Can wind power policies effectively improve the productive efficiency of Chinese wind power industry?

References

• Akbari, N., D. Jones, and R. Treloar. 2020. A cross-european efficiency assessment of offshore wind farms: A DEA approach. Renewable Energy 151:1186–95. doi:10.1016/j.renene.2019.11.130.
   Web of Science ®Google Scholar
• Bergen, W. G., and D. B. Bates. 1984. Ionophores: Their effect on production efficiency and mode of action. Journal of Animal Ence 58 (6):1465–83.
   PubMed Web of Science ®Google Scholar
• Boretti, A. 2021. Integration of solar thermal and photovoltaic, wind, and battery energy storage through AI in NEOM city. Energy and AI 3:100038. doi:10.1016/j.egyai.2020.100038.
   Google Scholar
• Browning, M. S., and C. S. Lenox. 2020. Contribution of offshore wind to the power grid: US air quality implications. Applied Energy 276:115474. doi:10.1016/j.apenergy.2020.115474.
   PubMed Web of Science ®Google Scholar
• Buzzigoli, L., A. Giusti, and A. Viviani. 2010. The evaluation of university departments. A case study for Firenze. International Advances in Economic Research 16 (1):24–38. doi:10.1007/s11294-009-9243-6.
   Google Scholar
• Chen, J., Y. Wu, M. Song, and Z. Zhu. 2017. Stochastic frontier analysis of productive efficiency in China’s forestry industry. Journal of Forest Economics 28:87–95. doi:10.1016/j.jfe.2017.05.005.
   Web of Science ®Google Scholar
• David, P. A., B. H. Hall, and A. A. Toole. 2000. Is public R&D a complement or substitute for private R&D? A review of the econometric evidence. Research Policy 29 (4–5):497–529. doi:10.1016/S0048-7333(99)00087-6.
   Web of Science ®Google Scholar
• Ding, X., O. Guedhami, Y. Ni, and J. A. Pittman. 2020. Local and foreign institutional investors, information asymmetries, and state ownership. Pacific-Basin Finance Journal 63:101405. doi:10.1016/j.pacfin.2020.101405.
   Web of Science ®Google Scholar
• Dong, F., and L. Shi. 2019. Regional differences study of renewable energy performance: A case of wind power in China. Journal of Cleaner Production 233:490–500.
   Web of Science ®Google Scholar
• Dong, F., & Li, W. (2021). Research on the coupling coordination degree of “upstream-midstream-downstream” of China’s wind power industry chain. Journal of Cleaner Production 283:124633.
   Web of Science ®Google Scholar
• Dong, F., and W. Li. 2020a. Research on the coupling coordination degree of” upstream-midstream-downstream” of China’s wind power industry chain. Journal of Cleaner Production 283:124633.
   Web of Science ®Google Scholar
• Dong, F., and W. Li. 2020b. Research on coupling mechanism of China’s wind power industry chain. International Journal of Green Energy 17 (12):770–82. doi:10.1080/15435075.2020.1798768.
   Web of Science ®Google Scholar
• Fan, X. C., W. Q. Wang, R. J. Shi, and F. T. Li. 2015. Analysis and countermeasures of wind power curtailment in China. Renewable and Sustainable Energy Reviews 52:1429–36. doi:10.1016/j.rser.2015.08.025.
   Web of Science ®Google Scholar
• Hayashi, D., J. Huenteler, and J. I. Lewis. 2018. Gone with the wind: A learning curve analysis of China’s wind power industry. Energy Policy 120:38–51. doi:10.1016/j.enpol.2018.05.012.
   Web of Science ®Google Scholar
• He, Z. X., S. C. Xu, W. X. Shen, H. Zhang, R. Y. Long, H. Yang, and H. Chen. 2016. Review of factors affecting China’s offshore wind power industry. Renewable and Sustainable Energy Reviews 56:1372–86. doi:10.1016/j.rser.2015.12.037.
   Web of Science ®Google Scholar
• Henriques, I. C., V. A. Sobreiro, H. Kimura, and E. B. Mariano. 2020. Two-stage DEA in banks: Terminological Controversies and future directions. Expert Systems with Applications 161:113632. doi:10.1016/j.eswa.2020.113632.
   PubMed Web of Science ®Google Scholar
• Hirschhausen, C., A. Cullmann, and A. Kappeler. 2006. Efficiency analysis of German electricity distribution utilities - Non-parametric and parametric tests. Applied Economics 38 (21):2553–66. doi:10.1080/00036840500427650.
   Web of Science ®Google Scholar
• Iribarren, D., M. Martín-Gamboa, and J. Dufour. 2013. Environmental benchmarking of wind farms according to their operational performance. Energy 61:589–97. doi:10.1016/j.energy.2013.09.005.
   Web of Science ®Google Scholar
• Jain, R. 2020. Bribery and firm performance in India: A political economy perspective. Journal of Asian Economics 68:101181. doi:10.1016/j.asieco.2020.101181.
   Web of Science ®Google Scholar
• Lerida-Navarro, C., G. Nombela, and J. M. Tranchez-Martin. 2019. European railways: Liberalization and productive efficiency. Transport Policy 83:57–67. doi:10.1016/j.tranpol.2019.09.002.
