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Modeling the effects of labor on housing reconstruction: A system perspective
Abstract
The quick recovery and rebuilding of the housing stock after disaster (natural or man-made) is critical for an affected region, from the socio-economic perspective. The recovery efforts demand a considerable amount of time and resources. An efficient emergency management response system needs to be designed, with the intention of allowing a smooth post disaster reconstruction operation. This paper seeks to analyze the impacts of a disaster on labor for housing recovery and rebuilding of a devastated region. A System Dynamics (SD) model is proposed to mimic and explore the issue of labor force (namely, construction workers) management. The model describes the behavior of labor in the housing restoration process. It provides insights on the interactions between the labor force and the housing inventory management.
... Delays and their representation are key concerns in model development. Kumar et al. (2015) mentioned the importance of the awareness of delays and flexibility in work schedules in policy design. Berariu et al. (2016b) and Besiou et al. (2011Besiou et al. ( , 2014) focused on the delays expected due to infrastructure damage at the post-disaster stage. ...
... Similarly, Diaz et al. (2015) suggested that further research should use actual data for their model's experiments and serve as a solid background for future predictions in the context of housing recovery. These examples highlight the challenges of obtaining adequate data to inform and test model development in various contexts (Hernantes et al., 2013;Hiltz et al., 2013;Kumar et al., 2015). Therefore, big data methods and processes for collecting HO data should be adopted in future studies. ...
... Diaz et al. (2015Diaz et al. ( , 2019,Kumar et al. (2015),Lawrence et al. (2022) Debris managementKim et al. (2018),Ramezankhani and Najafiyazdi (2008), Magalhães et al. (2020) Power companies and energy services Hernantes et al. (2013), Powell et al. (2016), Armenia et al. (2018) Information and communication services Suarez (2015), Hiltz et al. (2013), Diedrichs et al. (2016), Han et al. (2008), Zhong (2018) Healthcare services Ager et al. (2015), Arboleda et al. (2007), Babaei and Shahanaghi (2018), Su and Jin (2008), Khanmohammadi et al. (2018), Powell et al. (2018), Li et al. (2019), Xu et al. (2015), Voyer et al. (2016), Erkayman et al. (2022), Gonçalves et al. (2022), Rong et al. (2022), Van Oorschot et al. (2022) Shortages of facility services in residential, commercial and industrial facilities Hwang et al. (2015, 2016) Interactions across multiple service sectors Santella et al. (2009), Hernantes et al. (2013), Song et al. (2018)Source: ...
Purpose
Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.
Design/methodology/approach
To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.
Findings
The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.
Practical implications
As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.
Originality/value
While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.
... As post-disaster recovery activities ramp up, the complexity of coordinating resources become largely complex due to the large number of sources and waste caused by the effects of the catastrophic event, response and emergency activities Kumar et al., 2015). Number of significant studies offer the analysis on Katrina highlighting a variety of interesting and useful perspectives. ...
... Number of significant studies offer the analysis on Katrina highlighting a variety of interesting and useful perspectives. Kumar et al. (2015) analyze the impacts of a disaster on labor for housing recovery and rebuilding of a devastated region using a SD model to simulate and explore the issue of labor force management. ...
... As pointed out byKumar et al (2015), the stock of Post-Disaster Labor is amplified by the hiring rate set by the authority that centralizes employment and diminished by the quit rate. This rate is reliant on the average period of employment, which is significantly dependent on the circumstance of theeconomy and its stability (Antoni and Jahn 2009). ...
Severe catastrophic natural disasters adversely affect housing stock and regional capacity to build and repair houses, with unfavorable impacts on the business continuity of industrial and business organizations resting on that affected community. Restoring industrial capacity and business continuity is crucial for the organizations’ survival in the aftermath of a disaster but the process takes time while the affected region faces an unexpected surge in the demand for housing. Modeling approaches largely used in the supply chain management realm may support humanitarian logistics and policy-making by providing a testbed in which supply chain elements of the recovery process can be examined before implementing. This research presents a system dynamics model that considers the problem of housing recovery from the demand and supply perspective and provides significant insights for policymakers into how the production of permanent housing depends upon the uncertainties and feedback effects of material and labor. In order to highlight its utility, a hypothetical scenario in which a hurricane hits the U.S. Hampton Roads region, which is a major population center along the mid-Atlantic coast, has been configured by using actual data collected from both governmental and academic sources.
