Game Simulation of Interaction Between Mirrorless Camera Manufacturers Using Palisade Corporation Products

DOI: https://doi.org/10.25559/SITITO.019.202303.771-779

Abstract

The article focuses on game modeling of interaction between manufacturers of mirrorless cameras, the market of which is currently undergoing significant changes. It is pointed out that it is necessary to conduct a study of the phenomenon of interaction between manufacturers of mirrorless cameras, which are not limited exclusively to antagonism. The article proposes a mechanism for constructing and researching an advanced-level game-theoretic model that allows obtaining new information about the development of the economic situation associated with the choice of the moment of launching a new photographic product on the market. The strategies of mirrorless camera manufacturers were identified, the preferences of consumers of photographic equipment produced by two leading corporations – Fujifilm and Sony, which have significant market shares of mirrorless photographic equipment, were revealed. Digital Decision Tools and TopRank tools developed by Palisade Corporation are used to build the dynamics of the expected utility received by players in case of choosing the periods of product launch to the market (modeling the situation with uncertain parameters). The implemented approach made it possible to evaluate all the elements of the utility matrix of the first player (Fujifilm Corporation) and build the final matrix of the game, taking into account, in addition to the utility of the first player, the utility of the second player (Sony Corporation), isolated by the considered mirrorless cameras of the premium segment. Despite the advanced level of the constructed model, it belongs to the class of matrix game models, which made it possible to use a well–developed and proven mathematical apparatus in the practice of decision-making - the Laplace, Bayes criteria and the Hodge-Lehman criterion (relative to the utility matrix). This article is of interest for improving the game modeling of various economic problems and situations, as well as the development of the content of the professional training of a future economist at economic universities.

Author Biographies

Dmitry Anatolevich Vlasov, Plekhanov Russian University of Economics; Financial University under the Government of the Russian Federation

Associate Professor of the Department of Mathematical Methods in Economics; Associate Professor of the Department of Mathematics, Cand. Sci. (Ped.), Associate Professor

Alexander Valerievich Sinchukov, Financial University under the Government of the Russian Federation; Moscow Aviation Institute (National Research University)

Associate Professor of the Department of Mathematics; Associate Professor of the Chair No. 916, Cand. Sci. (Ped.)

