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| Research on Interaction Mechanism Between Collaborative Innovation and Surprise Innovation in High-Tech Enterprises |
| Yu Liping1, Zhong Changbiao2, Wang Anran3 , Lin Qiangwen4 |
1. School of Statistics and Mathematics,Zhejiang Gongshang University,Hangzhou 310018,China;
2. Business School,Yunnan University of Finance and Economics,Kunming 650221,China;
3. International Business School,Xi'an Jiaotong-Liverpool University,Suzhou 215123,China;
4. Scientific Bureau,Guangzhou College of Commerce,Guangzhou 511363,China |
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Abstract Government innovation policy includes direct and indirect innovation policy.It is of great significance to evaluate direct and indirect innovation policy and compare their performance.This paper introduces the technical progress variable in the macroscopic knowledge production function.After removing the impact of technological progress from total factor productivity,total factor productivity can represent innovation policy.Then the innovation policy data is standardized and used to subtract the direct innovation policy and thus indirect innovation policy is obtained.In this paper,the mechanism of direct and indirect policy is analyzed.The panel data model,panel threshold model and the Bayesian vector autoregressive model (BVAR) are synthetically used to study the performance of innovation policy and the interactive relationship between the variables.The results show the following.The measurement model of innovation policy is effective.The performance of indirect innovation policy is better than the performance of direct innovation policy.The elasticity of indirect innovation policy is directly proportional to the policy intensity,and has the threshold effect.The coordination capacity of direct and indirect innovation policy needs to be improved.The impact of innovation policy on innovation results has phase characteristics.The direct innovation policy can better promote enterprises to increase investment on R&D.
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Received: 31 May 2021
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2022, Vol. 3 
