To read this content please select one of the options below:

Industry 4.0 transition: a systematic literature review combining the absorptive capacity theory and the data–information–knowledge hierarchy

Lorenzo Ardito (Department of Mechanics, Mathematics and Management, Politecnico di Bari, Bari, Italy)
Roberto Cerchione (Department of Engineering, Università degli Studi di Napoli Parthenope, Napoli, Italy)
Erica Mazzola (Dipartimento di Ingegneria, Università degli Studi di Palermo, Palermo, Italy)
Elisabetta Raguseo (Department of Management and Production Engineering, Politecnico di Torino, Turin, Italy)

Journal of Knowledge Management

ISSN: 1367-3270

Article publication date: 17 December 2021

Issue publication date: 23 September 2022




The effect of the transition toward digital technologies on today’s businesses (i.e. Industry 4.0 transition) is becoming increasingly relevant, and the number of studies that have examined this phenomenon has grown rapidly. However, systematizing the existing findings is still a challenge, from both a theoretical and a managerial point of view. In such a setting, the knowledge management (KM) discipline can provide guidance to address such a gap. Indeed, the implementation of fundamental digital technologies is reshaping how firms manage knowledge. Thus, this study aims to critically review the existing literature on Industry 4.0 from a KM perspective.


First, the authors defined a structuring framework to highlight the role of Industry 4.0 transition along with absorptive capacity (ACAP) processes (acquisition, assimilation, transformation and exploitation), while specifying what is being managed, that is data, information and/or (actual) knowledge, according to the data-information-knowledge (DIK) hierarchy. The authors then followed the systematic literature review methodology, which involves the use of explicit criteria to select publications to review and outline the stages a process has to follow to provide a transparent and replicable review and to analyze the existing literature according to the theoretical framework. This procedure yielded a final list of 150 papers.


By providing a clear picture of what scholars have studied so far on Industry 4.0 transition, in terms of KM, this literature review highlights that among all the studied digital technologies, the big data analytics technology is the one that has been explored the most in each phase of the ACAP process. A constructive body of research has also emerged in recent years around the role played by the internet of things, especially to explain the acquisition of data. On the other hand, some digital technologies, such as cyber security and smart manufacturing, have largely remained unaddressed. An explanation of the role of these technologies has been provided, from a KM perspective, together with the business implications.


This study is one of the first attempts to revise the literature on Industry 4.0 transition from a KM perspective, and it proposes a novel framework to read existing studies and on which to base new ones. Furthermore, the synthesis makes two main contributions. First, it provides a clear picture of the different digital technologies that support the four ACAP phases in relation to the DIK hierarchy. Accordingly, these results can emphasize what the literature has looked at so far, as well as which digital technologies have gained the most attention and their impacts in terms of KM. Second, the synthesis provides prescriptive considerations on the development of future research avenues, according to the proposed research framework.



This work was supported by the Italian Ministry of Education, University and Research under the Program “Department of Excellence”, Legge 232/2016 (Grant No. CUP – D94I18000260001) and the Piano Operativo Nazionale (PON) “Ricerca e Innovazione” 2014-2020 AIM – Attrazione e Mobilità Internazionale.


Ardito, L., Cerchione, R., Mazzola, E. and Raguseo, E. (2022), "Industry 4.0 transition: a systematic literature review combining the absorptive capacity theory and the data–information–knowledge hierarchy", Journal of Knowledge Management, Vol. 26 No. 9, pp. 2222-2254.



Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

Related articles