Digital Transformation in the EU: Bibliometric Analysis and Digital Economy Trends Highlights

Abstract

This study highlights the Digital Transformation issues in recent scientific topics, as well as the trends in the European Union’s Digital Economy dynamics. The aim is to identify key and promising research topics in the digital field and define priorities for adopting digital innovations in the EU in terms of bibliographical and statistical aspects. The study includes a bibliographic analysis using publication metrics statistics, word cloud diagrams, and network clustering. There is also a quantitative analysis of the leading Digital Economy trends in the EU using correlation and cluster analyses and visualizations of the selected economic and Digital Transformation metrics. The results identify critical keywords in digitalization publications related to other key research and multidisciplinary areas. A grouping is proposed of research paper topics and research issues related to Digital Transformation in the EU and worldwide based on the identified trends in recent research proposals. The study examines the correlation of some digital indices and trends in EU countries’ GDP dynamics, R&D investment, and digital inclusion. From the clustering based on the data of a single digital market that promotes e-commerce for individuals and businesses, groups of EU countries have been identified as having the potential to increase digital inclusion and convergence growth rate. The results provide a basis for future research on Digital Transformation and determine the need for further intensification of EU digitalization.

1. Introduction

Digital transformation in the economies of countries worldwide and the European Union (EU) represents a significant shift in all areas of activity. It changes how businesses operate, how people interact, how governments provide services, how scientific studies are conducted, etc. Since 2014, the European Commission has been rigorously monitoring and reporting on the progress of its Member States in this digital journey through the Digital Economy and Society Index [1,2]. These reports show valuable results in identifying areas for priority action and offer a comprehensive EU-level analysis of critical digital policy areas.

The COVID-19 pandemic has accelerated the Digital Transformation processes across the EU, especially in cases where anti-pandemic measures forced people and SMEs to adopt digital solutions [3]. During this time, individuals, entrepreneurs, and businesses demonstrated a significant increase in the use of digital technologies, signaling a trend toward deeper digitalization. These changes occurred at different levels across various EU countries and economic sectors. For example, the increase in remote working was primarily observed in high-paid white-collar jobs, reflecting the nature of jobs that allow for remote organization. The pandemic also increased online communication with clients and saw a surge in the entry of ICT specialists into the European market.

Central to this Digital Transformation is the development and enhancement of digital skills. In today’s environment, digital skills are indispensable. They function not only as professional requirements but also as fundamental competencies for effective navigation in the digital sphere [4,5]. As the dependence on the internet and digital technologies grows, so does the demand for advanced digital skills and competencies in the workforce. Unique industries and wide-ranging spheres are increasing digital inclusion. In recognizing this need, the European Union has prioritized the digital transition to equip at least 80% of its population with the necessary digital skills and significantly increase the number of ICT specialists by 2030. This goal is a part of the broader “Path to the Digital Decade” proposal, which sets specific targets to guide and stimulate actions by both the EU and its Member States towards a digitally adept society (Digital Economy and Society Index, DESI [1,2]).

Despite the European Union’s concerted efforts to promote Digital Transformation, the full impact of these initiatives across its Member States still needs to be studied. Digital Economy trends provide a framework for assessing progress, but significant disparities in digital advancement reveal complex and uneven integration within the economy of the EU [6]. The level of Digital Transformation in the EU, as measured by the DESI and related indicators, influences the digital instruments of economic growth of the Member States and is widely represented in the European Commission policies and other analytical literature [1,2,7]. However, the issues of Digital Transformation in academic publications are broad. The main trends, future research proposals, and the existing thematic areas in the EU and the world should be explored.

Thus, the primary hypothesis of this study is that Digital Transformation, which is part of scientific investigations and measured by various indices, has specific subtopic points and is associated with countries (regions) and scientific objectives of specialization. Therefore, this study aims to identify key and promising research topics in the digital field and define priorities for adopting digital innovations in the EU in terms of bibliographical and statistical aspects. The authors seek to indicate the link between digitalization and performance across EU member countries, identify patterns and variations in Digital Intensity, and highlight the Digital Economy trends in the EU. The study’s objectives include scientific publication metadata analysis of word cloud and network clustering methods, discovering the top paper titles, and analyzing recent research findings on Digital Economy transformation; for this, we used correlation analysis to identify tendencies in adopting digital innovations and clustering EU countries based on their levels of Digital Intensity. A bibliometric analysis will also uncover critical trends, gaps, and differences in academic research on Digital Transformation.

