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Big IFs in Productivity-Enhancing Industry 4.0

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  • Oliver Kovacs

    (Institute of Economics and International Economics, National University of Public Service, 1083 Budapest, Hungary
    ICEG European Center, 1123 Budapest, Hungary)

Abstract

With the dawn of Industry 4.0, its productivity-boosting impact appears to be comfortably ensconced both in the media and in the scientific community. Still, our paper is to portend a rather dismal prognosis by outlining three big Inertia Forces (IFs) hindering the power of Industry 4.0 in reviving productivity growth in a more spectacular way. After applying a complexity view to the development of Industry 4.0 in deciphering the major IFs, the paper briefly exemplifies them by building on the case of Hungary, and it then draws some lessons for theorists and economic policy practitioners in the interest of a value-congruent development of Industry 4.0.

Suggested Citation

  • Oliver Kovacs, 2019. "Big IFs in Productivity-Enhancing Industry 4.0," Social Sciences, MDPI, vol. 8(2), pages 1-17, January.
    • Handle: RePEc:gam:jscscx:v:8:y:2019:i:2:p:37-:d:201238
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    1. Bak, Per & Chen, Kan & Scheinkman, Jose & Woodford, Michael, 1993. "Aggregate fluctuations from independent sectoral shocks: self-organized criticality in a model of production and inventory dynamics," Ricerche Economiche, Elsevier, vol. 47(1), pages 3-30, March.
    2. Antonella Petrillo & Fabio De Felice & Raffaele Cioffi & Federico Zomparelli, 2018. "Fourth Industrial Revolution: Current Practices, Challenges, and Opportunities," Chapters, in: Antonella Petrillo & Raffaele Cioffi & Fabio De Felice (ed.), Digital Transformation in Smart Manufacturing, IntechOpen.
    3. Fernando E. Garcia-Muiña & Rocío González-Sánchez & Anna Maria Ferrari & Davide Settembre-Blundo, 2018. "The Paradigms of Industry 4.0 and Circular Economy as Enabling Drivers for the Competitiveness of Businesses and Territories: The Case of an Italian Ceramic Tiles Manufacturing Company," Social Sciences, MDPI, vol. 7(12), pages 1-31, December.
    4. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
    5. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    6. Gilbert Cette & Jimmy Lopez & Jacques Mairesse, 2016. "Labour Market Regulations and Capital Intensity," NBER Working Papers 22603, National Bureau of Economic Research, Inc.
    7. Nolan, Brian & Thewissen, Stefan & Roser, Max, 2016. "GDP per capita versus median household income: What gives rise to divergence over time?," INET Oxford Working Papers 2016-03, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    8. Paul M. Romer, 2015. "Mathiness in the Theory of Economic Growth," American Economic Review, American Economic Association, vol. 105(5), pages 89-93, May.
    9. Alexandra M. de Pleijt & Jacob L. Weisdorf, 2017. "Human capital formation from occupations: the ‘deskilling hypothesis’ revisited," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 11(1), pages 1-30, January.
    10. Gilbert Cette & Jimmy Lopez & Jacques Mairesse, 2016. "Labour Market Regulations and Capital Intensity," NBER Working Papers 22603, National Bureau of Economic Research, Inc.
    11. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    12. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    13. Elzbieta Robak, 2017. "Expectations of generation Y connected with shaping the work-life balance. The case of Poland," Oeconomia Copernicana, Institute of Economic Research, vol. 8(4), pages 569-584, December.
    14. Zeira, Joseph & Nakamura, Hideki, 2018. "Automation and Unemployment: Help is on the Way," CEPR Discussion Papers 12974, C.E.P.R. Discussion Papers.
    15. Dan Andrews & Chiara Criscuolo & Peter N. Gal, 2016. "The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy," OECD Productivity Working Papers 5, OECD Publishing.
    16. Bronwyn H Hall & Georg von Graevenitz & Christian Helmers, 2021. "Technology Entry in the Presence of Patent Thickets," Oxford Economic Papers, Oxford University Press, vol. 73(2), pages 953-953.
    17. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    18. Carlota Perez, 2010. "Technological revolutions and techno-economic paradigms," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 34(1), pages 185-202, January.
    19. Antonin Bergeaud & Gilbert Cette & Remy Lecat, 2017. "Total Factor Productivity in Advanced Countries: A Longterm Perspective," International Productivity Monitor, Centre for the Study of Living Standards, vol. 32, pages 6-24, Spring.
    20. Judit Nagy & Judit Oláh & Edina Erdei & Domicián Máté & József Popp, 2018. "The Role and Impact of Industry 4.0 and the Internet of Things on the Business Strategy of the Value Chain—The Case of Hungary," Sustainability, MDPI, vol. 10(10), pages 1-25, September.
    21. John Martin & Stefano Scarpetta, 2012. "Setting It Right: Employment Protection, Labour Reallocation and Productivity," De Economist, Springer, vol. 160(2), pages 89-116, June.
    22. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    23. Christina D. Romer & David H. Romer, 2017. "New Evidence on the Aftermath of Financial Crises in Advanced Countries," American Economic Review, American Economic Association, vol. 107(10), pages 3072-3118, October.
    24. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2018. "An Empirical Investigation of the Relationship between Overall Equipment Efficiency (OEE) and Manufacturing Sustainability in Industry 4.0 with Time Study Approach," Sustainability, MDPI, vol. 10(9), pages 1-28, August.
    25. Sovinsky, Michelle & Eizenberg, Alon & Pechy, Andras, 2016. "Technology Adoption, Vertical Restraints and Partial Foreclosure: Changing the Structure of an Industry," VfS Annual Conference 2016 (Augsburg): Demographic Change 145680, Verein für Socialpolitik / German Economic Association.
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