TY - JOUR
T1 - Predicting factors influencing intention to donate for super Typhoon Odette victims
T2 - A structural equation model forest classifier approach
AU - Kurata, Yoshiki B.
AU - Prasetyo, Yogi Tri
AU - Ong, Ardvin Kester S.
AU - Cahigas, Maela Madel Labso
AU - Robas, Kirstien Paola E.
AU - Nadlifatin, Reny
AU - Persada, Satria Fadil
AU - Chuenyindee, Thanatorn
AU - Thana, Kriengkrai
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/10/15
Y1 - 2022/10/15
N2 - 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. Despite 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 Typhoon Odette, perceived severity, and perceived vulnerability led to a very high intention to donate 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 victims 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.
AB - 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. Despite 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 Typhoon Odette, perceived severity, and perceived vulnerability led to a very high intention to donate 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 victims 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.
KW - Intention to donate
KW - Protection motivation theory
KW - Random forest classifier
KW - Structural equation modeling
KW - Super typhoon
KW - Theory of planned behavior
UR - http://www.scopus.com/inward/record.url?scp=85137643413&partnerID=8YFLogxK
U2 - 10.1016/j.ijdrr.2022.103287
DO - 10.1016/j.ijdrr.2022.103287
M3 - Article
AN - SCOPUS:85137643413
SN - 2212-4209
VL - 81
JO - International Journal of Disaster Risk Reduction
JF - International Journal of Disaster Risk Reduction
M1 - 103287
ER -