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Participatory-based risk impact propagation and interaction pattern analysis using social network analysis

Version 2 2024-06-03, 16:32
Version 1 2019-11-14, 10:27
journal contribution
posted on 2024-06-03, 16:32 authored by CS Ongkowijoyo, H Doloi, Anthony MillsAnthony Mills
© 2019, Emerald Publishing Limited. Purpose: This paper aims to develop a novel risk analysis model that uses both participatory and computerized techniques to capture and model the dynamic of risk impact propagation and interaction pattern. Design/methodology/approach: In this research, an integrated model, applying modified participatory method and novel dichotomize procedure in the perspectives of social network topological analysis, is developed. Findings: Based on the analysis output, it is found that; (i) the risk propagation is characterized by its dynamic and non-linear impact pattern, and (ii) the risk interaction is distinguished based on the degree of connectedness between various risks. Research limitations/implications: This research assumes that the risk impact propagation and interaction pattern within the risk network are static. Further research is required to analyze the risk network in dynamic circumstances. Practical implications: This research contributes in delivering practical tools that could potentially provide a further path for developing mitigation strategy and policies that seek to address the complexity of risk phenomena, and thus enhance community resilience. Social implications: This research reveals some underlying patterns of how the risk impact propagation and interaction pattern are structured. Thus, it can help decision-makers make formal arrangements of particular urban infrastructure (UI) governance visible toward building risk plan and mitigation strategies. Originality/value: This research contributes to filling the risk management knowledge gap. It is suggested that analyzing risk using a network approach is suited to capture the intricate processes that shape the complexity of UI risk structural network. By validating the model, this research shows the applicability and capability of the model to improve both the RA accuracy and decision making effectiveness towards risk mitigation plan and strategy.

History

Journal

International Journal of Disaster Resilience in the Built Environment

Volume

10

Pagination

363-378

Location

Bingley, Eng.

ISSN

1759-5908

eISSN

1759-5916

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Issue

5

Publisher

Emerald Publishing

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