The Role of Small and Medium-Sized Enterprises in the Innovative Development of Post-War Regions
IaroslavPetrunenko
Doctor of Juridical Science,
Full Professor, Senior Researcher,
State Organization V. Mamutov Institute
of Economic and Legal Research of the
National Academy of Sciences of Ukraine,
Kyiv, Ukraine,
https://orcid.org/0000-0002-1186-730X
Oksana Khymych
Ph.D., Associate Professor, Researcher,
School of Business and Economics, Entrepreneurship,
Vrije Universiteit Amsterdam,
Amsterdam, Netherlands,
https://orcid.org/0000-0002-0629-8528
Liliia Tymoshchyk
Ph.D. in Economics,
Scientist Secretary,
Scientific Research Center for
Forensic Science of Information Technologies
and Intellectual Property of the
Ministry of Justice of Ukraine,
Kyiv, Ukraine,
https://orcid.org/0000-0002-7695-2169
Olha Hirna
Ph.D., Associate Professor,
Department of Management of Organizations,
Institute of Economics and Management,
Lviv Polytechnic National University,
Lviv, Ukraine,
https://orcid.org/0000-0002-6776-967X
Nataliia Sulima
Ph.D. in Economics,
Associate Professor,
Department of Economics,
National University of Life and
Environmental Sciences of Ukraine,
Kyiv, Ukraine,
https://orcid.org/0000-0002-3852-7989
Abstract
A sufficiently high level of development of small and medium-sized enterprises (SMEs) is an unquestionable competitive advantage for any region and generally indicates the potential for further development of the region's capabilities. The socio-economic conditions for entrepreneurial activity and development have undergone significant transformations in recent years due to the active military actions on the territory of Ukraine. The new realities of the Ukrainian economy shape new conditions for entrepreneurial activity and demand innovative solutions and tools from entrepreneurs. Given the research's relevance, this paper aims to determine the role of SMEs in ensuring the innovative development of post-war regions, focusing on specifying the factors that determine the potential efficiency of SME operations. To achieve the aim of the study, the author analysed relevant scientific sources on the chosen topic, which allowed for obtaining reasonable and objective results, and used a specific method of correlation and regression modelling, which allowed the identification of critical factors that affect the efficiency of small and medium-sized enterprises in the regions in the context of their innovation activity. The results of the correlation-regression analysis revealed a strong correlation between the financial performance of SMEs in a region and the following set of indicators: the volume of capital investment in the region, the number of organisations conducting scientific research and development in the region, the number of employees at SMEs by region, and the volume of goods sold by SMEs across the regions.
Keywords: Innovative Development, Regional Development, Business Performance, Financial Results, Regional Potential, Property Assessment, Asset Management, Management Efficiency, State Property.
Introduction
One condition for ensuring high economic growth rates in Ukraine during the post-war recovery and adaptation to global economic and political challenges is the dynamic development of small and medium-sized innovative enterprises, including small technology companies capable of enhancing the economy's technical capabilities across various sectors. A fundamental factor in developing small technology enterprises is the establishment of favourable economic and legal conditions for their operation.
Research Problem
Scientific research today helps businesses reduce costs. However, scientists' goals do not always align with entrepreneurs' objectives, which can create difficulties in integrating scientific developments into practical business activities (Mуkhalchenko et al., 2023; Syrtseva et al., 2022).
Small businesses are an integral part of large-scale production. They enable the redistribution of production costs within a shorter investment cycle and more efficient use of local resources. Small businesses are typically based on the entrepreneurial activities of small firms and enterprises, which are generally better able to adapt to challenging external conditions.
Small and medium-sized enterprises (SMEs) include business entities registered as legal entities or individual entrepreneurs, with activities that may be focused on various sectors and industries. According to international standards, based on the average number of employees per calendar year, enterprises are classified as follows (Scott, 2019; Tödtling et al., 2018; Tödtling et al., 2021):
In the context of high instability in the socio-economic landscape, identifying and effectively utilising opportunities and accounting for and mitigating threats and limitations to the development of SMEs is a crucial management task. Addressing this challenge will help discover new paths for developing Ukraine's economy during the post-war recovery period. Consequently, the academic community is united in the view that the SME sector should play a unique role in the development of modern Ukraine. Therefore, analysing and seeking solutions to the problems that constrain and hinder the growth of SMEs has become especially pertinent.
