Wright, George and Rowe, Gene. (2011) Group-based judgmental forecasting : an integration of extant knowledge and the development of priorities for a new research agenda. International Journal of Forecasting, 27 (1). pp. 1-13. ISSN 0169-2070

Abstract

We review and integrate the extant knowledge on group-based forecasting, paying particular attention to the papers included in this special issue of the International Journal of Forecasting. We focus on the relative merits of different methods of aggregating individual forecasts, the advantages of heterogeneity in group memberships, the impact of others’ opinions on group members, and the importance of perceptions of trust. We conclude that a change of opinion following group-based deliberation is most likely to be appropriate where the group membership is heterogeneous, the minority opinion is protected from pressure to conform, information exchange between group members has been facilitated, and the recipient of the advice is able — by reasoning processes — to evaluate the reasoning justifying the proffered advice. Proffered advice is least likely to be accepted where the advisor is not trusted — an evaluation which is based on the advisor having different perceived values to the recipient and being thought to be self-interested. In contrast, the outcome of a group-based deliberation is most likely to be accepted when there is perceived to be procedural fairness and the participants in the process are perceived to be trustworthy. Finally, we broaden our discussion of group-based forecasting to include a consideration of other group-based methodologies which are aimed at enhancing judgment and decision making. In particular, we discuss the relevance of research on small-group decision making, the nature and quality of the advice, group-based scenario planning, and public engagement processes. From this analysis, we conclude that, for medium- to long-term judgemental forecasting, a variety of non-outcome criteria need to be considered in the evaluation of alternative group-based methods.

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