The central issue of this study is how Digital Transformation is considered in scientific publications, especially in the post-COVID-19 crisis period. The basic stages are depicted in Figure 1.

Firstly, metadata and publications in the international scientific metric from Scopus and Web of Science databases are collected and statistically processed to study such trends. Next, particular economic indicators of EU countries, such as digital single market promoting and Digital Intensity, were statistically investigated. While previous studies provide an idea of the impact of digitalization, e.g., using the DESI on individual aspects of economic development, there is a need for additional and new theoretical and statistical analysis that identifies key topical trends and the potential for the implementation of digital innovations in EU countries. By achieving these objectives, this study will contribute valuable results concerning the role of Digital Transformation in economic development processes and provide strategic guidance for decision-making aspects to strengthen the Digital Economy of the EU.

2. Materials and Methods

This study used bibliometric analysis, keyword clustering, and statistical correlation to define Digital Transformation scientific research trends and economic growth indicators across the European Union (EU) and worldwide scientific research. The data were collected from publicly available sources, such as Eurostat, and scientific databases, such as Scopus and Web of Science. The analysis focused on digital integration, digital skills, and economic performance metrics, particularly GDP growth.

A bibliometric review of scientific publications from 2020 to 2024 was conducted, followed by keyword network clustering based on the Louvain method [8], which was used to identify core research areas in innovation, digitalization, and business transformation. The choice of the study period is due to the sharp increase in the number of publications related to Digital Transformation in this period (COVID-19 and post-COVID-19 period). Correlation analysis assessed the connection between digital indices and economic metrics, including digital market adoption and GDP growth across EU-27 countries. A hierarchical clustering method was then used to group countries based on their digital single market promotion levels and Digital Intensity to identify country patterns with different potentials for accelerated growth in Digital Intensity and digital technology adoption. The study also examined the trends of R&D investment on economic growth, focusing on sectors such as business, higher education, and non-profit organizations. All data used in the study are open source and publicly accessible, so no ethical approval was required.

To implement the tasks of statistical analysis, keyword network and clustering, and correlation analysis, the capabilities of the programming language Python were used, as well as Data Science tools [9] (e.g., the numpy, pandas, wordcloud, scipy, matplotlib, sklearn, and networkx libraries).

3. Results

3.1. Bibliometric Analysis

“Digital Economy” and “Digital Transformation” are top topics for current scientific investigations. For further bibliometric analysis, data were sourced from the international scientometric databases Scopus and Web of Science. The search and filtering employed the databases’ standard systems, with criteria including keywords or topics related to “Digital Transformation” and “Digital Economy”. The metadata was collected specifically for the last 5 years, capturing the significant increase in publications related to these themes over that period. This approach to the results can show academic interest and the volume of research in Digital Transformation and Digital Economy.

Table 1. Number of publications on Digital Economy topics in Scopus and WoS for 2020–2024 ¹.

Topic and/or Title	Scientific Base Name	Year of Publication	Number of Publications
Digital Transformation	WoS core Collection	2024 (8 month)	4155
Digital Transformation	WoS core Collection	2023	5414
Digital Transformation	WoS core Collection	2022	4943
Digital Transformation	WoS core Collection	2021	4026
Digital Transformation	WoS core Collection	2020	3013
Digital Transformation	Scopus	2024 (8 month)	2131
Digital Transformation	Scopus	2023	2659
Digital Transformation	Scopus	2022	1921
Digital Transformation	Scopus	2021	1434
Digital Transformation	Scopus	2020	979
Digital Economy	WoS core Collection	2024 (8 month)	2428
Digital Economy	WoS core Collection	2023	3278
Digital Economy	WoS core Collection	2022	3012
Digital Economy	WoS core Collection	2021	2354
Digital Economy	WoS core Collection	2020	2096

¹ Source: own study based on data received from https://www.webofscience.com and https://www.scopus.com/; data were retrieved on 1 September 2024.

demonstrates the number of scientific papers on search queries in the relevant international scientific databases.

The data in Table 1 reveal a trend of increasing publication numbers on “Digital Economy” and “Digital Transformation” topics, with a particularly notable rise in articles twice compared with the year 2020 for the Scopus scientific database. This uptrend suggests a growing academic interest and emphasis on these subjects. It is also apparent that the number of publications in Scopus is consistently relevant to the WoS Core Collection for the topics each year. The peak of publications for Digital Economy in the WoS Core Collection occurred in 2022 and 2023 (2024 has yet to end). Additionally, publications on Digital Transformation have been increasing each year, and this topic is gaining more focus within the academic community.

