Using weighted k-means to identify Chinese leading venture capital firms incorporating with centrality measures |
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| Affiliation: | 1. School of Information, Central University of Finance and Economics, Beijing, China;2. Department of Sociology, Tsinghua University, Beijing, China;3. School of Systems Science, Beijing Normal University, Beijing, China;4. National School of Development, Peking University, Beijing, China;1. State Key Lab of Mathematical Engineering and Advanced Computing, 450001 China;2. School of Cyber Science and Engineering,Wuhan University, 430079 China;3. Zhengzhou University of Light Industry, 450002, China;1. School of Mathematical Sciences, University of Adelaide, SA 5005, Australia;2. ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Australia;3. Data to Decisions Cooperative Research Centre (D2D CRC), Kent Town, SA 5067, Australia;4. D2D CRC stream lead, Australia;1. University of Waterloo, Canada;2. Ted Rogers School of Management, Ryerson University, Canada;3. Ontario Tech University, Canada |
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| Abstract: | Although identifying leading venture capital firms (VCs) is a meaningful challenge in the analysis of the Chinese investment market, this research topic is rarely mentioned in the relevant literature. Given the co-investment network of VCs, identifying leading VCs is equal to determine influential nodes in the field of complex network analysis. As there are some disadvantages and limitations of using single centrality measures and the multiple criteria decision analysis (MCDA) method to identify leading VCs, this paper incorporates with several different centrality measures of co-investment network of VCs, and then proposes a new approach based on the weighted k-means to rank VCs at both group and individual levels and identify the leading VCs. The proposed approach not only shows alternative groupings based on multiple evaluation criteria, but also ranks them according to their comprehensive score which is the weighted sum of these criteria. Empirical analysis shows the efficiency and practicability of the proposed approach to identify leading Chinese VCs. |
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