




































AGORA International Journal of Economical Sciences, http://univagora.ro/jour/index.php/aijes 

ISSN 2067-3310, E-ISSN 2067-7669 

Vol. 19, No. 1 (2025), pp. 303-314 

 

303 

 

THE IMPACT OF DIGITAL TRANSFORMATION ON ENTERPRISES' 

RESILIENCE: EVIDENCE FROM UKRAINE 
 

A. SOROKINA, L. LEBEDEVA 

 

Alyona Sorokina¹, Larysa Lebedeva² 

¹ ² State University of Trade and Economics, Ukraine 

¹ https://orcid.org/0000-0002-6512-2776, E-mail: a.sorokina@knute.edu.ua  

² https://orcid.org/0000-0001-8632-5460, E-mail: l.lebedeva@knute.edu.ua 

 

Abstract: The research focuses on determining the impact of digitalization factors on 

the resilience of Ukraine’s entrepreneurial sector. The main aim is to determine whether 

digitalization has a positive impact on the resilience of enterprises. The factors under research 

include the following: the availability of Internet access at Ukrainian enterprises, their e-

commerce, the number of employees involved in research and development, and the share of 

enterprises that employ ICT specialists. The research methodology has two components: the 

use of a multifactor nonlinear regression model and the calculation of the proposed Index of 

Digital Penetration in the Ukrainian business sector. The results show that the most influential 

factors of digitalization are: the presence of employees specializing in ICT and e-commerce. 

Both factors make Ukrainian enterprises more resilient and adaptive to shocks. However, the 

results of the Digital Penetration Index emphasize the low level of digital transformation in 

Ukrainian enterprises, particularly limited automation and insufficient use of cloud computing 

and artificial intelligence technologies. The results of the study confirm that digitalization does 

enhance the resilience of Ukraine's entrepreneurial sector, but the low level of digital 

transformation underscores the need for legislative action to accelerate the development of 

advanced digital technologies. In order to benchmark the experience, the authors compare the 

use of digital technologies in Ukrainian and EU enterprises. The results of the research can be 

used to deepen the study of sectoral resilience, the experience of EU countries, and to provide 

recommendations for digital development of Ukraine. 

Keywords: digital transformation, economic resilience, enterprises' resilience, digitalization 

 

INTRODUCTION 

Enterprise resilience in the context of digitalization refers to the ability of businesses to 

integrate digital technologies to maintain competitiveness, ensure the continuity of business 

processes, and absorb shocks of various kinds. Two positive effects of digital technology 

adoption by the entrepreneurial sector can be identified. First, at the micro-level, it directly 

improves enterprise efficiency (positive correlation may result from process automation, better 

data management, and enhanced communication capabilities (Wang et al., 2023)). 

Summarizing existing theoretical research (Caputo et al., 2020; Bican & Brem, 2020; Legner 

et al., 2017), digitalization affects enterprise productivity through operational efficiency 

improvement, market expansion, better communication between business and household 

sectors, product diversification, and adaptability to a changing business environment. In 

addition, according to recent research, the development of a digital culture has a beneficial 

impact on the sustainable development of enterprises (Serafimova & Vasilev, 2024). Such 

https://orcid.org/0000-0002-6512-2776
mailto:a.sorokina@knute.edu.ua
https://orcid.org/0000-0001-8632-5460
mailto:l.lebedeva@knute.edu.ua


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positive correlations contribute to enterprise resilience, as these conditions enable faster 

recovery following shock events. 

The second assertion logically follows: digital technology adoption by the 

entrepreneurial sector enhances the resilience of the entire economic system. This can be 

attributed to the transformation of business models and the creation of new products (which 

increase economic diversification and, hence, adaptability); global market entry and revenue 

source diversification (which improve competitiveness and recovery capacity); and cost 

reduction through digitalization (which enhances the system’s absorption capacity). 

