Digital Tools to Ensure Business Competitiveness and Self-Development of the Territories
Svitlana Tulchynska
D.Sc., Prof.,
Department of Economics and Entrepreneurship,
National Technical University of Ukraine
“Igor Sikorsky Kyiv Polytechnic Institute”,
Kyiv, Ukraine,
е-mail: tuha@ukr.net
Olena Arefieva
D.Sc., Prof.,
Department of Air Transport Economics,
National Aviation University, Kyiv, Ukraine,
е-mail: lena-2009-19@ukr.net
Maryna Shashyn
D.Sc., Prof.,
Department of Economics and Entrepreneurship,
National Technical University of Ukraine
“Igor Sikorsky Kyiv Polytechnic Institute”,
Kyiv, Ukraine,
е-mail: shashyna.marina@gmail.com
Anna Pohrebniak
PhD., Assoc. Prof.,
Department of Economics and Entrepreneurship,
National Technical University of Ukraine
“Igor Sikorsky Kyiv Polytechnic Institute”,
Kyiv, Ukraine,
е-mail: anna.u.pogrebnyak@gmail.com
Iegor Biriukov
PhD., Assoc. Prof.,
Department of Management,
Marketing and Public Administration,
IHE "Academician Yuriy Bugay
International Scientific and
Technical University", Kyiv, Ukraine,
е-mail: iegor.biriukov@icloud.com
Abstract
The article is devoted to the identification of the application areas of digital tools (DT) to ensure the business competitiveness and self-development of the territories. The issue of finding ways to establish sustainable forms of self-development of the territories by building the competitive environment for the functioning of the business sector in the digitalisation conditions is increasingly gaining popularity and relevance, which determines further scientific exploration in this scientific area. The issue of substantiating the provided business competitiveness and self-development of the territories requires qualitative deepening, based on the current realities of digital development of progressive economic systems in modern conditions. The methodological approach is proposed to assess the level of business competitiveness in the context of ensuring self-development of the territories in the digitalisation context, which is built using the tools of the taxonomic analysis, which allows for the selection of analytical parameters in the absence of restrictions on their quantity, qualitative nature, dimension or type of the selected descriptive statistical parameter, and to maintain the representativeness of the assessment despite the possible heterogeneity of the array of analytical parameters. The proposed methodological approach includes the following sequence of actions and calculations, namely; formation of the complex system of analytical parameters; normalization of the values of the analyzed parameters; qualitative analysis of the constructed array of analytical parameters; construction of the ideal vector, calculation of the values of the taxonomic distance between the normalized levels of analytical parameters and the values of the ideal vector; calculation of the intermediate calculated values to assess the level of business competitiveness in ensuring self-development of the territories represented by various types of deviations; calculation of the value of the maximum deviation of analytical parameters from the ideal vector; determination of the integral assessment of the level of business competitiveness in ensuring self-development of the territories; analytical interpretation of the obtained integral assessments using the Harrington verbal-numeric scale. Directions for the application of DT to increase the level of business competitiveness and to ensure self-development of the territories are proposed.
Keywords: Digitalization, Digital Tools, Open Data, Blockchain, Bid Data, Smart City, Artificial Intelligence, Internet of Things, Self-Development, Region, Business Competitiveness.
Introduction
Today, one of the key problems to ensure stable functioning of the regional economic systems is the search for relevant forms of organization and instrumental support to implement the systemic policy in the territorial development, which is due primarily to a wide range of risks and threats caused by the action of the legal regime of martial law and the associated challenges, embodied in the deepening of the asymmetry of spatial development of the territories, the intensification of problems of the socio-demographic nature, the physical destruction of the industrial and production potential of individual regions and the general reconfiguration of internal and external economic relations within the regional systems. In this context, the issue of finding ways to establish sustainable forms of self-development of the territorial entities by building the competitive environment for the functioning of the business sector becomes particularly relevant. This approach is based on the idea to achieve progressive synergy of interaction between factors of the stable environment to carry out the entrepreneurial activity and the targeted management policy aimed at ensuring the optimal involvement of existing components of the resource potential of the regions and building the appropriate network of interregional ties, which ultimately allows forming the systemic basis for the development of the competitive potential of the entrepreneurial sector based on self-development of the territories.
Self-development as an economic category is characterized by high level of complexity and can be defined as a systemic process to ensure the balanced development of the regional economic system, based on the rational use of existing resource potential and competitive advantages to achieve a high level of manageability of the organizational and managerial, financial, infrastructural and social subsystems of the region.
It is worth noting that the self-development concept of the territories is in close semantic and ontological relationship with the concept of business competitiveness, which function simultaneously within the specific regional economic system, interacting with each other in terms of the issues of formation, distribution and use of productive forces and the external effects of development generated by them, both positive and negative.