These trends reflect the digital shift after the COVID-19 pandemic and the strategic focus of the EU on digital skills and transformation as part of the “Path to the Digital Decade” initiative [10]. Thus, the increased number of publications may indicate significant research activity and interest, which could contribute to a deeper understanding of the Digital Economy’s role in economic growth and the successful implementation of Digital Transformation strategies.

To further refine the themes related to Digital Transformation, we utilized the “author keywords” and “index keywords” features from the Scopus database for 2023, as shown in Table 1. “Author keywords” are keywords formulated by the authors of the articles, while “index keywords” are generated by the Scopus database itself within the correct terms and definitions.

Unfortunately, the authors’ keywords have significant variability due to the inconsistency in terminology, which limits the scope of analytical operations that can be performed, such as a word cloud. The results of this word cloud analysis are presented in Figure 2. The data have been pre-cleaned to remove empty keywords (keywords such as digitalization and Digital Transformation) and reduce the regional aspect. The large size of the terms indicates they are frequently mentioned. As we can see, the top topics include “Sustainability”, “Innovation”, “Digital Economy”, “Artificial Intelligence”, “SMEs”, and “Industry 4.0”. Additional significant keywords such as “Digital Technologies”, “COVID-19”, and “Education” reflect the broad impact and interdisciplinary nature of Digital Transformation across different sectors and issues, which the authors define.

The proposed analysis of “author keywords” only sometimes reflects the methodologically correct main ideas of the research. Therefore, we consider a complex approach based on analyzing the “index keywords” formed by the database system.

Figure 3 depicts the network clustering according to “index keywords” for all scientific articles published in 2023 and indexed by the Scopus database with the topic or keyword “Digital Transformation” (the data filtered by publication type is “article”, and the regional aspect and general scientific keywords are excluded).

The “Network Clustering” methodology involves the Louvain clustering method [8] and widely known data-processing algorithms based on Python programming language tools [9]. In Figure 3, the size of each node means more central nodes are larger and indicate higher importance to the network. The color of each node represents different clusters, grouping keywords that are more closely connected into the same color category. The width of the edges is proportional to the weight of the co-occurrences between keywords.

Figure 3 illustrates the main clusters of keywords as follows. Keyword Cluster 1 is represented by a collection of nodes at the bottom of the figure, encompassing the most nodes. This cluster includes prominent keywords such as “human”, “patient safety”, “artificial intelligence”, “digital technology”, and “health”, and can be nominally termed “Human-Related Topics of Digital Technologies”. Keyword Cluster 2, centralized in the middle of the figure, features key terms such as “development”, “carbon”, “economic aspect”, “commerce”, and “digital economy”, which collectively may be named “the Digital Economy Development”. Keyword Cluster 3, visible at the top right of the figure, incorporates keywords such as “innovation”, “sustainable development”, “green economy”, “investment”, “business”, and “enterprise”, covering a range of indexed themes associated with business operations at meso- and macro-levels, and was named the “Digital Transformation of Business” cluster. Keyword Clusters 4 and 5, though less distinct, are positioned at the bottom right and far left of the central clusters, respectively. Keyword Cluster 4, referred to as the “Core Digital Technologies” cluster, might include terms such as “Industry 4.0”, “big data”, and “e-learning”. Keyword Cluster 5, the “Digitalization in Education and Digital Skills” cluster, focuses on digital education and skills development.

The word cloud and keyword cluster results (Figure 1 and Figure 2) help detect relevant papers. The criteria for selecting a paper are based on the following features: compliance with the group topic, the latest publications on the study date, the highest citation ratings according to scientometric databases ranking, and contextual analysis. Thus, scientific publications’ main issues and goals can be grouped into several subtopics.

The first group of papers, which discussed most human-related and fundamental digital technology challenges, discussed the internet, artificial intelligence, big data, health applications, and the human impacts of Digital Transformation (Keyword Cluster 1) issues. In addition, this group of publications also addresses key themes such as digital innovation, digitalization, digital skills, Industry 4.0 (part of Keyword Cluster 4), and skills improvement and e-education (part of Keyword Cluster 5).

