Abstract
The COVID-19 pandemic has profoundly disrupted global tourism, yet the cognitive mechanisms underlying tourists’ behavioral responses during health crises remain insufficiently understood. Drawing on an extended Theory of Planned Behavior (TPB) framework, this study investigates how epidemic perception, non-pharmaceutical interventions (NPIs), and moral norms shape tourists’ decision-making processes. Survey data were collected from 360 respondents with pre-existing travel plans in China during the early pandemic phase. Structural equation modeling (Amos and Smart-PLS) reveals that epidemic perception functions as a foundational cognitive anchor, significantly influencing NPIs, moral norms, subjective norms, and attitudes. Moral norms emerge as a pivotal mediator, directly shaping attitudes, perceived behavioral control, and behavioral intentions. Counterintuitively, NPIs exhibit a negative relationship with intention to cancel travel, suggesting that protective measures effectively mitigate perceived risks and enable tourists to reconcile travel desires with health concerns. Subjective norms exert both direct and indirect effects through moral pathways, underscoring the amplified role of social expectations during crises. Notably, perceived behavioral control does not significantly influence attitudes or intentions, indicating that moral and social imperatives temporarily overshadow resource-based considerations during public health emergencies. These findings advance theoretical understanding of pandemic-era travel behavior. Practically, they suggest that destinations should leverage epidemic perception through authoritative communication to activate moral and social norms, promote NPIs to rebuild traveler confidence, cultivate collective responsibility via social endorsement, and address practical barriers at the implementation stage to transform intentions into actual travel behavior.
Data availability
The datasets used and/or analysed during the current study available from the corresponding author Hu Chen on reasonable request via e-mail chenhu327@126.com.
References
Patino-Artaza, H., King, L. C. & Savin, I. Did COVID-19 really change our lifestyles? Evidence from transport energy consumption in Europe. Energy Policy 191, 114204. https://doi.org/10.1016/j.enpol.2024.114204 (2024).
Xi, H. et al. Evaluating travel behavior resilience across urban and rural areas during the COVID-19 pandemic: Contributions of vaccination and epidemiological indicators. Transp. Res. A Policy Pract. 180, 103980. https://doi.org/10.1016/j.tra.2024.103980 (2024).
Myftiu, J., Gigliarano, C., Maggi, E. & Scagni, A. University commuting during the COVID-19 pandemic: Changes in travel behaviour and mode preferences. Res. Transp. Bus. Manag. 53, 101091. https://doi.org/10.1016/j.rtbm.2023.101091 (2024).
Wang, Y., Choudhury, C., Hancock, T. O., Wang, Y. & Ortúzar, J. D. D. Influence of perceived risk on travel mode choice during COVID-19. Transp. Policy 148, 181–191. https://doi.org/10.1016/j.tranpol.2024.03.011 (2024).
Wang, X., Lai, I. K. W., Zhou, Q. & Pang, Y. H. Impacts of a low-risk perception and perceived benefits on tourists’ attitude and intention to undertake regional travel during the COVID-19 pandemic. Int. J. Environ. Res. Public Health 18(17), 9422. https://doi.org/10.3390/ijerph18179422 (2021).
Han, H. Travelers’ pro-environmental behavior in a green lodging context: Converging value-belief-norm theory and the theory of planned behavior. Tour. Manag. 47, 164–177. https://doi.org/10.1016/j.tourman.2014.11.006 (2015).
Chen, M.-F. & Tung, P.-J. Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. Int. J. Hosp. Manag. 36, 221–230. https://doi.org/10.1016/j.ijhm.2013.09.006 (2014).
Lee, C.-K., Song, H.-J., Bendle, L. J., Kim, M.-J. & Han, H. The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior. Tour. Manage. 33(1), 89–99. https://doi.org/10.1016/j.tourman.2011.02.006 (2012).
Slovic, P. Perception of risk. Science 236(4799), 280–285 (1987).
Brug, J., Aro, A. R., Oenema, A. & van Der Voort, C. SARS risk perception, knowledge, precautions, and information sources, The Netherlands. Emerg. Infect. Dis. 10(8), 1486–1489 (2004).
