Evolutionary game model of intellectual property pledge financing between technology-based SMEs and banks based on the EVCC - Li-na Dong; Mu Zhang (PLoS ONE, 2025)
This study aims to improve the market efficiency of intellectual property pledge financing, based on the perspective of willingness to perform of technology-based SMEs, this paper defined the end-of-period value conversion coefficient of pledged property (EVCC) to measure the comparative relationship between the end-of-period value of the pledged intellectual property and the sum of principal and interest of the loan and introduced it into the game payment matrix; using evolutionary game theory, based on the assumption of bounded rationality, an evolutionary game model of intellectual property pledge financing between technology-based SMEs and banks based on the EVCC was constructed, and a numerical simulation was then conducted. The results of asymptotic stability analysis showed that when a certain condition is met, the strategy combination (performance, loan) is the evolutionary stability strategy (ESS). The numerical simulation showed that the EVCC has a positive impact on the speed of technology-based SMEs choosing the performance strategy, and there is a positive threshold effect (The threshold is 0.90). The initial value of pledged intellectual property has a negative impact on the speed of technology-based SMEs choosing the performance strategy, and there is a reverse threshold effect (The threshold is 1250), as well as the pledge rate of intellectual property (The threshold is 0.375). However, the loan interest rate has no significant impact on the strategic choice of technology-based SMEs. In addition, the EVCC has no significant impact on the banks’ strategy choice. The initial value of pledged intellectual property has a negative impact on the speed of banks choosing loan strategies, and there is a reverse threshold effect (The threshold is 1250). The pledge rate of intellectual property has an inverted U-shaped impact on the speed of banks choosing loan strategies (ω* may be close to 0.30), and there is a reverse threshold effect (The threshold is 0.375). The loan interest rate has a positive impact on the speed of banks choosing loan strategies, and there is a positive threshold effect (The threshold is 0.03). In addition, the trustworthy joint incentive not only has a positive impact on the speed of technology-based SMEs choosing the performance strategy, but also has a positive impact on the speed of banks choosing the loan strategy, and both have a positive threshold effect (The threshold for both is 15), as well as the dishonesty joint punishment (The threshold for both is 85). This model enriches the multi-agent game theory framework of intellectual property pledge financing. The numerical simulation results can provide a decision-making reference for technology-based SMEs and banks to formulate intellectual property pledge financing strategies.