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CEO Gender and Firm’s Adoption of Artificial Intelligence Technology
- 1 Basis International School Park Lane Harbor, 516000, Huizhou, China
- 2 University of Nottingham Ningbo China, 315199, Ningbo, China
- 3 Jincheng No.1 Secondary School International Program,610041, Chengdu, China
* Author to whom correspondence should be addressed.
Abstract
In this rapidly evolving era, AI is an emerging industry with a significant presence in various industries. Factors affecting the extent to which AI is used in companies have been explored by many researchers, but the factor of CEO gender is rarely mentioned. To test the effect of CEO gender on the degree of corporate use of AI, this paper analyzes the text of corporate annual reports to measure the degree of each company's use of AI by counting the number of times the term AI appears in each annual report. The CEO gender information is manually collected to construct an indicator of the degree of corporate adoption of AI. In this paper, a theoretical hypothesis of the relationship between CEO gender and the degree of corporate use of AI based on the different attitudes of males and females towards ethical behavior and risk will be provided. Then, accorded with the panel data about companies from Chinese a-share non-financial, which was listed from 2000 - 2021, a two-way fixed-effects regression model is used to analyze the effect of CEO gender on the degree of firms' use of AI technology. The study results show that AI usage is higher in male than female CEOs. Based on the above findings, this paper not only reveals the influence of CEO gender on the extent of firms' AI use but also deepens the understanding of the differences in gender characteristics between males and females.
Keywords
Artificial Intelligence, Chief Executive Officer (CEO), Gender
[1]. Barton, D. (n.d.). Artificial Intelligence: Implications for china - mckinsey & company. ARTIFICIAL INTELLIGENCE: IMPLICATIONS FOR CHINA. https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/China/Artificial%20intelligence%20Implications%20for%20China/MGI-Artificial-intelligence-implications-for-China.pdf
[2]. Na, K., & Hong, J. (2017). CEO gender and earnings management. Journal of Applied Business Research (JABR), 33(2), 297-308.
[3]. Faccio, M., Marchica, M., & Mura, R. (2016). CEO gender, corporate risk-taking, and the efficiency of capital allocation. Journal of Corporate Finance, 39, 193–209.https://doi.org/10.1016/j.jcorpfin.2016.02.008
[4]. Expósito, A., Sanchis-Llopis, A., & Sanchis-Llopis, J. A. (2021). CEO gender and SMEs innovativeness: evidence for Spanish businesses. International Entrepreneurship and Management Journal, 1-38.
[5]. Yong Suk Lee a, a, b, c, d, AbstractThis paper examines how high-tech venture performance varies with AI-adoption intensity. We find that firm revenue increases only after sufficient investment in AI, Alekseeva, L., Arora, A., Augereau, A., Bresnahan, T., Eckhardt, J. T., Greenwood, J., Jovanovic, B., Lee, Y., Acemoglu, D., Aghion, P., Agrawal, A., Aral, S., Atkeson, A., … Felten, E. W. (2022, July 4). When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy. Technovation. https://www.sciencedirect.com/science/article/abs/pii/S0166497222001377
[6]. Khan, W. A., & Vieito, J. P. (2013). CEO gender and firm performance. Journal of Economics and Business, 67, 55-66.
[7]. Marianne, B. (2011). New perspectives on gender. In Handbook of labor economics (Vol. 4, pp. 1543-1590). Elsevier.
[8]. Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic literature, 47(2), 448-474.
[9]. Akerlof, G. A., & Kranton, R. E. (2000). Economics and identity. The quarterly journal of economics, 115(3), 715-753.
[10]. Altonji, J. G., & Blank, R. M. (1999). Race and gender in the labor market. Handbook of labor economics, 3, 3143-3259.
[11]. Booth, A., & Nolen, P. (2012). Choosing to compete: How different are girls and boys?. Journal of Economic Behavior & Organization, 81(2), 542-555.
[12]. Guiso, L., & Paiella, M. (2008). Risk aversion, wealth, and background risk. Journal of the European Economic association, 6(6), 1109-1150.
[13]. Hudgens, G. A., & Fatkin, L. T. (1985). Sex differences in risk taking: Repeated sessions on a computer-simulated task. The Journal of Psychology, 119(3), 197-206.
[14]. Bruce, A. C., & Johnson, J. E. (1994). Male and female betting behaviour: New perspectives. Journal of Gambling studies, 10(2), 183-198.
