Harnessing a Renewable Resource for Sustainability: The Role of Geothermal Energy in Italy’s Business Sector DOI Creative Commons
Angelo Arcuri,

Lorenzo Giolli,

Cosimo Magazzino

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1590 - 1590

Published: March 22, 2025

Addressing critical challenges such as climate change, environmental degradation, and resource depletion requires a swift transition to efficient environmentally friendly energy solutions. Among these, geothermal is recognized for its dependability, low impact, versatility. This study investigates the role of in Italy’s business sector, examining impact on companies social perception. It specifically evaluates how communicating geological, hydrological, atmospheric risks associated with projects influences firms’ likelihood experiencing acceptance challenges. Additionally, this research quantifies adoption companies’ costs CO2 emissions. The analysis further explores long-term implications expanding use renewable through sensitivity analysis, focusing effects emissions costs. findings indicate that firms geothermal-related are less likely experience compared those do not. Moreover, shows positively impacts performance by reducing Sensitivity demonstrates increasing proportion usage amplifies these benefits, thereby enhancing competitiveness. provides comprehensive framework promoting integration operations, offering valuable insights support global shift toward sustainable systems.

Language: Английский

Towards sustainable environment in North African countries: The role of military expenditure, renewable energy, tourism, manufacture, and globalization on environmental degradation DOI
Ghalieb Mutig Idroes,

Hasanur Rahman,

Imtiaz Uddin

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 368, P. 122077 - 122077

Published: Aug. 9, 2024

Language: Английский

Citations

25
Environmental and Economic Clustering of Indonesian Provinces: Insights from K-Means Analysis DOI Creative Commons
Teuku Rizky Noviandy, Irsan Hardi,

Zahriah Zahriah

et al.

Leuser Journal of Environmental Studies, Journal Year: 2024, Volume and Issue: 2(1), P. 41 - 51

Published: April 29, 2024

Indonesia's archipelago presents a distinctive opportunity for targeted sustainable development due to its complex interplay of economic advancement and environmental challenges. To better understand this dynamic identify potential areas focused intervention, study applied K-means clustering 2022 data on the Air Quality Index (AQI), electricity consumption, Gross Regional Domestic Product (GRDP). The analysis aimed delineate provinces into three distinct clusters, providing clearer picture varying levels impact across nation's diverse islands. Each cluster reflects specific dynamics, suggesting tailored policy interventions. results show that in Cluster 1, which exhibit moderate quality lower activity, introduction agricultural enhancements, eco-tourism, renewable energy initiatives is recommended. 2, marked by higher outputs conditions, would benefit from implementation smart urban planning, stricter controls, adoption clean technologies. Finally, 3, includes highly urbanized with robust growth, requires expanded green infrastructure, improved practices, enhanced public transportation systems. These recommendations aim foster balanced growth while preserving integrity Indonesia’s landscapes.

Language: Английский

Citations

20
Business Confidence in the Shift to Renewable Energy: A Country-Specific Assessment in Major Asian Economies DOI Creative Commons
Irsan Hardi, Ghalieb Mutig Idroes, Yoshihiro Hamaguchi

et al.

Journal of Economy and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

The growing awareness of the importance transitioning to sustainable energy sources emphasizes necessity fostering business optimism toward renewable energy, as businesses wield significant influence in driving innovation and scaling up deployment. Therefore, this study investigates impact confidence on long-term generation selected major Asian economies: China, Japan, South Korea, Indonesia, Turkey. Through country-specific assessments, we utilized three methods capable yielding empirical results: Fully-Modified OLS (FMOLS), Dynamic (DOLS), Canonical Cointegrating Regressions (CCR). also conducted a robustness check by utilizing Robust Least Squares (RLS) method, preceded multiple preliminary tests, ensure validity reliability results. findings show that all countries exhibit energy. However, there are variations level, with Turkey demonstrating high while those China Indonesia low confidence. found trade-off between levels consumption. In Turkey, correlates negative consumption, is aligned positive effect consumption This suggests dynamics development. Policy recommendations tailored each provided address these findings, aiming enhance trust within economies.

