Research Article
How to encourage Social Capital to invest on Sea-related Science and Technology Enterprises?--An Empirical Analysis Based on fsQCA Portfolio Model of China
@INPROCEEDINGS{10.4108/eai.29-3-2024.2347473, author={Ziyuan Fu and Hui Zheng}, title={How to encourage Social Capital to invest on Sea-related Science and Technology Enterprises?--An Empirical Analysis Based on fsQCA Portfolio Model of China}, proceedings={Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29--31, 2024, Wuhan, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2024}, month={6}, keywords={social capital; sea-related science and technology enterprises; fsqca; distributed cognition theory; perceived value theory}, doi={10.4108/eai.29-3-2024.2347473} }
- Ziyuan Fu
Hui Zheng
Year: 2024
How to encourage Social Capital to invest on Sea-related Science and Technology Enterprises?--An Empirical Analysis Based on fsQCA Portfolio Model of China
ICBBEM
EAI
DOI: 10.4108/eai.29-3-2024.2347473
Abstract
The innovation in marine science and technology is pivotal in driving the establishment of maritime power. Social capital involvement provides a crucial avenue for addressing financial challenges encountered by sea-related science and technology enterprises, marked by high investments, significant operational risks, and considerable return uncertainty. Leveraging Distributed Cognition Theory and Perceived Value Theory, this study constructs a theoretical framework to elucidate driving factors behind social capital investment in such enterprises. Subsequently, a fuzzy set qualitative comparative analysis model is employed to explore synergistic driving paths of diverse factors guiding social capital investment. Utilizing micro-survey data from Qingdao, a leading hub of marine science and technology in China, the analysis reveals that there are four equivalent synergistic paths motivating social capital investment. Private venture capital organizations predominantly lead the value-driven type, whereas government-guided type is primarily dominated by state-owned enterprises. These findings offer valuable insights for policymakers and technology entrepreneurs.