Many researchers (Bilan et al., 2019; Bordoloi et al., 2022; Wagner et al., 2021) emphasise that SMEs form the backbone of the economy, as they create the most jobs and provide significant tax revenue to local budgets. Hence, the importance of SMEs is most pronounced at the regional level. Based on the analysis of global experience in supporting SMEs, several critical tools for supporting this sector in a market economy can be identified – see Fig. 1.
Figure 1. Directions for Providing State Support to Small and Medium-Sized Enterprises
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Financial support includes preferential lending, grants for starting a business, etc. |
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Legislative support and provision of tax incentives for small and medium-sized businesses (single tax, simplified taxation system) |
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Organizational and legal support of entrepreneurs in strategically essential areas (agriculture, information technologies, etc.) |
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Personnel support through cooperation with the Employment Service and other bodies that can provide qualified personnel |
Source: Compiled by the author based on (Buriak et al., 2023; MacKinnon et al., 2019; Nilsen et al., 2023).
At the national level, the implementation of effective measures to support small and medium-sized enterprises (SMEs) requires a comprehensive approach encompassing various sectors of economic activity to achieve a systemic outcome (Erdin et al., 2020; MacKinnon et al., 2022; Reva & Demchenko, 2024; Berdar & Yaremko-Hladun, 2024) (Table 1).
Table 1. Strategic Interventions for Supporting SMEs at the National Level
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Strategic Intervention |
Description |
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Workforce Retraining Stimulus |
Government-led programmes aim to retrain the existing workforce to align with current labour market demands, prioritising support for combat veterans and individuals impacted by enemy shelling. |
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SME and Higher Education Collaborative Initiatives |
Development of targeted educational programmes to prepare future specialists according to specific industry needs, with pathways to employment for young professionals. |
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Corporate Competency Development |
Enabling enterprises to establish and enhance job-specific competencies through internal corporate training initiatives, adapting employee skills to meet organisational demands. |
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Support Mechanisms for Reverse Migration |
Establishment of conducive working conditions to encourage the return of refugees from European countries, implemented in partnership with SMEs. |
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Digitalisation and Automation Advancement |
Integration of information technologies to streamline processes in production, management, and oversight within SME operations. |
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SME Image Enhancement as Economic Pillars |
Strategic promotion of SMEs as foundational to the economy, fostering entrepreneurial engagement and the growth of new business ventures. |
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Regional Adaptation for SME Sector Development |
Tailored resource allocation to optimise regional strengths, focusing on sectoral growth in areas with the highest potential for economic development. |
Source: authors' own development
It is crucial to consider the regional specificities where SMEs are located to effectively use resources and foster the growth of sectors with the most significant potential in each part of the country.
Research Focus
The study focuses on determining the role of small and medium-sized enterprises in ensuring the innovative development of post-war regions and proving their importance for post-war recovery. In addition, special attention is paid to diagnosing the factors that determine the potential efficiency of small and medium-sized businesses in the context of instability and martial law.
Research Aim and Research Questions
Given the relevance of this research, the study aims to determine the role of SMEs in ensuring the innovative development of post-war regions, focusing on identifying the factors that influence SMEs' operational efficiency. To achieve this goal, attention must be given to the following tasks: analysing statistical data on the investment activity of SMEs in the regions and identifying the key factors affecting the future development of investment activity in SMEs.
Methodology
Literature sources were selected for their relevance to achieve objective study results. Additionally, the study analyzed statistical data related to the innovative development of small and medium-sized businesses, emphasizing regional distribution. A comprehensive approach to researching regional development specifics in Ukraine ensures that the proposed recommendations are complete and objective. Focusing on the innovative aspect of regional development, the analysis includes indicators such as regional capital investments, as these funds can drive creative growth. The study identifies critical directions for enhancing innovative activities among SMEs across regions. To assess the current development of regions, statistical data in dynamics must be considered, making statistical analysis methods appropriate (Ahmad et al., 2018; Rudevska et al., 2024). This approach enables diagnosing the challenges and potential of each region. Study participants include representatives of small and medium-sized businesses, government officials, and local community members who are primarily focused on the innovative development of regions both during post-war recovery and under martial law.
