Vol. 12 No. 4 (2024): Business & Management Studies: An International Journal
Articles

Clustering Türkiye and EU Member states according to their e-government performance: Evaluation with SD-based SAW method

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  • Hande Eren,
  • Emel Gelmez
Hande Eren
Assist. Prof. Dr., Kapadokya University, Nevşehir, Turkiye
Emel Gelmez
Assoc. Prof. Dr., Selçuk University, Konya, Turkiye

Published 2024-12-25

Keywords

  • E-Government Performance, Clustering Analysis, SD Method, SAW Method
  • E-Devlet Performansı, Kümeleme Analizi, SD Yöntemi, SAW Yöntemi

How to Cite

Clustering Türkiye and EU Member states according to their e-government performance: Evaluation with SD-based SAW method. (2024). Business & Management Studies: An International Journal, 12(4), 838-854. https://doi.org/10.15295/bmij.v12i4.2440

Copyright (c) 2024 Hande Eren- Emel Gelmez

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Clustering Türkiye and EU Member states according to their e-government performance: Evaluation with SD-based SAW method. (2024). Business & Management Studies: An International Journal, 12(4), 838-854. https://doi.org/10.15295/bmij.v12i4.2440

Abstract

With the development of technology, significant transformations have occurred in providing services to citizens by governments or states. In this process, the practical determination of the countries' e-government practices can be considered an important issue. In this context, the primary purpose of this study is to determine the e-government performances of Türkiye and the European Union (EU) countries by utilising Multi Criteria Decision Making (MCDM) methods. The study employed the E-government Development Index (EGDI) to align with its primary purpose. In this context, three criteria were used: online service index, human capital index and telecommunication infrastructure index. In order to determine the e-government performance of the countries, cluster analysis was first performed. WEKA program was used to implement the cluster analysis. As a result of the analyses, it was determined that Türkiye and 28 EU member countries were divided into 4 clusters in terms of e-government performance. The most consistent results among the applied algorithms were obtained from the EM algorithm. According to the results of the EM algorithm, the criteria averages were calculated for each cluster, and a new decision matrix was obtained with three criteria and four alternatives (clusters). The SD (Standard Deviation) method weighed the criteria for this new decision matrix. Applying the SD method, the criterion with the highest importance level was determined as the online service index. Then, the clusters were ranked among themselves with the SAW (Simple Additive Weighting) method. According to the results of the SAW method, it was determined that Cluster 1 had the best performance in terms of e-government performance; Cluster 1 was followed by Cluster 0, Cluster 3 and Cluster 2, respectively.

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