   Web of Science ®Google Scholar
• Lesser, J. A., and X. Su. 2008. Design of an economically efficient feed-in tariff structure for renewable energy development. Energy Policy 36 (3):981–90. doi:10.1016/j.enpol.2007.11.007.
   Web of Science ®Google Scholar
• Li, C. B., P. Li, and X. Feng. 2014. Analysis of wind power generation operation management risk in China. Renewable Energy 64:266–75. doi:10.1016/j.renene.2013.11.055.
   Web of Science ®Google Scholar
• Li, H., and L.-A. Zhou. 2005. Political turnover and economic performance: The incentive role of personnel control in China. Journal of Public Economics 89 (9–10):1743–62. doi:10.1016/j.jpubeco.2004.06.009.
   Web of Science ®Google Scholar
• Li, L., X. Ren, Y. Yang, P. Zhang, and X. Chen. 2018b. Analysis and recommendations for onshore wind power policies in China. Renewable & Sustainable Energy Reviews 82:156–67. doi:10.1016/j.rser.2017.06.114
   Google Scholar
• Li, L., A. McMurray, M. Sy, and J. Xue. 2018a. Corporate ownership, efficiency and performance under state capitalism: Evidence from China. Journal of Policy Modeling 40 (4):747–66. doi:10.1016/j.jpolmod.2018.03.002.
   Web of Science ®Google Scholar
• Li, L., X. Ren, Y. Yang, P. Zhang, and X. Chen. 2018b. Analysis and recommendations for onshore wind power policies in China. Renewable & Sustainable Energy Reviews 82:156–67. doi:10.1016/j.rser.2017.06.114.
   Web of Science ®Google Scholar
• Liao, Z. 2016. The evolution of wind energy policies in China (1995–2014): An analysis based on policy instruments. Renewable and Sustainable Energy Reviews 56:464–72. doi:10.1016/j.rser.2015.11.097.
   Web of Science ®Google Scholar
• Lin, B., and Y. Chen. 2019. Impacts of policies on innovation in wind power technologies in China. Applied Energy 247:682–91. doi:10.1016/j.apenergy.2019.04.044.
   Web of Science ®Google Scholar
• Luo, X. J., L. O. Oyedele, O. O. Akinade, and A. O. Ajayi. 2020. Two-stage capacity optimization approach of multi-energy system considering its optimal operation. Energy and AI 1:100005. doi:10.1016/j.egyai.2020.100005.
   Google Scholar
• Mattmann, M., I. Logar, and R. Brouwer. 2016. Wind power externalities: A meta-analysis. Ecological Economics 127 (127):23–36. doi:10.1016/j.ecolecon.2016.04.005.
   Google Scholar
• May, R. F., O. Reitan, K. M. Bevanger, S. H. Lorentsen, and T. Nygard. 2015. Mitigating wind-turbine induced avian mortality: Sensory, aerodynamic and cognitive constraints and options. Renewable & Sustainable Energy Reviews 42:170–81. doi:10.1016/j.rser.2014.10.002.
   Web of Science ®Google Scholar
• Niu, D., Z. Song, X. Xiao, and Y. Wang. 2018. Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method. Journal of Cleaner Production 170:193–204. doi:10.1016/j.jclepro.2017.09.113.
   Web of Science ®Google Scholar
• Onakpoya, I., J. W. Osullivan, M. Thompson, and C. Heneghan. 2015. The effect of wind turbine noise on sleep and quality of life: A systematic review and meta-analysis of observational studies. Environment International 82:1–9. doi:10.1016/j.envint.2015.04.014.
   PubMed Web of Science ®Google Scholar
• Papiez, M., S. Śmiech, and K. Frodyma. 2019. Factors affecting the efficiency of wind power in the European Union countries. Energy Policy 132:965–77. doi:10.1016/j.enpol.2019.06.036.
   Web of Science ®Google Scholar
• Sağlam, Ü. 2017a. The effect of electricity prices on the productive efficiency of 39 state’s wind power. Available at SSRN: https://ssrn.com/abstract=3006284
   Google Scholar
• Sağlam, Ü. 2017b. A two-stage data envelopment analysis model for efficiency assessments of 39 state’s wind power in the United States. Energy Conversion and Management 146 (146):52–67. doi:10.1016/j.enconman.2017.05.023.
   Google Scholar
• Sağlam, Ü. 2017c. Assessment of the productive efficiency of large wind farms in the United States: An application of two-stage data envelopment analysis. Energy Conversion and Management 153:188–214. doi:10.1016/j.enconman.2017.09.062.
   Web of Science ®Google Scholar
• Sağlam, Ü. 2018. A two-stage performance assessment of utility-scale wind farms in Texas using data envelopment analysis and Tobit models. Journal of Cleaner Production 201:580–98. doi:10.1016/j.jclepro.2018.08.034.
   Web of Science ®Google Scholar
• Sarica, K., and I. Or. 2007. Efficiency assessment of Turkish power plants using data envelopment analysis. Energy 32 (8):1484–99. doi:10.1016/j.energy.2006.10.016.
