Convergence and the Matthew Effect in the European Union Based on the DESI Index

Kovács, Tünde Zita; Bittner, Beáta; Huzsvai, László; Nábrádi, András

doi:10.3390/math10040613

Cited by 16 publications

(13 citation statements)

References 58 publications

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“…EU countries have been ranked according to the factor scores. As has been previously mentioned, this study confirmed some of the previous findings of other authors, e.g., Kinnunen et al [13], Borowiecki et al [14], Orviska and Hunady [49], Cheba et al [50], Kovács et al [54], etc. This study brings some new empirical insight into the digital economy problem and businesses' readiness for digital transformation in the EU.…”

Section: Discussionsupporting

confidence: 93%

“…However, they decided to use only four main clusters instead of three and seven sub-clusters in this paper [14]. In addition, Kovács et al [54] also used DESI in their analysis and revealed Denmark, Netherlands, Finland, and Sweden to have the highest internet services digital readiness. Nevertheless, the approach used in this paper is also unique due to the selection of variables.…”

Section: Discussionmentioning

confidence: 99%

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Digital Transformation in European Union: North is leading, and South is lagging behind

Hunady¹,

Pisár²,

Glavan³

et al. 2022

IJISPM

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The transformation of the economy into a digital environment has become a necessary step in recent years. The consequences of the COVID pandemic have accelerated the digital transformation and the growth of the digital economy. Intensive business engagement in the digital economy requires innovative digital solutions and online means of promotion and sale. European Union (EU) countries need to create the conditions for the gradual transformation. The paper analyses business readiness for the digital economy in EU countries. It aims to compare and assess the current situation of digital readiness based on the set of selected indicators. The analysis includes a multidimensional comparison of EU countries, classification based on cluster analysis, and ranking based on factor analysis results. Results show significant differences among EU countries. Newer member countries, mostly from South-Eastern Europe, are still lagging behind the EU average in e-Commerce activities, usage of social networks, and cloud computing. Furthermore, factor analysis has been conducted to determine underlining factors describing the overall digital readiness of EU countries and rank them accordingly. As well as in the cluster analysis, factor analysis revealed that Nordic EU member countries perform very well and show the highest digital readiness.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Digital Transformation in European Union: North is leading, and South is lagging behind

Hunady¹,

Pisár²,

Glavan³

et al. 2022

IJISPM

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“…The study by Marcysiak and Pleskacz (2021) analysed the degree of digitisation (DESI) in the Polish economy in comparison with the EU average, with particular emphasis on SMEs. Kovács et al (2022) used correlation analysis and principal component analysis to analyse the digital economy and society index. Leogrande et al (2022a) analysed the determinants of the "Broadband Price Index" in 28 European countries between 2014 and 2021 and used data of DESI.…”

Section: Desimentioning

confidence: 99%

“…Our results cannot be compared with existing research because, as stated in Literature Review (see Section 1), we are not aware that there exists research that has focused on cluster analysis. The research focuses mainly on comparing only a few countries (e.g., Moroz, 2017;Stoica & Bogoslov, 2017;Burlacioiu et al, 2018;Kontolaimou & Skintzi, 2018;Grinberga-Zalite & Hernik, 2019;Karnitis et al, 2019;Nagy, 2019), or other methods were used (e.g., Gerasenko & Levkovich, 2019;Kovács et al, 2022;Kutnjak et al, 2020;Leogrande et al, 2022a). Therefore, this paper filled research.…”

Section: Cluster Analysismentioning

confidence: 99%

Multidimensional Evaluation of EU and Slovakia in the Context of Digital Transformation

Jenčová¹,

Vašaničová²,

Miškufová³

2023

CEBR

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The Covid-19 pandemic highlighted the cardinal intent, in which digital technologies play a key role in building a sustainable future, revealing disparities between digitally equipped companies and those that are still implementing digital solutions. It showed the difference between urban, rural and remote areas with good connections. This paper is divided into two parts. The first aim is to evaluate the performance of the digital economy and society according to its basic dimensions, quantify and compare the position of 28 European Union countries (considering Great Britain as a member) in the international area using DESI -(Digital Economy and Society Index). It will look to evaluate the overall change in the development of the Slovak Republic between individual periods based on the main dimensions of the composite index. The second part aims to find the clusters of the European Union countries by using data of their rankings within five dimensions of DESI. Correlation analysis is used to meet the first aim, cluster analysis is used to meet the second aim. The data are obtained from the Ministry of Investment, Regional Development and Informatization of the Slovak Republic and the database of the European Centre for Digitization. The results show a statistically significant correlation in the rankings of the EU countries between the analysed years 2016-2020. Moreover, among the European Union countries, there are internal homogeneous and external heterogeneous groups of countries with respect to ranking within DESI dimensions. Cluster analysis has not been used so far in analysing DESI in the existing literature. Therefore, the results of this paper fill such a research gap. Implications for Central European audience: Quantification and comparison of the position of 28 European Union countries in the international area using DESI can help to identify and improve the digital competitiveness of European Union countries. Knowing five dimensions of DESI, its specific subdimensions, and indicators can help to identify controversial areas to which the state should pay attention. This paper deals, in more detail, with the position of Slovakia in the digital competitiveness of the EU using DESI.

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“…An overview of research focused on digital transformation based on the systematization of literary sources was conducted by Kraus et al (2021). Kovács et al (2022) investigate the convergence of countries based on the DESI indicator. They use the beta convergence and the sigma convergence methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Digital transformation and ICT sector performance in EU countries

Ivanová

Grmanová

2023

Problems and Perspectives in Management

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Digital transformation is now one of the most important topics in all EU countries in creating and managing strategies and visions for states, businesses, organizations, and citizens. The ICT sector is currently one of the most important sectors with significant added value. The main purpose of the paper is to identify the efficiency of the digitalization of the economy and society concerning the performance of the ICT sector. This paper uses multi-criteria efficiency evaluation methods – Data Envelopment Analysis (DEA models). Inputs in the basic DEA model are the dimensions’ values of the Digital Economy and Society Index (DESI), which are also used to express the DESI summary indicator, such as human capital, connectivity, digital technology integration, and digital public services. Output in the DEA model indicates the ICT share of GDP. Finally, output-oriented DEA models are used to express the efficiency score. The analysis results show that Bulgaria, Romania, Greece, and Malta have a below-average level of DESI, but they can be classified as efficient. Italy, Lithuania, and Slovenia are the worst performers in the efficiency score. The next step was to express the efficiency scores in the DEA models in terms of different combinations of inputs and outputs. Malta was efficient in all fifteen DEA models. Based on these findings, Malta is considered significantly positive. Its approaches can serve as an example for other countries. AcknowledgmentThis paper was supported by the Slovak Ministry of Education’s Scientific Grant Agency VEGA: “Digital Economy and Changes in the Education System as a Reflection on Labor Market Requirements”. Project registration number: [Reg. No.: 1/0689/20].

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Convergence and the Matthew Effect in the European Union Based on the DESI Index

Cited by 16 publications

References 58 publications

Digital Transformation in European Union: North is leading, and South is lagging behind

Digital Transformation in European Union: North is leading, and South is lagging behind

Multidimensional Evaluation of EU and Slovakia in the Context of Digital Transformation

Digital transformation and ICT sector performance in EU countries

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