Belief-Rule-Based Expert Systems for Evaluation of E- Government: A Case Study
This work addresses the challenge of evaluating e-government systems for developers and managers, offering a tool to improve decision-making under uncertainty, though it is incremental as it builds on existing expert system and belief rule base techniques.
The paper tackles the problem of evaluating complex e-government systems by proposing a Belief Rule-Based Expert System (BRBES) that handles uncertain data, and it shows that BRBES provides more accurate and reliable results compared to a recent evaluation method in a case study in Bangladesh.
Little knowledge exists on the impact and results associated with e-government projects in many specific use domains. Therefore it is necessary to evaluate the efficiency and effectiveness of e-government systems. Since the development of e-government is a continuous process of improvement, it requires continuous evaluation of the overall e-government system as well as evaluation of its various dimensions such as determinants, characteristics and results. E-government development is often complex with multiple stakeholders, large user bases and complex goals. Consequently, even experts have difficulties in evaluating these systems, especially in an integrated and comprehensive way as well as on an aggregate level. Expert systems are a candidate solution to evaluate such complex e-government systems. However, it is difficult for expert systems to cope with uncertain evaluation data that are vague, inconsistent, highly subjective or in other ways challenging to formalize. This paper presents an approach that can handle uncertainty in e-government evaluation: The combination of Belief Rule Base (BRB) knowledge representation and Evidential Reasoning (ES). This approach is illustrated with a concrete prototype, known as Belief Rule Based Expert System (BRBES) and put to use in the local e-government of Bangladesh. The results have been compared with a recently developed method of evaluating e-Government, and it is shown that the results of BRBES are more accurate and reliable. BRBES can be used to identify the factors that need to be improved to achieve the overall aim of an e-government project. In addition, various "what if" scenarios can be generated and developers and managers can get a forecast of the outcomes. In this way, the system can be used to facilitate decision making processes under uncertainty.