The research underscores the growing importance of managing modern digital tools, which can serve as vital instruments for enterprise development, especially given rapid technological changes, production methods, and organizational structures.
Data Analysis
The literature base for this study was selected through searches in the central databases Web of Science and Scopus. Through a review of scientific literature, groups interested in the research were identified, including government officials, business leaders and owners, financial directors, technical specialists, and others. The period for database searches was set from February 2019 to May 2024 to ensure the continuity and integrity of the research conducted in the last five years. Correlation-regression analysis was used to identify the relationship between net financial results as an indicator of SME innovation activity and indicators of enterprise activity in the labour market, production, and service provision. Overall, the study demonstrated that innovative technologies for SMEs should not be an end in themselves; they must have an applied nature, aiming to improve production efficiency and lead to increased financial effectiveness of business operations. In general, correlation and regression analysis allow for obtaining reasonable and mathematically proven data in studies with large amounts of data, such as statistical materials. The use of correlation and regression analysis is justified, given the availability of a significant number of observations (regions of Ukraine) and the ability to clearly define the dependent and independent variables in the model. Thus, a key issue becomes the development of directions for the innovative growth of Ukrainian regions, considering the specifics of financing and the functioning of each region. Since there is already a certain imbalance between the regions, attention should be focused on ensuring conditions for uniform regional development to minimise the negative impact of uneven regional development on the Ukrainian economy (Fig. 2)
Ethics
The study used data from publicly available sources, so the ethical standards of goitre and information processing were not violated.
Limitations
While emphasising the possibility of using a large number of sources for the study, certain limitations should also be taken into account. Given the martial law in Ukraine, it should be emphasised that there is a lack of the most up-to-date statistical material on regional development, which is published in open sources with certain restrictions.
Figure 2. Algorithm for selecting scientific sources for research
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Identification of studies via databases and registers |
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Records removed before screening: Duplicate records removed (n = 5) Records marked as ineligible by automation tools (n = 5) Records removed for other reasons (n = 5) |
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Records excluded** (n = 5) |
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Reports not retrieved (n = 5) |
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Screening
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Reports excluded: Reason 1 (narrow specialization) (n = 6) Reason 2 (purely mathematical articles) (n = 8) Reason 3 (irrelevant research) (n = 2) etc. |
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Included |
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Studies included in review (n =59) Reports of included studies (n = 31) |
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Reports assessed for eligibility (n = 75) |
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Reports sought for retrieval (n = 80) |
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Records identified from*: Databases (n = 100) |
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Records screened (n = 85) |
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Identification |
Sources: compiled by the authors
Results
Capital investment is crucial in regional development, stimulating business expansion in specific areas. Capital investments typically come from shareholders or investors who expect a return on their contributions (Petrunenko et al., 2021). Capital investment is critical to running a successful business, allowing companies to grow, develop innovative projects, and remain competitive.
In Ukraine, regions' innovative activity in attracting capital investments in business could be more balanced. The concentration of innovation-active enterprises, research organisations, and educational institutions varies significantly across regions. Figure 3 shows the region's distribution of capital investment volumes over the past four years.
Figure 3. Capital Investments by Region for 2020-2023
Sources: compiled by the authors based on the State Statistics Service of Ukraine (2024)
Based on Figure 2, it can be argued that, in the context of capital investment development by region, the critical areas for Ukraine are the Dnipropetrovsk, Lviv, and Kyiv regions, along with the city of Kyiv. Although innovation activity is present in other regions, it remains significantly lower. Therefore, the most active instruments for stimulating further innovative development of small and medium enterprises should be applied to the most active regions.
In addition to innovation activity, it is necessary to analyse the industrial production index (Chlebna et al., 2023; Pan et al., 2022; Saputra et al., 2019), which will allow for an evaluation of each region's relative contribution to the overall production of goods and services within the country—see Figure 3. According to the data in Figure 3, it becomes apparent that the most significant fluctuations in production indices pertain to those regions that were partially occupied in 2014-2015, where production capacities were located in territories not controlled by Ukraine.