This paper aims to assess the impact of digitalization factors on the resilience of 

Ukraine’s entrepreneurial sector. Research on the digitalization impact on enterprise resilience 

in Ukraine remains limited. While significant attention has been paid to economic security 

(Zinenko & Kobielieva, 2022; Hrinkevich et al., 2023; Ohrenych & Dibrova, 2023), innovation 

development, digitalization, and their implications for enterprise security (Popelo et al., 2023; 

Zubko et al., 2021; Kuzior et al., 2022; Dubyna et al., 2023), the concept of resilience and the 

direct impact of digital technologies are mostly explored theoretically. Therefore, expanding 

the research focus is appropriate. 

This research addresses the following questions: (1) Can digitalization factors influence 

the resilience of Ukrainian enterprises? (2) If so, which factors have greater or lesser impacts? 

(3) If digital technologies affect enterprise resilience, what is the current level of digital 

technology penetration in Ukraine’s entrepreneurial sector? 

 

METHODS 

The research consists of two quantitative components: (1) the application of a nonlinear 

regression model to assess the impact of digitalization on enterprise resilience and (2) the 

calculation of the Digital Technology Penetration Index for Ukraine’s entrepreneurial sector. 

The assessment of the impact of digitalization factors on enterprise resilience was 

conducted using mathematical modeling, particularly a multifactor nonlinear regression model. 

This method is widely employed by both Ukrainian (for assessing the impact of digitalization 

on economic security (Zubko et al., 2021)) and international researchers (for assessing the 

impact of digital technologies on urban resilience (Shi et al., 2023), the influence of digital 

transformation on SME resilience (Omoush et al., 2023), and the effect of innovation on urban 

disaster resilience (Samarakkody et al., 2023)). Several key theoretical and methodological 

considerations justify the choice of a nonlinear regression model: the influence of digitalization 

factors is often nonlinear due to varying intensities and speeds of enterprise adaptation to digital 

changes, and complementary or substitution effects are better evaluated through nonlinear 

models. 

The calculation of the Index involves the following steps: 

1. Selection of indicators and data collection. Indicators were chosen to reflect the level 

of digital technology adoption and use by national economy enterprises (Table 4). 



Alyona SOROKINA, Larysa LEBEDEVA 

 

305 

 

2. Definition of threshold values. Thresholds were developed considering Ukraine’s 

economic specifics (size, development dynamics, historical context, strategic 

digitalization goals), as well as the experience of EU countries. 

3. Data normalization according to threshold values. If an indicator value exceeds the 

threshold, it is normalized to 1; otherwise, it is normalized to 0. 

4. Calculation of digital technology penetration: 

𝐼𝑚 =
Σ𝑁 = 1

Σ𝑁𝑥
× 100% 

where 𝐼𝑚 is an integral indicator of the m-th sector of the economy, where m = (1, 2, 3) 

Nx=1 — is the number of indicators whose normalized value is 1; 

Nx — number of indicators. 

 

DATA 

The research process and results depend entirely on the availability of statistical data. 

The assessment of Ukraine’s digital environment used data from the State Statistics Service of 

Ukraine and official EU statistics, as well as international indices (Global Innovation Index 

and Frontier Technology Readiness Index). Due to the ongoing war initiated by Russia, data 

collection has been suspended or restricted, limiting the research scope. The quantitative 

assessment took into account only those time periods that had the most complete statistical 

data. For missing indicators, the latest available data were used. 

 

RESULTS 

To build this model, it is necessary to define the dependent variable (Y) and independent 

variables (X) (Table 1). Accordingly, within the model, the dependent variable will be an 

indicator that assesses the economic resilience of the entrepreneurial sector. The independent 

variables are indicators that will reflect the factors of digitalization's impact on resilience. 

As a dependent variable, the indicator of value added by production costs of economic 

entities was chosen. We believe that the selected indicator successfully demonstrates the 

resilience of the sector: value added by production costs actually means the ability of 

enterprises to create new economic value. Even in the face of shocks, enterprises with a stable 

level of value added are better able to maintain their operations and ensure financial 

independence. 

The indicators that will serve as independent variables and reflect the impact of 

digitalization on economic resilience are: the number of enterprises with access to the Internet; 

the volume of products (goods, services) sold by enterprises derived from e-commerce; the 

number of employees involved in research and development; and the share of enterprises with 

ICT specialists. 

