ABSTRACT. We develop a conceptual framework based on a systematic and comprehensive literature review on cyber-physical manufacturing systems. Building our argument by drawing on data collected from Capgemini, Microsoft, Omdia, PwC, Software AG, World Economic Forum, we performed analyses and made estimates regarding the link between Internet of Things-enabled sustainability, industrial big data analytics, and deep learning-enabled smart process planning. The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,900 respondents.
JEL Codes: E24; J21; J54; J64

Keywords: Internet of Things; sustainability; cyber-physical system; big data

How to cite: Throne, O., and Lăzăroiu, G. (2020). “Internet of Things-enabled Sustainability, Industrial Big Data Analytics, and Deep Learning-assisted Smart Process Planning in Cyber-Physical Manufacturing Systems,” Economics, Management, and Financial Markets 15(4): 49–58. doi:10.22381/EMFM15420205

Received 2 October 2020 • Received in revised form 11 December 2020
Accepted 12 December 2020 • Available online 14 December 2020