Expert Credibility Factors and Their Impact on Digital Innovation and Sustainability Adoption in China’s Social Media Ecosystem
The successful implementation of digital transformation initiatives depends critically on public trust in experts guiding these processes. In today’s digital media environment, expert trust faces significant challenges, potentially hindering sustainable innovation adoption. This study investigates how expert credibility dimensions and information characteristics shape trust in digital transformation experts among Chinese social media users. We employed a mixed-methods approach combining a survey of 850 Chinese social media users, a quasi-experiment testing a digital expert verification feature, and secondary data analysis. The study measured multiple dimensions of expert trust while examining relationships with expert cognition factors and media usage variables through regression, mediation, and structural equation modeling. Expert trust in digital transformation exists at moderate levels (M = 6.82/10), with higher trust in digital innovation research (M = 7.12) than specific sustainability recommendations (M = 6.59). Expert authenticity emerged as the strongest predictor of trust (β = 0.27), followed by professional competence (β = 0.21). A “digital exposure paradox” emerged whereby higher volumes of expert information negatively predicted trust (β = −0.18), while information quality positively predicted trust (β = 0.25). The digital verification feature causally enhanced trust (DID = 0.57), with institutional sources strengthening trust while user-generated content diminished it. The findings reveal that digital transformation expert trust involves multi-dimensional evaluations beyond traditional credibility assessments. The “digital exposure paradox” suggests that prioritizing information quality over quantity, demonstrating expert authenticity, and implementing verification mechanisms can enhance trust and accelerate sustainable digital transformation adoption.
Authors
- Shasha Li (ORCID: https://orcid.org/0000-0002-4886-5180)
- Chao Gao (ORCID: https://orcid.org/0000-0002-3158-397X)
Institutions
- Fudan University (CN)
- Chang'an University (CN)
- Technical University of Munich (DE)
Publication Details
- Journal
- Sustainability
- Published
- 2025-10-11
- DOI
- https://doi.org/10.3390/su17209017
- Primary Topic
- Risk Perception and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00