Fuzzy Cognitive Mapping to Uncover Vital Urban Functions and Their Interdependencies for Disaster Recovery

Soheil Mohammadi, Silvia De Angeli (), Fabrizio Bruno, Ilenia Spadaro, Giorgio Boni, Serena Cattari and Francesca Pirlone
Additional contact information
Soheil Mohammadi: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa
Silvia De Angeli: LOTERR - Centre de Recherche en Géographie - UL - Université de Lorraine, LIEC - Laboratoire Interdisciplinaire des Environnements Continentaux - INSU - CNRS - Institut national des sciences de l'Univers - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa
Fabrizio Bruno: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa, Scuola Universitaria Superiore IUSS Pavia, Palazzo del Broletto, Piazza Vittoria 15, 27100 Pavia, Italy
Ilenia Spadaro: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa
Giorgio Boni: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa
Serena Cattari: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa
Francesca Pirlone: DICCA - Dipartimento di Ingegneria Civile, Chimica e Ambientale [Genova] - UniGe - Università degli studi di Genova = University of Genoa

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Abstract: Engaging stakeholders in disaster recovery planning helps identify recovery needs accurately and integrates diverse perspectives into planning procedures. This study presents a quali-quantitative participatory method for identifying the urban functions that must be preserved to initiate the recovery process and ensure the rapid restoration of the entire urban system. The method involves evaluating the relative importance of different functions and analyzing their interdependencies through participatory fuzzy cognitive mapping (FCM) with local stakeholders. The inclusion of diverse stakeholders facilitates precise need assessment, fosters dynamic information exchange and promotes innovative, user-centred, bottom-up interventions that better reflect the realities of the affected communities. The approach was tested in a case study conducted in Sanremo, Italy, as part of broader research aimed at developing a decision support system to expedite recovery processes and enhance urban resilience. The participatory FCM session in Sanremo identified essential functions beyond emergency services, including supermarkets, educational services and pharmacies, centred around the temporary shelter function, which emerged as pivotal during the recovery process. A critical analysis of the FCM-based approach highlights its benefits and offers insights for further strengthening participatory planning in disaster recovery. | IntroductionInvolving stakeholders in disaster recovery planning helps ensure that recovery priorities are accurately identified, promotes meaningful dialogue among participants and brings together diverse viewpoints that can strengthen the overall planning process (Chandrasekhar et al. 2014). Understanding the needs and capacities of the community integrates various viewpoints into recovery plans, promoting the development of resilience in disaster-affected communities (

Keywords: stakeholder involvement; participatory planning; natural hazard disasters; graph analysis; FCM; FCM graph analysis natural hazard disasters participatory planning stakeholder involvement (search for similar items in EconPapers)
Date: 2025-08-10
Note: View the original document on HAL open archive server: https://hal.univ-lorraine.fr/hal-05245052v1
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Published in Journal of Contingencies and Crisis Management, 2025, 33 (3), ⟨10.1111/1468-5973.70071⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05245052

DOI: 10.1111/1468-5973.70071

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