Robustness of computational intelligent assurance models when assessing e-Commerce sites

E-commerce assurance platforms continue to emerge in order to facilitate trustworthy transactional relationships between buyers and sellers. However, as the sophistication of the e-commerce environments increase, the risks associated with transacting online also increase which pose a challenge to consumers to freely transact online. Although traditional assurance models are still used by various e-commerce sites, some of these models are not robust enough to provide adequate assurance on key areas of customer concerns in the cyber space. This research proposes a robust intelligent PRAHP framework built on Analytical Hierarchy Process complemented with an evidential reasoning from page ranking. PRAHP algorithms are modularised to run concurrently whose consensus decision takes place in a decision table. PRAHP objectively extracts real-life data directly from each of the 10 e-commerce websites comparatively using assurance attributes: Advanced Security, Policy, Advanced ISO, Advanced legislation and Availability. The assurance of e-commerce sites using PRAHP was experimented on small and large e-Commerce enterprises and validated by determining the effects of varied damping factor d on PRAHP, and comparing with customer´s site perceptions. The experimental results demonstrate that the proposed framework is sufficiently robust for current site assurance applications and shows the trustworthiness aspect of the framework in instances of uncertainty.