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Analysis of influencing factors on the development of agricultural enterprises based on e-commerce technologies

Journal: Agricultural and Resource Economics: International Scientific E-Journal (Vol.6, No. 4)

Publication Date:

Authors : ; ; ; ; ;

Page : 211-231

Keywords : agricultural enterprises; factors; e-commerce; management decisions; development.;

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Abstract

Purpose. The purpose of the study is to analyze and systematize the factors that affect the development of agricultural enterprises based on e-commerce technologies. To achieve this goal, it is necessary to: perform expert research to identify the list of factors and establish their relative importance; identify structural components that are common to all factors and apply cluster analysis to build a cluster of factors and dendrites; classify factors and build a method of taking into account factors in the formation of informed management decisions. Methodology / approach. During the study, the method of expert assessments was used, namely the method of questionnaires to collect the primary information needed to identify the list of factors and establish their relative importance. Cluster analysis (ball method and clast_izomorf_trec specification of the Microsoft Excel) and structural-process scientific approach were used to identify the nature of the relationships between factors and their grouping, which allowed building clusters and dendrites of factors. A system-dynamic scientific approach is used to form the classification of factors and to formulate the essence of the concepts “potential of factors to change the trajectory of conditions in which business decisions are formed” and “trajectory of change of conditions”. Results. It is proved that the development of agricultural enterprises based on e-commerce technologies is influenced by a number of factors that should be classified by content, nature, significance and structural similarity. The selection of these classification features and their corresponding groups of factors is necessary to enable the analytical processing of management information, in particular in the course of management decisions involving the use of e-commerce technologies. Unlike others, the proposed classification of factors is built by identifying their structural similarity. This became the basis for introducing into economics the concepts of “potential factors to change the trajectory of conditions in which business decisions are formed”, “trajectory of changing conditions”, as well as the development of a method of taking into account selected factors in management decisions. Originality / scientific novelty. For the first time, it was introduced into economics the concept of “potential of factors to change the trajectory of conditions in which business decisions are formed” and “trajectory of changing conditions”. These concepts are formulated on the basis of identifying the structural similarity of factors and measuring isomorphic distances between them. In the categorical-conceptual apparatus of economic analysis, these concepts will clarify the subject of parameterization of factors. The following was further developed: a) classification of factors influencing the development of agricultural enterprises on the basis of e-commerce technologies, which, in contrast to existing ones, is based on the selection of classification features and, within them, the types of factors; b) a method of factor consideration that differs from existing ones in that it clarifies the isomorphic nature of these factors and the relationships between them. This allows parameterizing factors and takes them into account when making management decisions. Practical value / implications. The classification of factors is constructed; the method of the account of these factors during formation of administrative decisions is developed. This is an applied tool for choosing the optimal management solution from a number of alternatives. The proposed classification and the constructed method can be used to model application software as a specification of existing decision support systems.

Last modified: 2021-05-25 00:41:10