Toolkit for managing the growth of the resource potential at agrarian enterprises

Abstract

The paper considers the composition of the toolkit for managing the growth of the resource potential at agrarian enterprises within the framework of the relevant mechanism and substantiates the procedures for its application in the context of increasing the competitiveness and efficiency of the activities at the mentioned business entities. The mechanism for managing the resource potential of an agrarian enterprise with appropriate tools is proposed, which allows to ensure the effective use of the resource potential, its effective management and economic stability of the agrarian enterprise based on the methodology of assessing the efficiency of using resource potential based on a multidimensional comparative analysis. The priority directions for the growth of the efficiency of using resources and production potential have been determined, which are related to the increase in the intensity of using production resources, their balance, the optimal combination of cluster membership of agricultural enterprises, which lead to a positive multiplier effect and an increase in the economic efficiency of agricultural production. It was established that the most objective procedure in the study of economic growth and efficiency of the agrarian sector of the economy is to conduct a multifactorial analysis, which is expedient to carry out taking into account the clustering that was provided in the study. The methodical approach to managing the resource potential of an agrarian enterprise has been developed, the essence of which results in the definition of the functional dependence between resource costs in the consumption process and the effective indicator of the produced goods based on the set of consumer properties, that is, a number of production parameters that are formed in the process of product consumption in subsequent production cycles. Keywords: economic development, resource potential, production potential, management tools, cluster analysis.