A configuration approach to reduce the risk of COVID-19 employees infection in the manufacturing firms: The role of machine automatization

Jorge Heredia Pérez, Cristian Geldes, Alejandro Flores, Walter Heredia, Felix M. Carbajal Gamarra, Luisa Miranda Obando

Research output: Contribution to journalArticle in a journalpeer-review


Does automation adoption mitigate the COVID-19 infection rate of employees? What resources and internal and external factors need to be configured with automation to mitigate COVID-19 contagion from employees successfully? According to the type of automation. What resources efficiently complement to mitigate the contagion rate from employers? From a fuzzy- set qualitative comparative analysis (fsQCA) approach, we analyzed 759 manufacturing firms in Finland, drawn from the World Bank 2020 Enterprise Survey; this study addresses the multiple configurations that drive pandemic risk mitigation and management. We find that configurations under automation reduce the risk of employee infection. Our results show the critical role of automation in employee safety. We argue that access to government support and the development of technological innovation are necessary conditions for implementing measures to prevent and mitigate the risk of contagion in the employee. In addition, the first configurationstates that manufacturing firms employing soft automation can successfully mitigate employee exposure. The second configuration states that high human resource flexibility successfully complements firms with complex automation to achieve high mitigation. Finally, the third configuration shows those manufacturing firms that employ low-tech automation (manual processes); in this manner, digitization enables successfully mitigating pandemic contagion.Moreover, it suggests recommendations for policymakers and managers.
Original languageEnglish
Pages (from-to)785-792
Number of pages8
JournalInternational Journal of Technology
Issue number4
StatePublished - 7 Oct 2022

Bibliographical note

Publisher Copyright:
© 2022,International Journal of Technology. All Rights Reserved.


  • Covid-19
  • Digitalization
  • Fsqca
  • Industry 4.0
  • Machine automatization


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