Fuzzy decision support for service selection in e-business environments

The emergence of semantic overlay networks as instruments to improve security, trust and stability in distributed virtual communities is recognized widely in the research community. We propose a fuzzy logic based framework which integrates social information such as trustworthiness, reputation and credibility ratings for individuals, alliances, organizations, services and products in e-commerce markets. This framework is designed to support the decision making process of autonomous agents during the selection of the optimal business partner. Fuzzy systems provide the ideal capabilities to process multiple criteria, which are composed of imprecise information and attribute definitions expressed in natural language. The proposed fuzzy models implement the DEco Arch framework and ontologies which provide details about concepts and their relationships in virtual communitie

A trust-aware framework for service selection and service quality review in e-business ecosystems

University of Technology, Sydney. Faculty of Information Technology.As e-Business has moved from a niche market to a decisive contributor for the success of most companies, some issues need to be solved in order to assist the continued success of e-Business. The challenge, to deploy fully autonomous business service agents which undertake transactions on behalf of their owners, often fails due to lack of trust in the agent and its decisions. Four aspects can overcome this challenge. Firstly, intelligent agents need to be equipped with self-adjusting reputation, trustworthiness and credibility evaluation mechanisms to assess the trustworthiness of potential counterparts prior to a business transaction. Secondly, such evaluation mechanisms must be transparent and easy to comprehend so agent owners develop trust in their agents’ decisions. Thirdly, the calculations of an agent must be highly customisable so that the agent owner can apply his personal experiences and security requirements to govern the decision making process of the intelligent agent. And finally, agents must communicate via standardised and open protocols in order to facilitate interaction between services deployed across different architectures and technologies. This thesis proposes the DEco Arch framework which integrates behavioural trust element relationships into various decision making processes found in e-Business ecosystems. We apply fuzzy-logic based soft computing techniques to increase user confidence and therefore enhance the adoption of the proposed assessment and review methodologies. A proof-of-concept implementation of the DEco Arch framework has been developed to showcase the proposed concepts in a case study and to conduct empirical experiments to evaluate the robustness and practicability of the proposed methodologies

PREdictive model for DISaster response configuration (PREDIS decision platform)

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe extraordinary conditions of a disaster, require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area. This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning. The aim of this research is to provide a solution to reduce the partner proliferation problem. To that end the main research question is put forward as “How to reduce the proliferation of partners in a disaster response”? Panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2013 via regression analysis, MA and AHP gives rise to the formation of a predictive decision-making platform called PREDIS. It is capable of predicting the human impact of the disaster (fatality, injured, homeless) of up to 3% of errors and enables the decision makers to estimate the required needs for each disaster and prioritises them based on the disaster type and socio-economics of the affected country. It further renders it possible to rank and optimise the desired partners based on the decision maker’s preferences. Verification of the PREDIS through a simulation game design using a sample group of decision makers, show that this technique enables the user to decide within one hour after the disaster strike using the widely available data at the time of the disaster. It also enables non-experts to decide almost identically to experts in terms of the similarity of the choices and the speed of the decision.The lack of an extensive database for the potential humanitarian partners from which to choose, is the limitation of this research in addition to the lack of standardised set of minimum requirements for the suitable partners.The model is also as strong as its data feed which is inconsistent in various humanitarian sources