Figure 4. Indices of industrial production by region for 2015-2023
Sources: compiled by the authors based on State Statistics Service of Ukraine (2024)
When focusing on the efficiency of regional development, it is essential to examine the financial performance indicators of enterprises (Blažek &Květoň, 2023; Feng et al., 2023) concentrated in these regions. Data on the positive and negative financial results of Ukrainian businesses by region are presented in Figure 4. According to regional statistics, enterprises in Kyiv city, Dnipropetrovsk, Donetsk, Zaporizhzhia, Kyiv, Lviv, Poltava, and Kharkiv regions generate the most significant financial results. Consequently, the leading regions in financial performance are those with the highest concentration of industrial enterprises, as previously demonstrated (Table 2).
Table 2. Financial results before taxation enterprises with a breakdown by large, medium, small and microenterprises by regions in 2023
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Region |
Profit loss before tax, mln.UAH |
Profitable enterprises |
Loss-making enterprises |
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in % to the total number of enterprises |
financial result, mln.UAH |
in % to the total number of enterprises |
financial result, mln.UAH |
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Ukraine |
-216594.8 |
66.1 |
724687.6 |
33.9 |
941282.4 |
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medium enterprises |
-27337.8 |
71.9 |
324016.9 |
28.1 |
351354.7 |
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small enterprises |
-79861.4 |
65.8 |
176857.0 |
34.2 |
256718.4 |
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Vinnytsya |
12106.9 |
73.0 |
20919.9 |
27.0 |
8813.0 |
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medium enterprises |
6859.0 |
80.3 |
9919.9 |
19.7 |
3060.9 |
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small enterprises |
3792.2 |
72.5 |
7223.3 |
27.5 |
3431.1 |
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Volyn |
4326.7 |
73.6 |
11600.6 |
26.4 |
7273.9 |
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medium enterprises |
3484.0 |
83.9 |
5466.5 |
16.1 |
1982.5 |
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small enterprises |
55.6 |
72.8 |
3582.4 |
27.2 |
3526.8 |
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Dnipropetrovsk |
-42128.5 |
69.1 |
59854.4 |
30.9 |
101982.9 |
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medium enterprises |
-2268.8 |
71.9 |
17033.5 |
28.1 |
19302.3 |
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small enterprises |
-2009.0 |
68.9 |
14535.6 |
31.1 |
16544.6 |
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Donetsk |
-17452.1 |
57.4 |
14261.1 |
42.6 |
31713.2 |
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medium enterprises |
-20932.2 |
58.8 |
2305.2 |
41.2 |
23237.4 |
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small enterprises |
-2757.1 |
57.4 |
950.2 |
42.6 |
3707.3 |
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Zhytomyr |
4368.7 |
67.8 |
11421.5 |
32.2 |
7052.8 |
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medium enterprises |
3588.5 |
70.4 |
6401.1 |
29.6 |
2812.6 |
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small enterprises |
424.9 |
67.6 |
3528.3 |
32.4 |
3103.4 |
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Zakarpattya |
-132.4 |
69.5 |
6123.4 |
30.5 |
6255.8 |
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medium enterprises |
1911.2 |
80.0 |
3648.8 |
20.0 |
1737.6 |
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small enterprises |
-1261.3 |
68.9 |
2315.4 |
31.1 |
3576.7 |
|
Zaporizhzhya |
-32731.5 |
63.3 |
9913.9 |
36.7 |
42645.4 |
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medium enterprises |
-4455.7 |
