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Optimization modeling of business processes of engineering service enterprises in the national economy

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Category: Content №4 2021

Last Updated on 23 August 2021

Published on 30 November -0001

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Authors:

L.Trachenko, orcid.org/0000-0002-5505-1345, Odesa National University of Economics, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L.Lazorenko, orcid.org/0000-0002-8505-1768, State University of Telecommunication, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Ye.Maslennikov, orcid.org/0000-0001-6400-7840, Odesa National I.I.Mechnikov University, Odesa, Ukraine

Yu.Hrinchenko, orcid.org/0000-0002-9439-5933, Odesa National I.I.Mechnikov University, Odesa, Ukraine

I.W.E.Arsawan, orcid.org/0000-0001-8493-5249, Politeknik Negeri Bali, Bali, Indonesia

V.Koval, orcid.org/0000-0003-2562-4373, National Academy of Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2021, (4): 165 - 171

https://doi.org/10.33271/nvngu/2021-4/165

Abstract:

Purpose. Construction of an economic and mathematical model of the optimal organization of a system of business processes and its testing at an enterprise in the field of engineering services.

Methodology. Methods of analysis and synthesis, systematization, theoretical generalization are used to study approaches to optimizing business processes of enterprises; modeling to create an economic and mathematical model of the optimal organization of the system of business processes; approbation of the developed model at an enterprise in the field of engineering services.

Findings. The article proves the need to assess the impact of various economic factors on the financial results of economic activities of enterprises and the construction of business systems of enterprises, economic and mathematical models for their optimization. It has been determined that business process modeling is an effective means of improving quality management systems in accordance with the requirements of the international standard ISO 9001:2015, determining, identifying and minimizing the risks of enterprises, ensuring their successful activities in general. An economic and mathematical model has been developed for the optimal organization of the system of business processes of an enterprise as a means of maximizing the total profit from the implementation of works and services.

Originality. An economic and mathematical model of the optimal organization of the system of business processes of enterprises in the field of engineering services has been built as an effective tool for improving their quality management systems and activities in general.

Practical value. The use of the constructed economic and mathematical model of the optimal organization of the system of business processes of enterprises in the field of engineering services will provide the management team with important information for making management decisions aimed at improving quality management systems, achieving key business goals and maximizing profits.

Keywords: business process system, economic and mathematical model, profit maximization, engineering services, business process costs, quality management systems, ISO 9001:2015

References:

1. Korzachenko, O., & Getman, V. (2011). Modelling the Choice of Optimal Structural Business Process Model in a Telecommunications Company. Computer Sciences, 45, 36-42. https://doi.org/10.2478/v10143-011-0039-9.

2. Babikova, A.V., Korsakov, M.N., & Sarafanov, A.D. (2017). Optimization of business processes of an industrial enterprise through the introduction of a process approach. Kreativnaya ekonomika, 11, 1195-1208. https://doi.org/10.18334/ce.11.11.38474.

3. Indulska, M., Recker, J., Rosemann, M., & Green, P. (2009). Business process modeling: Current issues and future challenges. InInternational Conference on Advanced Information Systems Engineering, (pp. 501-514). Berlin: Springer. https://doi.org/10.1007/978-3-642-02144-2_39.

4. Chukhra, N.I., & Matviy, S.I. (2015). Business process reengineering in the centralization of the industrial enterprises management. Marketing and Management of Innovations, (3), 172-181.

5. Chukurna, ., Nitsenko, V., Kralia, V., Sahachko, Y., Morkunas,M., & Volkov, A. (2019). Modelling and managing the effect of transferring the dynamics of exchange rates on prices of machine-building enterprises in Ukraine. Polish Journal of Management Studies,19. https://doi.org/10.17512/pjms.2019.19.1.09.

6. Luong, D.L., Tran, D.H., & Nguyen, P.T. (2021). Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution.International Journal of Construction Management, 21(3), 271-283. https://doi.org/10.1080/15623599.2018.1526630.

7. Vom Brocke, J., & Mendling, J. (2018). Business process management cases. Digital Innovation and Business Transformation in Practice. Springer. https://doi.org/10.1007/978-3-662-63047-1.

8. Melnyk, O.H., Mukan, O.V., & Zlotnik, M.L. (2019). Features of business processes modeling and its optimization in the context of international activities. Management and Entrepreneurship in Ukraine, 1(2), 43-52. https://doi.org/10.23939/smeu2019.02.043.

9. Mekonnen, N. (2019). Implementing business process reengineering (BPR) in government organization. International Journal of Advanced Research, (7), 109-120. https://doi.org/10.21474/IJAR01/9482.

10. Inghels, D. (2020). Introduction to Modeling Sustainable Development in Business Processes: Theory and Case Studies. Springer Nature. https://doi.org/10.1007/978-3-030-58422-1.

11. Prez-lvarez, J.M., Mat, A., Gmez-Lpez, M.T., & Trujillo,J. (2018). Tactical Business-Process-Decision Support based on KPIs Monitoring and Validation. Computers in Industry, 102, 23-39. https://doi.org/10.1016/j.compind.2018.08.001.

12. Kotenko, S., Nitsenko, V., Hanzhurenko, I., & Havrysh, V. (2020). The Mathematical Modeling Stages of Combining the Carriage of Goods for Indefinite, Fuzzy and Stochastic Parameters. International Journal of Integrated Engineering, 12(7), 173-180. https://doi.org/10.30880/ijie.2020.12.07.019.

13. Trachenko, L., Verkhoglyadova, N., Shevchenko, N., Kononova,I., & Sokolovska, I. (2020) Assessment of quality management systems of service companies. Intellectual economics, 14(1), 45-66. https://doi.org/10.13165/IE-20-14-1-03.

14. Baiyere, A., Salmela, H., & Tapanainen, T. (2020). Digital transformation and the new logics of business process management. European Journal of Information Systems, 29(3), 238-259. https://doi.org/10.1080/0960085x.2020.1718007.

15. Hutsaliuk, O., Koval, V., Tsimoshynska, O., Koval, M., & Skyba,H. (2020). Risk Management of Forming Enterprises Integration Corporate Strategy. TEM Journal, 9(4), 1514-1523. https://doi.org/10.18421/TEM94-26.

16. Arsawan, I.W.E., Koval, V., Rajiani, I., Rustiarini, N.W., Supartha, W.G., & Suryantini, N.P.S. (2020). Leveraging knowledge sharing and innovation culture into SMEs sustainable competitive advantage. International Journal of Productivity and Performance Management [Unpublished manuscript]. https://doi.org/10.1108/IJPPM-04-2020-0192.

17. Meidan, A., Garca-Garca, J.A., Escalona, M.J., & Ramos, I. (2017). A survey on business processes management suites. Computer Standards & Interfaces, 51, 71-86. https://doi.org/10.1016/j.csi.2016.06.003.

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