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ABSTRACT. Despite the relevance of artificial intelligence data-driven Internet of Things systems, real-time advanced analytics, and cyber-physical production networks in sustainable smart manufacturing, only limited research has been conducted on this topic. Using and replicating data from BCG, Capgemini, CompTIA, Deloitte, Eclipse Foundation, The Economist Intelligence Unit, MHI, PAC, Siemens, SME, Software AG, and we.CONECT, we performed analyses and made estimates regarding big data-driven decision-making processes in cyber-physical system-based smart factories. The results of a study based on data collected from 4,800 respondents provide support for our research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: Internet of Things; smart manufacturing; artificial intelligence

How to cite: Durana, P., Perkins, N., and Valaskova, K. (2021). “Artificial Intelligence Data-driven Internet of Things Systems, Real-Time Advanced Analytics, and Cyber-Physical Production Networks in Sustainable Smart Manufacturing,” Economics, Management, and Financial Markets 16(1): 20–30. doi: 10.22381/emfm16120212.

Received 12 January 2021 • Received in revised form 11 March 2021
Accepted 14 March 2021 • Available online 20 March 2021

Pavol Durana
This email address is being protected from spambots. You need JavaScript enabled to view it.
Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Neil Perkins
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The Big Data-driven Smart Manufacturing Laboratory
at AAER, San Francisco, CA, USA
(corresponding author)
Katarina Valaskova
This email address is being protected from spambots. You need JavaScript enabled to view it.
Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic

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