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Modeling the influencing factors of electronic word-of-mouth about CSR on social networking sites

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Abstract

Corporate social responsibility (CSR) information can now be disseminated via social networking sites. An organization’s image and upcoming portfolios are directly affected by electronic word of mouth (eWOM). It generates from its customers, employees, and other stakeholders. We developed a critical model to enlighten the behavior to share and comment on a negative news story about CSR displayed on Wechat and QQ to figure out what was causing this behavior. Structural equation modeling (SEM) and the partial least squares regression (PLS) approach were used to conduct a self-administered survey of hotel customers in China. Social and environmental awareness, information usefulness, corporate image, and a company’s motivation to comment and share on CSR news were all considered explanatory variables in our study. We asked 300 Wechat and QQ users to rate a fake environmental news story. We found that social and environmental awareness affects the effectiveness of information and the attitude toward behavior, which may describe the eWOM intent of the particular news. On the other hand, corporate reputation could discourage people from disseminating eWOM and sharing the news with their social linkage contacts. The findings of the study suggest having a better understanding of how specific CSR activities can increase customers’ commitment, which leads to positive eWOM, will benefit the hotel industry.

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Authors and Affiliations

Authors

Contributions

Lei Gang and Liu Haiming: Conceptualization, data curation, methodology, writing—original draft, data curation, visualization, supervision; Huang Hua: Visualization, editing; Muhammad Waqas: Review and editing and software.

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Correspondence to Muhammad Waqas.

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The authors declare that they have no known competing financial interests or personal relationships that seem to affect the work reported in this article. We declare that we have no human participants, human data, or human tissues.

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The authors declare no competing interests.

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Responsible Editor: Philippe Garrigues

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Hai Ming, L., Gang, L., Hua, H. et al. Modeling the influencing factors of electronic word-of-mouth about CSR on social networking sites. Environ Sci Pollut Res 29, 66204–66221 (2022). https://doi.org/10.1007/s11356-022-20476-8

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  • DOI: https://doi.org/10.1007/s11356-022-20476-8

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