COMPARATIVE ANALYSIS OF IT COMPANIES' PERFORMANCE EFFICIENCY BASED ON THE BENCHMARK DISTANCE METHOD

Abstract

Introduction. In the context of rapid digitalization and global competition, traditional methods of assessing business performance are becoming insufficient for IT sector companies, where intellectual capital and brand strength play a key role. The specific nature of technology enterprises' business models requires the integration of financial indicators with non-financial data reflecting the company's visibility in the digital environment and its attractiveness as an employer.

Purpose. The study aims to substantiate and practically approve an algorithm for comparative analysis of IT companies' performance efficiency based on the benchmark distance method, which allows ranking business entities by the rationality of their business models.

Materials and methods. The information base of the study included the financial statements of Ukrainian IT companies (Uaprom LLC, Rozetka.UA LLC, GlobalLogic Ukraine LLC, TietoEVRY Create Ukraine LLC), as well as non-financial data from Google Trends, GitHub, LinkedIn, and Glassdoor services. The research utilized the benchmark distance method based on Euclidean distance, an expert method for determining significance coefficients of indicators, and data normalization methods.

Results. A sequential algorithm for comparative analysis was developed, including the formation of a list of intangible parameters, the collection of financial indicators, and the calculation of an integral efficiency indicator. A comparative assessment of the selected companies as of 2024 was conducted. It was established that Rozetka.UA LLC (I=0.667) is characterized by the most efficient business model due to high asset turnover and significant activity in the online space, while TietoEVRY Create Ukraine LLC showed the largest deviation from the benchmark (I=0.807).

Discussion. Further research is proposed to focus on expanding the list of non-financial indicators, particularly through analyzing the intensity of software code development in public repositories, and on adapting the proposed methodology for predicting the resilience of IT businesses during crises.