In addition, we believe that it would be appropriate to assess the use of CRM systems 

by enterprises of the national economy (as this is a direct reflection of automation processes) 

and the state of cybersecurity, but currently there is no statistical data for the period under 

research. It should also be noted that due to the lack of statistical data for the share of the 



THE IMPACT OF DIGITAL TRANSFORMATION ON ENTERPRISES' RESILIENCE: 

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number of enterprises that employ ICT specialists (statistical data are not available for 2020 

and 2022), the model may contain a certain percentage of uncertainty - for the purpose of the 

assessment, the indicators for 2020 and 2022 were projected based on the growth (decline) 

rates of previous years. 

 

Table 1. Initial data for assessing the impact of digitalization on value added by economic 

entities' expenditures 

 Value added by 

production 

costs of 

economic 

entities 

The number of 

employees 

involved in 

research and 

development 

The number 

of 

enterprises 

with access 

to the 

Internet 

The volume of 

products (goods, 

services) sold by 

enterprises derived 

from e-commerce 

The share of 

enterprises 

with ICT 

specialists 

Year Y X1 X2 X3 X4 

2018 2640886379,2 88128 43303 228 035 634,70 22,3 

2019 3121256476,2 79262 43785 292 731 939,10 21,6 

2020 3294768464,7 78860 44271 364 571 488,00 20,9 

2021 4594232280,4 68808 44508 435 909 793,90 21,7 

2022 3947735837,3 53221 42785 465 316 898,70 17,7 

2023 4838907049,6 58567 34204 547 590 249,30 17,7 

Source: Website of the State Statistics Service of Ukraine, 2022 

 

Calculations and model building were based on a regression model in Excel. The level 

of reliability is defined as 0.95 - the boundaries of the confidence interval for each regression 

coefficient cover the true value with a probability of 95%. Considering the upper limit of the 

confidence interval for each of the coefficients, the model is as follows: 

�̌� =  −49274,9𝑋1  − 72464,9𝑋2  + 6,5𝑋3  + 433463774,7𝑋4  − 1029872880 

The coefficient of determination 𝑅2 is quite high and amounts to 0.999. Thus, the 

variation of value added by the costs of economic entities is 99% determined by the variation 

of the proposed factors, but there are 0.1% that are unaccounted for. 

These results allow us to assess the adequacy of the model. According to the Fisher's 

test of adequacy, the obtained F-value (0.02) is lower than the significance level (0.05), so since 

𝐹 < 𝑎, we can say that the model is generally statistically significant and adequate. We can 

assess the adequacy and statistical significance of each coefficient separately by using the 

critical t value from the Student's statistical table. If the critical significance level is 𝛼 = 0.05 

and the degree of freedom is n-m=2, the critical value is 2.920. As can be seen from the results 

of the t-test (Table 2), all available coefficients are greater than the critical value. This indicates 

that they are not statistically significant. Therefore, we consider it necessary to use a different 

type of model to evaluate the selected indicators. 

 



Alyona SOROKINA, Larysa LEBEDEVA 

 

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Table 2. Calculations of a multifactor linear model 

 Coefficients t-statistics p-value R-square The 

significance 

of F 

Y -1029872879,60175 -2,33445888668255 0,257650973 0,999 0,0240 

X1 -49274,90302 -10,8441748720604 0,058540589 

X2 -72464,89698 -10,5163655881444 0,060354627 

X3 6,54706318666723 17,1301999848115 0,037121463 

X4 433463774,656223 19,6914621593524 0,032301987 

Source: compiled by the authors 

 

From now on, we will use a power function with its transformation to a linear form as 

a result of logarithmizing. The function will have the following form: 

𝑙𝑛𝑌 = 𝑙𝑛𝐴 + 𝛼 × 𝑙𝑛𝑋1 + 𝛽 × 𝑙𝑛𝑋2 + 𝛾 × 𝑙𝑛𝑋3 + 𝛿 × 𝑙𝑛𝑋4 

The calculations were performed by building a regression model in Excel, and the 

results are as follows: �̀� = 10.33, 𝛼 = −1,02, 𝛽 = −0,9, 𝛾 = 0,61, 𝛿 = 2,39. 

