Preview

Vestnik of the Plekhanov Russian University of Economics

Advanced search

Barriers in Proliferating Digital Technologies at Russian Companies: Causes and Effects

https://doi.org/10.21686/2413-2829-2024-6-33-45

Abstract

The article analyzes work of enterprises dealing with digital technology introduction and use of such technologies in production and managerial processes, at the same time it studies reasons for this technology rejection. Topicality of the research is envisaged by high interest of Russian companies in using digital technologies in management and production processes. The rising popularity of digital technologies, in particular AI is based on searching for alternative methods of business-process optimization, raising efficiency and competitiveness of enterprises. It should be pointed out that in creation and introduction of digital technologies enterprises face various difficulties, including fragmentation and non-coordination of ideas about the essence of these technologies, opportunities of their application and control. The authors provide recommendations for enterprises on overcoming barriers in introduction of digital technologies, available at the time of the research, based on comprehensive analysis of strategies of their use with regard to concrete needs and characteristics of the organization. Theoretical and methodological foundation of the research was formed by achievements of the managerial approach to innovation introduction. Methods of expert and comparative analysis were used in the research. The information base of the project was built by works dealing with current trends and practices of management in view of digital transformation. As a result a systematized picture of enterprise functioning was developed in the context of overcoming barriers in introducing digital technologies and identification of situational and contextual variables influencing the effect of their introduction. These results can be used for further investigation of different aspects of enterprises’ work and management in conditions of digital economy.

About the Authors

A. S. Melnikov
Ural Federal University named after the First President of Russia B. N. Yeltsin
Russian Federation

Alexander S. Melnikov, Post-Graduate Student of the Department for International Economics and Management 

19 Mira Str., Yekaterinburg, Sverdlovsk region, 620002



E. G. Kalabina
Ural State Economic University, Yekaterinburg
Russian Federation

Elena G. Kalabina, Doctor of Economics, Professor of the Department for Economics of Enterprises 

62/45 March 8/Narodnaya Volya Str., Yekaterinburg, 620144



References

1. Abdrakhmanova G. I., Zinina T. S., Kiseleva E. V., Nechaeva E. G., Rudnik P. B., Frolov M. S. Tsifrovye tekhnologii v biznese: praktiki i barery ispolzovaniya [Digital Technologies in Business: Practices and Barriers to Use]. Moscow, NIU VSHE, 2024. (In Russ.). Available at: https://issek.hse.ru/mirror/pubs/share/890550370.pdf (accessed 10.04.2024).

2. Belyakov A. Iskusstvennyy intellekt dlya promyshlennykh kompaniy: keysy ekspertov TSIPRa [Artificial Intelligence for Industrial Companies: Cases of CIPR Experts]. (In Russ.). Available at: https://sk.ru/news/iskusstvennyj-intellekt-dlya-promyshlennyh-kompanijkejsy-ekspertov-cipra/ (accessed 11.04.2024).

3. Bolotskikh M., Dorokhova M. Iskusstvennyy intellekt v Rossii – 2023: trendy i perspektivy [Artificial Intelligence in Russia – 2023: Trends and Prospects]. (In Russ.). Available at: https://ai.gov.ru/knowledgebase/infrastruktura-ii/2023_iskusstvennyy_intellekt_v_rossii_2023_trendy_i_perspektivy_yakov_i_partnery_yandeks (accessed 11.04.2024).

4. Voronin S., Zavilevskiy M. et al. Prichiny uspekha i neudach proektov po avtomatizatsii [Reasons for the Success and Failure of Automation Projects]. Generalnyy director [General Director], 2006, No. 12. (In Russ.).

5. Gde «Ashan» primenyaet iskusstvennyy intellect [Where Auchan uses Artificial Intelligence]. (In Russ.). Available at: https://www.retail.ru/cases/gde-ashan-primenyaetiskusstvennyy-intellekt-/ (accessed 10.04.2024).

