创造力
提名
心理学
过程(计算)
社会心理学
计算机科学
政治学
法学
操作系统
作者
Spencer Harrison,Noah Askin,Lydia Paine Hagtvedt
标识
DOI:10.1177/00018392221136158
摘要
Many organizations rely on group work to generate creativity, but existing research lacks theory on how groups’ responses to recognition for creative achievement shape their subsequent creative outcomes. Through an inductive study of bands nominated for a Best New Artist Grammy from 1980 to 1990, we develop a theory of reactions to early recognition in creative groups. Our multi-method analyses include oral histories from members of each band and quantitative data, which we use to triangulate the processes they describe. Our findings reveal that groups developed sets of emergent reactions and active adjustments to the recognition and its consequences, which we call “recognition orientations.” We identify three such orientations—absorbing, insulating, and mixed—that reflect how groups interpret recognition and integrate it into their subsequent processes. Most groups struggled by absorbing recognition, which led to internalizing expectations and opening their relationships to outsiders, ultimately inhibiting creativity. Some groups began to insulate themselves from recognition by externalizing expectations and bounding relationships, allowing them to sustain creative output over time. Finally, other groups developed a mixed orientation, initially experiencing the pitfalls of elevated recognition-seeking but ultimately attempting to insulate their need for external recognition by refocusing on their creative process. These findings reveal that recognition can upend the creative process, and groups that begin absorbing recognition are, ironically, less likely to earn it again in the future. Filling a critical research gap on creative production among groups that intend to continue working together, the results distinguish the skills needed to manage recognition from those needed to generate creativity, and offer insight into how groups enact longevity.
科研通智能强力驱动
Strongly Powered by AbleSci AI