Simulation modeling of operation and coordination of agencies involved in post-disaster response and recovery

Sharif, Shahab Valaei; Moshfegh, Peyman Habibi; Kashani, Hamed

doi:10.1016/j.ress.2023.109219

Cited by 11 publications

(4 citation statements)

References 59 publications

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“…The role of the organization in this study was found more in open donation activities, holding prayers together, and distributing logistical assistance. Through training and simulation, it can be known the responsibility and role of institutions to reduce the impact of disasters [ 47 ] A centralized control from government elements or institutions is needed for successful disaster risk management [ 48 ]. This strategy is also supported by research results which state that cooperative disaster simulations are able to build a systematic framework in disaster management [ 49 ].…”

Section: Discussionmentioning

confidence: 99%

Social resilience and disaster resilience: A strategy in disaster management efforts based on big data analysis in Indonesian's twitter users

Khusna,

Sumarmi,

Bachri

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Social resilience and disaster resilience: A strategy in disaster management efforts based on big data analysis in Indonesian's twitter users

Khusna,

Sumarmi,

Bachri

et al. 2023

Heliyon

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“…The review of the literature showed that few studies have incorporated price expectations into the behaviour of actors involved in land and housing markets. By more closely linking the modelled behaviours of the market actors to their real-world behaviours, the simulation dynamics will link more closely to real-world dynamics, ideally improving the simulation platforms (Sterman 2000;Valaei Sharif et al 2023). To facilitate the replication of the proposed models, we produced Python code blocks that model the proforma and alternative expectation formation strategies, which could be utilized by any modelling team striving to represent expectation formation in agent-based market models (please refer to the Supplementary Materials for the model code).…”

Section: Discussionmentioning

confidence: 99%

Understanding the Effects of Market Volatility on Profitability Perceptions of Housing Market Developers

Valaei Sharif,

Parker,

Waddell

et al. 2023

JRFM

Self Cite

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Drastic shifts in prices and housing market trends in recent years, representing shocks to the housing system, have led many residential developers to pause or cancel their projects. In the already heated housing markets of the Greater Toronto Area (GTA), these supply frictions can have ramifications for affordability. Our study formulates a standardized “proforma” model of the profitability of a hypothetical condominium project in the city of Toronto, Canada, scheduled between 2019 to 2023, to explore the combined effect of developers’ price expectations and market volatility on developers’ decisions. Using the proposed proforma, we first identify the key drivers of development decisions. We then evaluate the impact of the expectation formation of key factors influencing perceived development profitability, including construction costs, sales prices, and interest rates, on the financial feasibility of potential developments. The results highlight that boundedly rational expectations can cause variations in profitability perceptions and potentially reverse development decisions in volatile market conditions. Our results highlight the sources of risk and uncertainty in development decisions, facilitating the recognition of possible solutions to mitigate these risks and increase affordable housing supplies. The proposed model can also enhance the realism of decision models in agent-based representations of land and housing markets.

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“…Distance to hospitals (Figure 2h); Relief immediately after an earthquake, especially on the first day, is very important for rescue operations and minimizing casualties. This parameter is essential for post-earthquake disaster management (Sharif, et al 2023). Availability of healthcare services, such as hospitals, helps mitigate the effects of emergencies and provides medical assistance and hospitalization services.…”

Section: Data Acquisitionmentioning

confidence: 99%

An Innovative Fusion of New Smile Random Forest and Fuzzy Analysis for Comprehensive Seismic hazard Assessment: A Case Study in Mersin, Türkiye

Yakar,

Kamran,

Alptekin

et al. 2024

Preprint

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This study addresses the critical issue of earthquake vulnerability in Mersin, Türkiye, given its susceptibility to seismic threats due to factors such as high population density, substandard constructions, narrow roads, and urban congestion. The research employs a comprehensive approach, utilizing a multi-criteria evaluation model and a novel hybrid random forest model to estimate the city's vulnerability proportionally. Spatial data encompassing physical, population, building quality, accessibility, relief, and hazard facilities were incorporated into the assessment. Weights for these components were determined through the Analytic Network Process (ANP) model, and a hybrid approach using Linear, Small, and Large functions calculated distances between options with fuzzy-fication. Resampling 10m x 10m maps addressed variations in spatial resolutions, while an 80% training set and 20% test set mitigated overfitting concerns. Expert opinions were pivotal in establishing criteria and sub-criteria for determining safe areas for temporary accommodation, rescue centers, and a seismic vulnerability map. The Smile Random Forest hybrid model was instrumental in generating these outcomes. Notably, the vulnerability map indicated that 24% of Mersin's areas fall within the high and very high vulnerability range. Key contributors to vulnerability included Geology factors (26.4), Land use (16.1), Epicenters (13.1), and slope and DEM (6.4). These findings underscore the imperative for strategic planning and interventions to minimize earthquake-induced damage in Mersin.

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Simulation modeling of operation and coordination of agencies involved in post-disaster response and recovery

Cited by 11 publications

References 59 publications

Social resilience and disaster resilience: A strategy in disaster management efforts based on big data analysis in Indonesian's twitter users

Social resilience and disaster resilience: A strategy in disaster management efforts based on big data analysis in Indonesian's twitter users

Understanding the Effects of Market Volatility on Profitability Perceptions of Housing Market Developers

An Innovative Fusion of New Smile Random Forest and Fuzzy Analysis for Comprehensive Seismic hazard Assessment: A Case Study in Mersin, Türkiye

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