EFFECT OF ARTIFICIAL INTELLIGENCE ON GREEN HUMAN RESOURCE MANAGEMENT OF PHARMACEUTICAL FIRMS IN ENUGU STATE
Abstract
This study evaluated the Effect of artificial intelligence on green human resource management of pharmaceutical firms in Enugu state. The broad objective of this study is to determine the effect of artificial intelligence on green human resource management of pharmaceutical firms in Enugu state, specifically, the study sort to determine the effect of machine learning on green talent management of pharmaceutical firms and ascertain the effect of expert systems on green workplace safety of pharmaceutical firms. A total population of one thousand five hundred and forty-two (1542), staff was used. The sample size of 308, using Freund and William's statistic formula at 5 percent margin of error. Regression statistical tools was used to test the hypotheses with the aid of SPSS Version 26. The results of the study revealed that Machine learning has significant positive effect on green talent management of pharmaceutical firms in Enugu state and that Expert systems have significant positive effect on green workplace safety of pharmaceutical firms in Enugu state. The study concluded that the integration of machine learning into green talent management has emerged as a pivotal factor in shaping the industry's approach to nurturing environmentally conscious talent, application of expert systems in this context has evidently contributed to the establishment of robust safety protocols and risk management procedures that align with environmentally sustainable principles. The study among other things recommended that pharmaceutical firms should implement expert systems that can assess workplace safety risks in real-time based on a combination of environmental factors, equipment usage, and employee behavior.
Keywords:
Artificial intelligence, Green, Human resource, ManagementDownloads
Published
DOI:
https://doi.org/10.5281/zenodo.14186512Issue
Section
How to Cite
License
Copyright (c) 2024 Ekpo Okpa Iyamba, Okechukwu Elizabeth Uzoamaka , Okwor, Onyeka Martins

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.
Chen, Y., Patel, M. N., and Walker, E. R., (2020). AI-Personality Assessment and Employee Performance Prediction. Personnel Psychology, (06)4
Ehnert, I., Harry, W., & Zink, K. J. (2016). Sustainability and HRM. In The Routledge Companion to Ethics, Politics and Organizations (pp. 407-424). Routledge.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Gülen, K., (2023). The building blocks of AI. Artificial Intelligence, Data Science, Available at: https://dataconomy.com/2023/04/03/basic-components-of-artificial-intelligence/#:~:text=The%20components%20of%20AI%20include,ways%20that%20were%20previously%20impossible.
Gupta, A., Brown, E. K., and Turner, R. M., (2021). Enhancing Employee Engagement through AI-Enabled Feedback Systems. Human Resource Management Review (07)2
Kamilaris, A., Prenafeta-Boldú, F. X., & Zorpas, A. A. (2018). Medical Waste Management Information Systems: A Case Study. Waste Management, 75, 53-63.
Kim, S., Johnson, H. D., and Martinez, G., (2019). Transformation of Learning and Development: AI-Powered Training Recommendations. Training and Development Journal, (09)6
Lopez, M. A., & Arvey, R. D. (2020). Artificial intelligence in human resources management: Challenges and a path forward. Human Resource Management Review, 30(1), 100725.
Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.
Mithas, S., Tafti, A., Bardhan, I., & Goh, J. (2021). Artificial Intelligence in the Age of Automation: Will Robots Replace Humans in the Firm?. MIS Quarterly, 45(1), 1-21.
Opatha, H. H. D. N. P. & Arulrajah, A. A. (2014). Green Human Resource Management: Simplified General Reflections. International Business Research; Vol. 7, No. 8; Published by Canadian Center of Science and Education
Parker, R., Steinemann, A., Cordell, D., & Adams, R. (2019). The environmental sustainability of pharmaceuticals: A call for research and action. Journal of Cleaner Production, 235, 1198-1208.
Renwick, D. W., Redman, T., & Maguire, S. (2013). Green human resource management: A review and research agenda. International Journal of Management Reviews, 15(1), 1-14.
Renwick, D. W., Redman, T., & Maguire, S. (2016). Green human resource management: A review and research agenda. International Journal of Management Reviews, 18(1), 1-16.
Russell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
Sharma, B., & Bhatnagar, J. (2020). Green talent management and employee green behavior: The mediating role of green human resource management practices. Business Strategy and the Environment, 29(4), 1753-1769.
Shen, W., Wang, C., Hu, Y., & Liao, Y. (2020). A conceptual framework for green safety management. Safety Science, 128, 104764.
Shi, Y., Wang, R., Shao, X., & Wen, Y. (2020). Environmental management practices in the pharmaceutical industry: A systematic review. Journal of Cleaner Production, 275, 122882.
Smith, J. A., Anderson, R. M., Williams, L. P., (2022). Impact of AI-Driven Recruitment on Candidate Selection Efficiency and Quality. Journal of Applied Psychology 07(3).
Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction. MIT Press.