Analysis of socio-economic factors affecting coastal community preparedness using structural equation modeling

Preparedness refers to the actions taken before a disaster to ensure an effective response. In disaster-related research, quantitative studies typically focus on observing direct correlations and regressions. However, directly measuring preparedness can be challenging. To comprehensively analyze variables, researchers often turn to Structural Equation Modeling (SEM), a powerful alternative. SEM is particularly useful when examining complex relationships among multiple variables. In a study focused on coastal communities in the cities of Banda Aceh, Mataram, and Ambon, the SEM method was applied using secondary data. The research considered one endogenous latent variable called “preparedness” and two exogenous latent variables related to social and economic factors, which are involving a collective of 932 participants. The results from the SEM method using GOFI criteria indicated that socio-economic factors significantly influenced coastal community readiness, with an R-squared value of 56.5%.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-08-21
DOI
https://doi.org/10.1051/itmconf/20246701051/pdf
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
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0.00
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article

Analysis of socio-economic factors affecting coastal community preparedness using structural equation modeling

Springer Link (Chiba Institute of Technology)
Mycorrhizal Fungi and Plant Interactions
article

Analysis of socio-economic factors affecting coastal community preparedness using structural equation modeling

article en

Abstract

Preparedness refers to the actions taken before a disaster to ensure an effective response. In disaster-related research, quantitative studies typically focus on observing direct correlations and regressions. However, directly measuring preparedness can be challenging. To comprehensively analyze variables, researchers often turn to Structural Equation Modeling (SEM), a powerful alternative. SEM is particularly useful when examining complex relationships among multiple variables. In a study focused on coastal communities in the cities of Banda Aceh, Mataram, and Ambon, the SEM method was applied using secondary data. The research considered one endogenous latent variable called “preparedness” and two exogenous latent variables related to social and economic factors, which are involving a collective of 932 participants. The results from the SEM method using GOFI criteria indicated that socio-economic factors significantly influenced coastal community readiness, with an R-squared value of 56.5%.

Springer Link (Chiba Institute of Technology)
Climate action
Openalex Percentile: Top 57%
Mycorrhizal Fungi and Plant Interactions
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