Управління логістичними витратами машинобудівних підприємств

Abstract

Thesis for granting the Degree of Candidate of Economical sciences in specialty 08.00.04 – economy and management of the enterprises (by types of economic activity). – National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2017. The thesis is devoted to the development and scientific substantiation of theoretical, scientific and methodological approaches to the logistics costs management in the conditions of Ukrainian mechanical engineering enterprises functioning. The study analyzes the existing approaches to the management of logistics costs, their classification, the organization of their assessment, accounting, analysis and forecasting, as well as the features of the mechanical engineering that affect the processes. Also, the terminological basis for logistics cost management was studied and improved by the development on logistics costs definition. The main distinctive features of logistics costs as an object of management are revealed and key components of the logistics costs management process are identified. Based on the content analysis of scientific literature, the criteria for classifying logistics costs are generalized and defined, the non-hierarchical faceted classification according to the logistics functions, the stage of logistical processes and the variability of costs over time is proposed. With the help of mathematical method (ID3) for constructing decision trees, the choice of cost management by types of activity is justified as a basis for developing a methodical approach to managing the logistics costs of a mechanical engineering enterprise. Using the methods of system analysis, generalization, as well as interviews with representatives of enterprises of the industry, many significant problems typical for domestic mechanical engineering enterprises were revealed. The paper analyzes trends in the development of mechanical engineering in Ukraine, and describes the technological and organizational processes characteristic in the industry. The specifics and problems of the activity of mechanical engineering enterprises, such as the insufficient use of information technologies, insufficient attention of managers to the systematic accounting of logistics costs, the lack of methodological and information support of these processes at enterprises and the shortcomings of the organizational structure are analyzed. The study substantiates the necessity of developing an effective system for estimating the costs of logistics of a mechanical engineering enterprise by types of its activity, allowing more accurate and detailed assessment and accounting for specific functional areas. The methodical approach to the organization of cost management by types of activity in the conditions of work of the enterprises of mechanical engineering is offered. The complex approach to the organization of decision-making and the use of information technologies in the context of logistics costs management is proposed. It involves the identification of costs, their structural, dynamic and factor analysis, the identification of the places and reasons for the occurrence of the largest logistics costs, making management decisions and their implementation, planning and forecasting of costs. The dissertation offers approaches to information support of these processes and implementation of obtained scientific results at domestic enterprises. The study theoretically substantiates and provides developed practical recommendations on the use of a set of analytical methods that improve the analysis of logistics costs of engineering enterprises. A method is proposed for forecasting logistics costs based on time series analysis, the mathematical base of which is the use of artificial neural networks. The necessary parameters of a three-layer neural network (perceptron) for the purposes of the logistics costs forecasting at mechanical engineering enterprises have been identified and justified, that allows to save resources by freeing up working labor force and increasing the accuracy of planning based on the obtained forecast data.