The self-development concept of the territories in its content covers not only accumulation and reproduction of existing elements of the resource potential, but also the capabilities of the system itself to ensure transformation of the relevant reproduction into sustainable competitive advantages based on ensuring their institutionalization and applying measures to stimulate the initiative activity of the business sector. In turn, the business competitiveness level directly depends on spatial conjuncture conditions, which are determined by the degree of infrastructure provision, the availability of qualified personnel, the development level of the local sales markets, and the characteristics of the regional innovation ecosystem. Thus, achieving the high level competitiveness by the business sector contributes to the growth of the volumes of generated added value, received tax revenues and is generally a catalyst for the investment and innovation activity of the territories, thereby expanding the financial base of their stable functioning, forming the appropriate prerequisites to accelerate the internal expanded reproduction.
Thus, there is a duality of the structural relationship between the concepts of self-development of the territories and ensuring business competitiveness, creating the corresponding multiplicative effect, because ensuring the sustainability of self-development of the territories forms an objective basis for the effective functioning of the competitive business sector, which in turn acts as a stimulating factor for the progressive spatial development of territories, contributing to the strengthening of the resource autonomy of the region and effective relevant adaptive properties of the system.
The purpose of the study is to substantiate theoretical and conceptual foundations and to develop the methodological approach to assess the business competitiveness level in ensuring self-development of the territories in the digitalisation context.
Literature review
Scientific research Guerra J. D., et al. (2025), Peng L. et al. (2025) is devoted to redesigning business models to increase the production sustainability using DT.
Adula M. et al. (2025), Gupta S. T. et al. (2025) analyzed the impact of innovation and DT on the business management, and explored the role of DT and technology to enable the knowledge exchange and business development. In Liao M.-H. et al. (2025), Kochuma, I. et al. (2024), Shwawreh S. et al. (2025) the features of development of the business strategy using DT are investigated, the marketing activities of the enterprise in the digital age are analyzed.
Lal R. et al. (2024), Salah A. H. et al. (2024), Abramova A. et al. (2021) assessed the optimizing of digital marketing strategies, and determined the impact of DT on the e-commerce development.
Varga J. et al. (2024), Sprokholt A. et al. (2024), Telukdarie A. et al. (2024) analyzed the impact of DT on the business competitiveness of Hungarian and Slovak enterprises, investigated business activity tools to support decision-making in digital transformation, and provided the analysis of DT to promote digital business opportunities.
Sousa M. (2024), Hazlehurst C. et al. (2023), Ravindran D. et al. (2023) investigated the role of digital communication technologies in the international business, and outlined the impact of the Internet of Things on the business efficiency and sustainability.
Csordás A. et al. (2022), Niemann J. et al. (2021), Dabas S. et al. (2021) analyzed the existing tools for digital business transformation, and assessed the advantages and disadvantages of implementing digital marketing tools at enterprises. Aquino-Arrieta K. et al. (2020), Řepa V. et al. (2019), Aagaard A. et al. (2018), Viknianska A. et al. (2021) analyzed the digital model as a tool to test the digital entrepreneurship in the economic system transformation.
However, it should be added that in modern conditions, the study of the issues of ensuring business competitiveness and self-development of the territories requires its qualitative deepening, based on the current realities of digital development of the progressive economic systems. After all, the possibility of the qualitative integration of the business sector and territorial entities into the modern digital environment determines their ability to overcome existing limitations of traditional models to ensure socio-economic development; effective use of information, knowledge, and intellectual resources of territories; the integration into global chains of the added value generation and generally serves as the indicator of institutional progressivity in the public administration, a guarantee of the transparent and legal regulatory system.
Methodology
Based on the above, it can be concluded that the issue of ensuring business competitiveness and self-development of the territories in modern trends of the digitalization of socio-economic systems is characterized by complex nature, covering a wide range of the influential variables and factors that determine the ability of spatial systems to organize the sustainable environment, increase competitiveness and achieve a state of self-development. Based on this, there is a need to form the holistic methodology to assess the relevant processes, aimed at carrying out the objective analysis and measuring the current level of business competitiveness in ensuring self-development of the territories, which will determine possible application of the selected digital management tools.
