Socio-Economic Determinants of Industrial Automation

The article examines the relationship between socio-economic development and a new wave of industrial automation using the examples of Japan, the Republic of Korea, China, the United States, Germany and India. A correlation analysis of industrial robotization rates and the dynamics of demographic change, unemployment, industrial value added, and investment in research and development is conducted, identifying the background and leading socio-economic determinants of industrial automation. The study concludes that demographic dynamics exert a background influence on the pace of industrial automation at the current stage. The potential for human capital formation in industrialized countries with natural population growth is becoming a benchmark for investment in research and development. However, changes in the age structure of the population show only a weak to moderate correlation with the pace of industrial robot installations. The revival of industrial automation in the second decade of the 21st century across countries at different stages of demographic transition highlights the leading role of other factors. These include the potential to increase industrial value added and the overall availability of labor, which determine the effectiveness of investments in industrial robotization. Based on this conclusion, a forecast is made regarding the emergence of an institutional factor, whose growing importance will likely slow the pace of investment in industrial automation.

1. Abeliansky A., Prettner K. (2017). Automation and Demographic Change. SSRN Electronic Journal. DOI: 10.2139/ssrn.2959977.

2. Acemoglu D. (2025). Institutions, Technology and Prosperity. NBER Working Paper. No. w33442. Available at: https://ssrn.com/abstract=5130534,accessed 23.06.2025.

3. Adachi D., Kawaguchi D., Saito Y. (2024). Robots and Employment: Evidence from Japan, 1978–2017. Journal of Labor Economics. Vol. 42, no. 2, pp. 591– 634. DOI:10.1086/723205.

4. Akimov A.V. (2016). Demographic explosion, population aging and labor-saving technologies: interaction in the 21st century. World Economy and International Relations. Vol. 60, no. 5, pp. 50–60 (in Russian). DOI: 10.20542/0131-2227-2016-60-5-50-60.

5. Cheng H., Jia R., Li D. (2019). The Rise of Robots in China. Journal of Economic Perspectives. Vol. 33, no. 2, pp. 71–88. DOI: 10.1257/jep.33.2.71.

6. Dobbs R., Manyika J., Woetzel J. (2015). No Ordinary Disruption: The Four Global Forces Breaking All the Trends. New York: PublicAffairs, 288 pp.

7. Glotova M.P., Danilin I.V. (2017). Development of advanced manufacturing technologies in China: tasks, results, challenges (using robotics as an example). Problems of the Far East. No. 4, pp. 41–51 (in Russian).

8. Holger G., Hoda M. (2024). Robotization and employment dynamics in German manufacturing value chains. Structural Change and Economic Dynamics. Vol. 68, March, pp. 133–147. DOI: 10.1016/j.strueco.2023.10.014.

9. Korus S. (2017). Industrial Robot Cost Decline. ARK-invest. Available at: https:// www.ark-invest.com/articles/analyst-research/industrial-robot-costs,accessed23.06.2025.

10. Phang H. (2005). Demographic dividend and labour force transformations in Asia. The case of the Republic of Korea. United Nations Publication, pp. 119–139.Available at: https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/unpd_egm_200508_09_phang.pdf,accessed23.06.2025.

11. Tsvetkova N.N. (2017). Afro-Asian countries: new trends in globalization and labor-saving technologies. Oriens. Afro-Asian Societies: History and Modernity. No. 6, pp. 88–104 (in Russian). DOI: 10.7868/S0869190817060085.

12. Varnavskiy V.G. (2025). Global trends in robotics. World Economy and International Relations. Vol. 69, no. 1, pp. 5–16 (in Russian). DOI: 10.20542/0131-2227-2025-69-1-5-16.