64.1 |
2718.5 |
35.9 |
7174.2 |
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small enterprises |
-352.1 |
63.3 |
3598.7 |
36.7 |
3950.8 |
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Ivano-Frankivsk |
-6589.1 |
75.6 |
10873.1 |
24.4 |
17462.2 |
|
medium enterprises |
-3957.9 |
72.1 |
4430.5 |
27.9 |
8388.4 |
|
small enterprises |
1821.8 |
75.8 |
3381.9 |
24.2 |
1560.1 |
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Kyiv |
1679.3 |
68.7 |
44859.4 |
31.3 |
43180.1 |
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medium enterprises |
-5872.9 |
69.6 |
13768.8 |
30.4 |
19641.7 |
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small enterprises |
-1534.8 |
68.7 |
10342.0 |
31.3 |
11876.8 |
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Kirovohrad |
10902.3 |
77.3 |
15224.8 |
22.7 |
4322.5 |
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medium enterprises |
4427.9 |
75.8 |
7286.1 |
24.2 |
2858.2 |
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small enterprises |
4640.7 |
77.3 |
6105.0 |
22.7 |
1464.3 |
|
Luhansk |
-305.0 |
52.9 |
385.7 |
47.1 |
690.7 |
|
medium enterprises |
-236.8 |
60.0 |
325.9 |
40.0 |
562.7 |
|
small enterprises |
-68.2 |
52.6 |
59.8 |
47.4 |
128.0 |
|
Lviv |
25056.4 |
69.4 |
45513.3 |
30.6 |
20456.9 |
|
medium enterprises |
17477.2 |
74.5 |
25924.4 |
25.5 |
8447.2 |
|
small enterprises |
2669.6 |
69.0 |
12132.3 |
31.0 |
9462.7 |
|
Mykolayiv |
-19280.4 |
68.9 |
10234.8 |
31.1 |
29515.2 |
|
medium enterprises |
-5600.1 |
64.7 |
4797.9 |
35.3 |
10398.0 |
|
small enterprises |
-455.8 |
69.2 |
4208.4 |
30.8 |
4664.2 |
|
Odesa |
-12614.9 |
63.8 |
26607.9 |
36.2 |
39222.8 |
|
medium enterprises |
-9672.3 |
70.8 |
12448.6 |
29.2 |
22120.9 |
|
small enterprises |
-5475.0 |
63.4 |
10623.8 |
36.6 |
16098.8 |
|
Poltava |
12227.4 |
71.1 |
28126.2 |
28.9 |
15898.8 |
|
medium enterprises |
7351.2 |
73.6 |
12083.0 |
26.4 |
4731.8 |
|
small enterprises |
3049.7 |
71.0 |
5976.1 |
29.0 |
2926.4 |
|
Rivne |
-6813.6 |
69.4 |
8675.0 |
30.6 |
15488.6 |
|
medium enterprises |
-9003.8 |
80.6 |
4809.1 |
19.4 |
13812.9 |
|
small enterprises |
1288.6 |
68.6 |
2853.6 |
31.4 |
1565.0 |
|
Sumy |
2502.9 |
65.7 |
12758.5 |
34.3 |
10255.6 |
|
medium enterprises |
2640.2 |
70.3 |
7252.3 |
29.7 |
4612.1 |
|
small enterprises |
-2140.6 |
65.4 |
2978.7 |
34.6 |
5119.3 |
|
Ternopil |
6305.8 |
72.8 |
10683.9 |
27.2 |
4378.1 |
|
medium enterprises |
3408.5 |
81.0 |
5578.3 |
19.0 |
2169.8 |
|
small enterprises |
2981.1 |
72.2 |
3963.4 |
27.8 |
982.3 |
|
Kharkiv |
-5534.4 |
60.8 |
19392.6 |
39.2 |
24927.0 |
|
medium enterprises |
-1554.1 |
69.4 |
10098.5 |
30.6 |
11652.6 |
|
small enterprises |
-1701.5 |
60.3 |
8103.5 |
39.7 |
9805.0 |
|
Kherson |
-9271.9 |
48.5 |
923.9 |
51.5 |
10195.8 |
|
medium enterprises |
-2717.4 |
50.0 |
434.0 |
50.0 |
3151.4 |
|
small enterprises |
-6554.5 |
48.4 |
489.9 |
51.6 |
7044.4 |
|
Khmelnytskiy |
6840.6 |
74.5 |
17513.1 |
25.5 |
10672.5 |
|
medium enterprises |
5923.4 |
77.8 |
9935.4 |
22.2 |
4012.0 |
|
small enterprises |
1970.0 |
74.3 |
4114.1 |
25.7 |
2144.1 |
|
Cherkasy |
361.1 |
73.7 |
17598.4 |
26.3 |
17237.3 |
|
medium enterprises |
7106.9 |
78.3 |
10417.9 |
21.7 |
3311.0 |
|
small enterprises |
2453.0 |
73.4 |
4759.0 |
26.6 |
2306.0 |
|
Chernivtsi |
2843.5 |
69.1 |
4052.7 |
30.9 |
1209.2 |
|
medium enterprises |
1621.6 |
78.2 |
2380.6 |
21.8 |
759.0 |
|
small enterprises |
1164.5 |
68.4 |
1614.7 |
31.6 |
450.2 |
|
Chernihiv |
10885.9 |
65.5 |
15012.8 |
34.5 |
4126.9 |
|
medium enterprises |
5513.0 |
71.1 |
7855.0 |
28.9 |
2342.0 |
|
small enterprises |
1453.0 |
64.9 |
3237.9 |
35.1 |
1784.9 |
|
City of Kyiv |
-164148.5 |
59.8 |
302156.7 |
40.2 |
466305.2 |
|
medium enterprises |
-32378.4 |
68.3 |
136697.1 |
31.7 |
169075.5 |
|
small enterprises |
-83316.2 |
59.4 |
56179.0 |
40.6 |
139495.2 |
