Use of machine learning for classifying manufacturing companies based on their digital transformation levels

dc.contributor.author Ece Acar
dc.contributor.author Gorkem Sariyer
dc.contributor.author Sariyer, Gorkem
dc.contributor.author Acar, Ece
dc.date.accessioned 2025-10-06T17:48:45Z
dc.date.issued 2025
dc.description.abstract The transformative role of machine learning technology in promoting technological innovation leading sustainable growth is becoming increasingly significant in today’s business era. In this study we implemented machine learning technology to classify the companies according to their digital transformation levels. We used manufacturing companies in Borsa Istanbul (BIST) index as the sample. We constructed a digital transformation level index based on text analysis to measure the frequency of keywords related to digital transformation. We used the sampled companies’ financial sustainability corporate governance performance and research & development (R&D) expenditures to model their digitalisation levels. We observed that between the various machine learning algorithms with 82% accuracy Random Forest outperformed the others. We also showed that while R&D expenditure was the most important feature financial performance-related features were also significant. Thus we concluded that companies with higher financial performances especially those making more expenditures for R&D activities have higher digital transformation levels. © 2025 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1504/IJIE.2025.147695
dc.identifier.issn 17453240, 17453232
dc.identifier.issn 1745-3232
dc.identifier.issn 1745-3240
dc.identifier.scopus 2-s2.0-105011764638
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011764638&doi=10.1504%2FIJIE.2025.147695&partnerID=40&md5=2cba63eddd6fe50b0019467725e1d688
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/8087
dc.identifier.uri https://doi.org/10.1504/IJIE.2025.147695
dc.language.iso English
dc.publisher Inderscience Publishers
dc.relation.ispartof International Journal of Intelligent Enterprise
dc.rights info:eu-repo/semantics/closedAccess
dc.source International Journal of Intelligent Enterprise
dc.subject Classification, Digital Transformation, Financial Performance, Machine Learning, R&d Expenditure
dc.subject Classification
dc.subject Machine Learning
dc.subject R&D Expenditure
dc.subject Digital Transformation
dc.subject Financial Performance
dc.title Use of machine learning for classifying manufacturing companies based on their digital transformation levels
dc.type Article
dspace.entity.type Publication
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gdc.author.scopusid 57189867008
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gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department
gdc.description.departmenttemp [Acar E.] Department of Business Administration, Faculty of Business, Yasar University, Izmir, Turkey; [Sariyer G.] Department of Business Administration, Faculty of Business, Yasar University, Izmir, Turkey
gdc.description.endpage 320
gdc.description.issue 3-4
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
gdc.description.startpage 305
gdc.description.volume 12
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gdc.virtual.author Acar, Özen Ece
oaire.citation.endPage 320
oaire.citation.startPage 305
person.identifier.scopus-author-id Acar- Ece (36573211300), Sariyer- Gorkem (57189867008)
publicationissue.issueNumber 3-4
publicationvolume.volumeNumber 12
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