Abstract
When several interdependent events affect the future of an organization, an industry, or a society, it is often useful to know how these events may affect each other. Determining the impact of external events on other such events, called a cross-impact analysis, is usually accomplished by asking knowledgeable people to (1) discuss any relationships among the events and (2) provide subjective estimates of conditional probabilities relating the events. However, there are two possible problems. First, in some political environments people may be reluctant to discuss the events openly. Second, the subjective probability estimates may violate the laws of probability theory, such as Bayes' theorem. We present a simple method, using group decision support systems (GDSS), for eliciting anonymous comments and preparing consistent probability estimates concerning interdependent events. We then illustrate our method by using it to perform a cross-impact analysis concerning the future of Hong Kong.
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