Aggregated Causal Maps: An Approach To Elicit And Aggregate The Knowledge Of Multiple Experts

摘要

This paper presents a systematic procedure to elicit and aggregate the knowledge of multiple individual experts and represent it in the form of an Aggregated Causal Map (ACM). This procedure differs from existing methods in two ways. First, unlike other methods, this method does not rely on group interaction in eliciting knowledge of multiple experts, and, therefore, is not fraught with biases associated with group dynamics. Second, this method uses both the idiographic and nomothetic approaches while existing methods focus on nomothetic approaches to knowledge elicitation. We draw on the strengths of both approaches by using the idiographic approach to elicit and aggregate the knowledge of multiple experts and the nomothetic approach to validate the knowledge elicited. We illustrate the procedure by constructing the ACM of eight key decision makers about an enterprise system adoption decision.