... Recovery models have been developed for generic systems (Nojima and Kameda 1992), power systems (Ouyang and Dueñas-Osorio 2012;Çaǧnan et al. 2006), water systems (Tabucchi et al. 2010), and transportation networks (Lee and Kim 2008), as well as interdependencies among infrastructure systems (Ramachandran et al. 2015;Setola et al. 2012;Min et al. 2011;Lee et al. 2007;Kujawski 2006). A growing number of models have been developed to understand housing recovery (Burton et al. 2017;Eid and El-Adaway 2017;Nejat and Ghosh 2016;Kumar et al. 2015;Huling and Miles 2015;Grinberger and Felsenstein 2014;Nejat and Damnjanovic 2012;Chang 2011, 2006). Comparably fewer models of community recovery-used here to refer to comprehensive models that represent multiple sectors of community and infrastructure-have been researched (Lin and Wang 2017;Grinberger and Felsenstein 2014;Frazier et al. 2013;Chang 2011, 2006). ...
... Time is not represented algorithmically in either of the preceding machine learning models, only housing recovery decisions. Kumar et al. (2015) used a system dynamics simulation approach to understand the influence of postevent labor supply and demand on housing recovery. Their model facilitates simulation of construction worker hiring policy scenarios and resultant changes in the labor force to understand the impact on housing production and repair. ...
... Because the recent development of Lindell's conceptual model, it has not commonly been used in the disaster recovery modeling literature. Even so, both Huling and Miles (2015) and Kumar et al. (2015) explicitly adopted the more nuanced conception of recovery provided by Lindell (2013) to guide development of their models. Conversely, a small number of reviewed models do not explicitly cite Lindell's (2013) conceptual model, but are more compatible with it than with Kates and Pijawka's (1977) (e.g., Felsenstein 2014, 2016). ...
The goal of this paper is to facilitate a community of practice for disaster recovery modeling. This community should include hazard and disaster researchers without modeling experience and modelers with no experience in hazard and disaster research, not just the growing number of researchers that have experience with both. Disaster recovery modelers should develop mutual resources such as data sets, programming libraries, documentation, and terminology. For a community of practice to function, it needs to generate and appropriate a shared repertoire of ideas, approaches, and institutional memory. A potential shared repertoire of eight complimentary recovery modeling approaches to adopt, research, and advance is laid out. The largest need for lifeline recovery modeling—the most commonly researched recovery topic—is to research how to simulate lifeline infrastructure as sociotechnical systems in comprehensive, meaningful ways. For housing recovery modeling, a major gap is the inability to simulate rental dynamics, as well as the role of race and ethnicity. Lastly, a concerted and coordinated research effort is needed to create comprehensive platforms for simulating community recovery.
... Table 1 summarizes the variables related to disasters and migratory movements found in the sample of 69 articles selected in the SLR. Disaster prevention [34,57] Disaster preparedness [26,35,38,44,58] Awareness level (AL) [35,37,44] Damage and Loss [34,35,43,62,63] Affected population (AP) [42,43,46,47,[63][64][65] Unaffected population (UAP) [42,46] Relief operation [28,36,46,47,61] Recovery operations [39,40,45,64,66,67] GAP between restorations and necessary restorations [39,40] GAP between people requiring and receiving relief [46,47] Mass migration out (MMO) [4,5,49] Press interest [35,48,59] Pressure to provide relief/recovery [46] International mobilization [26,35,65] (continued) Black market, fraud and corruption [73] Resettled Iimmigrant [54] Illegal immigrant [50,54] Socio-economic crises [4] Civil conflicts [4] Migration risks [4] Information of other immigrants [50] Desire for foreign labor [52] Politics regarding immigrants [4,[53][54][55] Pre-immigration and resettlement stressors [53] Desired foreign labor [52] Public-private partnership regarding immigrants resettlement [4] Impacts on countries receiving immigrants [4] Willingness to receive immigrants [4] Economic Impacts [4] Social security/safety impact [4] Income [4] Unemployment rate [4] Population resistance [4] These variables become even clear as they relate to each other. Thus, Sect. 3 presents the prosed CLD to detail the relations between variables. ...
