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Individual and group advice taking in judgmental forecasting: Is group forecasting superior to individual forecasting?
Author(s) -
Kim Hyo Young,
Lee Yun Shin,
Jun Duk Bin
Publication year - 2020
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.2158
Subject(s) - advice (programming) , quality (philosophy) , psychology , social psychology , applied psychology , computer science , philosophy , epistemology , programming language
We examined how individuals and groups behave in making judgmental forecasts when they are given external forecast advice. We compare individual and group advice‐taking behavior under different conditions: (a) when advice quality is fixed, (b) when advice quality is randomly varied, and (c) when there is feedback on advice quality or not. Participants in Study 1 received fixed advice of either reasonable or unreasonable quality while making their decisions. Participants in Study 2 randomly received both reasonable and unreasonable advice. We found in both studies that groups feel more confident than individuals. This greater confidence decreased the groups' reliance on advice. We also found that groups are better than individuals at discerning the quality of advice. In the group treatment, the group's reliance on advice increased according to the degree of disagreement with the initial decisions of the group members. In Study 3, participants randomly received both reasonable and unreasonable advice, and in addition, they received feedback on actual realizations that enabled them to learn about the quality of advice. In the presence of feedback on random advice quality, groups are no longer less receptive to advice than individuals; with feedback, both individuals and groups discount advice more than they do without feedback. Nevertheless, groups are still better than individuals at discerning the quality of advice. We conclude that group forecasting is better than individual forecasting across various conditions that we investigate except when advice quality is known to be consistently reliable.