Radiation protection authorities have seen a potential for applying multiattribute risk analysis in nuclear emergency management and planning to deal with conflicting objectives, different parties involved, and uncertainties. This type of approach is expected to help in the following areas: to ensure that all relevant attributes are considered in decision making; to enhance communication between the concerned parties, including the public; and to provide a method for explicitly including risk analysis in the process. A multiattribute utility theory analysis was used to select a strategy for protecting the population after a simulated nuclear accident. The value-focused approach and the use of a neutral facilitator were identified as being useful.

Abstract. Sensitivity analyses have for long been used to assess the impacts of uncertainties on outcomes of decision models. Several approaches have been suggested, but it has been problematic to get a quick overview of the total impact of all the uncertainties. Here we show how interval modeling can be used for global sensitivity analyses in multiattribute value trees, and a nuclear emergency case is used to illustrate the method. The approach is conceptually simple and computationally feasible. With intervals the decision maker can include all the possible uncertainties and quickly estimate their combined impact. This is especially useful in high-risk decisions where a worst case type of sensitivity analysis is essential. By varying the intervals one can also examine which uncertainties have the greatest impact and thus need the most consideration. Global sensitivity analysis reveals how the outcome is affected by many simultaneous variations in the model.

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The development of a product portfolio is a strategic decision which is often complicated by the large number of competing products, product interactions and high uncertainties about how successful the products will be in the marketplace. These decisions are commonly supported either by financially oriented approaches (e.g., net present value) or more qualitative approaches (e.g., scoring models) which, however, tend to suffer from shortcomings in capturing uncertainties and portfolio effects. Motivated by these, we report a real-life case study where a recently developed preference programming method -called Robust Portfolio Modelling (RPM) -was used to support the management group of a telecommunication company in the development of a strategic product portfolio in view of a 2-3 years time horizon. The positive experiences from this case study suggest that RPM may be useful even in other related settings where the presence of multiple objectives, uncertainties about product outcomes and possible variations in budgetary constraints must be accounted for.Reference to this paper should be made as follows: Lindstedt, M., Liesiö, J. and Salo, A. (2008) 'Participatory development of a strategic product portfolio in a telecommunication company', Int. J. Technology Management, Vol. 42, No. 3, Biographical notes: The research interests of Professor Ahti Salo (MSc 1987, D.Tech. 1992 include decision analysis, risk management, technology foresight and technology assessment. He has been in charge of a wide range of applied research projects funded by industrial firms, the Committee for the Future of the Parliament, the Ministry of Trade and Industry and the National Technology Agency in Finland, among others. He has published well over 30 refereed articles in leading journals such as Technological