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 prepa...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Sustainability 2022-11, Vol.14 (22), p.15442
Hauptverfasser: Kusonwattana, Poonyawat, Ong, Ardvin Kester S, Prasetyo, Yogi Tri, Mariñas, Klint Allen, Yuduang, Nattakit, Chuenyindee, Thanatorn, Thana, Kriengkrai, Persada, Satria Fadil, Nadlifatin, Reny, Robas, Kirstien Paola E
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 22
container_start_page 15442
container_title Sustainability
container_volume 14
creator Kusonwattana, Poonyawat
Ong, Ardvin Kester S
Prasetyo, Yogi Tri
Mariñas, Klint Allen
Yuduang, Nattakit
Chuenyindee, Thanatorn
Thana, Kriengkrai
Persada, Satria Fadil
Nadlifatin, Reny
Robas, Kirstien Paola E
description 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.
doi_str_mv 10.3390/su142215442
format Article
fullrecord <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2739478627</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A747188699</galeid><sourcerecordid>A747188699</sourcerecordid><originalsourceid>FETCH-LOGICAL-c371t-ba80fd655ccc19a5752f43b7b16d7685427c7e7146097fb84595a12600feba8d3</originalsourceid><addsrcrecordid>eNpVks9O3DAQxq2qlUALp76ApZ6qNtTOPye9RVsWVmJpVeAcOc44OzTYi-0UeNc-TM2mqsA-jPXN7_vGhyHkPWcnWVazL37ieZryIs_TN-QwZYInnBXs7Yv3ATn2_pbFk2W85uUh-fPDQY8qoBnoSqpgnaeN1jArYQt0bQKYgNbQYGmkd9IB1dbRDQYc5L5jNd1Ik2xkD3SFsf8NvfQBYhgautxa000Oo9v-RqPgM73eShyl6b_SxuwnDO5_0lVwkwqTkyM9vZ9meWN7GJ9_FD20cQE1KozAJey5SwgP1v2i50-dwwjsds5KtT0i77QcPRz_qwtyszq9Xp4nF9_P1svmIlGZ4CHpZMV0XxaFUorXshBFqvOsEx0ve1FWRZ4KJUDwvGS10F2VF3UheVoypiF6-2xBPsy5cez9BD60t3ZyJo5sU5HVuajKWBfkZKYGOUKLRtvgpIq3hztU1oDGqDciF7yqyrqOho-vDJEJ8BgGOXnfrq9-vmY_zaxy1nsHut05vJPuqeWsfV6P9sV6ZH8B-5evEw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2739478627</pqid></control><display><type>article</type><title>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</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Kusonwattana, Poonyawat ; Ong, Ardvin Kester S ; Prasetyo, Yogi Tri ; Mariñas, Klint Allen ; Yuduang, Nattakit ; Chuenyindee, Thanatorn ; Thana, Kriengkrai ; Persada, Satria Fadil ; Nadlifatin, Reny ; Robas, Kirstien Paola E</creator><creatorcontrib>Kusonwattana, Poonyawat ; Ong, Ardvin Kester S ; Prasetyo, Yogi Tri ; Mariñas, Klint Allen ; Yuduang, Nattakit ; Chuenyindee, Thanatorn ; Thana, Kriengkrai ; Persada, Satria Fadil ; Nadlifatin, Reny ; Robas, Kirstien Paola E</creatorcontrib><description>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.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su142215442</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Behavior ; Datasets ; Disasters ; Earthquakes ; Economic development ; Emergency management ; Emergency preparedness ; Fire hazards ; Mitigation ; Modelling ; Motivation ; Multivariate statistical analysis ; Neural networks ; Psychological research ; Structural equation modeling ; Sustainability ; Variables ; Wildfires</subject><ispartof>Sustainability, 2022-11, Vol.14 (22), p.15442</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-ba80fd655ccc19a5752f43b7b16d7685427c7e7146097fb84595a12600feba8d3</citedby><cites>FETCH-LOGICAL-c371t-ba80fd655ccc19a5752f43b7b16d7685427c7e7146097fb84595a12600feba8d3</cites><orcidid>0000-0002-8141-1957 ; 0000-0001-5196-8562 ; 