Data-Driven Evidential Reasoning Method for Evaluating e-Government Performance

The construction of electronic government (e-government) systems is a process of continuous improvement. It is necessary to evaluate the performance of e-government systems regularly to improve the services provided by government agencies and enhance the exchange of information between governments and citizens. Evaluating e-government performance based on citizens’ experience is a multiple criterion decision making (MCDM) problem under uncertainty, where assessments are qualitative, and many e-government system users are involved. Deriving criterion weights from a large amount of evaluation data is rarely discussed in previous MCDM studies. This paper proposes a data-driven evidential reasoning (DDER) method for evaluating e-government performance. A criteria framework from the citizens’ experience perspective, including service guide clarity, site usability, information sharing, documentation, and the availability of e-services, is proposed. Belief structures are used to portray uncertain assessments from e-government system users. The criterion weights are learned from the data by minimizing the dissimilarity between the aggregation assessments of the alternatives on each criterion and citizens’ historical observations on a whole. A case study is conducted in 16 cities of Anhui province in China to evaluate the performance of e-government systems. The ranking results verified the applicability and effectiveness of the proposed method.