Industrial Process Automation and Business Technology Management: A Cobb–Douglas Elasticity Perspective
Introduction. Technological advances and the emergence of artificial intelligence have contributed to the growing importance of industrial process automation. Furthermore, automation is a key driver of Industry 4.0, impacting industrial productivity and growth. A reliability-based approach is propos...
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| Date: | 2025 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
Dr. Viktor Koval
2025
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| Subjects: | |
| Online Access: | https://ees-journal.com/index.php/journal/article/view/315 |
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| Journal Title: | Economics Ecology Socium |
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Economics Ecology Socium| Summary: | Introduction. Technological advances and the emergence of artificial intelligence have contributed to the growing importance of industrial process automation. Furthermore, automation is a key driver of Industry 4.0, impacting industrial productivity and growth. A reliability-based approach is proposed to assess the impact of automation that quantitatively links technology investments to economic indicators, particularly the Cobb-Douglas production function.
Aim and tasks. This study aims to demonstrate a direct link between automation and industrial production using the Cobb-Douglas model. This model bridges the gap between classical production functions and modern technologies through linear and log-linear models, allowing for a more accurate assessment of the impact of automation on industry.
Results. The study found that adding one robot per 10,000 employees corresponds to a 0.055 percentage point increase in the industrial share. After applying the log-linear (Cobb-Douglas) specification, a result/coefficient of 0.53 was obtained, meaning that the industrial share would increase by 0.53% if only a 1% increase in robot deployment were realised. This result confirms that automation is a significant production factor with a proportional effect. The analysis showed that elasticity-based models can capture industrial dynamics more realistically than linear models. The empirical results provide a measurable basis for positioning automation alongside traditional factors, such as labour and capital. The comparative model approach provides evidence for the suitability of the Cobb-Douglas forms in contemporary industrial research, and the empirical findings lay the foundation for further large-scale research with broader datasets.
Conclusions. Automation contributes to the strategic development of industrial competitiveness, and its effectiveness is achieved only in conjunction with innovation, digitalisation, education, and support from institutional and economic environments. Automation increases added value, as confirmed by the Cobb-Douglas model. However, sustainable development also requires human capital, innovation, and effective environmental policies. A comprehensive approach will allow for an objective assessment of the industry's potential and the development of a sustainable development strategy. |
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