Development of collective intelligence in the enterprises’ digital transformation
/ 0
- Details
- Category: Content №3 2023
- Last Updated on 27 June 2023
- Published on 30 November -0001
- Hits: 2504
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
References.
1. Pór, G. (2021). Collective Intelligence Today. Retrieved from https://blogofcollectiveintelligence.com/author/coevolvingwithyou/.
2. Naplyokov, Y. (2021). Application of collective emotional intelligence to improve public administration in conditions of a dynamic environment. Economy and the state, 2(18), 16-25. https//doi.org/10.46922/2306-6806-2021-2-2 (18)-16-25.
3. Gloor, P. (2017). Swarm Leadership and the Collective Mind: Using Collaborative Innovation Networks to Build a Better Business. Bingley: Emerald Publishing. https://doi.org/10.1108/9781787142008.
4. Garreta-Domingo, M., Sloep, P. B., Hérnandez-Leo, D., & Mor, Yi. (2018). Design for collective intelligence: pop-up communities in MOOCs. AI & SOCIETY, 33, 1, 91-100. https://doi.org/10.1007/s00146-017-0745-0.
5. Verhulst, S. G. (2018). Where and when AI and CI meet: exploring the intersection of artificial and collective intelligence towards the goal of innovating how we govern. AI & SOCIETY, 33, 2, 293-297. https://doi.org/10.1007/s00146-018-0830-z.
6. Weng, S. S., Yang, M. H., & Hsiao, P. I. (2018). A factor-identifying study of the user-perceived value of collective intelligence based on online social networks. Internet Research, 28, 3, 696-715. https://doi.org/10.1108/intr-03-2017-0103.339.
7. Woolley, A., Aggarwa, I., & Malone, T. (2015). Collective intelligence and group performance. Current Directions in Psychological Science, 24, 6, 420-424. https://doi.org/10.1177/0963721415599543.
8. Ostrovska, H., Tsikh, H., Strutynska, I., Kinash, I., Pietukhova, O., Golovnya, О., & Shehynska, N. (2021). Building an effective model of intelligent entrepreneurship development in digital economy. Eastern-European Journal of Enterprise Technologies, 6(13(114)), 49-59. https://doi.org/10.15587/1729-4061.2021.244916.
9. Strutynska, I. (2019). Digital literacy of human capital business structures. Economic journal of Lesya Ukrainka Volyn National University, 4, 20, 93-100. https://doi.org/10.29038/2411-4014-2019-04-93-100.
10. Kuibida, V. S., Petroye, O. M., Fedulova, L. I., & Androschuk, H. O. (2019). Digital competences as a condition for the human capital quality formation. Collection of scientific works of the State Administration National Academy under the President of Ukraine, 1, 118-133. Retrieved from http://nbuv.gov.ua/UJRN/znpnadu_2019_1_16.
11. Ostrovska, H., Andrushkiv, B., Tsikh, H., Boichyk, I., & Stavnycha, N. (2022). Formation of priorities for the development of intellectual potential in the conditions of establishing a knowledge-based economy. Financial and credit activities: problems of theory and practice, 1(42), 415-427. https://doi.org/10.55643/fcaptp.1.42.2022.3561.
12. Kolot, A. (2021). Social and labor reality – XXI: philosophy of formation, opportunities and challenges. Economy of Ukraine, 2, 3-31. https://doi.org/10.15407/economyukr.2021.02.003.
13. Digital Competences Framework (DigComp 2.2) update published
(2022). Retrieved from https://ec.europa.eu/social/main.jsp?langId=en&catId=89&newsId=10193&furtherNews=yes.
14. Digital Competence Framework for Austria (2021). Retrieved from https://www.bmf.gv.at/dam/jcr:d0376afe-8fa8-4dfd-86d6-1f86fe367b1b/2021-07_DigComp_2.2_Digitales%20Kompetenzmodell_EN_barrierefrei.pdf.
15. Polowczyk, J. (2016). New business models based on internet. Economics and management organization, 2(22), 209-214.
Newer news items:
- Crowdsourcing for business strategy and sustainability: a partial least square structural equation model - 27/06/2023 03:35
- Ukraine labour potential modelling based on using the theory of unclear logic - 27/06/2023 03:35
- Analysis of motivation determinants in the implementation of online training of future managers at state universities - 27/06/2023 03:35
- Financial and credit support of market-oriented management of transport engineering enterprises - 27/06/2023 03:35
Older news items:
- Fundamental imperatives of eliminating uncertainty on the basis of monitoring the activity of the iron ore enterprise - 27/06/2023 03:35
- Experimental research on muffle furnace dynamic properties - 27/06/2023 03:35
- Evaluation and control of data relevance in information systems of the transport industry management - 27/06/2023 03:35
- Optimization of track distribution of industrial railway stations between car designations - 27/06/2023 03:35
- Methodology for assessing the influence of external and internal factors on the development of the digital economy - 27/06/2023 03:35
- Homomorphic filtering in digital multichannel image processing - 27/06/2023 03:35
- Economic aspects of assessment and marketing of carbon emissions by enterprises based on the principles of sustainable development - 27/06/2023 03:35
- Problem issues regarding legal liability for environmental offenses in Ukraine - 27/06/2023 03:35
- Mathematical model of air flow movement in a motorized filter respirator - 27/06/2023 03:35
- Methods for improving accounting and analytical support of enterprises in order to protect the environment - 27/06/2023 03:35
Archive