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Enabling the circular economy in the digital transformation era: evidence from an emerging country.
- Source :
- Kybernetes; 2024, Vol. 53 Issue 2, p779-802, 24p
- Publication Year :
- 2024
-
Abstract
- Purpose: Recently, the concept of the circular economy (CE) has witnessed significant momentum in academic and professional circles. However, there is a dearth of research that studies the enabling factors of the CE in the era of digital transformation. The existing research aimed to identify the impact of Industry 4.0 readiness on the CE in manufacturing firms operating in Jordan, as well as to identify the mediating role of the industrial Internet of things and big data analytics. Design/methodology/approach: For this work objectives, 380 questionnaires were analyzed. Convergent validity and discriminant validity tests were performed through partial least squares-structural equation modelling (PLS-SEM) in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyze the data and then hypothesis testing was performed. Findings: The results indicate that Industry 4.0 readiness, industrial Internet of things (IIoT) and big data analytics positively enable CE, also the IIoT and big data analytics positively mediate the nexus between Industry 4.0 readiness and CE. Practical implications: This study promotes the idea of focusing on Industry 4.0 readiness to enhance CE in the Jordanian manufacturing sector and knowing the effect of IIoT and big data analytics in this relationship. Originality/value: This research developed a theoretical model to understand how Industry 4.0 readiness might enhance the CE in manufacturing firms by invoking the IIoT and big data analytics as mediating constructs in the relationship between Industry 4.0 readiness and CE. This paper offers new theoretical and practical contributions that add value to industry 4.0 and CE literature by testing these constructs' mediation models in the manufacturing sector. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0368492X
- Volume :
- 53
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Kybernetes
- Publication Type :
- Periodical
- Accession number :
- 175021083
- Full Text :
- https://doi.org/10.1108/K-02-2023-0297