... The awareness level, in turn, influences the prevention/ preparedness to new disasters, that will affect the damage that a disaster can cause. In the CLD, we use the auxiliary variable "Damage and Loss" in a general manner but, papers address besides physical injuries [42,46], some infrastructure damages such as closed/restricted roads [40,45], ports [56,66], hospitals [58], industrial facilities [39], houses [64,67], public buildings [40] and communication systems [28]. ...
The number of migrants, refugees, and asylum seekers have dramatically increased in the past few years as a result of instability, socio-economic crises, and natural and human-made disasters. This growth of migratory movements has attracted the attention of academics interested in social-impact oriented research. In this context, this paper proposes a causal loop diagram to analyze the influence of disasters in migratory movements. Based on a systematic literature review (SLR) encompassing the system dynamics method, we identify variables that relate disasters and migratory movements. Thus, we contribute to the literature by proposing a taxonomy (list of variables) and a framework (a causal loop diagram) to support decision-makers in operations management resolutions.
... Labor availability limits the ability for housing reconstruction after a disaster. Labor management model to support housing construction after a disaster (Kumar, Diaz, Behr, & Toba, 2015). Flow of materials during reconstruction . ...
... linking disaster impacts with increased economic and population vulnerability (Sodhi, 2016). Regarding dynamic complexity, generic SD models have been developed to increase learning and understanding of the effect of feedback loops, delays, and accumulation dynamics in HO such as evacuees and resources flows (Berariu et al., 2016;Diaz et al., 2015;Kumar et al., 2015) and on risk (Cooke, 2003;Rudolph & Repenning, 2002) and preparedness (Kwesi-Buor et al., 2016). ...
One of the most nefarious consequences of violent conflicts is forced displacement. Refugee crises have impacts on both the refugees’ place of origin (e.g., loss of human capital) and the places where they resettle (e.g., demands on health systems). Humanitarian information technologies (IT) can be used to collect, process and analyze information that may contribute to improving the livelihoods of refugees. This chapter summarizes the role of humanitarian IT in assisting refugees or organizations that provide services to them in the four steps of the refugee pathway: displacement (e.g., collecting information about the current situation), journey (e.g., providing information about the closest services on a map), temporary settlement (e.g., monitoring health programs of refugee camps), and permanent settlement (e.g., processing refugee resettlement in a new country).
... Labor availability limits the ability for housing reconstruction after a disaster. Labor management model to support housing construction after a disaster (Kumar, Diaz, Behr, & Toba, 2015). Flow of materials during reconstruction . ...
... linking disaster impacts with increased economic and population vulnerability (Sodhi, 2016). Regarding dynamic complexity, generic SD models have been developed to increase learning and understanding of the effect of feedback loops, delays, and accumulation dynamics in HO such as evacuees and resources flows (Berariu et al., 2016;Diaz et al., 2015;Kumar et al., 2015) and on risk (Cooke, 2003;Rudolph & Repenning, 2002) and preparedness (Kwesi-Buor et al., 2016). ...
This chapter introduces the main ideas of the System Dynamics method and discusses and illustrates its applications in Humanitarian Operations problems. Complex, unpredictable and uncontrollable conditions characterize decision-making during disasters. System Dynamics and System Thinking are useful for increasing our understanding of complex systems and their dynamic behavior, caused by feedback and accumulation structures. System dynamics has been used to model strategic resource allocation and capacity building decisions, and for policy evaluation in all phases of the disaster cycle, particularly the preparedness phase. To illustrate the application of system dynamics in humanitarian operations, a simple model is developed for determining volunteer and truck needs for water delivery after an emergency.
... Brandon [42] emphasises the necessity for different management approaches for post-disaster scenarios due to the extreme conditions under which the management intervention takes place. Since disasters mainly impact lowincome nations, swift recovery and reconstruction in these countries is crucial from a socio-economic standpoint as well [43]. There is a pressing need for further research in managing reconstruction projects to address the gaps in existing knowledge. ...