[15]. Johnson, J. E., & Powell, P. L. (1994). Decision making, risk and gender: Are managers different?. British journal of management, 5(2), 123-138.
[16]. Sunden, A. E., & Surette, B. J. (1998). Gender differences in the allocation of assets in retirement savings plans. The American Economic Review, 88(2), 207-211.
[17]. Bernasek, A., & Shwiff, S. (2001). Gender, risk, and retirement. Journal of economic issues, 35(2), 345-356.
[18]. Lundeberg, M. A., Fox, P. W., & Punćcohaŕ, J. (1994). Highly confident but wrong: Gender differences and similarities in confidence judgments. Journal of educational psychology, 86(1), 114.
[19]. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The quarterly journal of economics, 116(1), 261-292.
[20]. Huang, J., & Kisgen, D. J. (2013). Gender and corporate finance: Are male executives overconfident relative to female executives?. Journal of financial Economics, 108(3), 822-839.
[21]. Phelps, S., & Mason, M. (1991). When women lose their jobs. Personnel Journal.
[22]. Goldin, C. (1990). Understanding the gender gap: An economic history of American women (No. gold90-1). National Bureau of Economic Research.
[23]. Bertrand, M., Goldin, C., & Katz, L. F. (2010). Dynamics of the gender gap for young professionals in the financial and corporate sectors. American economic journal: applied economics, 2(3), 228-255
[24]. Sun, F., Dutta, S., Zhu, P., & Ren, W. (2021). Female insiders' ethics and trading profitability. International Review of Financial Analysis, 74, 101710.
[25]. Doan, T., & Iskandar-Datta, M. (2020). Are female top executives more risk-averse or more ethical? Evidence from corporate cash holdings policy. Journal of Empirical Finance, 55, 161-176.
[26]. Mishra, S., Ewing, M. T., & Cooper, H. B. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 50(6), 1176-1197.
[27]. Li, J., Ma, S., Qu, Y., & Wang, J. (2023). The impact of artificial intelligence on firms’ energy and resource efficiency: Empirical evidence from China. Resources Policy, 82, 103507.
[28]. Guermazi, A., Tannoury, C., Kompel, A. J., Murakami, A. M., Ducarouge, A., Gillibert, A., ... & Hayashi, D. (2022). Improving radiographic fracture recognition performance and efficiency using artificial intelligence. Radiology, 302(3), 627-636.
[29]. Mak, K. K., & Pichika, M. R. (2019). Artificial intelligence in drug development: present status and future prospects. Drug discovery today, 24(3), 773-780.
[30]. Baghbani, A., Choudhury, T., Costa, S., & Reiner, J. (2022). Application of artificial intelligence in geotechnical engineering: A state-of-the-art review. Earth-Science Reviews, 228, 103991.
[31]. Chadaga, K., Prabhu, S., Sampathila, N., Nireshwalya, S., Katta, S. S., Tan, R. S., & Acharya, U. R. (2023). Application of artificial intelligence techniques for monkeypox: a systematic review. Diagnostics, 13(5), 824.
[32]. Ore, O., & Sposato, M. (2022). Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organizational Analysis, 30(6), 1771-1782.
[33]. Timmermans, J., Stahl, B. C., Ikonen, V., & Bozdag, E. (2010, November). The ethics of cloud computing: A conceptual review. In 2010 IEEE second international conference on cloud computing technology and science (pp. 614-620). IEEE.
[34]. Wang, W., & Siau, K. (2018). Ethical and moral issues with AI. https://doi.org/10.1080/16081625.2014.1003568
[35]. Larson, B. N. (2017). Gender as a variable in natural-language processing: Ethical considerations. Association for Computational Linguistics.
[36]. Koolen, C., & van Cranenburgh, A. (2017). These are not the stereotypes you are looking for: Bias and fairness in authorial gender attribution. In Proceedings of the First Ethics in NLP workshop (pp. 12-22). Association for Computational Linguistics (ACL).
[37]. Bossmann, J. (2016, October). Top 9 ethical issues in artificial intelligence. In World Economic Forum (Vol. 21).
Cite this article
Yi,J.;Wang,Y.;Liu,Y. (2024). CEO Gender and Firm’s Adoption of Artificial Intelligence Technology. Advances in Economics, Management and Political Sciences,82,305-314.
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