Diagnostics of Monetary Assets of Ukrainian Agribusiness Entities: Relevance, Peculiarities, and the Process of Algorithm Construction Cover Image
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Diagnostics of Monetary Assets of Ukrainian Agribusiness Entities: Relevance, Peculiarities, and the Process of Algorithm Construction
Diagnostics of Monetary Assets of Ukrainian Agribusiness Entities: Relevance, Peculiarities, and the Process of Algorithm Construction

Author(s): Inna NAZARENKO, Alvina Oriekhova
Subject(s): Economy, Business Economy / Management, Agriculture
Published by: ASERS Publishing
Keywords: algorithm; monetary assets; mixed monetary assets; diagnostics; neuron network; principle

Summary/Abstract: The purpose of the article is to provide the scientific ground of the organizational and methodological aspects and the construction of algorithm for the monetary assets (including mixed assets) diagnostics for the agrarian entities. The findings are to be based on the complementary synthesis of the dominant principles of the diagnostic process. Their practical implementation will allow a reliable assessment of the assets as well as to identify in a timely manner the influence of the external and internal factors of destructive nature. The application of cognitive economic and mathematical methods will provide a prediction of the financial result, clear definition of prospective managerial initiatives and outline the strategic scenario for the development of agribusiness entities. Violation of payment discipline, the decrease of funds mobility of Ukrainian agribusiness entities and deterioration of the basic parameters of their financial condition is proven to occur under the current situation. The necessity of using diagnostics as an efficient management mechanism is substantiated. The algorithm of the diagnostic process of monetary assets (including mixed assets) is developed, which structural decomposition represents the integrity of the preparatory, research and final stages.

  • Issue Year: VIII/2017
  • Issue No: 07 (23)
  • Page Range: 1373-1380
  • Page Count: 8
  • Language: English