German Josephine D, Ong Ardvin Kester S, Redi Anak Agung Ngurah Perwira, Prasetyo Yogi Tri, Robas Kirstien Paola E, Nadlifatin Reny, Chuenyindee Thanatorn
School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines.
Industrial Engineering Department, Sampoerna University, Jakarta, 12780, Indonesia.
Environ Dev. 2023 Mar;45:100823. doi: 10.1016/j.envdev.2023.100823. Epub 2023 Feb 20.
The need for stability in the economy for world development has been a challenge due to the COVID-19 pandemic. In addition, the increase of natural disasters and their aftermath have been increasing causing damages to infrastructure, the economy, livelihood, and lives in general. This study aimed to determine factors affecting the intention to donate for victims of Typhoon Odette, a recent super typhoon that hit the Philippines leading to affect 38 out of 81 provinces of the most natural disaster-prone countries. Determining the most significant factor affecting the intention to donate may help in increasing the engagement of donations among other people to help establish a more stable economy to heighten world development. With the use of deep learning neural network, a 97.12% accuracy was obtained for the classification model. It could be deduced that when donors understand and perceive both severity and vulnerability to be massive and highly damaging, then a more positive intention to donate to victims of typhoons will be observed. In addition, the influence of other people, the holiday season when the typhoon happened, and the media as a platform have greatly contributed to heightening the intention to donate and control over the donor's behavior. The findings of this study could be applied and utilized by government agencies and donation platforms to help engage and promote communication among donors. Moreover, the framework and methodology considered in this study may be extended to evaluate intention, natural disasters, and behavioral studies worldwide.
由于新冠疫情，世界发展所需的经济稳定面临挑战。此外，自然灾害及其后果不断增加，对基础设施、经济、生计乃至总体生命造成破坏。本研究旨在确定影响为台风“奥黛特”受害者捐款意愿的因素。“奥黛特”是最近袭击菲律宾的一场超级台风，该国81个省份中有38个是自然灾害高发地区。确定影响捐款意愿的最重要因素，可能有助于提高其他人的捐款参与度，以建立更稳定的经济，促进世界发展。通过使用深度学习神经网络，分类模型的准确率达到了97.12%。可以推断，当捐赠者认识到并感知到严重性和脆弱性都很大且破坏性很强时，就会观察到更积极的向台风受害者捐款的意愿。此外，他人的影响、台风发生时的节假日以及作为平台的媒体，都极大地促进了捐款意愿的提高，并对捐赠者的行为产生了控制作用。本研究的结果可供政府机构和捐赠平台应用和利用，以帮助促进捐赠者之间的参与和沟通。此外，本研究中考虑的框架和方法可能会扩展到全球范围内对意愿、自然灾害和行为研究的评估。