   Web of Science ®Google Scholar
• Song, M., S. Wang, and L. Cen. 2015. Comprehensive efficiency evaluation of coal enterprises from production and pollution treatment process. Journal of Cleaner Production 104:374–79. doi:10.1016/j.jclepro.2014.02.028.
   Web of Science ®Google Scholar
• Takayabu, H., S. Kagawa, H. Fujii, S. Managi, and S. Eguchi. 2019. Impacts of productive efficiency improvement in the global metal industry on CO2 emissions. Journal of Environmental Management 248:109261. doi:10.1016/j.jenvman.2019.109261.
   PubMed Web of Science ®Google Scholar
• Tarancón, M. Á., M. J. Gutiérrez-Pedrero, F. E. Callejas, and I. Martínez-Rodríguez. 2018. Verifying the relation between labor productivity and productive efficiency by means of the properties of the input-output matrices. The European Case. International Journal of Production Economics 195:54–65. doi:10.1016/j.ijpe.2017.10.004.
   Web of Science ®Google Scholar
• Tu, Q., R. Betz, J. Mo, and Y. Fan. 2019. The profitability of onshore wind and solar PV power projects in China - A comparative study. Energy Policy 132:404–17. doi:10.1016/j.enpol.2019.05.041.
   Web of Science ®Google Scholar
• Ullah, A., T. Silalertruksa, P. Pongpat, and S. H. Gheewala. 2019. Efficiency analysis of sugarcane production systems in Thailand using data envelopment analysis. Journal of Cleaner Production 238:117877. doi:10.1016/j.jclepro.2019.117877.
   Web of Science ®Google Scholar
• Wang, B., Z. Yang, J. Xuan, and K. Jiao. 2020. Crises and opportunities in terms of energy and AI technologies during the COVID-19 pandemic. Energy and AI 2 (6). doi:10.1148/ryai.2020190168.
   Google Scholar
• Wang, M., and C. Feng. 2020. Regional total-factor productivity and environmental governance efficiency of China’s industrial sectors: A two-stage network-based super DEA approach. Journal of Cleaner Production 273:123110. doi:10.1016/j.jclepro.2020.123110.
   Web of Science ®Google Scholar
• Wang, X., Z. Jiang, and Y. Zheng. 2020. Effect of innovation policy mix on innovation efficiency: Evidence from Chinese wind power industry chain. Science & Public Policy 47 (1):31–46.
   Web of Science ®Google Scholar
• Wang, Z., H. Qin, and J. I. Lewis. 2012. China’s wind power industry: Policy support, technological achievements, and emerging challenges. Energy Policy 51:80–88. doi:10.1016/j.enpol.2012.06.067.
   Web of Science ®Google Scholar
• Wu, P., Y. Wang, Y. H. Chiu, Y. Li, and T. Y. Lin. 2019. Production efficiency and geographical location of Chinese coal enterprises-undesirable EBM DEA. Resources Policy 64:101527. doi:10.1016/j.resourpol.2019.101527.
   Web of Science ®Google Scholar
• Wu, Y., Y. Hu, X. Xiao, and C. Mao. 2016. Efficiency assessment of wind farms in China using two-stage data envelopment analysis. Energy Conversion and Management 123:46–55. doi:10.1016/j.enconman.2016.06.014.
   Web of Science ®Google Scholar
• Xin-gang, Z., and W. Zhen. 2019. The technical efficiency of China’s wind power list enterprises: An estimation based on DEA method and micro-data. Renewable Energy 133:470–79. doi:10.1016/j.renene.2018.10.049.
   Web of Science ®Google Scholar
• Xiong, L., F. Wang, B. Cheng, and C. Yu. 2018. Identifying factors influencing the forestry production efficiency in Northwest China. Resources, Conservation and Recycling 130:12–19. doi:10.1016/j.resconrec.2017.11.009.
   Web of Science ®Google Scholar
• Zerrahn, A. 2017. Wind Power and Externalities. Ecological Economics 141: 245–60.
   Web of Science ®Google Scholar
• Zhang, F., T. Tang, J. Su, and K. Huang. 2020. Inter-sector network and clean energy innovation: Evidence from the wind power sector. Journal of Cleaner Production 263:121287. doi:10.1016/j.jclepro.2020.121287.
   Web of Science ®Google Scholar
• Zhang, R., G. Q. Shen, M. Ni, and J. K. Wong. 2019. An overview on the status quo of onshore and offshore wind power development and wind power enterprise localization in China. International Journal of Green Energy 16 (15):1646–64. doi:10.1080/15435075.2019.1681429.
   Web of Science ®Google Scholar
• Zhao, X., and Wei, Z. 2019. The technical efficiency of China’s wind power list enterprises: An estimation based on DEA method and micro-data. Renewable Energy 133:470–79. doi:10.1016/j.renene.2018.10.049
   Google Scholar
• Zhao, Y., K. K. Tang, and L. Wang. 2013. Do renewable electricity policies promote renewable electricity generation? Evidence from panel data. Energy Policy 62:887–97. doi:10.1016/j.enpol.2013.07.072.
   Web of Science ®Google Scholar