0000-0002-5089-0537 ; 0000-0003-3535-9657 ; 0000-0001-9284-9826</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Kusonwattana, Poonyawat</creatorcontrib><creatorcontrib>Ong, Ardvin Kester S</creatorcontrib><creatorcontrib>Prasetyo, Yogi Tri</creatorcontrib><creatorcontrib>Mariñas, Klint Allen</creatorcontrib><creatorcontrib>Yuduang, Nattakit</creatorcontrib><creatorcontrib>Chuenyindee, Thanatorn</creatorcontrib><creatorcontrib>Thana, Kriengkrai</creatorcontrib><creatorcontrib>Persada, Satria Fadil</creatorcontrib><creatorcontrib>Nadlifatin, Reny</creatorcontrib><creatorcontrib>Robas, Kirstien Paola E</creatorcontrib><title>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</title><title>Sustainability</title><description>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.</description><subject>Behavior</subject><subject>Datasets</subject><subject>Disasters</subject><subject>Earthquakes</subject><subject>Economic development</subject><subject>Emergency management</subject><subject>Emergency preparedness</subject><subject>Fire hazards</subject><subject>Mitigation</subject><subject>Modelling</subject><subject>Motivation</subject><subject>Multivariate statistical analysis</subject><subject>Neural networks</subject><subject>Psychological research</subject><subject>Structural equation modeling</subject><subject>Sustainability</subject><subject>Variables</subject><subject>Wildfires</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpVks9O3DAQxq2qlUALp76ApZ6qNtTOPye9RVsWVmJpVeAcOc44OzTYi-0UeNc-TM2mqsA-jPXN7_vGhyHkPWcnWVazL37ieZryIs_TN-QwZYInnBXs7Yv3ATn2_pbFk2W85uUh-fPDQY8qoBnoSqpgnaeN1jArYQt0bQKYgNbQYGmkd9IB1dbRDQYc5L5jNd1Ik2xkD3SFsf8NvfQBYhgautxa000Oo9v-RqPgM73eShyl6b_SxuwnDO5_0lVwkwqTkyM9vZ9meWN7GJ9_FD20cQE1KozAJey5SwgP1v2i50-dwwjsds5KtT0i77QcPRz_qwtyszq9Xp4nF9_P1svmIlGZ4CHpZMV0XxaFUorXshBFqvOsEx0ve1FWRZ4KJUDwvGS10F2VF3UheVoypiF6-2xBPsy5cez9BD60t3ZyJo5sU5HVuajKWBfkZKYGOUKLRtvgpIq3hztU1oDGqDciF7yqyrqOho-vDJEJ8BgGOXnfrq9-vmY_zaxy1nsHut05vJPuqeWsfV6P9sV6ZH8B-5evEw</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Kusonwattana, Poonyawat</creator><creator>Ong, Ardvin Kester S</creator><creator>Prasetyo, Yogi Tri</creator><creator>Mariñas, Klint Allen</creator><creator>Yuduang, Nattakit</creator><creator>Chuenyindee, Thanatorn</creator><creator>Thana, Kriengkrai</creator><creator>Persada, Satria Fadil</creator><creator>Nadlifatin, Reny</creator><creator>Robas, Kirstien Paola E</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-8141-1957</orcidid><orcidid>https://orcid.org/0000-0001-5196-8562</orcidid><orcidid>https://orcid.org/0000-0002-5089-0537</orcidid><orcidid>https://orcid.org/0000-0003-3535-9657</orcidid><orcidid>https://orcid.org/0000-0001-9284-9826</orcidid></search><sort><creationdate>20221101</creationdate><title>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</title><author>Kusonwattana, Poonyawat ; Ong, Ardvin Kester S ; Prasetyo, Yogi Tri ; Mariñas, Klint Allen ; Yuduang, Nattakit ; Chuenyindee, Thanatorn ; Thana, Kriengkrai ; Persada, Satria Fadil ; Nadlifatin, Reny ; Robas, Kirstien Paola E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c371t-ba80fd655ccc19a5752f43b7b16d7685427c7e7146097fb84595a12600feba8d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Behavior</topic><topic>Datasets</topic><topic>Disasters</topic><topic>Earthquakes</topic><topic>Economic