The selection of risk management techniques using case-based reasoning

Abstract

Risk needs to be managed at every stage of a construction project and by all organisations involved. Although there is a wide range of techniques available, numerous studies have shown that practitioners rely only on a few techniques. The research presented in this paper has developed a framework for breaking down risk management problems. Assessing 179 examples in the literature against this framework, a library has been created that combines techniques with given problem characteristics. Case-based reasoning (CBR) uses the principle of human reasoning as a methodology for solving problems by matching new cases to similar historic cases. This research has used the similarity measuring capability of CBR to propose risk techniques for new situations. It has been shown through CBR that risk management problems can be defined by a combination of political, economic, social, technological, legal and environmental factors with fuzziness, incompleteness and randomness. A tool has been created that can suggest the most appropriate risk technique to be used for a given situation. Validation has shown that the recommended techniques are the most appropriate, on the basis of the case-base, more than 90% of the time. This work shows the applicability of CBR to the risk management problem and, by exploring the heuristic parameters of CBR, adds to the knowledge base in this type of modelling.

Keywords:

• risk techniques
• risk management
• built environment
• case-based reasoning
• artificial intelligence

Acknowledgements

The support of the Engineering and Physical Sciences Research Council (EPSRC) in funding this work is gratefully acknowledged.