The diffusion of contactless payment technologies has become a critical component of digital transformation strategies aimed at enhancing SME competitiveness in developing economies. Among these technologies, Quick Response (QR) Code Payment offers a low-cost and infrastructure-light solution, yet its adoption among SMEs remains uneven. This study investigates the determinants of QR Code Payment adoption and its subsequent effects on SMEs’ sustainability performance. Anchored in the Technology Acceptance Model (TAM) and the Resource-Based View (RBV), the proposed framework incorporates perceived usefulness, perceived ease of use, digital literacy, QR Code Payment adoption, and sustainability performance as core constructs. Integrating TAM and RBV is essential because belief-based perceptions translate into actual adoption only when supported by adequate organizational resources and capabilities, making adoption decisions the product of an interaction between what users believe and what the firm is able to execute. Survey data from 326 SMEs in the Special Region of Yogyakarta, Indonesia, were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that perceived usefulness and digital literacy significantly drive QR Code Payment adoption, whereas perceived ease of use does not, suggesting that performance-oriented beliefs and capability endowments outweigh perceptions of simplicity in shaping adoption behavior. Furthermore, QR Code Payment adoption positively influences economic, social, and environmental aspects of sustainability performance. These findings highlight the strategic value of digital payment integration for advancing SME sustainability and underscore the need to strengthen digital capabilities to accelerate technological uptake. The study extends the literature by jointly applying TAM and RBV to elucidate how belief structures and firm-level capabilities interact to shape adoption outcomes and their performance implications within resource-constrained contexts. For ecosystem coordinators, aligning merchant education with simple analytics dashboards can help SMEs turn payment data into insights—underscoring the need for policy support from government, financial institutions, and payment providers to ensure QR payment adoption translates into real performance gains.

The carbon tax, one of Indonesia’s climate change mitigation instruments for achieving the Nationally Determined Contribution (NDC) target, has been continuously delayed since 2022. A carbon tax is applied to carbon-based products, particularly those derived from the oil and gas sector. The oil and gas sector aims to achieve a targeted production increase of 1 million barrels of oil and 12 Billion Cubic Feet (BCF) of gas by 2030, as mandated by the Indonesian government. However, the rise of the production target may lead to a rise in carbon emissions, contradicting the country's emission reduction commitments. This study aims to explore the perspectives of the government and the oil and gas industry regarding the urgency and readiness of carbon tax implementation in Indonesia’s oil and gas sector, as well as assessing alternative policies for emission reduction. Using a qualitative methodology, semi-structured interviews were conducted to obtain primary data. The result indicates the urgency of implementing a carbon tax in Indonesia’s oil and gas sector to reduce carbon emissions, support energy transition, and achieve Net Zero Emission (NZE), but it is outweighed by both government and industry unreadiness. The Regulatory Framework aspect primarily influences the government's unreadiness, as the absence of a carbon tax roadmap as a technical implementation guideline, combined with ongoing fuel subsidies, contributes to policy incoherence. On the other hand, the Production Sharing Contract (PSC), as the Regulatory Framework of the oil and gas sector, has the potential to be amended once the carbon tax is implemented. The findings provide an overview of the government’s considerations contributing to the years-long delay in implementation and enrich the government's viewpoint on developing a carbon tax policy, considering the industry's perspective and readiness factors.

Grobogan Regency, Central Java, is characterized by karst landscapes, particularly in the Sukolilo Karst Landscape Area (Kawasan Bentang Alam Karst—KBAK Sukolilo), which plays a crucial role in regional water availability. Although the northern and western parts of the regency have the potential to store groundwater due to karstification, the southern regions often face water scarcity and prolonged droughts. This study aims to (1) identify the spatial distribution of springs in KBAK Sukolilo, and (2) analyze water availability across the karst area. A quantitative research approach was employed, focusing on 43 springs distributed across six subdistricts: Klambu, Brati, Grobogan, Tawangharjo, Wirosari, and Ngaringan. Data collection involved field observations, interviews, and documentation, while spatial and environmental analyses were conducted using Geographic Information Systems (GIS). The findings reveal an uneven and dynamic distribution of springs, with some springs recorded in 2018 no longer active or traceable in 2024 due to land cover changes and diminished discharge. Based on study, it was seen that the water demand in three sub-districts exceeded the water availability. Water balance analysis indicates that Brati, Grobogan, and Ngaringan are categorized as water-deficit areas, whereas Klambu, Tawangharjo, and Wirosari experience a water surplus. These results highlight the urgent need for integrated water resource management in karst environments, particularly in addressing regional disparities in water availability.

The increasing integration of distributed renewable resources such as photovoltaic (PV), wind, and battery energy storage systems (BESS) introduces both opportunities and challenges in managing hybrid microgrids. This study develops a forecast-integrated load control framework for a six-classroom microgrid supplied by PV, wind, BESS, diesel generator, and the utility grid. Short-term forecasts of renewable generation and building load are embedded in a Particle Swarm Optimization (PSO) model to generate 15-minute scheduling decisions. The objective function minimizes grid import, peak demand, and operating cost while maintaining comfort and technical constraints. The framework was experimentally validated using IoT-enabled sensing and SCADA-based control at an educational facility. Results demonstrate forecasting accuracy above 92%, a 31% reduction in peak demand, a 28% increase in PV self-consumption, and a 21.5% reduction in energy costs compared with rule-based and GA-based strategies. Sensitivity and robustness analyses confirm stable performance under ±15% forecast deviation. The proposed framework provides a scalable, adaptive, and cost-effective strategy for renewable-rich microgrids, offering direct implications for smart campus and commercial energy management.

In the present study, the Archimedes turbine is employed at low heads at Barrages and regulators in Anbar Province, Iraq. It is a small hydropower station that is suitable for application because it does not require high storage water (high head) in a Barrage. The 3D numerical model (ANSYS) has been employed for simulating and determining the power produced from the turbine in the Barrages. The physical model is applied to determine the optimal inclination angles of the shaft turbine (α) with a suitable water flow rate. This physical model was applied after conducting a set of tests that included different inclination angles of the shaft turbine (30°, 35°, 40°, 45°) and different discharges also reached the highest efficiency of 89.4% for the optimal angle of the model 35°. The results show Ramadi and Fallujah Barrages are the best investments in generating power because the discharges of these barrages continue throughout the year. Using Archimedes screw turbine as clean energy technology is an effective method and can be used to generate clean power without the need for large storage water because it appropriates the hydrologic conditions of the Euphrates River in Iraq. This study supports renewable energy, improves energy access, and contributes to energy efficiency and energy security for local communities.