For instance, Calzati and Van Loenen (2023) [10] investigated the digital strategy of the EU, advocating for citizen-centric governance models that balance economic goals with social inclusion, digital sovereignty, and environmental sustainability. Martins et al. (2022) [11] explored the digitalization of EU security practices, highlighting tools such as biometric databases that raise questions about sovereignty, interoperability, and privacy concerns. Sun et al. (2020) [12] proposed a framework for enhancing interoperability and privacy in Industry 4.0 systems using distributed ledger technology, addressing GDPR-related challenges. That is, these and similar works focus on human problems in the context of Digital Transformation and data protection, such as GDPR-related issues.

In the educational domain, Kuzheliev et al. (2023) [4] explored the role of Digital Transformation in enhancing distance learning, emphasizing its positive effects on accessibility and efficiency of education. Svarc et al. (2020) [13] investigated the impact of national intellectual capital on Digital Transformation, demonstrating how social and human capital contributes to closing the digital divide among EU nations. Štaffenová and Kucharčíková (2023) [5] focused on human capital management, particularly the readiness of organizations to adopt digital technologies while ensuring compliance with data protection frameworks such as GDPR. Szeles and Simionescu (2020) [14] also highlighted the critical role of educational attainments and patent activity in fostering regional digital economies.

Mavlutova et al. (2023) [15] and Shkurat et al. (2022) [16] examined how Digital Transformation fosters sustainable development and Post-Pandemic Recovery in the context of the financial sector. The authors emphasized operational efficiency and financial inclusion through innovative technologies such as digital payments. Nosratabadi et al. (2023) [17] analyzed the social sustainability of Digital Transformation across the EU, revealing its alignment with sustainable development goals and identifying disparities in digital readiness among Member States.

Troitiño et al. (2023) [18] composed a complex book on Digital Transformation with EU aspects. It extends this discussion by providing a comprehensive interdisciplinary perspective on the digital development of the EU. The book explores political science insights, international relations, economics, and law in addressing the digital transition of the EU. It emphasizes the responsibility of the EU to foster prosperity while safeguarding European values, digital sovereignty, cybersecurity, and ethical governance in the digital revolution.

Thus, the first group of works mainly relates to Cluster 1 (Figure 2) to a greater extent since the studies emphasize the critical need for social and technical research. However, the works use digital innovations (Keyword Cluster 4) and institutes to maintain digital competencies (Keyword Cluster 5). However, in this group of works, the following subtopics are clearly distinguished: social and legal features in introducing and using digital technologies, as well as achieving sustainable development goals; technical, legal, and ethical challenges; and the development of digital skills.

The second group of problems focuses on the core economic trends, Digital Economy dynamics, and growth challenges associated with Digital Transformation at the regional and national levels (mainly associated with Keyword Cluster 2). This group primarily integrates studies that analyze the macroeconomic implications, digital readiness, and structural transformation within the EU and beyond.

Kovács et al. (2022) [19] examined convergence trends in the EU Digital Economy using the DESI for EU countries. They identified a “Matthew effect” (the rich get richer) among Member States, with richer countries benefiting disproportionately from digital investments. Olczyk and Kuc-Czarnecka (2022) [20] also used statistical analysis on DESI data, but the authors improved the methodology of the DESI to assess its impact on GDP growth. They demonstrated how enhanced connectivity and targeted digital initiatives contribute to bridging economic disparities within the EU. Similarly, Hunady et al. (2022) [21] provided statistical-based insights into the Digital Economy’s indices, clustering EU countries by similarity/dissimilarity in the overall digital readiness of enterprises. The authors showed that Nordic countries outperform Southern and Eastern Europe in e-commerce, cloud computing, and digital innovation areas. Kisel’áková et al. (2022) [22] examined EU countries’ Digital Economy levels using the DESI and Digital Competitiveness Ranking and underscored the importance of human capital, digital skills, and technology integration as driving forces of Digital Transformation. Tarjáni et al. (2023) [23] analyzed the International Digital Economy and Society Index (I-DESI) and underscored the importance of multivariate approaches in assessing and planning Digital Transformation initiatives. Zeverte-Rivza et al. (2023) [3] expanded on the statistical analysis of the EU by focusing on digitalization in the bioeconomy of the Baltic states and Poland. Finally, Ogrean and Herciu (2020) [24] complemented DESI statistical insights with Romania’s Centru Region data analysis. Their study aligned regional priorities with the digital strategy and targeted policies of the EU to address infrastructure, innovation, and governance gaps. Burger-Helmchen and Meghisan-Toma (2018) [25] also provided an overview of the Digital Single Market Strategy of the EU and emphasized the role of digital technologies in economic growth, connectivity, and policy innovation. Thus, much work has been devoted to the quantitative analysis of the DESI, especially for EU countries and regions. The issues of digital trends and digital disparities have been key in recent years.

