ABSTRACT
With the advent of the knowledge economy, inbound open innovation for knowledge-intensive SMEs has attracted more and more attention. However, the distinctiveness between them and traditional SMEs in this process remains undiscussed. This paper investigates how different partnerships influence knowledge-intensive SMEs' innovative performance by demonstrating the organisational learning capability mechanism. Based on the survey data from 248 Chinese knowledge-intensive SMEs, this paper finds that both market-based and science-based partnerships play nonnegligible roles in knowledge-intensive SMEs' innovative performance, and organisational learning capability partially mediates these relationships. In addition, when the environmental turbulence increases, knowledge-intensive SMEs prefer science-based partnerships. The research results indicate that knowledge-intensive SMEs have different partner selection strategies for open innovation compared to traditional SMEs, which could be affected by the turbulence of the external environment. This study sheds light on the relationship between open innovation and the performance of knowledge-intensive SMEs.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 According to the National Bureau of Statistics of China (http://www.gov.cn/gongbao/content/2019/content_5419213.htm), knowledge-intensive manufacturing generally includes ICT manufacturing, new equipment manufacturing, new materials manufacturing, medicine and medical industry, environmental protection industry, etc. Knowledge-intensive service industries generally include ICT services, R&D and technical service, etc.
2 According to the standard of the Ministry of Science & Technology of China (http://www.innofund.gov.cn/).
3 The data on the number of SMEs in China is collected from the China Economic Census Yearbook 2018 (http://www.stats.gov.cn/tjsj/pcsj/jjpc/4jp/zk/indexce.htm), and the data on knowledge-intensive SMEs is collected on the official website of the Ministry of Science and Technology of the People's Republic of China (https://www.most.gov.cn/index.html)
4 The data is collected on the official website of the Ministry of Science and Technology of the People's Republic of China (https://www.most.gov.cn/index.html) as of May 2022 (the last update of the data in this paper).
5 From the news on the official website of the Ministry of Science and Technology of the People's Republic of China (https://www.most.gov.cn/index.html).
Additional information
Funding
Notes on contributors
Jun Jin
Jun Jin received the Ph.D. degree in economics from the University of St. Gallen, St. Gallen, Switzerland, in 2005. She is currently an Associate Professor with the Department of Innovation, Entrepreneurship, and Strategy, School of Management, Zhejiang University, Hangzhou, China. She is also the Visiting Professor with the Singapore University of Technology and Design, Singapore. Her research interests include the areas of global innovation, catching up strategies, open innovation, and eco-innovation.
Meng Li
Meng Li is currently working toward the Ph.D. degree in management science and engineering with Zhejiang University, Hangzhou, China. His current research interests include open innovation, optimal distinctiveness.