study

Predicting the revisit intention of volunteer tourists using the merged model between the theory of planned behavior and norm activation model

Predicting the revisit intention of volunteer tourists using the merged model between the theory of planned behavior and norm activation model: Despite the importance of the theory of planned behavior (TPB) and norm activation model (NAM) in explicating revisit intention, predictions based on the merging of these theories remain sparse in the youth volunteer tourism segment. To understand revisit intention formation, a meta-analysis is performed to draw a macro conclusion using prosocial studies as a representative of volunteer tourism in investigating the predictive power of the aforementioned-merged theories. Subsequently, latent growth curve modeling is applied to extend the understanding of tourist type identification to volunteer tourism research. The introduction of NAM into TPB marginally adds value to predictive power. Evidenzgrad B, Risk of Bias unclear.

Quelle

Autor:innen: Noppadol Manosuthi, Jin‐Soo Lee, Heesup Han

Jahr: 2020

Journal/Quelle: Journal of Travel & Tourism Marketing

DOI: 10.1080/10548408.2020.1784364

APA-Quelle

Manosuthi, N., Lee, J., & Han, H. (2020). Predicting the revisit intention of volunteer tourists using the merged model between the theory of planned behavior and norm activation model. Journal of Travel & Tourism Marketing. https://doi.org/10.1080/10548408.2020.1784364

Zitationen laut Paper-Korpus: 125

Forschungsfrage / Summary

Despite the importance of the theory of planned behavior (TPB) and norm activation model (NAM) in explicating revisit intention, predictions based on the merging of these theories remain sparse in the youth volunteer tourism segment. To understand revisit intention formation, a meta-analysis is performed to draw a macro conclusion using prosocial studies as a representative of volunteer tourism in investigating the predictive power of the aforementioned-merged theories. Subsequently, latent growth curve modeling is applied to extend the understanding of tourist type identification to volunteer tourism research. The introduction of NAM into TPB marginally adds value to predictive power.

Methode und Evidenzqualität

Studientyp: Studie

Risk of Bias: unclear

Evidenzgrad: B

Key Findings

Evidence-Fill Queue: Findings werden aus Volltext, Abstract und Review-Notizen konsolidiert.

Effektgrößen / Outcomes

Evidence-Fill Queue: Effektgrößen und Outcomes werden aus Volltext-Extraktionen priorisiert.

Conversion-Implikationen

Evidence-Fill Queue: Conversion-Implikationen werden nur ausgespielt, wenn Mechanismus, Kontext und Messgröße ableitbar sind.

Limitationen

Evidence-Fill Queue: Limitationen werden aus Risk-of-Bias-, Sample- und Methodikfeldern ergänzt.

Verknüpfte Konzepte

Unterstützte Claims

FAQ

Worum geht es in dieser Studie?

Predicting the revisit intention of volunteer tourists using the merged model between the theory of planned behavior and norm activation model: Despite the importance of the theory of planned behavior (TPB) and norm activation model (NAM) in explicating revisit intention, predictions based on the merging of these theories remain sparse in the youth volunteer tourism segment. To understand revisit intention formation, a meta-analysis is performed to draw a macro conclusion using prosocial studies as a representative of volunteer tourism in investigating the predictive power of the aforementioned-merged theories. Subsequently, latent growth curve modeling is applied to extend the understanding of tourist type identification to volunteer tourism research. The introduction of NAM into TPB marginally adds value to predictive power. Evidenzgrad B, Risk of Bias unclear.

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