International Conference on Social Sciences and Humanities Research · Vol. 2 No. July Issue (2026)

Ways Of Improving The Efficiency Of Human Capital Under Remote Staff Management And Hybrid Work

Authors

  • Mohirabonu Abdumannofova

Keywords

digital transformation remote work hybrid work human capital return on human capital HCROI KPI labour productivity labour market digital management staff turnover digital onboarding continuous learning

Abstract

This paper analyses the operating characteristics of remote and hybrid labour models under digital transformation and their impact on the return on human capital. The study examines contemporary approaches to assessing labour productivity under remote management, in particular the possibilities of using the Human Capital Return on Investment (HCROI) indicator and KPI measures. Traditional and hybrid labour models are compared in terms of enterprise costs, staff turnover, labour productivity and team communication. Organisational and economic proposals for improving the efficiency of human capital use are also developed, taking into account the specific features of the labour market of Uzbekistan. The results of the study demonstrate the importance of improving result-based management, continuous learning and digital onboarding mechanisms under remote and hybrid working conditions.

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References

1. Abduraxmanov, Q. X. (2023). Human Resource Management: textbook. Tashkent. Available at: https://lib.gsbe.uz/files/resources/documents/1d409c82-8320-4585-a92b-8d43a6b134b1.pdf (in Uzbek)

2. Abduraxmanov, Q. X. (2024). Prospects for the development of human capital and the labour market in Uzbekistan. Scientific Electronic Journal “Labour Economics and Human Capital”, no. 2(6), pp. 14–22. https://doi.org/10.5281/zenodo.11630352 (in Uzbek)

3. Bloom, N. (n.d.). Hybrid Work Is Here to Stay. NBER Working Paper. Cambridge, MA: National Bureau of Economic Research.

4. Bloom, N., Han, R. & Liang, J. (2024). Hybrid working from home improves retention without damaging performance. Nature, 630, 920–925. https://doi.org/10.1038/s41586-024-07500-2

5. Brynjolfsson, E., Horton, J. J., Ozimek, A., Rock, D., Sharma, G. & TuYe, H.-Y. (2020). COVID-19 and Remote Work: An Early Look at US Data. NBER Working Paper No. 27344. Cambridge, MA: National Bureau of Economic Research.

6. Brynjolfsson, E., Li, D. & Raymond, L. R. (2023). Generative AI at Work. NBER Working Paper No. 31161. Cambridge, MA: National Bureau of Economic Research. Available at: https://danielle. li/assets/docs/GenerativeAIatWork.pdf

7. Brynjolfsson, E. et al. (n.d.). What the parameters of remote work imply for the future of the economy. SSRN Electronic Journal.

8. Kholiqov, Sh. R. (2025). Legal and organisational-economic aspects of regular and temporary remote work. InLibrary information and library portal, pp. 112–118. Available at: https://inlibrary.uz/index. php/science-research/article/view/79315 (in Uzbek)