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Methodological approach for determining the size of the optimal raw material zone in the logistics system of dairy processing enterprise

Author

Listed:
  • Antoshchenkova, Vitalina
  • Onegina, Viktoriya
  • Gutsul, Tetiana
  • Boblovskyi, Oleksandr
  • Kravchenko, Yuliia

Abstract

Purpose. The purpose of the article is the improvement of the methodological approach for determining the optimal raw material area in the logistics system of a milk processing enterprise using economic-mathematical tools. Methodology / approach. The research is based on the applying such methods as analysis, synthesis, generalization, induction, deduction – to determine the content and subsystem of the logistic system of milk processing plant, factors of the size of the raw material area of the milk processing enterprise, formulating conclusions regarding the methodological approach to assessing its rational size; economic-mathematical modeling and cluster analysis – to determine the rational size of the raw material area of the milk processing enterprise; graphic – for a visual presentation of the cluster analysis of the raw material zone of the milk processing enterprise according to the Ward’s method. The research was carried out on the basis of statistical data of the Main Department of Statistics in Chernihiv Region, reports of agricultural enterprises of Chernihiv Region and data of the authors’ own observations for 2011–2021 (for the calculation of some indicators, data for 2020–2021 were used). Results. The peculiarities, role and tasks of logistics in the dairy sub-complex were determined, a conceptual model of the logistics system for the milk processing plant was developed, which consists of functional and provisional subsystems and covers production, purchasing, transport, certification, storage and processing processes, minimizes logistical risks. In order to identify reserves of the optimization of the raw material area, a cluster analysis was conducted (the Ward’s method was chosen as the clustering method), based on data on the volume of milk purchases, distance from the factory and potential opportunities for expanding the raw material area. The economic-mathematical model was designed, which allows determining the optimal raw material area of the processing enterprise based on the criterion of minimum transport costs for the delivery of dairy raw materials, as well as determining the optimal structure of dairy production based on the criterion of minimum technological costs of processing raw materials in the production of various types of milk products, taking into account the volume of consumer demand. The economic-mathematical model was tested and used to determine the rational distance of milk producers from the milk processing enterprise at a distance of 46–56 km in the studied region. Originality / scientific novelty. The methodical approach to determine the optimal raw material area in the logistics system of a milk processing enterprise has been improved by using economic-mathematical tools and applying cluster analysis according to the Ward’s method. Practical value / implications. The results of the study can be used to calculate the optimal raw material area of milk processing enterprises, which will contribute to the sustainable development of the dairy sub-complex, of all its participants, from producers of raw materials (milk) to the final consumer.

Suggested Citation

  • Antoshchenkova, Vitalina & Onegina, Viktoriya & Gutsul, Tetiana & Boblovskyi, Oleksandr & Kravchenko, Yuliia, 2023. "Methodological approach for determining the size of the optimal raw material zone in the logistics system of dairy processing enterprise," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(01), March.
  • Handle: RePEc:ags:areint:337426
    DOI: 10.22004/ag.econ.337426
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    References listed on IDEAS

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    1. Alexandra Brintrup & Johnson Pak & David Ratiney & Tim Pearce & Pascal Wichmann & Philip Woodall & Duncan McFarlane, 2020. "Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3330-3341, June.
    2. Chowdhury, Md Maruf H. & Quaddus, Mohammed, 2017. "Supply chain resilience: Conceptualization and scale development using dynamic capability theory," International Journal of Production Economics, Elsevier, vol. 188(C), pages 185-204.
    3. Mona Haji & Laoucine Kerbache & Mahaboob Muhammad & Tareq Al-Ansari, 2020. "Roles of Technology in Improving Perishable Food Supply Chains," Logistics, MDPI, vol. 4(4), pages 1-24, December.
    4. Sara Saberi & Mahtab Kouhizadeh & Joseph Sarkis & Lejia Shen, 2019. "Blockchain technology and its relationships to sustainable supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2117-2135, April.
    5. Onegina, Viktoriya & Megits, Nikolay & Kravchenko, Olha & Kravchenko, Yuliia, 2022. "Price transmission in milk supply chain in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 8(01), March.
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