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The Role of Artificial Intelligence in Promoting Employee Workplace Green Behaviors: A Systematic Analysis

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  • Danzen OlazoORCID iD verified by the author (show author details)

    Danzen Olazo

    Department of Management, School of Business and Accountancy, Holy Angel University, Angeles City, Philippines, Philippines

    0000-0002-1213-3631

    Corresponding author

  • Joy Anne EvaristoORCID iD verified by the author (show author details)

    Joy Anne Evaristo

    Department of Management, School of Business and Accountancy, Holy Angel University, Angeles City, Philippines, Philippines

    0009-0005-3801-4146

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Olazo, D., & Evaristo, J. A. (2025). The Role of Artificial Intelligence in Promoting Employee Workplace Green Behaviors: A Systematic Analysis. SEISENSE Business Review, 5(1), 15-28. https://doi.org/10.33215/2hddey70

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Abstract

This systematic literature review explores the intersection of artificial intelligence (AI) and employee workplace green behaviors, examining how AI interventions can enhance sustainable practices in organizations. The paper addresses three primary research questions: (1) What role does AI play in promoting employee workplace green behaviors? (2) How is AI currently applied to enhance green behaviors within organizational settings? and (3) What are the barriers or enablers for AI-driven interventions in fostering green behaviors? A comprehensive search strategy was employed, identifying key studies on AI applications in sustainability and employee behaviors. The findings suggest that AI can drive green behaviors through smart resource management, behavior tracking, and decision-making support, while highlighting barriers such as technological limitations and organizational resistance. The paper concludes with recommendations for organizations seeking to leverage AI for sustainability and discusses the theoretical and practical implications of AI in fostering environmentally responsible workplace practices.

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Copyright (c) 2025 Danzen Olazo, Joy Anne Evaristo

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Vol. 5 No. 1 (2025): SEISENSE Business Review View Issue

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2025-122026-11

Article history

  1. ReceivedJanuary 4, 2025
  2. Published March 18, 2025

Author Biographies

Danzen Olazo

Department of Management, School of Business and Accountancy, Holy Angel University, Angeles City, Philippines Philippines ORCID

Dr. Danzen B. Olazo is a Certified Marketing Management Specialist, Licensed Professional Teacher, Statistician, and Researcher. He serves as an Associate Professor in the Department of Management at Holy Angel University, Pampanga, teaching both undergraduate and graduate students. His expertise includes statistics, research methods, business analytics, marketing research.  He earned his Ph.D. in Business from De La Salle University and holds both a master’s and bachelor’s degree in business management from Holy Angel University. He has also completed short courses at the Asian Institute of Management (AIM), Makati City, and received training from the British Columbia Institute of Technology (BCIT), Vancouver, Canada. Danzen has been invited to various schools and universities to discuss quantitative research, particularly in utilizing open-source software for data analysis. He is also a mentor for the Kapatad Me Programunder the Local Government Unit of Pampanga, guiding MSMEs in business development. He was a nominee for the 43rd Agora Awards as Most Outstanding Marketing Educator at the Collegiate Level and has received numerous prestigious accolades, including Most Exemplary Transformation Educator and Researcher by the International Organization for Educators and Researchers Inc. at Grand Hyatt Taipei, Taiwan, 6th place in AD Indexing Citation in the World Scientist Ranking (2024) under Holy Angel University, and Gawad Saliksik 2024 Recognition from De La Salle University, Manila. Danzen has presented and published numerous research papers in local and international conferences, with his works accessible on Google Scholar, ResearchGate, and Scopus-indexed journals. He also serves as a reviewer for various academic publications. 

Joy Anne Evaristo

Department of Management, School of Business and Accountancy, Holy Angel University, Angeles City, Philippines Philippines ORCID

Professor Joy Anne Evaristo is a Doctor of Business Administration candidate at De La Salle University, currently preparing for her final dissertation defense. She serves as an Assistant Professor at the Department of Management, Holy Angel University, where she teaches International Trade, Marketing, Research, Sustainability, and Retail Management. With a passion for green behavior and sustainability, she actively participates in local and international conferences, sharing her expertise and research insights. Professor Evaristo is also an Institute Review Board (IRB) scientist reviewer for various research studies, ensuring ethical and scientific rigor. Beyond academia, she mentors micro, small, and medium enterprises (MSMEs) in Pampanga as a lecturer in the Kapatid Mentor ME program, empowering entrepreneurs to succeed through sustainable practices and innovative strategies.

