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
Abstract
:1. Introduction
2. Conceptual Framework
3. Methodology
3.1. Participants
3.2. Questionnaire
3.3. Structural Equation Modeling
3.4. Artificial Neural Network
4. Results
4.1. Structural Equation Modeling Results
4.2. Artificial Neural Network Results
5. Discussion
5.1. Theoretical and Practical Contribution
5.2. Limitations and Future Research
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Category | n | % |
---|---|---|---|
Gender | Male | 176 | 48.1 |
Female | 190 | 51.9 | |
Age | 15–24 years old | 87 | 23.8 |
25–34 years old | 60 | 16.4 | |
35–44 years old | 58 | 15.8 | |
45–54 years old | 66 | 18.0 | |
55–64 years old | 84 | 23.0 | |
More than 64 | 11 | 3.00 | |
Education | Junior High School | 10 | 2.70 |
Senior High School | 51 | 13.9 | |
Technical–Vocation | 32 | 8.70 | |
College | 208 | 56.8 | |
Master’s Degree | 57 | 15.6 | |
PhD Degree | 8 | 2.20 | |
Monthly Salary/Allowance | Less than THB 10,000 Baht | 91 | 24.9 |
THB 10,001–20,000 | 51 | 13.9 | |
THB 20,001–30,000 | 59 | 16.1 | |
THB 30,001–40,000 | 57 | 15.6 | |
THB 40,001–50,000 | 26 | 7.10 | |
THB 50,001–60,000 | 31 | 8.50 | |
More than THB 60,000 | 51 | 13.9 | |
Are you enrolled in fire insurance? | Yes | 191 | 52.2 |
No | 175 | 47.8 |
Construct | Items | Measurement Items | References |
---|---|---|---|
Fire Perspective | FE1 | I think workplaces and houses should prepare for fire and smoke control protocols. | Kurata et al. [8] |
FE2 | I think workplaces and houses should have fire alarms. | Kurata et al. [8] | |
FE3 | I think workplaces and houses should preparing for fire evacuation plans. | Kurata et al. [8] | |
FE4 | I think workplaces and houses should preparing for fire safety policies. | Kurata et al. [8] | |
FE5 | I think workplaces and houses should holding fire insurance policies. | Kurata et al. [8] | |
FE6 | I think workplaces and houses should preparing for fire precautions system. | Kurata et al. [8] | |
Geographic Perspective | GP1 | I think the government should classify fire risk areas. | Kuhlicke et al. [31] |
GP2 | I think the government should monitor the risky areas. | Kuhlicke et al. [31] | |
GP3 | I think the government should manage the control on fuel consumption and usage. | Kuhlicke et al. [31] | |
GP4 | I think that wildlife is a serious threat that may cause fire. | Kuhlicke et al. [31] | |
Government Response | GR1 | I think the government should pay remediation for fire victims. | Kurata et al. [8] |
GR2 | I think the government should establish a fire foundation. | Kurata et al. [8] | |
GR3 | I think the government should practice fire evacuation plans. | Kurata et al. [8] | |
GR4 | I think the government should managing policies on renewable energy, fossil fuels, and coal. | Kurata et al. [8] | |
GR5 | I think the government should establish reforestation campaigns for response as emission reduction. | Kurata et al. [8] | |
Perceived Severity | PS1 | I find fire as a serious hazard which causes accident. | Ong et al. [4] |
PS2 | I find that fires can lead to property lost. | Ong et al. [4] | |
PS3 | I find that fire can lead to serious injuries. | Ong et al. [4] | |
PS4 | I find that fire causes severe danger compared to other accidents. | Ong et al. [4] | |
