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ABSTRACT. I develop a conceptual framework based on a systematic and comprehensive literature review on Internet of Things-based real-time production logistics. Building my argument by drawing on data collected from AMG World, The Boston Consulting Group, Deloitte, KSM, MIT Sloan Management Review, PwC, SME, and teknowlogy, I performed analyses and made estimates regarding top five barriers preventing/slowing smart technology (%), effect of automation on the number and skill level of jobs in manufacturing (%), expectations for artificial intelligence adoption across industries (impact on offerings, %), significance of data and analysis competences in the context of Industry 4.0 (%), and retailers planning to invest in artificial intelligence and Internet of Things technologies (%). The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,200 respondents.
JEL codes: E24; J21; J54; J64

Keywords: big data analytics; Internet of Things; real-time production logistics

How to cite: Gaffney, Malcolm (2020). “Cutting-Edge Process Monitoring and Data Analytics Systems in Internet of Things-based Real-Time Production Logistics,” Journal of Self-Governance and Management Economics 8(1): 100–106. doi:10.22381/JSME8120202

Received 12 January 2020 • Received in revised form 14 March 2020
Accepted 17 March 2020 • Available online 28 March 2020

Malcolm Gaffney
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Artificially Intelligent Algorithmic Systems Research Unit
at AAER, Toronto, Canada

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