The relationship between aid and corruption remains ambiguous. On the one hand, aid may benefit a country if the aid management system runs efficiently and transparently. On the other hand, aid tends to create new problems, namely corruption, especially in developing countries. This research examines the aid-corruption paradox in Indonesian provinces from a spatial perspective. The data was obtained from the Indonesian Ministry of Finance, the National Development Planning Agency of Indonesia, the Corruption Eradication Commission of Indonesia, and the Electronic Procurement Service, referring to 34 Indonesian provinces between 2011 and 2019. The research applies the spatial panel method and uses Haversine distance to construct the weighted matrix. The spatial error model (SEM) is the best for Model 1 (Grants) and Model 2 (Loans) and the best corruption model in Model 3 (Gratification). The spatial autoregressive model (SAR) is the best approach for Model 4 (Public Complaints) and Model 5 (Corruption). The findings show that there is no spatial dependence between provinces in Indonesia in terms of grants or loans. However, corruption in Indonesia is widespread.

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.

Urban mobility in Grand Lomé is affected by several negative externalities, including road congestion, insecurity and environmental pollution. Traffic jams cause considerable economic losses, estimated at more than 13,000 CFA francs per month for some public officials, and represent a financial drain of several million CFA francs per day on the Togolese economy. These challenges are accentuated by rapid urbanization and a dizzying increase in the number of vehicles, especially motorcycle taxis. These factors not only cause economic losses, but also to the deterioration of the quality of life of the inhabitants. On average, motorists lose up to 49.5 min per day in traffic jams, with fuel and time costs estimated at hundreds of thousands of CFA francs per year for each user of the main boulevards. Through an in-depth analysis of the impacts of these negative externalities on mobility and sustainable development, this study reveals that traffic congestion, combined with the lack of road infrastructure, generates considerable economic and environmental costs. These traffic jams also worsen air pollution, making the transport sector responsible for 80% of greenhouse gas emissions. These proposed solutions include: 1) The modernization of road infrastructure, culminating in the construction of new lanes entirely dedicated to public and non-motorized transport. 2) The regulation of motorcycle taxis, inspired by regional examples, to improve safety and efficiency. 3) The introduction of rapid transit systems, such as Bus Rapid Transit (BRT), to make travel more fluid. 4) The implementation of strict environmental standards and regular technical controls to reduce greenhouse gas emissions. These proposals aim to reduce social and economic costs, while promoting sustainable mobility and a better quality of life for residents.

This paper focuses on examining the relationship among organizational factor, work-related factor, psychological factor, personal factor and the commitment of oil palm smallholders toward Malaysian Sustainable Palm Oil (MSPO) certification. The study employed a descriptive research methodology and a structured survey instrument to gather data from oil palm smallholders (n = 441) through simple random sampling technique. Data analysis was conducted using SPSS and partial least square structural equation modeling (PLS-SEM) to test the proposed relationship. The findings reveal that organizational factors significantly impact the affective (β = 0.345, p < 0.05), normative (β = 0.424, p < 0.05), and continuance commitment (β = 0.339, p < 0.05) of oil palm smallholders. Additionally, work-related factors show a substantial effect on these same dimensions of commitment; affective (β = 0.277, p < 0.05), normative (β = 0.263, p < 0.05), and continuance (β = 0.413, p < 0.05). Psychological factors significantly impact the affective (β = 0.216, p < 0.05) and normative commitment (β = 0.146, p < 0.05), with no statistically significant influence on continuance commitment. Conversely, personal factors exhibit limited influence, affecting only continuance commitment (β = 0.104, p < 0.05) to a minor degree, with no statistically significant impact on affective and normative commitment. The present research is among the few empirical findings that have examined the oil palm smallholders' commitment towards MSPO certification. By emphasizing the role of organizational and work-related factors, the study offers valuable insights for stakeholders within the oil palm sector, highlighting areas to enhance smallholder commitment toward sustainability standards. Consequently, this study contributes a unique perspective to the existing body of literature on sustainable practices in the oil palm industry.

This study investigates how corruption impacts sustainability in African countries. Using public databases, the research draws on the African Development Bank’s corruption indicators and the World Bank’s financial inclusion metrics. The findings reveal that as financial inclusion increases, particularly through the use of digital financial services, perceptions of corruption decrease. However, economic growth paradoxically correlates with an increased perception of corruption due to rising consumption demands. The study concludes that promoting financial literacy, along with robust governance, is essential for combating corruption and fostering sustainable development.

The rapid increase in the aging population has raised significant concerns about the living conditions and well-being of elderly residents in old communities. This study addresses these concerns by proposing a Sustainable Urban Renovation Assessment Model (SURAM) specifically designed to enhance elderly-friendly environments in Chongqing City. The model encompasses multiple dimensions, including the comfort of public facilities, service safety and convenience, medical travel services, infrastructure security, life service convenience, neighbor relations, ambulance aid accessibility, commercial service facilities, privacy protection, elderly care facilities and service supply, and medical and health facilities. By employing factor analysis, the study reduces the dimensionality of the 49 indicator factors, allowing for a more focused and comprehensive evaluation of the effectiveness of aging-friendly renovation efforts. The main factors identified in the proposed model include community infrastructure security, elderly comfort of community public facilities, completeness and convenience of surrounding living services, and security and convenience of elderly care services. The results reveal that the age-appropriate comfort of public facilities plays a significant role in achieving successful aging-appropriate renovation outcomes. The findings demonstrate that by addressing specific needs such as safety, accessibility, and convenience, communities can significantly improve the quality of life for elderly residents. Moreover, the application of SURAM provides actionable insights for policymakers, urban planners, and community stakeholders, guiding them in implementing targeted initiatives for sustainable and inclusive urban development.