EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 267 (2021) E3S Web Conf., 267 (2021) 01008 References
Open Access
Issue
E3S Web Conf.
Volume 267, 2021
7th International Conference on Energy Science and Chemical Engineering (ICESCE 2021)
Article Number 01008
Number of page(s) 7
Section Energy Development and Utilization and Energy-Saving Technology Application
DOI https://doi.org/10.1051/e3sconf/202126701008
Published online 04 June 2021
  1. Kittner N, Lill F, Kammen D M. Energy storage deployment and innovation for the clean energy transition[J]. Nature Energy, 2017, 2(9): 1–6. [Google Scholar]
  2. Li X, Yang X, Xue H, et al. Metal–organic frameworks as a platform for clean energy applications[J]. EnergyChem, 2020, 2(2): 100027. [Google Scholar]
  3. Lowitzsch J, Hoicka C E, Van Tulder F J. Renewable energy communities under the 2019 European Clean Energy Package–Governance model for the energy clusters of the future?[J]. Renewable and Sustainable Energy Reviews, 2020, 122: 109489. [Google Scholar]
  4. Obama B. The irreversible momentum of clean energy[M]. Science, 2017, 355(6321): 126–129. [CrossRef] [PubMed] [Google Scholar]
  5. Carter E, Yan L, Fu Y, et al. Household transitions to clean energy in a multiprovincial cohort study in China[J]. Nature Sustainability, 2020, 3(1): 42–50. [Google Scholar]
  6. Xie B C, Zhao W, Yin Z L, et al. How much will the residents pay for clean energy? Empirical study using the double bound dichotomous choice method for Tianjin, China[J]. Journal of Cleaner Production, 2019, 241: 118208. [Google Scholar]
  7. Wei J, Duan H, Yan Q. Shale gas: Will it become a new type of clean energy in China?—A perspective of development potential[J]. Journal of Cleaner Production, 2021, 294: 126257. [Google Scholar]
  8. Tan H, Thurbon E, Kim S Y, et al. Overcoming incumbent resistance to the clean energy shift: How local governments act as change agents in coal power station closures in China[J]. Energy Policy, 2021, 149: 112058. [Google Scholar]
  9. Chen J, Liu W, Jiang D, et al. Preliminary investigation on the feasibility of a clean CAES system coupled with wind and solar energy in China[J]. Energy, 2017, 127: 462-478. [Google Scholar]
  10. Hongtao L, Wenjia L. The analysis of effects of clean energy power generation[J]. Energy Procedia, 2018, 152: 947-952. [Google Scholar]
  11. Ma Y, Yan J, Sha J, et al. Dynamic simulation of the atmospheric environment improved by a focus on clean energy utilization of resource-based cities in China[J]. Journal of Cleaner Production, 2018, 192: 396-410. [Google Scholar]
  12. Gu F, Wang J, Guo J, et al. How the supply and demand of steam coal affect the investment in clean energy industry? Evidence from China[J]. Resources Policy, 2020, 69: 101788. [Google Scholar]
  13. Isoaho K, Goritz A, Schulz N. Governing clean energy transitions in China and India[J]. The Political Economy of Clean Energy Transitions, 2017: 231-249. [Google Scholar]
  14. Xiao Q, Gao M, Xiao X, et al. A novel grey Riccati–Bernoulli model and its application for the clean energy consumption prediction[J]. Engineering Applications of Artificial Intelligence, 2020, 95: 103863. [Google Scholar]
  15. Wang G, Xu Y, Ren H. Intelligent and ecological coal mining as well as clean utilization technology in China: Review and prospects[J]. International Journal of Mining Science and Technology, 2019, 29(2): 161–169. [Google Scholar]
  16. Wang J, Zhao T, Zhang X. Environmental assessment and investment strategies of provincial industrial sector in China—Analysis based on DEA model[J]. Environmental Impact Assessment Review, 2016, 60: 156-168. [Google Scholar]
  17. Liu Q, Wang S, Zhang W, et al. China’s municipal public infrastructure: Estimating construction levels and investment efficiency using the entropy method and a DEA model[J]. Habitat International, 2017, 64: 59-70. [Google Scholar]
  18. Kang Y Q, Xie B C, Wang J, et al. Environmental assessment and investment strategy for China’s manufacturing industry: A non-radial DEA based analysis[J]. Journal of Cleaner Production, 2018, 175: 501-511.. [Google Scholar]
  19. Tan X. China’s overseas investment in the energy/resources sector: Its scale, drivers, challenges and implications[J]. Energy Economics, 2013, 36: 750-758. [Google Scholar]
  20. Zhang S, Wang W, Wang L, et al. Review of China’s wind power firms internationalization: Status quo, determinants, prospects and policy implications[J]. Renewable and Sustainable Energy Reviews, 2015, 43: 1333-1342. [Google Scholar]
  21. Ghemawat P, Hout T. Can China’s Companies Conquer the World: The Overlooked Importance of Corporate Power[J]. Foreign Aff., 2016, 95: 86. [Google Scholar]
  22. Duan F, Ji Q, Liu B Y, et al. Energy investment risk assessment for nations along China’s Belt & Road Initiative[J]. Journal of Cleaner Production, 2018, 170: 535-547. [Google Scholar]
  23. Shen W, Power M. Africa and the export of China’s clean energy revolution[J]. Third World Quarterly, 2017, 38(3): 678–697. [Google Scholar]
  24. Zeng S, Jiang C, Ma C, et al. Investment efficiency of the new energy industry in China[J]. Energy Economics, 2018, 70: 536-544. [Google Scholar]
  25. He Y, Chen C, Hu Y. Managerial overconfidence, internal financing, and investment efficiency: Evidence from China[J]. Research in International Business and Finance, 2019, 47: 501-510. [Google Scholar]
  26. Shahzad F, Rehman I U, Nawaz F, et al. Does family control explain why corporate social responsibility affects investment efficiency?[J]. Corporate Social Responsibility and Environmental Management, 2018, 25(5): 880–888. [Google Scholar]
  27. Li Y, He J, Xiao M. Risk disclosure in annual reports and corporate investment efficiency[J]. International Review of Economics & Finance, 2019, 63: 138-151. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.