Applied Ecology and Environmental Sciences
ISSN (Print): 2328-3912 ISSN (Online): 2328-3920 Website: https://www.sciepub.com/journal/aees Editor-in-chief: Alejandro González Medina
Open Access
Journal Browser
Go
Applied Ecology and Environmental Sciences. 2025, 13(1), 27-33
DOI: 10.12691/aees-13-1-4
Open AccessArticle

Spatiotemporal Distribution and Efficiency Measurement of Major Global Electricity Export Countries

Mengyao Zhang1,

1School of Economics and Management, Tiangong University, Tianjin, China

Pub. Date: May 05, 2025

Cite this paper:
Mengyao Zhang. Spatiotemporal Distribution and Efficiency Measurement of Major Global Electricity Export Countries. Applied Ecology and Environmental Sciences. 2025; 13(1):27-33. doi: 10.12691/aees-13-1-4

Abstract

With the continuous growth of global energy demand and increasing environmental concerns, electricity, as a critical energy carrier, has become increasingly vital in global economic and social development. This study systematically analyzed the spatiotemporal distribution characteristics and efficiency evolution of the top 50 global electricity-exporting countries from 2014 to 2023 using the DEA-BCC model and Malmquist index method. Key findings include: (1) Electricity exports exhibited significant regional agglomeration, with Europe maintaining dominance through its mature transnational grid systems, while China emerged as Asia’s core driver, boosting regional export volumes. (2) Efficiency measurements revealed a decline in the number of DEA-strongly efficient countries (from 4 to 3) and an increase in weakly efficient countries (to 6), primarily due to insufficient scale efficiency. Major exporters such as the U.S. and Italy remained inefficient owing to suboptimal resource allocation. (3) Total factor productivity (TFP) showed an average annual growth of 7.7%, driven by technological progress, but scale efficiency stagnated (index: 0.899), indicating room for scaling optimization.

Keywords:
Electricity Spatiotemporal distribution Efficiency DEA-BCC Malmquist index

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  International Energy Agency (IEA), World Energy Outlook 2020, IEA Publications, Paris, 2020, 50-55.
 
[2]  Qiang Zhang, Debin Du, Weidong Guo, Ziming Yan, Wanpeng Cao, Qifan Xia. Spatio-temporal evolution and key drivers of global energy structural power. Acta Geographica Sinica, 78(9): 2316-2337, 2023.
 
[3]  He Ze, Yang Yu, Liu Yi, et al. Characteristics of evolution of global energy trading network and relationships between major countries. Progress in Geography, 38(10): 1621-1632, 2019.
 
[4]  Xia Qifan, Du Debin. Evolution of energy trade structure in the 21st Century Maritime Silk Road and its trade relations with China. Geographical Research,, 41(7): 1797-1813, 2022.
 
[5]  Zhaohui Chong, Xinjie Jiang, Ze He. Research on the network dependence characteristics and substitution in international trade: Fossil energy and renewable energy. Geographical Research, 41(12): 3214-3228, 2022.
 
[6]  Li Wang, Liang Wu, Yanpeng Li, et al.. The geopolitical driving forces and mechanism on Arctic energy exploitation. Acta Geographica Sinica, 76(5): 1078-1089, 2021.
 
[7]  Ziling Yu, Lili Ma, Mengcheng Ren. Research on the construction of power interconnection network of China-ASEAN "big grid cluster". World Geography Research, 32 (08): 25-36, 2023.
 
[8]  Beibei Wang, Zhongyao Chen, Xin Gu, et al. Study on cross-border electricity trade pattern and construction time sequence of countries along the "Belt and Road". Global Energy Internet, 4(01): 77-85, 2021.
 
[9]  Yue Wang, Yingjia Liu, Ling Ji, et al. Analysis of global electricity trade network structure. Electric Power Construction, 37(03): 129-136, 2016.
 
[10]  Charnes, A. C., Cooper, W. W., and Rhodes, E. L. Measuring the efficiency of decision making units. European Journal of Operational Research, 3(4): 338-339, 1978.