Evidence map›Paper›PMID 37990111›Full record

ArticleScientific reports2023

Economic implications of autonomous adaptation of firms and households in a resource-rich coastal city.

Alessandro Taberna, Tatiana Filatova, Stefan Hochrainer-Stigler, Igor Nikolic, Brayton Noll

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Alessandro TabernaDepartment of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands. a.taberna@tudelft.nl.ORCID http://orcid.org/0000-0002-0207-4148
Tatiana FilatovaDepartment of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands. t.filatova@tudelf.nl.
Stefan Hochrainer-StiglerInternational Institute for Applied Systems Analysis, Schlossplatz 1, 2361, Laxenburg, Austria.
Igor NikolicDepartment of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands.
Brayton NollDepartment of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands.
Delft University of Technology · NLInternational Institute for Applied Systems Analysis · AT

Funding

EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas " Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013)) 758014EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 758014
6 · The paper itself

Abstract

Climate change intensifies the likelihood of extreme flood events worldwide, amplifying the potential for compound flooding. This evolving scenario represents an escalating risk, emphasizing the urgent need for comprehensive climate change adaptation strategies across society. Vital to effective response are models that evaluate damages, costs, and benefits of adaptation strategies, encompassing non-linearities and feedback between anthropogenic and natural systems. While flood risk modeling has progressed, limitations endure, including inadequate stakeholder representation and indirect risks such as business interruption and diminished tax revenues. To address these gaps, we propose an innovative version of the Climate-economy Regional Agent-Based model that integrates a dynamic, rapidly expanding agglomeration economy populated by interacting households and firms with extreme flood events. Through this approach, feedback loops and cascading effects generated by flood shocks are delineated within a socio-economic system of boundedly-rational agents. By leveraging extensive behavioral data, our model incorporates a risk layering strategy encompassing bottom-up and top-down adaptation, spanning individual risk reduction to insurance. Calibrated to resemble a research-rich coastal megacity in China, our model demonstrates how synergistic adaptation actions at all levels effectively combat the mounting climate threat. Crucially, the integration of localized risk management with top-down approaches offers explicit avenues to address both direct and indirect risks, providing significant insights for constructing climate-resilient societies.

Identifiers

PMID37990111
PMCPMC10663627
OpenAlexW4388866170

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.