技术融合距离的聚类特征与影响因素——基于大规模专利数据的实证研究

›› 2019, Vol. 31 ›› Issue (8): 97-109.

技术融合距离的聚类特征与影响因素——基于大规模专利数据的实证研究

冯科, 曾德明

湖南大学工商管理学院, 长沙 410082

收稿日期:2019-02-21 出版日期:2019-08-28 发布日期:2019-09-11
通讯作者: 冯科(通讯作者),湖南大学工商管理学院助理教授,硕士生导师,博士
作者简介:曾德明,湖南大学工商管理学院教授,博士生导师,博士。
基金资助:
国家自然科学基金项目（71603080; 71472061;71602046）；湖南省自然科学基金项目（2015JJ4016）；湖南大学“中央高校基本科研业务费专项资金” 项目资助。

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

Feng Ke, Zeng Deming

School of Business Administration, Hunan University, Changsha 410082

Received:2019-02-21 Online:2019-08-28 Published:2019-09-11

摘要/Abstract

摘要：

建设工业4.0需要推动新兴信息技术与其他领域技术的深度融合。然而跨领域、远距离的技术融合面临较大的风险与挑战。采用电子信息、汽车、装备制造产业1985-2014年约240万专利数据，以三大产业中的技术领域为研究对象，基于聚类分析研究其技术融合距离动态发展过程中的聚类特征，利用Tobit模型解析其技术融合距离的影响因素。实证研究表明，融合距离最远的技术领域，其动态发展过程表现出多元化、差异化的聚类特征；申请人合作团队规模、产学合作、专利积累、政府科技计划投入显著促进技术融合距离的延伸；发明人团队规模则对技术融合距离先提升、后抑制。应鼓励合作创新、优先关注前期积累丰富的技术领域、构建多目标结合的融合性技术领域财政资金投入组合。

关键词: 技术融合距离, 聚类特征, 影响因素, Tobit模型

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

冯科, 曾德明. 技术融合距离的聚类特征与影响因素——基于大规模专利数据的实证研究[J]. , 2019, 31(8): 97-109.

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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