Within the framework of this study, as the methodological basis to implement the analytical procedures for assessing the business competitiveness level in ensuring self-development of the territories in the digitalisation conditions, it is proposed to apply the tools of the taxonomic analysis. The choice of the taxonomic analysis method as a key tool to assess the business competitiveness level in ensuring self-development of the territories is explained by the need to ensure quantitative consideration of the multi-faceted manifestations of the researched issues and the formation of the relevant analytical conclusions. The essence of the taxonomic analysis is to consider the studied objects (regions) and their corresponding descriptive data as individual points of the multidimensional space with the subsequent calculation of the parameters of the Euclidean distance between these points. The quantitative parameters of the dimension of the corresponding multidimensional system are determined by the number of selected analytical parameters that describe the studied objects. It should be noted that this method allows free selection of analytical parameters without restrictions on their quantity, qualitative nature, dimension or type of the selected descriptive statistical parameter. That is, the taxonomic analysis method allows for preserving the representativeness of the assessment despite the possible heterogeneity of the array of analytical parameters, which is achieved by implementing the procedure to normalize the levels of analytical parameters provided for by this method, which in turn allows for reducing the heterogeneous array of data to the comparable form, obtaining the final result of the integral assessment. Therefore, the application of the taxonomic analysis method in the assessing the business competitiveness level in ensuring self-development of the territories allows for the application of the entire available spectrum of descriptive analytical parameters, forming generalized integral assessments on their basis.
Conducting the taxonomic analysis of the business competitiveness level in ensuring self-development of the territories involves the implementation of sequential calculation, which can be summarized as the following list of stages (Fig. 1):
, (1)
where: A is the observation matrix;
n –number of analyzed time periods (study periods);
m –number of analytical evaluation parameters;
xij – value of analytical parameter j in period i.
(2)
where:xij – level of analytical parameter i in array j;
–average value of the analytical parameter and in array j ;
–value of the standard deviation for the i-th analytical parameter.
(3)
(4)
where d_i0is – the taxonomic distance between the values of the ideal vector and .
(5)
where, is the average level of deviations of the analytical parameters from the ideal vector.
(6)
where is the standard deviation level d_i0.
(7)
where is the maximum deviation of the analytical parameters from the ideal vector according to the three-sigma rule.
(8)
where is the intermediate indicator to assess the business competitiveness level in ensuring self-development of the territories.
(9)
where С_i is the integral assessment of the business competitiveness level in ensuring self-development of the territories.
The implementation of the above-described stages of carrying out calculation procedures using the methodological apparatus of the taxonomic analysis requires the formation of the input array of information data represented by the system of analytical parameters to assess the business competitiveness level in ensuring self-development of the territories. Taking into account the previously identified features of the researched issues, it is proposed to implement the comprehensive approach to the formation of the system of analytical parameters, which allows covering a wide range of factors influencing the business competitiveness level within regional economic systems, taking into account the economic, social and environmental components of the analysis.
Results
The economic component of the analysis of business competitiveness in ensuring self-development of the territories is designed to take into account, within the framework of the proposed methodology, the effective indicators of the functioning of the region, the basic parameters of financial stability and investment activity of the business sector within the region, which serve as the indicators of the competitiveness level of business entities, while forming the prerequisites for the effective implementation of ensuring self-development. Within the framework of this analytical component, it is proposed to use the following analytical parameters, namely: volume of products sold (goods, services) of business entities; the number of operating business entities; added value at the cost of production of business entities; capital investments; net profit (loss) of enterprises; consumer price index; regional volumes of exports of goods; share of enterprises that have suffered losses in the total number of enterprises.
Fig. 1. Stages of a methodological approach to assess the business competitiveness level
in ensuring elf-development of the territories in the digitalization context
Source: built by the authors
The social component of business competitiveness in ensuring self-development of the territories involves supplementing the input array of the analytical parameters with indicators that reflect the provision of the region with human resources, the availability of sufficient financing of the human resource component of the functioning of the business sector, the development level of the knowledge potential of personnel and the prospects to provide the region with a sufficient number of the qualified specialists. This range of indicators directly characterizes the resource degree of self-sufficiency of the regional entities in the development level of the human capital. Within the framework of this analytical component, it was proposed to apply the following analytical parameters: the number of employees by business entities in the region; personnel costs of business entities in the region; the number of higher education institutions; the number of applicants to higher education institutions.
The environmental component of business competitiveness in ensuring self-development of the territories characterizes the current state of the natural environment of the region, which directly affects the degree of ecological safety of the territories, the level of population health, and available technogenic and ecological risks. Within the framework of this analytical component, it is proposed to use the following analytical assessment parameters: emissions of pollutants into the atmospheric air from stationary sources; current costs of environmental protection in the region; emissions of carbon dioxide into the atmospheric air from stationary sources of emissions by region.
Therefore, the proposed system of analytical parameters to assess the business competitiveness level in ensuring self-development of the territories includes 15 analytical parameters; the study is based on these indicators for the period 2019-2023 (State Statistics Service of Ukraine, 2024).
