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When Does External Knowledge Benefit Team Creativity? The Role of Internal Team Network Structure and Task Complexity

知识管理 创造力 团队构成 任务(项目管理) 知识整合 过程(计算) 团队效能 样品(材料) 多样性(控制论) 计算机科学 突出 业务 心理学 领域知识 工程类 社会心理学 人工智能 化学 操作系统 系统工程 色谱法
作者
Vijaya Venkataramani,Chaoying Tang
出处
期刊:Organization Science [Institute for Operations Research and the Management Sciences]
卷期号:35 (1): 92-115 被引量:43
标识
DOI:10.1287/orsc.2023.1661
摘要

Creativity in teams is spurred by members’ access to diverse knowledge, often from interactions with external sources. However, not all teams that have the capabilities to acquire such external knowledge are equally creative. Integrating theories of absorptive capacity and creative synthesis in teams, we propose that teams’ external knowledge acquisition capabilities in securing a wide variety of knowledge resources need to be complemented by internal knowledge integration capabilities that facilitate balanced/equal participation of all team members in the creative problem-solving process. In turn, this combination enables effective information elaboration processes underlying the generation of truly creative team outcomes. We test these ideas in two field studies. First, in a sample of 81 research and development teams in three organizations in science and technology fields, we find that teams’ connections with a wide range of external parties—indicating their external knowledge acquisition capability—benefit their creativity, but only when the team’s internal team member problem-solving network structure—an indicator of the team’s knowledge integration capability—is less centralized (i.e., not controlled by one or few members). We further demonstrate that these effects are more salient when the team’s task is more complex. Replicating these findings in a second sample of 57 project teams in an energy manufacturing and services firm, we show that these effects are mediated by the team’s information elaboration processes. Theoretical and practical implications are discussed. Funding: This research was supported by grants received by C. Tang and her colleagues at UCAS, from the National Natural Science Foundation of China [Projects 71974178, 71932009], MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation at UCAS, and the Fundamental Research Funds for the Central Universities [Project E2E40806X2]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.1661 .
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