How does multidimensional interaction of knowledge transfer affects digital innovation capability?

ABSTRACT

This study establishes the link between multi-dimensional interaction of knowledge transfer paths and digital innovation capability from both macro−global (native, cross−border) and micro−knowledge type (auxiliary and complementary) perspectives. Using the data of Chinese firms, we find that the matching of the “supply” of native knowledge network and auxiliary knowledge “demand” is more conducive to the improvement of digital innovation capability than matching of the “demand” of complementary knowledge. The matching of the “supply” of cross−border knowledge network and the “demand” of complementary knowledge are more conducive to the improvement of digital innovation capability than matching with the “demand” of auxiliary knowledge. Digital environment scanning capability and knowledge flow coupling moderates the relationship between complementary and auxiliary knowledge transfer and digital innovation capability. Our findings have important implications for the construction of digital innovation network systems.

KEYWORDS:

• Knowledge transfer
• digital innovation capability
• digital environment scanning ability
• degree of knowledge flow coupling

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Digital technology often refers to ABCD: A: Artificial Intelligence (AI), B: Blockchain, C: Cloud Computing, D: Big Data or a broader SMACIT technology (S is social-related technology, Social; M is mobile-related technology, Mobile; A is analysis Related technology, Analytics, C is cloud-related technology, Cloud; IT is Internet of Things technology, IoT).

2. See the link for details: https://www.ibm.com/garage/method/.

3. The “Statistical Classification of the Digital Economy and Its Core Industries (2021)” has been adopted at the 10th executive meeting of the National Bureau of Statistics on May 14, 2021. http://www.gov.cn/.

Additional information

Funding

The work was supported by the National Social Science Foundation major project of China [20&ZD083].