Confidence in aggregation of expert opinions

We investigate the case of a single decision maker (DM) who obtains probabi listic forecasts regarding the occurrence of a unique target event from J d istinct, symmetric, and equally diagnostic expert advisors (judges). The pa per begins with a mathematical model of DM's aggregation process of expert opinions, in which confidence in the final aggregate is shown to be inverse ly related to its perceived variance. As such, confidence is expected to va ry as a function of factors such as the number of experts, the total number of cues, the fraction of cues available to each expert, the level of inter -expert overlap in information, and the range of experts' opinions. In the second part of the paper, we present results from two experiments that supp ort the main (ordinal) predictions of the model. (C) 2000 Elsevier Science B.V. All rights reserved. PsycINFO classification: 2340, 3650.