PS5 | I think sanction against breach of fire regulations are important. | Ong et al. [4] | |
Perceived Vulnerability | PV1 | I think I am vulnerable to fire. | Prasetyo et al. [36] |
PV2 | I think my area is very vulnerable to fire. | Prasetyo et al. [36] | |
PV3 | I think my family is vulnerable to fire. | Prasetyo et al. [36] | |
PV4 | I think my friends are vulnerable to fire. | Prasetyo et al. [36] | |
Response Cost | RC1 | I think we should fine sanction against breach of fire regulations. | Gumasing et al. [9] |
RC2 | I think we should claim loss fee from fire insurance companies. | Gumasing et al. [9] | |
RC3 | I think we should pay remediation for fire victims. | Gumasing et al. [9] | |
Perceived Behavioral Control | PB1 | I can find the fire alarm and push it when needed. | Ong et al. [4] |
PB2 | I can call emergency numbers to report fire incidents. | Ong et al. [4] | |
PB3 | I can perform first aid to others if they are injured. | Ong et al. [4] | |
PB4 | I can find fire extinguishers in my workplace. | Ong et al. [4] | |
PB5 | I can soak my handkerchief and cover my nose when there is fire. | Ong et al. [4] | |
PB6 | I think I can mitigate immediately the fire in my area. | Ong et al. [4] | |
PB7 | I can control myself and perform low crawl on knees to find an emergency exit. | Ong et al. [4] | |
PB8 | I will use a ladder instead of an elevator when fire happens. | Ong et al. [4] | |
PB9 | I can evacuate from fire accidents. | Ong et al. [4] | |
Subjective Norm | SN1 | I think people in the industrial estate is likely to have fire hazards. | Prasetyo et al. [36] |
SN2 | I think my family is highly likely to feel fire hazards. | Prasetyo et al. [36] | |
SN3 | I think my role and status is likely to influence fire hazards. | Prasetyo et al. [36] | |
SN4 | I think my workplace is likely to cause fire hazards. | Kurata et al. [8] | |
SN5 | I think my lifestyle is likely to influence fire hazards. | Kurata et al. [8] | |
SN6 | People around me think that I should prepare for fire hazards. | Kurata et al. [8] | |
SN7 | I feel that people important to me think that I should prepare for fire hazards. | Ong et al. [28] | |
SN8 | My family influenced me to think that I should prepare for fire hazards. | Ong et al. [28] | |
SN9 | The government influenced me to think that I should prepare for fire hazards. | Ong et al. [28] | |
Attitude Towards Behavior | AT1 | I feel fire is a danger to the community. | Kurata et al. [8] |
AT2 | I feel fire is a danger to wildlife. | Kurata et al. [8] | |
AT3 | I feel fire is a danger to people and properties. | Kurata et al. [8] | |
AT4 | I feel people in community are not aware of the fire. | Kurata et al. [8] | |
Intention to Prepare | IP1 | I prefer not to use old electronic appliances to prevent fires. | Ong et al. [4] |
IP2 | I keep chemical substances in their own places to prevent fire. | Ong et al. [4] | |
IP3 | I maintain circuits and electronic system to prevent fires. | Ong et al. [4] | |
IP4 | I keep oils away from electronic sources to prevent fires. | Ong et al. [4] | |
IP5 | I keep fuels away from electronic sources to prevent fires. | Ong et al. [4] | |
IP6 | I keep children away from electronic sources to prevent fires. | Ong et al. [4] | |
