Novel idea generation in social networks is optimized by exposure to a "Goldilocks" level of idea-variability.
PNAS Nexus
; 1(5): pgac255, 2022 Nov.
Article
en En
| MEDLINE
| ID: mdl-36712363
ABSTRACT
Recent works suggest that striking a balance between maximizing idea stimulation and minimizing idea redundancy can elevate novel idea generation performances in self-organizing social networks. We explore whether dispersing the visibility of high-performing idea generators can help achieve such a trade-off. We employ popularity signals (follower counts) of participants as an external source of variation in network structures, which we control across four conditions in a randomized setting. We observe that popularity signals influence inspiration-seeking ties, partly by biasing people's perception of their peers' novel idea-generation performances. Networks that partially disperse the top ideators' visibility using this external signal show reduced idea redundancy and elevated idea-generation performances. However, extreme dispersal leads to inferior performances by narrowing the range of idea stimulation. Our work holds future-of-work implications for elevating idea generation performances of people.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Clinical_trials
Idioma:
En
Revista:
PNAS Nexus
Año:
2022
Tipo del documento:
Article
País de afiliación:
Estados Unidos