Language: Английский

Citations

15
Enhancing Environmental Quality: Investigating the Impact of Hydropower Energy Consumption on CO2 Emissions in Indonesia DOI Creative Commons

Putri Maulidar,

Sintia Fadila,

I Hafizah

et al.

Ekonomikalia Journal of Economics, Journal Year: 2024, Volume and Issue: 2(1), P. 53 - 65

Published: April 28, 2024

Achieving sustainable environmental quality has become a critical global issue, necessitating the reduction of carbon dioxide (CO2) emissions and greenhouse gas (GHG) to mitigate pollution. Hydropower energy potential play significant role in this effort by providing clean, renewable source that can help reduce reliance on fossil fuels decrease CO2 emissions. This study examines dynamic impact hydropower consumption, economic growth, capital, labor Indonesia's from 1990 2020. Applying Autoregressive Distributed Lag (ARDL) method, findings demonstrate consumption negative effect both short long term, indicating increasing leads Conversely, exhibits positive influence suggesting rise contributes higher levels Indonesia. Furthermore, Granger causality analysis reveals bidirectional relationship between consumption. The robustness ARDL results is confirmed through additional tests using Fully-Modified Ordinary Least Squares (FMOLS), Dynamic (DOLS), Canonical Cointegrating Regressions (CCR) methods. underscore importance promoting for effective management Policymakers should prioritize investments infrastructure, encourage adoption energy-efficient technologies, develop skilled workforce increased force participation.

Language: Английский

Citations

14
Shadow Economy, Energy Consumption, and Ecological Footprint in Indonesia DOI Creative Commons
Irsan Hardi, Mohd Afjal, Muhlis Can

et al.

Sustainable Futures, Journal Year: 2024, Volume and Issue: unknown, P. 100343 - 100343

Published: Oct. 1, 2024

Language: Английский

Citations

12
The Impact of Non-Green Trade Openness on Environmental Degradation in Newly Industrialized Countries DOI

Sil Van Hek,

Muhlis Can, Jan Brusselaers

et al.

Ekonomikalia Journal of Economics, Journal Year: 2024, Volume and Issue: 2(2), P. 66 - 81

Published: May 14, 2024

Environmental degradation due to human over-exploitation is one of the most pressing global issues. The ten Newly Industrialized Countries (NICs) have recently witnessed substantial economic growth and involvement in trade. In discussion on environmental degradation, trade has a crucial role. Scholars use openness test scale effect environment. This research investigates non-green openness, growth, energy consumption ecological footprint. Panel estimation techniques such as cross-sectional dependence, slope homogeneity, unit root, cointegration analyses are applied panel data NICs between 2003 2016. Fully Modified Ordinary Least Squares (FMOLS) method reveals that increases panel. Energy also found increase degradation. Moreover, Kuznets Curve (EKC) hypothesis validated. presents few relevant policy implications. should invest green an energy-efficient economy focus stimulating catalyst for sustainable development order improve quality their can be done by introducing higher tariffs products investing technological innovations production methods renewable energy. Although local pollution European Union (EU) decreases, threatens state Therefore, approached international problem detrimental effects all countries different phases development.

Language: Английский

Citations

12
Business Confidence in Indonesia: Which Macroeconomic Factors Have Long-Term Impact? DOI
Irsan Hardi, Najabat Ali,

Niroj Duwal

et al.

Indatu Journal of Management and Accounting, Journal Year: 2024, Volume and Issue: 2(1), P. 40 - 54

Published: June 19, 2024

Business confidence refers to the level of optimism or pessimism that business owners have about prospects their companies and overall economy. Thus, focus this study is examine long-term impact various macroeconomic factors—economic growth, government expenditure, interest rates, inflation, exchange composite stock price index—on index in Indonesia by utilizing monthly data from January 2009 December 2022. We employ Dynamic Ordinary Least Squares (DOLS) Fully-Modified (FMOLS) as main methods, with Canonical Cointegrating Regressions (CCR) a robustness check method. The also utilizes pairwise Granger causality tests for comprehensive analysis. findings indicate all factors significantly long term across methodologies. Specifically, economic exert positive impact, while rates negative on index. This evidence emphasizes importance businesses diligently monitor trends understand patterns these indicators so can better anticipate changes sentiment. Taking perspective when making strategic decisions investments advisable, recognizing influence may be more pronounced over time.