This paper seeks to identify and categorise challenges encountered in managing post-disaster re-construction projects. Literature relevant to the topic was identified using keywords from two databases—Scopus and Web of Science, and then filtered using title screening and abstract screening. Subsequently, an analysis of 66 relevant papers between 2000 and 2023 revealed a total of 223 challenges relating to post-disaster reconstruction. These were then categorised into nine groups—quality and workmanship; contractual, legislation and policy; management and collaboration; resources; community engagement and culture; financial; physical/territorial; natural causes; and other challenges. Among these nine categories, resource challenges; management and collaboration challenges; and contractual, legislation, and policy challenges emerged as notably prevalent issues. While acknowledging the unique contextual nuances of post-disaster scenarios, it is important to emphasise that the challenges identified here are general in nature,serving as a foundational resource for government and various implementing agencies to devise context-specific mitigation measures. Additionally, the research findings offer insights and directions for future research aimed at enhancing post-disaster reconstruction management, particularly in addressing gaps in reconstruction legislation, policies, and processes, as well as the lesser-explored domain of non-residential reconstruction projects. Given the increasing incidence of post-disaster projects failing to achieve their objectives, understanding and effectively addressing these possible challenges is paramount. Hence, this paper provides a comprehensive foundation for developing tailored mitigation strategies and refining management practices in post-disaster reconstruction endeavors.
... The model illustrates work behavior in housing restoration. This provides insight into the interaction between labor and labor supply [28]. ...
This research is discussing about the construction project scheduling that is integrated between the implementation time with the resources needed periodically and in total. Because, determining the time of implementation of construction is very important as a basic reference, when the commencement of work and when the work must be completed. So far, the project scheduling method that is often used by engineers is the time schedule bar chart method, S curve method, Critical Path Method (CPM) method and other methods. After that, the time schedule is developed into scheduling material procurement and manpower, but the scheduling planning system is often out of sync with the implementation time schedule, material supply schedule and manpower supply schedule, therefore construction project delays often occur due to improper supply of material and manpower. That is part of the cause of the loss, therefore there needs to be an integrated scheduling program. How to produce an integrated program is, conducting research by combining methods namely, time schedule bar chart method, S curve method, CPM method, BOW analysis, SNI analysis, statistics, and supported by 60 random sampling data of project documents, consisting of, construction drawings, BOQ, and cost budget plan. Through the process according to these methods, an integrated program will be produced. Why is it necessary to use a program that results from this research, because this program is easy to use, simply enter the building area and planned implementation time at the input layer, the implementation schedule, and the required resources, will be detected automatically, both periodically and in total. This program uses Microsoft Excel applications and is very simple. This program can only be used for scheduling residential construction projects 1 level to 2 levels, with a building area between 36 m2 to 290 m2. Cannot be used in other projects because each construction project has different characteristics.
... Note: Data derived from extraction of the demographic information in questionnaire survey Ensure funds or funding sources are readily available for reconstruction(Kumar et al., 2015;Macaskill and Guthrie, 2018) 6.19 1.075Ensure unbiased interest from either the publicAbe et al., 2018;Roosli and Collins, 2016;Roosli et al., 2018;Thayaparan et al., 2015) ...
Purpose
The purpose of this paper is to elicit the expectations for resilient post-disaster rebuilds from Caribbean project end-users. In anticipation of future climatological, meteorological, hydrological or geophysical disasters disaster, key stakeholders can articulate and incorporate strategies for resilience development, thus leading to improved end-users’ satisfaction and confidence.
Design/methodology/approach
This paper engages the results of a systematic literature review that identified 24 empirical resilience factors for post-disaster reconstruction projects. These factors informed a semi-structured questionnaire to elicit the perspectives of Caribbean end-users on a seven-point Likert scale. The quantitative analysis of both factor ranking and principal component analysis was performed to identify correlations and provides further interpretations on the desires of the end-users for resilient rebuilds.
Findings
The results presented in this paper highlight the collective perspectives on the Caribbean end-users on what they perceived to be aiding more resilient reconstruction projects. They identified reconstruction designs mindful of future hazards, policies that aid climate change mitigation, active assessment of key structures, readily available funding sources and ensuring stakeholder’s unbiased interest as the top-most empirical factors. Factor analysis suggested collaborations with inclusive training and multi-stakeholder engagement, critical infrastructure indexing and effective governance as the critical resilience development factors.
