Impact of COVID-19 on Digital Transformation: An Empirical Analysis of Manufacturing Companies


  • Francesca Capo
  • Lorena M. D’Agostino
  • Salvatore Torrisi



data-driven decision making; management practices; digital transformation; institutional logics; COVID-19


Purpose of the paper: This study explores whether and how the restrictions resulting from COVID-19 crisis have affected digital transformation (DT) measured by the adoption of data-driven decision-making (DDD) and structured management (SM) practices.

Methodology: On the basis of an original survey of 102 manufacturing firms located in Lombardy, we explore the DDD and SM practices before and during the lockdown, which began on 8 March 2020. The factors explaining heterogeneous responses to the crisis, namely, institutional logic, firm size, technological sectors, and family business, are also considered.

Findings: We find that during the lockdown, firms suffered a setback in the use of DDD and SM. However, there is a significant heterogeneity in the response across firms. The factors considered in our study poorly explain this heterogeneity in DDD. Meanwhile, all factors, except institutional logic, effectively explain the differences in SM.

Research limits: This study provides a preliminary and descriptive analysis. Further analysis is needed to better identify causality and co-factors. 

Practical implications: DT could be particularly sensitive to crisis, and crisis response varies across different dimensions of DT (i.e. DDD and SM) and types of firms. This implies that a variety of firms may benefit from DT but that DT requires specific managerial attention.

Originality of the study: This study employs an original dataset that sheds new light on how the pandemic has affected DT. It focuses on one of the largest European manufacturing regions which was severely hit by the first wave of the pandemic.


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