Ferguson, N. et al. Strategies for mitigating an influenza pandemic. Nature 442(7101), 448–452 (2006).
Song, H. J., Lee, C. K. & Kim, D. Y. The effect of the perception of influenza A(H1N1) on international travel decision-making process of group tourists. J. Tour. Sci. 35(7), 189–209 (2011).
Yoon, S. M., Oh, S. Y. & Yoon, S. J. A study for the effect relationship about overseas trip intention of local by using theory of planned behavior(TPB): Focusing on the additional role of prior knowledge and perceived risk[J]. Korean J. Hospitality & Tourism 19(6), 289–307 (2010).
Sjöberg, L. Factors in risk perception. Risk Anal. 20(1), 1–11. https://doi.org/10.1111/0272-4332.00001 (2000).
Williams, A. M. & Baláž, V. Tourism risk and uncertainty: Theoretical reflections. J. Travel Res. 54(3), 271–287. https://doi.org/10.1177/0047287514523334 (2015).
Quintal, V. A., Lee, J. A. & Soutar, G. N. Risk, uncertainty and the theory of planned behavior: A tourism example. Tour. Manage. 31(6), 797–805. https://doi.org/10.1016/j.tourman.2009.11.005 (2010).
Reisinger, Y. & Mavondo, F. Travel anxiety and intentions to travel internationally: Implications of travel risk perception[J]. J. Travel Res. 43(3), 212–225 (2005).
Bell, D. et al. Nonpharmaceutical interventions for pandemic influenza, national and community measures. Emerg. Infect. Dis. 12(1), 88–94. https://doi.org/10.3201/eid1201.051371 (2006).
World Health Organization. Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza. WHO (2019). https://www.who.int/publications/i/item/non-pharmaceutical-public-health-measuresfor-mitigating-the-risk-and-impact-of-epidemic-and-pandemic-influenza
Aiello, A. E. et al. Mask use, hand hygiene, and seasonal influenza-like illness among young adults: A randomized intervention trial. J. Infectious Diseases 201(4), 491–498 (2010).
Jefferson, T., Del Mar, C. B., Dooley, L., Ferroni, E., Al-Ansary, L. A., Bawazeer, G. A., & Glasziou, P. P. Physical interventions to interrupt or reduce the spread of respiratory viruses. Cochrane Database of Systematic Reviews, 2011(7), CD006207 (2011).
Cowling, B. J. et al. Entry screening to delay local transmission of 2009 pandemic influenza A (H1N1). BMC Infect. Dis. 10, 82. https://doi.org/10.1186/1471-2334-10-82 (2010).
Wilder-Smith, A. & Freedman, D. O. Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (COVID-19) epidemic. J. Travel Med. 27(2), taaa020 (2020).
Ferguson, N. M., Laydon, D., Nedjati-Gilani, G., Imai, N., Ainslie, K., Baguelin, M., & Imperial College COVID-19 Response Team. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand (Report 9). Imperial College London (2020).
Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T (1991).
Conner, M. & Armitage, C. J. Extending the theory of planned behavior: A review and avenues for future research. J. Appl. Soc. Psychol. 28(15), 1429–1464. https://doi.org/10.1111/j.1559-1816.1998.tb01453.x (1998).
Rivis, A., Sheeran, P. & Armitage, C. J. Expanding the affective and normative components of the Theory of Planned Behavior: A meta-analysis of anticipated affect and moral norms. J. Appl. Soc. Psychol. 39(12), 2985–3019. https://doi.org/10.1111/j.1559-1816.2009.00558.x (2009).
Hongliang, Q. Study on the relationship between moral norm and tourists’ civilization tourism behavioral intention: An extended theory of planned behavior model. Zhejiang Social Sci. 26(3), 96–103+159 (2016).
Kim, W. J. et al. Predicting The Intention To Board Eco-Cruise By Extending The Theory Of Planned Behavior In The Moral Behavior Perspective[J]. Korean J. Hospitality & Tourism 23(5), 67–85 (2013).
