Development of a model for decision support systems to control the process of investing in information technologies

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.194531

Keywords:

optimal investment strategies, decision support, multi-step game, software product

Abstract

A model for managing the investment process has been proposed, using an example of investing in information technologies (IT) taking into consideration that a given process is multifactorial in character. The difference between our model and those constructed previously is that, firstly, it considers the investment process as a complex structure, for which it is not enough to model it as a one-factor category. Secondly, our model is based on solving a bilinear multi-step quality play with several terminal surfaces. The solution has been derived within a new class of bilinear multi-step games that describe the interaction of objects in multidimensional space. Consideration of the investment process in such a statement provides an opportunity to adequately describe the process of finding rational strategies of players in the course of investing in information technologies. The study conducted has made it possible to implement the model’s programming code in the MATLAB simulation environment. Software product, the decision support system "IT INVESTMENT", has been developed. The mathematical core of the DSS is based on the application of a new class of bilinear differential games. The proposed solution makes it possible to find the optimal investment strategies for potential investors; its application enabled to reduce the discrepancies between forecasting data and actual return on investment, for example, in IT projects. The resulting solution has made it possible to represent graphically the sets of preferences of investors in the process of investing in IT projects, taking into consideration the multifactor character in multidimensional space. It has been shown that such an approach, combined with the application of computer simulation and DSS, would provide an investor with wider opportunities to analyze and choose rational financial strategies

Author Biographies

Valeriy Lakhno, National University of Life and Environmental Sciences of Ukraine Heroiv Oborony str., 15, Kyiv, Ukraine, 03041

Doctor of Technical Sciences, Professor

Department of Computer Systems and Networks

Volodimir Malyukov, National University of Life and Environmental Sciences of Ukraine Heroiv Oborony str., 15, Kyiv, Ukraine, 03041

Doctor of Physical and Mathematical Sciences, Associate Professor

Department of Computer Systems and Networks

Nataliia Mazur, Borys Grinchenko Kyiv University Bulvarno-Kudriavska str., 18/2, Kyiv, Ukraine, 04053

PhD

Department of Information and Cyber Security

Lidiia Kuzmenko, Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine Chokolivskiy blvd., 13, Kyiv, Ukraine, 03186

Postgraduate Student

Berik Akhmetov, National Aviation University Kosmonavta Komarova ave., 1, Kyiv, Ukraine, 03058

PhD

Department of Information Technology Security

Vitalii Hrebeniuk, National Academy of Security Service of Ukraine Mykhaylo Maksymovych str., 22, Kyiv, Ukraine, 03022

