Utilizing HRM in Web Services and the Role of AI: Triple Bottom Line Sustainability
Keywords:
Management of Human Resources, Triple Bottom Line, United Nations Goal, HRM, AIAbstract
In the contemporary business landscape, organizations are increasingly recognizing the pivotal role of their employees as their most valuable assets. This acknowledgment has propelled Human Resource Management (HRM) into a strategic position where it ensures that a company's workforce is effectively managed, motivated, and engaged. HRM has evolved significantly over time, transitioning from its historical administrative functions to a more holistic and strategic approach in managing human capital. With the integration of web services and artificial intelligence (AI) into HRM practices, there has been a profound transformation in the way organizations manage their human resources, enhancing efficiency and effectiveness while contributing to a comprehensive approach to sustainability known as the Triple Bottom Line (TBL). This article delves into the utilization of HRM in web services and the transformative role of AI in achieving Triple Bottom Line sustainability. It also highlights how AI fosters social sustainability by reducing bias and discrimination, promoting diverse and inclusive recruitment, and supporting employee well-being. Furthermore, it discusses the impact of AI on environmental sustainability, particularly in optimizing remote work and minimizing ecological footprints. In conclusion, this article underscores the symbiotic relationship between HRM, web services, and AI and their pivotal role in achieving the Triple Bottom Line. It demonstrates how these modern tools and technologies enhance economic, social, and environmental sustainability, making HRM an essential component of responsible and sustainable business practices in the digital age.
References
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Fellander, A., Daniela Langhans, S., Tegmark, M., & Nerini, F. F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. NATURE COMMUNICATIONS, 11(1). https://doi.org/10.1038/s41467-019-14108-y
Ranjbari, M., Esfandabadi, Z. S., Zanetti, M. C., Scagnelli, S. D., Siebers, P.-O., Aghbashlo, M., Peng, W., Quatraro, F., & Tabatabaei, M. (2021). Three pillars of sustainability in the wake of COVID-19: A systematic review and future research agenda for sustainable development. JOURNAL OF CLEANER PRODUCTION, 297. https://doi.org/10.1016/j.jclepro.2021.126660
Garg, V., Srivastav, S., & Gupta, A. (2018). Application of Artificial Intelligence for Sustaining Green Human Resource Management. 2018 International Conference on Automation and Computational Engineering, ICACE 2018, 113–116. https://doi.org/10.1109/ICACE.2018.8686988
Pal, S., Das, P., Mandal, I., Sarda, R., Mahato, S., Nguyen, K.-A., Liou, Y.-A., Talukdar, S., Debanshi, S., & Saha, T. K. (2021). Effects of lockdown due to COVID-19 outbreak on air quality and anthropogenic heat in an industrial belt of India. JOURNAL OF CLEANER PRODUCTION, 297. https://doi.org/10.1016/j.jclepro.2021.126674
Pierrat, E., Rupcic, L., Hauschild, M. Z., & Laurent, A. (2021). Global environmental mapping of the aeronautics manufacturing sector. JOURNAL OF CLEANER PRODUCTION, 297. https://doi.org/10.1016/j.jclepro.2021.126603
Hannan, M. A., Al-Shetwi, A. Q., Ker, P. J., Begum, R. A., Mansor, M., Rahman, S. A., Dong, Z. Y., Tiong, S. K., Mahlia, T. M. I., & Muttaqi, K. M. (2021). Impact of renewable energy utilization and artificial intelligence in achieving sustainable development goals. ENERGY REPORTS, 7, 5359–5373. https://doi.org/10.1016/j.egyr.2021.08.172
Pierrat, E., Rupcic, L., Hauschild, M. Z., & Laurent, A. (2021). Global environmental mapping of the aeronautics manufacturing sector. JOURNAL OF CLEANER PRODUCTION, 297. https://doi.org/10.1016/j.jclepro.2021.126603
Chang, T.-M., Hsu, M.-F., & Lin, S.-J. (2018). Integrated news mining technique and AI-based mechanism for corporate performance forecasting. INFORMATION SCIENCES, 424, 273–286. https://doi.org/10.1016/j.ins.2017.10.004
Wang, K., Zhao, Y., Gangadhari, R. K., & Li, Z. (2021). Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China. SUSTAINABILITY, 13(19). https://doi.org/10.3390/su131910983
Taimoor, N., & Rehman, S. (2022). Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey. IEEE ACCESS, 10, 535–563. https://doi.org/10.1109/ACCESS.2021.3137364
Rahman, M. S., Hossain, M. A., Chowdhury, A. H., & Hoque, M. T. (n.d.). Role of enterprise information system management in enhancing firms competitive performance towards achieving SDGs during and after COVID-19 pandemic. JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT. https://doi.org/10.1108/JEIM-04-2021-0163
Ponnusamy, V. K., Kasinathan, P., Madurai Elavarasan, R., Ramanathan, V., Anandan, R. K., Subramaniam, U., Ghosh, A., & Hossain, E. (2021). A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid. SUSTAINABILITY, 13(23). https://doi.org/10.3390/su132313322
Bukhari, S.N.H.; Jain, A.; Haq, E.; Mehbodniya, A.; Webber, J. Ensemble Machine Learning Model to Predict SARS-CoV-2 T-Cell Epitopes as Potential Vaccine Targets. Diagnostics 2021, 11, 1990. https://doi.org/10.3390/diagnostics11111990
Syed Nisar Hussain Bukhari, Amit Jain, Ehtishamul Haq, Moaiad Ahmad Khder, Rahul Neware, Jyoti Bhola, Moslem Lari Najafi, "Machine Learning-Based Ensemble Model for Zika Virus T-Cell Epitope Prediction", Journal of Healthcare Engineering, vol. 2021, Article ID 9591670, 10 pages, 2021. https://doi.org/10.1155/2021/9591670
Pigola, A., da Costa, P. R., Carvalho, L. C., Silva, L. F. da, Kniess, C. T., & Maccari, E. A. (2021). Artificial Intelligence-Driven Digital Technologies to the Implementation of the Sustainable Development Goals: A Perspective from Brazil and Portugal. SUSTAINABILITY, 13(24)
Ponnusamy, V. K., Kasinathan, P., Madurai Elavarasan, R., Ramanathan, V., Anandan, R. K., Subramaniam, U., Ghosh, A., & Hossain, E. (2021). A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid. SUSTAINABILITY, 13(23). https://doi.org/10.3390/su132313322
Rahman, M. S.,] Hossain, M. A., Chowdhury, A. H., & Hoque, M. T. (n.d.). Role of enterprise information system management in enhancing firms’ competitive performance towards achieving SDGs during and after the COVID-19 pandemic. JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT. https://doi.org/10.1108/JEIM-04-2021-0163
