在组织间学习中,合作者应该有多么相似:最佳的认知接近和知识复杂性.
Yeokyung Hwang1,2, Junseok Hwang1,2, Junmin Lee3
1Technology Management, Economics, and Policy Program, Seoul National University, Seoul, South Korea.
PloS one
|December 19, 2025
概括
知识的复杂性对协作创新有不同的影响. 高复杂性有利于更多的合作伙伴获得量,但通过削弱近距离和创新成果之间的联系来阻碍质量.
科学领域:
- 创新研究 研究 创新研究
- 组织行为 组织行为
- 知识产权管理知识产权管理
背景情况:
- 有效的知识交流对于知识密集型行业的创新至关重要.
- 认知接近与协作创新之间的相互作用,特别是在复杂的知识环境中,需要进一步研究.
- 现有的研究表明,认知接近与创新之间存在非线性,反向的U形关系,但知识复杂性的调节作用尚不清楚.
研究的目的:
- 检查知识复杂性如何调节认知接近与协作创新之间的关系.
- 为了区分对协作数量与协作质量的影响.
- 在复杂的创新生态系统中提供对合作伙伴选择策略的见解.
主要方法:
- 分析了来自57,000多个组织的65万多项美国生物技术专利 (1976-2024年).
- 使用基于CPC的Jaccard相似性的认知接近度的测量.
- 通过基于知识组合网络的结构复杂性框架来运行知识复杂性.
- 应用负二项式回归来分析数据.
主要成果:
- 知识的复杂性调节了近距离与创新的关系,不同于协作量和质量.
- 对于协作量,增加的复杂性将最佳近距离向右移动,并使反转的U曲线变得平坦.
- 对于协作质量,高复杂性会导致向左移动和近水平关系,表明曲线效应的分解.
结论:
- 认知接近通过不同的机制影响合作伙伴选择和创新实现,特别是在高度知识复杂的情况下.
- 吸收能力仍然是伙伴关系决策的关键,但随着复杂性增加,新产品与接近效应断开了联系.
- 知识的复杂性起到结构调节者的作用,完善了近距离理论,并为高级创新的战略合作伙伴选择提供了信息.
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