Integration of biometric technologies into a personnel management system in a digital economy

Economic Annals-ХХI: Volume 186, Issue 11-12, Pages: 103-111

Citation information:
Tomakova, I., & Kopteva, Zh. (2020). Integration of biometric technologies into a personnel management system in a digital economy. Economic Annals-XXI, 186(11-12), 103-111. doi: https://doi.org/10.21003/ea.V186-12

Irina Tomakova
PhD (Economics),
Associate Professor of the Management and Audit Department,
Southwest State University
94, 50 Let Oktyabrya Str., Kursk, 305040, Russian Federation
tomakova@mail.ru
ORCID ID: https://orcid.org/0000-0001-7419-1813

Zhanna Kopteva
PhD (Economics),
Associate Professor of the Management and Audit Department,
Southwest State University
94, 50 Let Oktyabrya Str., Kursk, 305040, Russian Federation
koptevvv@mail.ru
ORCID ID: https://orcid.org/0000-0003-1198-6357

Integration of biometric technologies into a personnel management system in a digital economy

Abstract. Digital technologies are widely used by the world population and development of digital economy is reflected in national projects, as well as in federal and regional programs. Therefore, the topic of biometric technologies is especially important now because such technologies have been used in various areas of economic activity. Yet, despite great opportunities which biometric technologies have, their use in personnel work has not been sufficiently studied. The paper presents a comprehensive analysis of the possibility of integration of biometric technologies into the personnel management system and provides an assessment of their impact on the efficiency of modern companies. Statistical data analysis is theoretical and practical basis of the study. Problems and negative factors that prevent the introduction of biometrics in modern business segment are determined more relevant on its basis. The authors of the paper have analyzed the current state and growth rate of the global market of biometric systems.

As a result of this study, the approach to assessing the effectiveness of introducing biometric technologies into personnel management system of modern companies has been scientifically proven. Also, it has been determined that biometric technologies can simplify the procedure for normalizing labour processes because biometric time recorders allow for tracking the time of employees’ stay in various departments, detailed movement schemes, the efficiency of each employee’s activity during the working day. Due to biometric time recorders, it is also possible to prepare reports about work and rest conditions of employees, evaluate the effectiveness of their work and keep records of employees transferred to distance work. Further, it is possible to formulate labour standards of various categories of employees and form the total wage fund. It has been found that the integration of biometric technologies into personnel management system will increase the intensity of the use of organizations’ labour resources.

Keywords: Biometric Technologies; Efficiency; Personnel Management; Labour Rationing; Economics; Management System and Access Control (MSAC)

JEL Classification: J29; L86; M11

Acknowledgements and Funding: The authors received no direct funding for this research.

Contribution: The authors contributed equally to this work.

