Optimal-fit model of risk perception and travel-related behaviors during a global pandemic

Liu-Lastres, Bingjie; Yang, Yang; Zhang, Carol X.

Abstract

Risk perception research plays a critical role in tourism studies, given its ability to shape the appeal and viability of destinations. There has been a surge in research on tourism risk perception and travel-related behaviors due to the pandemic. This context offers a unique opportunity to review and aggregate risk perception studies to identify behavior patterns and changes. Accordingly, this study adopted the PSALSAR framework to analyze these studies, which consists of a synthesized literature review and a meta-analysis of tests involving competing theoretical models. The synthesis revealed the various behavioral outcomes and diverse theoretical backgrounds included in the sample. Our meta-analysis uncovered the model with an optimal fit and delineated the relationships among tourists' cognitive and affective risk perceptions, efficacy beliefs, and behavior across different stages. This study offers theoretical and empirical insights into the effects of tourists' risk perception attitude variables. Findings can inform more effective tourism crisis management strategies for destination management and marketing.

Citation

Liu-Lastres, B., Yang, Y., & Zhang, C. X. (2024). Optimal-fit model of risk perception and travel-related behaviors during a global pandemic. Journal of Destination Marketing and Management, 34, Article 100958. https://doi.org/10.1016/j.jdmm.2024.100958

• Journal Article Type: Article
• Acceptance Date: Oct 23, 2024
• Online Publication Date: Nov 11, 2024
• Publication Date: 2024-12
• Deposit Date: Nov 21, 2024
• Publicly Available Date: Nov 12, 2025
• Journal: Journal of Destination Marketing and Management
• Print ISSN: 2212-571X
• Electronic ISSN: 2212-571X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 34
• Article Number: 100958
• DOI: https://doi.org/10.1016/j.jdmm.2024.100958
• Keywords: Risk perception; tourist behavior; decision making; meta-analysis; literature review; competing model testing; PSALSAR framework 2
• Public URL: https://nottingham-repository.worktribe.com/output/42214231