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Technological unemployment, robotisation, and green deal: A story of unstable spillovers in China and South Korea (2008–2018)

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  • Focacci, Chiara Natalie

Abstract

The growing use of robots in the current ICT revolution has sparked a serious debate about the potential threat robots pose to human labour. In parallel, the convergence towards a more sustainable economy has caused a transformation of firms and a consequent restructuring of employment. In this article we investigate the problem of technological unemployment and environmental rebound effect by looking at how relationships between jobless growth, industrial robots usage, CO2 emissions, and renewable energy consumption changed over time in China and South Korea. Findings from a competition model based on differential equations for the period 2008–2018 show that robots do not always increase unemployment growth. On the other hand, the type of relationship between unemployment and sustainable use of energy changes over time, questioning the possibility of a smart green new deal.

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  • Focacci, Chiara Natalie, 2021. "Technological unemployment, robotisation, and green deal: A story of unstable spillovers in China and South Korea (2008–2018)," Technology in Society, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:teinso:v:64:y:2021:i:c:s0160791x20313075
    DOI: 10.1016/j.techsoc.2020.101504
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    Cited by:

    1. Wang, Jianlong & Wang, Weilong & Liu, Yong & Wu, Haitao, 2023. "Can industrial robots reduce carbon emissions? Based on the perspective of energy rebound effect and labor factor flow in China," Technology in Society, Elsevier, vol. 72(C).
    2. Yuri Lima & Carlos Eduardo Barbosa & Herbert Salazar dos Santos & Jano Moreira de Souza, 2021. "Understanding Technological Unemployment: A Review of Causes, Consequences, and Solutions," Societies, MDPI, vol. 11(2), pages 1-17, May.
    3. AlMalki, Hameeda A. & Durugbo, Christopher M., 2023. "Evaluating critical institutional factors of Industry 4.0 for education reform," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Chiara Natalie Focacci, 2023. "Old versus young: How much do countries spend on social benefits? Deterministic modeling for government expenditure," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 363-377, February.
    5. Beier, Grischa & Matthess, Marcel & Shuttleworth, Luke & Guan, Ting & de Oliveira Pereira Grudzien, David Iubel & Xue, Bing & Pinheiro de Lima, Edson & Chen, Ling, 2022. "Implications of Industry 4.0 on industrial employment: A comparative survey from Brazilian, Chinese, and German practitioners," Technology in Society, Elsevier, vol. 70(C).
    6. Scheer, Antonina & Schwarz, Moritz & Hopkins, Debbie & Caldecott, Ben, 2022. "Whose jobs face transition risk in Alberta? Understanding sectoral employment precarity in an oil-rich Canadian province," LSE Research Online Documents on Economics 115358, London School of Economics and Political Science, LSE Library.
    7. Zhang, Qi-nan & Zhang, Fan-fan & Mai, Qiang, 2023. "Robot adoption and labor demand: A new interpretation from external competition," Technology in Society, Elsevier, vol. 74(C).
    8. Focacci, Chiara Natalie & Perez, Carlota, 2022. "The importance of education and training policies in supporting technological revolutions: A comparative and historical analysis of UK, US, Germany, and Sweden (1830–1970)," Technology in Society, Elsevier, vol. 70(C).
    9. Filippi, Emilia & Bannò, Mariasole & Trento, Sandro, 2023. "Automation technologies and their impact on employment: A review, synthesis and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    10. Du, Longzheng & Lin, Weifen, 2022. "Does the application of industrial robots overcome the Solow paradox? Evidence from China," Technology in Society, Elsevier, vol. 68(C).

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