The trajectories of companies’ financial architecture in the real economy

  • Received January 31, 2020;
    Accepted February 26, 2020;
    Published March 6, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.17(1).2020.11
  • Article Info
    Volume 17 2020, Issue #1, pp. 119-133
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The formation of an effective company’s financial architecture, which includes such basic elements as the capital structure, ownership structure, and the state of corporate governance, has a significant impact on maintaining a certain market position and ensuring stable profitability of activity. This research aims at determining the state of financial architecture, changing its trajectory, and its impact on company’s market position. Twenty-two (22) Ukrainian companies were selected for the study from the list of top 200 in terms of the largest volume of sales revenue received, and those that provided full financial statements for the period from 2007 till 2017. To determine the state of company’s financial architecture and the relevant market position, the authors used a cluster analysis using the method of the most remote neighbors. Algorithms of Kohonen’s self-organizing maps were applied. Harrington’s desirability function was used to determine the integral index. The selected sample demonstrated a high level of ownership concentration in almost all companies and showed that only a few individuals controlled a significant amount of assets, thereby confirming the oligarchic structure of the Ukrainian economy. As a result, seven cluster groups were obtained, reflecting the companies in terms of the quality of their financial architecture. Only five companies in the total sample were found to have high-quality financial architecture, i.e., capital structure and ownership structure are consistent and optimal and ensure that the company maintains a leading market position.

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    • Figure 1. Cluster map
    • Figure 2. Cluster analysis reference groups
    • Figure 3. Group of the most Ukrainian stable companies (within the relevant range)
    • Figure 4. Group of conditionally stable Ukrainian companies (within the relevant range)
    • Figure 5. Group of Ukrainian unstable companies (within the relevant range)
    • Figure 6. Group of Ukrainian companies under crisis (within the relevant range)
    • Table 1. Companies in the top 200 largest revenue-producing companies of Ukraine in 2017
    • Table 2. Description of quantitative characteristics of clusters
    • Table 3. Characteristics of companies based on cluster assessment
    • Table 4. General characteristics of clusters
    • Table 5. Dynamics of the analyzed companies’ patterns for 2011–2017
    • Conceptualization
      Inna Shkolnyk
    • Project administration
      Inna Shkolnyk
    • Supervision
      Inna Shkolnyk
    • Resources
      Urszula Mentel
    • Validation
      Urszula Mentel
    • Writing – review & editing
      Urszula Mentel
    • Formal Analysis
      Alina Bukhtiarova
    • Software
      Alina Bukhtiarova
    • Visualization
      Alina Bukhtiarova
    • Investigation
      Maya Dushak
    • Methodology
      Maya Dushak
    • Writing – original draft
      Maya Dushak