Academia-industry collaboration, government funding and innovation efficiency in Chinese industrial enterprises

ABSTRACT

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.

KEYWORDS:

• Collaboration with universities
• collaboration with research institutes
• government funding
• innovation efficiency

Acknowledgements

We sincerely thank the two anonymous reviewers for their constructive comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Bojun Hou ([email protected]) is a PhD candidate of the School of Management at USTC and a visiting PhD student of Michael G. Foster School of Business, University of Washington.

Jin Hong ([email protected], corresponding author) is an associate professor in the School of Management, USTC. He is also a visiting research fellow of Curtin University Sustainability Policy (CUSP) Institute.

Hongying Wang ([email protected]) is an associate professor of political science at the University of Waterloo.

Chongyang Zhou ([email protected]) is a PhD student jointed trained by the School of Management, University of Science and Technology of China and Department of Economics and Finance, City University of Hong Kong.

ORCID

Bojun Hou http://orcid.org/0000-0002-5415-5492

Chongyang Zhou http://orcid.org/0000-0001-9923-1949

Notes

1 FRONTIER4.1 software is used with time-varying efficiency model.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant Nos. 71172213 and 71572188].