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Industry 4.0 and production recovery in the covid era

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  • Cugno, Monica
  • Castagnoli, Rebecca
  • Büchi, Giacomo
  • Pini, Marco

Abstract

This study aims to use a quantitative analysis to explore the effects of openness to Industry 4.0 on the perceived production recovery post the COVID-19 pandemic, mediated by digital and classical reorganization. Openness to Industry 4.0 is measured by the breadth of the number of technologies adopted. The production recovery is measured by the perception of firms that a return to pre-COVID-19 production levels will happen within either 2021, 2022, or 2023. The study takes a representative sample of 2622 manufacturing small and medium enterprises across Italy (surveyed between October and November 2020) through a mediation analysis based on nonlinear probability models (KHB method). The results of the models show the following. First, openness to Industry 4.0 has a positive and significant direct effect on a perceived production recovery in the short term (within 2021) and medium term (within 2022 and 2023). Further, this effect is accelerated in the short term by digital reorganization and in the medium term by the addition of a classical reorganization. The research provides relevant managerial implications based on a large sample of current empirical data, showing that Industry 4.0 technologies, when adopted in tandem with the digital reorganization of production activity, can accelerate production recovery to pre-COVID-19 levels.

Suggested Citation

  • Cugno, Monica & Castagnoli, Rebecca & Büchi, Giacomo & Pini, Marco, 2022. "Industry 4.0 and production recovery in the covid era," Technovation, Elsevier, vol. 114(C).
    • Handle: RePEc:eee:techno:v:114:y:2022:i:c:s0166497221002248
    DOI: 10.1016/j.technovation.2021.102443
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    2. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).

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