社会资本影响了研发效率 —基于中国省际面板数据的经验研究

科研管理 ›› 2013, Vol. 34 ›› Issue (5): 73-79,110.

社会资本影响了研发效率 —基于中国省际面板数据的经验研究

史欣向¹, 梁彤缨²

1. 中山大学管理学院, 广东广州 510275;
2. 华南理工大学工商管理学院, 广东广州 510641

收稿日期:2011-08-04 修回日期:2012-01-09 出版日期:2013-05-27 发布日期:2013-05-20
基金资助:
教育部人文社会科学研究项目,项目编号(11YJA630053),起止时间(2011-2014年);广东省软科学项目,项目编号(2010B070300022),起止时间(2010-2011年)。

Does social capital affect R&D efficiency—An empirical study based on the provincial panel data from in China

Shi Xinxiang¹, Liang Tongying²

1. School of Business, Sun Yat-Sen University, Guangzhou 510275, China;
2. School of Business Administration, South China University of Technology, Guangzhou 510641, China

Received:2011-08-04 Revised:2012-01-09 Online:2013-05-27 Published:2013-05-20

摘要/Abstract

摘要： 本文利用中国省际区域面板数据研究了社会资本对研发效率的影响。首先从构成社会资本的单个要素出发,分别考察了信任、规范、社会网络对研发效率的影响。研究结果表明,"信任"对研发的中间产出效率、"规范"对研发的最终产出效率具有显著的正向影响,而"社会网络"无论对研发的中间产出效率还是对最终产出效率的影响均不显著。随后,通过因子分析将各单个要素凝练成为社会资本变量,并以此探讨了社会资本与研发效率的关系,发现社会资本对研发的中间产出效率和最终产出效率均具有显著的正向作用。

关键词: 社会资本, 研发效率, 随机前沿模型

Abstract: The relation between social capital and R&D efficiency is explored by using the panel data from provinces in China. Firstly, the effect of three factors constituting social capital on R&D efficiency is respectively analyzed. The results suggest that trusts plays a positive role in the intermediate output efficiency of R&D and norms do same thing to the ultimate output efficiency of R&D, meanwhile social networks have insignificant effect on either output efficiencies of R&D. Then, the relationship between R&D efficiency and social capital which is integrated from trusts, norms, and networks is studied by using factor analysis approach. It is found that social capital has significantly positive influence both on the intermediate and ultimate output efficiencies of R&D.

Key words: social capital, R&D efficiency, stochastic frontier model

中图分类号:

F270.3

史欣向, 梁彤缨. 社会资本影响了研发效率 —基于中国省际面板数据的经验研究[J]. 科研管理, 2013, 34(5): 73-79,110.

Shi Xinxiang, Liang Tongying. Does social capital affect R&D efficiency—An empirical study based on the provincial panel data from in China[J]. Science Research Management, 2013, 34(5): 73-79,110.

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