Cloud Model-Based Development Level Evaluation for Digital Governments

Abstract

With the development of digital transformation, advancing digital government construction is crucial for enhancing public service efficiency, increasing transparency, and promoting civic engagement, which has drawn significant attention from governments and academia. However, traditional evaluation methods for digital governments have limited capabilities in addressing data uncertainty and complex relationships, often requiring strict assumptions and lacking flexibility in integrating multi-dimensional information. Cloud models, which combine probability theory and fuzzy logic, are well-suited to handle these challenges. This paper proposes a Cloud Model-Based Development Level Evaluation method to evaluate the development level of digital governments. A comprehensive evaluation framework is established, with metrics designed to evaluate the maturity and effectiveness of digital government initiatives. Furthermore, each metric is transformed into a development-level cloud model using quantitative methods tailored to that specific indicator. To achieve an overall evaluation, weighting coefficients are applied to generate a hybrid cloud model that evaluates the development level of digital governments. Finally, the practical efficacy and validation of the proposed method are demonstrated through an experiment, thereby confirming its applicability and reliability.