Table 1. Dependence of the main macroeconomic indicators of Ukraine and the average for the European Union on the state of human capital as a factor of state regulation of the national economy, 2023
|
Region/ Indicator |
Number of higher education institutions |
Number of students |
Volume of products sold (goods, services) by business entities |
Number of employees in business entities |
Personnel costs of business entities |
Regional volumes of goods exports |
Consumer Price Index |
Current expenses for environmental protection |
Number of operating business entities |
Value added by production costs of business entities |
Capital investments |
Share of enterprises that suffered losses in the total number of enterprises |
Emissions of pollutants into the atmosphere from stationary sources |
Carbon dioxide emissions into the atmosphere from stationary emission sources by region |
Net profit (loss) of enterprises |
|
Vinnytsia |
12 |
37898 |
358961303 |
260138 |
33512737 |
1698854 |
104 |
1173504 |
73106 |
109719995 |
19212450 |
24 |
80.5 |
3860 |
15760531 |
|
Volyn |
8 |
28035 |
295123421 |
177437 |
22885407 |
823812 |
105 |
480223 |
45974 |
98217314 |
12497407 |
23 |
4.4 |
437 |
8874057 |
|
Dnipropetrovsk |
29 |
82444 |
1411494863 |
735314 |
140191535 |
4696391 |
104 |
7758115 |
160478 |
366793942 |
63067801 |
26 |
385.1 |
16311 |
29471822 |
|
Zhytomyr |
5 |
21454 |
201802230 |
186305 |
22969046 |
531141 |
105 |
380934 |
52588 |
60583262 |
11566280 |
27 |
7 |
565 |
5697931 |
|
Transcarpathian |
7 |
22493 |
131054206 |
149316 |
17681914 |
1359226 |
105 |
497766 |
48761 |
37858343 |
8893280 |
27 |
2 |
152 |
5503674 |
|
Zaporizhzhia |
12 |
50540 |
295402213 |
213663 |
32296191 |
1456744 |
105 |
1750939 |
51204 |
75727735 |
8563679 |
32 |
52 |
6862 |
-71873854 |
|
Ivano-Frankivsk |
10 |
36610 |
174019413 |
191832 |
19216980 |
616154 |
105 |
792740 |
60421 |
51645150 |
12002208 |
20 |
147 |
9975 |
3723451 |
|
Kiev |
7 |
20868 |
881154518 |
434389 |
72865670 |
1837566 |
105 |
1501994 |
124761 |
253380512 |
51184367 |
25 |
55 |
3771 |
43676007 |
|
Kirovohrad |
7 |
17270 |
178062237 |
146102 |
17032298 |
810194 |
105 |
299846 |
39725 |
52253778 |
9147036 |
20 |
7 |
476 |
8475899 |
|
Lviv |
21 |
108968 |
855380676 |
526134 |
71688782 |
2552393 |
105 |
1519012 |
149350 |
323318393 |
44790018 |
26 |
57 |
2208 |
44516834 |
|
Mykolaiv |
9 |
21561 |
168079257 |
146907 |
18066517 |
1000672 |
105 |
642501 |
49324 |
52715403 |
8991126 |
26 |
5 |
547 |
33916 |
|
Odessa |
21 |
75355 |
574738189 |
397437 |
44174969 |
1797917 |
104 |
702391 |
128752 |
191767018 |
19150399 |
31 |
27 |
723 |
15058798 |
|
Poltava |
8 |
41174 |
375757319 |
282728 |
38912618 |
1433241 |
104 |
6801886 |
67411 |
125755051 |
24130778 |
25 |
30 |
1928 |
17239370 |
|
Rivne |
7 |
26128 |
156042832 |
170756 |
17601771 |
594570 |
104 |
787405 |
47982 |
40204828 |
13506009 |
26 |
7 |
1608 |
2743040 |
|
Sumy |
6 |
22979 |
153332816 |
154301 |
19168351 |
701728 |
104 |
698415 |
41630 |
49035632 |
8956585 |
28 |
12 |
849 |
6555486 |
|
Ternopil |
6 |
37971 |
163166516 |
149189 |
17593483 |
686741 |
104 |
96786 |
41357 |
46445361 |
11823173 |
24 |
8 |
305 |
7788928 |
|
Kharkiv |
30 |
119032 |
507562185 |
439788 |
49184510 |
777989 |
105 |
1742706 |
150589 |
184942862 |
18057050 |
33 |
38 |
3837 |