Criveanu (2023) [26] highlighted the role of Digital Intensity and e-commerce as key drivers of sustainable economic growth in EU countries. The study demonstrates that Digital Transformation fosters organizational resilience and aligns with sustainable development goals. Sánchez-Bayón (2023) [27] evaluated the macroeconomic implications of Digital Transformation in the EU tourism industry and underscored the paradox of the growing importance yet insufficient adaptation of digital and economic transformations.

Many studies (Keyword Cluster 2, Figure 2) have also concentrated on circular economy issues and natural management (manufacturing production, carbon dioxide emission resource allocation, climate change, etc.) within Digital Transformation aspects. Su et al. (2023) [28] provided a statistical analysis of the impact of Digital Transformation on the productivity of heavily polluting enterprises in China. Huang et al. (2023) [29] examined the Digital Transformation of the transportation industry across 43 global economies, demonstrating its significant impact on reducing carbon intensity by using technological innovation, industrial upgrading, and energy optimization. Hu [30] focused on the synergistic effects of pollution reduction and carbon emission mitigation enabled by digital economic policies in Chinese prefecture-level cities. Most of the research data are presented for Asian countries; however, the findings can form the basis for further developing digital technologies in EU countries in those aspects.

Thus, the second group of works mainly relates to Keyword Cluster 2 and focuses on assessing the development trends of the Digital Economy by analyzing the DESI and its components and examining the relationship between digital innovation and industrial development. These are the key problems of further research regarding the general functioning of the Digital Economy in the context of Digital Transformation in the EU.

The third group focuses on digital innovations for businesses and SMEs and related subtopics, such as the green economy and innovative technology adaptation (those papers are mainly related to Keyword Cluster 3). Ancillo and Gavrila (2022) [31] widely investigated the evolving role of research and development (R&D) in fostering entrepreneurship, innovation, digitization, and Digital Transformation, particularly in response to the disruptive impact of COVID-19. Almeida et al. (2022) [32] provided a wide-range bibliometric analysis of European Horizon 2020 projects addressing Digital Transformation in SMEs. They reveal collaborative R&D innovation driver aspects, showing the value of EU programs in fostering scientific excellence and practical technological adoption. Chatzistamoulou (2023) [33] explored how Digital Transformation fosters sustainability transitions in European SMEs, aligning with the twin objectives of digitalization and the European Green Deal. The author identifies factors that promote sustainable business strategies (participation in public procurement and robust institutional frameworks). Holl and Rama (2023) [34] analyzed the spatial patterns and drivers of SME digitalization in Europe, highlighting disparities between urban and rural areas, and they stated that rural SMEs often lagged in DT despite potential gains from innovation, related public support, and promoting policies. Rupeika-Apoga et al. (2022) [35] investigated the public support mechanisms for SMEs to undergo Digital Transformation effectively and defined financial support and public support problems. Roman and Rusu (2022) [36] focused on the level of SME digitalization in EU countries, identifying barriers such as infrastructural gaps and limited technological expertise; they investigated the impact of digital technologies on SME performance. Ogrean and Herciu (2021) [37] highlighted key challenges for Romanian SMEs, such as limited digital infrastructure and technological expertise, which hinder their progress toward achieving digitalization and sustainability goals. Roblek et al. (2021) [38] examined the role of Digital Transformation as a disruptive innovation for manufacturing SMEs. The authors’ study highlights how Digital Transformation influences product and process innovation and organizational culture and how the emergence of smart factories creates opportunities for sustainable growth.

The third group of studies focuses on Digital Transformation problems for business issues, e.g., SMEs. They identify government and financial support priorities and the need for organizational transformation. Most of the studies point to the critical need for tailored policies, robust institutional frameworks, and innovative methods to maximize the benefits of Digital Transformation while addressing the unique business challenges.

Thus, the keyword and bibliometric analysis provide a foundational understanding of the current research problems in Digital Transformation topics. They highlight the interconnectedness of critical issues such as human-related Digital Transformation, digital innovation, sustainability, Digital Economy, and SMEs while showing how less-connected themes such as green technology and teaching play a role. This bibliometric overview underscores the growing academic focus on Digital Transformation and its various facets, particularly considering the post-pandemic shift toward digitalization.