development</topic><topic>Emergency management</topic><topic>Emergency preparedness</topic><topic>Fire hazards</topic><topic>Mitigation</topic><topic>Modelling</topic><topic>Motivation</topic><topic>Multivariate statistical analysis</topic><topic>Neural networks</topic><topic>Psychological research</topic><topic>Structural equation modeling</topic><topic>Sustainability</topic><topic>Variables</topic><topic>Wildfires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kusonwattana, Poonyawat</creatorcontrib><creatorcontrib>Ong, Ardvin Kester S</creatorcontrib><creatorcontrib>Prasetyo, Yogi Tri</creatorcontrib><creatorcontrib>Mariñas, Klint Allen</creatorcontrib><creatorcontrib>Yuduang, Nattakit</creatorcontrib><creatorcontrib>Chuenyindee, Thanatorn</creatorcontrib><creatorcontrib>Thana, Kriengkrai</creatorcontrib><creatorcontrib>Persada, Satria Fadil</creatorcontrib><creatorcontrib>Nadlifatin, Reny</creatorcontrib><creatorcontrib>Robas, Kirstien Paola E</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kusonwattana, Poonyawat</au><au>Ong, Ardvin Kester S</au><au>Prasetyo, Yogi Tri</au><au>Mariñas, Klint Allen</au><au>Yuduang, Nattakit</au><au>Chuenyindee, Thanatorn</au><au>Thana, Kriengkrai</au><au>Persada, Satria Fadil</au><au>Nadlifatin, Reny</au><au>Robas, Kirstien Paola E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>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</atitle><jtitle>Sustainability</jtitle><date>2022-11-01</date><risdate>2022</risdate><volume>14</volume><issue>22</issue><spage>15442</spage><pages>15442-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su142215442</doi><orcidid>https://orcid.org/0000-0002-8141-1957</orcidid><orcidid>https://orcid.org/0000-0001-5196-8562</orcidid><orcidid>https://orcid.org/0000-0002-5089-0537</orcidid><orcidid>https://orcid.org/0000-0003-3535-9657</orcidid><orcidid>https://orcid.org/0000-0001-9284-9826</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2071-1050
ispartof Sustainability, 2022-11, Vol.14 (22), p.15442
issn 2071-1050
2071-1050
language eng
recordid cdi_proquest_journals_2739478627
source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Behavior
Datasets
Disasters
Earthquakes
Economic development
Emergency management
Emergency preparedness
Fire hazards
Mitigation
Modelling
Motivation
Multivariate statistical analysis
Neural networks
Psychological research
Structural equation modeling
Sustainability
Variables
Wildfires
title 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
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T12%3A15%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predicting%20Factors%20Affecting%20the%20Intention%20to%20Prepare%20for%20Mitigation%20of%20Man-Made%20Fire%20Disasters%20in%20Chonburi%20Province,%20Thailand:%20An%20Integration%20of%20Structural%20Equation%20Modeling%20and%20Artificial%20Neural%20Network%20Hybrid%20Approach&rft.jtitle=Sustainability&rft.au=Kusonwattana,%20Poonyawat&rft.date=2022-11-01&rft.volume=14&rft.issue=22&rft.spage=15442&rft.pages=15442-&rft.issn=2071-1050&rft.eissn=2071-1050&rft_id=info:doi/10.3390/su142215442&rft_dat=%3Cgale_proqu%3EA747188699%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2739478627&rft_id=info:pmid/&rft_galeid=A747188699&rfr_iscdi=true