ArticleHeliyon2023
Understand, track and develop enterprise workplace safety, and sustainability in the industrial park.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Industrial parks make great contributions to the local economy, society, and culture, but they have also encountered many problems, such as limited resources, the longevity of ecological restoration, and the contagion of safety accidents. As a socioeconomic and ecological composite system formed by the interaction of multiple stakeholders, the solutions to succeed in workplace sustainability in industrial parks are still not known. The purpose of this study is to explore how to integrate existing resources to achieve a win-win situation in industrial park safety and environmental protection issues. According to Actor-network Theory and a systematic search, this study identifies the relevant subjects from selected 24 studies and clarifies the interactions made by these subjects. In sum, this study concludes two main modes of developing workplace sustainability in the park from multiple actors' perspectives: self-regulation of inner park subjects and the driving force of exterior park subjects.
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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.