Abstract

Public technology innovation procurement plays an essential role in alleviating current major social challenges. In the process of government procurement, the hidden adverse selection and moral hazard caused by the unobservable technology types and efforts of enterprises are not conducive to the sustainable improvement of technology innovation quality. To sustainably encourage enterprises to improve the quality of public technology innovation procurement, based on principal-agent and incentive regulation theories, this paper designs quality-incentive contracts under single- and dual-asymmetric information conditions. We discuss the impact of various relevant factors on contract design and the level of effort by solving and analyzing the model. Furthermore, we validate the effects of the proportion of enterprise technological type, the uncertainty of technological innovation, and the quality-benefit coefficient on the contract parameters and the expected profits of both parties through numerical simulation. The results show that under dual-asymmetry information, the government can motivate enterprises to realize self-selection and improve the quality of technological innovation by designing information screening contracts. The government’s revenue is closely related to the proportion of enterprises’ technology types in the market, and information rents can swamp the government’s expected revenues when the market proportion of high-type enterprises is small. The uncertainty of technological innovation will reduce the effort of enterprises and the incentive effect of the contract. The quality-benefit coefficients of the government and enterprises have different impacts on the intensity of contract incentives with higher quality-benefit coefficients of the government, therefore having better incentive effects for enterprises. The research conclusion provides a reference for the government to design a sustainable incentive contract to improve the quality of public technology innovation.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call