3.2. Statistically Measuring the Digital Transformation Highlights in the EU

Based on the bibliometric analysis of critical Digital Transformation topics, let us provide a statistical evaluation, explicitly measuring the relationship between digital indices and GDP growth. Analyzing various digital factors, such as digital inclusion, e-commerce adoption, and e-government activities, aims to provide empirical evidence on how these elements contribute to economic expansion.

The Pearson correlation matrix for some digital indices and GDP growth (

Table 2. Correlation matrix of the digital indices and GDP growth for the EU-27 countries ¹.

	z1	z2	d1	d2	d3	d4
z1	1.0000
z2	0.8265	1.0000
d1	0.9043	0.8955	1.0000
d2	0.8538	0.9174	0.9200	1.0000
d3	0.8639	0.8928	0.9911	0.9095	1.0000
d4	0.8046	0.8745	0.9668	0.8783	0.9794	1.0000

¹ Source: authors’ estimation based on Eurostat data [39].

) reveals a significant positive relationship between the digital inclusion of individuals and GDP growth, with a correlation coefficient of 0.9043 and 0.8955 for actual and lagged GDP growth metrics. This correlation suggests that as digital inclusion increases, there is a corresponding rise in GDP, indicating that digital skills and internet access drive economic growth. The data also shows a strong positive correlation between promoting e-commerce for businesses and individuals and GDP growth, with coefficients of 0.8538–0.9174 and 0.8639–0.8928, respectively. Moreover, one-year lagged values of GDP growth show a higher linear correlation between these indicators. This coefficient highlights the importance of a digital single market and e-commerce in economic expansion. e-government activities show a somewhat lower yet positive correlation with GDP growth at 0.8046–0.8745, suggesting that while adopting e-government services impacts, it might not be as significant as other digital factors.

The variables for Table 2 are as follows:

z1—Real GDP (Gross Domestic Product) of a particular year relative to the 2010 base;

z2—One-year lagged real GDP of a specific year relative to the 2010 base;

d1—Digital inclusion: individuals and percentage of individuals;

d2—Digital single market: promoting e-commerce for business by size class of enterprise and the percentage of enterprises;

d3—Digital single market: promoting e-commerce for individuals and the percentage of individuals;

d4—e-government activities of individuals via websites and the percentage of individuals.

Overall, the Pearson correlation matrix (Table 2) highlights the inter-related nature of Digital Transformation and economic performance, affirming the investment directions in digital infrastructure, skills, and services to foster economic growth in the EU.

In continuing the analysis of empirical data on the development of the Digital Economy of the EU countries, we analyzed the sources of innovation financing. The dynamics of the GDP and Gross Domestic Expenditure on R&D (GERD) for the EU (27 countries) [11] highlight the same trends in these variables. The Eurostat data are confirmed by the similar trends in GDP changes and Gross Domestic Expenditure on R&D. This suggests that as R&D spending increases, GDP also tends to increase. Moreover, the business enterprise and higher education sectors share the most significant innovation expenditures in terms of proportions. However, the private non-profit sector has shown more substantial changes in recent years (especially doubling in 2022), which indicates the increased role of public organizations and the importance of sustainability indicators (different from business and government). The main conclusion is that the same trends are present in research and development (R&D) initiatives in all sectors. The private sector forms the central spending of the innovations and paints a trend of harmonized growth and substantial impact on GDP. The business enterprise sector has a vast share of all Gross Domestic Expenditure on R&D. The second seat is for GERD from the higher education sector resources. Higher education and scientific institutes are not just repositories of knowledge but also vital grounds for research and development, for instance, through the scientific entrepreneurship mechanism. These institutions remain appropriate in stimulating innovative growth, acting as incubators for raising ideas and boosting their application, significantly influencing the economy, e.g., GDP. Thus, the same trends exist to foster a future of growth and sustainability. The businesses and other entities leverage each sector’s strengths as competitors for innovation adaptation.

In continuing the analysis of Digital Transformation quantitative shifts by EU regions, Figure 4 demonstrates the structures of the enterprises with very low, low, high, and very high Digital Intensity indexes.

The data in Figure 4 represent the Digital Intensity index across enterprises within selective European countries in 2022. The index classifies enterprises based on their digital integration levels, ranging from very low to very high. A key observation is the prevalence of enterprises with low-to-moderate Digital Intensity, suggesting a substantial scope for growth in digital adoption. These data prove, again, that countries such as Montenegro, Romania, and Bulgaria show a low rate of enterprises with very high Digital Intensity indexes. Still, they indicate the potential for rapid digital advancement. These data underscore the importance of targeted digital upscaling strategies to enhance the digital capabilities of businesses, which can lead to more incredible innovation and competitiveness in the European market.

