Efficiency of digital transformation in the EU-27: A sequential bi-objective MCDEA BCC, super-efficiency and slack-based measure framework
DOI:
https://doi.org/10.55573/JISED.118757Keywords:
Data Envelopment Analysis, Bi-Objective MCDEA, Super-Efficiency, Slack-Based Measure, digital transformation, EU-27Abstract
Digital transformation has become increasingly important for improving public-sector performance and the delivery of electronic government services. Nevertheless, European Union (EU) member states differ substantially in their ability to convert digital access, institutional support, and innovation-related resources into effective digital public-service outcomes. This study evaluates the relative efficiency of digital transformation across the EU-27 using a sequential Data Envelopment Analysis (DEA) framework. Three input indicators—Internet Users, Government Support, and Gross R&D Expenditure—and three output indicators—Online E-Government Services, Satisfaction with eID, and Interaction with Public Administration—are examined. The analytical framework comprises three complementary stages. The Bi-Objective Multiple Criteria Data Envelopment Analysis (MCDEA) BCC Output-Oriented model is first used to estimate relative efficiency and identify frontier-efficient countries. Super-Efficiency analysis is subsequently applied to the frontier-efficient countries to provide additional discrimination, whereas the non-oriented Slack-Based Measure (SBM) model is used to examine input excesses, output shortfalls, and benchmark projections among the remaining countries. The Bi-Objective MCDEA BCC results identify Hungary and Portugal as frontier-efficient, each with an efficiency score of 1.000. Super-Efficiency analysis produces scores of 0.9999997 for Hungary and 1.009678 for Portugal, providing further differentiation between the two frontier countries. The SBM analysis reveals substantial heterogeneity in non-radial efficiency, with Cyprus recording the lowest SBM score of 0.2117047 within the evaluated EU-27 sample. The slack analysis further demonstrates that relatively inefficient countries exhibit different combinations of unused enabling capacity and output shortfalls. The sequential framework therefore provides complementary evidence on efficiency measurement, frontier discrimination, and inefficiency diagnosis, thereby extending digital-transformation benchmarking beyond reliance on a single efficiency score.
Downloads
References
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261-1264. https://doi.org/10.1287/mnsc.39.10.1261
Bánhidi, Z., & Dobos, I. (2023). Measurement of digital development with partial orders, Tiered DEA, and cluster analysis for the European Union. International Review of Applied Sciences and Engineering. https://doi.org/10.1556/1848.2023.00612
Bánhidi, Z., & Dobos, I. (2024). Measuring digital development: Ranking using data envelopment analysis (DEA) and network readiness index (NRI). Central European Journal of Operations Research. https://doi.org/10.1007/s10100-024-00919-y
Brodny, J., & Tutak, M. (2022a). Analyzing the level of digitalization among the enterprises of the European Union member states and their impact on economic growth. Journal of Open Innovation: Technology, Market, and Complexity, 8(2), 70. https://doi.org/10.3390/joitmc8020070
Brodny, J., & Tutak, M. (2022b). Digitalization of small and medium-sized enterprises and economic growth: Evidence for the EU-27 countries. Journal of Open Innovation: Technology, Market, and Complexity, 8(2), 67. https://doi.org/10.3390/joitmc8020067
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
da Silva, A. F., Marins, F. A. S., & Dias, E. X. (2020). Improving the discrimination power with a new multi-criteria data envelopment model. Annals of Operations Research, 287(1), 127-159. https://doi.org/10.1007/s10479-019-03446-1
da Silva, A. F., Miranda, R. D. C., Marins, F. A. S., & Dias, E. X. (2024). A new multiple criteria data envelopment analysis with variable return to scale: Applying bi-dimensional representation and super-efficiency analysis. European Journal of Operational Research, 314(1), 308-322. https://doi.org/10.1016/j.ejor.2023.09.008
Emrouznejad, A., Brzezicki, Ł., & Lu, C. (2025). Development and evolution of slacks-based measure models in data envelopment analysis: A comprehensive review of the literature. Journal of Economic Surveys, 39(5), 2106-2133. https://doi.org/10.1111/joes.12682
Georgescu, M. R., Stoica, E. A., Bogoslov, I. A., & Lungu, A. E. (2022). Managing efficiency in digital transformation-EU member states performance during the COVID-19 pandemic. Procedia Computer Science, 204, 432-439. https://doi.org/10.1016/j.procs.2022.08.053
Ghasemi, M.-R., Ignatius, J., & Emrouznejad, A. (2014). A bi-objective weighted model for improving the discrimination power in MCDEA. European Journal of Operational Research, 233(3), 640-650. https://doi.org/10.1016/j.ejor.2013.08.041
Guo, I.-L., Lee, H.-S., & Lee, D. (2017). An integrated model for slack-based measure of super-efficiency in additive DEA. Omega, 67, 160-167. https://doi.org/10.1016/j.omega.2016.05.002
Hatami-Marbini, A., & Toloo, M. (2017). An extended multiple criteria data envelopment analysis model. Expert Systems with Applications, 73, 201-219. https://doi.org/10.1016/j.eswa.2016.12.030
Horváthová, J., & Mokrišová, M. (2024). The use of the data envelopment analysis-Malmquist approach to measure the performance of digital transformation in EU countries. Economies, 12(11), 291. https://doi.org/10.3390/economies12110291
İnel, M. N. (2019). An empirical study on measurement of efficiency of digital transformation by using data envelopment analysis. Management Science Letters, 9(4), 549-556. https://doi.org/10.5267/j.msl.2019.1.008
Ivanová, E., & Grmanová, E. (2023). Digital transformation and ICT sector performance in EU countries. Problems and Perspectives in Management, 21(1). https://doi.org/10.21511/ppm.21(1).2023.05
Krejnus, M., Stofkova, J., Stofkova, K. R., & Binasova, V. (2023). The use of the DEA method for measuring the efficiency of electronic public administration as part of the digitization of the economy and society. Applied Sciences, 13(6), 3672. https://doi.org/10.3390/app13063672
Lobonț, O. R., Criste, C., Vintilă, A. I., Crăciun, A. F., & Moldovan, N. C. (2025). Assessing digital performance of public services in the EU: E-governance and technology integration. Systems, 13(6), 425. https://doi.org/10.3390/systems13060425
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498-509. https://doi.org/10.1016/S0377-2217(99)00407-5
Tone, K., Toloo, M., & Izadikhah, M. (2020). A modified slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 287(2), 560-571. https://doi.org/10.1016/j.ejor.2020.04.019
Tran, T.-H., Mao, Y., Nathanail, P., Siebers, P.-O., & Robinson, D. (2019). Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis. Omega, 85, 156-165. https://doi.org/10.1016/j.omega.2018.06.008
Xie, Q., Zhang, L. L., Shang, H., Emrouznejad, A., & Li, Y. (2021). Evaluating performance of super-efficiency models in ranking efficient decision-making units based on Monte Carlo simulations. Annals of Operations Research, 305(1-2), 273-323. https://doi.org/10.1007/s10479-021-04148-3
Yalçın, E. C. (2021). Efficiency measurement of digitalization on EU countries: A study based on data envelopment analysis. International Journal of Management, Knowledge and Learning, 10(1), 323-333. https://doi.org/10.53615/2232-5697.10.323-333
