Industry 4.0 and production recovery in the covid era

Monica Cugno, Rebecca Castagnoli, Giacomo Büchi and Marco Pini

Technovation, 2022, vol. 114, issue C

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.

Keywords: COVID-19; Industry 4.0; SME; Manufacturing; Production recovery; Mediator; Digital reorganization; Classical reorganization (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497221002248
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:114:y:2022:i:c:s0166497221002248

DOI: 10.1016/j.technovation.2021.102443

Access Statistics for this article

Technovation is currently edited by Jonathan Linton

More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().