Data · dataset · 2025
SCALAR household climate change adaptation and resilience survey
Listed in DANS Data Station Social Sciences and Humanities and ODISSEI Portal — shown once because both records carry DOI 10.17026/dans-x9h-nj3w
This panel survey contains data from households located in large, coastal urban centers in the United States (Miami, Houston, and New Orleans greater areas), the Netherlands (Rotterdam greater area, Zeeland province), China (Shanghai greater area), and Indonesia (Jakarta greater area, other cities in Java).
Description
The last fifth wave of the SCALAR surveys has also covered an additional country: the United Kingdom (London, Norfolk/Suffolk coast, Somerset).
China was omitted from the fifth survey wave due to the operational reasons. The surveys are focused on soliciting information on households' socio-economic background, perceptions, adaptive capacities, self-assessed resilience, place attachment, social influence, policy and other factors influencing individual climate change adaptation behavior (here contextualized to floods). The SCALAR project team has developed the questionnaires grounded in theories and best practices from the past survey literature.
Read the rest (12 more)
The surveys were conducted online by YouGov and the data presented are from identical, translated questions in the respective languages of each country. The first survey was launched in late March 2020, and a subsequent survey followed every six months for the following year and a half; in October 2020, April 2021, and November 2021. The spacing was specifically designed to allow sufficient time for the households to realize their adaptation intentions, yet still be in frequent enough intervals to encourage continued household participation.
The fifth wave was conduced in July-August 2023. In this archive, you will find a subset of the data collected for each survey; 20 households in each country, for all five waves of responses. Authors contributions: B.N., T.F. and A.N. designed the questionnaires for waves 1-4 of the survey.
T.F. and T.W. designed the questionnaires for wave 5 of the survey. T.F. developed the goals of the surveys, its academic scope and format, and provided academic advice for B.N. and T.W. PhD theses. The development of the questionnaire and the analysis of the data for waves 1-4 constitute the core of the PhD project of B.N. The development of the questionnaire and the analysis of the data for wave 5 is part of the PhD project of T.W. The design, implementation and analysis of the survey was possible thanks to the ERC ‘SCALAR’ project developed and led by T.F. We are thankful to the funding from European Research Council project ‘SCALAR: Scaling up behavior and autonomous adaptation for macro models of climate change damage assessment’ (grant agreement no. 758014) under the European Union’s Horizon 2020 Research and Innovation Program.
Related publications: PhD Thesis of Dr. Brayton Noll (2023): repository.tudelft.nl/islandora/object/uuid%3A0d49cb3e-6dd8-4a9e-abc6-b847de938aea?collection=research Noll, B., Filatova, T., Need, A, de Vries, P. (2023) ‘Uncertainty in individual risk judgments associates with vulnerability and curtailed climate adaptation’, Journal of Environmental Management, 325, 116462, pubmed.ncbi.nlm.nih.gov/36272292/ Noll, B., T.Filatova, A.Need (2022) ‘One and done?
Exploring linkages between households’ intended adaptations to climate-induced floods’, Risk Analysis, 1-19, doi.org/10.1111/risa.13897 Noll B., Filatova, T., Need, A. & Taberna, A. (2021) ‘Contextualizing cross-national patterns in household climate change adaptation’, Nature Climate Change doi.org/10.1038/s41558-021-01222-3 This panel survey contains data from households located in large, coastal urban centers in the United States (Miami, Houston, and New Orleans greater areas), the Netherlands (Rotterdam greater area, Zeeland province), China (Shanghai greater area), and Indonesia (Jakarta greater area, other cities in Java).
The last fifth wave of the SCALAR surveys has also covered an additional country: the United Kingdom (London, Norfolk/Suffolk coast, Somerset). China was omitted from the fifth survey wave due to the operational reasons. The surveys are focused on soliciting information on households' socio-economic background, perceptions, adaptive capacities, self-assessed resilience, place attachment, social influence, policy and other factors influencing individual climate change adaptation behavior (here contextualized to floods).
