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Predicting Factors Affecting the Intention to Prepare for Mitigation of Man-Made Fire Disasters in Chonburi Province, Thailand: An Integration of Structural Equation Modeling and Artificial Neural Network Hybrid Approach
News regarding different man-made fire disasters has been increasing for the past few years, especially in Thailand. Despite the prominent fire in Chonburi Province, Thailand, the intention to prepare has been widely underexplored. This study aimed to predict factors affecting the intention to prepare for the mitigation of man-made fire disasters in Chonburi Province, Thailand. A total of 366 valid responses through convenience sampling were utilized in this study that produced 20,496 datasets. With the 20,496 datasets, structural equation modeling and artificial neural network hybrid were utilized to analyze several factors under the extended and integrated protection motivation theory and the theory of planned behavior. Factors such as geographic perspective, fire perspective, government response, perceived severity, response cost, perceived vulnerability, perceived behavioral control, subjective norm, and attitude were evaluated simultaneously to measure the intention to prepare for a fire disaster. The results showed that geographic perspective, subjective norm, and fire experience were the most important factors affecting the intention to prepare. Other factors were significant with perceived behavioral control as the least important. In addition, the results showed how the region is prone to man-made fire disasters and that the government should consider mitigation plans to highlight the safety of the people in Chonburi Province, Thailand. This study is considered the first complete study that analyzed behavioral intention to prepare for the mitigation of man-made fire disasters in the Chonburi Province region of Thailand. The results of this study could be utilized by the government as a foundation to create mitigation plans for the citizens of Thailand. Finally, the findings of this study may be applied and extended to measure the intention to prepare for other man-made fire disasters worldwide.
Predicting Factors Affecting the Intention to Prepare for Mitigation of Man-Made Fire Disasters in Chonburi Province, Thailand: An Integration of Structural Equation Modeling and Artificial Neural Network Hybrid Approach
News regarding different man-made fire disasters has been increasing for the past few years, especially in Thailand. Despite the prominent fire in Chonburi Province, Thailand, the intention to prepare has been widely underexplored. This study aimed to predict factors affecting the intention to prepare for the mitigation of man-made fire disasters in Chonburi Province, Thailand. A total of 366 valid responses through convenience sampling were utilized in this study that produced 20,496 datasets. With the 20,496 datasets, structural equation modeling and artificial neural network hybrid were utilized to analyze several factors under the extended and integrated protection motivation theory and the theory of planned behavior. Factors such as geographic perspective, fire perspective, government response, perceived severity, response cost, perceived vulnerability, perceived behavioral control, subjective norm, and attitude were evaluated simultaneously to measure the intention to prepare for a fire disaster. The results showed that geographic perspective, subjective norm, and fire experience were the most important factors affecting the intention to prepare. Other factors were significant with perceived behavioral control as the least important. In addition, the results showed how the region is prone to man-made fire disasters and that the government should consider mitigation plans to highlight the safety of the people in Chonburi Province, Thailand. This study is considered the first complete study that analyzed behavioral intention to prepare for the mitigation of man-made fire disasters in the Chonburi Province region of Thailand. The results of this study could be utilized by the government as a foundation to create mitigation plans for the citizens of Thailand. Finally, the findings of this study may be applied and extended to measure the intention to prepare for other man-made fire disasters worldwide.
Predicting Factors Affecting the Intention to Prepare for Mitigation of Man-Made Fire Disasters in Chonburi Province, Thailand: An Integration of Structural Equation Modeling and Artificial Neural Network Hybrid Approach
Poonyawat Kusonwattana (author) / Ardvin Kester S. Ong (author) / Yogi Tri Prasetyo (author) / Klint Allen Mariñas (author) / Nattakit Yuduang (author) / Thanatorn Chuenyindee (author) / Kriengkrai Thana (author) / Satria Fadil Persada (author) / Reny Nadlifatin (author) / Kirstien Paola E. Robas (author)
2022
Article (Journal)
Electronic Resource
Unknown
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