Examining artificial intelligence and energy efficiency in the MENA region: The dual approach of DEA and SFA

被引:27
作者
Hossin, Md Altab [1 ]
Alemzero, David [2 ]
Wang, Ruping [3 ]
Kamruzzaman, M. M. [4 ]
Mhlanga, Mitchell N. [5 ]
机构
[1] Chengdu Univ, Sch Innovat & Entrepreneurship, 2025 Chengluo Ave, Chengdu 610106, Sichuan, Peoples R China
[2] Jiangsu Univ, Sch Econ & Finance, Zhenjiang 212013, Jiangsu, Peoples R China
[3] China West Normal Univ, Sch Management, Nanchong 637002, Peoples R China
[4] Jouf Univ, Coll Comp & Informat Sci, Dept Comp Sci, Sakakah, Saudi Arabia
[5] Jiangxi Univ Finance & Econ, Dept Int Trade, Nanchang, Jiangsu, Peoples R China
关键词
Artificial intelligence; Energy efficiency; MENA region; DEA; Stochastic frontier analysis; PRODUCTION FRONTIERS; COUNTRIES;
D O I
10.1016/j.egyr.2023.03.113
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The potential growth, privileged geographic location, emerging economies, and large market led to much potential research in the Middle East and North Africa (MENA) region. However, the role of Artificial intelligence (AI), along with other variables for energy efficiency (EE), to deliver economic and environmental benefits are yet underexplored in this region and brings a research lacuna. Thus, this study aims to present scientific evidence for the EE through the interaction effects of AI and energy use (ENEU) along with other variables in the MENA region from 2000-2021 using the dual approaches of data envelope analysis (DEA) and stochastic frontier analysis (SFA). The results confirm that countries such as Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Malta, Oman, Saudi Arabia, Tunisia, UEA, and the West Bank are the most energy efficient, deriving an efficiency value of one from their optimal solution of DEA. The panel's SFA analysis shows that AI, patents, renewable energy, and gross domestic product per capita (GDPPC) are meaningful and directly contribute to the study countries' EE gains. The interaction term of AI and ENEU is significant, which implies the relevance of AI and ENEU in achieving EE. Furthermore, EE is negatively related to carbon intensity between 17.4% and 64.5% or worsens EE by 49.3% depending on the country, allowing the region to meet its climate targets and achieve the environmental benefits of deploying AI. In addition, it means that the MENA region can integrate AI and ENEU to curb the increasing decentralization of the national grid, which leads to energy efficiency gains in this region. This calls for integrating Al and energy in an effective way to enhance the human consumption of energy, taking the needs of the environment into consideration in order to attain efficiency and intelligent energy use. The study attempts to shed light on energy use while integrating AI to achieve economic and environmental efficiencies in the MENA region.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:4984 / 4994
页数:11
相关论文
共 71 条
[1]   Scaling up renewable energy in Africa: measuring wind energy through econometric approach [J].
Abbas, Qaiser ;
Khan, Abdul Razzaq ;
Bashir, Ahmed ;
Alemzero, David Ajene ;
Sun, Huaping ;
Iram, Robina ;
Iqbal, Nadeem .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 27 (29) :36282-36294
[2]  
Acquah P.M., 2021, DETERMINANTS ENERGY
[3]   Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities [J].
Ahmad, Tanveer ;
Zhang, Dongdong ;
Huang, Chao ;
Zhang, Hongcai ;
Dai, Ningyi ;
Song, Yonghua ;
Chen, Huanxin .
JOURNAL OF CLEANER PRODUCTION, 2021, 289
[4]   EFFICIENCY CHARACTERIZATIONS IN DIFFERENT DEA MODELS [J].
AHN, T ;
CHARNES, A ;
COOPER, WW .
SOCIO-ECONOMIC PLANNING SCIENCES, 1988, 22 (06) :253-257
[5]  
Aigner D, 1977, Journal of Econometrics, V6, P21, DOI 10.1016/0304-4076(77)90052-5
[6]   Heterogeneous effects of energy efficiency and renewable energy on economic growth of BRICS countries: A fixed effect panel quantile regression analysis [J].
Akram, Rabia ;
Chen, Fuzhong ;
Khalid, Fahad ;
Huang, Guanhua ;
Irfan, Muhammad .
ENERGY, 2021, 215
[7]   Prospects of wind energy deployment in Africa: Technical and economic analysis [J].
Alemzero, David ;
Acheampong, Theophilus ;
Huaping, Sun .
RENEWABLE ENERGY, 2021, 179 :652-666
[8]   Assessing energy security in Africa based on multi-dimensional approach of principal composite analysis [J].
Alemzero, David Ajene ;
Sun, Huaping ;
Mohsin, Muhammad ;
Iqbal, Nadeem ;
Nadeem, Muhammad ;
Vo, Xuan Vinh .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (02) :2158-2171
[9]  
Alnafrah I, 2021, J INNOV ENTREPRENEUR, V10, P26, DOI [DOI 10.1186/S13731-021-00159-3, 10.1186/s13731-021-00159-3]
[10]  
[Anonymous], 2017, Digitalization Energy, DOI [DOI 10.1787/9789264286276-EN, 10.1021/acs.jafc.8b00483, 10.1787/9789264286276-en]