In continuing with quantitative assessments of digital inclusion in EU countries, let us investigate the “Digital single market—promoting e-commerce for business” and “Digital single market—promoting e-commerce for individuals” in EU-27 countries for the post-COVID-19 period. Figure 5 and

Table 3. Cluster centroids for selected variables ¹.

Cluster	x1_mean	x1_mean_3	x1_mean_ch	x1_mean_ch_3	x2_mean	x2_mean_3	x2_mean_ch	x2_mean_ch_3
1	28.69	31.88	3.47%	0.23%	69.07	81.28	5.02%	4.56%
2	15.96	17.73	4.41%	3.17%	64.59	73.32	5.12%	3.34%
3	8.63	11.77	7.99%	9.10%	22.56	37.77	18.62%	25.64%
4	21.79	28.59	9.34%	11.76%	47.13	61.22	8.23%	6.57%
5	12.51	16.16	10.03%	14.45%	39.72	54.51	9.68%	11.41%

¹ Source: authors’ estimation based on Eurostat data [39].

show the results of the hierarchical cluster analysis for timescale datasets from 2020 to 2022 based on the index’s average, increase, and growth rate.

The variables for Table 3 are as follows:

x1_mean and x1_mean_3—Average value of the “Digital Single Market—Promoting e-commerce for businesses by size class of enterprises” from 2013 to 2022 and 2020 to 2022, respectively;

x1_mean_ch and x1_mean_ch_3—Average growth rate of value for the “Digital Single Market—Promoting e-commerce for businesses by size class of enterprises” from 2013 to 2022 and 2020 to 2022, respectively;

x2_mean and x2_mean_3—Average value of the “Digital Single Market—Promoting e-commerce for individuals” from 2013 to 2022 and 2020 to 2022, respectively;

x2_mean_ch and x2_mean_ch_3—Average growth rate of value of the “Digital Single Market—Promoting e-commerce for individuals” from 2013 to 2022 and 2020 to 2022, respectively.

Five clusters were identified in the hierarchical cluster analysis concerning the Digital Single Market from 2020 to 2022.

Cluster 1 includes countries demonstrating stable maximum levels yet low growth rates in digital commerce for both businesses and individuals. The average growth rate in this cluster suggests a consistent but gradual adaptation to digital market demands. One can consider the saturation effect for these countries.

Cluster 2 includes countries with intermediate growth rates, reflecting a more dynamic response to the digital single market yet still facing challenges in maximizing the potential of digital commerce. These countries can be considered the most difficult in terms of leveling the extent of digitalization in the EU and the convergence of the digital single market.

Cluster 3 features countries that initially lagged in promoting e-commerce but have shown rapid growth rates, surpassing other clusters in recent years. Over the past 3 years, these countries have demonstrated the highest growth rate in terms of the digital single market, promoting e-commerce for individuals, which was almost nine times higher than the level for Cluster 2.

Cluster 4 represents countries with high growth rates and substantial engagement in the digital single market, indicating the effective integration of digital strategies at both the individual and business levels.

Cluster 5 comprises countries with the highest growth rates, suggesting aggressive digital adoption and significant advancements in promoting e-commerce, especially for businesses. These countries may also serve as benchmarks for successful digital market strategies.

Thus, each cluster provides insights into different trajectories of digital market development across the EU, reflecting how various strategies and regional characteristics impact digital commerce growth. However, Clusters 3–5 are characterized by significant potential for implementing Digital Transformation innovations, particularly those related to the digital single market. The transition from data to actionable insights becomes crucial as economies aim to leverage the momentum of digital progress observed during recent years.

3.3. Highlights of Digital Transformation Concepts

Based on the bibliometric and statistical analyses, the synergy between variance economic trends and academic research results is a cornerstone for achieving robust digital economies, especially within businesses (incl. SMEs) applying digital innovations. As a summary result, it illustrates the interconnection of various central elements in the modern digital landscape. The central “Industry 4.0” paradigm introduces new business models and tools essential for navigating the digital and big data domains. The concepts of the multifaceted relationship between business activities and the operational domains of business entities highlight the pivotal role of universities, research institutions, and the non-profit sector in the Digital Transformation process. The contemporary Digital Transformation concepts outline how technological pillars such as artificial intelligence, big data, and cloud computing feed into advanced analytical models and tools that inform and transform business processes. Specialized digital skills such as data analysis models and web-based visualization tools are imperative for effectively operating these advanced resources within this framework. The related investigations delineate the pivotal role of applying many processes, including supply chain, business processes, resource management, green technology, and sustainability. Given the complexity of these components, the expertise required transcends the capabilities typically found within business entities’ staff.

