A fuzzy inference model for risk based informed decision-making in e-business

Since its invention, the web has considerably advanced and it now provides its users with sophisticated technologies and processes for facilitating interactions. This has enabled its users to complete their tasks by efficient ways, which reduces the duration of their interaction/s and in turn increases their productivity. But in such an environment, it is imperative for a user to make informed decisions in a proactive way by which it can achieve its aims and maximize its interaction experience. In the literature, various approaches have been proposed which a user can consider and utilize while making an interaction-based decision in web-based ecommerce. But at the same time the notion of risk has been considerably ignored in that domain; even though it has been mentioned in the literature that risk plays an important part while decision-making in any domain. So in order to have such an analysis of risk while decision-making, in this paper we highlight the importance of risk and then propose a fuzzy inference model for assisting risk-based decision making in e-commerce business interactions

Transactional risk-based decision making system in e-business interactions

The credit crunch and economic crisis have demonstrated the need to properly understand, characterize and assimilate risk in business activities. Failure to do this has resulted in serious consequences to the users involved. So the analysis and management of risk is one of the important pre-requisites to ensure a successful outcome in a business activity in any domain. In this paper we propose an approach by which an interaction initiating user in the domain of e-business ascertains beforehand the level of transactional risk in the successful completion of its business activity and utilizes it to determine on an interaction. The proposed model considers the different sub-categories and characteristics of transactional risk and ascertains in numeric and semantic terms the different levels and severities of its occurrence. It then utilizes the determined analysis of transactional risk to recommend on an informed interaction-based decision to the interaction initiating user