我国风险投资机构网络社群:结构识别、动态演变与偏好特征研究

摘要/Abstract

摘要：

本文从我国资本市场上出现的风险投资"抱团"现象入手,以CVSource数据库为数据基础,应用模块性指标G-N算法,动态识别了我国风险投资机构网络社群结构,进而探讨了社群结构的稳定性,最后基于网络社群特征分析,对社群成员身份的稳定性和风险投资机构间偏好特征进行了研究。结果表明,社群现象在我国风险投资网络中广泛存在,且趋势愈发显著;风险投资网络社群结构的变动具有延续性与稳定性;我国风险投资机构网络社群特征所呈现出机构间相互偏好在投资行业特征方面倾向于同质,而在投资阶段和投资项目的地理分布特征方面倾向于异质。本文对风险投资网络社群的分析,有助于从网络社群层次探讨风险投资机构的投资行为,为深入分析联合风险投资的网络行为提供了新的视角。

关键词: 风险投资, 网络社群结构, 稳定性, 偏好特征

Abstract:

Starting with the analysis of the "clustering" phenomenon of venture investments in China's capital markets, this paper, based on the CVSource database, dynamically detects the structure of china's VC network communities with the Girvan-Newman algorithm, and discusses the structure stability. Finally, it studies the stability of the community status of VCs and the characteristics of preference between venture capital institutions. The results show that the community phenomenon is widespread and increasingly significant in China's VC network. The structure of China's VC network communities changes continuously and stably. The characteristics of China's VC network communities indicate institutions prefer partners that are heterogeneous in investment industry feature but homogeneous in investment stage and geographical distribution features. The analyses of VC network Communities contribute to study of VCs investment behavior at the network communities level, and offer an interesting new angle to look further into VC's network behavior.

Key words: venture capital, network communities structure, stability, preference features

罗吉, 党兴华. 我国风险投资机构网络社群:结构识别、动态演变与偏好特征研究[J]. , 2016, 28(5): 61-72.

Luo Ji, Dang Xinghua. Study on China's VC Network Communities: Structure Recognition, Dynamic Evolution and Preference Features[J]. , 2016, 28(5): 61-72.

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