Source: MinFinMedia (2024).
Analyzing the financial results of small and medium-sized enterprises (SMEs) in Ukraine during martial law reveals that SMEs are operating inefficiently in the current conditions. The overall financial result across Ukraine shows a negative outcome, indicating a significant adverse impact of the war on the state of SMEs and their potential for further development.
An important question is whether these enterprises' innovative activities can improve their financial performance and whether other factors influence their ability to generate profit. To answer this, a correlation-regression analysis method can be applied, allowing us to determine the strength of the relationship between variables that characterize the innovation and financial development of Ukraine's regions. The indicators for conducting the correlation-regression analysis are presented in Table 3.
Table 3. Dataset of initial indicators for conducting a correlation-regression analysis of the efficiency of SMEs by region based on several dependent factors.
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Dependent indicator in the correlation-regression model |
Independent indicators in the correlation-regression model |
|||
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Financial results of small and medium enterprises in the region |
The volume of capital investments in the region |
The number of organisations carrying out scientific research and development in the region |
The number of employees in small and medium-sized enterprises by region |
Volume of products sold by small and medium-sized enterprises by region |
Source: compiled by the authors based on (Strielkowski et al., 2024; Wu & Dong, 2022; Zrybnieva et al., 2023)
In Figure 5, the results of the conducted correlation-regression analysis are presented.
Figure 5. Output data and results of the correlation-regression analysis of the efficiency of small and medium-sized enterprises in the regions based on a range of dependent factors
Sources: compiled by the authors
Regression equation:
Financial results of small and medium enterprises in the region = -20,14 + 0,32 × The volume of capital investments in the region + 0,07 × The number of organisations carrying out scientific research and development in the region + 0,11 × The number of employees in small and medium-sized enterprises by region + 0,17 × Volume of products sold by small and medium-sized enterprises by region.
Based on the data presented in Figure 4, we can assert that the model meets the statistical characteristics, with the correlation coefficient 𝑅=0.96. This indicates that the selected independent variables explain 96% of the trends of the dependent variable. To verify the adequacy of the model, it is also essential to check the model against the normal distribution of the data used for constructing the model and the distribution of errors, as shown in Figure 6.
Figure 6. Checking the model data for compliance with the ordinary distribution law
Sources: compiled by the authors
Based on the data presented in Figure 6, the model's initial data adhere to the customary distribution law; therefore, the model can be considered suitable for practical application. After assessing the statistical characteristics of the model, it is appropriate to proceed to the economic interpretation of its results. Thus, the financial performance of small and medium-sized enterprises in the region is directly influenced by several factors, among which their ability to make capital investments and conduct research and development is particularly noteworthy. It is evident that it is only possible to develop the innovative component of operations with the involvement of personnel; consequently, the workforce's size also impacts the enterprise's profitability.
