Regional Differences and Influencing Factors of Green Innovation Efficiency in China’s 285 Cities

Yingshi Shang, Yanmin Niu () and Peng Song
Additional contact information
Yingshi Shang: School of Economics and Management, Qingdao University of Science and Technology, Qingdao 266061, China
Yanmin Niu: School of Mathematical Sciences, Ocean University of China, Qingdao 266100, China
Peng Song: School of Economics and Management, Qingdao University of Science and Technology, Qingdao 266061, China

Sustainability, 2023, vol. 16, issue 1, 1-18

Abstract: Green innovation is an important concept of high-quality development to achieve resource conservation and ecological protection. To explore whether there is an imbalance in the development of green innovation in China and find the reasons for this phenomenon, it is of vital importance to investigate the regional differences of green innovation efficiency (GIE) and its influencing factors. Many scholars have studied the performance of green innovation from the efficiency perspective but concentrated on provincial-level analysis and lacked heterogeneity analysis of the influencing factors. To fill this gap, this study explores the regional differences of GIE of 285 prefecture-level and above cities in China during the period 2003–2019, and then employs the spatial error model (SEM) to explore the heterogeneity of influencing factors. The results show that: (1) The GIE in China and its three regions underwent an overall increasing process, revealing regional heterogeneity, with most efficient cities agglomerated in the Eastern region. (2) The spatial difference of GIE in China was narrowing, and the within-region Gini coefficient in the three regions presented a similar trend. Between-region difference contributed the largest to the regional differences, especially between the Central and Western regions. The kernel density estimation results showed that GIE presents significant spatial characteristic of polarization. (3) The SEM model analysis indicated that economic development, government motivation, industrial structure, financial support, and population scale affected GIE profoundly in China, and there was significant spatial heterogeneity in the impact of each influencing factor. Western cities were mainly driven by governmental support in green innovation, while Eastern and Central cities were driven by economic development and improved industrial structure.

Keywords: green innovation efficiency; regional differences; distribution dynamics; influencing factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/1/334/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/1/334/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2023:i:1:p:334-:d:1310318

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().