Identification and evaluation of the impact of uncertainty factors on the activities of agricultural enterprises

Abstract

The article considers t the problem of determination of the degree of influence of uncertainty factors on the performance of an agricultural enterprise. Uncertainty and risk are an integral part of business life, and in agriculture they are all the more significant, since agricultural companies are greatly dependent on the influence of natural factors and phenomena. Consequently, the assessment of the directions and the strength of the impact of risk factors is of great importance for the plans and projects for the company's activities. After carrying out a schematic factor analysis of the financial results of the agricultural enterprise, the author selected parameters such as crop yields and average selling price, for analyzing the degree of exposure to uncertain factors. Since both the selected parameters are affected by a large number of both certain factors and factors uncontrollable for the company's management, the author finds it unacceptable to apply factor analysis to them. In the first place, the author justifies this by the difficulty in determining the weights of each influencing factor. Instead, the author suggests grouping all the factors on the basis of their certainty and definition of the influence degree for each group. For this purpose, the variability of each parameter in different series was analyzed: for several years in one enterprise and for one year in a number of similar enterprises. It was found that fluctuations in crop yields by enterprises were higher than by years. This forced the author to bring out the conclusion that there is a significantly greater influence of certain factors on this indicator. On the other hand, when analyzing prices, the opposite situation emerged: here the influence of uncertain factors is much stronger. As a result, the proposal was made for the projecting method, such as economic and mathematical modeling, to use the data from both the firm being the subject of modeling, and from the similar enterprises available from the regional Department of Agriculture. In this case, the accuracy of the forecast will be much higher, besides, it can be developed in 3 or 5 probability scenarios.