Özet:

The object of research is the process of self-financing, as a leading direction in the system of investment support for the development of business entities. One of the most problematic places in resolving this issue is prioritizing these investments. During the study, the statistical method is used to analyze and summarize statistical information and the methods of cluster analysis and k-means to classify the main groups of indicators of technical and operational and economic and marketing parameters for the use of agricultural machinery. As well as methods of matrix analysis and multidimensional spaces – for the positioning of enterprises and the rationale for the choice of investment areas. The paper proposes theoretical and methodological principles and conclusions, which together solve an important practical problem – the need to search for areas of investment in the development of individual parameters of agricultural machinery. The analysis of the state and characteristics of the activities of agricultural engineering enterprises of Ukraine is made. The necessity of breakthrough development of the machine-building sector of the agro-industrial complex is emphasized. It is noted that most of the Ukrainian enterprises producing agricultural machinery have outdated equipment, so they need re-equipment and significant financial injections. When classifying the priority areas of investment, it is found that agricultural machinery, which is now produced by Ukrainian engineering enterprises, needs to be completely changed. Therefore, a list of stages for the selection of areas for improving tractor equipment is proposed. The proposed approach to determining the priority of investing provides for the classification of quality indicators according to the priority of their improvement according to a certain algorithm. The investment areas are evaluated and it is established that the final decision on investing in the development of certain parameters of agricultural machinery can be made by improving only those indicators of a certain group that were obtained using clustering. Due to the simplicity of the proposed approach, it can be applied not only for agricultural engineering, but also for other enterprises of the economic complex of Ukraine. Compared with similar well-known approaches, its use will allow more accurate research and obtain the necessary data for targeted investment in the face of limited funds. Author Biographies Olena Kitchenko, National Technical University «Kharkiv Polytechnic Institute», 2, Kyrpychova str., Kharkiv, Ukraine, 61002 PhD, Associate Professor Department of Economics and Marketing

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