Consequently, the demand for highly skilled employees and scientific entrepreneurship is projected to intensify, particularly within the managerial aspects of the digital innovation adoption lifecycle. Therefore, the interdependencies between digital skills and various resource management sectors suggest a collaborative ecosystem where commercial researchers and academic bodies drive the integration of digital technology into core business practices. This integration aims to enhance efficiency and innovation within logistics, resource management, sales, and marketing, fostering a systematic approach to digital adoption in the economy and for some business entities.

4. Discussion

The synthesis of the research results highlights the dynamic evolution of digitalization, which requires further study of its relationship with GDP, overall and regional economic growth, and additional opportunities to implement digital innovations.

Differences in the maturity levels of the Digital Economy in the EU show that while some Member States have focused on their digital potential, others have significant untapped opportunities. These differences point to the need for tailored strategies that ensure a more inclusive adoption of digital innovations, especially for enterprises lagging in digital integration. Thus, studying the causes of uneven digital development within the EU can be considered a key aspect of further research.

The empirical findings from hierarchical cluster analyses and structural assessments of the adoption of digital innovations emphasize the critical role of statistical research in Digital Economy issues. Therefore, the analysis and in-depth study of Digital Transformation trends in the EU countries based on the DESI and its components and improving the methodology for calculating this indicator remain relevant. Leveraging research and management expertise is essential to ensure equitable and sustainable digital growth in the EU and elsewhere. Tailored digital strategies should be developed to strengthen the foundations of the Digital Economy, including specifics for a particular region. This could include assessing the readiness and capabilities of businesses and other actors, especially SMEs, to adopt digital innovation.

5. Conclusions

A bibliometric statistical analysis confirmed the assumption of a growing trend in scientific interest and publication volume on topics related to the “Digital Economy” and “Digital Transformation” over the past 5 years. This surge was evident during the COVID-19 period and continues today. This increase in research activity was observed in both the Scopus and Web of Science databases.

The analysis organized keywords from Digital Transformation research into five distinct keyword clusters, reflecting the core themes found in the scholarly articles of 2023. The first keyword cluster highlights human-related issues and foundational challenges in digital technology, such as artificial intelligence and health technologies. The second keyword cluster focuses on digital economic aspects, encompassing economic development and digital commerce. The third keyword cluster discusses digital innovation in business, with topics such as sustainable development and the green economy. The fourth keyword cluster deals with core digital technologies, exploring areas such as big data and Industry 4.0. The fifth keyword cluster revolves around digitalization in education, including improving digital skills and educational technologies. Each keyword cluster provides insights into various facets of Digital Transformation, illustrating the field’s extensive impact and interdisciplinary approach.

The bibliographic analysis of Digital Transformation problems and their specifics in the EU also helps to categorize the research papers into three main research topic groups. The first group examines the impact of human-related and fundamental digital technology challenges, e.g., the internet, artificial intelligence, big data, health applications, and the human implications of Digital Transformation. The second group explores the core economic trends, Digital Economy dynamics, and growth challenges associated with Digital Transformation at regional and national levels. The third group addresses the challenges of digital innovations for businesses and SMEs and related subtopics, such as the green economy and innovative technology adaptation.

The varied levels of Digital Economy advancement across EU countries suggest differential growth trends and a call for support, particularly for businesses and SMEs. The relationship between R&D expenditure and GDP growth across various sectors underscores the critical role of innovation in economic development. The findings advocate leveraging the distinct strengths of each institutional sector to foster a future of sustainable growth, focusing on the significant contributions of the business enterprise sector and the high growth rate in non-profit financing.

The statistical analysis of the EU countries based on Digital Intensity and digital single market indices defines the countries with the highest potential for enhancing digital adoption; for example, Romania and Bulgaria have a significant opportunity to leverage their trends for Digital Economy advancement. Future investigations and practical acts should harness this potential, particularly enhancing digital skills and infrastructure, to maximize the country’s Digital Economy prospects.

Therefore, integrating digital technology in the economy and business practices, in particular, emerges as a critical driver for efficiency, defining scientific research trends, and supporting digital innovation adoption strategies within the EU economic framework.