In the global venture capital (VC) landscape, cross-community collaboration is vital for foreign VC firms, especially in markets like China, where the business environment and the guanxi culture present unique challenges. Using co-investment data from 2000 to 2014, this study identifies seven communities through a semi-supervised detection method, categorizing them by the predominance of domestic or foreign VCs. Cross-community collaboration refers to partnerships between VC firms from different communities, involving at least one domestic and one foreign VC. Logistic regression analysis reveals that industry distance does not significantly impact cross-community collaboration. However, industry hotness and local knowledge positively moderate this relationship. In the Chinese context, signaling theory suggests that cross-community collaborations between foreign and domestic VCs act as a signal of credibility. Guanxi, characterized by trust and reciprocity, encourages foreign VCs to foster long-term relationships with domestic counterparts, helping them bridge industrial and cultural gaps. Additionally, industry hotness and local experience reduce investment risk and uncertainty, leading foreign VCs to engage more frequently in cross-community collaborations that link domestic and foreign ecosystems. This study integrates signaling theory with guanxi in the cross-community VC context, emphasizing the strategic role of syndication as a signal in emerging markets like China.

Existing research suggests that elite clubs exist in venture capital markets, but a standard for determining their size and composition is lacking. This paper addresses this challenge by using the weighted k-means sorting algorithm to construct a research framework for elite clubs. Validating the framework with investment events data from China’s venture capital market (2001–2018), intriguing findings emerge. The ranking of Venture Capitalists (VCs) follows a power-law distribution, providing evidence for elite clubs’ existence. The analysis identifies a turning point in the score curve, serving as a valuable indicator for club boundaries. Elite clubs demonstrate relatively high stability, maintaining advantages and elite status in future competitions. Empirical validation confirms the proposed framework’s superior stability compared to existing methods. Importantly, elite club members outperform non-elites significantly. This paper effectively identifies elite clubs in the Chinese venture capital market, helping other VCs recognize potential partners, access high-quality information, and enhance investment performance.