Originality/value
To the best of the authors’ knowledge, this paper is first of its kind to explore the perspective of the Caribbean people regarding disaster reconstruction projects. It addresses developmental avenues for measurement indicators towards resilience monitoring and improvement. Additionally, the perspectives can provide construction industry professionals with tools for improved operational resilience objective-setting guidance, for Caribbean construction.
... Resource management factors. It involves engaging appropriate skillsets and methods (Abe et al., 2018;Kumar et al., 2015) to minimise any rework tendencies while exploiting modern techniques to mitigate or alleviate the effects of new construction industry risks, such as congestions from urbanisation, retrofitting and climate change. Ensuring accessible funding sources are readily available (Macaskill and Guthrie, 2018), effective procurement collaborations (Johannessen et al., 2014) and the management of IJDRBE resources that also embraces waste management in all forms (Moon et al., 2017), acts as financial conservator methods. ...
Purpose
The purpose of this paper is to investigate the literature on resilience factors applied to post-disaster reconstruction projects and to develop a guiding framework to assist in their strategic selection and application.
Design/methodology/approach
A systematic review was undertaken on the literature’s account in four major bibliographic databases to elicit resilience factors contributing to improving post-disaster reconstruction projects' robustness. Through summative content analysis and open-coding of research outputs over the past decade, the factors identified informed the development of a conceptual framework that can significantly impact the built environment’s resilience development process.
Findings
The review found 24 resilience factors open-coded into five criteria groups: governance, innovations, reconstruction approaches, resource management and stakeholder expectations. While these factors have influenced reconstruction projects, the recently increased participation of clients and end-users in construction management accentuates their strategic selection and applications.
Research limitations/implications
The research focused on English language articles; therefore, any claim to a comprehensive resilience factors listing can be amiss. The framework provides a platform for developing clear measurement indicators for allocating project resources and determining resilience deficiencies.
Practical implications
Results confirm the designs and assessment of a resilient built environment extends beyond the traditional structural characteristics, but includes the ability of the integrated network of buildings and infrastructure to support the continuous delivery of the community’s social and economic services in normal and post-disaster settings.
Originality/value
The review is very specific as it attempts to develop a novel conceptual framework for guiding developers and practitioners in the application of resiliency to post-disaster reconstruction projects.
... Many quantitative studies have measured postdisaster housing recovery (or restoration) using improvement value data (Hamideh, 2015;, permit data (Lester, Perry, & Moynihan, 2014;Stevenson, Emrich, Mitchell, & Cutter, 2010), or postdisaster aerial imagery of structures (Hoshi, Murao, Yoshino, Yamazaki, & Estrada, 2014) as proxy measures. Few probabilistic or predictive models exist for housing recovery including optimizing recovery outcomes from various temporary housing solutions (El-Anwar, 2010; El-Anwar, El-Rayes, & Elnashai, 2010), a decision support system for assigning families to temporary housing units and locations (Rakes, Deane, Rees, & Fetter, 2014), an agent based model of household-based decisions to rebuild (Nejat & Damnjanovic, 2012), a least absolute shrinkage and selection operator model on household decision making (Nejat & Ghosh, 2016), material resource system dynamics model on construction material supply and labor supply (Kumar, Diaz, Behr, & Toba, 2015) for rebuilding housing, and a Markov chain model for building functionality restoration that was designed generically, but could be applied to housing functionality restoration (Lin & Wang, 2017). Most of these studies focus on the physical process of rebuilding, and on recovery of houses, as opposed to recovery of households. ...
Housing recovery is an unequal and complex process presumed to occur in four stages: emergency shelter, temporary shelter, temporary housing, and permanent housing. This work questions the four‐stage typology and examines how different types of shelter align with multiple housing recovery stages given different levels of social vulnerability. This article also presents a Markov chain model of the postdisaster housing recovery process that focuses on the experience of the household. The model predicts the sequence and timing of a household going through housing recovery, capturing households that end in either permanent housing or a fifth possible stage of failure. The probability of a household transitioning through the stages is computed using a transition probability matrix (TPM). The TPM is assembled using proposed transition probability models that vary with the social vulnerability of the household. Monte Carlo techniques are applied to demonstrate the range of sequences and timing that households experience going through the housing recovery process. A set of computational rules are established for sending a household to the fifth stage, representing a household languishing in unstable housing. This predictive model is exemplified on a virtual community, Centerville, where following a severe earthquake scenario, differences in housing recovery times exceed four years. The Centerville analysis results in nearly 5% of households languishing in unstable housing, thereby failing to reach housing recovery. These findings highlight the disparate trajectories experienced by households with different levels of social vulnerability. Recommendations are provided at the end for more equitable postdisaster recovery policies.
