Predicting factors influencing intention to donate for super Typhoon Odette victims: A structural equation model forest classifier approach

Super Typhoon Odette has been reported as one of the world's most devastating natural disasters in 2021. It caused massive damages and casualties in 10 out of 17 regions in the Philippines. De-spite the available platforms for donation, a massive amount is still needed to help mitigate the aftermath of the typhoon. This study aimed to predict factors influencing intention to donate to Super Typhoon Odette victims that happened during the holiday season in 2021 by integrating protection motivation theory and extending the theory of planned behavior. An online self-administered survey was administered and 1031 respondents voluntarily participated. Structural Equation Modeling (SEM) and Random Forest Classifier (RFC) showed that understanding Ty-phoon Odette, perceived severity, and perceived vulnerability led to a very high intention to do-nate to Typhoon Odette victims. It was seen that when people understand how severe the natural disaster is and how vulnerable the affected area is, they would have a high intention to help through donations. This is the first study that evaluated the intention to donate to typhoon vic-tims that happened during the 2021 holiday season. The results of this study could be utilized to promote different platforms to collect more donations for the victims of the Typhoon Odette in the Philippines. Finally, this study's new use of SEM and RFC can evaluate the intention to donate to massive natural disaster aftermath worldwide.