Research on the Efficiency and Synergistic Effect of Industrial Green Innovation Development in the Beijing–Tianjin–Hebei Urban Agglomeration

This research centers on one of northern China’s most crucial economic regions—the Beijing–Tianjin–Hebei urban agglomeration. This paper primarily addresses the present circumstances, developments, and obstacles pertaining to industrial green development and industrial innovation in the region, with a particular focus on its role in fostering integrated economic and environmental growth. This study utilizes a global super-efficiency SBM model and a coupled coordination model, along with a panel data analysis technique, to determine the extent of green development, innovation, and green innovation collaboration in the Beijing–Tianjin–Hebei urban agglomeration cluster between 2018 and 2022. The study revealed that, despite notable advancements in industrial green development in the Beijing–Tianjin–Hebei urban agglomeration in recent years, the disparity in urban development persists, with some cities exhibiting a relatively low input–output ratio for green innovation. There is a pressing need to enhance overall efficiency through policy guidance and technical support. Furthermore, the study underscores the significance of bolstering regional collaboration and facilitating the sharing of resources and technological exchange to attain harmonized regional development.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-02-04
DOI
https://doi.org/10.3390/su17031244
Citations
6
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
25.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Efficiency and Synergistic Effect of Industrial Green Innovation Development in the Beijing–Tianjin–Hebei Urban Agglomeration

Hong Wu, Xuewei Wen
6 citations
Sustainability
Regional Development and Environment
25.21
article

Research on the Efficiency and Synergistic Effect of Industrial Green Innovation Development in the Beijing–Tianjin–Hebei Urban Agglomeration

Hong Wu, Xuewei Wen
article en
6 citations

Abstract

This research centers on one of northern China’s most crucial economic regions—the Beijing–Tianjin–Hebei urban agglomeration. This paper primarily addresses the present circumstances, developments, and obstacles pertaining to industrial green development and industrial innovation in the region, with a particular focus on its role in fostering integrated economic and environmental growth. This study utilizes a global super-efficiency SBM model and a coupled coordination model, along with a panel data analysis technique, to determine the extent of green development, innovation, and green innovation collaboration in the Beijing–Tianjin–Hebei urban agglomeration cluster between 2018 and 2022. The study revealed that, despite notable advancements in industrial green development in the Beijing–Tianjin–Hebei urban agglomeration in recent years, the disparity in urban development persists, with some cities exhibiting a relatively low input–output ratio for green innovation. There is a pressing need to enhance overall efficiency through policy guidance and technical support. Furthermore, the study underscores the significance of bolstering regional collaboration and facilitating the sharing of resources and technological exchange to attain harmonized regional development.

SustainabilityVol. 17(3)
Fujian University of Technology (CN)
National Social Science Fund of China
Openalex Percentile: Top 1%
Regional Development and Environment
25.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.