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

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.

Authors

Institutions

Publication Details

Journal
International Journal of Intelligent Enterprise
Published
2025-01-01
DOI
https://doi.org/10.1504/ijie.2025.147695
Primary Topic
Economic and Technological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Ece Acar, Görkem Sarıyer
International Journal of Intelligent Enterprise
Economic and Technological Systems Analysis
article

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

Ece Acar, Görkem Sarıyer
article en

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.

International Journal of Intelligent EnterpriseVol. 12(3/4)
Yaşar University (TR)
Openalex Percentile: Top 75%
Economic and Technological Systems Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Use of machine learning for classifying manufacturing companies based on their digital transformation levels — Ece Acar, Görkem Sarıyer · International Journal of Intelligent Enterprise (2025) | TGRS Research Map | TGRS