Robot adoption and energy performance: Evidence from Chinese industrial firms

Citations

Cited by:

1. Xi Lin & Ling‐Yun He, 2023. "‘Going global’ and pollution in home country: Evidence from Chinese industrial firms," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(4), pages 1135-1174, October.
2. Wang, Hua & Liao, Lingtao & Wu, Ji (George), 2023. "Robot adoption and firm's capacity utilization: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
3. Xi Lin & Ling-Yun He, 2023. "The More the Merrier? Evidence from Firm-Level Exports and Environmental Performance in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 125-172, January.
4. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
5. Xiaoyi Li & Qibo Tian, 2023. "How Does Usage of Robot Affect Corporate Carbon Emissions?—Evidence from China’s Manufacturing Sector," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
6. Huang, Keqi & Liu, Qiren & Tang, Chengjian, 2023. "Which firms benefit from robot adoption? Evidence from China," Journal of Asian Economics, Elsevier, vol. 86(C).
7. Huang, Keqi & Liu, Qiren, 2024. "Artificial intelligence and outward foreign direct investment: Evidence from China," Journal of Asian Economics, Elsevier, vol. 92(C).
8. He, Ling-Yun & Huang, Geng, 2023. "Can importing improve the energy efficiency? Theory and evidence from Chinese industrial firms," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 451-469.
9. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
10. Da Gao & Chang Liu & Xinyan Wei & Yang Liu, 2023. "Can River Chief System Policy Improve Enterprises’ Energy Efficiency? Evidence from China," IJERPH, MDPI, vol. 20(4), pages 1-17, February.
11. Zhang, Dongyang, 2024. "The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence," Energy Economics, Elsevier, vol. 133(C).
12. Ke-Liang Wang & Ting-Ting Sun & Ru-Yu Xu, 2023. "The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises," Economic Change and Restructuring, Springer, vol. 56(2), pages 1113-1146, April.
13. Huang, Geng & He, Ling-Yun & Lin, Xi, 2023. "Deterioration or improvement? Intermediate product import and enterprises' environmental performance," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 139-150.
14. Huang, Geng & Lin, Xi & He, Ling-Yun, 2023. "Good for the environment? Foreign investment opening in service sector and firm's energy efficiency," Energy Economics, Elsevier, vol. 127(PA).
15. Gan, Jiawu & Liu, Lihua & Qiao, Gang & Zhang, Qin, 2023. "The role of robot adoption in green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
16. Zhang, Yi & Wang, Ting & Liu, Chun, 2024. "Beyond the modern productivity paradox: The effect of robotics technology on firm-level total factor productivity in China," Journal of Asian Economics, Elsevier, vol. 90(C).
17. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
18. Zhang, Xiaojing & Khan, Khalid & Shao, Xuefeng & Oprean-Stan, Camelia & Zhang, Qian, 2024. "The rising role of artificial intelligence in renewable energy development in China," Energy Economics, Elsevier, vol. 132(C).
19. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
20. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
21. Cui, Huijie & Liang, Shangkun & Xu, Canyu & Junli, Yu, 2024. "Robots and analyst forecast precision: Evidence from Chinese manufacturing," International Review of Financial Analysis, Elsevier, vol. 94(C).
22. Tang, Yuwei & He, Zhenyu, 2024. "Extreme heat and firms' robot adoption: Evidence from China," China Economic Review, Elsevier, vol. 85(C).
23. Huzhou Zhu & Bin Sang & Chunyuan Zhang & Lin Guo, 2023. "Have Industrial Robots Improved Pollution Reduction? A Theoretical Approach and Empirical Analysis," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(4), pages 153-172, July.
24. Li, Jianjun & Wu, Zhouyi & Yu, Kaijia & Zhao, Wei, 2024. "The effect of industrial robot adoption on firm value: Evidence from China," Finance Research Letters, Elsevier, vol. 60(C).
25. Yin, Zi Hui & Zeng, Wei Ping, 2023. "The effects of industrial intelligence on China's energy intensity: The role of technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
26. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
27. Shen, Qiong & Pan, Yuxi & Meng, Xiangxu & Ling, Xiao & Hu, Shilei & Feng, Yanchao, 2023. "How does the transition policy of mineral resource-exhausted cities affect the process of industrial upgrading? New empirical evidence from China," Resources Policy, Elsevier, vol. 86(PB).
28. Shizhong Peng & Haoran Peng & Shirong Pan & Jun Wu, 2023. "Digital Transformation, Green Innovation, and Pollution Abatement: Evidence from China," Sustainability, MDPI, vol. 15(8), pages 1-18, April.