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Graph models for evaluating production capacities of enterprises

Author

Listed:
  • Natalya V. Kireeva

    (Socio-Economic Institute (branch of the Academy of Labour and Social Relations), Chelyabinsk, Russia)

  • Evgenia S. Zambrzhitskaya

    (Nosov Magnitogorsk State Technical University, Magnitogorsk, Chelyabinsk oblast, Russia)

  • Elena A. Makarova

    (OOO “Russkiy Khleb Food Group”, Magnitogorsk, Chelyabinsk oblast, Russia)

Abstract

The known methods for evaluating production capacities of industrial enterprises mostly submit approximate estimates and are typical of the planned economy. Currently, their practical application is limited, because the product range of companies is no longer fixed. Models created using the graph theory and matrix calculus are capable of overcoming these limitations and providing relevant information support for management decisions. The paper focuses on developing a method for evaluating the production capacity of an enterprise using graph models. Methodologically, the research relies on the graph theory and industrial engineering; applies methods of analysis and synthesis, matrix modelling. The central idea of the proposed models is that an enterprise is a depersonalized production system made up of certain links forming a production chain. To perform relevant calculations the graph model is aligned with the matrix model, which reckons with the main parameters of the production system: technological relationships, product mix, time and material consumption rates, production capacity of each link. The key difference between the graph model and currently existing approaches lies in abandoning the principle of a bottleneck link and switching to the concept of a limiting link, as well as using conditional units of product range. Testing the proposed models on a case of a bakery enterprise proves the efficiency of the method for assessing the production capacity. The developed graph model allows for sound management of production capacities due to the understanding of the flexibility of a product range and technological relationships.

Suggested Citation

  • Natalya V. Kireeva & Evgenia S. Zambrzhitskaya & Elena A. Makarova, 2021. "Graph models for evaluating production capacities of enterprises," Journal of New Economy, Ural State University of Economics, vol. 22(2), pages 134-154, July.
  • Handle: RePEc:url:izvest:v:22:y:2021:i:2:p:134-154
    DOI: 10.29141/2658-5081-2020-22-2-7
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    References listed on IDEAS

    as
    1. Morrison, Catherine J., 1986. "Productivity measurement with non-static expectations and varying capacity utilization : An integrated approach," Journal of Econometrics, Elsevier, vol. 33(1-2), pages 51-74.
    2. de Haan, J. & Naus, F. & Overboom, M., 2012. "Creative tension in a lean work environment: Implications for logistics firms and workers," International Journal of Production Economics, Elsevier, vol. 137(1), pages 157-164.
    3. Tong Zhao & Zhijie Song & Tianjiao Li, 2018. "Effect of innovation capacity, production capacity and vertical specialization on innovation performance in China's electronic manufacturing: Analysis from the supply and demand sides," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    4. Jayaram, Jayanth & Das, Ajay & Nicolae, Mariana, 2010. "Looking beyond the obvious: Unraveling the Toyota production system," International Journal of Production Economics, Elsevier, vol. 128(1), pages 280-291, November.
    5. Zhuo-wan Liu & Tomas Balezentis & Yao-yao Song & Guo-liang Yang, 2019. "Estimating Capacity Utilization of Chinese State Farms," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    6. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2019. "Estimating capacity utilization of Chinese manufacturing industries," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 94-110.
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    More about this item

    Keywords

    production capacity; production system; product mix; graph theory; matrix modelling; enterprise;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • M29 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Other

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