ArticleScientific reports2023
Green innovation efficiency and multiple paths of urban sustainable development in China: multi-configuration analysis based on urban innovation ecosystem.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 32 citations in OpenAlex.
- Impact of Spatial structure of urban agglomerations on green innovation in China.Scientific reports · 2026Article
- Study on urban passenger transport carbon reduction pathways based on system dynamics.Scientific reports · 2025Article
- Driving forces of digital transformation in chinese enterprises based on machine learning.Scientific reports · 2024Article
- The effect of producer service agglomeration externalities on urban green innovation efficiency in China.Heliyon · 2024Article
- Evaluation of innovation primacy in cross-regional central cities: Evidence from the Huaihai Economic Zone in China (2010-2020).PloS one · 2024Article
- Enhancing the energy level of regional digital innovation ecosystems: A configuration perspective.PloS one · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Enhancing the effectiveness of urban green innovation is a powerful strategy for advancing urban sustainability. A strong urban innovation ecosystem is a crucial building block for advancing urban green innovation's effectiveness. We use the fsQCA method to investigate the pathways and models of innovation ecosystems to promote the green innovation efficiency of cities from a histological perspective, using 71 innovative cities in China as cases. This method is based on the DEA-SBM model to measure the green innovation efficiency of cities and the Necessary Conditions Analysis. According to our analysis, individual innovation factors are not required to increase urban green innovation efficiency. But cities with good openness can attract creative forces and foster open innovation, which is essential for producing high levels of green innovation efficiency in cities. The innovation subject-balanced development model, the innovation environment-innovation asset dual drive model, and the innovation subject-open drive model have all been identified as additional models to support urban innovation efficiency. Finally, we discovered that it is not possible to increase the efficiency of green innovation in the city when each innovation factor in the city is performing poorly, and when there is also a lack of innovation subject and system openness. This study attempts to offer fresh theoretical angles and a variety of urban low-carbon development pathways.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.