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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Integral Assessment of the Enterprise Investment Attractiveness: Testing the Hypothesis of Non-Conformity to Investor’s Interests

N.M. Yakupova, S.J. Levachkova, G.M. Iskhakova, E.I. Kadochnikova and A.V. Lelyuk
Page: 4927-4930 | Received 21 Sep 2022, Published online: 21 Sep 2022

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https://doi.org/10.36478/jeasci.2017.4927.4930

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Abstract

The study attempts to improve the construction of a dynamic model for assessing the investment attractiveness of the enterprise. The researchers use the calculation of the Kendall correlation coefficient for two rank series by comparing the actual order of the growth rates of investment appeal indices with the standard ones based on internal environment indicators of a leading chemical enterprise. The researchers calculate the dynamic assessment of investment attractiveness. The study emphasizes that the maximum value of the dynamic assessment of investment attractiveness is equal to one in the case when all observed characteristics conform to the interests of potential investors. To test the null hypothesis about the statistical insignificance of the Kendall correlation coefficient the "tau" statistics and the calculation of the critical values of the Kendall rank correlation coefficient were used. The researchers employed an applied statistical analysis of the company’s internal environment indicators for the dynamic assessment of investment attractiveness. In future, this technique will help researchers formulate unified approaches to assessing investment attractiveness by systemizing both internal and external factors based on the structure of the relationships between them.

How to cite this article:

N.M. Yakupova, S.J. Levachkova, G.M. Iskhakova, E.I. Kadochnikova and A.V. Lelyuk. Integral Assessment of the Enterprise Investment Attractiveness: Testing the Hypothesis of Non-Conformity to Investor’s Interests.
DOI: https://doi.org/10.36478/jeasci.2017.4927.4930
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.4927.4930