Olha O. Kravchenko, 80_03
Wednesday, 06 December 2017 00:37 | Author: Покотиленко Р.В. | 
Olha O. Kravchenko
Doctor of Economics
State University of Infrastructure and Technology
04071, Ukraine, Kyiv, Kyrylivs’ka str., 9
E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
Analysis of the financial risks of the ukrainian railway transport
Section: Problems of economy of industrial enterprises and manufacturing complexes
Ekon. promisl. 2017, 80(4): 47-62
Language: English
Abstract | Full text (PDF)
DOI:
References
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14. Kupriyanovskiy, V.P., Sinyagov, S.A., Namiot, D.E., Utkin, N.A., Nikolaev, D.E., & Dobryinin, A.P. (2017). Transformation of Industry in the Digital Economy – Design and Manufacturing. International Journal of Open Information Technologies, 1, Vol. 5, pp. 50-70 [in Russian].
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23. Sheer, A.-V. What’s Behind the Term "Industry 4.0". Retrieved from http://www.i-love-bpm.ru/s%D1%81heer/chto-skryvaetsya-za-terminom-industriya-40 [Accessed 08 Sept. 2017]. [in Russian].
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25. Auschitzky, E., Hammer, M., & Rajagopaul, A. How big data can impro-ve manufacturing. McKinsey. Режим доступа: http://www.mckinsey.com/business-functions/operations/our-insights/how-big-data-can-improve-manufacturing [Accessed 28 Sept. 2017].
26. Brynjolfsson, E., & McElheran, K. Data in Action: Data-Driven Decision Making in U.S. Manufacturing. Режим доступа: http://www.economics.cornell.edu/sites/default/files/files/events/Brynjolfsson_McElheran_AEA_2016.pdf [Acces¬sed 25 Aug. 2017].
27. Dymola for physical modelling and simulation using Modelica. Claytex. Режим доступа: http://www.claytex.com/ products/dymola/ [Acces¬sed 28 Sept. 2017].
28. Fishwick, P. (2007). Handbook of Dynamic System Modeling (Chapman & Hall/CRC Computer and Information Sci-ence Series). New York: Chapman and Hall/CRC.
29. Geisberger, E., & Broy, M. (2012). Agenda CPS: Integrierte For schungs agenda Cyber-Physical Systems (acatech STUDIE) (German Edition). New York: Springer-Verlag, 297 p.
30.Gröger, C., Niedermann, F., & Mitschang, B. (2012, July) Data Mining-driven Manufacturing Process Optimization. Proceedings of the World Congress on En-gineering (Vol. III, pp. 1475-1481). London: WCE.
31.Hermann, M., Pentek, T., & Otto, B. (2016). Design Principles for Industrie 4.0 Scenarios. 49th Hawaii International Conference on System Sciences (HICSS), pp. 3928-3937.
32. Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014). Toward Scalable Systems for Big Data Analytics: a Technology Tutorial. IEEE Access, 2. pp. 652-687.
33. Industrie 4.0 – What is it? Germany Trade & Invest. Режим доступа: https://industrie4.0.gtai.de/INDUSTRIE40/ Navigation/EN/Topics/Industrie-40/what-is-it.html [Acces¬sed 08 Sept. 2017].
34. Information Resources Manage-ment Association. The Internet of Things: Breakthroughs in Research and Practice (2017). Information Resources Management Association. Hershey: IGI Global.
35.Innovationen für die Produktion von morgen. Режим доступа: https://www.bmbf.de/pub/Industrie_4.0.pdf [Accessed 08 Sept. 2017].
36. Jeschke, S., Brecher, C., Song, H., & Rawat, D. (2017). Industrial Internet of Things. Cybermanufacturing Systems. Her-ausgeber: Springer International Publishing Switzerland.
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38. Lasi, H., Kemper, H.-G., Fettke, P., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engi-neering, 4 (6), pp. 239-242.
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40. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. New York: McKinsey Global Institute.
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45. Saraee, M. How can companies start implementing the Smart Industry concept? Режим доступа: https://www.smart-industry.nl/site/assets/files/2158/how_can_ companies_start_implementing_the_smart_ industry_concept.pdf [Acces¬sed 08 Sept. 2017].
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50. Zhou, Z., Xie, S., & Chen, D. (2012). Fundamentals of Digital Manufac-turing Science. London: Springer-Verlag London Limited.
