Modeling the impact of industry 4.0 base technologies on the development of organizational learning capabilities

Guilherme Luz Tortorella (), Flavio S. Fogliatto (), Michel J. Anzanello (), Alejandro Mac Cawley Vergara (), Roberto Vassolo () and Jose Arturo Garza-Reyes ()
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Guilherme Luz Tortorella: The University of Melbourne
Flavio S. Fogliatto: Universidade Federal do Rio Grande do Sul
Michel J. Anzanello: Universidade Federal do Rio Grande do Sul
Alejandro Mac Cawley Vergara: Pontifícia Universidade Católica
Roberto Vassolo: Universidad Austral
Jose Arturo Garza-Reyes: University of Derby

Operations Management Research, 2023, vol. 16, issue 3, No 3, 1104 pages

Abstract: Abstract In this paper, we examine the impact of adopting Industry 4.0 (I4.0) base technologies on the development of seven learning dimensions used as proxies for organization learning capabilities. We conducted a grounded theory approach in which 129 practitioners from different manufacturing companies were surveyed, and their responses analyzed through multivariate techniques. Findings allowed us to raise a theoretical framework for explaining learning development in organizations undergoing I4.0 adoption. We identified three clusters of adopters: (i) beginners, (ii) in-transition, and (iii) advanced. We found an ascending learning trend in clusters (i) and (iii) and a stationary learning pattern in (ii). Our study advances the understanding of how learning capabilities are affected as organizations advance I4.0 adoption. Our findings also gauge expectations regarding the effects of I4.0 base technologies’ adoption on learning capabilities, helping academics and practitioners anticipate potential issues and develop countermeasures accordingly.

Keywords: Industry 4.0; Organizational learning; Learning profiles; I4.0 base technologies; Empirical study (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12063-022-00329-w

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