| Issue |
E3S Web Conf.
Volume 371, 2023
International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2022)
|
|
|---|---|---|
| Article Number | 01065 | |
| Number of page(s) | 11 | |
| Section | Smart Farming and Precision Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202337101065 | |
| Published online | 28 February 2023 | |
Mathematical methods for assessing the investment attractiveness of territories
1 Don State Technical University, 344003 Rostov-on-Don, Russia
2 National Research University "Moscow Power Engineering Institute", 111250 Moscow, Russia
* Corresponding author: irina-sk@list.ru
The article is devoted to the use of mathematical methods in assessing the investment attractiveness of territories. The work includes the selection of indicators that are the basis for comparison, their mathematical processing and generalization using such methods as normalization of indicators, correlation analysis, t-SNE visualization method, cluster analysis, principal components analysis, ranking method. Using these methods, it became possible to obtain the rating of municipalities on the example of one of the regions of the Southern Federal District of the Russian Federation - Rostov region. The rating is compiled separately for urban districts and municipal districts. The principal components analysis was used to study the relative importance of indicators, which eliminates the need to interview experts in the course of the research. The use of mathematical methods in assessing the investment attractiveness of municipalities made it possible to obtain a final assessment for each municipality, as well as to identify leaders and underperformers. This approach, which is notable for the availability of the information and less time-consuming calculations, is of interest both to local governments of municipalities and regional authorities. This methodology can be recommended to private investors for the selection of investment objects and the assessment of investment risks.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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