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April 10, 2026Mathematics0 citationsOpen Access

Analysing Digital Government Performance Indicators Using a Clustering Technique-Embedded Fuzzy Decision-Making Framework

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MEMehmet ErdemAÖAkın ÖzdemirHKHatice Yalman Kosunalp

Key Points

  • The aim is to enhance the efficiency of digital government services through the evaluation of performance indicators.
  • Identified seven main criteria and twenty-one sub-criteria for evaluating performance.
  • Developed a fuzzy decision-making framework with the intuitionistic trapezoidal fuzzy number-based analytical hierarchy process.
  • Applied k-means clustering to group 165 countries based on performance indicators.
  • Utilized the TOPSIS method to rank digital governments within each cluster.
  • Identified digital technologies, innovation, and economy as key criteria for government operations.
  • Four distinct clusters of countries were formed based on their digital government performance.
  • Switzerland, Rwanda, North Macedonia, and Eswatini ranked highest in their respective clusters.
  • Sensitivity analysis was performed across ten different scenarios to validate results.

Abstract

Digital transformation is reshaping societies by promoting the adoption of advanced technologies. Moreover, the digitization of public services has become an important focus for governments. In this paper, digital government performance indicators are analyzed to improve the efficiency of digitizing public services. Based on this awareness, the seven main criteria and twenty-one sub-criteria are determined. Then, a fuzzy decision-making framework is proposed to evaluate digital government performance across 165 countries as alternatives. To the best of our knowledge, limited studies have investigated an integrated clustering-based fuzzy decision-making framework for evaluating digital government performance. The intuitionistic trapezoidal fuzzy number-based analytical hierarchy process (ITFNAHP), a part of the introduced framework, is developed to find the weights of the main criteria and sub-criteria. Digital technologies, innovation, and the economy are the most significant criteria for digital government operations. The k-means clustering method is then employed to group the alternatives. The four clusters are obtained from the clustering technique. Next, the technique of order preference similarity to ideal solution (TOPSIS) is introduced to rank the digital governments of each cluster. Switzerland, Rwanda, North Macedonia, and Eswatini are the top choices among others in each cluster, respectively. Additionally, a sensitivity analysis is conducted considering the ten different situations. In addition, the managerial and policy implications are discussed, including the achievement of Sustainable Development Goals (SDGs).

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Cite This Study

Erdem et al. (2026) studied this question.

synapsesocial.com/papers/69d894526c1944d70ce054eehttps://doi.org/10.3390/math14071233
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