Impact assessment (IA) in policy making processes has received increasing attention in recent years. One of the major challenges in IA is how to rationally handle and make maximum use of information in uncertain and qualitative data so that the best course of action can be reliably identified. It is discussed in this chapter how the Evidential Reasoning (ER) approach for multiple criteria decision analysis (MCDA) can be used to take the challenge. The ER approach and its software implementation, called the Intelligent Decision System (IDS), are developed with a focus on rationally handling a large amount of information of both a qualitative and quantitative nature and possibly with different degrees of uncertainties in assessment problems. It applies belief decision matrices for problem modelling so that different formats of available data and uncertain knowledge can be incorporated into assessment processes. It uses an evidential reasoning process on the data to generate assessment outcomes that are informative, rational and reliable. Several examples are examined to demonstrate how IDS can be used to support activities in different stages of an IA process, namely (a) problem structuring, (b) assessment model building, including value elicitation, (c) data collection, management, and aggregation, and (d) data presentation and sensitivity analysis. This investigation shows that IDS is not only a versatile assessment supporting tool, but also a knowledge management tool which helps to organise assessment knowledge and data systematically for better traceability, consistency and efficiency in assessment.
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Xu, DL., Yang, JB., Liu, X. (2008). Handling Uncertain and Qualitative Information in Impact Assessment – Applications of IDS in Policy Making Support. In: Da Ruan, Hardeman, F., van der Meer, K. (eds) Intelligent Decision and Policy Making Support Systems. Studies in Computational Intelligence, vol 117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78308-4_9
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