Tourist Behavioral Responses to Destination Revitalization Policies in China

Qin, Wen's dataset contains empirical data from a multi-method study conducted between October 2023 and February 2024. It includes a qualitative pilot with 64 tourist interviews and three experimental studies with 955 total participants. The data measures perceived warmth, perceived competence, and travel behavioral intention under different policy conditions.

Use Cases

• Analyze the relationship between perceived warmth and travel behavioral intention across rigid versus flexible policy conditions.
• Examine the moderating effect of temporal distance on the link between perceived competence and behavioral outcomes like coupon acceptance.
• Model the impact of experimental condition assignment on social judgment measures and behavioral responses in field settings.
• Compare behavioral outcomes, such as hotel accommodation coupon choice, between on-site tourists and online experiment participants.

Strengths

• Multi-method design combining qualitative data from 64 interviews with quantitative data from 955 experimental participants.
• Includes behaviorally grounded measures like hotel coupon choice and scenic spot admission discount acceptance.
• Data collection spans both online scenario-based experiments and field experiments with on-site tourists.

Limitations

• Sample is geographically limited to China, which may restrict generalizability to other cultural contexts.
• The experimental nature of the data may not fully capture real-world, unobserved tourist decision-making.
• The dataset's structure is complex, integrating multiple sub-studies which may require careful merging and interpretation.

Provenance

Source

ICPSR Harvested Dataverse

Collection Method

Mixed methods: semi-structured interviews and randomized online/field experiments.

Time Range

October 2023 to February 2024

Freshness

Data was collected between October 2023 and February 2024, with a platform record last updated in February 2026.

Geography

China