Business process reengineering in retail: optimizing a company's distribution network

Vagonova O. H.; Kasyanenko L. V.; Chornobaev V. V.; Ashcheulova O. M.; Harzha M. S.

Article

Issue:	2024 №4 (88)
Section:	Trade
UDK:	658.5:339.37
DOI:	https://doi.org/10.33271/ebdut/88.130
Article language:	Ukrainian
Pages:	130-140
Title:	Business process reengineering in retail: optimizing a company's distribution network
Authors:	Vagonova O. H., Dnipro University of Technology, Kasyanenko L. V., Dnipro University of Technology, Chornobaev V. V., Dnipro University of Technology, Ashcheulova O. M., Dnipro University of Technology, Harzha M. S., Dnipro University of Technology
Annotation:	Methods. The study is based on the use of the following methods: classification of retail enterprises by logistical, territorial and organizational characteristics; a system approach to designing logistics networks; discrete and continuous modeling for optimizing the distribution network. Particular attention is paid to the analysis of corporate strategies and market conditions that affect the design of distribution networks. Results. The study showed that reengineering of business processes in retail trade contributes to the formation of competitive distribution networks. The analysis of classifications of retail enterprises was conducted and tools were proposed for their rational grouping, taking into account the assortment, regional features and organizational structure. It was determined that the implementation of modern logistics strategies allows reducing service costs, improving the quality of customer service and ensuring flexibility of logistics processes. The proposed approaches contribute to adaptation to changes in the market environment, which is especially relevant in conditions of growing competition. The main factors influencing the choice of modeling methods are identified and recommendations for building optimal logistics networks are developed. Novelty. A comprehensive approach to designing logistics networks is proposed, which combines simplified and complex modeling methods for effective resource management. Special emphasis is placed on the integration of corporate strategy with logistics processes and taking into account changing market conditions. Practical value. The results of the study have significant practical value for retail enterprises that seek to increase their efficiency in a dynamic market. The proposed modeling methods allow reducing transportation and warehousing costs, as well as optimizing inventory levels. The use of modern approaches to designing logistics networks contributes to an increase in the level of customer service and increasing their loyalty. Recommendations for choosing logistics strategies can be applied not only in retail trade, but also in other sectors of the economy where optimization of logistics processes is necessary. The implementation of the proposed approaches allows enterprises to adapt to changing market conditions, increase the efficiency of resource use, and ensure long-term sustainability of business.
Keywords:	Reengineering, Business processes, Retail, Logistics network, Distribution network, Corporate strategy, Optimization
File of the article:	EV20244_130-140.pdf
Literature:	1. Al-Refaie, A., & Kokash, T. (2022). Optimization of Sustainable Reverse Logistics Network with Multi-Objectives Under Uncertainty. Journal of Remanufacturing, vol. 1, pp. 1-23. https://doi.org/10.1007/s13243-022-00118-5 2. Dyer, J.S., Fishburn, P.C., Steuer, R.E., Wallenius, J., & Zionts, S. (1992). Multiple Criteria Decision Making, Multiattribute Utility Theory: The Next Ten Years. Management Science, vol. 38, no. 5, pp. 645-654. https://doi.org/10.1287/mnsc.38.5.645 3. Erlenkotter, D. (1989). The General Optimal Market Area Model. Annals of Operations Research, vol. 18, pp. 43-70. https://doi.org/10.1007/bf02097795 4. Fisher, M. L. (1997). What Is the Right Supply Chain for Your Product?, Harvard Business Review, vol. 75, no. 2, pp. 105-116. 5. Gattorna, J. (2015). Dynamic Supply Chains: How to Design, Build and Manage People-Centric Value Networks, 3rd ed, Pearson Education, London, UK. 6. Heckmann, I. (2016). Location Logistics in Supply Chain Management, Springer Gabler, Wiesbaden, Germany. 7. Henning, M.A. & van Vuuren, J.H. (2022). Graph and Network Theory: An Applied Approach Using Mathematica, Springer, New York, USA. 8. Huang, G., & Zhang, D. (2021). Globally Optimal Facility Locations for Continuous-Space Facility Location Problems. Applied Sciences, vol. 11, no. 16, pp. 1-25. https://doi.org/10.3390/app11167321 9. Keeney, R.L., & Raiffa, H. (1993). Decisions with Multiple Objectives: Preferences and Value Tradeoffs, Cambridge University Press, New York, USA. 10. Rushton, A., Croucher, P., & Baker, P. (2017). The Handbook of Logistics & Distribution Management, 6th ed, Kogan Page Publishers, London, UK. 11. Saaty, T.L,. & Vargas, L.G. (2012). Models, Methods, Concepts & Applications of the Analytic Hierarchy Process, Springer Science+Business Media, New York, USA. https://doi.org/10.1007/978-1-4614-3597-6 12. Schniederjans, M.J. (2013). Goal Programming, in Gass, S.I., & Fu, M.C. (eds.), Encyclopedia of Operations Research and Management Science, Springer, New York, USA, pp. 658-661. https://doi.org/10.1007/978-1-4419-1153-7_393 13. Shavarani, S.M., López-Ibáñez, M., & Knowles, J.D. (2023). An Interactive Decision Tree- Based Evolutionary Multi-Objective Algorithm. Evolutionary Multi-Criterion Optimization, Conference Proceedings, pp. 620-634. https://doi.org/10.1007/978-3-031-27250-9_44 14. Werner, F. (2019). Discrete Optimization: Theory, Algorithms, and Applications. Mathematics, vol. 7, no. 5, p. 397. https://doi.org/10.3390/math7050397.

Home