TY - JOUR
T1 - Academia-industry collaboration, government funding and innovation efficiency in Chinese industrial enterprises
AU - Hou, Bojun
AU - Hong, Jin
AU - Wang, Hongying
AU - Zhou, Chongyang
PY - 2019
Y1 - 2019
N2 - This article uses a stochastic frontier model to elaborate how academia-industry research and development collaboration and government funding influence the innovation efficiency of industrial enterprises through a panel dataset from 2009 to 2015, including 30 provinces in China. We find that the research institute-industry collaboration promotes innovation efficiency of enterprises, while university-industry collaboration is adversely associated with innovation efficiency. Government funding plays a positive role on innovation efficiency across the board. Next, we divide the sample into three clusters according to enterprises’ innovation ability. In the first cluster, which has the least innovation ability, research institute-industry collaboration, university-industry collaboration and government funding have no significant effect on enterprise innovation efficiency. In the second and third clusters, university-industry collaboration exerts a negative impact on innovation efficiency but government funding improves innovation efficiency. At the same time, we investigate the interaction effects of enterprise R&D personnel and academia-industry collaboration and government funding on innovation efficiency. We find some heterogeneity in the full sample and the three sub-samples.
AB - This article uses a stochastic frontier model to elaborate how academia-industry research and development collaboration and government funding influence the innovation efficiency of industrial enterprises through a panel dataset from 2009 to 2015, including 30 provinces in China. We find that the research institute-industry collaboration promotes innovation efficiency of enterprises, while university-industry collaboration is adversely associated with innovation efficiency. Government funding plays a positive role on innovation efficiency across the board. Next, we divide the sample into three clusters according to enterprises’ innovation ability. In the first cluster, which has the least innovation ability, research institute-industry collaboration, university-industry collaboration and government funding have no significant effect on enterprise innovation efficiency. In the second and third clusters, university-industry collaboration exerts a negative impact on innovation efficiency but government funding improves innovation efficiency. At the same time, we investigate the interaction effects of enterprise R&D personnel and academia-industry collaboration and government funding on innovation efficiency. We find some heterogeneity in the full sample and the three sub-samples.
KW - Collaboration with universities
KW - collaboration with research institutes
KW - government funding
KW - innovation efficiency
UR - http://www.scopus.com/inward/record.url?scp=85057562178&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85057562178&origin=recordpage
U2 - 10.1080/09537325.2018.1543868
DO - 10.1080/09537325.2018.1543868
M3 - RGC 21 - Publication in refereed journal
SN - 0953-7325
VL - 31
SP - 692
EP - 706
JO - Technology Analysis and Strategic Management
JF - Technology Analysis and Strategic Management
IS - 6
ER -