Schwartz, S. H. Normative influences on altruism. In Advances in experimental social psychology (ed. Berkowitz, L.) 221–279 (Academic Press, 1977).
Raats, M., Shepherd, R. & Sparks, P. Including moral dimensions of choice within the structure of the theory of planned behavior. J. Appl. Soc. Psychol. 25(6), 484–494. https://doi.org/10.1111/j.1559-1816.1995.tb01900.x (1995).
Bamberg, S. & Möser, G. Twenty years after Hines, Hungerford, and Tomera: A new meta-analysis of psycho-social determinants of pro-environmental behaviour. J. Environ. Psychol. 27(1), 14–25. https://doi.org/10.1016/j.jenvp.2006.12.003 (2007).
López-Mosquera, N. Gender differences, theory of planned behavior and willingness to pay. J. Environ. Psychol. 45, 165–175. https://doi.org/10.1016/j.jenvp.2015.12.002 (2016).
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley
Ajzen, I. From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (eds Kuhl, J. & Beckmann, J.) 11–39 (Springer, 1985).
Armitage, C. J. & Conner, M. Efficacy of the theory of planned behavior: A meta-analytic review. Br. J. Soc. Psychol. 40(4), 471–499. https://doi.org/10.1348/014466601164939 (2001).
Kraft, P., Rise, J. & Sutton, S. Perceived difficulty in the theory of planned behavior: Perceived behavioral control or affective attitude?. Br. J. Soc. Psychol. 44(3), 479–496. https://doi.org/10.1348/014466605X48934 (2005).
Cheng, S., Lam, T. & Hsu, C. Negative word-of-mouth communication intention: An application of the theory of planned behavior. J. Hosp. Tour. Res. 30(1), 95–116. https://doi.org/10.1177/1096348005282528 (2006).
Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
Cialdini, R. B., & Trost, M. R. Social influence: Social norms, conformity, and compliance. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 2, pp. 151–192). McGraw-Hill (1998).
Bandura, A. Self-efficacy: The exercise of control (Freeman, 1997).
Zhou, L., Li, Q. & Zhu, L. Outcome efficacy, people-destination affect, and tourists’ environmentally responsible behavior intention: A revised model based on the theory of planned behavior. J. Zhejiang Univ. (Humanities Soc. Sci.) 44(2), 88–98 (2014).
Nam, S. K. A study on behavior intention depending on perception of risk of tourism in North Korea using integrated framework of TPR and TPB: Focusing on the moderating effect of the awareness of importance in tourism of North Korea (Unpublished doctoral dissertation). Kyung Hee University, Seoul (2020).
Yun, K. N. (2020). A study on behavior intention depending on perception of risk of tourism in North Korea using integrated framework of TPR and TPB: Focusing on the moderating effect of the awareness of importance in tourism of North Korea (Unpublished doctoral dissertation). Kyung Hee University, Seoul.
Aguiar-Quintana, T., Román, C. & Gubisch, P. M. M. The post-COVID-19 tourism recovery led by crisis-resistant tourists: Surf tourism preferences in the Canary Islands. Tour. Manag. Perspect. 44, 101041. https://doi.org/10.1016/j.tmp.2022.101041 (2022).
Bouzaghrane, M. A., Obeid, H., González, M. C. & Walker, J. Human mobility reshaped? Deciphering the impacts of the COVID-19 pandemic on activity patterns, spatial habits, and schedule habits. EPJ Data Sci. 13(1), 24. https://doi.org/10.1140/epjds/s13688-024-00463-4 (2024).
Yuan, L., Sho, K., Eom, S. & Lee, S. Changes in visitor behaviour across COVID-19 pandemic: Unveiling urban visitation dynamics and non-linear relationships with the built environment using mobile big data. Habitat Int. 154, 103216. https://doi.org/10.1016/j.habitatint.2024.103216 (2024).
Faulkner, J., Schaller, M., Park, J. H. & Duncan, L. A. Evolved disease-avoidance mechanisms and contemporary xenophobic attitudes. Group Process. Intergroup Relat. 7(4), 333–353. https://doi.org/10.1177/1368430204044000 (2004).
