IDEAS home Printed from https://ideas.repec.org/a/vrs/bjeust/v13y2023i2p177-203n5.html
   My bibliography  Save this article

Evolution of the Digital Economy and Society Index in the European Union: Α Socioeconomic Perspective

Author

Listed:
  • Masoura Melpomeni

    (Department of Mechanical, Engineering and Aeronautics, University of Patras, Rio 26504, Greece)

  • Malefaki Sonia

    (Department of Mechanical, Engineering and Aeronautics, University of Patras, Rio 26504, Greece)

Abstract

The rapid development of information and communication technologies (ICT) in recent years has brought about significant changes in many social sectors such as communication, economy, entertainment, and others. To define the key role that ICT plays in its development course, the European Union (EU) has developed a composite indicator, the Digital Economy and Society Index (DESI), to assess the digital policy performance of its Member States. In the current work, an attempt is made to evaluate the performance of the EU countries on the digital economy and society with respect to implemented EU digital policies by studying the five dimensions of the DESI for the years 2014–2019, using the corresponding DESI reports (DESI 2015 – DESI 2020). Moreover, the digital convergence among EU Member States, in terms of similarity of their performance in the five dimensions of the DESI by grouping them according to the optimal number of clusters, is also examined. Since the optimal number of clusters is two, EU Member States are classified in two groups, one of high and one of low performance in the five dimensions of the DESI. The evolution of each member country and the possible transitions from one group to another during the years 2014–2019 is also a point of interest. The grouping of EU Member States into the two clusters showed that socioeconomic factors may affect the overall DESI. Linear mixed effect models confirm the positive effect of Gross Domestic Product per capita, the public expenditure for education and research and development (R&D) on the DESI and the negative effect of the average number of weekly working hours. The results could be used to reform the existing EU digital policies and identify areas where further improvement is needed.

Suggested Citation

  • Masoura Melpomeni & Malefaki Sonia, 2023. "Evolution of the Digital Economy and Society Index in the European Union: Α Socioeconomic Perspective," TalTech Journal of European Studies, Sciendo, vol. 13(2), pages 177-203, December.
  • Handle: RePEc:vrs:bjeust:v:13:y:2023:i:2:p:177-203:n:5
    DOI: 10.2478/bjes-2023-0020
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/bjes-2023-0020
    Download Restriction: no

    File URL: https://libkey.io/10.2478/bjes-2023-0020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Alonso, Ariel & Litière, Saskia & Laenen, Annouschka, 2010. "A Note on the Indeterminacy of the Random-Effects Distribution in Hierarchical Models," The American Statistician, American Statistical Association, vol. 64(4), pages 318-324.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leonardo Grilli & Carla Rampichini, 2015. "Specification of random effects in multilevel models: a review," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 967-976, May.
    2. Pei Wang & Erin L. Abner & Changrui Liu & David W. Fardo & Frederick A. Schmitt & Gregory A. Jicha & Linda J. Van Eldik & Richard J. Kryscio, 2023. "Estimating random effects in a finite Markov chain with absorbing states: Application to cognitive data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(3), pages 304-321, August.
    3. Reza Drikvandi & Geert Verbeke & Geert Molenberghs, 2017. "Diagnosing misspecification of the random-effects distribution in mixed models," Biometrics, The International Biometric Society, vol. 73(1), pages 63-71, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:bjeust:v:13:y:2023:i:2:p:177-203:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.