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report-bertsch

Short Term Scientific Mission of Valentin Bertsch (University of Karlsruhe, Germany) visiting Manchester Business School (MBS), UK,
within the ESF-COST Action on Algorithmic Decision Theory (Action number IC0602)

March 2008, Scientific Report

The main purpose of the Short Term Scientific Mission was the development and discussion of a sensitivity analysis framework allowing to investigate the impact of simultaneously varying the different preference and utility parameters on the results of a multi-attribute utility theory (MAUT) analysis.

In general, many fruitful discussions in the broad field of decision support, participatory approaches and the impact of risk and uncertainty took place. Moreover, potential future collaboration opportunities in the area of decision making under uncertainty were discussed throughout the whole time of the visit.

A paper entitled "Sensitivity Analysis Techniques in Multi Attribute Utility Theory" has been prepared during the visit. This paper will be submitted to OR Spectrum.

The aim in this paper is to extend some of the existing sensitivity analysis techniques to allow a more comprehensive investigation of the impact of the different sources of uncertainty on the results of a MAUT analysis. In particular, in order to be able to explore the robustness of decision processes, it is important to analyse which uncertainties are most relevant in terms of the results. Furthermore, the methods proposed in the paper are aimed at improving group decision support, i.e. at fostering consensus building by facilitating the elicitation of preference and utility parameters through sensitivity analyses. An important and challenging area of applying multi-attribute methods is industrial risk and emergency management. In modern industrial production networks and their external environment complex decision situations need to be resolved with respect to the potential impact on the society in a wide variety of circumstances. Usually, various scientific expert groups are involved with heterogeneous technical background knowledge in different disciplines. Know-how from economic, ecological, engineering and natural sciences must be brought together, taking into account political and socio-psychological factors resulting in a typical multi-attribute decision analysis (MADA) problem. Additionally, with the increasing demand from the media and the public for information and justification from authorities, methods are required to assess how decisions are taken. MADA seeks to facilitate the communication with the public and the media and can be helpful in forming an audit trail and in enhancing public confidence and understanding in relation to complex group decisions. The aim in the paper, therefore, is to apply the new sensitivity analysis approaches within a case study in the area of industrial risk management. Special emphasis is given to appropriate graphical illustrations in order to support the tangibility of the results.

Finally, I would like to thank the European Science Foundation and the steering committee of the COST action on Algorithmic Decision Theory for the funding of my visit. I had the opportunity to work with very nice, friendly and supportive colleagues in the research group at Manchester Business School. Special thanks go to Simon French, Clare Bayley and Nadia Papamichail for their support during my visit.