Recently, the research results of Professor Li Guo's team of the School of Management and Economics, Beijing Institute of Technology “Does CSR Reduce Idiosyncratic Risk?Roles of Operational Efficiency and AI Innovation” is officially published in Production and Operations Management, an international top journal of management science.The work was conducted by Professor Lee Guo and his PhD student Li Na with Professor Suresh P. Sethi, University of Texas, Dallas, USA.
With the rapid development of artificial intelligence, social ethics anomie problems such as personal privacy leakage and big data killing have become increasingly prominent, and China's corporate social responsibility management is facing new challenges.In order to clarify the corporate social responsibility, Idiosyncratic risk interaction mechanism and artificial intelligence mechanism, and provide decision advice and management support for Chinese enterprises to more effectively deal with business ethics problems , Beijing Institute of technology professor, doctoral students, collected 1614 Chinese listed companies’ data and carry out relevant empirical research.This study is the first to incorporate AI innovation into the consideration of social responsibility management, and it is the first to identify the U-type relationship between corporate social responsibility performance and corporate Idiosyncratic risk in the Chinese situation.At present, our country is in a new journey of modern socialist modernization, the research results provide scientific decision-making advice and solid management support for our government and enterprise development of artificial intelligence, strengthen the key digital technology innovation application, promote green development, further implement the innovation, coordination, green, open, sharing new development concept, to achieve higher quality, more efficient, more fair, more sustainable, more safe development.
Details of the paper:
Guo Li, Na Li, Suresh P. Sethi. Does CSR reduce idiosyncratic risk? Roles of operational efficiency and AI innovation. Production and Operations Management, 2021, 30(7), 2027–2045.
https://doi.org/10.1111/poms.13483
Homepage:https://sme.bit.edu.cn/gbszdw/gbjxzy/gbsglkxywlx/3ee06feed3464635ad6e5d20752be232.htm
Original link:https://onlinelibrary.wiley.com/doi/10.1111/poms.13483
