Transformation stages of the Russian industrial complex in the context of economy digitization
-
Author(s)Victoria AkberdinaLink to ORCID Index: https://orcid.org/0000-0002-6463-4008
,
Anna KalininaLink to ORCID Index: https://orcid.org/0000-0001-6086-8387
,
Andrey VlasovLink to ORCID Index: https://orcid.org/0000-0001-5581-4982
-
DOIhttp://dx.doi.org/10.21511/ppm.16(4).2018.17
-
Article InfoVolume 16 2018, Issue #4, pp. 201-211
- Cited by
- 951 Views
-
160 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
The present article presents an approach to evaluating the transformation of the industrial complex in the context of deep penetration of digital technologies into the material sector of the economy. The authors propose a theoretical research platform based on the theory of a new industrial society, substantiate a methodology, which comprises reproduction, institutional and synergetic approaches. The study showed that the transformation of the industrial complex, caused by any factors and implemented in any conditions, is always a discrete process of qualitative changes, resulting in significant structural changes and institutional transformations. The authors proposed a methodology to define the stages of industrial complex transformation in a digital economy. The authors’ model of the digitization process consists of five stages – primary information and communication digitization; electronic data exchange with external partners; use of specialized software; electronic data exchange with external partners. Within this framework, an empirical analysis was carried out to determine the digitization level of the industrial complex of Russia that implies a sufficiently high degree of primary computerization, the involvement of the industrial enterprises in the “digital” communication with counterparties and the dynamic software development. The study shows that the process of digital transformation of the Russian industry is still in its formative stages.
- Keywords
-
JEL Classification (Paper profile tab)О14, О25, O33
-
References51
-
Tables4
-
Figures1
-
- Figure 1. Digitalization process of the industrial complex
-
- Table 1. First stage: primary information and communication digitization in Russia as of 2017
- Table 2. Second stage: electronic data exchange in the chains of the final product creation and its sale to consumers in Russia as of 2017
- Table 3. Third stage: use of specialized software in Russia as of 2017
- Table 4. Fourth stage: own production for ICT in Russia as of 2017
-
- Aptekman, A., Kalabin, V., Klintsov, V. et al. (2017). Digital Russia: A New Reality: Report by McKinsey Company. Moscow: McKinsey.
- Arrow, K. J. (1973). Information and Economic Behavior. Stockholm: Federation of Swedish Industries.
- Ashton, K. (2009, June). That “Internet of Things” Thing. In the Real World, Things Matter More Than Ideas. RFID Journal, 123-128.
- Babaev, B. D. (Ed.). (2012). Multilevel Social Reproduction: Questions of Theory and Practice: Collection of Scientific Essays. Ivanovo: Ivanovo State University.
- Baller, S., Dutta, S., & Lanvin, B. (Eds.). (2016). The Global Information Technology Report – 2016.
- Bell, D., & Inozemtsev, V. L. (2007). The Age of Disunity: Reflections on the World of the 21st Century. Moscow: Svobodnaya mysl. Tsentr issledovanii postindustrialnogo obshchestva.
- Bodrunov, S. D. (2014). Re-industrialization. Round-Table Talk in the Free Economic Society of Russia. The World of New Economy, 1, 11-17.
- Bodrunov, S. D. (2016). The Coming of New Industrial Society: Reloaded. Moscow: Institute of New Industrial Development named after S.Y. Vitte.
- Bolychev, O. N. (2014). The Concept of the Network in the System of Basic Concepts of Regional Economic and Geographical Research. Baltic Region, 4(22), 79-93.
- Burt, R. S. (1995). Structural Holes: The Social Structure of Competition. Cambridge: Harvard University Press.
- Buzgalin, A. V., & Kolganov, A. I. (2007). Global Capital (2nd ed.). Moscow: Editorial URSS.
- Chakravorti, B., & Chaturvedi, R. S. (2017). The Digital Planet-2017.
- Chernyak, L. (2012). The Internet of Things Platform. Open Systems. DBMS, 7, 98-104.
- Coase, R. (2007). The Firm, the Market and the Law: Collection of Articles. Moscow: Novoe izdatelstvo.
- Desai, M. (2018) Simple and Extended Reproduction. In The New Palgrave Dictionary of Economics. London: Palgrave Macmillan.
