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dc.contributor.authorOzemre, M.
dc.contributor.authorKabadurmus, O.
dc.date.accessioned2021-01-25T20:48:02Z
dc.date.available2021-01-25T20:48:02Z
dc.date.issued2020
dc.identifier10.1108/JEIM-08-2019-0222
dc.identifier.issn17410398
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85085352010&doi=10.1108%2fJEIM-08-2019-0222&partnerID=40&md5=03c54c7745c0c9a18ec4bcabff0c341e
dc.identifier.urihttps://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9704
dc.description.abstractPurpose: The purpose of this paper is to present a novel framework for strategic decision making using Big Data Analytics (BDA) methodology. Design/methodology/approach: In this study, two different machine learning algorithms, Random Forest (RF) and Arti
dc.language.isoEnglish
dc.publisherJournal of Enterprise Information Management
dc.titleA big data analytics based methodology for strategic decision making
dc.typeArticle
dc.description.affiliationsBIMAR Information Technology Services, Izmir, Turkey; Department of International Logistics Management, Yasar University, Izmir, Turkey


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