Liudmila Nikolova
ABSTRACT
Currently, the competitiveness of enterprises implementing their activities in the framework of digital technologies has increased significantly. Digital economics drastically changes all stages of the activities of an enterprise from production management to its relationship with the state. As is well known, digital economics is characterized by the formation of economic models implemented in a software product that allows you to manage the activities of the enterprise continuously and to minimize the costs and risks of non-receipt of profit. The purpose of this study is to form an innovative model based on key aspects for assessing the efficient management of the renewal and use of fixed assets in the digital economy. In order to achieve this goal, we first had to clarify the classification of fixed assets, which allows us to think that the developed innovative model corresponds to the concept and technology of digital economics. Based on this clarified classification of fixed assets, we developed an innovative model for assessing the efficient management of the renewal and use of fixed assets in the digital economy. This model is a comprehensive assessment of the efficient management of the renewal and use of fixed assets. The following methods were used in the research: situational, dynamic analysis, correlation and regression analysis, the method of constructing a normative system of indicators, the method of trend extrapolation, tabular and graphical interpretation of empirical and factual information.
The developed innovative model for assessing the efficient management of the renewal and use of fixed assets can be applied in enterprises in sectors of the economy.
- E. Abushova, E. Burova, and S. Suloeva, A. Shcheglova, 2018. Complex approach to selecting priority lines of business by an enterprise. 2017 6th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions, ICRITO 2017, 565--569Google Scholar
- E.S. Balashova, and E.A. Gromova, 2017. Economic effect in the framework of lean production. Journal of Applied Economic Sciences, 12(4), 1188--1193Google Scholar
- E.S. Balashova, and E.A. Gromova, 2018. Russian industrial sector in the conditions of the Fourth Industrial Revolution. IOP Conference Series: Materials Science and Engineering, 404 (1)Google Scholar
- A.V. Bataev, 2018. Analysis and development the digital economy in the world. Proceedings of the 31st International Business Information Management Association Conference, 61--71.Google Scholar
- T.A. Bayaskalanov, 2014. Updating of basic production assets. News of the Irkutsk State Economic Academy, 2, 71--79.Google Scholar
- M. Delgado, M.E. Porter and S. Stern, 2014. Clusters, convergence, and economic performance, Researc Policy, 43, 1785--1799.Google ScholarCross Ref
- D.S. Demidenko, V.V. Kulibanova, and V.G. Maruta, 2018). Using the principles of "digital economy" in assessing the company's capitalization. Proceedings of the 31st International Business Information Management Association Conference, 6087--6091Google Scholar
- D.S. Demidenko and E.D. Malevskaia-Malevich (2016). Features of optimal control of dynamic processes in enterprise economics. Proceedings of the 27th International Business Information Management Association Conference - Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth, IBIMA 2016. 27, Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth., 1606--1612.Google Scholar
- D.S. Demidenko, E.D. Malevskaia-Malevich, and Dubolazova, Y.A., Victorova, N.G. (2018). Optimization of the innovation process management at a manufacturing enterprise. Proceedings of the 31st International Business Information Management Association Conference, 996--1003.Google Scholar
- O.V. Demyanova, 2014 Formation of a multidimensional model of the effectiveness of the modern economy: Author's abstract. dis. Dan. O.V. Demyanova. Saint-Petersburg State University of Economics, St. Petersburg, Russia.Google Scholar
- G.V. Dvas, and Y.A. Dubolazova, (2018). Risk assessment and risk management of innovative activity of the enterprise. Proceedings of the 31st International Business Information Management Association Conference, 5650--5653.Google Scholar
- V.V. Glukhov, and E.S. Balashova (2015). Reservation of increasing the efficiency of industrial enterprises on the basis of competence management. Scientific and technical statements SPbGPU. Economics, 3 (221), 192--197.Google Scholar
- T. Hillig Subsector Analysis: Zambia. The power crisis and its consequences for solar energy in the Zambian mining sector // German Energy Solutions Initiative. https://www.giz.de/fachexpertise/downloads/giz2016-en-pep-ssa-market-analysis-pv-extractive-industry-zambia.pdf.Google Scholar
- International Energy Agency. http://www.iea.org/statistics/.Google Scholar
