Theory and Methodology A Bayesian network approach to making inferences in causal maps

The main goal of this paper is to describe a new graphical structure called ÔBayesian causal mapsÕ to represent and analyze domain knowledge of experts. A Bayesian causal map is a causal map, i.e., a network-based representation of an expertÕs cognition. It is also a Bayesian network, i.e., a graphical representation of an expertÕs knowledge based on probability theory. Bayesian causal maps enhance the capabilities of causal maps in many ways. We describe how the textual analysis procedure for constructing causal maps can be modi®ed to construct Bayesian causal maps, and we illustrate it using a causal map of a marketing expert in the context of a product development decision. Ó 2001 Elsevier Science B.V. All rights reserved.