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Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States

Sayı: 49 26 Aralık 2022
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Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States

Öz

This study aims to determine the digital intensity levels, which are an indicator of the digital transformation performance of the countries. With this scope, the digital intensity efficiency levels of the European Union member countries were calculated by data envelopment analysis (DEA). The input-oriented Charnes Cooper and Rhodes (CCR-O) Model has been used to determine the digital intensity of the countries. The input criteria of the DEA model were obtained from the digital skills data in The Digital Economy and Society Index-2021 (DESI), and the output criteria were obtained from the digital intensity data of the same index. Digital content creation communication and collaboration, online information and communication, information and data literacy, problem-solving, and safety skills are input criteria for digital skills. Very low, low, high, and very high data were used as output criteria for digital intensity. According to the findings, Hungary, Spain, Slovakia, and Ireland are not at the full efficiency level. It is also stated in the study that input variables should be directed to reach the full efficiency level of the countries that are not at the full efficiency level. Accordingly, it was observed that Hungary, Spain, Ireland and Slovakia are not at the full productivity level. it can be said that these countries have digital skills but their digital intensity is not high. In this respect, it can be concluded that they do not make use of these skills sufficiently.

Anahtar Kelimeler

Digital Skills, Digital Intensity, EU Member States, DESI

Kaynakça

  1. Aniela, B., Marian, Z. & Badea, D. N. (2019). Economic growth and digital skills: An overview on the EU-28 country clusters. Annals of the Constantin Brâncuşi. University of Târgu Jiu, Economy Series, vol. 6, 78-85, December. https://ideas.repec.org/a/cbu/jrnlec/y2019v6p78-85.html
  2. Bánhidi Z., Dobos I. & Nemeslaki A. (2019). Comparative analysis of the development of the digital economy in Russia and EU measured with DEA and using dimensions of DESI. St Petersburg University Journal of Economic Studies, Vol. 35, iss. 4, 588–605. https://doi.org/10.21638/spbu05.2019.405
  3. Bashir, S. & Miyamoto, K. (2020). Digital skills: Frameworks and programs. World Bank1 April 2020 https://documents1.worldbank.org/curated/en/562351611824219616/pdf/Digital-Skills-Frameworks-and-Programs.pdf
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  5. Broadband Commission for Sustainable Development (2017). Working group on education: Digital skills for life and work, https://unesdoc.unesco.org/ark:/48223/pf0000259013
  6. European Centre for the Development of Vocational Training-CEDEFOP (2021). The European skills and jobs survey (ESJS). https://www.cedefop.europa.eu/en/publications/working-papers?search=&year=&country=&language=All&sort_order=DESC&items_per_page=24&page=1
  7. Chaaben, N. & Mansouri, F. (2017). Digital economic and social evolution of Tunisia. Proceedings of the Joint International Conference, Monastier di Treviso, Italy, 24–27 May 2017, University of Primorska Press.
  8. Charnes, A., Cooper, W. W.& Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
  9. Chetty, K., Aneja, U., Mishra, V., Gcora, N., & Josie, J. (2017). Bridging the digital divide: Skills for the new age. G20-Insights. https://www.g20-insights.org/wp-content/uploads/2017/05/Digital_Bridging-the-digital-divide-skills-for-the-new-ageII-.pdf
  10. Claro, M., Preiss, D. D., San Martín, E., Jara, I., Hinostroza, J. E., Valenzuela, S., Cortes, F., & Nussbaum, M. (2012). Assessment of 21st century ICT skills in Chile: Test design and results from high school level students. Computers & Education, 59(3), 1042-1053. doi:10.1016/j.compedu

Kaynak Göster

APA
Kaygısız, E. G. (2022). Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 49, 175-190. https://doi.org/10.52642/susbed.1153198
AMA
1.Kaygısız EG. Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States. SUSBED. 2022;(49):175-190. doi:10.52642/susbed.1153198
Chicago
Kaygısız, Esra G. 2022. “Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 49: 175-90. https://doi.org/10.52642/susbed.1153198.
EndNote
Kaygısız EG (01 Aralık 2022) Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 49 175–190.
IEEE
[1]E. G. Kaygısız, “Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States”, SUSBED, sy 49, ss. 175–190, Ara. 2022, doi: 10.52642/susbed.1153198.
ISNAD
Kaygısız, Esra G. “Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 49 (01 Aralık 2022): 175-190. https://doi.org/10.52642/susbed.1153198.
JAMA
1.Kaygısız EG. Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States. SUSBED. 2022;:175–190.
MLA
Kaygısız, Esra G. “Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 49, Aralık 2022, ss. 175-90, doi:10.52642/susbed.1153198.
Vancouver
1.Esra G. Kaygısız. Determination of Digital Density Efficiency by Data Envelopment Analysis: EU Member States. SUSBED. 01 Aralık 2022;(49):175-90. doi:10.52642/susbed.1153198