Technological Unemployment: A Bibliometric Perspective on Job Displacement and Innovation
Roshan Kumar1 and Shakti Kant Sharma2
1Research Scholar, Faculty of Commerce, Banaras Hindu University, Varanasi, Email: kumarroshan@bhu.ac.in
2Research Scholar, Faculty of Commerce, Banaras Hindu University, Varanasi, Email: sk801303@bhu.ac.in
ABSTRACT:
Technological advances, especially in AI and robots, have affected labour markets, raising concerns about technological unemployment. This research systematically analyses technological unemployment literature, focussing on how developing technologies affect employment dynamics, income inequality, and job displacement. Through descriptive, network, coupling, and cluster methodologies, the research reveals crucial themes like the complicated relationship between innovation and employment, AI’s dual impact on productivity and inequality, and the need for effective educational and governmental solutions. The study uses Vos-Viewer to analyse publication trends, citation networks, and theme clusters in 124 Scopus publications. The paper divides research into six clusters. Key findings show that technology development displaces some occupations but generates others, while the advantages are not universal. Job polarisation, pay inequality, and educational reform are major concerns. The research emphasises the need to balance technological benefits with worker protections and offers a holistic strategy to technological unemployment that includes policy and educational improvements.
Keywords: Technological unemployment, Job displacement, Labour Markets, AI and robots, Bibliomatric perspective
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REFERENCES:
Avis, J. (2018). Socio-technical imaginary of the fourth industrial revolution and its implications for vocational education and training: A literature review. Journal of Vocational Education & Training, 70(3), 337-363.
Baier-Fuentes, H., Merigó, J. M., Amorós, J. E., and Gaviria-Marín, M. (2019). International entrepreneurship: a bibliometric overview. International Entrepreneurship and Management Journal, 15(2), 385–429. doi:10.1007/s11365-017-0487-y
Bertani, F., Ponta, L., Raberto, M., Teglio, A., & Cincotti, S. (2021). The complexity of the intangible digital economy: an agent-based model. Journal of business research, 129, 527-540.
Bertani, F., Raberto, M., & Teglio, A. (2020). The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment. Review of Evolutionary Political Economy, 1(3), 329-355.
Bhaskar, R., and Bansal, S. (2022, June 30). Nineteen Years of Emerging Markets Finance and Trade: A Bibliometric Analysis. Emerging Markets Finance and Trade, 58(14), 4120–4135. doi:10.1080/1540496x.2022.2086041
Bordot, F. (2022). Artificial intelligence, robots and unemployment: Evidence from OECD countries. Journal of Innovation Economics & Management, (1), 117-138.
Bruun, E. P., & Duka, A. (2018). Artificial intelligence, jobs and the future of work: Racing with the machines. Basic Income Studies, 13(2), 20180018.
Calvino, F., & Virgillito, M. E. (2018). The innovation‐employment nexus: a critical survey of theory and empirics. Journal of Economic surveys, 32(1), 83-117.
Calvino, F., & Virgillito, M. E. (2018). The innovation‐employment nexus: a critical survey of theory and empirics. Journal of Economic surveys, 32(1), 83-117.
Campa, R. (2019). Technological unemployment and universal basic income: A scientometric analysis. Sociologies in Dialogue, 5(1).
Chuang, S., & Graham, C. (2018). Embracing the sobering reality of technological influences on jobs, employment and human resource development. European Journal of Training and Development.
Coad, A., & Rao, R. (2011). The firm-level employment effects of innovations in high-tech US manufacturing industries. Journal of Evolutionary Economics, 21, 255-283.
Cumming, D., Kumar, S., Lim, W. M., and Pandey, N. (2022, October 4). Mapping the venture capital and private equity research: a bibliometric review and future research agenda. Small Business Economics, 61(1), 173–221. doi:10.1007/s11187-022-00684-9
Danaher, J. (2017). Will life be worth living in a world without work? Technological unemployment and the meaning of life. Science and engineering ethics, 23(1), 41-64.
Danaher, J. (2019). The rise of the robots and the crisis of moral patiency. ai & Society, 34(1), 129-136.
