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ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to better understand cognitive decision-making algorithms for sustainable manufacturing processes in Industry 4.0. Using and replicating data from Capgemini, Deloitte, McKinsey, Optus Business, and PwC, we performed analyses and made estimates regarding Industry 4.0 levers mapped to the main value drivers (%), current status of smart factory initiatives (%), and transformation management intensity parameters (%). Data were analyzed using structural equation modeling.
JEL codes: E24; J21; J54; J64

Keywords: cognition; decision making; algorithm; Industry 4.0; sustainability

How to cite: Hollowell, Jane Catherine, Boris Kollar, Jaromir Vrbka, and Erika Kovalova (2019). “Cognitive Decision-Making Algorithms for Sustainable Manufacturing Processes in Industry 4.0: Networked, Smart, and Responsive Devices,” Economics, Management, and Financial Markets 14(4): 9–15. doi:10.22381/EMFM14420191

Received 17 August 2019 • Received in revised form 11 December 2019
Accepted 12 December 2019 • Available online 15 December 2019

Jane Catherine Hollowell
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Data-driven Automated Decision-Making
at CLI, Melbourne, Australia
(corresponding author)
Boris Kollar
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Jaromir Vrbka
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Institute of Technology and Business in Ceske Budejovice,
The School of Expertness and Valuation, Czech Republic
Erika Kovalova
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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