2223350 |
|
Khmelnytskyi |
11 |
27109 |
200328256 |
207751 |
22278998 |
777887 |
106 |
540141 |
67226 |
59952927 |
15153113 |
22 |
18 |
2029 |
11276177 |
|
Cherkasy |
8 |
32436 |
342516924 |
208046 |
26644553 |
1221196 |
105 |
557985 |
57843 |
91422459 |
14283813 |
24 |
61 |
2898 |
10921704 |
|
Chernivtsi |
3 |
20964 |
99741984 |
111986 |
9498149 |
193684 |
105 |
187243 |
42402 |
28760681 |
4741733 |
28 |
1 |
152 |
2516375 |
|
Chernihiv |
4 |
15941 |
143750292 |
151430 |
18557554 |
893235 |
104 |
535483 |
42186 |
39880134 |
12631781 |
31 |
14 |
554 |
2356993 |
|
City of Kyiv |
83 |
281428 |
5776861345 |
1828760 |
462832078 |
9401102 |
106 |
5246272 |
321032 |
2066501024 |
226008702 |
33 |
27 |
3968 |
268727378 |
|
x jser |
18.3277311 |
48997 |
512396589 |
348447 |
45223217 |
2071983 |
231013 |
932803 |
79137.76 |
155828844 |
23761159 |
26 |
75 |
3908 |
3718459 |
|
s j |
18.3376864 |
57114 |
980347160 |
380733 |
76240017 |
2731877 |
906708 |
1709500 |
60360 |
320154287 |
37909368 |
4 |
147 |
5468 |
26228953 |
Source: constructed by the authors based on State Statistics Service of Ukraine (2024)
During the practical implementation of the proposed author's methodology to assess the business competitiveness level in ensuring self-development of the territories, the implementation stages of the taxonomic analysis were sequentially carried out, previously defined. Intermediate indicators of the assessment are presented in Table 2.
It is worth adding that, given the current conditions of the legal regime of the martial law and the limited access to descriptive data characterizing the regions of Ukraine that are partially or fully under temporary occupation, the calculation of relevant integral estimates for the Luhansk, Donetsk, and Kherson regions in 2022-2023 is impossible.
Table 2. Intermediate estimated values to assess the business competitiveness level in ensuring self-development of the territories
|
Region/Year |
2019 |
2020 |
2021 |
2022 |
2023 |
|||||
|
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
|
|
Vinnytsia |
21,740 |
0.815 |
21,950 |
0.842 |
21,871 |
0.830 |
21,947 |
0.836 |
21,370 |
0.745 |
|
Volyn |
22,172 |
0.831 |
22,377 |
0.858 |
22,298 |
0.846 |
22,285 |
0.849 |
21,989 |
0.766 |
|
Dnipropetrovsk |
17,972 |
0.674 |
19,133 |
0.734 |
18,693 |
0.709 |
19,391 |
0.739 |
18,530 |
0.646 |
|
Donetsk |
21,365 |
0.801 |
22,013 |
0.844 |
21,887 |
0.831 |
- |
- |
- |
- |
|
Zhytomyr |
22,233 |
0.834 |
22,384 |
0.859 |
22,351 |
0.848 |
22,591 |
0.861 |
22,269 |
0.776 |
|
Transcarpathian |
22,167 |
0.831 |
22,387 |
0.859 |
22,374 |
0.849 |
22,456 |
0.856 |
22,240 |
0.775 |
|
Zaporizhzhia |
20,501 |
0.769 |
21,362 |
0.819 |
21,073 |
0.800 |
22,011 |
0.839 |
23,383 |
0.815 |
|
Ivano-Frankivsk |
22,072 |
0.827 |
22,251 |
0.853 |
22,206 |
0.843 |
22,257 |
0.848 |
22,082 |
0.769 |
|
Kiev |
20,777 |
0.779 |
21,196 |
0.813 |
20,924 |
0.794 |
21,429 |
0.816 |
20,151 |
0.702 |
|
Kirovohrad |
22,305 |
0.836 |
22,425 |
0.860 |
22,370 |
0.849 |
22,411 |
0.854 |
22,209 |
0.774 |
|
Luhansk |
22,433 |
0.841 |
22,567 |
0.866 |
22,623 |
0.859 |
- |
- |
- |
- |
|
Lviv |
20,540 |
0.770 |
20,911 |
0.802 |
20,743 |
0.787 |
20,676 |
0.788 |
19,409 |
0.676 |
|
Mykolaiv |
21,628 |
0.811 |
22,028 |
0.845 |
21,893 |
0.831 |
22,450 |
0.855 |
22,282 |
0.776 |
