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ABSTRACT. Despite the relevance of smart manufacturing technologies, only limited research has been conducted on this topic. Using and replicating data from BI Intelligence, Capgemini, Deloitte, eMarketer, Forbes, PwC, Statista, and Zebra Technologies, we performed analyses and made estimates regarding industries targeted by machine learning application developers (%), the main areas of interest for manufacturers within Industry 4.0 (%), retailers planning to invest in artificial intelligence and Internet of Things technologies by 2021 (%), and benefits of implementing artificial intelligence (%). Data collected from 4,400 respondents are tested against the research model by using structural equation modeling.
JEL codes: E24; J21; J54; J64

Keywords: smart manufacturing; data-driven algorithm; sustainable value creation

How to cite: Whittle, Therese, Elena Gregova, Ivana Podhorska, and Zuzana Rowland (2019). “Smart Manufacturing Technologies: Data-driven Algorithms in Production Planning, Sustainable Value Creation, and Operational Performance Improvement,” Economics, Management, and Financial Markets 14(2): 52–57. doi:10.22381/EMFM14220193

Received 10 December 2018 • Received in revised form 10 May 2019
Accepted 12 May 2019 • Available online 1 June 2019

Therese Whittle
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The Social Analytics Laboratory at CSA,
Birmingham, England
(corresponding author)
Elena Gregova
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Department of Economics,
Faculty of Operation and Economics
of Transport and Communications,
University of Zilina, Zilina, Slovak Republic
Ivana Podhorska
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Department of Economics,
Faculty of Operation and Economics
of Transport and Communications,
University of Zilina, Zilina, Slovak Republic
Zuzana Rowland
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The Institute of Technology and Business in Ceske Budejovice,
The School of Expertness and Valuation, Czech Republic

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