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Author: search.filters.author.Borisoglebskaya, L. N.Subject: search.filters.subject.Commerce

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    Item type:Publication,
    Predictive methodology for assessing periodic market fluctuations
    (2021-01-01)
    Sergeev, S. M.
    ;
    Barykin, S. E.
    ;
    Burova, A. Yu
    ;
    Borisoglebskaya, L. N.
    ;
    Buniak, V. L.
    The paper presents the results of developing algorithms aimed at optimizing managerial decision-making in commerce. The most difficult task in constructing algorithms for supporting managerial decisions within the Industry 4.0 paradigm is to develop an interface for machine-to-machine interaction between data flows describing the current market demand and software-controlled subsystems of digital logistics platforms. Several problems have to be solved, taking into account diverse criteria. We used methods of stochastic mathematical modeling, queuing theory and the theory of optimal decisions, proposing a procedure for assessing periodic movements of consumer demand with uncertain dynamics of market indicators. A convenient implementation is offered in the form of software for digital logistics platforms, relevant for a wide range of business applications.