Evaluation of E-commerce System Trustworthiness Using Multi-criteria Analysis

被引:0
|
作者
Wang, Lifeng [1 ]
Wu, Zhengping [2 ]
机构
[1] Univ Bridgeport, Dept Comp Sci & Engn, Bridgeport, CT 06604 USA
[2] Calif State Univ San Bernardino, Dept Comp Sci & Engn, San Bernardino, CA 92407 USA
关键词
trustworthiness; measurement; multi-criteria analysis; trust space; trust model;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Trustworthiness is a very critical element and should be treated as an important reference when customers try to select proper e-commerce systems. Trustworthiness evaluation requires the management of a wide variety of information types, parameters and uncertainties. Multi-criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform trustworthiness evaluations as a result of its flexibility and the possibility. For making trustworthiness measurement simple and standardized, this paper proposes a novel trustworthiness measurement model based on multi-criteria decision analysis. Recently, a lot of great efforts have been carried out to develop decision making for evaluation of trustworthiness and reputation. However, these research works still stay on the stage of theoretical research. This paper proposes and implements a trustworthiness measurement model using multi-criteria decision making approach for e-commerce systems. Firstly, this paper recognizes trust factors of e-commerce systems and distributes the factors in our designed multi-dimensional trust space and trust trustworthiness measurement model. All relevant factors are filtered, categorized and quantified. Then, our designed multi-criteria analysis mechanism can deal with the trust factors and analyze their trust features from different perspectives. Finally, the evaluated trustworthiness result is provided. Meanwhile, we also have a knowledge learning based approach to improve the accuracy of the result. At the end of this paper, we have conducted several experiments to validate our designed trustworthiness measurement by involving real world data. Our evaluated trustworthiness result and real world data are matched very well.
引用
收藏
页码:86 / 93
页数:8
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