... It is generally accepted that predictive models of housing recovery can provide valuable insights and serve as a platform for evaluating the benefits of different mitigation actions. Many techniques have been employed in developing housing recovery models, such as linear regression (Sutley et al., 2019), system dynamics (Kumar et al., 2015), discrete event simulation (Huling and Miles, 2015), Markov chains (Lin and Wang, 2019), fuzzy-logic (De Iuliis et al., 2019), Monte Carlo simulation (Burton et al., 2017;Zeng and Zhang, 2019), and agent-based models (Grinberger and Felsenstein, 2014;Miles and Chang, 2011;Nejat and Damnjanovic, 2012). Nonetheless, there is growing agreement that housing recovery needs to be modeled in the context of the community, being influenced by infrastructural and socioeconomic factors, and constrained by the availability resources (Bilau et al., 2018;Davidson, 2015;Ellingwood et al., 2018;Lee et al., 2019;Masoomi and van de Lindt, 2018;Sutley et al., 2017). ...
A framework of agent-based models for housing recovery is presented and used to investigate post-earthquake recovery in the City of Vancouver, Canada. Housing recovery is modeled for a portfolio of buildings, contrasting with the practice of assessing the reconstruction of buildings in isolation. Thus, the presented approach better captures the effect of competition for resources, infrastructure disruptions, and socioeconomic factors on recovery. The analyses include models for damage, inspection, financing, power infrastructure, and labor/materials for repairs. The presented approach is applied to simulate the recovery of 114,832 residential buildings in 22 neighborhoods in Vancouver. Results indicate that recovery after a strong earthquake will take more than three years. The density of old and rented buildings, and the income and immigration status of the homeowners are shown to be good predictors of the speed of recovery for a neighborhood. Mitigation measures are compared and it is shown that retrofitting the most physically vulnerable buildings or doubling the available workforce are effective at reducing housing recovery times. It is demonstrated that the equity in recovery between low and high socioeconomic status homeowners is improved if mitigation measures are implemented. The results presented in this article can inform disaster recovery plans and mitigation actions in Vancouver and similar communities.
... A multilinear regression model developed by the author in [52] can be used for predicting approximate increases in cost, which helps in allocating sufficient funds in the planning phase. The simulation dynamics (SD) developed by author in [53] helps managers maker sounder decisions pertaining to whether to hire more laborers or operate with the currently available workforce. ...
The number of natural catastrophic events has increased remarkably in recent decades, and the resulting challenges of construction projects have increased even more. It is imperative to recognize these challenges and employ suitable strategies to mitigate them to avoid project failures, which is the basis of this study. To become more knowledgeable about this subject, more than 100 scholarly articles, including peer-reviewed papers and other types of publications, were reviewed and a list of eleven challenges was developed. The next step was to identify the management strategies that could be applied to overcome the challenges. The outcomes from this study concisely help decision-makers and project managers allocate their resources wisely after a disaster, implement construction activities more efficiently, and achieve higher rates of productivity while reducing the consequences of disruptive events.
... These models vary based on the adopted (or developed) conceptual frameworks, numerical methods, the nature of the input variables and the outcomes. Figure 1 provides an overview of the numerical methods that have been used to model disaster housing recovery in prior studies (Burton et al 2015;Cole PMS 2003;Eid and El-Adaway 2017;Huling and Miles 2015;Kumar et al. 2015;Nejat 2011;Nejat and Ghosh 2016;Xia and Schleuss 2016). Linear (and generalized linear) regression models have been used to evaluate the effect of different factors (e.g., occupant tenure, neighborhood income) on the sequence of household movements, pace of recovery and household decisions. ...
