Assessment of Investment Attractiveness of RF Entities Using Artificial Intelligence

Difficult geopolitical situation in the world has made the issue of attracting private investment into the economy at the meso-management Level relevant for Russia Currently, the solution of this problem is impossible without monitoring the investment attractiveness of the subjects of the Russian Federation. The purpose of the study is to develop an adequate methodology for assessing the investment attractiveness of Russian regions. Based on competitive benchmarking techniques, the investment attractiveness of territories (within the country) is assessed in dynamics over a number of years. The results of a retrospective assessment conducted using the index method are deepened by cluster analysis. Also, the authors’ methodology allows us to assess not only the actual investment attractiveness of Russian regions, but also assumes the formation of a forecast. At the same time, the above tasks are solved with the help of artificial intelligence. The results of the retrospective assessment showed that in 2019-2022, Moscow and St. Petersburg were the pronounced leaders in the rating of investment attractiveness among the subjects of the Russian Federation. At the bottom of the rating (they did not rise above 71st place) on a regular basis were all the republics from the North Caucasus Federal District, as well as the Republic of Kalmykia and the Republic of Tyva, which are included, respectively, in the Southern Federal District and the Siberian Federal District. Based on the results of the cluster analysis, it can be seen that all Russian regions in 2019-2022 could be organized into three groups characterized by above-average, average and below-average levels of investment attractiveness. The quality of the formed cluster structure has improved over the entire analyzed period of time: the share of subjects of the Russian Federation with above-average investment attractiveness has almost doubled. The results of the (retro and prospective) assessment according to the authors’ methodology allow us to conclude that there are significant reserves for the growth of investment attractiveness of all Russian regions without exception. Based on the decomposition of its results, the leadership of the constituent entities of the Russian Federation will be able to develop measures to improve the effectiveness of the regional investment policy.

1. Barabashev A. G., Makarov A. A., Makarov I. A. On the improvement of indicative quality assessment of public administration. Voprosy gosudarstvennogo i munitsipal’nogo upravleniya = Public Administration Issues. 2019;(2):7-38. (In Russ.).

2. Dobrolyubova E. I. In reference to the correlation between governance quality and human development. Voprosy gosudarstvennogo i munitsipal’nogo upravleniya = Public Administration Issues. 2020;(4):31-58. (In Russ.).

3. Litvintseva G., Goldobina A. Factors and ways of enhancing the investment attractiveness of the region. Idei i idealy = Ideas and Ideals. 2019;11(4-2):243-266. (In Russ.). DOI: 10.17212/2075-0862-2019-11.4.2-243-266

4. Sergeev L. I., Samsonov A. V., Kotenko A. A. Investment analysis of the state of the regional economy. ETAP: ekonomicheskaya teoriya, analiz, praktika = ETAP: Economic Theory, Analysis, and Practice. 2023;(3):82-102. (In Russ.). DOI: 10.24412/2071-6435-2023-3-82-103

5. Braunerhjelm P., Eklund J. E. Taxes, tax administrative burdens and new firm formation. Kyklos. 2014;67(1):1-11. DOI: 10.1111/kykl.12040

6. Chowdhury F., Terjesen S., Audretsch D. Varieties of entrepreneurship: Institutional drivers across entrepreneurial activity and country. European Journal of Law and Economics. 2015;40(1):121-148. DOI: 10.1007/s10657-014-9464-x

7. Dreher A., Gassebner M. Greasing the wheels? The impact of regulations and corruption on firm entry. Public Choice. 2013;155(3):413-432. DOI: 10.1007/s11127-011-9871-2

8. Emelyanov Yu.S., Leonova Yu. Yu. The indicators of evaluation of investment attractiveness of Russian regions. Upravlencheskie nauki v sovremennom mire = Managerial Science in the Modern World. 2016;2(2):501-506. (In Russ.).

9. Zav’yalov D.V., Kireeva N. S. Methods and approaches to assessing the investment attractiveness of cluster structures of agribusiness. Ekonomika: vchera, segodnya, zavtra = Economics: Yesterday, Today and Tomorrow. 2017;7(10А):38-49. (In Russ.).

10. Litvinova E. V. Evaluation of investment attractiveness of municipalities (Moscow region for example). Ekonomika i predprinimatel’stvo = Journal of Economy and Entrepreneurship. 2016;(1-1):323-329. (In Russ.).

11. Palkina M. V. Features of the implementation of innovation policy at the municipal level. Innovatsionnoe razvitie ekonomiki = Innovative Development of Economy. 2016;(6-2):57-62. (In Russ.).