Accordingly, taking into account the logarithmization of the coefficients, we have the 

following form of the function: 

𝑌𝑐𝑎𝑙𝑐 = exp (10,33) × 𝑋1
−1,02 × 𝑋2

−0,9 × 𝑋3
0,61 × 𝑋4

2,39
 

The final result after calculating the exponential function: 

𝑌𝑐𝑎𝑙𝑐 = 30,638.1 × 𝑋1
−1,02 × 𝑋2

−0,9 × 𝑋3
0,61 × 𝑋4

2,39
 

The coefficient of determination 𝑅2 of the newly created model remained at the same 

level - 0.99, which still indicates a high influence of the factors considered. We can also assess 

the adequacy of the model, in particular, using Fisher's criteria. For this purpose, we will use 

the result of the F-value for the built model and the tabulated F-value for the significance level 

of 0.05. To select the correct table value, we also took into account the number of independent 

variables (4) and the total number of observations (6) minus the number of parameters. 

Accordingly, 𝐹𝑡𝑎𝑏𝑙𝑒 = 7.7, 𝐹𝑐𝑎𝑙𝑐 = 3354,08; 𝐹𝑐𝑎𝑙𝑐 > 𝐹𝑡𝑎𝑏𝑙𝑒. We can conclude that the model 

is reliable, all factors have an impact on the dependent variable (p-value in Table 3). 

 

Table 3. Results of calculations using a power function with logarithmization 

 Coefficients t-statistics p-value R-square The significance of F 

Y 10,32814803 28,62656837 0,022229734 0,999 0,012949335 

X1 -1,015903715 -24,22316748 0,026266527 

X2 -0,903507143 -26,19640569 0,024290005 

X3 0,607733673 39,84619939 0,015973573 

X4 2,392693185 35,46667481 0,017945047 

Source: compiled by the authors 

Thus, according to the results of the calculations, the factor of the availability of ICT 

employees at enterprises has the greatest impact on the entrepreneurial sector's resilience. There 

are several reasons for this: first of all, enterprises with ICT specialists are able to demonstrate 



THE IMPACT OF DIGITAL TRANSFORMATION ON ENTERPRISES' RESILIENCE: 

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greater preparedness for digital threats (cyberattacks or NDA data leaks), which directly affects 

their ability to maintain functionality during economic shocks. In addition, there is a possibility 

of greater flexibility and technical competitiveness of the enterprise: the presence of ICT 

specialists in the enterprise allows for the introduction of modern digital technologies, and thus, 

increases the efficiency of operational processes. 

The results also show that e-commerce has a significant impact, which can be explained 

accordingly: 

1. E-commerce actually eliminates most of the barriers to doing business: physical 

interaction between consumer and seller is replaced by digital communication (which 

is faster and more affordable), and it is easier to expand the market - it becomes possible 

to compete not only in the national but also in the international market, with a positive 

result of diversifying the customer base. 

2. Another positive effect of e-commerce is the reduction of transaction costs: enterprises 

can increase their profitability by reducing the cost of renting premises, logistics, etc. 

However, of course, there is also the possibility that costs will be incurred for 

maintaining a website, CRM systems to automate customer interaction, and the 

development of digital marketing campaigns. 

The impact of Internet access at the enterprise and the number of employees involved 

in R&D is also statistically significant. However, it should be noted that the effectiveness of 

these two factors is difficult to assess in the short term (which is why their impact is negative 

in the current situation, see Table 3). For example, the effect of R&D can be traced 

conditionally in 5-10 years, and the effect of using the Internet connection is also not 

immediately noticeable (or its significance is not so great). In order to comprehensively assess 

the level of digital transformation of Ukraine's entrepreneurial sector, we propose to consider 

the developed Digital Penetration Index (Table 4). 

