The evolution of k-shell in syndication networks reveals financial performance of venture capital institutions

IF 2.9 2区 社会学 Q1 ANTHROPOLOGY
Ruiqi Li , Jing Liang , Cheng Cheng , Xiaoyan Zhang , Longfeng Zhao , Chen Zhao , H. Eugene Stanley
{"title":"The evolution of k-shell in syndication networks reveals financial performance of venture capital institutions","authors":"Ruiqi Li ,&nbsp;Jing Liang ,&nbsp;Cheng Cheng ,&nbsp;Xiaoyan Zhang ,&nbsp;Longfeng Zhao ,&nbsp;Chen Zhao ,&nbsp;H. Eugene Stanley","doi":"10.1016/j.socnet.2023.09.006","DOIUrl":null,"url":null,"abstract":"<div><p>Venture capital (VC) is a relatively newly emergent industry that is still subject to large uncertainties in China. Therefore, building a robust social network with other VC institutions is a good way to share information, various resources, and benefit from skill and knowledge complementarity to against risks. Strong evidences indicate that better networked VC institutions are of a better financial performance, however, most of previous works overlook the evolution of VC institutions and only focus on some simple topology indicators of the static syndication network, which also neglects higher-order network structure and cannot give a comprehensive evaluation. In this paper, based on VC investment records in the Chinese market, we construct temporal syndication networks between VC institutions year by year. As k-shell decomposition considers higher-order connection patterns, we employ k-shell as an evaluation of the influence of VC institutions in syndication networks. By clustering time series of k-shell values, the VC institutions in China fall into five groups that are quite different from each other on financial performances and investment behaviors. This, in turn, proves the power of our method that only based on proper sequential network properties, we can reveal their financial investment performance. Compared to other network centrality measurements, k-shell is a better indicator that is indicated by a smaller intra-group distance and a larger inter-group distance.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"76 ","pages":"Pages 191-202"},"PeriodicalIF":2.9000,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Networks","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378873323000655","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
引用次数: 1

Abstract

Venture capital (VC) is a relatively newly emergent industry that is still subject to large uncertainties in China. Therefore, building a robust social network with other VC institutions is a good way to share information, various resources, and benefit from skill and knowledge complementarity to against risks. Strong evidences indicate that better networked VC institutions are of a better financial performance, however, most of previous works overlook the evolution of VC institutions and only focus on some simple topology indicators of the static syndication network, which also neglects higher-order network structure and cannot give a comprehensive evaluation. In this paper, based on VC investment records in the Chinese market, we construct temporal syndication networks between VC institutions year by year. As k-shell decomposition considers higher-order connection patterns, we employ k-shell as an evaluation of the influence of VC institutions in syndication networks. By clustering time series of k-shell values, the VC institutions in China fall into five groups that are quite different from each other on financial performances and investment behaviors. This, in turn, proves the power of our method that only based on proper sequential network properties, we can reveal their financial investment performance. Compared to other network centrality measurements, k-shell is a better indicator that is indicated by a smaller intra-group distance and a larger inter-group distance.

联合网络中k-shell的演化揭示了风险投资机构的财务绩效
风险投资是一个相对新兴的行业,在中国仍存在很大的不确定性。因此,与其他风险投资机构建立一个强大的社交网络是共享信息、各种资源、从技能和知识互补中获益以抵御风险的好方法。强有力的证据表明,网络化程度越高的风险投资机构财务绩效越好,但以往的研究大多忽视了风险投资机构的演变,只关注静态联合网络的一些简单拓扑指标,也忽视了高阶网络结构,无法对其进行综合评价。在本文中,基于中国市场上的风险投资记录,我们逐年构建风险投资机构之间的时间联合网络。由于k-shell分解考虑了高阶连接模式,我们使用k-shell来评估VC机构在联合网络中的影响。通过对k壳价值的时间序列进行聚类,将中国风险投资机构分为五组,它们在财务表现和投资行为上存在很大差异。这反过来证明了我们的方法的强大性,即只有基于适当的顺序网络属性,我们才能揭示它们的财务投资性能。与其他网络中心性测量相比,k-shell是一个更好的指标,它由较小的组内距离和较大的组间距离来指示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Social Networks
Social Networks Multiple-
CiteScore
5.90
自引率
12.90%
发文量
118
期刊介绍: Social Networks is an interdisciplinary and international quarterly. It provides a common forum for representatives of anthropology, sociology, history, social psychology, political science, human geography, biology, economics, communications science and other disciplines who share an interest in the study of the empirical structure of social relations and associations that may be expressed in network form. It publishes both theoretical and substantive papers. Critical reviews of major theoretical or methodological approaches using the notion of networks in the analysis of social behaviour are also included, as are reviews of recent books dealing with social networks and social structure.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信