ABSTRACT. The aim of this paper is to synthesize and analyze existing evidence on sustainable smart manufacturing. Using and replicating data from Accenture, Bain, Capgemini, CompTIA, IW Custom Research, Kronos, McKinsey, Microsoft, PAC, PwC, and Software AG, we performed analyses and made estimates regarding the link between business process optimization, cognitive decision-making algorithms, and artificial intelligence data-driven Internet of Things systems. Data were analyzed using structural equation modeling.
JEL codes: E24; J21; J54; J64
Keywords: artificial intelligence; Internet of Things; sustainable smart manufacturing
How to cite: Williams, A., Suler, P., and Vrbka, J. (2020). “Business Process Optimization, Cognitive Decision-Making Algorithms, and Artificial Intelligence Data-driven Internet of Things Systems in Sustainable Smart Manufacturing,” Journal of Self-Governance and Management Economics 8(4): 39–48. doi:10.22381/JSME8420204
Received 6 September 2020 • Received in revised form 11 December 2020
Accepted 15 December 2020 • Available online 18 December 2020
{slider Authors'contacts}
Arthur Williams
arthur.williams@aa-er.org
The Cyber-Physical Smart Manufacturing Systems
Research Unit at AAER, Boston, MA, USA
(corresponding author)
Petr Suler
petr.suler@seznam.cz
The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic
Jaromir Vrbka
vrbka@mail.vstecb.cz
The Institute of Technology and Business in Ceske Budejovice,
The School of Expertness and Valuation, Czech Republic