Development of collective intelligence in the enterprises’ digital transformation
- Details
- Category: Content №3 2023
- Last Updated on 27 June 2023
- Published on 30 November -0001
- Hits: 2546
Authors:
H.Y.Ostrovska*, orcid.org/0000-0002-9318-2258, Ternopil Ivan Pul’uj National Technical University, Ternopil, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
I.V.Strutynska, orcid.org/0000-0001-5667-6569, Ternopil Ivan Pul’uj National Technical University, Ternopil, Ukraine, е-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
R.Р.Sherstiuk, orcid.org/0000-0001-6253-9421, Ternopil Ivan Pul’uj National Technical University, Ternopil, Ukraine, е-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
О.M.Pietukhova, orcid.org/0000-0002-4020-6949, National University of Food Technologies, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
I.А.Yasinetska, orcid.org/0000-0002-2996-4394, Podillya State Agrarian and Engineering University, Kamianets-Podilskyi, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (3): 157 - 163
https://doi.org/10.33271/nvngu/2023-3/157
Abstract:
Purpose. Theoretical and methodical foundations deepening and projecting concerning business structures collective intelligence recommendations improvement based on human capital digital literacy in enterprises’ digital transformation.
Methodology. The presented scientific research results were obtained using general and special cognition methods: morphological analysis, generalization and scientific abstraction; dialectical cognition, deduction and induction; system and cluster data analysis by Data Mining means; grouping and systematization; graphical and tabular presentation; abstract-logical method; econometric trend formation method.
Findings. We deployed a science position regarding the progress of the enterprises collective intellect based on one of the main components – human capital computer knowledge. Emphasis is placed on anthropocentricity, which plays a decisive role in the business structures’ innovative activity. Our study argued the demand for joint intellect technologies in the enterprises’ cyber conversion. We highlighted the mass cooperation fundamental principles, which are based on a new management paradigm and proposed a new understanding of the categories essence: “digital competence”, “digital competency” and “knowledge culture”. Our research revealed computer knowledge concept subject status as an imperative for the joint intellect improvement. We analyzed the “EU digital competencе frameworks”; proposed the computer literacy framework for the enterprises’ staff capital; determined the primary role of education in the context of the society digital proficiency formation.
Originality. We improved the science and methodical approach to determining company’s staff capital computer literacy level based on the analysis of “EU digital competencе frameworks”. The proposed method makes it possible to determine the cyber maturity potential and readiness for computer technologies implementation into business practice in order to ensure its development.
Practical value. The results of authors’ science projects and practical recommendations contribute to the effective use and development of the business organizations’ collective intelligence and their network associations in the conditions of cybernated conversion.
Keywords: innovative development, human capital, collective intelligence, digital transformation, digital competency, DigComp 2.2, digital literacy
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