CLUSTER ANALYSIS APPROACHES TO ASSESSING THE FINANCIAL AND ECONOMIC ACTIVITIES OF ENTERPRISES
Journal Title: Комп’ютерне моделювання: аналіз, управління, оптимізація - Year 2019, Vol 1, Issue 1
Abstract
The article is devoted to the financial and economic assessment of the state of road transport enterprises in Ukraine through the use of multidimensional statistical cluster analysis. The article solved the task of analyzing the financial and economic state of enterprises in Ukraine for 2013-2017 years in the STATISTICA software product, taking into account financial and economic indicators. The study used four groups of indicators: liquidity, financial stability, business activity, profitability according to the financial statements of ten road transport enterprises. The use of the k-means method and the agglomerative tree-clustering method made it possible to divide enterprises into three clusters that reflect their state: crisis, pre-crisis, and non-crisis. When the k-means method is used, the initial centers of the clusters are specified by the method of sorting the distance and selecting observations at constant intervals, observations that maximize the initial distances between the clusters are chosen. The value of intergroup and average group variances, the F parameter and the level of significance were obtained, which made it possible to identify financial and economic indicators that are most informative for the clustering process using the k-means method. For clustering using the agglomerative tree-clustering method, the single link method was taken as the clustering rule. As a result of clustering, a dendrogram was constructed, which allows determining the clusters depending on the distance between them. This made it possible to analyse the characteristics of various aspects of the financial condition of the enterprise, to identify the parameters that form the initial clusters of the state of enterprises, and the clusters, which form separate clusters and gradually join the first clusters. A horizontal tree diagram of road transport enterprises has been built, which reflects enterprises that are closely shrinking with each other and form new clusters by combining. The clusters obtained using the method of k-means and agglomerative method of tree clustering were analyzed and conclusions regarding their state were drawn.
Authors and Affiliations
В. Р. Писарькова, Н. Ю. Науменко
Keywords
Related Articles
- EP ID EP642559
- DOI 10.32434/2521-6406-2019-5-1-63-69
- Views 128
- Downloads 0
Интеллектуальная система поддержки принятия решений по управлению доменной плавкой
Представлены функциональные и алгоритмические особенности разработанной в Институте черной металлургии интеллектуальной системы поддержки принятия решений по управлению доменной плавкой. Идеология построения интеллектуал...
RECOGNITION AND GENERATION OF QR/BAR CODES IN MOBILE APPLICATIONS
The article is devoted to the analysis of methods of recognition and generation of QR/bar codes in mobile applications. The most common algorithms for detecting and generating codes are considered: Otsu method, Reed-Solo...
Метод пакетного навчання нейромереж нелінійної авторегресії для прогнозу прибутку інтернет-магазину
У статті розглядаються і аналізуються існуючі методи прогнозування прибутку інтернет-магазину. В сучасній електронній комерції є проблема недостатньої ефективності автоматизації бізнес-процесів інтернет-магазину. Ґрунтую...
About methods of dynamically constructing graphical user interface based on the structure of applied ontology
Modern tools for developing user interfaces, namely, interface builders and user interface management systems, offer a simpler, more convenient and understandable approach to developing user interfaces. To implement the...
Algorithm to solve a problem of optimum separation of sets with additional couplings
Problems of manufacturing arrangement have been considered for more than a century. However, they are still topical. For instance, despite the fact that a number of models and techniques to solve discrete problems of arr...