Publication Type
Journal Article
Version
publishedVersion
Publication Date
12-2010
Abstract
Using meta-analysis, we find a consistent positive correlation between emotion recognition accuracy (ERA) and goal-oriented performance. However, this existing research relies primarily on subjective perceptions of performance. The current study tested the impact of ERA on objective performance in a mixed-motive buyer-seller negotiation exercise. Greater recognition of posed facial expressions predicted better objective outcomes for participants from Singapore playing the role of seller, both in terms of creating value and claiming a greater share for themselves. The present study is distinct from past research on the effects of individual differences on negotiation outcomes in that it uses a performance-based test rather than self-reported measure. These results add to evidence for the predictive validity of emotion recognition measures on practical outcomes.
Keywords
Emotion recognition, Accuracy, Decoding, Negotiation, Workplace, Performance, Emotional intelligence
Discipline
Industrial and Organizational Psychology | Organizational Behavior and Theory
Research Areas
Organisational Behaviour and Human Resources
Publication
Journal of Nonverbal Behavior
Volume
31
Issue
4
First Page
205
Last Page
224
ISSN
0191-5886
Identifier
10.1007/s10919-007-0033-7
Publisher
Springer
Citation
ELFERBEIN, Hillary Anger; FOO, Maw Der; WHITE, Judith; TAN, Hwee Hoon; and AIK, Voon Chuan.
Reading Your Counterpart: The Benefit of Emotion Recognition Accuracy for Effectiveness in Negotiation. (2010). Journal of Nonverbal Behavior. 31, (4), 205-224.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/2515
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10919-007-0033-7
Included in
Industrial and Organizational Psychology Commons, Organizational Behavior and Theory Commons