The conducted correlation-regression analysis indicates that for the continued effective functioning of small and medium-sized businesses in the regions and for active recovery during the post-war period, attention should be paid to their comprehensive development, taking into account not only their innovative activity but also the stimulation of production processes and the engagement of qualified personnel.
Discussion
In recent years, the issue of uneven regional development in Ukraine has become particularly pressing, especially since the onset of full-scale hostilities on its territory. The eastern, southern, and northern districts have endured noteworthy pulverization. At the same time, the central and western parts of the nation have taken in a impressive number of inside uprooted people and experienced harm to foundation. Meanwhile, small and medium-sized enterprises are struggling due to a decrease in the population's purchasing power and disruptions in energy supply.
In any case, it is fundamental to stress that the uneven improvement of Ukraine's districts was apparent indeed some time recently the war and was impacted by each area's geological, demographic, and social specifics. Therefore, attention should be focused on the contentious issues that arise while analysing the innovative activity of small and medium-sized enterprises in different regions.
In the academic literature, authors predominantly highlight that regional development is the foundation of a country's economic success (Castro-Arce et al., 2020; Mustafin et al., 2022; Kosovych, 2022). In this context, the government should ensure maximum regional development uniformity. Achieving this is undoubtedly challenging, especially for large countries spanning vast territories. In any case, uniform territorial advancement ought to ended up one of the needs of state approach in guaranteeing the feasible improvement of administrative-territorial units (Rantala & Ukko, 2019; Samara et al., 2023; Storozhyk, 2024). Additionally, it is essential to consider the perspective of leading scholars, who assert that a primary task for contemporary Ukrainian regions is to preserve industrial potential and a viable workforce. At the same time, development can occur during the post-war recovery period.
The primary step towards diagnosing and along these lines changing the state of territorial advancement, agreeing to conspicuous researchers (Hervás-Oliver et al., 2021; Fan et al., 2020; Michálková et al., 2023), is to conduct a thorough analysis of statistical data and if necessary, to cluster districts based on their financial and budgetary advancement, the volume of pulled in speculations, and the potential for creating particular segments. The issue of territorial clustering has too been broadly examined within the writing (Lin, 2020; Mukhalchenko et al., 2023), permitting analysts to choose beginning information for investigation and utilize the comes about to create measures custom-made to each interesting gather of locales. In any case, it ought to be famous that for Ukraine nowadays, clustering will as it were serve a demonstrative reason and will not show key headings for progressing the region's circumstance.
Suggestions for improving territorial exercises can essentially center on creating a arrange for drawing in speculations from private and organization financial specialists (Guo et al., 2022; Le et al., 2021; Prokop & Stejskal, 2019), as well as making ideal conditions for fortifying inventive action inside the locales (Kuczabski et al., 2023; Saputra et al., 2020; Yaskov&Smiesova, 2023). In any case, inventive movement ought to not be restricted to a particular division or industry; instep, it can be realised in any field, because it serves as a fundamental condition for convenient and comprehensive territorial advancement.
A isolated zone of logical inquire about (Afanasieva, 2023; Leckel et al., 2020; Zhou et al., 2021) centers on creating money related administration apparatuses at the territorial level. The quality of administrative choices made by local specialists altogether impacts the region's capacity to form ideal conditions for trade improvement and draw in speculations.
Characterizing territorial execution and viability pointers remains a subject of discussion within the writing. One gather of analysts (Hao et al., 2022; Medeiros et al., 2020; Sydorenko, 2024) recommends basically centering on pointers related to budget incomes and the money related execution of administrative bodies; others (Al-Hanakta et al., 2021; Batorshyna et al., 2021; Grillitsch&Sotarauta, 2020) underscore the influx of the workforce to the locale and the nearness of tourism streams. A widespread methodological approach to deciding the viability of territorial advancement has yet to be displayed within the writing, and this can be a course for advance investigate. All things considered, the money related execution markers produced by undertakings in a locale can demonstrate the advancement of a particular region or group of districts.