The SCALAR project team has developed the questionnaires grounded in theories and best practices from the past survey literature. The surveys were conducted online by YouGov and the data presented are from identical, translated questions in the respective languages of each country. The first survey was launched in late March 2020, and a subsequent survey followed every six months for the following year and a half; in October 2020, April 2021, and November 2021.
The spacing was specifically designed to allow sufficient time for the households to realize their adaptation intentions, yet still be in frequent enough intervals to encourage continued household participation. The fifth wave was conduced in July-August 2023. In this archive, you will find a subset of the data collected for each survey; 20 households in each country, for all five waves of responses.
Authors contributions: B.N., T.F. and A.N. designed the questionnaires for waves 1-4 of the survey. T.F. and T.W. designed the questionnaires for wave 5 of the survey. T.F. developed the goals of the surveys, its academic scope and format, and provided academic advice for B.N. and T.W. PhD theses.
The development of the questionnaire and the analysis of the data for waves 1-4 constitute the core of the PhD project of B.N. The development of the questionnaire and the analysis of the data for wave 5 is part of the PhD project of T.W. The design, implementation and analysis of the survey was possible thanks to the ERC ‘SCALAR’ project developed and led by T.F. We are thankful to the funding from European Research Council project ‘SCALAR: Scaling up behavior and autonomous adaptation for macro models of climate change damage assessment’ (grant agreement no. 758014) under the European Union’s Horizon 2020 Research and Innovation Program.
Related publications: PhD Thesis of Dr. Brayton Noll (2023): repository.tudelft.nl/islandora/object/uuid%3A0d49cb3e-6dd8-4a9e-abc6-b847de938aea?collection=research Noll, B., Filatova, T., Need, A, de Vries, P. (2023) ‘Uncertainty in individual risk judgments associates with vulnerability and curtailed climate adaptation’, Journal of Environmental Management, 325, 116462, pubmed.ncbi.nlm.nih.gov/36272292/ Noll, B., T.Filatova, A.Need (2022) ‘One and done?
Exploring linkages between households’ intended adaptations to climate-induced floods’, Risk Analysis, 1-19, doi.org/10.1111/risa.13897 Noll B., Filatova, T., Need, A. & Taberna, A. (2021) ‘Contextualizing cross-national patterns in household climate change adaptation’, Nature Climate Change doi.org/10.1038/s41558-021-01222-3
Links
Where it is published
- Dataverse dataset page ssh.datastations.nl/dataset.xhtml?persistentId=doi%3A10.17026%2FDANS-X9H-NJ3W ↗
landing page · from ssh datastations nl
- Dataverse dataset page portal.odissei.nl/dataset.xhtml?persistentId=doi%3A10.17026%2FDANS-X9H-NJ3W ↗
landing page · from portal odissei nl
- DOI doi.org/10.17026/dans-x9h-nj3w ↗
DOI / persistent id · from ssh datastations nl
Catalogue records · 2
- Dataverse API ssh.datastations.nl/api/datasets/:persistentId/?persistentId=doi%3A10.17026%2FDANS… ↗
metadata API · from ssh datastations nl
- Dataverse API portal.odissei.nl/api/datasets/:persistentId/?persistentId=doi%3A10.17026%2FDANS… ↗
metadata API · from portal odissei nl
Topics
- Stated by source
- Earth and Environmental Sciences · Earth and Environmental Sciences · Social Sciences · Social Sciences
- From keywords
- Earth & Environmental Science · Earth & Environmental Science · Humanities · Ocean & Atmospheric Science · Ocean & Atmospheric Science · Psychology & Behavioral Science · Psychology & Behavioral Science · Social Science · Social Science
- Inferred from text
- Climate change impacts and adaptation 73%
Provenance · 2 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DANS Data Station Social Sciences and Humanities | doi:10.17026/DANS-X9H-NJ3W | 8 d ago | JSON v1 |
| ODISSEI Portal | doi:10.17026/DANS-X9H-NJ3W | 5 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4101 | enrichment · ssh datastations nl | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:psychology-behavioral | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:psychology-behavioral | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| created_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| description | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /description |
| publication_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| title | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /name |
| updated_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| version_label | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 |