ReviewEnvironmental science and pollution research international2021
A critical review of the current research mainstreams and the influencing factors of green total factor productivity.
Review in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 106 citations in OpenAlex.
- Impact of artificial intelligence-driven urban renewal strategies green economic efficiency and resident health in China.Frontiers in public health · 2025Article
- Article
- Article
- How does the digital economy affect the development of the green economy? Evidence from Chinese cities.PloS one · 2023Article
- Impact of Artificial Intelligence on Regional Green Development under China's Environmental Decentralization System-Based on Spatial Durbin Model and Threshold Effect.International journal of environmental research and public health · 2022Article
- Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity.International journal of environmental research and public health · 2022Article
- A road map for environmental sustainability and green economic development: an empirical study.Environmental science and pollution research international · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 4 countries.
Funding
Abstract
The current world economy needs to undergo a green transformation. Green total factor productivity provides the basis for judging whether a country or region can attain long-term sustainable development. However, there is little research into the factors that influence green total factor productivity and this has become an obstacle in the transition to a greener economy. On filtering relevant articles and interviews data collected from 2009 to 2019, open decoding, spindle decoding, and selective decoding are carried out to classify research conducted into green total factor productivity. From this analysis, cutting-edge research and knowledge gaps in green total factor productivity are identified. Also, an influencing factor model of green total factor productivity is built. Findings suggest that technical, economic, and government are the three main research streams involved in this transformation process. In particular, technology plays a decisive role, economy plays a guaranteeing role, and government plays a regulatory role. Moreover, the impact of these factors cannot be isolated, as each influence and mediate the other two. Results from this study will help further popularize green total factor productivity and provide a new starting point for reducing energy consumption and environmental pollution.
Indexed as
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.