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Business environment distance, absorptive capacity and innovation performance of EMNEs: evidence from China.
- Source :
- Kybernetes; 2023, Vol. 52 Issue 10, p4531-4550, 20p
- Publication Year :
- 2023
-
Abstract
- Purpose: This paper investigates the effect of business environment distance on innovation performance of emerging market multinational enterprises (EMNEs) and explores the mediating effect of absorptive capacity between the two, and it further analyzes the moderating effect of skilled migrants in the relationship between business environment distance and absorptive capacity. Design/methodology/approach: An empirical analysis based on a fixed effect model is conducted using data of Chinese MNEs listed on the Shanghai and Shenzhen Stock that expand into developed markets from 2011 to 2018. Findings: The results suggest business environment distance positively affects the innovation performance of EMNEs, and can enhance innovation performance by affecting absorptive capacity of EMNEs. In addition, skilled migrants strengthen the relationship between business environment distance and absorptive capacity of EMNEs. Practical implications: Chinese MNEs should fully exploit business environment distance to acquire the technology needed for innovation activities, and strengthen absorptive capacity to maximize the benefits from innovation. Chinese government needs to strengthen the construction of skilled migrants to facilitate knowledge and technology transfer. Originality/value: Combining springboard theory and institutional theory, this paper integrates macro and micro perspectives to explore whether and how business environment distance affects innovation performance of Chinese MNEs. The paper provides a good theoretical basis and important practical reference value for enhancing the technological innovation capability of Chinese MNEs and the overall technological innovation level of China. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0368492X
- Volume :
- 52
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Kybernetes
- Publication Type :
- Periodical
- Accession number :
- 173344850
- Full Text :
- https://doi.org/10.1108/K-11-2021-1094