References

Adel, A. Y., & Alzyoud, Y. (2022). Artificial intelligence for sustaining green human resource management: A literature review. IEEE Xplore. https://doi.org/10.1109/ICETSIS55481.2022.9888840 DOI: https://doi.org/10.1109/ICETSIS55481.2022.9888840

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T DOI: https://doi.org/10.1016/0749-5978(91)90020-T

Akter, M. S. (2024). AI for sustainability: Leveraging technology to address global environmental issues. Journal of Artificial Intelligence General Science (JAIGS), 3(1), 40–48. https://doi.org/10.60087/jaigs.v3i1.64 DOI: https://doi.org/10.60087/jaigs.v3i1.64

Andeobu, L., Wibowo, S., & Grandhi, S. (2022). Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review. Science of The Total Environment, 834, 155389. https://doi.org/10.1016/j.scitotenv.2022.155389 DOI: https://doi.org/10.1016/j.scitotenv.2022.155389

Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees' perceptions of our future workplace. Journal of Management & Organization, 24(2), 239–257. https://doi.org/10.1017/jmo.2016.55 DOI: https://doi.org/10.1017/jmo.2016.55

Chang, Y.-L., & Ke, J. (2024). Socially responsible artificial intelligence empowered people analytics: A novel framework towards sustainability. Human Resource Development Review, 23(1), 88-120. https://doi.org/10.1177/15344843231200930 DOI: https://doi.org/10.1177/15344843231200930

Chen, J., Viardot, E., & Brem, A. (2019). Innovation and innovation management. Journal of Innovation Management, 7(4), 10-17.

Damioli, G., Van Roy, V., & Vertesy, D. (2021). The impact of artificial intelligence on labor productivity. Eurasian Business Review, 11(1), 1–25. https://doi.org/10.1007/s40821-020-00172-8 DOI: https://doi.org/10.1007/s40821-020-00172-8

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008 DOI: https://doi.org/10.2307/249008

Fang, B., Yu, J., Chen, Z., Osman, A., Farghali, M., Ihara, I., Hamza, E., Rooney, D., & Yap, P. S. (2023). Artificial intelligence for waste management in smart cities: A review. Environmental Chemistry Letters, 21, 1-18. https://doi.org/10.1007/s10311-023-01604-3 DOI: https://doi.org/10.1007/s10311-023-01604-3

Fapohunda, T., Genty, K., & Olanipekun, L. (2021). Green training and development practices on environmental sustainability: Evidence from WAMCO PLC. Journal of Educational Management & Social Sciences, 1, 1-19. https://doi.org/10.48112/jemss.v1i2.212 DOI: https://doi.org/10.48112/jemss.v1i2.212

Gaur, O., Afaq, A., Arora, G. K., & Khan, N. (2023). Artificial intelligence for carbon emissions using system of systems theory. Ecological Informatics, 76, 102165. https://doi.org/10.1016/j.ecoinf.2023.102165 DOI: https://doi.org/10.1016/j.ecoinf.2023.102165

Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2021). A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management. https://doi.org/10.1108/IJPPM-08-2020-0427 DOI: https://doi.org/10.1108/IJPPM-08-2020-0427

Guillen Jr, N. B. (2022). Continuance intention of massive open online course learners in higher education: A sustainable development initiative. SEISENSE Business Review, 2(1), 67-79. DOI: https://doi.org/10.33215/sbr.v2i1.810

Guillen, N., & Lim, C. T. (2023). Unlocking growth opportunities for Philippine micro, small, and medium enterprises through Facebook advertising and growth hacking strategies in the post-pandemic era. International Journal of Multidisciplinary: Applied Business and Education Research, 4(8), 2884-2893. DOI: https://doi.org/10.11594/ijmaber.04.08.26

Higgins, J. P., Green, S., & Cochrane Collaboration. (2011). Cochrane handbook for systematic reviews of interventions (Version 5.1.0). Cochrane Collaboration.

Howard, J. (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62(11), 917-926. DOI: https://doi.org/10.1002/ajim.23037

Jamiu, A., Odugbesan, S., Haj, S. A., Aghazadeh, R., Al-Qaralleh, E., & Sogeke, O. S. (2022). Green talent management and employees' innovative work behavior: The roles of artificial intelligence and transformational leadership. Journal of Knowledge Management. https://doi.org/10.1108/jkm-08-2021-0601 DOI: https://doi.org/10.1108/JKM-08-2021-0601

Kar, S., Kar, A. K., & Gupta, M. P. (2022). Modeling drivers and barriers of artificial intelligence adoption: Insights from a strategic management perspective. Information Systems and Analytics for Society, 12(1), Article 1503. https://doi.org/10.1002/isaf.1503 DOI: https://doi.org/10.1002/isaf.1503

Kapoor, R., Gupta, P., & Li, H. (2022). Artificial intelligence for green supply chain management: Insights from global and local practices. International Journal of Supply Chain Management, 7(4), 211-223.

