Abstract

The existing literature on population immobility, especially immobility associated with climate change-related disaster, is very finite. Consequently, the understanding of population immobility in disaster-prone areas is still low. This article adds to the literature on population immobility by modeling decision to stay in the disaster-prone area amongst fishermen community in Tambak Lorok, Semarang. The survey was conducted among the residents of Kampung Tambak Lorok Semarang, which is prone to 3 disasters simultaneously i.e. sea level rise, land subsidence, and tidal inundation. The study sample was 235 heads of households selected using proportional sampling area technique. This study constructs three factors: place valuation, disaster adaptation, and stakeholder intervention. These three factors used as explanatory variables for modeling the decision to stay. The study employed a Confirmatory Factor Analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyses the data and examines the logical relationship between those three factors in staying decision. Our results suggest that the place valuation and disaster adaptation significantly influence the decision to stay, while stakeholder interventions are influential but not significant. We concur that residents with positive place valuation and good disaster adaptation tend to stay although threatening by disaster. More broadly, this study contributes to our understanding of population immobility in the disaster-prone area by modeling the decision to stay.

Details

Title
Modeling (Im) mobility: the decision to stay in disaster prone area amongs fishermen community in Semarang
Author
Amin, Choirul; Sukamdi; Rijanta
Section
Disaster Mitigation & Management
Publication year
2019
Publication date
2019
Publisher
EDP Sciences
ISSN
25550403
e-ISSN
22671242
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2301796121
Copyright
© 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.