|
Odesa |
20,918 |
0.784 |
21,202 |
0.813 |
21,075 |
0.800 |
21,585 |
0.822 |
20,976 |
0.731 |
|
Poltava |
21,089 |
0.791 |
21,569 |
0.827 |
21,518 |
0.817 |
21,910 |
0.835 |
21,420 |
0.746 |
|
Rivne |
22,286 |
0.836 |
22,434 |
0.860 |
22,322 |
0.847 |
22,470 |
0.856 |
22,237 |
0.775 |
|
Sumy |
22,093 |
0.828 |
22,379 |
0.858 |
22,300 |
0.846 |
22,684 |
0.864 |
22,292 |
0.777 |
|
Ternopil |
22,332 |
0.837 |
22,483 |
0.862 |
22,442 |
0.852 |
22,446 |
0.855 |
22,210 |
0.774 |
|
Kharkiv |
20,017 |
0.750 |
20,485 |
0.786 |
20,338 |
0.772 |
21,373 |
0.814 |
20,896 |
0.728 |
|
Kherson |
22,260 |
0.835 |
22,394 |
0.859 |
22,333 |
0.848 |
- |
- |
- |
- |
|
Khmelnytskyi |
22,038 |
0.826 |
22,132 |
0.849 |
22,107 |
0.839 |
22,192 |
0.846 |
21,856 |
0.762 |
|
Cherkasy |
21,934 |
0.822 |
22,130 |
0.849 |
22,092 |
0.838 |
22,137 |
0.843 |
21,816 |
0.760 |
|
Chernivtsi |
22,586 |
0.847 |
22,682 |
0.870 |
22,789 |
0.865 |
22,770 |
0.868 |
22,640 |
0.789 |
|
Chernihiv |
22,272 |
0.835 |
22,443 |
0.861 |
22,320 |
0.847 |
22,770 |
0.868 |
22,516 |
0.785 |
|
City of Kyiv |
13,943 |
0.523 |
15,509 |
0.595 |
14,912 |
0.566 |
15,765 |
0.601 |
10,773 |
0.375 |
|
M(d i0 ) |
21.26690637 |
21.63299774 |
21.5141489 |
21.72763594 |
21.16118193 |
|||||
|
σ 0 |
1.802402111 |
1.480184789 |
1.611459661 |
1.506137121 |
2.512091258 |
|||||
|
d 0 |
26.6741127 |
26.0735521 |
26.34852788 |
26.24604731 |
28.6974557 |
|||||
Source: compiled by the authors based on calculations
Using the obtained intermediate estimated values of the assessment of the business competitiveness level in ensuring self-development of the territories, the corresponding integral indicator was calculated. The indicators of the dynamics of the integral assessment of the business competitiveness level in ensuring self-development of the territories are presented in Table 3.
Table 3 – Dynamics of the integrated assessment of the business competitiveness level in ensuring self-development of the territories in 2019-2023
|
Region |
Year , % |
Deviation , +/-, % |
||||||||
|
2019 |
2020 |
2021 |
2022 |
2023 |
2020Δ |
2021Δ |
2022Δ |
2023Δ |
||
|
Vinnytsia |
18.5 |
15.8 |
17.0 |
16.4 |
25.5 |
-2.7 |
1.2 |
-0.6 |
9.2 |
|
|
Volyn |
16.9 |
14.2 |
15.4 |
15.1 |
23.4 |
-2.7 |
1.2 |
-0.3 |
8.3 |
|
|
Dnipropetrovsk |
32.6 |
26.6 |
29.1 |
26.1 |
35.4 |
-6.0 |
2.4 |
-2.9 |
9.3 |
|
|
Donetsk |
19.9 |
15.6 |
16.9 |
- |
- |
-4.3 |
1.4 |
- |
- |
|
|
Zhytomyr |
16.6 |
14.1 |
15.2 |
13.9 |
22.4 |
-2.5 |
1.0 |
-1.2 |
8.5 |
|
|
Transcarpathian |
16.9 |
14.1 |
15.1 |
14.4 |
22.5 |
-2.8 |
0.9 |
-0.6 |
8.1 |
|
|
Zaporizhzhia |
23.1 |
18.1 |
20.0 |
16.1 |
18.5 |
-5.1 |
1.9 |
-3.9 |
2.4 |
|
|
Ivano-Frankivsk |
17.3 |
14.7 |
15.7 |
15.2 |
23.1 |
-2.6 |
1.1 |
-0.5 |
7.9 |
|
|
Kiev |
22.1 |
18.7 |
20.6 |
18.4 |
29.8 |
-3.4 |
1.9 |
-2.2 |
11.4 |
|
|
Kirovohrad |
16.4 |
14.0 |
15.1 |
14.6 |
22.6 |
-2.4 |
1.1 |
-0.5 |
8.0 |
|
|
Luhansk |
15.9 |
13.4 |
14.1 |
- |
- |
-2.5 |
0.7 |
- |
- |
|
|
Lviv |
23.0 |
19.8 |
21.3 |
21.2 |
32.4 |
-3.2 |
1.5 |
-0.1% |
11.1 |
|
|
Mykolaiv |
18.9 |
15.5 |
16.9 |
14.5 |
22.4 |
-3.4 |
1.4 |
-2.4% |
7.9 |
|
|
Odesa |
21.6 |
18.7 |
20.0 |
17.8 |
26.9 |
-2.9 |
1.3 |
-2.3% |
9.1 |
|
|
Poltava |
20.9 |
17.3 |
18.3 |
16.5 |
25.4 |
-3.7 |
1.1 |
-1.8% |
8.8 |
|
|
Rivne |
16.4 |
14.0 |
15.3 |
14.4 |
22.5 |
-2.5 |
