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ABSTRACT. We draw on a substantial body of theoretical and empirical research on big data-driven decision-making processes, real-time advanced analytics, and cyber-physical production networks in Industry 4.0-based manufacturing systems, and to explore this, we inspected, used, and replicated survey data from BDV, Capgemini, Deloitte, McKinsey, MHI, and Siemens, performing analyses and making estimates regarding how a smart production planning and control system harnesses Internet of Things sensing networks and Internet of Things-based real-time production logistics by use of industrial big data analytics and machine learning algorithms. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: cyber-physical production network; smart manufacturing; big data

How to cite: Rogers, S., and Kalinova, E. (2021). “Big Data-driven Decision-Making Processes, Real-Time Advanced Analytics, and Cyber-Physical Production Networks in Industry 4.0-based Manufacturing Systems,” Economics, Management, and Financial Markets 16(4): 84–97. doi: 10.22381/emfm16420216.

Received 17 March 2021 • Received in revised form 12 December 2021
Accepted 15 December 2021 • Available online 20 December 2021

Sarah Rogers
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Labor Institute,
New York City, NY, USA
(corresponding author)
Eva Kalinova
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The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic

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