Sensitivity analyses in multi‐attribute decision support for off‐site nuclear emergency and recovery management

Abstract

Purpose

Emergency situations may differ in many ways but they share some common characteristics, such as the sudden onset and the need to transparently evaluate various usually conflicting objectives. In nuclear power generation, however, emergency situations constitute a special challenge. The focus of this paper is to highlight the role of multi‐criteria decision analysis (MCDA) in nuclear emergency and recovery management on the basis of a hypothetical case study.

Design/methodology/approach

Multi‐attribute value theory as one field of research within MCDA is introduced. Special emphasis is placed on the modelling of the decision makers' preferences which is a crucial part in any multi‐criteria analysis. A central aim is to facilitate the preference elicitation in group decision processes.

Findings

The management of emergency situations in nuclear power generation necessitates the consideration of technical, economic, environmental, socio‐psychological and political aspects. Furthermore, various stakeholder and expert groups with diverse background knowledge and different views, responsibilities and interests are involved in such a decision‐making process. MCDA can help to take into account various incommensurable aspects and the subjective preferences of the decision makers and thus contribute to transparency and traceability of decision‐making processes. Since the preference parameters are inherently afflicted with uncertainties, thorough sensitivity analyses are important to visualise the impact of the uncertainties in an understandable way.

Originality/value

A new approach to sensitivity analysis is proposed, allowing one to comprehensibly visualise and communicate the impact of the uncertainties associated with the subjective preference parameters on the results of the decision analysis.

Citation

Bertsch, V., Treitz, M., Geldermann, J. and Rentz, O. (2007), "Sensitivity analyses in multi‐attribute decision support for off‐site nuclear emergency and recovery management", International Journal of Energy Sector Management, Vol. 1 No. 4, pp. 342-365. https://doi.org/10.1108/17506220710836075