Post-earthquake recovery models can be used to quantify the resilience-related benefits of policies intended to mitigate building seismic risk. An assessment of the effect of the Los Angeles Soft-Story Ordinance on the post-earthquake housing recovery of residential communities is presented. An inventory of approximately 8000 buildings located in fve Los Angeles neighborhoods is considered. The neighborhoods vary based on the percentage
of soft-story buildings, population density and the fraction of renter- and owner-occupied residences. Archetype buildings that are representative of the target inventory are developed based on a building-by-building survey performed using Google Street View. Variations in the number of stories and presence and layout of the soft first story are considered in the development of the archetypes. Analytical building-level damage fragility curves are developed using the results from nonlinear analyses of structural models representing
each archetype. A scenario-based damage assessment is performed using shaking intensities generated from the Southern California ShakeOut scenario, and a discrete-time state-based stochastic process model is used to represent post-earthquake recovery. The quantified effect of the Ordinance retrofit varied based on the considered recovery metric. For instance, the initial loss of occupancy for the entire inventory is reduced by 25%. However, if the time to restore 90% occupancy is used as the recovery performance metric, the Ordinance retrofit leads to a 64% reduction.
... Training and education for a legacy, transitional and future workforce is a major opportunity for coordination and investment. Following disasters, there is often a tremendous shortage among general contractors and skilled and semi-skilled trades working in the construction industry (Kumar et al. 2015). For instance, following Hurricane Irma in 2017, the State of Florida dedicated $20 million from the Community Development Block Grant Disaster Recovery allocations to a Workforce Recovery Training Program to train Florida residents in the construction trades (FDEO 2019). ...
... While it is understood that there is a positive correlation between training and increased capacity at the community level [10], the means through which household learning occurs is not well understood. Specifically, calls in the literature highlight the need to study the effectiveness of post-disaster training programs [18,34]. ...
The incorporation of safer building practices into shelter after disasters continues to plague recovery efforts. While limited resources are one potential cause, evidence from case studies suggests that poor adoption of safer construction may stem from a knowledge deficit. Despite these shortcomings, previous research has done little to examine the current state of construction education and training in post-disaster shelter and housing, and there is lacking evidence to support how households acquire new knowledge of construction practice. Examining nineteen shelter projects in the Philippines following Typhoon Haiyan, training methods were categorized using Kolb's experiential learning theory poles. Fuzzy-set qualitative comparative analysis (fsQCA) was then used to analyze the impact of these methods on community construction knowledge. Findings reveal that households acquired knowledge either through a combination of formal training methods that encompassed reflective observation, active experimentation, and concrete experiences or alternatively through observation of on-site construction activities.
... Riverine flooding is a worldwide threat to low-lying formal and informal built environments near watercourses that annually causes enormous human suffering, death and loss of livelihoods, damage to infrastructure and interruptions to economic activity [1]. Developing countries are particularly vulnerable to flooding impacts [2][3][4][5] for many reasons, including fragile economies [2], lack of risk awareness [6], preparedness and coping capacities [7], and lack of planning, implementation and enforcement of urban development, zoning regulations and building standards [8,9]. In many cities, this has led to largely unplanned and unmanaged urban growth characterized by poor or de facto non-existing construction standards [10,11], with informal settlements usually located in high-risk areas such as river banks and flood plains [12][13][14]. ...
Herein we investigate Life Cycle Cost (LCC) and Return on Investment (ROI) as potential decision variables for evaluating the economic performance (ROI) and financial feasibility (LCC) of a set of flood mitigation strategies over time. The main novelty of this work is the application of LCC and ROI analyses at the urban level to an asset portfolio of flood-prone buildings. Reduced flood damage is treated probabilistically as avoided costs (LCC analysis) and returns (ROI analysis), respectively. The proposed methodology is applied to the case of Dar es Salaam, Tanzania, which suffers severe riverine flooding on a sub-annual basis. Specifically, LCC and ROI of five mitigation scenarios that include large-scale catchment rehabilitation, settlement set-backs and waste management are compared with the current situation. The main result is that the highest-performing flood mitigation option includes both conventional interventions and ecosystem rehabilitation.
