Uptake and implementation of Nature-Based Solutions: An analysis of barriers using Interpretive Structural Modeling.

Autor: Sarabi S; Information Systems in the Built Environment (ISBE) Group, Department of Built Environment, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands. Electronic address: s.ershad.sarabi@tue.nl., Han Q; Information Systems in the Built Environment (ISBE) Group, Department of Built Environment, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands., Romme AGL; Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands., de Vries B; Information Systems in the Built Environment (ISBE) Group, Department of Built Environment, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands., Valkenburg R; Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands., den Ouden E; Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, the Netherlands.
Jazyk: angličtina
Zdroj: Journal of environmental management [J Environ Manage] 2020 Sep 15; Vol. 270, pp. 110749. Date of Electronic Publication: 2020 Jun 12.
DOI: 10.1016/j.jenvman.2020.110749
Abstrakt: Cities increasingly have to find innovative ways to address challenges arising from climate change and urbanization. Nature-based solutions (NBS) have been gaining attention as multifunctional solutions that may help cities to address these challenges. However, the adoption and implementation of these solutions have been limited due to various barriers. This study aims to identify a taxonomy of dominant barriers to the uptake and implementation of NBS and their relationships. Fifteen barriers are identified from the literature and expert interviews and then ranked through a questionnaire. Interpretive Structural Modeling (ISM) serves to identify the mutual interdependencies among these barriers, which results in a structural model of six levels. Subsequently, Cross-impact matrix multiplication applied to classification (MICMAC analysis) is used to classify the barriers into four categories. The results suggest that political, institutional and knowledge-related barriers are the most dominant barriers to NBS. Cities that intend to apply NBS can draw on these findings, especially by more effectively prioritizing and managing their actions.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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