IP7 | I turn off electronic sources when not in use to prevent fires. | Ong et al. [4] |
Variable | Item | Mean | StD | Factor Loading | |
---|---|---|---|---|---|
Initial | Final | ||||
Fire Perspective | FE1 | 4.5000 | 0.79983 | 0.788 | 0.788 |
FE2 | 4.5874 | 0.77760 | 0.910 | 0.910 | |
FE3 | 4.5656 | 0.77270 | 0.925 | 0.924 | |
FE4 | 4.5519 | 0.76304 | 0.908 | 0.908 | |
FE5 | 4.4290 | 0.82703 | 0.789 | 0.789 | |
FE6 | 4.6311 | 0.68886 | 0.876 | 0.876 | |
Geographic Perspective | GP1 | 4.3470 | 0.81582 | 0.940 | 0.940 |
GP2 | 4.3634 | 0.81874 | 0.940 | 0.941 | |
GP3 | 4.3852 | 0.83859 | 0.828 | 0.828 | |
GP4 | 4.4454 | 0.77708 | 0.699 | 0.699 | |
Government Response | GR1 | 4.3060 | 0.88477 | 0.691 | 0.690 |
GR2 | 4.2923 | 0.91520 | 0.799 | 0.798 | |
GR3 | 4.3743 | 0.80362 | 0.882 | 0.882 | |
GR4 | 4.4098 | 0.81177 | 0.869 | 0.869 | |
GR5 | 4.3634 | 0.88002 | 0.704 | 0.704 | |
Perceived Severity | PS1 | 4.6475 | 0.73565 | 0.848 | 0.854 |
PS2 | 4.7077 | 0.69384 | 0.917 | 0.932 | |
PS3 | 4.6503 | 0.73510 | 0.887 | 0.890 | |
PS4 | 4.2131 | 0.89653 | 0.611 | 0.587 | |
PS5 | 4.4071 | 0.79094 | 0.678 | 0.661 | |
Perceived Vulnerability | PV1 | 2.5820 | 1.08165 | 0.811 | 0.809 |
PV2 | 2.4399 | 1.09065 | 0.888 | 0.896 | |
PV3 | 2.4016 | 1.07520 | 0.906 | 0.908 | |
PV4 | 2.5164 | 1.06938 | 0.833 | 0.829 | |
Response Cost | RC1 | 4.4536 | 0.74523 | 0.778 | 0.778 |
RC2 | 4.4645 | 0.78520 | 0.755 | 0.757 | |
RC3 | 4.5355 | 0.75315 | 0.764 | 0.764 | |
Perceived Behavioral Control | PB1 | 3.2104 | 1.25272 | 0.614 | 0.615 |
PB2 | 3.4590 | 1.22406 | 0.643 | 0.644 | |
PB3 | 2.8115 | 1.08032 | 0.671 | 0.672 | |
PB4 | 3.4973 | 1.28372 | 0.723 | 0.724 | |
PB5 | 3.8825 | 1.12011 | 0.726 | 0.727 | |
PB6 | 2.6066 | 1.15075 | 0.618 | 0.619 | |
PB7 | 3.3989 | 1.10262 | 0.768 | 0.769 | |
PB8 | 4.2814 | 1.00956 | 0.618 | 0.619 | |
PB9 | 3.6913 | 1.03911 | 0.732 | 0.733 | |
Subjective Norm | SN1 | 4.5847 | 0.66801 | 0.747 | 0.753 |
SN2 | 4.3470 | 0.82915 | 0.719 | 0.717 | |
SN3 | 4.5082 | 0.73926 | 0.772 | 0.773 | |
SN4 | 4.3497 | 0.82634 | 0.754 | 0.749 | |
SN5 | 4.4781 | 0.80974 | 0.765 | 0.766 | |
SN6 | 4.4208 | 0.81628 | 0.785 | 0.786 | |
SN7 | 4.4754 | 0.77862 | 0.783 | 0.785 | |
SN8 | 4.5137 | 0.74656 | 0.798 | 0.799 | |
SN9 | 4.0874 | 0.96117 | 0.604 | 0.598 | |
Attitude Towards Behavior | AT1 | 4.6093 | 0.74966 | 0.874 | 0.905 |
AT2 | 4.5956 | 0.76239 | 0.853 | 0.871 | |
AT3 | 4.6940 | 0.65318 | 0.829 | 0.816 | |
AT4 | 4.0574 | 0.89104 | 0.445 | - | |
Intention to Prepare | IP1 | 4.0137 | 1.05847 | 0.625 | 0.614 |
IP2 | 4.3115 | 0.84479 | 0.791 | 0.790 | |
IP3 | 4.4016 | 0.77981 | 0.799 | 0.804 | |
IP4 | 4.3470 | 0.86789 | 0.844 | 0.849 | |
IP5 | 4.3852 | 0.80865 | 0.832 | 0.839 | |
IP6 | 4.0765 | 0.96494 | 0.700 | 0.695 | |
IP7 | 4.3415 | 0.84450 | 0.714 | 0.716 |
Goodness of Fit Measures of SEM | Parameter Estimates | Minimum Cut-Off | Suggested by |
---|---|---|---|
Incremental Fit Index (IFI) | 0.896 | >0.80 | Gefen et al. [53] |
Tucker–Lewis Index (TLI) | 0.887 | >0.80 | Gefen et al. [53] |
Comparative Fit Index (CFI) | 0.895 | >0.80 | Gefen et al. [53] |
Goodness of Fit Index (GFI) | 0.860 | >0.80 | Gefen et al. [53] |
Adjusted Goodness of Fit Index (AGFI) | 0.833 | >0.80 | Gefen et al. [53] |