It is also worth noting that the interest in the concept of the system of regional innovation development that has significantly increased in the literature in recent years is related to the search for new forms of understanding the competitive environment that is changing under the influence of digital technologies ((Angelakis &Μanioudis, 2024; Stoika et al., 2023; Thomas et al., 2021). At the same time, it should be added that the formation of flexible production networks and appeals to new forms of cooperation between all participants in regional innovation development accompanies digital transformation. However, it should also be noted that the definitions of approaches to regional innovation development vary in detail but are united in their interpretation of collective nature as an identifying feature: participants in regional innovation processes depend on each other to create value through the pooling of competencies, sharing of resources and redistribution of risks. They cooperate through interactive networks, performing different roles and functions in creating new values and joint interdependent development.
Also, for example, in (Luo et al., 2023; Rodríguez-Pose & Ketterer, 2020), the issues of innovative regional development are defined as a set of activities, norms and institutions, as well as the relations between them that develop in the process of innovation. However, the literature (Irfan et al., 2022; Luo et al., 2023) also presents a view that innovative approaches to regional development are considered as an 'organisational integrity' and an environment of innovation at the current stage of economic development with its characteristic segmentation and determination of the direction of development of each particular region. It is worth supplementing the opinion of the above scholars with the idea that in Ukraine, achieving economic integrity in the regional development process is possible. However, the process of innovative development of regions at the present stage is complicated by the unevenness of the extent to which regions have suffered due to military operations and the amount of money needed to restore each region. Moreover, it is critical to ensure balanced regional development without the emergence of regions of leaders and regions of outsiders. Disproportions in developing territorial systems are the most critical problem of post-war regional development in Ukraine.
Modern digitalisation processes, on the one hand, exacerbate inequalities, and on the other hand, are seen as a real opportunity to level the information space, provide communication, access to various services, distance education and remote employment, and other opportunities (Angelakis et al., 2024). However, this idea should be developed and added, as it is most relevant for peripheral areas remote from large cities and agglomerations, especially those suffering the most from hostile shelling. However, these benefits are limited by the still unevenly developed information infrastructure, the cost of its modernisation and expansion, the lack or poor quality of communication services, and the need for more motivation and literacy of the population. This increases the relevance of monitoring innovative development dynamics in Ukraine's different territories.
Considering the problems of integrating spatial and socio-economic development of regions, researchers (Ding et al., 2021) note the difference between the goals of spatial policy and socio-economic policy in regional subsystems. On the one hand, the objectives of spatial policy include the rational use of space, protection of the natural and cultural environment, and functional management of space. On the other hand, only at the level of the central territorial units do the tasks of socio-economic policy include creating optimal living conditions for the population of this territory, stimulating economic and labour market development, entrepreneurship, innovation, and attractiveness of the territories.
Conclusion
As a result of the conducted research, an analysis of the statistical data regarding the financial and economic development of the regions of Ukraine was performed. The study indicated that the most economically powerful administrative-territorial unit is the city of Kyiv and the Kyiv region, along with the Dnipropetrovsk and Lviv regions, with the highest concentration of legal entities. Consequently, the most significant amounts of investment are attracted here. Subsequently, an analysis of the financial results generated by small and medium-sized enterprises in the regions was conducted, which revealed that the situation in 2023 is unfavourable, necessitating that small businesses develop and implement measures to optimise their system of innovative development and realise the economic potential of small and medium-sized enterprises in the regions.
Based on the correlation-regression analysis conducted, it was established that there exists a strong dependency between the financial results of small and medium-sized enterprises in the region and the following set of indicators: the volume of capital investments in the region, the number of organisations conducting research and development in the region, the number of employees engaged in small and medium-sized enterprises across the regions, and the volume of products sold by small and medium-sized enterprises in the regions. Accordingly, to enhance the operational effectiveness of small businesses in the regions, it is essential to ensure the innovative development of these enterprises and create conditions for enhancing their human resource potential.
Considering the significant attention scholars have paid to this research topic, it can be inferred that it will continue to be the focus of academic inquiry. The primary directions for future scientific research in this area may include issues related to state support for small and medium-sized enterprises during the post-war recovery period and aspects of the digital development of contemporary Ukrainian small and medium-sized businesses.
References
