Bridging the innovation gap: An AI and game-theoretic framework for optimizing angel investor-startup matching
Shanghai Jiao Tong University Journal CenterThis paper introduces a novel methodology for analysing and optimising the matching process between angel investors and startup companies by integrating artificial intelligence (AI) and game-theoretic models. Leveraging the natural language processing capabilities of AI engines such as Gemini and ChatGPT 4, we extract and analyse historical investment patterns to identify critical qualitative and quantitative criteria influencing investment decisions. These criteria are further refined through R programming simulations, optimising cutoff values using the Youden index to balance sensitivity and specificity in predicting successful matches. Our findings demonstrate the effectiveness of a hybrid framework that combines qualitative preferences with quantitative metrics, offering a comprehensive tool for enhancing strategic investment decisions. This study represents the first attempt to apply AI technologies systematically to the investor-startup matching process, contributing practical insights for investors, entrepreneurs, and intermediaries in navigating the early-stage investment landscape. The proposed approach not only improves matching efficiency but also supports the creation of stronger, more aligned partnerships within the entrepreneurial ecosystem.
- Journal
- China Finance Review International