Assessing Renewable Energy Adoption to Achieve Sustainable Development Goals in Ha’il Region

Rabab Triki, Shawky Mohamed Mahmoud, Younès Bahou () and Mohamed Mahdi Boudabous
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Rabab Triki: Management Information Systems Department, Applied College, Ha’il University, P.O. Box 2440, Ha’il 55424, Saudi Arabia
Shawky Mohamed Mahmoud: Computer Science Department, Applied College, Ha’il University, P.O. Box 2440, Ha’il 55424, Saudi Arabia
Younès Bahou: Computer Science Department, Applied College, Ha’il University, P.O. Box 2440, Ha’il 55424, Saudi Arabia
Mohamed Mahdi Boudabous: Department of Information and Computer Science, College of Computer Science and Engineering, Ha’il University, P.O. Box 2440, Ha’il 55424, Saudi Arabia

Sustainability, 2025, vol. 17, issue 13, 1-15

Abstract: Today’s environmental issues are among the primary themes that researchers explore in their search for practical solutions to achieve the Sustainable Development Goals (SDGs), such as reducing carbon emissions and promoting sustainable practices. Renewable energy is crucial to overcoming future challenges, causing many countries to accelerate their adoption at various levels. In this context, the impact of renewable energy adoption on achieving the Sustainable Development Goals in the Ha’il region has been evaluated. Specifically, two techniques are employed. The first technique is an empirical model based on the Vector Error Correction Model (VECM), which identifies the SDGs related to renewable energy in achieving SDGH. Only three SDGs (SDG7, SDG12, and SDG13) were found to influence SDGH significantly. The second technique uses deep learning, specifically LSTM networks, to forecast SDGH behavior over a ten-year period about the three selected SDGs. The results indicate that these three SDGs play a crucial role in sustainable development in the Ha’il region. Therefore, this research produces strategic recommendations to optimize the adoption of renewable energy in the Ha’il region. These findings provide policymakers with a data-driven framework to enhance strategies, utilize resources more efficiently, and promote broader sustainability initiatives.

Keywords: renewable energy; SDGs; VECM; deep learning technique; LSTM networks; Ha’il region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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