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Strategic key elements in big data analytics as driving forces of IoT manufacturing value creation: A challenge for research framework

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dc.title Strategic key elements in big data analytics as driving forces of IoT manufacturing value creation: A challenge for research framework en
dc.contributor.author Rajnoha, Rastislav
dc.contributor.author Hadač, Jakub
dc.relation.ispartof IEEE Transactions on Engineering Management
dc.identifier.issn 0018-9391 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2021
dc.type article
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.identifier.doi 10.1109/TEM.2021.3113502
dc.relation.uri https://ieeexplore.ieee.org/document/9577226
dc.subject Big Data analytics (BDA) en
dc.subject business en
dc.subject business intelligence en
dc.subject business intelligence (BI) en
dc.subject business performance en
dc.subject cyber-physical production systems en
dc.subject data visualization en
dc.subject databases en
dc.subject Industry 4.0 en
dc.subject intelligent manufacturing en
dc.subject Internet of Things (IoT) en
dc.subject knowledge information systems en
dc.subject knowledge management en
dc.subject manufacturing en
dc.subject planning and scheduling en
dc.subject real-time systems en
dc.subject tools en
dc.subject value creation en
dc.description.abstract Big Data (BD)-driven business intelligence (BI) is considered to be a new development stage within industrial engineering management to achieve higher business value creation. The article provides extensive research of BD-driven approaches to identify strategic knowledge and value-creating components within Internet of Things (IoT) manufacturing. Due to previous research studies focused mostly on partial solutions and lack a holistic view, this article topic is still far from being sufficiently explored and resolved. The article presents the results of an extensive research study of contemporary professional literature with a specific aim to provide a more holistic and systematical view on the current state and future trends in this issue. To solve this high complex research problem, both quantitative and qualitative research methodology approaches are used. The article is primarily based on a systematic literature review covering 187 essential and 36 additional current research papers within the Web of Science and Scopus database from 2012 to the present. Research findings identify the seven key strategic elements determining that Big Data analytics (BDA) can become a real and tremendous business value creation driver within IoT intelligent manufacturing. These research results provide important conclusions and implications for challenging future investigations into BDA and BI systems in the context of advancing the Industry 4.0 revolution. In conclusion, we propose a final suggestion in the form of a strategic future research chain from IoT through BDA to value creation based on BD intelligence within IoT manufacturing, whereas seven strategic elements might play a crucial. Author en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1010643
utb.identifier.obdid 43882847
utb.identifier.scopus 2-s2.0-85118249029
utb.identifier.wok 000732665900001
utb.identifier.coden IEEMA
utb.source j-scopus
dc.date.accessioned 2021-11-09T12:16:21Z
dc.date.available 2021-11-09T12:16:21Z
dc.description.sponsorship Internal Grant Agency of Tomas Bata University in Zlin [IGA/FaME/2020/009-Process]
dc.rights Attribution 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Rajnoha, Rastislav
utb.contributor.internalauthor Hadač, Jakub
utb.fulltext.affiliation Rastislav Rajnoha https://orcid.org/0000-0002-9332-9926 and Jakub Hadač
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the Internal Grant Agency of Tomas Bata University in Zlín under Grant IGA/FaME/2020/009-Process optimization and knowledge information support in Industry 4.0 companies.
utb.wos.affiliation [Rajnoha, Rastislav; Hadac, Jakub] Tomas Bata Univ Zlin, Fac Management & Econ, Zlin 76001, Czech Republic
utb.scopus.affiliation Tomas Bata University in Zlín, Faculty of Management and Economics, Zlín 760 01 Czech Republic (e-mail: rajnoha@utb.cz).; Tomas Bata University in Zlín, Faculty of Management and Economics, Zlín 760 01 Czech Republic (e-mail: hadac@utb.cz).
utb.fulltext.projects IGA/FaME/2020/009
utb.fulltext.faculty -
utb.fulltext.ou -
utb.identifier.jel -
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