Doctor of Economics
State University of Infrastructure and Technology
04071, Ukraine, Kyiv, Kyrylivs’ka str., 9
E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
Analysis of the financial risks of the ukrainian railway transport
Section: Problems of economy of industrial enterprises and manufacturing complexes
Ekon. promisl. 2017, 80(4): 47-62
Language: English
Abstract | Full text (PDF)
DOI:
Abstract: The object of the paper is the financial risks of the railway transport. Today the financial situation of Ukraine's railway transport tends to deteriorate due to the systemic crisis of the national economy, the severance of existing economic ties, the critical wear and tear on non-negotiable assets, as well as an ineffective financial management. This led to the complexities of the formation of sufficient financial resources, the growth of financial risks and, as a result, the reduction of the international ratings. It is shown that little attention is paid to the risks, arising in the course of operating activities in the JSC ‘Ukrzaliznytsia’.
The paper analyzes financial risks of Ukrainian railway transport (financing of operating activities, liquidity, interest, credit and currency). The analysis showed that the industry is facing problems related to the financing of operating activities, providing the necessary level of liquidity and, consequently, the cost of the resources involved. This leads to a decrease in the ability of Ukrzaliznytsia to carry out the operational activities, reduce its effectiveness and, as a result, further deterioration of the financial condition.
In order to improve the financial situation and reduce the financial risks of railway enterprises, the directions of their reduction are offered: optimization of the structure of financial resources by reducing the share of borrowed funds, limiting the amount of high-risk financial transactions, limiting the volume of current assets in the form of low liquid and illiquid assets, rationalizing the policy of managing financial instruments, implementation of scientifically sound financial management system. The strategy and tactics for managing financial risks of the railway enterprises should be based on the balance between expected benefits and possible risks.
Keywords: financial condition, financial resources, financial risk, analysis, railway transport.
JEL code: G 320, G 390, L 920.
The paper analyzes financial risks of Ukrainian railway transport (financing of operating activities, liquidity, interest, credit and currency). The analysis showed that the industry is facing problems related to the financing of operating activities, providing the necessary level of liquidity and, consequently, the cost of the resources involved. This leads to a decrease in the ability of Ukrzaliznytsia to carry out the operational activities, reduce its effectiveness and, as a result, further deterioration of the financial condition.
In order to improve the financial situation and reduce the financial risks of railway enterprises, the directions of their reduction are offered: optimization of the structure of financial resources by reducing the share of borrowed funds, limiting the amount of high-risk financial transactions, limiting the volume of current assets in the form of low liquid and illiquid assets, rationalizing the policy of managing financial instruments, implementation of scientifically sound financial management system. The strategy and tactics for managing financial risks of the railway enterprises should be based on the balance between expected benefits and possible risks.
Keywords: financial condition, financial resources, financial risk, analysis, railway transport.
JEL code: G 320, G 390, L 920.
References
1. Analysis of World Experience in the Development of Industry and Approaches to the Digital Transformation of the Industry of the Member States of the Eurasian Economic Union: Informational and Analytical Report (2017). Moscow: Eurasian Economic Commission [in Russian].
2. Byelyakov, K.I. (2008). Informati-zation in Ukraine: Problems of organiza-tional, Legal and Scientific Support: mono-graph. Кyiv: KVIC [in Ukrainian].
3. Vasilenko, V. (2013). Technological Modes in the Context of the Aspiration of Economic Systems to the Ideal. Sotsial'no-ekonomichni problemy i derzhava, 1, Vol. 8, pp. 65-72 [in Russian].
4. Voronin, A.V. (2013). Modeling of Technical Systems. Tomsk: Tomsk Poly-technic University [in Russian].
5. Glazev, S.Yu. (2012). The Modern Theory of Long Waves in the Development of the Economy. Ekonomicheskaya nauka sovremennoy Rossii, 2 (57), pp. 8-27 [in Russian].
6. Gromova, T. Will the world survive the fourth industrial revolution? Delovaya stolitsa. Retrieved from http://fastsalttimes.com/sections/obzor/522.html [Accessed 07 Oct. 2017] [in Russian].
7. "Digital Dividends" World Devel-opment Report (2016). Washington: Interna-tional Bank for Reconstruction and Devel-opment / World Bank [in Russian].
8. Dyuzhev, D.V. (2008). The Specifics of Information Society Formation in Ukraine: History and Modernity. Nauka. Relihiya. Suspil'stvo, 2, pp. 130-135 [in Russian].