Language: Английский

Citations

11
A Model-Agnostic Interpretability Approach to Predicting Customer Churn in the Telecommunications Industry DOI Creative Commons
Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

et al.

Infolitika Journal of Data Science, Journal Year: 2024, Volume and Issue: 2(1), P. 34 - 44

Published: May 27, 2024

Customer churn is critical for businesses across various industries, especially in the telecommunications sector, where high rates can significantly impact revenue and growth. Understanding factors leading to customer essential developing effective retention strategies. Despite predictive power of machine learning models, there a growing demand model interpretability ensure trust transparency decision-making processes. This study addresses this gap by applying advanced specifically Naïve Bayes, Random Forest, AdaBoost, XGBoost, LightGBM, predict dataset. We enhanced using SHapley Additive exPlanations (SHAP), which provides insights into feature contributions predictions. Here, we show that LightGBM achieved highest performance among with an accuracy 80.70%, precision 84.35%, recall 90.54%, F1-score 87.34%. SHAP analysis revealed features such as tenure, contract type, monthly charges are significant predictors churn. These results indicate combining analytics methods provide telecom companies actionable tailor strategies effectively. The highlights importance understanding behavior through transparent accurate paving way improved satisfaction loyalty. Future research should focus on validating these findings real-world data, exploring more sophisticated incorporating temporal dynamics enhance prediction models' applicability.

Language: Английский

Citations

10
An Interpretable Machine Learning Strategy for Antimalarial Drug Discovery with LightGBM and SHAP DOI Creative Commons
Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

et al.

Journal of Future Artificial Intelligence and Technologies, Journal Year: 2024, Volume and Issue: 1(2), P. 84 - 95

Published: Aug. 7, 2024

Malaria continues to pose a significant global health threat, and the emergence of drug-resistant malaria exacerbates challenge, underscoring urgent need for new antimalarial drugs. While several machine learning algorithms have been applied quantitative structure-activity relationship (QSAR) modeling compounds, there remains more interpretable models that can provide insights into underlying mechanisms drug action, facilitating rational design compounds. This study develops QSAR model using Light Gradient Boosting Machine (LightGBM). The is integrated with SHapley Additive exPlanations (SHAP) enhance interpretability. LightGBM demonstrated superior performance in predicting activity, an ac-curacy 86%, precision 85%, sensitivity 81%, specificity 89%, F1-score 83%. SHAP analysis identified key molecular descriptors such as maxdO GATS2m contributors activity. integration not only enhances predictive but also provides valuable importance features, aiding approach bridges gap between accuracy interpretability, offering robust framework efficient effective discovery against strains.

Language: Английский

Citations

8
Spatial-temporal characteristics and drivers of urban built-up areas land low-carbon efficiency in China DOI Creative Commons
Jinjun Guo, Pengfei Feng, Han Xue

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 10, 2025

Understanding the evolution of low-carbon efficiency in urban built-up areas is essential for developing countries striving to meet sustainable development goals. However, mechanisms driving and associated pathways remain underexplored. This study applies Global Data Envelopment Analysis (DEA) model, Malmquist-Luenberger Index, econometric models evaluate its determinants across China's from 2010 2022. The findings reveal a significant increase efficiency, 0.555 0.785 2022, reflecting an overall improvement 41.4% (P < 0.05). Spatially, demonstrates pronounced "east-high west-low" distribution, highlighting regional disparities spatial correlations. Temporal changes are primarily driven by technological advancements shifts frontier. disproportionate gains during periods high resource input suggest inefficiencies production factor allocation, particularly densely populated centers. Unlike natural endowments, concentrated inputs such cities often impede improvements. underscore need context-sensitive strategies, as one-size-fits-all model may not address diverse challenges posed disparities. By leveraging market optimize allocation strengthen interregional connectivity, this provides actionable insights promoting land economies.

Language: Английский

Citations

1