Clustering analysis application on Industry 4.0-driven global indexes

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dc.authorscopusid57212228050
dc.authorscopusid43761893400
dc.contributor.authorAnuşlu, M.D.
dc.contributor.authorFirat, S.Ü.
dc.date.accessioned2024-06-13T20:15:55Z
dc.date.available2024-06-13T20:15:55Z
dc.date.issued2019
dc.departmentİstanbul Gedik Üniversitesi
dc.description3rd World Conference on Technology, Innovation and Entrepreneurship, WOCTINE 2019 -- 21 June 2019 through 23 June 2019 -- -- 141488
dc.description.abstractIndustry 4.0 is one of the most important topics in the academia and business world in recent years as a result of digital milestones in innovation area. Industry 4.0 is considered a great revolution in both manufacturing and services sectors. One of the reasons why Industry 4.0 is described as a revolution is the search for new solutions that unappeared before, to the challenges associated with energy, resources, environment, social and economic impacts by using modern technologies to ensure sustainable prosperity. Another reason is the use of modern technologies such as digital chains, smart systems and industrial internet to accelerate innovation as a result of faster implementation of new business models. The other one, is Industry 4.0 lighten the load of current challenges such as shorter product lifecycles, higher product complexity, and global supply chains for manufacturers in order to make the companies more flexible and responsive to business trends. According to global index scores in several areas as economic, environmental, sustainability, innovation etc. that published by international organizations, the positions of countries relative to other countries can be analyzed. Countries can evaluate their current status according to their index scores and have the opportunity to develop strategies for the performance level that they targeted. The aim of this study is to group countries within the scope of significant impact areas of Industry 4.0 by using Global Innovation Index, Sustainable Development Goals Index, Logistics Performance Index and Environmental Performance Index. By using the global indices mentioned above, countries are grouped and evaluated by using Clustering Analysis from data mining methods. © 2019 The Authors. Published by Elsevier B.V.
dc.description.sponsorshipFirat University Scientific Research Projects Management Unit, FÃœBAP
dc.description.sponsorshipThis work was supported by Scientific Research Projects Coordination Unit of Istanbul Gedik University.
dc.identifier.doi10.1016/j.procs.2019.09.037
dc.identifier.endpage152
dc.identifier.issn1877-0509
dc.identifier.scopus2-s2.0-85076259101
dc.identifier.scopusqualityN/A
dc.identifier.startpage145
dc.identifier.urihttps://doi.org/10.1016/j.procs.2019.09.037
dc.identifier.urihttps://hdl.handle.net/11501/958
dc.identifier.volume158
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofProcedia Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectClustering Analysis
dc.subjectEnvironmental Performance Index
dc.subjectGlobal Innovation Index
dc.subjectIndustry 4.0
dc.subjectSustainable Development Goals Index
dc.subjectData mining
dc.subjectEconomic and social effects
dc.subjectEngineering research
dc.subjectEnvironmental management
dc.subjectIndustry 4.0
dc.subjectLife cycle
dc.subjectPlanning
dc.subjectSupply chains
dc.subjectClustering analysis
dc.subjectEnvironmental performance indices
dc.subjectFaster implementation
dc.subjectGlobal innovation
dc.subjectInternational organizations
dc.subjectPerformance indices
dc.subjectProduct life cycles
dc.subjectSocial and economic impacts
dc.subjectSustainable development
dc.titleClustering analysis application on Industry 4.0-driven global indexes
dc.typeConference Object

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