Trustworthiness Measurement of E-commerce Systems Using Fuzzy Hybrid Multi-criteria Analysis

Mutual trust has been the most important factor for users to do business with each other. But the trustworthiness of an entire system provides assurance for users to choose a particular e-commerce platform at the first place. As a difficult-to-observe property of an e-commerce system, the measurement of overall trustworthiness is obstructed by quantification, accuracy and reliability. This paper proposes a fuzzy hybrid multi-criteria analysis approach to measure the trustworthiness of e-commerce systems. Trust factors involved in e-commerce systems are collected and grouped. Then, these factors are quantified and placed in a designated trust space using customized fuzzy membership functions. Based on the nature of various trust factors and alternatives, multi-criteria analysis is applied. After all relevant factors are filtered, categorized and quantified, the proposed multi-criteria analysis method will process all trust factors and analyze their features from different perspectives. To precisely process the proposed trustworthiness measurements, feature categorization, membership function adjustment, criteria function and priority voting function adaptation are also used. Finally, a combination of fuzzy quantified factors and multi-criteria analysis can expose the credibility of all e-commerce system aspects. Experiment results show that the proposed measurements can evaluate and rank e-commerce system trustworthiness accurately and effectively.