1.3 |
-0.9% |
8.1 |
|
|
Sumy |
17.2 |
14.2 |
15.4 |
13.6 |
22.3 |
-3.0 |
1.2 |
-1.8% |
8.7 |
|
|
Ternopil |
16.3 |
13.8 |
14.8 |
14.5 |
22.6 |
-2.5 |
1.1 |
-0.3% |
8.1 |
|
|
Kharkiv |
25.0 |
21.4 |
22.8 |
18.6 |
27.2 |
-3.5 |
1.4 |
-4.2% |
8.6 |
|
|
Kherson |
16.5 |
14.1 |
15.2 |
- |
- |
-2.4 |
1.1 |
- |
- |
|
|
Khmelnytskyi |
17.4 |
15.1 |
16.1 |
15.4 |
23.8 |
-2.3 |
1.0 |
-0.6 |
8.4 |
|
|
Cherkasy |
17.8 |
15.1 |
16.2 |
15.7 |
24.0 |
-2.6 |
1.0 |
-0.5 |
8.3 |
|
|
Chernivtsi |
15.3 |
13.0 |
13.5 |
13.2 |
21.1 |
-2.3 |
0.5 |
-0.3 |
7.9 |
|
|
Chernihiv |
16.5 |
13.9 |
15.3 |
13.2 |
21.5 |
-2.6 |
1.4 |
-2.0 |
8.3 |
|
|
Kyiv |
47.7 |
40.5 |
43.4 |
39.9 |
62.5 |
-7.2 |
2.9 |
-3.5 |
22.5 |
|
Source: compiled by the authors based on calculations
Thus, as a result of the assessment of the business competitiveness level in ensuring self-development of the territories based on using the taxonomic analysis method, it was found that the vast majority of the regions of Ukraine are characterized by a low level of the business competitiveness. Moreover, during the studied period, two crisis periods of the reduced integral indicator were recorded, which took place in 2020 and 2022, which is explained by the impact of the direct consequences of the coronavirus pandemic and the beginning of the full-scale invasion on the ability to maintain the effective functioning of both the business sector and local authorities.
Fig. 2. Integrated assessment of the business competitiveness level in ensuring self-development of the territories, 2023
Source: constructed by the authors
The largest levels of reduction in the integral assessment indicator in 2020 are observed for Kiev (7.2%), Dnipropetrovsk (6.0%), Zaporizhzhia (5.1%) and Donetsk (4.3%) regions. During 2021, a partial recovery of the values of the integral assessment indicator of the business competitiveness was observed, however, with the beginning of the full-scale invasion, a further reduction has taken place. During 2022, the highest levels of the reduced analyzed indicator were demonstrated by the most industrially developed regions of Ukraine, close to the zones of active hostilities, in particular Kiev (2.9%), Kharkiv (4.2%), Zaporizhzhia (3.9%) and Dnipropetrovsk (2.9%) regions. In 2023, the highest indicators of the business competitiveness level in ensuring self-development of the territories are characteristic of Kiev (62.5%), Dnipropetrovsk (35.4%), Lviv (32.4%), city of Kyiv (29.8%), Kharkiv (27.2%) and Odessa (26.9%) regions.
Fig. 3. Deviation of the integrated assessment of the business competitiveness level in ensuring self-development of the territories, 2023.
Source: constructed by the authors
Based on the obtained integral assessments of the business competitiveness level in ensuring self-development of the territories, it is proposed to consider the analytical interpretation of the values of integral assessments in terms of the application of a specific range of DT aimed at increasing the business competitiveness level of the regions and ensuring their effective self-development. The interpretation table is built based on the Harrington's verbal-numeric scale with the corresponding promising areas of the application of DT for different values of the integral assessment indicator (Table 4).