Doctor of Law, Head of Scientific Laboratory

References

  1. Zuboff, S. (2015). Big other: Surveillance Capitalism and the Prospects of an Information Civilization. Journal of Information Technology, 30 (1), 75–89. doi: https://doi.org/10.1057/jit.2015.5
  2. McArthur, D. (2002). Investing in digital resources. New Directions for Higher Education, 2002 (119), 77–86. doi: https://doi.org/10.1002/he.74
  3. Madon, S., Krishna, S. (2018). The Digital Challenge: Information Technology in the Development Context. Routledge, 386. doi: https://doi.org/10.4324/9781315196978
  4. Woodard, C. J., Ramasubbu, N., Tschang, F. T., Sambamurthy, V. (2013). Design Capital and Design Moves: The Logic of Digital Business Strategy. MIS Quarterly, 37 (2), 537–564. doi: https://doi.org/10.25300/misq/2013/37.2.10
  5. Bai, C., Sarkis, J. (2016). Supplier development investment strategies: a game theoretic evaluation. Annals of Operations Research, 240 (2), 583–615. doi: https://doi.org/10.1007/s10479-014-1737-9
  6. Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M. (2014). Internet of Things for Smart Cities. IEEE Internet of Things Journal, 1 (1), 22–32. doi: https://doi.org/10.1109/jiot.2014.2306328
  7. Akhmetov, B. S., Akhmetov, B. B., Lakhno, V. A., Malyukov, V. P. (2019). Adaptive model of mutual financial investment procedure control in cybersecurity systems of situational transport centers. NEWS of National Academy of Sciences of the Republic of Kazakhstan, 3 (435), 159–172. doi: https://doi.org/10.32014/2019.2518-170x.82
  8. Mithas, S., Tafti, A., Mitchell, W. (2013). How a Firm’s Competitive Environment and Digital Strategic Posture Influence Digital Business Strategy. MIS Quarterly, 37 (2), 511–536. doi: https://doi.org/10.25300/misq/2013/37.2.09
  9. Tiwana, A., Ramesh, B. (2001). E-services: problems, opportunities, and digital platforms. Proceedings of the 34th Annual Hawaii International Conference on System Sciences. doi: https://doi.org/10.1109/hicss.2001.926311
  10. Mazzarol, T. (2015). SMEs engagement with e-commerce, e-business and e-marketing. Small Enterprise Research, 22 (1), 79–90. doi: https://doi.org/10.1080/13215906.2015.1018400
  11. Sedera, D., Lokuge, S., Grover, V., Sarker, S., Sarker, S. (2016). Innovating with enterprise systems and digital platforms: A contingent resource-based theory view. Information & Management, 53 (3), 366–379. doi: https://doi.org/10.1016/j.im.2016.01.001
  12. Mohammadzadeh, A. K., Ghafoori, S., Mohammadian, A., Mohammadkazemi, R., Mahbanooei, B., Ghasemi, R. (2018). A Fuzzy Analytic Network Process (FANP) approach for prioritizing internet of things challenges in Iran. Technology in Society, 53, 124–134. doi: https://doi.org/10.1016/j.techsoc.2018.01.007
  13. Selçuk, A. L. P., Özkan, T. K. (2015). Job choice with multi-criteria decision making approach in a fuzzy environment. International Review of Management and Marketing, 5 (3), 165–172.
  14. Kache, F., Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations & Production Management, 37 (1), 10–36. doi: https://doi.org/10.1108/ijopm-02-2015-0078
  15. Akhmetov, B. B., Lakhno, V. A., Akhmetov, B. S., Malyukov, V. P. (2018). The Choice of Protection Strategies During the Bilinear Quality Game On Cyber Security Financing. Bulletin of the National Academy of Sciences of the Republic of Kazakhstan, 3, 6–14.
  16. Lakhno, V., Malyukov, V., Gerasymchuk, N., Shtuler, I. (2017). Development of the decision making support system to control a procedure of financial investment. Eastern-European Journal of Enterprise Technologies, 6 (3 (90)), 35–41. doi: https://doi.org/10.15587/1729-4061.2017.119259
  17. Smit, H. T. J., Trigeorgis, L. (2010). Flexibility and Games in Strategic Investment. Multinational Finance Journal, 14 (1/2), 125–151. doi: https://doi.org/10.17578/14-1/2-4
  18. Arasteh, A. (2017). Considering the investment decisions with real options games approach. Renewable and Sustainable Energy Reviews, 72, 1282–1294. doi: https://doi.org/10.1016/j.rser.2016.10.043
  19. Gottschlich, J., Hinz, O. (2014). A decision support system for stock investment recommendations using collective wisdom. Decision Support Systems, 59, 52–62. doi: https://doi.org/10.1016/j.dss.2013.10.005
  20. Strantzali, E., Aravossis, K. (2016). Decision making in renewable energy investments: A review. Renewable and Sustainable Energy Reviews, 55, 885–898. doi: https://doi.org/10.1016/j.rser.2015.11.021
  21. Nagurney, A., Daniele, P., Shukla, S. (2016). A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints. Annals of Operations Research, 248 (1-2), 405–427. doi: https://doi.org/10.1007/s10479-016-2209-1
  22. Akhmetov, B., Balgabayeva, L., Lakhno, V., Malyukov, V., Alenova, R., Tashimova, A. (2019). Mobile Platform for Decision Support System During Mutual Continuous Investment in Technology for Smart City. Studies in Systems, Decision and Control, 731–742. doi: https://doi.org/10.1007/978-3-030-12072-6_59
  23. Nikol’skii, M. S. (2017). A Study of the Generalized Pontryagin Test Example from the Theory of Differential Games. Proceedings of the Steklov Institute of Mathematics, 299 (S1), 158–164. doi: https://doi.org/10.1134/s0081543817090188
  24. Krasovskii, N. A., Tarasyev, A. M. (2018). Demand Functions in Dynamic Games. IFAC-PapersOnLine, 51 (32), 271–276. doi: https://doi.org/10.1016/j.ifacol.2018.11.394

Published

2020-02-29

How to Cite

Lakhno, V., Malyukov, V., Mazur, N., Kuzmenko, L., Akhmetov, B., & Hrebeniuk, V. (2020). Development of a model for decision support systems to control the process of investing in information technologies. Eastern-European Journal of Enterprise Technologies, 1(3 (103), 74–81. https://doi.org/10.15587/1729-4061.2020.194531

Issue

Section

Control processes