 

Table 4. Input data for the calculation of the Digital Penetration Index in the entrepreneurial 

sector of Ukraine 

№ Indicator 

Threshold 

value 2022 

1 Share of enterprises engaged in e-commerce in the total number of enterprises, %. ≥ 22 6.1 

2 

Share of the number of enterprises using fixed Internet access in the total number of 

enterprises, %. ≥ 90 61.8 

3 

Share of the number of enterprises applying ICT security measures in the enterprise's 

information and communication systems in the total number of enterprises, %. ≥ 90 73.2* 

4 

Share of enterprises purchasing cloud computing services in the total number of 

enterprises, %. ≥ 40 9,8 

5 Exports of ICT services, USD billion ≥ 6.5 7.52 



Alyona SOROKINA, Larysa LEBEDEVA 

 

309 

 

6 

Share of the number of enterprises that faced problems due to ICT security incidents 

in the total number of enterprises, %. ≥ 15 24.7 

7 

Share of the employed population in the ICT sector in the total number of employed 

people, % ≥ 4 1.9** 

8 

Share of the number of enterprises using artificial intelligence technologies in the total 

number of enterprises, %. ≥ 6 5.4 

9 Global Innovation Index ≥ 30 32,3 

10 Frontier Technology Readiness Index ≥ 0.61 0.59 

Source: Website of the State Statistics Service of Ukraine, Global Innovation Index (GII), 

Frontier technology readiness index 

* — statistical data for 2023; 

** — statistical data for 2021; 

After analyzing the available statistics, we can calculate the level of digital penetration 

in Ukraine's entrepreneurial sector using the following formula: 

𝐼𝑚 =
Σ𝑁 = 1

Σ𝑁𝑥
× 100% 

Thus, the calculation is as follows: 

𝐼1 =
3

10
× 100% = 30% 

The level of digital technology penetration in Ukraine's business sector is 30%. 

According to the proposed assessment scale (Table 5), this level is low, which means minimal 

adoption of digital technologies. Business processes are mostly performed manually, but there 

is a small percentage of automation. The level of digital skills of employees is also low and 

needs to be significantly improved. 

 

Table 5 

Digital penetration 

scale 

Penetration level Meaning 

100-80% High Business operations are fully dependent on digital 

technologies. Business processes are automated, 

artificial intelligence, cloud computing, and IoT 

are used. Employees' digital skills are at a high 

level. 

80-60% Sufficient Digital technologies are actively used in 

operations, but not to the fullest extent. Thus, 

business process automation is selective and 

digital tools are partially used. The level of digital 

skills of employees is average. 

60-40% Moderate Digital technologies are used only for certain 

business processes, automation is fragmented, 

with limited use of digital tools. There is a need to 

improve the digital skills of employees. 



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40-20% Low Digital technologies are implemented at a minimal 

level. Business processes are mostly performed 

manually, but there is a small percentage of 

automation and use of digital tools. Low level of 

digital skills of employees. 

20-0% Extremely low Digital technologies are hardly used, and 

enterprises are dominated by “traditional” 

approaches to doing business, without significant 

automation. The level of digital skills among 

employees is too low. 

Source: compiled by the authors 

 

Statistical analysis shows that the weakest points of Ukraine's entrepreneurial sector are 

indicators related to automation (in particular, the use of AI and cloud computing in 

enterprises). Compared to EU countries, the share of enterprises using AI technologies in 

Ukraine is not very high - 5.4% (statistical data of enterprises with 10 to 49 employees) 

(Website of the State Statistics Service of Ukraine, 2022), while the average value in EU 

countries is 6.2% (Eurostat, 2022). It is also worth noting that a characteristic feature of the 

national economy is the invariance of this indicator depending on the size of the enterprise: the 

share of large enterprises using AI technologies in Ukraine is 5.2% (which is 0.2% less than 

the same share in the context of small enterprises). On the contrary, compared to small 

enterprises, large enterprises in the EU use AI technologies more often - 14.5% (Eurostat, 2022) 

across the EU. Obviously, the conditions of a full-scale war somewhat limit the introduction 

of innovative technologies in enterprises, but as a rule, large enterprises are more resilient and 

adaptive to shocks, so it is surprising that they fund AI technologies less. 

