Regions rich in natural resources often exhibit a high dependency on revenue from Revenue Sharing Funds (DBH). This dependency can pose long-term challenges, especially when commodity prices experience significant fluctuations. This study examines the role of Revenue Sharing Funds from Natural Resources (DBH SDA) on economic growth in 491 regencies/cities in Indonesia during the 2010–2012 period. The analysis employs panel data regression. The selection of this period was based on the occurrence of a resource boom characterized by a surge in global demand for natural resource commodities, accompanied by an increase in commodity prices. This condition positively impacted the revenues of both the nation and resource-rich regions. The results of the study show that economic growth is not influenced by DBH SDA but rather by General Allocation Funds (DAU). This indicates that the central government still plays a significant role in determining economic growth at the regency/city level in Indonesia. Regions need to prioritize economic diversification to reduce reliance on DBH SDA and DAU. Investment in productive sectors, such as infrastructure, education, and technology, can be a strategic approach to accelerating regional economic growth.

The Bini people of Edo State, located in the Edo South senatorial district, have been the focus of a study investigating the impact of international migration on Nigerian infrastructure. The study employed a descriptive-qualitative approach, using a survey research methodology and structured questionnaires to gather data from 401 respondents. The study used regression and thematic analysis to examine the collected data, focusing on the connection between migration and the advancement of infrastructure. The findings suggest that low incomes, job insecurity, and the development of domestic infrastructure contribute to the momentum behind international migration movements. The study suggests that remittances from migrants and investments are needed to alleviate the situation, highlighting the need for a more inclusive and sustainable approach to addressing the challenges faced by the Bini people in Edo State.

In light of swift urbanization and the lack of precise land use maps in urban regions, comprehending land use patterns becomes vital for efficient planning and promoting sustainable development. The objective of this study is to assess the land use pattern in order to catalyze sustainable township development in the study area. The procedure adopted involved acquiring the cadastral layout plan of the study area, scanning, and digitizing it. Additionally, satellite imagery of the area was obtained, and both the cadastral plan and satellite imagery were geo-referenced and digitized using ArcGIS 9.2 software. These processes resulted in reasonable accuracy, with a root mean square (RMS) error of 0.002 inches, surpassing the standard of 0.004 inches. The digitized cadastral plan and satellite imagery were overlaid to produce a layered digital map of the area. A social survey of the area was conducted to identify the specific use of individual plots. Furthermore, a relational database system was created in ArcCatalog to facilitate data management and querying. The research findings demonstrated the approach's effectiveness in enabling queries for the use of any particular plot, making it adaptable to a wide range of inquiries. Notably, the study revealed the diverse purposes for which different plots were utilized, including residential, commercial, educational, and lodging. An essential aspect of land use mapping is identifying areas prone to risks and hazards, such as rising sea levels, flooding, drought, and fire. The research contributes to sustainable township development by pinpointing these vulnerable zones and providing valuable insights for urban planning and risk mitigation strategies. This is a valuable resource for urban planners, policymakers, and stakeholders, enabling them to make informed decisions to optimize land use and promote sustainable development in the study area.

This study aims to develop a framework that helps organizations to fulfill their environmental and social responsibility amid constraints in selecting which stakeholders’ interest comes first and the essential to have an evolved strategic planning that can accommodate broader systemic planning and practice that will yield authenticity in business sustainability with components of environmental worldview of its leaders and organizational learning in the framework. This research uses the method of literature review with the data from interviews and content analysis of the report from one organization that has successfully implemented social and environmentally friendly practices. Based on an in-depth review of literatures on worldview, organizational learning, and strategic planning, and with empirical study from one organization, a conceptual framework by combination of the existing concepts is produced to enable an integration of theories in a range of possible actions for organizations to achieve sustainable development. The result from this research’s framework will allow further study to be carried out in the future to verify associations between existing concepts or variables within the framework, and to produce next empirical results in supporting those theories being reviewed in this paper.

Background: Bitcoin mining, an energy-intensive process, requires significant amounts of electricity, which results in a particularly high carbon footprint from mining operations. In the Republic of Kazakhstan, where a substantial portion of electricity is generated from coal-fired power plants, the carbon footprint of mining operations is particularly high. This article examines the scale of energy consumption by mining farms, assesses their share in the country’s total electricity consumption, and analyzes the carbon footprint associated with bitcoin mining. A comparative analysis with other sectors of the economy, including transportation and industry is provided, along with possible measures to reduce the environmental impact of mining operations. Materials and methods: To assess the impact of bitcoin mining on the carbon footprint in Kazakhstan, electricity consumption from 2016 to 2023, provided by the Bureau of National Statistics of the Republic of Kazakhstan, was used. Data on electricity production from various types of power plants was also analyzed. The Life Cycle Assessment (LCA) methodology was used to analyze the environmental performance of energy systems. CO₂ emissions were estimated based on emission factors for various energy sources. Results: The total electricity consumption in Kazakhstan increased from 74,502 GWh in 2016 to 115,067.6 GWh in 2023. The industrial sector’s electricity consumption remained relatively stable over this period. The consumption by mining farms amounted to 10,346 GWh in 2021. A comparative analysis of CO₂ emissions showed that bitcoin mining has a higher carbon footprint compared to electricity generation from renewable sources, as well as oil refining and car manufacturing. Conclusions: Bitcoin mining has a significant negative impact on the environment of the Republic of Kazakhstan due to high electricity consumption and resulting carbon dioxide emissions. Measures are needed to transition to sustainable energy sources and improve energy efficiency to reduce the environmental footprint of cryptocurrency mining activities.

This article explores the role of informatization in the integration and development of the cultural and tourism industry, and proposes corresponding analysis and strategies. Firstly, informatization improves the quality and efficiency of cultural and tourism products and services by enhancing the design and production process and personalizing and customizing the services. Secondly, informatization expands the boundaries of cultural and tourism products and markets by utilizing the internet and mobile applications to extend the spatial and temporal boundaries, and leveraging data analysis and intelligent technologies to broaden the scope and scale. Lastly, informatization enhances the management and operational level of the cultural and tourism industry, improving efficiency and decision-making through the use of advanced technologies such as big data and artificial intelligence.