Abstract
The article is concerned with developing mathematical support and algorithms for solving the problem of economic diagnostics of enterprises. IT-companies and start-ups (IT projects) that have special characteristics during the growth period were selected as the object of research. Based on the system analysis of data domain there has been developed a system of quantitative and qualitative characteristics to identify the economic state of the IT companies and start-ups in the external and internal environment. Scales of indices of different nature have been determined. Methods to introduce order and equivalence relations for the found peer companies have been given in order to compare their proximity to the analyzed company. Metrics used for comparing the companies are considered taking into account the quantitative and qualitative characteristics. The possibilities of distributing innovative IT projects using fuzzy clustering algorithms are considered. The comparative analysis of two basic algorithms - Fuzzy Classifier Means algorithm and Gustafson - Kessel algorithm - has been given. The clustering procedure for each algorithm is shown, as well as the graphic results of their operation. There was done the clustering quality assessment using a distribution coefficient, entropy of classification, and Hie-Beni index. It has been inferred that using Gustafson - Kessel algorithm provides better results for solving the problem of splitting IT projects for their economic diagnostics
Highlights
The task of estimation is one of the low-formalized tasks of economic systems management under conditions of uncertainty
The article is concerned with developing mathematical support and algorithms for solving the problem of economic diagnostics of enterprises
Metrics used for comparing the companies are considered taking into account the quantitative and qualitative characteristics
Summary
The task of estimation is one of the low-formalized tasks of economic systems management under conditions of uncertainty. It is possible to construct various functions for selecting CK (IT) and CD (IT) in case the absence of information about the relative importance of characteristics and the availability of characteristics of both quantitative and qualitative type They narrow the Pareto set and take into account only the mutual relations between the estimates of the analogs without taking into account the absolute values of the differences in the estimates by characteristics. The use of such indicators for economic diagnostics of an IT start-up is difficult, as for the decision-making on investment it is necessary to take into account the financial component of the project, and risks, finance, marketing and others This means that the IT project needs to be evaluated according to certain groups of criteria.
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