Technology Acceptance And Knowledge Sharing Survey Of Shanghai University Teachers

384 university teachers from Shanghai participated in a cross-sectional survey testing an extended Technology Acceptance Model. The dataset contains self-reported measures of knowledge-sharing behavior, perceived usefulness, perceived enjoyment, and active professional engagement. The study examines predictors of knowledge sharing via social media in a digitally mature higher education context.

Use Cases

• Analyze the relationship between behavioral intention and self-reported knowledge-sharing behavior among 384 survey respondents.
• Test the predictive power of perceived usefulness and perceived enjoyment on active professional engagement in social media use.
• Model the non-significant effect of perceived ease of use on knowledge-sharing outcomes in a mature digital setting.
• Examine the survey's extended TAM constructs to identify value- and engagement-driven mechanisms for collaboration.

Strengths

• Survey includes 384 university teacher respondents, providing a substantive sample size for analysis.
• Data is structured around validated TAM constructs like perceived usefulness and behavioral intention.
• Study focuses on a specific, digitally mature context (Shanghai higher education), offering geographic and contextual clarity.
• Dataset is openly licensed under CC BY 4.0 for reuse and redistribution.

Limitations

• Dataset is very small at 19.6 KB, likely containing only summary statistics or a single table, not raw survey responses.
• Relies on self-reported measures of knowledge-sharing behavior, which may be subject to social desirability bias.
• Cross-sectional design limits ability to infer causal relationships between model constructs.

Provenance

Source

figshare

Collection Method

Cross-sectional survey analyzed using PLS-SEM.

Time Range

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Freshness

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Geography

Shanghai, China