期刊论文详细信息
Scientific Research and Essays
Optimizing the process of developing E-government website using decision support system
Osama Mohammad Rababah1 
关键词: E-government;    E-government software developments;    metrics;    quality evaluation;    decision support systems.;   
DOI  :  5897/SRE2015.6361
学科分类:社会科学、人文和艺术(综合)
来源: Academic Journals
PDF
【 摘 要 】

The purpose of this paper was to address the issue of E-government website evaluation regarding the provision of a decision-making framework built around the concepts of website evaluation. The proposed framework deploys a Bayesian Belief Network (BBN) to conquer the subjectivity and inaccuracy that characterizes the conventional models for E-government website quality assessment. Since the developments of E-government system are becoming more and more complex, an entire quantitative evaluation process concerning all pertinent quality characteristics is also a complex issue. This is caused by a lot of intervening features, and by the compound logic relationships among attributes and characteristics. To achieve the preferred quality of E-government website, it is essential to produce an intelligent engine that enables evaluation of E‑government system’s quality. This intelligent engine would provide a consistent and practical approach for assessing the quality of the E-government website. The assessment can be carried out prior to the completion of the software development, therefore, providing insight into the trend and direction of correction and improvements. It can also be performed on accomplished and operational work, providing analysis of areas for enhancement. The performance of the intelligent engine should be pretty quick and practical in providing an overall comprehensive assessment with root-cause analysis that would lead to corrective measures to improve the quality of E‑government website. Case studies were selected to demonstrate this and justify its validity.

【 授权许可】

CC BY   

【 预 览 】
附件列表
Files Size Format View
RO201902010490206ZK.pdf 749KB PDF download
  文献评价指标  
  下载次数:10次 浏览次数:14次