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ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore product decision-making information systems, real-time sensor networks, and artificial intelligence-driven big data analytics in sustainable Industry 4.0. Using and replicating data from BCG, BDO, Capgemini, Management Events, PAC, and PwC, we performed analyses and made estimates regarding production network performance. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: sustainable Industry 4.0; artificial intelligence; big data analytics

How to cite: Novak, A., Bennett, D., and Kliestik, T. (2021). “Product Decision-Making Information Systems, Real-Time Sensor Networks, and Artificial Intelligence-driven Big Data Analytics in Sustainable Industry 4.0,” Economics, Management, and Financial Markets 16(2): 62–72. doi: 10.22381/emfm16220213.

Received 14 January 2021 • Received in revised form 15 June 2021
Accepted 19 June 2021 • Available online 25 June 2021

Andrej Novak
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Faculty of Operation and Economics
of Transport and Communications,
Department of Air Transport,
University of Zilina, Zilina, Slovak Republic
Daniel Bennett
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The Sharing Economy Platforms Laboratory
at CLI, Montreal, Canada
(corresponding author)
Tomas Kliestik
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic

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