Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

A vast number of methods for solving multi-criteria decision problems have been suggested for assessing criteria weights requiring more exact input data than users normally are able to provide. In particular, the selection of adequate criteria weights is difficult and in order to be realistic, other methods must be introduced. One class of such methods is to introduce so called surrogate weights, where numerical weights are assigned to each criterion based on a cardinal or ordinal rank ordering, assumed to represent the information extracted from the user. One essential problem is the robustness of such methods. In this article, we compare state-of-the-art methods based on surrogate weights from the literature and, utilising a simulation approach, discuss underlying assumptions and robustness properties. This results in a quantitative measurement of these weighting methods and a methodology applicable also to forthcoming methods.

The role of information and communication technology (ICT) in enabling various development goals including the millennium development goals and ultimately human development is no longer disputed. Emphasis is now being placed on optimizing ICT benefits on the quality of life (QoL) of people, especially in developing countries. To address this need, this paper reports a study that applied Sen's capability approach to explore how individuals in rural communities in Uganda perceived the importance of ICT toward their QoL and how this perception influenced ICT adoption. It was established that while perception was inclined to social benefits, ICT uptake and use toward improved QoL is still limited. One reasonable conclusion is therefore that state and policymakers should adopt a pluralistic approach to ICT provision: one that does not only focus on availability and affordability, but also considers expanding people's awareness and agency for development benefit. ICT investments otherwise have a high risk of being severely underutilized.