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Multilevel prognosis of logistics chains in case of uncertainty: information and statistical technologies implementation

1
Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
2
Chistopol autonomous campus, Kazan National Research Technical University, Kazan, Russia
*
Author to whom correspondence should be addressed.
J. Open Innov. Technol. Mark. Complex. 2018, 4(1), 2; https://doi.org/10.1186/s40852-018-0081-8
Received: 31 October 2017 / Accepted: 10 January 2018 / Published: 29 January 2018
Effective, strategic, current and operational management of modern logistics systems requires continuous monitoring and forecasting of their condition in many parameters. Especially these questions are critical in justifying the need for modernization or technical re-equipment of the logistics chains, when the issue for the evaluation of its technical and economic potential is relevant. It can be concluded that there is the need to study the issues of formation of scientifically based logistics solutions. Moreover, by analogy with the systems theory in engineering, it comes to research of the effectiveness of these decisions in conditions of limited, incomplete and often inaccurate information. In general, investment decision on logistics chain modernization is an evaluation of the proposed alternatives for the manager using a set of indicators. It seems to be appropriate to use a method of the potential distribution of probabilities when manager know only the data of relevant characteristics of the logistics chain projects. The application of the method is presented and it is shown that the quantitative estimates calculated by this method are relative and strongly depend on the choice of the base project.
Keywords: Logistics chain, Generalized indicator, Bayesian criterion, Shannon entropy, Subjectivity Logistics chain, Generalized indicator, Bayesian criterion, Shannon entropy, Subjectivity
MDPI and ACS Style

Lukashevich, N.; Svirina, A.; Garanin, D. Multilevel prognosis of logistics chains in case of uncertainty: information and statistical technologies implementation. J. Open Innov. Technol. Mark. Complex. 2018, 4, 2. https://doi.org/10.1186/s40852-018-0081-8

AMA Style

Lukashevich N, Svirina A, Garanin D. Multilevel prognosis of logistics chains in case of uncertainty: information and statistical technologies implementation. Journal of Open Innovation: Technology, Market, and Complexity. 2018; 4(1):2. https://doi.org/10.1186/s40852-018-0081-8

Chicago/Turabian Style

Lukashevich, Nikita, Anna Svirina, and Dmitry Garanin. 2018. "Multilevel prognosis of logistics chains in case of uncertainty: information and statistical technologies implementation" Journal of Open Innovation: Technology, Market, and Complexity 4, no. 1: 2. https://doi.org/10.1186/s40852-018-0081-8

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