References

1. Carranza J.E. Product innovation and adoption in market equilibrium: The case of digital cameras. International Journal of Industrial Organization. 2010;28(6):604-618. https://doi.org/10.1016/j.ijindorg.2010.02.003
2. Xiao J. Markov Perfect Equilibrium in the US digital camera market. International Journal of Industrial Organization. 2008;26(5):1233-1249. https://doi.org/10.1016/j.ijindorg.2007.12.005
3. Bernacki J. Digital camera identification by fingerprint s compact representation. Multimedia Tools and Applications. 2022;81(15):21641-21674. https://doi.org/10.1007/s11042-022-12468-0
4. Hanji P., Zhong F., Mantiuk R.K. Noise-Aware Merging of High Dynamic Range Image Stacks Without Camera Calibration. In: Bartoli A., Fusiello A. (eds.) Computer Vision ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science. Vol. 12537. Cham: Springer; 2020. p. 376-391. https://doi.org/10.1007/978-3-030-67070-2_23
5. Wolf M. Image Capture Systems and Algorithms. In: Smart Camera Design. Cham: Springer; 2018. p. 67-133. https://doi.org/10.1007/978-3-319-69523-5_3
6. Mikhailova V.M., Samarskaya V.S. Modern Market Trends Cameras. Scientific Works of KubSTU. 2019;(2):665-675. (In Russ., abstract in Eng.) EDN: IEPOTC
7. Agieva M.T., Korolev A.V., Ougolnitsky G.A. Static and Dynamic Game Theoretic Models of Opinion Control in Marketing Networks. Contributions to Game Theory and Management. 2021;14:8-19. https://doi.org/10.21638/11701/spbu31.2021.01
8. Vlasov D.A., Karasev P.A., Sinchukov A.V. Quantitative Analysis of the Camera Market Based on the Integrated Application Of game-Theoretic and Econometric Approaches. Scientific Research and Development. Economics of the Firm. 2021;10(2):15-22. (In Russ., abstract in Eng.) https://doi.org/10.12737/2306-627X-2021-10-2-15-22
9. Bhuiyan B.A. An Overview of Game Theory and Some Applications. Philosophy and Progress. 2018;59(1-2):111-128. https://doi.org/10.3329/pp.v59i1-2.36683
10. Liu C., Zhu E., Zhang Y., Zhang Q., Wei X. Characterization, verification and generation of strategies in games with resource constraints. Automatica. 2022;140:110254. https://doi.org/10.1016/j.automatica.2022.110254
11. Bekius F., Gomes S.L. A framework to design game theory-based interventions for strategic analysis of real-world problems with stakeholders. European Journal of Operational Research. 2023;309(2):925-938. https://doi.org/10.1016/j.ejor.2023.01.046
12. Manuel C. Game Theory. In: Runehov A.L.C., Oviedo L. (eds.) Encyclopedia of Sciences and Religions. Dordrecht: Springer; 2013. p. 919-924. https://doi.org/10.1007/978-1-4020-8265-8_1258
13. Yevsyeyeva E., Skafa O. Game Theory in Economics Education. Didactics of Mathematics. 2016;13:39-52. Available at: https://www.dbc.wroc.pl/Content/39678/Yevsyeyeva_Game_Theory_In_Economics_Education_2016.pdf (accessed 24.08.2023).
14. Radmacher F.G., Thomas W. A Game Theoretic Approach to the Analysis of Dynamic Networks. Electronic Notes in Theoretical Computer Science. 2008;200(2):21-37. https://doi.org/10.1016/j.entcs.2008.02.010
15. Zemskova E.S. Analysis of consumer behavior in the digital economy from the perspective of generation theory. The Eurasian Scientific Journal. 2019;11(5):28. (In Russ., abstract in Eng.) EDN: YTCZBJ
16. Sakhbieva A.I. Features of Consumer Behavior in the Digital Economy. Humanities, Social-Economic and Social Sciences. 2021;(3):238-240. (In Russ., abstract in Eng.) https://doi.org/10.23672/u5712-4804-4106-e
17. Reinartz W., Wiegand N., Imschloss M. The impact of digital transformation on the retailing value chain. International Journal of Research in Marketing. 2019;36(3):350-366. https://doi.org/10.1016/j.ijresmar.2018.12.002
18. Kolenteev N.Ya., Kobeleva A.S. The choice of optional solutions in uncertain conditions. Special'naja tehnika i tehnologii transporta. 2020;(8):286-293. (In Russ., abstract in Eng.) EDN: WEUIUI
19. Michaelis V.V. Primenenie nekotoryh kriteriev pri vybore optimal'noj strategii v teorii igr [Application of some criteria in choosing the optimal strategy in game theory]. Information Technology and Mathematical Modeling in the Management of Complex Systems. 2016;(15):89-95. (In Russ., abstract in Eng.) EDN: WNDFND
20. Ibrahim M.A.R., Jaini1 N.I., Khalif K.M.N.K. A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods. Journal of Physics: Conference Series. 2021;1988:012056. https://doi.org/10.1088/1742-6596/1988/1/012056
21. Heiets I., Oleshko T., Leshchinsky O. Application of Game Theory to Business Strategy. In: Bobek V., Horvat T. Business and Management Annual. Vol. 2023. IntechOpen; 2023. https://doi.org/10.5772/intechopen.111790
22. Abedian M., Amindoust A., Maddahi R., Jouzdani J. A game theory approach to selecting marketing-mix strategies. Journal of Advances in Management Research. 2022;19(1):139-158. https://doi.org/10.1108/JAMR-10-2020-0264
23. Thielmann I., Böhm R., Ott M., Hilbig B.E. Economic Games: An Introduction and Guide for Research. Collabra: Psychology. 2021;7(1):1-29. https://doi.org/10.1525/collabra.19004
24. van de Schoot R., Depaoli S., King R. et al. Bayesian statistics and modelling. Nature Reviews Methods Primers. 2021;1:1. 26 p. https://doi.org/10.1038/s43586-020-00001-2
25. Mikhaleva M.Yu. Multi-criteria analysis of the optimal investment distribution problem taking into account the variability of events. Fundamental research. 2020;(7):64-77. (In Russ., abstract in Eng.) https://doi.org/10.17513/fr.42807
Published
2023-10-15
How to Cite
VLASOV, Dmitry Anatolevich; SINCHUKOV, Alexander Valerievich. Game Simulation of Interaction Between Mirrorless Camera Manufacturers Using Palisade Corporation Products. Modern Information Technologies and IT-Education, [S.l.], v. 19, n. 3, p. 771-779, oct. 2023. ISSN 2411-1473. Available at: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/980>. Date accessed: 09 sep. 2025. doi: https://doi.org/10.25559/SITITO.019.202303.771-779.
Citation Formats
Issue
Vol 19 No 3 (2023): Modern Information Technologies and IT-education
Section
Cognitive information technologies in the digital economics
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