Trust in Logistics Services

Program Code: 
Description of Work: 


Trust and Reputation is vital to Transport Logistics Industry, Government, Consumers, Business etc, especially if we look at long-term strategies. Recommendation systems through collective intelligence and crowdsourcing techniques to determine the trust and reputation of service providers and making recommendations to the customers; The contribution of this research is to build a set of methodologies for evaluating the trust, security and accountability mechanisms, analysing cascading failures and calculate the value at Risk Models, and their application to government, extended enterprises and the consortium industry. Another aspect of the research work include defining a new conceptual framework for an enhanced Service-Oriented Architecture (SOA) infrastructure – Service Space – with regard to service distribution and service discovery. We will explore the junction of the frontiers of several ICT disciplines: software architecture, information retrieval, distributed systems, business intelligence and SOA. The September 2014 16 framework will integrate web services, social networking and the Web 2.0 technology by conceptualising and realising a number of original web-compliant SOA architectural styles for service-oriented computing. The research will integrate Web 2.0 practices into the area of web services / SOA. In particular, the concept of being able to search for an entity in order to form a coalition with it is central to the idea of the formation of Digital Ecosystems. Traditional service discovery mechanisms, which are typically non-semantic in nature, suffer from many issues, most notable of which is the imprecision of search results. Moreover, there is no method by which the quality of a service provider that has been nominated as a result of the search process can be ensured. The recommendation systems will provide methods that filter and rank the result of search processes based on the quality of the service providers retrieved as a result of the search process. The proposed system keeps track of the quality of all the service providers and displays them for the end-user the recommendation dashboard during the search-retrieval process.

Description of Work:

This project involves design and development of algorithms, knowledge, information analysis techniques, good mathematical knowledge as well as numerical modelling.


Prof Elizabeth Chang (