Root Mean Square Error (RMSEA) | 0.060 | <0.07 | Steiger [54] |
No | Variable | Direct Effect | p-Value | Indirect Effect | p-Value | Total Effect | p-Value |
---|---|---|---|---|---|---|---|
1 | GR → RC | 0.591 | 0.005 | - | - | 0.591 | 0.005 |
2 | FE → RC | 0.585 | 0.023 | - | - | 0.585 | 0.023 |
3 | FE → PS | 0.481 | 0.006 | - | - | 0.481 | 0.006 |
4 | GP → PS | 0.326 | 0.009 | - | - | 0.326 | 0.009 |
5 | PV → PB | 0.257 | 0.004 | - | - | 0.257 | 0.004 |
6 | RC → PB | 0.343 | 0.009 | - | - | 0.343 | 0.009 |
7 | RC → SN | 0.512 | 0.013 | - | - | 0.512 | 0.013 |
8 | RC → AT | 0.629 | 0.005 | - | - | 0.629 | 0.005 |
9 | PS → SN | 0.431 | 0.013 | - | - | 0.431 | 0.013 |
10 | PS → AT | 0.257 | 0.021 | - | - | 0.257 | 0.021 |
11 | PB → IP | 0.180 | 0.043 | - | - | 0.180 | 0.043 |
12 | SN → IP | 0.602 | 0.009 | - | - | 0.602 | 0.009 |
13 | AT → IP | 0.296 | 0.042 | - | - | 0.296 | 0.042 |
14 | GR → PB | - | - | 0.203 | 0.003 | 0.203 | 0.003 |
15 | GR → AT | - | - | 0.303 | 0.003 | 0.303 | 0.003 |
16 | GR → SN | - | - | 0.371 | 0.005 | 0.371 | 0.005 |
17 | GR → IP | - | - | 0.270 | 0.007 | 0.270 | 0.007 |
18 | FE → PB | - | - | 0.201 | 0.012 | 0.201 | 0.012 |
19 | FE → AT | - | - | 0.507 | 0.011 | 0.507 | 0.011 |
20 | FE → SN | - | - | 0.491 | 0.011 | 0.491 | 0.011 |
21 | FE → IP | - | - | 0.363 | 0.018 | 0.363 | 0.018 |
22 | GP → AT | - | - | 0.140 | 0.003 | 0.140 | 0.003 |
23 | GP → SN | - | - | 0.084 | 0.002 | 0.084 | 0.002 |
24 | GP → IP | - | - | 0.065 | 0.002 | 0.065 | 0.002 |
25 | PV → IP | - | - | 0.020 | 0.014 | 0.020 | 0.014 |
26 | PS → IP | - | - | 0.198 | 0.019 | 0.198 | 0.019 |
Variables | Importance | Normalized Importance |
---|---|---|
Geographic Perspective | 0.221 | 100 |
Subjective Norm | 0.203 | 92.3 |
Fire Experience | 0.200 | 91.8 |
Perceived Severity | 0.194 | 87.6 |
Attitude Towards Behavior | 0.188 | 85.2 |
Response Cost | 0.484 | 83.4 |
Perceived Behavioral Control | 0.170 | 76.9 |
Government Response | 0.167 | 75.7 |
Perceived Vulnerability | 0.109 | 49.3 |
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Kusonwattana, P.; Ong, A.K.S.; Prasetyo, Y.T.; Mariñas, K.A.; Yuduang, N.; Chuenyindee, T.; Thana, K.; Persada, S.F.; Nadlifatin, R.; Robas, K.P.E. 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. Sustainability 2022, 14, 15442. https://doi.org/10.3390/su142215442
Kusonwattana P, Ong AKS, Prasetyo YT, Mariñas KA, Yuduang N, Chuenyindee T, Thana K, Persada SF, Nadlifatin R, Robas KPE. 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. Sustainability. 2022; 14(22):15442. https://doi.org/10.3390/su142215442
Chicago/Turabian StyleKusonwattana, Poonyawat, Ardvin Kester S. Ong, Yogi Tri Prasetyo, Klint Allen Mariñas, Nattakit Yuduang, Thanatorn Chuenyindee, Kriengkrai Thana, Satria Fadil Persada, Reny Nadlifatin, and Kirstien Paola E. Robas. 2022. "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" Sustainability 14, no. 22: 15442. https://doi.org/10.3390/su142215442
APA StyleKusonwattana, P., Ong, A. K. S., Prasetyo, Y. T., Mariñas, K. A., Yuduang, N., Chuenyindee, T., Thana, K., Persada, S. F., Nadlifatin, R., & Robas, K. P. E. (2022). 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. Sustainability, 14(22), 15442. https://doi.org/10.3390/su142215442