Kock, F., Josiassen, A. & Assaf, A. G. The xenophobic tourist. Ann. Tour. Res. 74, 155–166. https://doi.org/10.1016/j.annals.2018.11.005 (2019).
Sonmez, S. F. & Graefe, A. R. Determining future travel behavior from past travel experience and perceptions of risk and safety. J. Travel Res. 37(2), 171–177 (1998).
Wang, K. & de Vos, J. Trends in leisure and shopping travel: From pre- to post-COVID-19 pandemic. Travel Behav. Soc. 39, 100956. https://doi.org/10.1016/j.tbs.2024.100956 (2025).
Aledort, J., Lurie, N., Wasserman, J. & Bozzette, S. Non-pharmaceutical public health interventions for pandemic influenza: An evaluation of the evidence base. BMC Public Health 7(1), 208–216 (2007).
Aro, A. R., Vartti, A. M., Schreck, M., Turtiainen, P. & Uutela, A. Willingness to take travel-related health risks: A study among the Finnish tourists in Asia during the Avian influenza outbreak. Int. J. Behav. Med. 16(1), 68–73. https://doi.org/10.1080/10705500802677313 (2009).
Qiu, H., Wang, D. & Wang, Y. Social costs of tourism during the COVID-19 pandemic. Ann. Tour. Res. 84, 102994. https://doi.org/10.1016/j.annals.2020.102994 (2020).
Savari, M., Ghezi, M. & Molavi, H. Encouraging low-water-use crops: Behavioral drivers and policy recommendations for sustainable water management. Environ. Sustain. Indic. 26, 100711. https://doi.org/10.1016/j.indic.2025.100711 (2025).
Kaiser, F. G. & Gutscher, H. The proposition of a general version of the theory of planned behavior: Predicting ecological behavior. J. Appl. Soc. Psychol. 33(3), 586–603. https://doi.org/10.1111/j.1559-1816.2003.tb02110.x (2003).
Zhang, C. X., Wang, L. & Rickly, J. Non-interaction and identity change in Covid-19 tourism. Ann. Tour. Res. 89, 103211. https://doi.org/10.1016/j.annals.2021.103211 (2021).
Savari, M. & Khaleghi, B. Analysis of psychological and social factors affecting climate change adaptation and mitigation behaviors among Iranian rice farmers. Sci. Rep. 15(1), 30431. https://doi.org/10.1038/s41598-025-15580-x (2025).
Chen, M. F. Extending the theory of planned behavior model to explain people’s energy savings and carbon reduction behavioral intentions to mitigate climate change in Taiwan—Moral obligation matters. J. Clean. Prod. 112, 1746–1753. https://doi.org/10.1016/j.jclepro.2015.09.058 (2016).
Thørgersen, J. Recycling and morality: A critical review of the literature. Environ. Behav. 28(4), 536–558. https://doi.org/10.1177/0013916596284003 (1996).
Botetzagias, I., Dima, A. F. & Malesios, C. Extending the theory of planned behavior in the context of recycling: The role of moral norms and of demographic predictors. Resour. Conserv. Recycl. 95, 58–67. https://doi.org/10.1016/j.resconrec.2014.11.004 (2015).
Arvola, A. et al. Predicting intentions to purchase organic food: The role of affective and moral attitudes in the theory of planned behavior. Appetite 50(2–3), 443–454. https://doi.org/10.1016/j.appet.2007.11.008 (2008).
Savari, M., Yazdanpanah, M. & Rouzaneh, D. Applying conservation agriculture practices as a strategy to control soil erosion and carbon sequestration. Results Eng. 26, 104854. https://doi.org/10.1016/j.rineng.2025.104854 (2025).
Han, H., Hsu, L.-T. & Sheu, C. Application of the Theory of Planned Behavior to green hotel choice: Testing the effect of environmental friendly activities. Tour. Manag. 31(3), 325–334. https://doi.org/10.1016/j.tourman.2009.03.013 (2010).
Lam, T. & Hsu, C. H. C. Predicting behavioral intention of choosing a travel destination. Tour. Manag. 27(4), 589–599. https://doi.org/10.1016/j.tourman.2005.02.003 (2006).
