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ABSTRACT. This article presents an empirical study carried out to evaluate and analyze Industry 4.0 production networks. Building my argument by drawing on data collected from AMG World, BI Intelligence, Deloitte, Harvard Business Review, PwC, SME, and teknowlogy, I performed analyses and made estimates regarding top five specific features of digital technology most attractive to companies (%), application of typical Internet of Things-related technologies (%), and machine learning areas having the greatest impact on organizations (%). Data collected from 4,300 respondents are tested against the research model by using structural equation modeling.
JEL codes: E24; J21; J54; J64

Keywords: Industry 4.0; cyber-physical system; real-time big data analytics

How to cite: Horick, Colleen (2020). “Industry 4.0 Production Networks: Cyber-Physical System-based Smart Factories, Real-Time Big Data Analytics, and Sustainable Product Lifecycle Management,” Journal of Self-Governance and Management Economics 8(1): 107–113. doi:10.22381/JSME8120203

Received 9 January 2020 • Received in revised form 18 March 2020
Accepted 19 March 2020 • Available online 28 March 2020

Colleen Horick
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Artificial Intelligence Systems Laboratory
at ISBDA, Dublin, Ireland

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