How Groups Differ from Individuals in Learning from Experience: Evidence from a Contest Platform

We examine how groups differ from individuals in how they tackle two fundamental trade-offs in learning from experience—namely, between exploration and exploitation and between over- and undergeneralization from noisy data (which is also known as the “bias-variance” trade-off in the machine learning...

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Veröffentlicht in:	Organization science (Providence, R.I.) R.I.), 2024-07, Vol.35 (4), p.1512-1534
1. Verfasser:	He, Tianyu
Format:	Artikel
Sprache:	eng
Schlagworte:	aggregation Alternatives Educational objectives Experiential learning Exploitation group learning Groups groups versus individuals learning-by-doing cycle organizational learning teams
Online-Zugang:	Volltext
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