Has The Application of Artificial Intelligence Expanded the Internal Income Gap Within Enterprises?
DOI:
https://doi.org/10.54097/k6r7zm43Keywords:
Artificial Intelligence; Income Gap; Listed Companies; Chinese Economy.Abstract
This study explores the impact of artificial intelligence (AI) technology application on the internal wage gap within enterprises and the moderating role of employee scale. Using panel data from Chinese A-share listed companies from 2011 to 2022 and an AI application level index constructed through text mining methods, this paper analyzes through a fixed effects model and finds that the application of AI technology significantly increases the wage gap between management and ordinary employees, especially in non-state-owned enterprises, non-manufacturing, and high-tech industries. However, the effect of this wage gap increase is relatively weaker in large enterprises, indicating that company size can mitigate the impact of AI technology to a certain extent. This finding contributes to a deeper understanding of how technological progress shapes the internal wage structure of enterprises and is significant for enterprises and governments to formulate fair wage policies, providing new strategies to promote internal wage equality within enterprises.
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References
Almada-Lobo F. The industry 4.0 revolution and the future of Manufacturing Execution Systems (MES). Journal of innovation management, 2015, 3(4): 16-21.
Lăzăroiu G, Bogdan M, Geamănu M, et al. Artificial intelligence algorithms and cloud computing technologies in blockchain-based fintech management. Oeconomia Copernicana, 2023, 14(3): 707-730.
Cao X, Xu L, Duan Q. EM Algorithm-Based Enterprise Digital Transformation: Green Innovation Efficiency of Enterprise Investment. Mathematical Problems in Engineering, 2022, 2022.
Zhen Y, Jin C. Innovation and Governance of Corporate Social Responsibility in the Digital and Intelligent Era. Journal of Shanghai University of Finance and Economics, 2020, 22(06): 33-51.
Bahoo S, Cucculelli M, Qamar D. Artificial intelligence and corporate innovation: A review and research agenda. Technological Forecasting and Social Change, 2023, 188: 122264.
Harayama Y, Milano M, Baldwin R, et al. Artificial Intelligence and the Future of Work. Reflections on Artificial Intelligence for Humanity, 2021: 53-67.
Fossen F M, Sorgner A. New digital technologies and heterogeneous employment and wage dynamics in the United States: Evidence from individual-level data. 2019.
Siddharthan N S. Paradigm Changes in Technology and Employment. Accelerators of India's Growth—Industry, Trade and Employment: Festschrift in Honor of Bishwanath Goldar, 2020: 3-12.
Mahesh K M, Aithal P S, Sharma K R S. Impact of Aatmanirbharta (Self-reliance) Agriculture and Sustainable Farming for the 21st Century to Achieve Sustainable Growth. International Journal of Applied Engineering and Management Letters (IJAEML), 2023, 7(2): 175-190.
Ales L, Kurnaz M, Sleet C. Technical change, wage inequality, and taxes. American Economic Review, 2015, 105(10): 3061-3101.
Frey C B, Osborne M A. The future of employment: How susceptible are jobs to computerisation? Technological forecasting and social change, 2017, 114: 254-280.
Felten E W, Raj M, Seamans R. The occupational impact of artificial intelligence: Labor, skills, and polarization. NYU Stern School of Business, 2019.
Georgieff A, Hyee R. Artificial intelligence and employment: New cross-country evidence. 2021.
Wu Fei, Hu Huizhi, Lin Huiyan, et al. Enterprise Digital Transformation and Capital Market Performance: Empirical Evidence from Stock Liquidity. Management World, 2021, 37(07): 130-144+10.
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