IDEAS home Printed from https://ideas.repec.org/r/eee/jrpoli/v81y2023ics0301420723000326.html
   My bibliography  Save this item

Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Tao Chen & Shuwen Pi & Qing Sophie Wang, 2025. "Artificial Intelligence and Corporate Investment Efficiency: Evidence from Chinese Listed Companies," Working Papers in Economics 25/05, University of Canterbury, Department of Economics and Finance.
  2. Chen Xu & Yu He, 2025. "The Impact of ESG Performance on Green Technology Innovation: A Moderating Effect Based on Digital Transformation," Sustainability, MDPI, vol. 17(7), pages 1-22, April.
  3. Lin, Weiwen & Qin, Shan & Zhou, Xinzhu & Guan, Xin & Zeng, Yanzhao & Wang, Zeyu & Shen, Yaohan, 2024. "Three-dimensional quantitative mineral prediction from convolutional neural network model in developing intelligent cleaning technology," Resources Policy, Elsevier, vol. 88(C).
  4. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
  5. Hanyu Zhang & Kaiyue Zhang & Taihua Yan & Xiaonan Cao, 2025. "The impact of digital infrastructure on regional green innovation efficiency through industrial agglomeration and diversification," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-15, December.
  6. Li, Chengming & Wang, Yilin & Zhou, Zhihan & Wang, Zeyu & Mardani, Abbas, 2023. "Digital finance and enterprise financing constraints: Structural characteristics and mechanism identification," Journal of Business Research, Elsevier, vol. 165(C).
  7. Gao, Yajuan & Zhang, Congqing & Wang, Yilin & Wang, Shuaihao & Zou, Yunjin & Gao, Junhong & Wang, Zeyu, 2023. "Fiscal decentralization and rural resource utilization efficiency: Evidence from quasi-natural experiment in China," Resources Policy, Elsevier, vol. 87(PB).
  8. Dongwei Li & Jing Xiao & Fangfang Yang, 2024. "Artificial Intelligence and Enterprise Green Innovation: Intrinsic Mechanisms and Heterogeneous Effects," Sustainability, MDPI, vol. 16(21), pages 1-18, October.
  9. Zhong, Qian & Zhang, Qun & Yang, Jingjing, 2025. "Can artificial intelligence empower energy enterprises to cope with climate policy uncertainty?," Energy Economics, Elsevier, vol. 141(C).
  10. Zhao, Xiongfei & Li, Shuangjie, 2025. "Artificial intelligence and public environmental concern: Impacts on green innovation transformation in energy-intensive enterprises," Energy Policy, Elsevier, vol. 198(C).
  11. Jiang, Zhengyu & Zhang, Xinyi & Zhao, Yingzhi & Li, Chengming & Wang, Zeyu, 2023. "The impact of urban digital transformation on resource sustainability: Evidence from a quasi-natural experiment in China," Resources Policy, Elsevier, vol. 85(PA).
  12. Xinyue Yu & Libo Fan & Yang Yu, 2025. "Artificial Intelligence and Corporate ESG Performance: A Mechanism Analysis Based on Corporate Efficiency and External Environment," Sustainability, MDPI, vol. 17(9), pages 1-22, April.
  13. Wu, Yifan & Yuan, Yiming & Song, Xueyin, 2025. "The impact of AI adoption on R&D productivity: Evidence from Chinese pharmaceutical manufacturing industry," Journal of Asian Economics, Elsevier, vol. 97(C).
  14. Shuhui Yu & Xin Guan & Junfan Zhu & Zeyu Wang & Youting Jian & Weijia Wang & Ya Yang, 2023. "Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China," Sustainability, MDPI, vol. 15(11), pages 1-14, June.
  15. Liu, Yeshen & Wang, Beibei & Song, Zhe, 2025. "Promoting or inhibiting: The impact of artificial intelligence application on corporate environmental performance," International Review of Financial Analysis, Elsevier, vol. 97(C).
  16. Cui, Lijuan & Xu, Yekun, 2025. "Technological change and entrepreneurial activities: Evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 72(C), pages 330-346.
  17. Ruiyu Hu & Zemenghong Bao & Zhisen Lin & Kun Lv, 2024. "The Innovative Construction of Provinces, Regional Artificial Intelligence Development, and the Resilience of Regional Innovation Ecosystems: Quasi-Natural Experiments Based on Spatial Difference-in-D," Sustainability, MDPI, vol. 16(18), pages 1-37, September.
  18. Dai, Yuhui & Hu, Shaobo & Zhai, Zhenkai, 2024. "Policy role, information disclosure, and enterprise innovation," Finance Research Letters, Elsevier, vol. 63(C).
  19. Wenjie Li & Guanyu Guo & Huangying Gu & Shuhao Lai & Yuanjie Duan & Chengming Li, 2024. "Digital Economy as a Buffer: Alleviating the Adverse Effects of Land Resource Mismatch on Food Security," Land, MDPI, vol. 13(11), pages 1-21, October.
  20. Yin, Lei & Du, Shanxing & Chen, Ge, 2024. "The influence of the bank–firm relationship on enterprises’ technological innovation efficiency: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1583-1600.
  21. Wang, Zongrun & Cao, Xuxin & Ren, Xiaohang & Taghizadeh-Hesary, Farhad, 2024. "Can digital transformation affect coal utilization efficiency in China? Evidence from spatial econometric analyses," Resources Policy, Elsevier, vol. 91(C).
  22. Zhai, Minhan & Wu, Wenqing & Tsai, Sang-Bing, 2025. "The effects of Artificial intelligence orientation on inefficient investment: Firm-level evidence from China's energy enterprises," Energy Economics, Elsevier, vol. 141(C).
  23. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
  24. Zhang, Jingshen & Zhou, Xinzhu & Bai, Rong & Dong, Haoyang & Tang, Tingting & Wang, Zeyu & Yang, Ya & Huang, Feng, 2024. "Impact of environmental supervision reform on green innovation in mineral enterprises," Resources Policy, Elsevier, vol. 88(C).
  25. Li, Cong & Zhang, Yue & Liu, Xihua & Sun, Jiawen, 2025. "Does artificial intelligence promote green technology innovation in the energy industry?," Energy Economics, Elsevier, vol. 144(C).
  26. Gao, Shiya & Guan, Xin & Tang, Run & Zhu, Junfan & Wang, Zeyu & Xu, Wei, 2023. "Resource curse, economic efficiency and green recovery based on three-subject framework," Resources Policy, Elsevier, vol. 85(PB).
  27. Jin, Ting & Liang, Feiyan & Dong, Xiaoqi & Cao, Xiaojuan, 2023. "Research on land resource management integrated with support vector machine —Based on the perspective of green innovation," Resources Policy, Elsevier, vol. 86(PB).
  28. Sun, Jingjing & Zhai, Chenchen & Dong, Xiaoqi & Li, Chengming & Wang, Zeyu & Li, Dandan & Sun, Yongping, 2023. "How does digital infrastructure break the resource curse of cities? Evidence from a quasi-natural experiment in China," Resources Policy, Elsevier, vol. 86(PA).
  29. Zhao, Congyu & Dong, Kangyin & Wang, Kun & Nepal, Rabindra, 2024. "How does artificial intelligence promote renewable energy development? The role of climate finance," Energy Economics, Elsevier, vol. 133(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.