 

Figure 1. Share of enterprises using AI technologies in Ukraine and EU countries 

 
Source: compiled on the basis of (Eurostat, 2022; Website of the State Statistics Service of Ukraine, 2022) 

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Alyona SOROKINA, Larysa LEBEDEVA 

 

311 

 

The share of the number of enterprises that purchase and use cloud computing services 

is also low compared to EU enterprises. While the average value for the EU countries is 42.5% 

(2023), only 9.8% of Ukrainian enterprises take advantage of cloud computing. 

Internet access also needs to be improved. In 2023, 80.8% of Ukrainian enterprises had 

access to a fixed-line Internet connection, which is 19% more than in 2022. However, under 

ideal conditions, this figure should reach at least 90%, as the experience of EU countries shows. 

We assume that this may be due to infrastructure constraints: areas with low population density 

have a lower number of fixed Internet access lines, where providers are not economically 

interested in laying fixed networks. In addition, damage to or destruction of infrastructure as a 

result of hostilities, especially in frontline areas, significantly complicates access to the fixed 

Internet. It should not be forgotten that enterprises with unstable income tend to use an 

alternative network - the mobile Internet. 

The level of digital security in the business sector can be indicated by the share of 

enterprises that use ICT security measures. According to statistics, in 2023, there were not too 

many ICT incidents among Ukrainian enterprises - the share of the number of enterprises that 

faced problems was 24.7% (in the total number of enterprises) (Website of the State Statistics 

Service of Ukraine, 2022). The most vulnerable economic activities are: manufacturing 

(production of coke and petroleum products, basic pharmaceutical products and 

pharmaceuticals); wholesale and retail trade; computer programming, consulting and related 

activities; provision of information services; travel agencies, travel operators, provision of 

other reservation services and related activities. 

 

Figure 2. Types of ICT incidents among Ukrainian enterprises 

 
Source: compiled on the basis of (Eurostat, 2022; Website of the State Statistics Service of Ukraine, 2022) 

At the same time, security measures are used by the vast majority of enterprises in the 

national economy - 73.2% in 2023. The most commonly used security measures include strong 

password authentication (66.3%) (unfortunately, more secure authentication methods, such as 

biometric methods or a combination of two authentication methods, are used much less 

frequently), backing up data to a secure location (52.7%), controlling network access (44.6%), 

encrypting data, documents, or email (23%), and VPN (21.4%). However, these figures are 

21.8

3.9

5.9

2.2

0.6

0.7

0.0 5.0 10.0 15.0 20.0 25.0

Unavailability of ICT services due to hardware or…

Unavailability of ICT services due to an external…

Destruction or corruption of data due to…

Destruction or corruption of data due to…

Disclosure of confidential data through…

Disclosure of confidential data due to…

Share of the number of enterprises that faced 
problems due to ICT security incidents

Share of the number of enterprises that faced problems due to ICT security incidents



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significantly lower than in the EU, where 92% of businesses use at least one security measure 

on average. The most popular in the EU are password authentication (82%), backups (78%), 

and network access control (65%). 

The strength of the digital transformation process of Ukraine's business sector is the 

size of ICT exports and the resilience of the IT sector as a whole. Even though the national 

economy's ICT services exports have a positive upward trend, 2023 was the first year when the 

value of this indicator decreased. According to the World Bank, in 2023, Ukraine's ICT services 

exports amounted to USD 6.8 billion. USD (for comparison, in 2022, the value of the indicator 

was 7.52 billion USD, which is 0.72 billion USD less. USD, which is 0.72 billion more). It is 

noted that the reason for this may be a slowdown in economic growth in global markets. The 

countries from which the revenue from ICT exports comes are: USA (USD 2,667 million), 

Malta (USD 567 million), Great Britain (USD 535 million), Cyprus (USD 362 million), Israel 

(USD 293 million), Germany (USD 275 million), and Switzerland (USD 274 million). All of 

these countries are currently experiencing a recession, and the demand for ICT services is not 

as high as it was during COVID-19. Local reasons are also worth highlighting: increased 

investment risks due to a full-scale invasion and the mobilization process, which affects the 

number of IT professionals. 

