Framework of Using Machine Leaning Techniques in Human Resource Management in Vietnamese Companies

• Autorzy: Thu Thuy Nguyen Thi , Nguyen Bich-Loan , Chi Trung Nguyen

Identyfikatory

DOI

10.15439/2021KM8

• Języki publikacji: EN

Abstrakty

EN

The COVID-19 pandemic requires many companies changing the way of their operations because of the lock down of movement and limitation of facing contact, etc. This also is an opportunity for companies to utilize technology and use digital space to keep their works and companies' activities. Companies can encourage their labors via policies of promotions. However, how to evaluate employee performance fairly, unbiasedly, and transparently? The existence of AI (Artificial Intelligence), especially machine learning, might be a solution for this due to the fact that it can automatically evaluate individual workers' performance. Therefore, the performance evaluation process ensures that the system works without interference from people outside of the system. In the paper, a framework of KPIs building systems to evaluate individual workers is represented as a solution for applying the advantage of AI (machine learning techniques) in Vietnamese companies. It can help them to improve the labor productivity and increase the workers' quality in the labor market in general.

Słowa kluczowe

EN

human resource management; machine learning; Artificial Intelligence; techniques; key performance indicators

PL

zarządzanie zasobami ludzkimi; nauczanie maszynowe; Sztuczna inteligencja; techniki; kluczowe wskaźniki efektywności

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2021
• Tom: Vol. 28
• Strony: 295--300
• Opis fizyczny: Bibliogr. 20 poz., wykr., il.

Twórcy

autor

Thu Thuy Nguyen Thi

• Thuongmai University 79, Ho Tung Mau, Mai Dich Ha Noi, Viet Nam

autor

Nguyen Bich-Loan

• Thuongmai University 79, Ho Tung Mau, Mai Dich Ha Noi, Viet Nam

autor

Chi Trung Nguyen

• Hanoi National University of Education 136 Xuan Thuy, Cau Giay Ha Noi, Viet Nam

Bibliografia

• 1. Benbya, H., & McKelvey B. 2006. Using coevolutionary and complexity theories to improve IS alignment: A multilevel approach. Journal of Information Technology, 21(4), 284298
• 2. Benbya, H., Nan, N., Tanriverdi, H., & Youngjin, Y. 2020. Complexity and information systems research in the emerging digital world. MIS Quarterly, 44(1), 1-17.
• 3. Bích Ngọc. 2019. Việt Nam: Mức độ sẵn sàng tham gia Cách mạng công nghiệp 4.0. Tạp chí Con số và sự kiện, Tổng cục Thống kê, Bộ Kế hoạch và Đầu tư – ISSN 2734 -9144. Available at website: http://consosukien.vn/viet-nam-muc-do-san-sang-tham-gia-cach-mang-cong-nghiep-4-0.htm
• 4. Chu Thị Bích Ngọc. 2018. Nâng cao chất lượng nguồn nhân lực Việt Nam trong cuộc CMCN 4.0, Tạp chí Tài chính, Availabe at website http://tapchitaichinh.vn/nghien-cuu--trao-doi/trao-doi-binh-luan/nang-cao-chat-luongnguon-nhan-luc-viet-nam-trong-cuoc-cach-mang-cong-nghiep-40-147363.html
• 5. Daniel, F. 2019. Machine Learning in Human Resources – Applications and Trends. Available at website: https://emerj.com/ai-sector-overviews/machine-learning-in-human-resources/
• 6. Daugherty, P., & Wilson, H. J. 2018. Human + machine: Reimagining work in the age of AI. Harvard Business Review Press.
• 7. Davenport, T. 2018. The AI advantage: How to put the artificial intelligence revolution to work. MIT Press.
• 8. Deloitte. 2020. Thriving in the era of pervasive AI: Deloitte’s state of AI in the enterprise (3rd ed.) https://www2.deloitte.com/us/en/insights/focus /cognitive-technologies/state-of-ai-andintelligent-automation-in-business-survey.html
• 9. Gregor, S., Lin, A. Gedeon, T., Riaz, A. and Zhu, D. 2014. Neuroscience and a nomological network for the understanding and assessment of emotions in information systems research. Journal of Management Information Systems, 30(4),13-47.
• 10. Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, H. 2020. The role of artificial intelligence and data network effects for creating user value. Academy of Management Review, 30(4), 13-47.
• 11. Hppy, 2016. the white paper and see how you can create an integrated, engaging employee experience using people analytics. Availabel at website: https://gethppy.com
• 12. Julia, M. 2020. How Machine Learning is Changing HR Industry. Availabe at website: https://codetiburon.com/machine-learning-changing-hr-industry/
• 13. Murray, A. Rhymer, J., & Simon, D. (in press). Humans and technology: Forms of conjoined agency in organizations. Academy of Management Review.
• 14. Nguyễn Thị Bích Loan. 2018. Báo cáo tổng kết hội thảo “CMCN 4.0: Cơ hội và thách thức đối với phát triển kinh tế Việt Nam”. Đại học Thương mại.
• 15. Nguyễn Trọng Hoài. 2018. Quốc tế hóa giáo dục Việt Nam: đào tạo nguồn nhân lực trong bối cảnh CMCN 4.0, Conference proceeding of “Nhu cầu nhân lực chất lượng cao cho phát triển trong bối cảnh CMCN 4.0”, page 236 – 252.
• 16. Olga,Y. 2020. How to Create an Applicant Tracking System and Improve Your Recruitment Process. Availabe at website: https://codetiburon.com/how-to-build-an-applicant-tracking-system/
• 17. Sarah, W. 2021. The Impact Of Machine Learning In HR. Available at website: https://gethppy.com/hrtrends/the-impact-of-machine-learning-in-hr
• 18. Trần Mai Đông et al. 2018. Tác động của cuộc CMCN 4.0 đến đời sống xã hội và dịch chuyển cơ cấu nguồn lao động, Conference proceeding of “Nhu cầu nhân lực chất lượng cao cho phát triển trong bối cảnh CMCN 4.0”. Page: 181 – 189.
• 19. workday Inc. 2021. Availbale at website: https://www.workday.com
• 20. https://www.statista.com/

Uwagi

1. Preface

2. Session: International Conference on Research in Management and Technovation