9. The Law of Ukraine "On the Basic Principles of the Development of the Infor-mation Society in Ukraine for 2007-2015" (2007). Uryadovyy kur"yer, 28 [in Ukrainian].
10. Information Technologies in Ukraine: The Colossus on Clay Feet. Retrieved from https://dou.ua/lenta/articles/it-in-ukraine/ [Accessed 07 Oct. 2017] [in Russian].
11. Information Technologies as the Stimulus for the Development of Ukrainian Society. Retrieved from http://data.ngorg. od.ua/ru/informacionnye-tehnologii-kak-stimul-razvitiya-ukrainskogo-obshchestva [Accessed 11 Sept. 2017] [in Russian].
12. Kaplan, A.V., Kaplan, V.E., Mas-chenko, M.V., & Ovechkina, E.V. (2007). The Solution of Optimization Tasks in the Economy. Moscow: Fenix [in Russian].
13. Kupriyanovskiy, V.P., Namiot, D.E., & Sinyagov, S.A. (2016). Cyber-Physical Systems as the Basis of the Digital Economy. International Journal of Open Information Technologies, 2, Vol. 4, pp. 18-25 [in Russian].
14. Kupriyanovskiy, V.P., Sinyagov, S.A., Namiot, D.E., Utkin, N.A., Nikolaev, D.E., & Dobryinin, A.P. (2017). Transformation of Industry in the Digital Economy – Design and Manufacturing. International Journal of Open Information Technologies, 1, Vol. 5, pp. 50-70 [in Russian].
15. Paklin, N.B., & Oreshkov, V.I. (2009). Business Intelligence: from Data to Knowledge. St. Petersburg: Peter [in Russian].
16. The Portrait of a Ukrainian IT professional. Retrieved from https://dou.ua/ lenta/articles/portret-ukrainskogo-it-specialista/ [Accessed 19 Sept. 2017] [in Russian].
17. "Industry 4.0": Creation of a Digital Enterprise. The Main Results of the Research in the Metallurgical Industry/ PwC. Retrieved from https://www.pwc.ru/ru/ mining-and-metals/publications/assets/industry-4-metals-key-findings_rus.pdf [Accessed 28 Sept. 2017] [in Russian]
18. Distributed data processing using Hadoop. IBM, 2017 [in Russian].
19. Romanchuk, Ya. Third industrial revolution: essence, influence, consequences. Retrieved from http://liberty-belarus.info/o-kapitalizme/kapitalizm-dlya-lyuboznatelnykh/ item/848-tretya-promyshlennaya-revolyutsiya-sut-vliyanie-posledstviya#l2 [Accessed 25 Aug. 2017] [in Russian].
20. State, Problems and Prospects of the Development of the Information Society in the CIS. (2012).Commonwealth of Inde-pendent States. Executive committee. Moscow [in Russian].
21. Trofimova, E. (2016). Cyber Vulnerability of the Smart Manufacturing. Сontrol Еngineering Rossiya, 1 (61), pp. 34-36 [in Russian].
22. Chekletsov, V. (2015). The Fourth Revolution: Internet of Things. Ekspert, January, pp. 42-44. Retrieved from http://www.ncca.ru/file?Files&141 [Accessed 08 Sept. 2017]. [in Russian].
23. Sheer, A.-V. What’s Behind the Term "Industry 4.0". Retrieved from http://www.i-love-bpm.ru/s%D1%81heer/chto-skryvaetsya-za-terminom-industriya-40 [Accessed 08 Sept. 2017]. [in Russian].
24. Atzori, L., Lera, A., & Morabito, G. (2010). The internet of things: a survey. Computer Networks. Режим доступа: https://www.researchgate.net/profile/Luigi_Atzori2/publication/222571757_The_Internet_of_Things_A_Survey/links/546b36df0cf2f5eb180914e5/The-Internet-of-Things-A-Survey.pdf [Acces¬sed 28 Sept. 2017].
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26. Brynjolfsson, E., & McElheran, K. Data in Action: Data-Driven Decision Making in U.S. Manufacturing. Режим доступа: http://www.economics.cornell.edu/sites/default/files/files/events/Brynjolfsson_McElheran_AEA_2016.pdf [Acces¬sed 25 Aug. 2017].
27. Dymola for physical modelling and simulation using Modelica. Claytex. Режим доступа: http://www.claytex.com/ products/dymola/ [Acces¬sed 28 Sept. 2017].
