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环境因素对中国国家公园微信公众参与度的影响——一项社会认知分析

The impact of environmental factors on public engagement on WeChat in China's national parks- a socio-cognitive analysis.

作者信息

Lu Juan, Zhang Huiying, Han Jiarui, Zhang Xingnian

机构信息

College of management and economics, Tianjin University, Tianjin, 300072, China.

College of Politics and Public Administration, Qinghai Nationalities University, Xining, 810007, China.

出版信息

Sci Rep. 2025 Jun 1;15(1):19193. doi: 10.1038/s41598-025-01073-4.

DOI:10.1038/s41598-025-01073-4
PMID:40451793
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12127479/
Abstract

Based on social cognitive theory and engagement hierarchy structure, this study aims to investigate how environmental factors influence public interaction behavior on WeChat, the official social media platform used by China's national parks (NPs). Using monthly panel data from July 2018 to December 2023, this research employs advanced econometric models such as two-way fixed effects, Least Squares Dummy Variable (LSDV), and Difference Generalized Method of Moments (D-GMM) estimators to analyze the complex dynamics of public interaction and messaging. The results highlight the significant positive impact of policies and news in driving public behavior on social media, while academic conferences have a dampening effect. The study introduces the mediating role of WeChat and the moderating effect of the administrative level. In addition, the study shows that the engagement structure of China's NPs on WeChat is mainly at the level of information and community building, with limited progress in facilitating public action on environmental protection or policymaking. The findings suggest that tailored strategies, considering local contexts and the development stages of NPs, are essential for effective public service strategies. The results of the study can help inform how environmental factors and social media tools can be used to increase public engagement with NPs.

摘要

基于社会认知理论和参与层次结构,本研究旨在调查环境因素如何影响中国国家公园(NP)官方社交媒体平台微信上的公众互动行为。本研究使用2018年7月至2023年12月的月度面板数据,采用双向固定效应、最小二乘虚拟变量(LSDV)和差分广义矩估计法(D-GMM)估计量等先进计量模型,分析公众互动和信息传递的复杂动态。结果突出了政策和新闻对推动社交媒体上公众行为的显著积极影响,而学术会议则有抑制作用。该研究引入了微信的中介作用和行政级别的调节作用。此外,研究表明,中国国家公园在微信上的参与结构主要处于信息和社区建设层面,在促进公众参与环境保护或政策制定方面进展有限。研究结果表明,考虑到当地情况和国家公园的发展阶段,制定量身定制的策略对于有效的公共服务策略至关重要。该研究结果有助于说明如何利用环境因素和社交媒体工具来提高公众对国家公园的参与度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/833694617895/41598_2025_1073_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/95bd09f570e4/41598_2025_1073_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/78089c765e66/41598_2025_1073_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/6eb9ff9e6c7f/41598_2025_1073_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/bb3bb5bd37df/41598_2025_1073_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/cafb140acb93/41598_2025_1073_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/833694617895/41598_2025_1073_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/95bd09f570e4/41598_2025_1073_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/78089c765e66/41598_2025_1073_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/6eb9ff9e6c7f/41598_2025_1073_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/bb3bb5bd37df/41598_2025_1073_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/cafb140acb93/41598_2025_1073_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b35/12127479/833694617895/41598_2025_1073_Fig6_HTML.jpg

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