 

DISCUSSIONS 

Thus, the use of a quantitative approach, specifically building a nonlinear regression 

model, enabled the identification of the impact of digitalization factors on the resilience of 

Ukraine’s entrepreneurial sector. According to the results, the most significant influence on 

value added by production costs of economic entities stems from the presence of ICT 

specialists in enterprises and the adoption of e-commerce. The presence of ICT specialists 

directly affects economic resilience by ensuring productivity and adaptability. Employees with 

ICT skills and, accordingly, a high level of digital culture, increase resilience, strengthening 

the enterprise's innovation potential, flexibility to change and competitiveness (Serafimova & 

Vasilev, 2024). E-commerce, in turn, is no less important for enterprise resilience. Enterprises 

that use e-commerce as a sales channel can respond more swiftly to demand fluctuations, scale 

sales, and optimize transaction costs. These factors most significantly contribute to enhancing: 

(1) economic efficiency, (2) digital adaptability, and (3) resilience to external shocks. 

However, the results of the Digital Technology Penetration Index for Ukraine's 

entrepreneurial sector indicate that processes related to e-commerce and the employment of 

ICT specialists remain among the weak points of the national economy, as their values fall 

below threshold levels. This undoubtedly limits the resilience of Ukraine’s entrepreneurial 

sector. Firstly, there is a substantial negative impact on adaptability—in the case of 

macroeconomic or geopolitical shocks (such as the onset of the full-scale invasion), enterprises 

lacking digital sales channels or automated processes are less able to adapt to changes. 

Secondly, this contributes to reduced competitiveness across the economy, as a low percentage 

of ICT specialists constrains the adoption of advanced digital technologies. 



Alyona SOROKINA, Larysa LEBEDEVA 

 

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Despite the comprehensive analysis, the research has certain limitations. The most 

significant limitation relates to the use of statistical data. It would have been preferable to 

analyze a longer time period, thereby obtaining more regression observations, which would 

have greatly increased the accuracy of the results. However, official data for some selected 

indicators were unavailable. This affected both the time frame for the regression model and the 

calculation of the Digital Technology Penetration Index. As noted, the Index was calculated 

only for 2022, which considerably limits the ability to draw precise conclusions. Nevertheless, 

this period provided the most comprehensive set of statistical data for the selected indicators. 

The choice of threshold values for the Index indicators is also a matter of discussion. In 

most cases, their development is based on a quantitative method, i.e., calculating the median 

value among the results of the European Union countries, but certain qualitative characteristics 

were also taken into account (such as the historical context of Ukraine's economic 

development, the pace of digitalization and its strategic vision in the country, current shocks, 

etc.), which indicates a degree of subjectivity in this approach. 

Considering the results and limitations, the study has the potential for further 

development. The publication of official statistics for more specific indicators (e.g., 

cybersecurity, cloud computing, and AI) is becoming regular, so it is expected that it will be 

possible to assess longer time periods in the future and expand the analysis of the Index 

indicators, which will make the analysis more accurate and comprehensive. Additionally, 

sectoral analysis warrants attention. Understanding that digitalization factors do have a positive 

impact on the resilience of enterprises, the question arises as to which industries are more 

affected and whether digitalization is a key factor for all industries. In this regard, it would be 

valuable to compare the most significant sectors contributing to Ukraine’s GDP and assess the 

impact of digitalization factors on them. 

Also, since the research is partly based on a comparison of Ukraine's experience with 

the EU countries, there is a need for a broader analysis: a comparison of regression analysis of 

the impact of digitalization on EU and Ukrainian enterprises, and a study of the experience of 

European countries. Although the results of the study and the developed Index are adapted to 

the economic conditions of Ukraine and there is no direct generalization of the study, it is 

possible to adapt the methodology and structure of the research to other countries. 

 

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