异质网络如何影响公司的创新表现? 一个基于集群和分类的研究分析
Liping Zhang1,2, Hanhui Qiu1, Jinyi Chen1
1College of Business Administration, Huaqiao University, Quanzhou 362021, China.
Entropy (Basel, Switzerland)
|November 24, 2023
概括
企业可以通过战略管理合作来提高创新绩效. 工业-大学-研究 (IUR) 伙伴关系从多元化的合作伙伴中受益,而企业间 (IF) 合作则在深入参与高创新绩效方面壮成长.
科学领域:
- 人工智能的人工智能
- 创新管理 创新管理
- 网络分析 网络分析
背景情况:
- 中国的人工智能专利格局 (2013-2022) 为分析合作提供了丰富的数据集.
- 了解企业层面的创新驱动因素对于竞争优势至关重要.
研究的目的:
- 在中国人工智能领域构建和分析工业-大学-研究 (IUR) 和企业间 (IF) 合作网络.
- 调查网络特征对企业创新绩效的非线性影响.
- 确定不同类型的焦点公司及其最佳合作策略.
主要方法:
- 来自中国人工智能行业的专利数据分析 (2013-2022年).
- 计算创新绩效 (专利数量和质量) 的透权重方法.
- 阶层聚类和分类和回归树 (CART) 算法用于机制分析.
主要成果:
- 根据网络中心性,结构性漏洞,协作广度和深度,确定了两种类型的焦点公司.
- 影响创新绩效的网络特征在不同焦点公司类型之间有很大差异.
- 在IUR网络中,通过广泛的,异质的伙伴关系,在IF网络中通过深入的协作实现了高创新绩效.
结论:
- 企业应该根据其网络位置和类型量身定制合作策略.
- 政策制定者可以利用这些发现来促进更有效的创新生态系统.
- 该研究提供了可操作的见解,通过战略网络管理来加强企业层面的创新.
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