation system more inclusive by introducing a tax incentive policy related to zakat (obligatory Islamic alms for the wealthy). Additionally, it explores the establishment of relevant institutions to facilitate zakat collection and distribution. The study employs the method of comparative legal research, combined with exploratory research techniques, to examine taxation and zakat systems in different countries. The study’s findings indicate that incorporating zakat incentives, either in the form of tax credits or deductions, into Uzbekistan’s taxation system can enhance the role of zakat institutions in the country’s economy and reduce tax evasion to some extent. Moreover, it proposes a preliminary model of zakat management for Uzbekistan based on conclusions of the comparative study of various countries and analysis of the national legislation. Finally, the research highlights the necessity of a systematic approach to educate the public about zakat obligations, which is crucial for operation of proposed zakat management model and improving compliance. The study provides essential policy recommendations, including the implementation of zakat tax incentives, enhancing public zakat literacy, and ensuring the efficient operation of zakat institutions. By adopting these measures, the government of Uzbekistan can foster a more equitable and effective taxation system, contributing to socioeconomic development and poverty alleviation.

With the rapid economic growth, the concept of digital economy and sustainable development has gradually become the main task facing our country. This paper constructs the evaluation system of the development level of digital economy and the comprehensive index of regional sustainable development by the entropy weight method, uses the two-way fixed effect model to explore the influence mechanism of digital economy on the sustainable development of the Yangtze River Delta region.

A decent income is an important part of overcoming economic disparities in agricultural development, especially in developing countries where most of the population are small farmers. As a developing country, Indonesia has also established a decent standard of living by setting a minimum wage as a reference for a decent income at the national and regional levels. However, this benchmark is not relevant to be applied uniformly at all levels of workers. This research determines the national coffee development area as the study center. We developed the Anker living wage methodology as a simple concept for determining living income for certain worker communities, especially for small farmers in rural areas who dominate the type of work in Indonesia. a socio-spatial approach is used to visualize the distribution of the dynamics of a decent life in various conditions of farming households. We found that 96.6% of coffee farming households in the national coffee development area had an inadequate living income, and only 3.4% were at an adequate level. We conclude that the current state of agricultural land management does not guarantee a decent income, even though efforts have been made to maximize agricultural crop productivity. The spatial description also shows that this condition is evenly distributed throughout residential areas. It is hoped that this approach can become an essential reference in implementing agricultural development programs that focus on welfare and equitable development as benchmarks for sustainable development goals in the future.

An extensive assessment index system was developed to evaluate the integration of industry and education in higher vocational education. The system was designed using panel data collected from 31 provinces in China between 2016 and 2022. The study utilized the entropy approach and coupled coordination degree model to examine the temporal and spatial changes in the level of growth of the integration of industry and education in higher vocational education, as well as the factors that impact it. In order to examine how the integration of industry and education in higher vocational education develops over time and space, as well as the factors that affect it, we utilized spatial phasic analysis, Tobit regression model, and Dagum’s Gini coefficient. The study’s findings suggest that between 2016 and 2022, the integration of industry and education in higher vocational education showed a consistent improvement in overall development. Nevertheless, there are still significant regional differences, with certain areas showing limited levels of integration, while the bulk of regions are either in a state of low integration with high clustering or low integration with low clustering. Most locations showed either a “low-high” or “low-low” level of agglomeration, indicating a significant degree of spatial concentration, with a clear trend of higher concentration in the east and lower concentration in the west. The progress of industrial structure and the degree of regional economic development have a substantial impact on the amount of integration of industry and education in higher vocational education. There is a notable increase in the amount of integration between industry and education in higher vocational education, which has a favorable effect. Conversely, the local employment rate has a substantial negative effect on this integration. Moreover, the direct influence of industrial structure optimization is restricted. The Gini coefficient of the development level of integration of industry and education in higher vocational education exhibits a slight rising trend. Simultaneously, there is a varying increase in the Gini coefficient inside the group and a decrease in the Gini coefficient between the groups. The disparities in the level of integration between Industry and Education in the provincial area primarily stem from inter-group variations across the locations. To promote the integration of industry and education in higher vocational education, it is recommended to strengthen policy support and resource allocation, address regional disparities, improve professional configuration, and increase investment in scientific and technological innovation and talent development.

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.