A Social Network Analysis on Venture Capital Alliance’s Exit from an Emerging Market
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This study investigated the impacts of network structure on a venture capital (VC) alliance’s successful exit from an emerging market by empirically analyzing joint VC data in China.
We find that, compared to a mature capital market, the mechanism not only has a certain commonality but also shows the emerging market’s particularities.
From the commonality perspective, the mechanism has a positive effect on successful exit by obtaining heterogeneity information.
These particularities are manifested in the following three aspects.
First, the mechanism is not conducive to deepening the enterprise value chain to establish credibility by obtaining short-term cash during an initial public offering with the enhancement of the VC alliance’s intervention ability for enterprise development.
In addition, a VC alliance’s independent judgment is bound by the VC market.
Furthermore, the problem of over-trust in investees reduces the likelihood of a VC alliance’s successful exit.
Therefore, we should pay more attention to the particularity of emerging markets such as China to improve the relevant management mechanism.
American Psychological Association (APA)
Wu, Jing& Luo, Chuan& Liu, Ling. 2020. A Social Network Analysis on Venture Capital Alliance’s Exit from an Emerging Market. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1142032
Modern Language Association (MLA)
Wu, Jing…[et al.]. A Social Network Analysis on Venture Capital Alliance’s Exit from an Emerging Market. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1142032
American Medical Association (AMA)
Wu, Jing& Luo, Chuan& Liu, Ling. A Social Network Analysis on Venture Capital Alliance’s Exit from an Emerging Market. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1142032
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142032