- Dyatlov, S. A. (2014). Network Effects and Increasing Returns in the Information and Innovation Economy. Bulletin of Saint Petersburg State University of Economy, 2(86), 7-11.
- Frankel, B. (1987). The Post- Industrial Utopians. Universiy of Wisconsin Press.
- Grabher, G., Stark, D. (1997). Organizing Diversity: Evolutionary Theory, Network Analysis, and the Postsocialist Transformations. In G. Grabher & D. Stark (Eds.), Restructuring Networks: Legacies, Linkages, and Localities in Postsocialism (pp. 1–32). London and New York: Oxford University Press.
- Granovetter, M. (1992). Networks and Organizations: Structure, Form, and Action. Harvard Business School.
- Granovetter, M. (2006). Business Groups and Social Organizations. In N. Smelser & R. Swedberg (Eds.) The Handbook of Economic Sociology (2nd ed.). Princeton: Princeton University Press.
- Heilbroner, R. (1974). An Inquiry into the Human Prospect (2nd ed.). W.W. Norton.
- IMD World Competitiveness Center (2017). The World Digital Competitiveness Rankings – 2017.
- Inozemtsev, V. L. (2014). Postindustrial/Industrial Dichotomy. World of Changes, 1, 144-147.
- Khubiev, K. A. (Ed.). (2012). Modern Nature of Cyclical Reproduction. Moscow: MGU, TEIS.
- Konyukhovskaya, A., Tsyplenkov, V., & Nedelsky, V. (2016). Industrial Robotics in Russia and the World. Moscow: The National Association of the Robotics Market Participants.
- Kumar, K. (1978). Prophecy and Progress: The Sociology of Industrial and Post-Industrial Society. Alein Lane.
- Kumar, K. (1996). From Post- Industrial to Post-Modern Society: New Theories of the Contemporary World. Oxford, UK; Cambridge, USA: Blackwell.
- Kuzmin, E. A. (2017). A Study on the Problems of the Structure of Transaction Costs. Problems and Perspectives in Management, 15(3), 224-233.
- Maevskii, V. I. (2012). On the Switching Reproduction Mode. TERRA ECONOMICUS, X(1), 38-49.
- Moore, G. E. (1965). Cramming More Components onto Integrated Circuits. Electronics, 38(8), 114-117.
- National Association of the Robotics Market Participants (2016). Analytical Research: World Robotics Market.
- Nizhegorodtsev, R. M. (2002). Information Economy. Book 1. Information Universe: Information Bases of Economic Growth. Moscow: Kostroma.
- Popov, E. V. (2016). Networks. Ekaterinburg: AMB.
- Powell, W., & Brantley, P. (1992). Competitive Co-Operation in Biotechnology: Learning Through Networks? In N. Nohria & R. Eccles (Eds.), Networks and Organizations: Structure, Form, and Action (pp. 78-94). Boston, MA: Harvard Business School Press.
- Prause, G., & Atari, S. (2017). On Sustainable Production Networks for Industry 4.0. Entrepreneurship and Sustainability Issues, 4(4), 421-431.
- Ministry of Industry and Trade of Russia (2017). Press Release of the Meeting of the Presidential Council on Strategic Development and Priority Projects of July 5, 2017.
- Ragulina, Y. V., Semenova, E. I., Zueva, I. A., Kletskova, E. V., & Belkina, E. N. (2018). Perspectives of Solving the Problems of Regional Development with the Help of New Internet Technologies. Entrepreneurship and Sustainability Issues, 5(4), 890-898.
- Romanova, O. A., Akberdina, V. V., & Bukhvalov, N. Y. (2016). Common Values in Modeling the Modern Techno-Economic Paradigm. Economic and Social Changes: Facts, Trends, Forecast, 3(45), 173-190.
- Romanova, O. A., Korovin, G. B., & Kuzmin, E. A. (2017). Analysis of the Development Prospects for the High-Tech Sector of the Economy in the Context of New Industrialization. Espacios, 38(59), 25.
- Russian Federal State Statistics Service (2017). Data on the Use of Information and Communication Technologies and the Production of Computers, Software and Services in These Areas.
- Ryazanov, V. (2013). Time for a New Industrialization: Russian Prospects. Economist, 8, 24-36.
- Samašonok, K., Išoraitė, M., & Leškienė-Hussey, B. (2016). The Internet Entrepreneurship: Opportunities and Problems. Entrepreneurship and Sustainability Issues, 3(4), 329-349.
