USING DATA ENVELOPMENT ANALYSIS TO EVALUATE THE EFFICIENCY OF EUROPEAN UNION COUNTRIES IN INFORMATION TECHNOLOGIES

Öz

In an environment where international competitive conditions are becoming increasingly difficult in parallel with the changes in science and technology, the importance of developments in information technologies is increasing day by day. This study aims to specify the relative efficiency of European Union countries in the field of information technologies using Data Envelopment Analysis. In this direction, four inputs and four outputs are determined. According to both the CCR and BCC models, Austria, Croatia, Czechia, France, Germany, Lithuania, Poland, Slovakia, Slovenia, and Spain are the countries that cannot show 100% performance in obtaining information technology outputs with the information technology inputs determined in the study. While Belgium and Poland are effective in the BCC analysis, they are not effective in the CCR analysis. In this case, Belgium and Poland are technically effective in BCC analysis, but can not achieve scale efficiency. Input and output rates of inefficient countries are interpreted by comparing them with best practice benchmarks.

Anahtar Kelimeler

• Data Envelopment Analysis
• Effectiveness
• European Union Countries
• Information Technologies

Kaynakça

1. Aceituno, J. C., Orzaez, M. H., Cepeda, J. T., Nieto, A. M. and Ramos, J. G. (2023) "Application of the Data Envelopment Analysis Technique to Measure the Environmental Efficiency of the 27 Countries of the European Union During the Period 2012-2020", Clean Technologies and Environmental Policy, 1-29.
2. Banker, R. D., Charnes, A. and Cooper, W. W. (1984) "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis", Management Science, 30(9):1078-1092.
3. Castellano, R., Gabriella De, B. and Punzo, G. (2023) "Well-being in OECD Countries: An Assessment of Technical and Social Efficiency Using Data Envelopment Analysis", International Review of Economics, 141-176.
4. Charnes, A., Cooper, W. W. and Rhodes, E. (1978) "A Measuring the Efficiency of Decision Making Units", European journal of operational research, 2(6):429-444.
5. Cook, W. D., Tone, K. and Zhu, J. (2014) "Data envelopment analysis: Prior to choosing a model", Omega, 44: 1-4.
6. Cooper, W. W., Seiford, L. M. and Tone, K. (2007). "Data Envelopment Analysis: A Comprehensive Text With Models, Applications, References and DEA-Solver Software" (Vol. 2). New York: Springer.
7. Cooper, W. W., Seiford, L. M. and Zhu, J. (2011) "Data Envelopment Analysis: History, Models and Interpretations", London: Springer.
8. Cvetkoska, V. (2011) "Data Envelopment Analysis Approach and Its Application In Information and Communication Technologies", HAICTA, 421-430.

9. Erdin, C. and Çağlar, M. (2023) "National Innovation Efficiency: a DEA-Based Measurement of OECD Countries", International Journal of Innovation Science, 15(3):427-456.
10. European Commission (2023) "European Innovation Scoreboard 2023", Publications Office of the European Union.
11. Eurostat (2023) https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Main_Page (11.10.2023) Golany , B. and Roll, Y. (1989) "An application procedure for DEA", Omega, 17(3):237-250.
12. Hsieh, L. F. and Lin, L. H. (2010) "A Performance Evaluation Model for International Tourist Hotels in Taiwan—An Application of The Relational Network DEA", International Journal of Hospitality Management, 29(1):14-24.
13. Keçek, G. (2010) "Veri Zarflama Analizi Teori ve Uygulama Örneği", Ankara: Siyasal Kitabevi.
14. Liu, J., Gong, Y., Zhu, J. and Titah, R. (2022) "Information Technology and Performance: Integrating Data Envelopment Analysis and Configurational Approach", Journal of the Operational Research Society, 73(6):1276-1293.
15. Paradi, J. C., Yang, Z. and Zhu, H. (2011) "Assessing Bank and Bank Branch Performance: Modeling Considerations and Approaches", Handbook on Data Envelopment Analysis, 315-361.
16. Shafer, S. M.and Byrd, T. A. (2000) "A Framework for Measuring The Efficiency of Organizational Investments in Information Technology Using Data Envelopment Analysis", Omega, 28(2):125-141.
17. Sherman, H. D. and Zhu, J. (2006) "Service Productivity Management: Improving Service Performance Using Data Envelopment Analysis (DEA)", USA: Springer .
18. Thanassoulis, E., Dyson, R. G. and Foster, M. J. (1987) "Relative Efficiency Assessments Using Data Envelopment Analysis: An Application to Data on Rates Departments", Journal of the Operational Research Society, 38:397-41.
19. Xu, K., Mei, R., Sun, W., Zhang, H. and Liang, L. (2023) "Estimation of Sustainable Innovation Performance in European Union Countries: Based on the Perspective of Energy and Environmental Constraints", Energy Reports, 9:1919-1925.
20. Yaylalı, M., Oktay, E., Akan, Y. and Kaynak, S. (2007) "Türkiye Ve Avrupa Birliğine Üye Ülkelerin Bilgi Ekonomisi Performanslarının Veri Zarflama Analizi Metoduyla Karşılaştırılması", Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(1):1-25.
21. Zhu, J. and Zhu, J. (2014) "Data Envelopment analysis", Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis With Spreadsheets, New York: Springer.