DOI: https://doi.org/10.21003/ea.V186-12

References

1. Abomhara, M., Yayilgan, S. Y., Nweke, L. O., & Székely, Z. (2021). A comparison of primary stakeholders’ views on the deployment of biometric technologies in border management: Case study of SMart mobILity at the European land borders. Technology in Society, 64, 101484.
   https://doi.org/10.1016/j.techsoc.2020.101484
2. Anand, A., Labati, R. A., Genovese, A., Muñoz, E., Piuri, V., Scotti, F., & Sforza, G. (2016). Enhancing fingerprint biometrics in automated control with adaptive cohorts [Paper presentation]. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Greece, Athens.
   https://doi.org/10.1109/SSCI.2016.7850073
3. Bersin, J. (2017, November 6). What are the 3 big HR technology disruptions for 2018? InsideHR.
   https://www.insidehr.com.au/hr-technology-disruptions-2018
4. Bowyer, K. W., & Burge, M. J. (2016). Handbook of Iris Recognition (2nd ed.). Springer, London.
   https://doi.org/10.1007/978-1-4471-6784-6
5. Deloitte. (2020). Global Human Capital Trends.
   https://www.deloitte.com/us/en/pages/human-capital/articles/introduction-human-capital-trends.htm
6. Grishina E. A. (2015). Biometric technologies in Russian banks: dreams or reality. Science and society, 22(3), 17-21 (in Russ.).
7. ICT Moscow. (2018). Review of the international market of biometric technologies and their application in the financial sector.
   https://ict.moscow/research/obzor-mezhdunarodnogo-rynka-biometricheskikh-tekhnologii-i-ikh-primenenie-v-finansovom-sektore (in Russ.)
8. Kopteva, Zh. Yu. (2014). On the issue of creating a national payment system of bank cards in Russia: Economic and legal aspect. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta (Bulletin of the South-West State University), 1, 83-85 (in Russ.).
9. Kopteva, Zh. Yu., Afanasyeva, L. A., & Afanasyev, A. A. (2017). Optimization of the personnel policy of the enterprise by introducing innovative personnel technologies. Modern Scientist, 2, 79-82 (in Russ.).
10. Korenevsky, N. A., Tomakova, R. A., Seregin, S. P., & Rybochkin, A. F. (2013). Neural networks with macro-layers for classification and prediction of retinal pathologies. Medical equipment, 280(4), 16-18.
    http://www.mtjournal.ru/upload/iblock/362/362a1ad90c7a8a5cbb323e27f76762c6.pdf (in Russ.)
11. Krylova, I. Yu., & Rudakova, O. S. (2018). Biometric technologies as a mechanism for ensuring information security in the digital economy. Young Scientist, 231(45), 74-79.
    https://moluch.ru/archive/231/53640 (in Russ.)
12. Kulikov, V. (2003). New segments of the information technology market. Biometric technologies. Journal Electronics: Science, Technology, Business, 48(6), 55-57.
    https://www.electronics.ru/journal/article/1231 (in Russ.)
13. Lazutina, A. L., & Lebedeva, T. E. (2019). New requirements for the quality of personnel management in the digital economy and management. Topical issues of the modern economy, 5, 177-180 (in Russ.).
14. Li, S. Z., & Jain, A. K. (2011). Handbook of Face Recognition (2nd ed.). Springer-Verla, London.
    https://www.springer.com/gp/book/9780857299314
15. Li, S. Z., & Jain, A. K. (2015). Encyclopedia of Biometrics (2nd ed.). Springer US.
    https://www.springer.com/gp/book/9781489974877
16. Maltsev, A. (2011, August 11). Modern biometric identification methods. Habr.
    https://habrahabr.ru/post/126144 (in Russ.)
17. Mazaraki, A., & Fomina, O. (2016). Tools for management accounting. Economic Annals-XXI, 159(5-6), 48-51.
    https://doi.org/10.21003/ea.V159-10
18. Natorina, A. (2020). Business optimization in the digital age: insights and recommendations. Economic Annals-XXI, 181(1-2), 83-91.
    https://doi.org/10.21003/ea.V181-07
19. Panteleeva, T. A., Arustamov, E. A., & Maksaev, A. A. (2019). The possibilities of artificial intelligence in the management of human resources in a free enterprise. Russian journal of resources, conservation and recycling, 6(3), 1-9.
    https://doi.org/10.15862/10ECOR319 (in Russ.)
20. Rychenkova, I. V., Rychenkov M. V., & Kireev V. S. (2014.) The economic effect of the introduction of an automated access control and management system as a factor in improving competitiveness. Modern problems of Science and Education, 6.
    http://science-education.ru/ru/article/view?id=16908 (in Russ.)
21. Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019). Ethical, Legal, and Social Implications of Biometric Technologies. In M. Obaidat, I. Traore, & I. Woungang (Ed.), Biometric-Based Physical and Cybersecurity Systems. Springer, Cham.
    https://doi.org/10.1007/978-3-319-98734-7_21
22. Tomakova, R. A., Filist, S. A., & Pykhtin, A. I. (2017). Development and Research of Methods and Algorithms for Intelligent Systems for Complex Structured Images Classification. Journal of Engineering and Applied Sciences, 12(22), 6039-6041.
    https://medwelljournals.com/abstract/?doi=jeasci.2017.6039.6041
23. Tomakova, R. A., Filist, S. A., Pykhtin, A. I., & Ostrotskaja, S. V. (2019). Classification on Mulchannel Images Based on Cellular Processes [Paper presentation]. 19th International Multidisciplinary Scientific Geoconference SGEM 2019, 145-152, Albena, Bulgaria.
    http://toc.proceedings.com/49675webtoc.pdf
24. Unal, С., & Tecim, V. (2018). The Use of Biometric Technology for Effective Personnel Management System in Organization. KnE Social Sciences, 3(10), 221-232.
    https://knepublishing.com/index.php/KnE-Social/article/view/3540
25. Van Esch, P., Black, J. S., Franklin, D., & Harder, M. (2020). AI-enabled biometrics in recruiting: Insights from marketers for managers. Australasian Marketing Journal, 00(0), 1-10.
    https://doi.org/10.1016/j.ausmj.2020.04.003
26. Vinnikova, I. S., & Kuznetsova, E. A. (2016). Features of the use of biometric indicators in the protection of savings of the population. Online journal NAUKOVEDENIE (Online journal Science of Science), 8(2), 1-8.
    http://naukovedenie.ru/PDF/60EVN216.pdf (in Russ.)
27. Volner, R., & Boreš, P. (2009). Biometric Techniques in Identity Management Systems. Elektronika ir Elektrotechnika, 95(7), 55-58.
    https://eejournal.ktu.lt/index.php/elt/article/view/10045
28. Yavorsky, N. K. (2020). Digital technologies in the personnel management system. Young scientist, 309(19), 260-262.
    https://moluch.ru/archive/309/69896 (in Russ.)

Received 24.08.2020
Received in revised form 2.10.2020
Accepted 14.10.2020
Available online 28.12.2020