6. Gileva T. A. Tsifrovaya zrelost predpriyatiya: metody otsenki i upravleniya [Digital Maturity of an Enterprise: Methods of Assessment and Management]. Vestnik UGNTU. Nauka, obrazovanie, ekonomika. Seriya ekonomika [Bulletin of USPTU. Science, Education, Economics. Series Economics], 2019, No. 1 (27), pp. 38–52. (In Russ.).

7. Edinyy istochnik dannykh po energopotrebleniyu i ustoychivomu razvitiyu [Single Source of Data on Energy Consumption and Sustainable Development]. (In Russ.). Available at: https://www.se.com/kz/ru/work/services/sustainability-business/energy-and-sustainabilitysoftware/energy-management-software-resource-advisor.jsp (accessed 10.04.2024).

8. Ivanov M. V., Sakhratova T. V. Kompleksnyy podkhod pri vnedrenii sistem informatsionnykh tekhnologiy v upravlenii predpriyatiyami [An Integrated Approach to the Implementation of Information Technology Systems in Enterprise Management]. Nauchnyy vestnik MGTU GA [Scientific Bulletin of MSTU GA], 2013, No. 4 (190), pp. 49–52. (In Russ.).

9. Ispolzovanie tsifrovykh tekhnologiy organizatsiyami po Rossiyskoy Federatsii, subektam Rossiyskoy Federatsii i vidam ekonomicheskoy deyatelnosti [The use of Digital Technologies by Organizations in the Russian Federation, Constituent Entities of the Russian Federation and Types of Economic Activity]. (In Russ.). Available at: https://rosstat.gov.ru/statistics/science (accessed 10.04.2024).

10. Ryzhkov V., Chernov E., Nefedova O., Tarasova V. Tsifrovaya transformatsiya v Rossii: analiticheskiy otchet na osnove rezultatov oprosa rossiyskikh kompaniy [Digital Transformation in Russia: Analytical Report Based on the Results of a Survey of Russian Companies]. (In Russ.). Available at: https://komanda-a.pro/blog/dtr_2018 (accessed 10.04.2024).

11. Turovets Yu., Vishnevskiy K. Iskusstvennyy intellekt v Rossii: kto, chto i kak vnedryaet [Artificial Intelligence in Russia: who is Implementing what and how]. (In Russ.). Available at: https://issek.hse.ru/news/862013645.html (accessed 02.04.2024).

12. Ueyls P., Ross D. Upravlenie IT: opyt kompaniy-liderov. Kak informatsionnye tekhnologii pomogayut dostigat prevoskhodnykh rezultatov [IT Management: the Experience of Leading Companies. How Information Technology Helps Achieve Superior Results]. Moscow, Alpina Biznes Buks, 2005. (In Russ.).

13. Shapovalova A. Vedyakhin zayavil o gotovnosti Sbera delitsya AI-tekhnologiyami s arabskimi stranami [Vedyakhin Announced Sber's Readiness to Share AI Technologies with Arab Countries]. (In Russ.). Available at: https://lenta.ru/news/2024/02/23/vedyahin/ (accessed 02.04.2024).

14. CGI Global 1000. Insights from Conversations with Business and IT Executives around the World. Available at: https://www.cgi.com/sites/default/files/2022-09/cginl_presentatie_cgi-global-1000.pdf (accessed 02.04.2024).

15. Miller D. Synthetic Data and Artificial Intelligence Combine to Improve Machine Vision. Available at: https://www.automationworld.com/analytics/article/22223515/siemens-synthai-machine-vision (accessed 10.04.2024).

16. The Zero Gap Revolution: Innovations in Manufacturing. Available at: https://fastercapital.com/content/The-Zero-Gap-Revolution--Innovations-in-Manufacturing.html (accessed 10.04.2024).


Review

For citations:


Melnikov A.S., Kalabina E.G. Barriers in Proliferating Digital Technologies at Russian Companies: Causes and Effects. Vestnik of the Plekhanov Russian University of Economics. 2024;(6):33-45. (In Russ.) https://doi.org/10.21686/2413-2829-2024-6-33-45

Views: 155


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2413-2829 (Print)
ISSN 2587-9251 (Online)