- Shatrevich, V., & Strautmane, V. (2015). Industrialisation Factors in Post-Industrial Society, Entrepreneurship and Sustainability, 3(2), 157-172.
- Valtukh, K. K. (2009). Reproduction and Pricing. Theory. System Statistics Studies. Moscow: Yanus-K.
- Varian, K. R. (2005). Economic Theory of Information Technology. In L. G. Melnik (Ed.), Socio-Economic Problems of the Information Society. Sumy: ITD “Universitetskaya kniga”.
- Webster, F. (2006). Theories of Information Society. Routledge.
- Weiber, R. (2003). Empirical Laws of the Network Economy. Theoretical and Practical Aspects of Management, 4, 45-57.
- Weiber, R. (2005). Laws of the Network Economy. Problems of Forecasting, 4, 86-91.
- White, H.C. (2002). Markets from Networks: Socioeconomic Models of Production. Princeton: Princeton University Press.
- Williamson, O. (1979). Transaction-Cost Economics: The Governance of Contractual Relations. Journal of Law Economics, XXII(2), 223-261.
- Williamson, O. E. (2007). The Economic Institutions of Capitalism. Firms, Markets, Relational Contracting. In C. Boersch & R. Elschen (Eds.), Das Summa Summarum des Management. Gabler.
-
Relationship of generations X, Y, Z with new communication technologies
Adriana Grenčíková 
,
Sergej Vojtovič
doi: http://dx.doi.org/10.21511/ppm.15(si).2017.09
Problems and Perspectives in Management Volume 15, 2017 Issue #2 (cont. 3) pp. 557-563 Views: 2365 Downloads: 682 TO CITE АНОТАЦІЯAt present times, the impact of new technologies on job creation is going to be a serious problem in personnel management. In the human resources contents, this issue still remains in minor attention. As a result of new communication technologies development in the near future, we will be facing too many changes in working patterns and demands on staff regarding job requirements. Simultaneously with the above stated changes on labor market, a new generation of workers is emerging that grew up with the development of communication technologies, they profess different lifestyle from the one the generations have had before. Many of these generations become employers and bring new approaches to employment of people being different from traditional working patterns. Despite the facts being alleged in this study, it is difficult to estimate to what extent those changes will affect Slovak labor market. Gradual development of technologies is an ongoing process in Slovakia as well and in four years robotics is to be a key technology in most manufacturing plants mainly in automotive industry. Currently, three generations are present on labor market that may have a different approach to changes being implemented nowadays. In this study, the authors analyze the survey results on the use of communication technologies by Generations X, Y, Z, and their abilities to be prepared for changes on labor market. Survey provides interesting information about the access of different generations to communication technologies and their relationship with technical innovations.
-
Financial modeling trends for production companies in the context of Industry 4.0
Inga Kartanaitė ,
Bohdan Kovalov ,
Oleksandr Kubatko ,
Rytis Krušinskas
doi: http://dx.doi.org/10.21511/imfi.18(1).2021.23
Investment Management and Financial Innovations Volume 18, 2021 Issue #1 pp. 270-284 Views: 1300 Downloads: 388 TO CITE АНОТАЦІЯOver the years, technological progress has accelerated highly, and the speed, flexibility, human error reduction, and the ability to manage the process in real time have become more critical and required production companies to adapt production and business models according to the needs. The demand for real-time decision support systems adapted to these raising business needs is continuously growing. Nevertheless, businesses usually face challenges in identifying new indicators, data sources, and appropriate financial modeling methods to analyze them. This paper aims to define and summarize the main financial/economic forecasting methods for production companies in the context of Industry 4.0. Main findings show forecasting accuracy of up to 96% when combining economic and demand information, optimal forecasting period from 10 months to five years, more frequent use of soft indicators in forecasting, the relationship between company’s size and production planning. Four groups of indicators used in financial modeling, such as (I) production-related, (II) customers’ and demand-oriented, (III) industry-specific, and (IV) media information indicators, were separated. The analysis forms a suggestion for decision-makers to pay more attention to the forecasting object identification, indicators’ selection peculiarities, data collection possibilities, and the choice of appropriate methods of financial modeling.
Acknowledgment
This work was partly supported by Project No. 0121U100470 “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy”.
