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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月1日

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  • Juan Lu,
  • Huiying Zhang,
  • Jiarui Han,
  • Xingnian Zhang

摘要

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.