Dodel, M., & Mesch, G. S. (2020). Perceptions about the impact of automation in the workplace. Information, Communication & Society, 23(5), 665-680.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., and Lim, W. M. (2021, September). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. doi:10.1016/j.jbusres.2021.04.070
Ernst, E., Merola, R., & Samaan, D. (2019). Economics of artificial intelligence: Implications for the future of work. IZA Journal of Labor Policy, 9(1).
Feldmann, H. (2013). Technological unemployment in industrial countries. Journal of Evolutionary Economics, 23, 1099-1126.
Fu, X. M., Bao, Q., Xie, H., & Fu, X. (2021). Diffusion of industrial robotics and inclusive growth: Labour market evidence from cross country data. Journal of Business Research, 122, 670-684.
Goos, M. (2018). The impact of technological progress on labour markets : policy challenges. Oxford Review of Economic Policy, 34, 362-375.
Jung, J. (2020). The fourth industrial revolution, knowledge production and higher education in South Korea. Journal of Higher Education Policy and Management, 42(2), 134-156.
Kaur, M., Kaur, J., & Kaur, R.K. (2023). Adapting to Technological Disruption: Challenges and Opportunities for Employment. 2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), 347-352.
Kessler, M. M. (1963, January). Bibliometric coupling between scientific papers. American Documentation, 14(1), 10–25. doi:10.1002/asi.5090140103
Kim, T. W., & Scheller-Wolf, A. (2022). Technological unemployment, meaning in life, purpose of business, and the future of stakeholders. In Business and the Ethical Implications of Technology (pp. 13-31). Cham: Springer Nature Switzerland.
Kim, Y. J., Kim, K., & Lee, S. (2017). The rise of technological unemployment and its implications on the future macroeconomic landscape. Futures, 87, 1-9.
Kolade, O., & Owoseni, A. (2022). Employment 5.0: The work of the future and the future of work. Technology in Society, 71, 102086.
Kuzior, A. (2022). Technological unemployment in the perspective of Industry 4.0. Virtual Economics, 5(1), 7-23.
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P., & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1-e34.
Marchant, G.E., Stevens, Y.A., & Hennessy, J.M. (2014). Technology, Unemployment & Policy Options: Navigating the Transition to a Better World.
McClure, P. K. (2018). “You’re fired,” says the robot: the rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), 139-156.
Novakova, L. (2020). The impact of technology development on the future of the labour market in the Slovak Republic. Technology in Society, 62, 101256.
Özcan, R. (2019). The rise of robots! Effects on employment and income. Öneri Dergisi, 14(51), 1-17.
Pandey, D. K., Hunjra, A. I., Bhaskar, R., & Al-Faryan, M. A. S. (2023). Artificial intelligence, machine learning and big data in natural resources management: a comprehensive bibliometric review of literature spanning 1975–2022. Resources Policy, 86, 104250.
Pattnaik, D., Kumar, S., and Vashishtha, A. (2020, June 13). Research on trade credit – a systematic review and bibliometric analysis. Qualitative Research in Financial Markets, 12(4), 367–390. doi:10.1108/qrfm-09- 2019-0103
Peters, M. A., Jandrić, P., & Hayes, S. (2019). The curious promise of educationalising technological unemployment: What can places of learning really do about the future of work?. Educational Philosophy and Theory, 51(3), 242-254.
Rąb-Kettler, K., & Lehnervp, B. (2019). Recruitment in the Times of Machine Learning. Management Systems in Production Engineering, 27 (2), 105–109.
Richters, O., & Siemoneit, A. (2019). Growth imperatives: Substantiating a contested concept. Structural Change and Economic Dynamics, 51, 126-137.
Walden, E., Cogo, G. S., Lucus, D. J., Moradiabadi, E., & Safi, R. (2018). Neural Correlates of Multidimensional Visualizations. MIS Quarterly, 42(4), 1097-A8.
Wu, J. J., & Atkinson, R. D. (2017). How technology-based start-ups support US economic growth. Information Technology & Innovation Foundation ITIF, November.