Issue #1 (Volume 17 2026)

Type of the article: Research Article

Abstract
This paper aims to examine the role of artificial intelligence (AI) training effectiveness in achieving a green growth strategy in Jordan, particularly at the Jordanian Electric Power Company, which represents the Jordanian energy sector. The analysis is supported by the multifaceted program evaluation framework by Daniel Stufflebeam (CIPP). AI training is considered a strategic intangible asset that promotes the growth of rare and invaluable intangible human capital. Quantitative cross-sectional research design was applied, targeting employees of the Jordanian Electric Power Company. Using a simple random sampling, 178 valid responses were directly engaged. The assessment of the theoretical and structural models was done using SPSS and SmartPLS. The results indicated that AI training effectiveness is a significant predictor of the green growth strategy’s outcomes (β = 0.562, t = 8.990, p < 0.001), explaining 31.6% of the variance. The strongest predictor among the CIPP dimensions was the dimension of input (β = 0.556, R2 = 0.310), then the dimensions of context (β = 0.532, R2 = 0.283), process (β = 0.516, R2 = 0.266), and product (β = 0.487, R2 = 0.237). These findings indicate that highly developed training programs, when designed according to the organizational context, resource-rich, and executed effectively, yield quantifiable skills development and play an influential role in meeting the goals of the national green growth strategy.

Acknowledgment
Gratitude is expressed to the Middle East University, Amman, Jordan, for the financial support to cover this article’s publishing fee.

Type of the article: Research Article

Abstract
This study examines the effect of ESG reporting on the financial performance of green companies listed in Indonesia between 2020 and 2024, totaling 85 companies with 425 observations. Using ESG scores and corporate financial data from Bloomberg, three panel models were estimated: a random-effects model for ROA, a fixed-effects model for ROE, controlling for size, leverage, growth, and cash flow, and a test for sectoral differences between energy and non-energy companies. The results indicate that governance scores are positively associated with ROA (β = 0.011, p = 0.092), whereas ESG scores are weakly positively associated with ROA (β = 0.020, p = 0.080). Environmental and social scores are not statistically significant to ROA or ROE. For ROE, firm size is the main significant predictor (β = 2.126, p = 0.042). The results observe significant differences between the energy and non-energy sectors, with the energy sector reporting higher financial performance after controlling for ESG. Finally, this study indicates that ESG reporting policies that promote good governance can yield faster returns to shareholders.

Acknowledgment
This study was supported by the Ministry of Research, Technology, and Greater Education and Al-Madani School of Economic Sciences. 

Type of the article: Research Article

Abstract
This study aims to empirically examine the dynamic effects of geopolitical risk, economic policy uncertainty, and climate policy uncertainty on CO₂ emissions in G7 economies, utilizing annual data from 1990 to 2022. To account for cross-sectional dependence and parameter heterogeneity, the analysis employs a cross-sectional autoregressive distributed lag (CS-ARDL) model. Diagnostic tests confirm significant cross-sectional dependence and slope heterogeneity among the variables. All variables are integrated of order one, I (1), confirmed by unit root tests. In contrast, the cointegration test provides a strong indication of a stable long-run relationship among geopolitical risk, policy uncertainty measures, and CO₂ emissions. The outcomes show that a 1% rise in the geopolitical risk index leads to a statistically significant long-run rise of 0.042% in per capita CO₂ emissions. In addition, a 1% increase in economic policy uncertainty and climate policy uncertainty is associated with long-run increases of 0.028% and 0.015%, respectively. These results remain robust across alternative estimators. Overall, the evidence suggests that heightened geopolitical risk and policy-related uncertainties significantly exacerbate environmental degradation in G7 economies, highlighting the necessity for strategies that improve stability, reduce uncertainty, and encourage renewable energy adoption as part of a long-term environmental strategy.

Type of the article: Research Article

Abstract
This study aims to investigate the economic effect of climate change by providing rigorous evidence of its impact in the most climate-susceptible economies, with Vietnam as a representative case. The study scrutinizes the economic growth impact of climate change while examining the intervening roles of renewable energy usage, trade openness, and the interaction between renewable energy usage and financial development in both the short and long run. Applying the ARDL framework using Vietnam’s data from 1992 to 2022, the results provide evidence that climate change exerts a direct influence on growth across both time horizons. Specifically, a one-degree Celsius increase in temperature is associated with an approximate 0.18% increase in GDP in the long run, and 0.018% in the short run. The findings suggest that greater reliance on renewable energy contributes positively to economic performance, as a 1% increase in the renewable energy share within the energy mix corresponds to a 1.1% expansion in GDP. In contrast, increased trade openness is found to adversely affect long-run growth, with a 1% rise in openness linked to a GDP contraction of about 0.004%. Furthermore, the joint effect of renewable energy utilization and financial development does not display a statistically significant influence on long-run growth. Conversely, short-run dynamics indicate that changes in this interaction support growth, while adjustments in renewable energy consumption and trade openness tend to dampen growth performance. The study recommends policies that enhance climate resilience, promote renewable energy, and support trade strategies to strengthen production value chains for sustainable growth.

Type of the article: Research Article

Abstract
This study investigates the long-run and short-run determinants of CO₂ emissions in African countries, with a particular focus on the roles of globalization, renewable energy consumption, and economic growth for 24 African countries over 1990–2021. Using a panel ARDL framework with PMG, MG, and DFE estimators, we estimate both short-run and long-run relationships and conduct co-integration, cross-section dependence, and robustness checks. The PMG long-run estimates confirm an Environmental Kuznets Curve: GDP has a positive long-run elasticity of 0.237 with CO₂ (p < 0.01), while its square indicates a turning point; renewable energy reduces emissions (long-run elasticity −0.158, p < 0.01); globalization (KOF index) is associated with higher emissions (elasticity 0.350, p < 0.01). Non-renewable energy results are sensitive to estimator choice. Error-correction terms are negative and significant, indicating adjustment to the long-run equilibrium. Results are robust to alternative specifications and subsamples. Policy implications include accelerating renewable deployment and adopting trade and investment policies that favor cleaner technologies to align growth with climate objectives.

Type of the article: Research Article

Abstract
Aligning environmental objectives with economic performance is an ongoing challenge in the renewable energy transition, especially in emerging solar markets facing operational inefficiencies and uneven policy implementation. This paper examines the environmental and economic efficiency of large-scale solar energy conversion projects by employing a Material Flow Cost Accounting methodology based on ISO 14051 standards. Based on the operating and financial performance data of 83 solar energy conversion projects (46 from India and 37 from Jordan) covering the period 2017–2023, avoidable energy loss costs due to dust settling, heat stress, grid curtailment, and plant downtime have been estimated and quantified cumulatively in both settings. The findings indicate a technical efficiency of 88.4% and 77.9% with an average energy loss potential of 128 and 274 gigawatt-hours per year in both settings of Jordan and India, respectively, causing an economic loss potential of 9.2% and 18.7%, respectively, collectively amounting to a financial loss potential of about 54.6 million annually. Systematic plant maintenance and coordinated use in electric grids increased output potential by about 16% and lowered costs by 13%, with efficient management options collectively leading to an 11.5% increase in financial returns in Jordan and a 19.3% boost in India’s financial performance. Based on findings, MFCA methodology is indeed capable of interlinking environmental protection with economic performance for efficient, sustainable energy policymaking within developing nations.