Cluster Features and Driving Factors of Distance of Technology Convergence: ——An Empirical Study Based on Large-scale Patent Data

Abstract

Abstract:

In the era of industry 4.0, long-term economic growth relies on converging emerging information technologies with technologies in other areas. However, cross-boundary and distant technology convergence faces great risk and challenges. Based on 1985-2014 patent data in the IT, automobile, and equipment manufacturing sectors, this paper uses cluster analysis to reveal the cluster features of the development of distance of technology convergence, and studies the driving factors for distant technology convergence based on Tobit model. The results indicate that the development of distance of technology convergence exhibits multiple and differentiated cluster features; size of assignee teams, industry-university collaboration, patent stock, and governmental S&T funding stimulate the distance of technology convergence; size of inventor teams first enhances and then constrains the distance of technology convergence. Thus, our suggestion is that the relevant policies should encourage collaboration and prioritize technological areas with rich patent accumulation, and develop a S&T funding portfolio with multiple converging technological areas.

Key words: distance of technology convergence, cluster features, driving factors, Tobit model

Feng Ke, Zeng Deming. Cluster Features and Driving Factors of Distance of Technology Convergence: ——An Empirical Study Based on Large-scale Patent Data[J]. , 2019, 31(8): 97-109.

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