Household adaptation intentions to earthquake risks in rural China

Yu, Junlei; Sim, Timothy; Guo, Chunlan; Han, Ziqiang; Lau, Jocelyn; Su, Guiwu

doi:10.1016/j.ijdrr.2019.101253

Cited by 12 publications

(7 citation statements)

References 22 publications

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“…The advantage of vulnerability mapping is helpful to determine the action for reducing vulnerability. Since the study area is located in rural, earthquake impacts can lead to an increase in poverty due to destroyed household assets and livelihood [12]. In addition, this mapping will be a useful tool for disaster management for regional planning of future activities in the area, as well as their coping capacities and resilience of risk elements [13,14].…”

Section: Resultsmentioning

confidence: 99%

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Earthquake vulnerability mapping in the at-risk Opak Fault, Sengon Village, Central Java, Indonesia

et al. 2020

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This study aims to perform vulnerability assessment in a detailed scale at villages adjacent to Opak fault, Central Java. The study took place in Sengon Village, Prambanan District, Klaten Regency. Sengon is located near Opak fault zone and experienced tremendous disaster in 2006. The method for vulnerability assessment in earthquake hazard used in this study involves three criteria, i.e. physical, social, and economic with various indicators within. The mapping unit are hamlet units, which more detailed than village unit. The result of physical vulnerability assessment in Sengon village was dominated by a medium level of vulnerability. Sengon village has clustered settlement characteristics and this is a type of rural village in Indonesia. The advantage of clustered settlements is that there is a large evacuation site in this case paddy fields. The socio-economic vulnerability indicates that the majority of Sengon village are informal workers. This will have a big impact if an earthquake occurs because there will be many people lose their income. The total vulnerability assessment shows that all levels of vulnerability are distributed similarly. The advantage of this study is helpful to determine the action for reducing vulnerability especially in the at-risk of earthquake hazard.

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Section: Resultsmentioning

confidence: 99%

“…For a rural area like Sengon village, disaster insurance program is the best way for reducing poverty. However, the problem is their willingness to buy [12]. Rural people might be not interested in disaster insurance.…”

Section: Resultsmentioning

confidence: 99%

Earthquake vulnerability mapping in the at-risk Opak Fault, Sengon Village, Central Java, Indonesia

et al. 2020

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“…Similarly, Osberghaus 65 observed in Germany that homeowners’ likelihood of insuring against flood damage increases with historical damage and the prospect of future damage. Yu et al 70 found that factors such as households' risk perception, education level, and profession significantly affect the intention to adapt to earthquake risks in rural China.…”

Section: Discussionmentioning

confidence: 99%

Uncovering the factors that affect earthquake insurance uptake using supervised machine learning

Ng’ombe,

Addai,

Mzyece

et al. 2023

Sci Rep

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The escalating threat of natural disasters to public safety worldwide underlines the crucial role of effective environmental risk management tools, such as insurance. This is particularly evident in the case of earthquakes that occurred in Oklahoma between 2011 and 2020, which were linked to wastewater injection, underscoring the need for earthquake insurance. In this regard, from a survey of 812 respondents in Oklahoma, USA, we used supervised machine learning techniques (i.e., logit, ridge, least absolute shrinkage and selection operator (LASSO), decision tree, and random forest classifiers) to identify the factors that influence earthquake insurance uptake and to predict individuals who would acquire earthquake insurance. Our findings reveal that influential factors that affect earthquake insurance uptake include demographic factors such as older age, male gender, race, and ethnicity. These were found to significantly influence the decision to purchase earthquake insurance. Additionally, individuals residing in rental properties were less likely to purchase earthquake insurance, while longer residency in Oklahoma had a positive influence. Past experience of earthquakes was also found to positively influence the decision to purchase earthquake insurance. Both decision trees and random forests demonstrated good predictive capabilities for identifying earthquake insurance uptake. Notably, random forests exhibited higher precision and robustness, emerging as an encouraging choice for earthquake insurance modeling and other classification problems. Empirically, we highlight the importance of insurance as an environmental risk management tool and emphasize the need for awareness and education on earthquake insurance as well as the use of supervised machine learning algorithms for classification problems.

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“…On the one hand, the income of one breadwinner is often insufficient for a rural household, and rural mothers are therefore pushed to find employment in the cities (Guo & Shen, 2014). Disasters in rural areas have also caused parents to move to the cities to make a living (Yu et al, 2019). The education level of rural mothers has generally increased, and they may no longer wish to do agricultural work in the countryside like their parents or in-laws (Guo & Shen, 2016).…”

Section: Understanding Rural Migrant Working Mothers In Chinamentioning

confidence: 99%

Moving together or left behind? An examination of rural migrant working mothers' childcare strategies in the cities

Guo,

Lin,

Zhu

2024

Child

Self Cite

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BackgroundIn China, an increasing number of rural mothers participate in urban labour markets, but little is known about their decisions regarding childcare while living in these cities. Why do some rural mothers migrate to the cities with their children, whereas others leave their children behind in the countryside?MethodsThis study analysed 1852 samples from the 2016 China Migrant Dynamic Survey of rural migrant mothers collected in the Pearl River Delta (PRD). These mothers were registered with agricultural hukou outside of the PRD and had at least one child under 18 years of age.ResultsThe results indicated that 57.8% of these mothers migrated together with their children. Rural migrant mothers who were self‐employed, had a higher level of household income on a log10 scale and had a longer duration of migration were more willing to adopt closely performing motherhood than rural migrant mothers who were not self‐employed. Additionally, rural working mothers who were intra‐provincial migrants and had a smaller number of children were more likely to bring their children to the cities than rural working mothers who were inter‐provincial migrants.ConclusionsThis study works to strengthen the understanding of rural migrant working mothers' childcare strategies, provide insights for future policy studies and contribute to evidence‐based recommendations for policymakers regarding internal rural‐to‐urban migration, migrant women and the wellbeing of the families of migrants.

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Household adaptation intentions to earthquake risks in rural China

Cited by 12 publications

References 22 publications

Earthquake vulnerability mapping in the at-risk Opak Fault, Sengon Village, Central Java, Indonesia

Earthquake vulnerability mapping in the at-risk Opak Fault, Sengon Village, Central Java, Indonesia

Uncovering the factors that affect earthquake insurance uptake using supervised machine learning

Moving together or left behind? An examination of rural migrant working mothers' childcare strategies in the cities

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