Industrial Green Innovation Efficiency: Spatial Patterns, Evolution, and Convergence in the Yangtze River Economic Belt
Year: 2025
Type: article
Abstract: This study examines the relationship between technological innovation and economic development in the Yangtze River economic belt context. Specifically, the study employs the SBM-GML model to assess the efficiency of industrial green technology innovation across 110 prefecture-level cities between 2006 and 2022. The study also employs exploratory spatial data analysis (ESDA) and the Spatio-temporal transition method to analyze the spatial evolution pattern of the GML index of industrial green technology innovation. In addition, the study investigates the convergence mechanism using absolute and conditional β convergence models. The findings reveal that the GML index of industrial green technology innovation in the Yangtze River Economic Belt exhibits an upward trend, and technological progress is a key driver. Moreover, the spatial and temporal transition of the GML index of industrial green technology innovation shows substantial spatial dependence and solid spatial stability. The study also finds regional heterogeneity in the absolute and conditional β convergence characteristics and their influencing factors. Considering regional differences, the results suggest differentiated policy recommendations to promote the coordinated development of industrial green technological innovation efficiency in the Yangtze River Economic Belt. The study contributes to the literature on the relationship between technological innovation and economic development, highlighting the importance of spatial considerations and regional heterogeneity in promoting sustainable economic growth.
Source: Sustainability
DOI: 10.3390/su17114880
Authors: Mengchao Yao, Jingjing Pan
Institution: Xinjiang University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: Xinjiang University
OpenAlex ID: W4410773941