Beyond Compensatory Benchmarking: A Robust Multi-Criteria Decision Support Framework for Regional Digital Economy Performance
DOI:
https://doi.org/10.35877/soshum4682Keywords:
Digital Economy Performance, Decision Support System (DSS), Multi-Criteria Decision Making (MCDM), Analytical Hierarchy Process (AHP), TOPSISAbstract
The multi-dimensional nature of the digital economy is such that there is a need to develop new methodologies to overcome the limitations of existing methods of measuring regional digital economy performance beyond composite indicators. The existing methods of benchmarking, which are based on compensatory aggregation, may mask structural problems in key governance areas. The research aims to develop an integrated multi-criteria decision support system to evaluate regional digital economy performance by applying the Analytical Hierarchy Process (AHP) with the geometric mean method for determining the weight of each criterion and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking. The quantitative approach to multi-criteria decision-making (MCDM) has been used to develop the decision support system. The results of the research indicate that the digital economy’s cybersecurity and digital trust are the most influential factors in determining digital economy performance. The results of the TOPSIS analysis indicate that there is a clear stratification of digital economy performance across regions, with the best-performing regions having well-developed digital infrastructure, human capital readiness, and cybersecurity. The results of the sensitivity analysis indicate that the ranking of digital economy performance is robust across all scenarios. The research contributes to theory by providing a new approach to measuring digital economy performance. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support. The research contributes to the methodological approach to multi-criteria decision-making by providing an integrated approach to decision support. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support.
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Copyright (c) 2026 Leroy Samy Uguy, Esther Kembauw, Robbi Rahim

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

