Modeling the investment attractiveness of ecosystem business models in the context of a platform economy

Authors

  • Iryna Fadyeyeva Doctor of Economics Habilitated, Professor, Department of Finance, Accounting and Taxes, Institute of Economics and Management, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine https://orcid.org/0000-0002-6978-1621
  • Oleksandr Oliinyk Postgraduate Student, Department of Economics, Accounting and Taxation, East European University named after Rauf Ablyazov, Cherkasy, Ukraine https://orcid.org/0009-0004-6093-753X
  • Tetyana Vader PhD in Public Administration, Senior Lecturer, Associate Professor at the Department of Management and Marketing, Pryazovskyi State Technical University, Dnipro, Ukraine https://orcid.org/0009-0008-1744-6646

DOI:

https://doi.org/10.5281/zenodo.20502537

Keywords:

market capitalization, multivariate OLS regression, network effects, customer retention effect, co-creation of value, ecosystem business model, platform economy, financial sustainability, sustainable development.

Abstract

The rapid development of ecosystem business models in the platform economy attracts the attention of many investors. At the same time, traditional approaches to assessing the investment attractiveness of such models do not fully account for their multivariate nature, scalability, and network effects.

The purpose of the study is to develop a methodology for modeling the investment attractiveness of ecosystem business models in the context of digital platform operations.

The study uses multivariate log-linear regression to develop an econometric model of the investment attractiveness of ecosystem business models in the platform economy. Using the least squares method, based on panel data from Apple, Microsoft, Amazon, and Alphabet for 20212025, the model coefficients were determined, allowing the impact of operational scaling and asset monetization parameters on the level of the companys market capitalization to be predicted.

The high accuracy of the developed model was established, with a coefficient of determination of which is 94.18%. The operational scale coefficient of the model was calculated, its statistical significance was confirmed, and it was shown that a 1% increase in ecosystem income increases the platform's total market value by 0.88% due to network effects. It was demonstrated that an increase in the monetization coefficient by 1 point leads to an increase in the platforms actual value by 14.13%. It is substantiated that, in the absence of effective mechanisms for scaling and retaining customers, digital platforms do not offer a basic level of investment attractiveness.

The results obtained deepen understanding of the nature of platform capitalization through the formation of internal cross-subsidization flows, digital asset synergies, and the high cost of switching customers to another platform. The practical value of the study lies in the creation of a reliable diagnostic tool for venture and institutional investors, which enables objective assessment of the sustainability of ecosystem business models under macroeconomic instability.

Published

2026-04-30

How to Cite

Fadyeyeva, I., Oliinyk, O., & Vader, T. (2026). Modeling the investment attractiveness of ecosystem business models in the context of a platform economy. Achievements of the Economy: Prospects and Innovations, (29). https://doi.org/10.5281/zenodo.20502537