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Simulation experiments of supply chain in a period of small and big disasters

Author

Listed:
  • Halicki Marcin

    (Department of Regional Policy and Food Economy, College of Natural Sciences, The University of Rzeszów, Rzeszów, Poland)

  • Kwater Tadeusz

    (Department of Computer Science, Institute of Technical Engineering, State University of Technology and Economics in Jarosław, Jarosław, Poland)

Abstract

Aim/purpose – The aim of this paper is to present a strategy that allows companies to recover from disasters, when creating a supply chain. Furthermore, it also shows the impact on the company’s resources that are used in the implementation of the strategy in case of small and big disasters. Thanks to the proposed solution, it is possible to analyze each company individually, as well as in groups, at any given time.

Suggested Citation

  • Halicki Marcin & Kwater Tadeusz, 2021. "Simulation experiments of supply chain in a period of small and big disasters," Journal of Economics and Management, Sciendo, vol. 43(1), pages 339-356, May.
    • Handle: RePEc:vrs:jecman:v:43:y:2021:i:1:p:339-356:n:14
    DOI: 10.22367/jem.2021.43.16
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    References listed on IDEAS

    as
    1. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
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    More about this item

    Keywords

    supply chain; disaster; strategy; threats; simulations;
    All these keywords.

    JEL classification:

    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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