economic potential, potential growth, real estate development company, development management, primary real estate price, fuzzy logic multifactor model, management automation, artificial intelligence technologies, informed management decisions, digitalization


Constant changes in the economic environment of development companies, as well as a large number of impact factors on the economic results of these companies, complicate the management processes of their economic potential formation and growth. Optimization of the management system for the economic potential growth of development companies requires the implementation of multifactorial models of informed decision-making, built on algorithms of fuzzy logical inference. Based on this, the article develops a multifactorial input-output model of fuzzy logical inference regarding the primary real estate price of the development project. The model is dynamic because it includes the time impact factors on the resulting values, thus it can be used throughout the entire cycle of the development project implementation. It grants obtaining of two output price values: full and with the maximum possible discount, depending on the input data for a specific real estate object, which is a tool both for increasing the company's pricing policy management effectiveness, as well as for developing of a system for profitability maximization of each development project. In addition, the algorithm of this model application in the economic potential growth management system of the development company is proposed, as well as the spheres of its practical utilization at different levels of managerial decision-making are considered. Analysis of the developed model disadvantages led to the development of methods for their minimization through automation and artificial intelligence technologies. The application of the Simulink environment of the MATLAB software complex made it possible to develop a software implementation of the developed model, which allows not only to minimize the identified disadvantages but also to apply artificial intelligence technologies for its further improvement. The software implementation, taking into account the features of the model, is presented in the form of a hierarchical system consisting of three subsystems, each of which is not only a component mechanism for obtaining the model resulting values but also allows for obtaining intermediate values for each separate subsystem, which favor multi-level result analysis to make informed management decisions.


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Author Biography

Andrii Rosynskyi, Kyiv National University of Construction and Architecture

Postgraduate Student, Assistant Lecturer of the Department of Construction Economics, Kyiv National University of Construction and Architecture, Kyiv, Ukraine


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How to Cite




Chapter 3. Modern management technologies