28. Fishwick, P. (2007). Handbook of Dynamic System Modeling (Chapman & Hall/CRC Computer and Information Sci-ence Series). New York: Chapman and Hall/CRC.
29. Geisberger, E., & Broy, M. (2012). Agenda CPS: Integrierte For schungs agenda Cyber-Physical Systems (acatech STUDIE) (German Edition). New York: Springer-Verlag, 297 p.
30.Gröger, C., Niedermann, F., & Mitschang, B. (2012, July) Data Mining-driven Manufacturing Process Optimization. Proceedings of the World Congress on En-gineering (Vol. III, pp. 1475-1481). London: WCE.
31.Hermann, M., Pentek, T., & Otto, B. (2016). Design Principles for Industrie 4.0 Scenarios. 49th Hawaii International Conference on System Sciences (HICSS), pp. 3928-3937.
32. Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014). Toward Scalable Systems for Big Data Analytics: a Technology Tutorial. IEEE Access, 2. pp. 652-687.
33. Industrie 4.0 – What is it? Germany Trade & Invest. Режим доступа: https://industrie4.0.gtai.de/INDUSTRIE40/ Navigation/EN/Topics/Industrie-40/what-is-it.html [Acces¬sed 08 Sept. 2017].
34. Information Resources Manage-ment Association. The Internet of Things: Breakthroughs in Research and Practice (2017). Information Resources Management Association. Hershey: IGI Global.
35.Innovationen für die Produktion von morgen. Режим доступа: https://www.bmbf.de/pub/Industrie_4.0.pdf [Accessed 08 Sept. 2017].
36. Jeschke, S., Brecher, C., Song, H., & Rawat, D. (2017). Industrial Internet of Things. Cybermanufacturing Systems. Her-ausgeber: Springer International Publishing Switzerland.
37. Kim, K., Jung, J.-K., & Choi, J.-Y. (2016). Impact of the Smart City Industry on the Korean National Economy: Input-Output Analysis. Sustainability, 8 (7). pp. 649-678.
38. Lasi, H., Kemper, H.-G., Fettke, P., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engi-neering, 4 (6), pp. 239-242.
39. Lee, J., Lapira, E., Bagheri, B., & Kao, H. (2013). Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters, 1. pp. 38-41.
40. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. New York: McKinsey Global Institute.
41. Nedelcu, B. (2013). About Big Data and its Challenges and Benefits in Manufacturing. Database Systems Journal, 4, Issue 3, pp. 10-19.
42. Networked Readiness Index (2015). Режим доступа: http://reports.weforum.org/ global-information-technology-report-2015/ economies/#indexId=NRI&economy=UKR [Accessed 25 Aug. 2017].
43. Nonaka, Y. Suginishi, Y., Lengyel, A., & Katsumura, Y. (2015, August) The S-Model: A digital manufacturing system combined with autonomous statistical analysis and autonomous discrete-event simulation for smart manufacturing. IEEE International Conference on Automation Science and Engineering (CASE) (pp. 1006-1011). Gothenburg: IEEE.
44. Reimann, M., & Ruckriegel, C. (2017). Road2CPS Priorities and Recom-mendations for Research and Innovation in Cyber-Physical Systems. Stuttgart: Steinbeis-Editions.
45. Saraee, M. How can companies start implementing the Smart Industry concept? Режим доступа: https://www.smart-industry.nl/site/assets/files/2158/how_can_ companies_start_implementing_the_smart_ industry_concept.pdf [Acces¬sed 08 Sept. 2017].
46. Smart Enterprise demo for manu-facturing. Pharaos Navigator. Режим до-ступа: https://enterprise.win2biz.com/static/ content/en/525/Explaining-Enterprise-Model. html [Accessed 08 Sept. 2017].
47. The 2016 IMD World Com-petitiveness Scoreboard. Режим доступа: http://www.imd.org/globalassets/wcc/docs/scoreboard-2016.pdf [Acces¬sed 08 Sept. 2017].
48. Yin, S., & Kaynak, O. (2015). Big Data for Modern Industry: Challenges and Trends. Proceedings of the IEEE, 2 Vol. 103, pp. 143-146.
49. Zaitsev, D.A. (2012). Universal Petri Net. Cybernetics and Systems Analysis, Vol. 48, Issue 4, pp. 498-511.
50. Zhou, Z., Xie, S., & Chen, D. (2012). Fundamentals of Digital Manufac-turing Science. London: Springer-Verlag London Limited.
Last Updated (Wednesday, 06 December 2017 00:38)