12. Shmeleva L. A., Abrashkin M. S. Modern methods of evaluation of investment attractiveness of regions. Voprosy regional’noi ekonomiki = Problems of Regional Economy. 2015;(4):129-135. (In Russ.).

13. Bajraktari N. Investment aspects of regional development. Academic Journal of Interdisciplinary Studies. 2015;4(2):551-554. DOI: 10.5901/ajis.2015.v4n2p551

14. Golaydo I. M., Parshutina I. G., Gudimenko G. V., Lazarenko A. L., Shelepina N. V. Evaluation, forecasting and management of the investment potential of the territory. Journal of Applied Economic Sciences. 2017;12(2):615-632. URL: https://ritha.eu/storage/567/JAES-Spring-2(48)-XII-2017_online.pdf

15. Hunt T., Lavery S., Vittery W., Berry C. UK regions and European structural and investment funds. SPERI British Political Economy Brief. 2016;(24). URL: https://media.ukandeu.ac.uk/wp-content/uploads/2016/05/UK-regions-European-structural-and-investment-funds.pdf

16. Iamsiraroj S. The foreign direct investment-economic growth nexus. International Review of Economics & Finance. 2016;42:116-133. DOI: 10.1016/j.iref.2015.10.044

17. Yakushev N. O., Mazilov E. A. Methodological approach to assessing the investment attractiveness of the region’s local territory. Problemy razvitiya territorii = Problems of Territory’s Development. 2020;(4):68-87. (In Russ.). DOI: 10.15838/ptd.2020.4.108.5

18. Loseva O. V., Fedotova M. A. Assessment of investment attractiveness of socio-economic entities. Imushchestvennye otnosheniya v Rossiiskoi Federatsii = Property Relations in the Russian Federation. 2021;(3):58-67. (In Russ.). DOI: 10.24411/2072-4098-2021-10304

19. Fedotova M. A., Loseva O. V. Estimation of growth factors investment attractiveness of regions. Imushchestvennye otnosheniya v Rossiiskoi Federatsii = Property Relations in the Russian Federation. 2015;(2):61-70. (In Russ.).

20. Myakshin V. N., Petrov V. N., Pesiakova T. N. Methodology for assessing the effectiveness of investment policy in Russian regions. Ekonomika regiona = Economy of Regions. 2023;19(1):259-273. (In Russ.). DOI: 10.17059/ekon.reg.2023-1-20

21. Myakshin V. N., Petrov V. N., Pesyakova T. N. Management of investment processes in the regions of the Russian Federation on the basis of a balanced system of indicators. Finance: Theory and Practice. 2023;27(2):38-49. DOI: 10.26794/2587-5671-2023-27-2-38-49

22. Brown M. G. Keeping score: Using the right metrics to drive world-class performance. New York, NY: Productivity Press; 2020. 226 р.

23. Kober R., Northcott D. Testing cause-and-effect relationships within a balanced scorecard. Accounting & Finance. 2021;61(S 1):1815-1849. DOI: 10.1111/acfi.12645

24. Vladimir V. F., Mercedes N. C., Francisca C. M.M., Jose M. V.D. Balanced scorecard: Key tool for strategic learning and strengthening in business organizations. Academic Journal of Interdisciplinary Studies. 2020;9(3):1-11. DOI: 10.36941/ajis-2020-0036

25. Aliakbari Nouri F., Shafiei Nikabadi M., Olfat L. Developing the framework of sustainable service supply chain balanced scorecard (SSSC BSC). International Journal of Productivity and Performance Management. 2019;68(1):148-170. DOI: 10.1108/IJPPM-04-2018-0149

26. Dwivedi R., Prasad K., Mandal N., Singh S., Vardhan M., Pamucar D. Performance evaluation of an insurance company using an integrated Balanced Scorecard (BSC) and Best-Worst Method (BWM). Decision Making: Applications in Management and Engineering. 2021;4(1):33-50. DOI: 10.31181/dmame2104033d

27. Mamabolo A., Myres K. Performance measurement in emerging market social enterprises using a balanced scorecard. Journal of Social Entrepreneurship. 2020;11(1):65-87. DOI: 10.1080/19420676.2018.1561499

28. Sharma D., Sharma U. Analysis of balanced scorecard usage by private companies. Pacific Accounting Review. 2021;33(1):36-63. DOI: 10.1108/PAR-06-2019-0076

29. Borisov A. N., Borodin A. I., Gubarev R. V., Dzyuba E. I., Sagatgareev E. R. Managing the investment attractiveness of the federal subjects of Russia in the context of the UN sustainable development goals. Vestnik MGIMO-Universiteta = MGIMO Review of International Relations. 2022;15(3):202-230. (In Russ.). DOI: 10.24833/2071-8160-2022-3-84-202-230