Behavioural decision theory for multi-criteria decision analysis: a guided tour

Abstract

Multi-criteria decision analysis (MCDA) involves asking decision makers difficult questions, and can leave them thinking that their judgements are not as coherent as they might have thought. This experience can be distressing and may even lead to rejection of the analysis. The psychology of preference sheds light both on how people naturally make choices without decision analytic assistance, and on how people think about the MCDA elicitation questions. As such, it can help the analyst to respond helpfully to difficulties which decision makers may face. In this paper, we review research from Behavioural Decision Theory relevant to MCDA. Our review follows the MCDA process, discussing research relevant to the structuring, value elicitation, and weighting phases of the analysis, outlining relevant and important findings, and open questions for research and practice.

Keywords:

• decision analysis
• multi-criteria decision analysis
• behavioural decision theory
• psychology
• decision biases
• experiments
• problem structuring

This paper is a revised version of a Keynote Paper given in the Decision Analysis stream at Young OR15 in Bath, March 2007.

This paper is a revised version of a Keynote Paper given in the Decision Analysis stream at Young OR15 in Bath, March 2007.

Acknowledgements

This paper has grown out of our teaching together on courses OR304 Decision Analysis in Theory and Practice, OR425 Decision Analysis in Social Context, and Barbara Fasolo's teaching on OR405 Advanced Topics in Behavioural Decision Theory, and we are indebted to our co-teachers, Larry Phillips, Carlos Bana e Costa, Val Belton, Daniel Read, and Greg Davies for numerous stimulating discussions. We thank Larry Phillips for supplying us with the data on which Figure 2 is based, and Gilberto Montibeller for helpful comments. We are grateful to Ana Barcus for inviting us to present a keynote at Young OR and to the YOR audience for questions, comments, and appreciation. We thank the reviewers for helpful suggestions that improved the clarity of this paper.