Chang, M. K. Predicting unethical behavior: A comparison of the Theory of Reasoned Action and the Theory of Planned Behavior. J. Bus. Ethics. 17(16), 1825–1834. https://doi.org/10.1023/A:1005721401993 (1998).
Oliver, R. L. & Bearden, W. O. Crossover effects in the Theory of Reasoned Action: A moderating influence attempt. J. Consum. Res. 12(3), 324–340 (1985).
Trafimow, D., Sheeran, P., Conner, M. & Finlay, K. A. Evidence that the type of person affects the strength of the perceived behavioural control–intention relationship. Br. J. Soc. Psychol. 41(2), 253–270. https://doi.org/10.1348/014466602165081 (2002).
Wan, C., Shen, G. Q. & Yu, A. The moderating effect of perceived policy effectiveness on recycling intention. J. Environ. Psychol. 37, 55–60 (2014).
Zhang, F. & Hu, J. Analysis of the mechanism of the pollution-free planting behavior of fruit farmers based on the theory of planned behavior——An investigation of apple growers in 16 cities (districts) in Shandong Province. Issues in Agri. Econ. 34(07), 48–55+111 (2013).
Beck, L. & Ajzen, I. Predicting dishonest actions using the Theory of Planned Behavior. J. Res. Pers. 25(3), 285–301 (1991).
Ting, X. Consumers’Intention to visit green hotels: Based on TPB perspective[J]. Tourism Tribune 31(6), 94–103 (2016).
Hsu, C. & Lam, T. Theory of Planned Behavior: Potential travelers from China. J. Hosp. Tour. Res. 28(1), 63–82. https://doi.org/10.1177/1096348004263004 (2004).
Sparks, B. & Pan, G. W. Chinese outbound tourists: Understanding their attitudes, constraints and use of information sources. Tour. Manag. 30(4), 483–494 (2009).
Likert, R. A technique for the measurement of attitudes. Arch. Psychol. 140, 1–55 (1932).
DeVellis, R. F. Scale development: Theory and applications (4th ed.). SAGE Publications (2016).
Chen, H., Kim, J. H., Liu, Y. & Wang, Y. A research on the driving power about user psychological behavior from the quality of urban rail transit service: A case study of Beijing, Shanghai and Chongqing. China. Urban Problems 11(12), 96–103 (2018).
Bentler, P. M. & Chou, C. P. Practical issues in structural modeling. Sociological Methods Res. 16(1), 78–117. https://doi.org/10.1177/0049124187016001004 (1987).
Loehlin, J. C. Latent variable models: An introduction to factor, path, and structural analysis (2nd ed.). Lawrence Erlbaum Associates (1992).
Nunnally, J. C., & Bernstein, I. H. Psychometric theory (3rd ed.). McGraw-Hill (1994).
Fornell, C. & Larcker, D. F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50. https://doi.org/10.1177/002224378101800104 (1981).
Hu, L.-T. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. 6(1), 1–55. https://doi.org/10.1080/10705519909540118 (1999).
Preacher, K. J. & Hayes, A. F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879 (2008).
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. Multivariate data analysis (7th ed.). Pearson Prentice Hall (2010).
Funding
Natural Science Foundation of Shandong Provincial, Research on the Travel Decision Mechanism and Response Strategies of Tourists under the Background of the Epidemic. (ZR202103030582).
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Ke Zong： Conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing—original draft preparation. Hu Chen：writing—review and editing, visualization, supervision, project administration, funding acquisition. Rui Yang: methodology, software, validation, formal analysis.
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The studies involving human participants were reviewed and approved by College of Public Administration, Shandong Agricultural University Ethics Committee (Approval Number: 2022.5948565). The participants provided their written informed consent to participate in this study. All methods were performed in accordance with relevant guidelines and regulations.
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Zong, K., Chen, H. & Yang, R. The analysis for mechanism deduction and empirical test of tourists’ behavior decision-making under the background of COVID-19. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45040-z
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DOI: https://doi.org/10.1038/s41598-026-45040-z