Table 4. Interpretation of the results of the integrated assessment of the business competitiveness level in ensuring self-development of the territories
Source: (McKinsey & Company, 2023)
|
The meaning of the integral estimate business competitiveness level |
Promising directions for the application of digital tools in ensuring self-development of the territories |
|
Very high (0.8-1) |
Implementation of Internet of Things and “smart city” technologies in the functioning of the region's transport, energy and utility infrastructure; strategizing regional self-development based on big data analysis tools and artificial intelligence; application of blockchain technologies in contracting foreign economic activities of business entities; integration into global digital systems |
|
High (0.63-0.8) |
Creation of expanded platforms for the provision of digital services, their comprehensive integration with state digital services; introduction of tools for modeling scenarios of socio-economic development based on big data and artificial intelligence technologies; application of blockchain technologies in the formation of digital registers and means of recording contract procedures |
|
Average (0.37-0.63) |
Ensuring full-scale digitalization of the local government system in terms of a wide range of electronic document management services, digital service platforms and open data platforms; finding ways to integrate big data analysis tools into monitoring socio-economic indicators of the region; stimulating the business sector to implement digitalization of business processes |
|
Low (0.2-0.37) |
Implementation of digital administrative services, in terms of business registration, reporting and licensing; creation of comprehensive educational programs to expand the digital skills of the population; use of specialized software in the field of management as a source of reducing costs associated with the implementation of bureaucratic procedures |
|
Very low (0-0.2) |
Ensuring the gradual development of basic elements of digital infrastructure (Internet coverage, digitalization of the simplest accounting procedures in the document flow system, creation of advisory centers for overcoming the "digital divide" for entrepreneurs and the population), search for grant funding for digital development programs of territories |
Source: developed by the authors
The key systemic features of ensuring the effective implementation of the territorial self-development include the following:
- promoting the achievement of resource autonomy of the region to limit the economic dependence of territories in terms of ensuring the stability and continuity of supply of certain types of raw materials;
- development of the institutional and legal basis for the functioning of territories on the self-development principles, which involves the legal consolidation and normalization of certain regulatory aspects of ensuring self-development processes both from the point of view of the appropriate level of authority of local authorities and applied mechanisms for financing and ensuring fiscal decentralization;
- ensuring structural and organizational orderliness of the strategic principles of the region's development in terms of analyzing its competitive potential and identifying relevant promising areas for implementing existing competitive advantages;
- ensuring the innovative orientation of the regional development policy, which involves the implementation of modern digital solutions, the implementation of applied principles of building a knowledge economy, and the formation of a trajectory of inclusive development of the region;
- prioritization of the strategic goal-setting strategy of the spatial development of territories, which includes the implementation of scenario planning approaches to form the roadmap for the functioning of the management system in objectification of individual probabilistic scenarios of the state of the external environment in the long and medium term;
- application of the cluster approach in managing the regional self-development, which allows for the reasonable differentiation of territorial entities based on an assessment of their respective competitive capabilities to achieve optimal organization of the system of cooperative relationships and infrastructural support for the expanded reproduction;
- promoting the localization of the region's production potential to achieve the resource and raw material independence of the region's enterprises and resource concentration , which will ensure synergy of interaction between the financial, production, infrastructure, logistics and production components of the region's resource potential.
Next, we propose to consider in more detail the key DT designed to increase the efficiency of implementing self-development of the territories and ensuring business competitiveness in modern conditions:
Internet of Things are represented by high-tech intelligent systems designed to integrate the physical and digital environment of the spatial organization of local economic systems. These technological solutions allow for more effective implementation of control and monitoring functions in the development of the methodological approach to assess the impact of digital technologies on the effectiveness of territorial development management and ensuring their self-development.
Conclusion
Thus, as a result of the study, the application of the author's methodology to assessing the level of business competitiveness in the context of ensuring the self-development of territories in the context of digitalization was substantiated and tested, the corresponding values of integral assessments were calculated and a table of interpretation of the values of the integral assessment of the region's competitiveness and a prospective list of measures for using DT to ensure the self-development of territories was formed.
It is substantiated that the key DT that contribute to ensuring the self-development of territories by increasing business competitiveness are: digital platforms of open data, blockchain technologies, digital document management tools and electronic services, big data analysis tools, "smart city" technologies, artificial intelligence and machine learning tools, "Internet of Things" technologies.
Further research is required on issues related to the development of a methodological approach to assessing the impact of digital technologies on the effectiveness of territorial development management and ensuring their self-development.
The scientific novelty of the study lies in the development of a methodological approach to assessing the level of business competitiveness in the context of ensuring the self-development of territories in the context of digitalization, which, unlike existing ones, is built using taxonomic analysis tools.
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