SynthesisInternational journal of environmental research and public health2019
What Hinders the Development of Green Building? An Investigation of China.
Synthesis in International journal of environmental research and public health, 2019. 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.
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Who cites it
7 citing papers in PubMed.
- Article
- The Outlook of Green Building Development in China during the "Fourteenth Five-Year Plan" Period.International journal of environmental research and public health · 2023Article
- How Do Government Policies Promote Green Housing Diffusion in China? A Complex Network Game Context.International journal of environmental research and public health · 2022Article
- Evolutionary Game and Simulation of Green Housing Market Subject Behavior in China.Computational intelligence and neuroscience · 2022Article
- Investigating the Critical Factors of Professionals' BIM Adoption Behavior Based on the Theory of Planned Behavior.International journal of environmental research and public health · 2021Article
- Investigating the Dynamics of China's Green Building Policy Development from 1986 to 2019.International journal of environmental research and public health · 2020Article
- Investigating the Crucial Aspects of Developing a Healthy Dormitory based on Maslow's Hierarchy of Needs-A Case Study of Shenzhen.International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid development of the economy, people are paying more and more attention to the environmental problems. In this circumstance, the concept of a circular economy is proposed for making efficient use of resources and minimizing the production of waste and other emissions. Each year, the construction sector consumes a vast volume of resources and makes impacts on the environment. To align with the development of the circular economy, the concept of green building is proposed. In China, though the concept of green building has been promoted for decades, the development status is far from optimistic. Thus, this paper aims to investigate the barriers that hinder green building development (GBD) in China. Through a systematic review and semi-structured interviews with experienced industrial practitioners, 24 potential barriers of GBD in China were identified. A questionnaire survey was then conducted for data collection. After descriptive and inferential statistical analyses, a partial least squares structural equation model (PLS-SEM) was established to investigate the impacts of different barriers on GBD. Results showed that the lack of policy and industry guidance, the immature market environment, and the lack of environmental awareness are the most important GBD barriers in China. This research can assist stakeholders in better understanding the status of GBD in China and enable decision-makers to formulate appropriate strategies to promote green building.
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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.