- A.E. Karlik and V.V. Platonov, 2016. Study of the organizational and dynamic cooperation of enterprises, Saint-Petersburg State University of Economics, St. Petersburg, Russia.Google Scholar
- L.D. Khabachev, U.I. Plotkina, T.M. Bugaeva and A.B. Yurkova, 2018. Assessment of systemic effects from integration of distributed generation facilities into regional energy systems. 2017 6th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions, ICRITO 2017, 188--193.Google Scholar
- O.E. Kichigin, O.S. Nadezhina, V.A. Degtereva, and D. Ovsyanko, 2018. The concept of participation of fuel-energy companies in development of regional socio-economic systems. Proceedings of the 32nd International Business Information Management Association Conference, 6837--6842Google Scholar
- H. Kurtz and N. Salvadori 2004. Production Theory. Finance and Statistics. Moscow, Russia.Google Scholar
- V.M. Kuzichev, S.S. Chernov and A.Y. Perminov (2009). The concept and classification of objects of the enterprise property complex. Problems of the modern economy, 4.Google Scholar
- E.D. Malevskaia-Malevich, S.A. Leonov, and A. Kopachev, 2018. Factor analysis model of the total cost of quality in the enterprise production process. Proceedings of the 32nd International Business Information Management Association Conference, 5886--5890.Google Scholar
- S.V. Markiv Metodika analiza effektivnosti ispolzovaniya osnovnykh fondov vertikalno integrirovannoi gaz. Author. Economics PhD candidate, http://www.dissercat.com/content/metodika-analiza-effektivnosti-ispolzovaniya-osnovnykh-fondov-vertikalno-integrirovannoi-gaz.Google Scholar
- A. Marshall, 2017. Fundamentals of Economics. Eksmo, Moscow, RussiaGoogle Scholar
- M.D. Mednikov, A.S. Sokolitsyn, M.V. Ivanov, and N.A. Sokolitsyna, 2017. Forming optimal enterprise development strategies. Proceedings of the 30th International Business Information Management Association Conference, 1053--1063.Google Scholar
- M.D. Mednikov, A.S. Sokolitsyn, M.V. Ivanov, N.A. Sokolitsyna, and V.N. Yuryev, 2018. Forming optimal industrial enterprise management strategy. Proceedings of the 32nd International Business Information Management Association Conference, 6589--6599.Google Scholar
- Opportunities in the energy sector in Zambia. https://www.giz.de/fachexpertise/downloads/pep2015-en-ssa-iv-pv-mmembe.pdf.Google Scholar
- E.S. Ozerov, S.V. Pupentsova, V.A. Leventsov, and M.S. Dyachkov, 2018. Selecting the best use option for assets in a corporate management system. 2017 6th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions, ICRITO 2017, 162--170.Google Scholar
- L.P. Padalko (1979). Criteria and methods for optimal control of the electric power system. Science and Technology, Minsk, USSR.Google Scholar
- J. Richard (2009). Audit and analysis of the economic activity of the enterprise. IO YUNITI, Moscow, Russia.Google Scholar
- E.V. Polyakov (2017). Energy Sector Economics. Armada, Moscow, RussiaGoogle Scholar
- D.G. Rodionov, E.A. Konnikov, and O.A. Konnikova, (2018). Approaches to ensuring the sustainability of industrial enterprises of different technological levels. Journal of Social Sciences Research, Special 3, 277--282.Google Scholar
- J.- B. Say (2000). Treatise on state economy. Delo, Moscow, RussiaGoogle Scholar
- A.S. Sokolitsyn, M.V. Ivanov, and N.A. Sokolitsyna, (2017). Corporate governance: Estimating resource providing corporative industrial organization. Proceedings of the 29th International Business Information Management Association Conference, 191--200.Google Scholar
- A.S. Sokolitsyn, M.V. Ivanov and N.A. Sokolitsyna, (2017). Statistic modeling industrial enterprises production process parameters. Proceedings of the 30th International Business Information Management Association Conference, 1041--1052.Google Scholar
Index Terms
- An innovative model assessment of efficient management a renewal and using the fixed assets of enterprises in the digital economy
Recommendations
Time-Dependent Model of Corporate Investments in Fixed Assets
The article examines the simplest model of investment in fixed assets by a corporation using debt. The value of corporation's equity is the evaluation criterion. The value of equity can be determined by direct capitalization of gross profit in the ...
Portfolio Choice with Illiquid Assets
We present a model of optimal allocation to liquid and illiquid assets, where illiquidity risk results from the restriction that an asset cannot be traded for intervals of uncertain duration. Illiquidity risk leads to increased and state-dependent risk ...
Valuing Thinly Traded Assets
We model illiquidity as a restriction on the stopping rules investors can follow in selling assets, and apply this framework to the valuation of thinly traded investments. We find that discounts for illiquidity can be surprisingly large, approaching 30%-...
Comments