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

Citra S. Ongkowijoyo (School of Architecture and Built Environment, Deakin University, Geelong, Australia)
Hemanta Doloi (Faculty of Architecture, Building and Planning, University of Melbourne, Victoria, Australia)
Anthony Mills (School of Architecture and Built Environment, Deakin University, Geelong, Australia)

International Journal of Disaster Resilience in the Built Environment

ISSN: 1759-5908

Article publication date: 14 October 2019

Issue publication date: 30 October 2019

127

Abstract

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.

Keywords

Citation

Ongkowijoyo, C.S., Doloi, H. and Mills, A. (2019), "Participatory-based risk impact propagation and interaction pattern analysis using social network analysis", International Journal of Disaster Resilience in the Built Environment, Vol. 10 No. 5, pp. 363-378. https://doi.org/10.1108/IJDRBE-06-2017-0041

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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