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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.