Conceptual grounds of modelling and managing logistics risk of an enterprise

Vitlinskyy Valdemar V. () and Skitsko Volodymyr I. ()
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Vitlinskyy Valdemar V.: Kyiv National Economic University named after. V. Getman
Skitsko Volodymyr I.: Kyiv National Economic University named after. V. Getman

The Problems of Economy, 2013, issue 4, 246_253

Abstract: The article considers theoretical and methodological problems on managing and modelling logistics risk of an enterprise. It shows that managerial decisions in logistics are made in situations, which are characterised with: uncertainty and randomness of results of the risky activity; conflict; counteraction; multi-variance of solution; when simultaneously not all alternative variants of solutions are similarly favourable. The article analyses existing approaches to definition of the "logistics risk" term and offers own definition: logistics risk of an enterprise is an economic category, which reflects specific features of perception by enterprise management of objectively existing uncertainty and conflict, absence of a complete (exhaustive) information at the moment of decision making, which are inherent in the processes of forecasting, planning, managing, co-ordinating and controlling the material, service, information and financial flows and the flow of intellectual and labour resources. Moreover, the article gives own interpretation of the object, subject and source of logistics risk of an enterprise. It considers existing approaches to classification of the logistics risk of an enterprise and offers the one, pursuant to which the logistics risk of an enterprise could be classified by types of flows and components of the logistics system of different levels. It studies the problem of building the system of management of logistics risk at an enterprise and offers own view on solution of this problem. It analyses scientific instruments of the economic and mathematical modelling of the logistics risk of an enterprise.

Keywords: logistics risk of an enterprise; management; modelling; logistics risk management (search for similar items in EconPapers)
Date: 2013
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