Liu, Y., Zhang, X., & Li, M. (2021). Barriers to AI adoption in sustainability: Organizational and technological challenges. Journal of Business Research, 131, 360-372.

Lozano, R. (2015). A holistic perspective on corporate sustainability drivers. Corporate Social Responsibility and Environmental Management, 22(1), 32-45. DOI: https://doi.org/10.1002/csr.1325

Madancian, M., Taherdoost, H., Farhaoui, Y., & Khan, I. U. (2024, July). Leveraging AI for sustainable leadership: A transformative approach. In International Conference on Communication, Information, and Digital Technologies (CIDT2024) (Vol. 13185, pp. 71-75). SPIE. https://doi.org/10.1117/12.3033521 DOI: https://doi.org/10.1117/12.3033521

Nguyen, L., Tan, Y., & Lee, S. (2020). AI applications in environmental responsibility: A comprehensive review. Sustainability Science, 25(5), 1247-1261.

Olazo, D. B. (2022). Measuring the level of digital marketing capabilities, digital marketing strategies and challenges and issues of SMEs in adopting digital marketing. J. Mark. Adv. Pract, 4, 79-96.

Olazo, D. B. (2023). Measuring the impact of CSR practices on customer satisfaction during pandemic: a quantitative study in the Philippines. Social Responsibility Journal, 19(8), 1521-1534. DOI: https://doi.org/10.1108/SRJ-06-2022-0244

Rajani, H., Pillai, S., Sunitha, A., Pathanjali, S., Roopa, A., Adarsh, P., & Preethi, . (2024). Artificial intelligence-based green human resource management for organization’s operation model. IEEE Xplore. https://doi.org/10.1109/icrtcst61793.2024.10578475 DOI: https://doi.org/10.1109/ICRTCST61793.2024.10578475

Rosales, M., Magsumbol, J., Palconit, M. G., Culaba, A., & Dadios, E. (2020). Artificial intelligence: The technology adoption and impact in the Philippines. In Proceedings of the 2020 International Conference on Hybrid Natural Intelligence for Computer Engineering and Management (HNICEM), 1–6. https://doi.org/10.1109/HNICEM51456.2020.9400025 DOI: https://doi.org/10.1109/HNICEM51456.2020.9400025

Sanwal, T., Rajput, J., Tyagi, M., Yadav, S., Avasthi, S., & Sareen, P. (2025). The application of AI to the adoption of green HRM practices. In Green HRM Awareness and Training in Higher Education Institutions (pp. 241-268). IGI Global. https://doi.org/10.4018/979-8-3693-2956-6.ch01 DOI: https://doi.org/10.4018/979-8-3693-2956-6.ch010

Sari, R., Min, S., Purwoko, H., Furinto, A., & Tamara, D. (2020). Artificial intelligence for a better employee engagement. International Research Journal of Business Studies, 13(2), 173-188. https://doi.org/10.21632/irjbs.13.2.173-188 DOI: https://doi.org/10.21632/irjbs.13.2.173-188

Schultz, P. W. (2019). Encouraging pro-environmental behavior in organizations: A review of the research and future directions. Journal of Organizational Behavior, 40(6), 825-841. https://doi.org/10.1002/job.2374 DOI: https://doi.org/10.1002/job.2374

Tshabalala, L. (2023). The role of artificial intelligence in enhancing workforce productivity: Advanced computing applications in HR. Journal of Advanced Computing Systems, 3(12), 26-33.

Ukoba, K., Olatunji, K. O., Adeoye, E., Jen, T.-C., & Madyira, D. M. (2024). Optimizing renewable energy systems through artificial intelligence: Review and prospects. Energy & Environment, 35(7), 3833-3879. https://doi.org/10.1177/0958305X241256293 DOI: https://doi.org/10.1177/0958305X241256293

Verma, A., Gupta, K., & Sharma, K. (2023). Artificial intelligence: A catalyst for human resource transformation. Journal of Organizational Transformation & Social Change, 20(2), 132-144.

Yutuc, A. V., Olazo, D. B., & Sarmiento, P. J. D. (2021). Business sectors’ initiatives on health and safety protocols and vaccination program among employees during the COVID-19 pandemic. Journal of Public Health, 43(4), e751-e752. DOI: https://doi.org/10.1093/pubmed/fdab139

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