Determinants of villagers’ satisfaction with post-disaster reconstruction: Evidence from surveys ten years after the Wenchuan earthquake

Yibin Ao, Jinglin Zhong, Zijun Zhang, Lili Han, Yan Wang*, Yunfeng Chen, T. Wang*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
53 Downloads (Pure)

Abstract

Residents’ satisfaction with post-disaster reconstruction in earthquake-stricken areas directly affects their quality of life, which cannot be ignored in post-disaster reconstruction. More than 10 years after the Wenchuan earthquake, we took ten randomly selected villages in the five areas hardest-hit by the Wenchuan earthquake as research objects and obtained 483 valid completed questionnaires. The villagers were randomly sampled and descriptive statistical analysis, factor analysis, and ordered logistic regression were used to explore the factors and relationships influencing villagers’ satisfaction with post-disaster reconstruction in Wenchuan earthquake-stricken areas. The results show that: 1) the more rural residents know about the post-disaster reconstruction, the greater their level of satisfaction; 2) the more the annual income of families increases after resettlement, the greater the satisfaction of rural residents with the post-disaster reconstruction; 3) six public factors, namely the village committee acts as, housing construction quality, public service, policy of benefiting farmers, cultural environment, and hardware environment, all significantly positively affect residents’ overall satisfaction with post-earthquake reconstruction. This study thus enriches the theory of residents’ satisfaction studies and the practice of post-earthquake reconstruction.
Original languageEnglish
Article number952700
Number of pages14
JournalFrontiers in Environmental Science
Volume10
DOIs
Publication statusPublished - 2022

Keywords

  • earthquake-stricken area
  • post-disaster reconstruction
  • satisfaction analysis
  • factorial analysis
  • ordered logistic regression

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