Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and measurement of regional science and technology innovation policy urgently require research attention.
In this paper, we use text mining and principal component analysis to analyze the classification and measurement of technology innovation policy based on data obtained from Zhongguancun Science Park.
The empirical results indicate that regional science and technology innovation policy can be divided into four types: authoritative, guiding, urgent and periodical. The key measurements are function type, intensity, resource supply, funding level and funding effectiveness.
A comparative analysis is performed to investigate the different types of regional science and technology innovation policy measurement. Additionally, the study’s limitations are discussed, and future research directions are proposed.
