Building a model of supply chains duopoly taking into account the marketing and innovative activities of manufacturing enterprises
DOI:
https://doi.org/10.15587/1729-4061.2022.253821Keywords:
supply chain, duopoly, equilibrium solution, marketing activity, innovation activity, industrial enterprise, competitive environmentAbstract
This paper reports the construction and analysis of the economic and mathematical model of the duopoly of supply chains, based on the model of optimization of plans for the release and delivery of multi-range articles, taking into consideration the marketing and innovative activities of industrial enterprises. Demand for goods is supposed to be an increasing function of advertising costs. In this case, marketing investments affect only the base selling prices of articles and do not affect competitive discounts. The explicit form of this dependence can be established as a result of marketing research. It is also assumed that investments in innovative technological projects could reduce industrial costs; production costs are decreasing functions of the size of the investment. It is believed that the demand function is linearly dependent on the total volume of output produced. The criterion of optimality for supply chains is the maximum of the total profit received from the sale and delivery of finished products to points of consumption, taking into consideration the costs of production and advertising. As a result of this study, equilibrium solutions of the duopoly according to Cournot and Stackelberg were found. That has made it possible to determine the optimal values of product volumes for output, the size of investment investments, as well as product advertising costs. The model helped study the impact of investment deductions and advertising costs on the acquisition of competitive advantages by manufacturing enterprises. A numerical illustration of the results obtained is given. The proposed approach could be used to build and analyze dynamic optimization models taking into consideration the innovation and marketing activities of enterprises, as well as to study other market structures
References
- Ji, Y., Li, M., Qu, S. (2018). Multi-objective linear programming games and applications in supply chain competition. Future Generation Computer Systems, 86, 591–597. doi: https://doi.org/10.1016/j.future.2018.04.041
- Li, S., Lai, M., Xue, W. (2018). Bundling Strategy and Channel Competition in Supply Chains with Complementary Products. Procedia Computer Science, 126, 1730–1739. doi: https://doi.org/10.1016/j.procs.2018.08.104
- Mahmoodi, A. (2020). Stackelberg–Nash equilibrium of pricing and inventory decisions in duopoly supply chains using a nested evolutionary algorithm. Applied Soft Computing, 86, 105922. doi: https://doi.org/10.1016/j.asoc.2019.105922
- Sjoerdsma, M., van Weele, A. J. (2015). Managing supplier relationships in a new product development context. Journal of Purchasing and Supply Management, 21 (3), 192–203. doi: https://doi.org/10.1016/j.pursup.2015.05.002
- Gualandris, J., Kalchschmidt, M. (2014). Customer pressure and innovativeness: Their role in sustainable supply chain management. Journal of Purchasing and Supply Management, 20 (2), 92–103. doi: https://doi.org/10.1016/j.pursup.2014.03.001
- Krykavskyy, Y., Yakymyshyn, L. (2018). Complexity of marketing and logistics strategies in the supply chain of fast moving consumer goods. Marketing and digital technologies, 2 (1), 21–32. doi: https://doi.org/10.15276/mdt.2.1.2018.2
- Klepikova, O. (2020). On influence of supply firm’s market policy on optimization of its ordering policy within supply chain. Herald of Khmelnytskyi National University, 288 (6), 130–133. doi: https://doi.org/10.31891/2307-5740-2020-288-6-20
- Peng, Y., Lu, Q., Xiao, Y., Wu, X. (2019). Complex dynamics analysis for a remanufacturing duopoly model with nonlinear cost. Physica A: Statistical Mechanics and Its Applications, 514, 658–670. doi: https://doi.org/10.1016/j.physa.2018.09.143
- Sinha, A., Malo, P., Frantsev, A., Deb, K. (2014). Finding optimal strategies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm. Computers & Operations Research, 41, 374–385. doi: https://doi.org/10.1016/j.cor.2013.07.010
- Yue, D., You, F. (2017). Stackelberg-game-based modeling and optimization for supply chain design and operations: A mixed integer bilevel programming framework. Computers & Chemical Engineering, 102, 81–95. doi: https://doi.org/10.1016/j.compchemeng.2016.07.026
- Zijm, H., Klumpp, M., Clausen, U., Hompel, M. ten (Eds.) (2016). Logistics and Supply Chain Innovation. Lecture Notes in Logistics. Springer, 431. doi: https://doi.org/10.1007/978-3-319-22288-2
- Malinovskiy, D. A., Postan, M. Ya. (2012). Ob odnoy veroyatnostnoy modeli funktsionirovaniya portovo-promyshlennogo kompleksa. Metody ta zasoby upravlinnia rozvytkom transportnykh system, 19 (1), 41–54. Available at: https://www.researchgate.net/publication/317021619_Ob_odnoj_veroatnostnoj_modeli_funkcionirovania_portovo-promyslennogo_kompleksa
- Kurudzhi, Y., Moskvichenko, I., Postan, M. (2017). Method of finding equilibrium solutions for duopoly of supply chains taking into account the innovation activity of enterprises. Eastern-European Journal of Enterprise Technologies, 3 (4 (87)), 25–30. doi: https://doi.org/10.15587/1729-4061.2017.103989
- Postan, M., Kurudzhy, Y. (2021). Model of optimal of manufacturing and delivering of final product to consumers taking into account costfor marketing. Development of Management and Entrepreneurship Methods on Transport, 2 (75), 65–76. doi: https://doi.org/10.31375/2226-1915-2021-2-65-76
- Postan, M. Ya., Malynovs’kiy, D. A. (2009). Model of Optimal Planning of Commodities Production and Their Delivery to Consumers by Distribution Channels. Metody ta zasoby upravlinnia rozvytkom transportnykh system, 15, 19–28. Available at: https://www.researchgate.net/publication/318508334_Model_optimalnogo_planirovania_proizvodstva_i_dostavki_produkcii_predpriatia_po_raspredelitelnym_kanalam
- Struchenkov, V. I. (2016). Prikladnye zadachi optimizatsii. Moscow: Solon-Press, 314.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Yuliia Kurudzhy, Iryna Mayorova, Iryna Moskvichenko

This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.