... Some scholars use SDM to conduct research on the evolution of earthquake disasters and the post-disaster recovery and reconstruction. Quick post-disaster recovery and the reconstruction of housing stock is important for an affected region, as well as the analysis of the effects of a disaster on labour for housing recovery and rebuilding in the devastated area (Kumar et al., 2015). Using unstructured big data, Papadopoulos et al. (2017) proposed and tested a theoretical framework to explain resilience in supply chain networks for sustainability. ...
Poverty eradication and sustainable development are common missions of humanity and are top priorities of the Chinese government. Nevertheless, the poverty of reservoir immigrants is usually interwoven with eco-environmental and geo-disaster factors, making poverty alleviation the most challenging task in rural China. In this context, a System Dynamics Model (SDM) is used to explore interactive mechanisms of eco-environment, geo-disasters and immigrant poverty as well as enable policy makers to understand the impacts of different investment strategies on the key variables and the sustainable development of China's Poverty-stricken Reservoir Regions (CPRR). Based on data from 1998 to 2014, this paper simulates the Wanzhou reservoir area. It designs four policy scenarios to simulate changes to the major variables: sewage treatment investment, disaster control investment, soil erosion control investment and poverty alleviation fund, from 2015 to 2020. It is found that 1) China's Poverty-stricken Reservoir Regions are highly likely to achieve the poverty reduction goal by 2020 by taking the coordinated strategy and pay more attention to disaster management; and 2) the coordinated development scenario could reduce poverty, sewage discharge, disease incidence, geo-disasters and soil erosion, and increase the areas of forest cover and agricultural land systematically. The SDM method is reliable for the dynamic development analysis of CPRR. The results could offer policy recommendations to policy makers and provide a method to implement best practices for the sustainable development of CPRR.
... Yet most research focuses on qualitative analysis and resources management in the context of disaster housing recovery, such as recovery approaches either donor-assisted or owner-driven (Andrew et al., 2013), and the role of social capital (Mukherji, 2014), etc. Diaz et al. (2015) developed a system dynamics model to study the supply problem of reconstruction material in an affected area, and described the behavior of material resources in the housing reconstruction and recovery planning in a catastrophic event. Kumar et al. (2015) proposed a system dynamics model to reproduce and explore the issue of labor force (e.g., construction workers) management. They specifically analyzed the impact of a disaster on labor for the housing recovery, and rebuilding of a devastated region. ...
A coordinated approach is developed to integrate three preventive measures (i.e. building reinforcement, reinforcement of road networks, and facility location of relief supplies), with the objectives of minimizing budgets and risk-induced penalties. The Conditional Value-at-Risk is employed as a decision-making tool to evaluate diverse decisions of prevention based on the degree of risk aversion. Based on a real-world case of an earthquake, a series of scenarios were designed, and the applicability of the proposed model was studied. The coordinated approach for investing preventive measures is cost-efficient in helping reduce the impact of disaster on society.
In the aftermath of a catastrophic weather event, housing recovery and reconstruction activities are highly complex. Coordinating housing recovery activities is generally challenging because complex supply chains converge simultaneously in a highly uncertain environment. In this environment, anticipating and quantifying the extent of potential damage and determining the actions that must be taken to rebuild the housing stock may assist regions in allocating resources for reconstruction. This article presents the development of a comprehensive disaster management framework to assist decision-makers in predicting the impact of projected natural disasters on housing. This framework uses a simulation-based approach to quantify likely regional losses and generate informed scenarios that support the identification of enablers and barriers that may intervene in the reconstruction process considering local governments that moderate the rebuilding pace. We further investigate how adopting the proactive part of the framework leads to a better understanding of the disaster management process by developing a case study in the Hampton Roads Region of the USA. This complex exercise shows the intricacies of disaster preparedness for housing recovery for displaced populations.
In coastal cities, the damage stemming from hurricanes and severe tropical storms may reduce housing stock. Accelerating the reconstruction of housing stock becomes crucial in minimizing the time that residents are displaced. It is critical to understand how to better coordinate all available resources for an effective and balanced reconstruction where nongovernmental organizations (NGOs), government agencies, volunteers, and many other complex resources converge. This study combines Monte Carlo and beta models to assess supply, costs, and recovery times. The models capture the immediate and long-term costs of reconstruction activities under highly uncertain conditions using embedded stochastic components on projected materials, labor, and equipment flows. The model identifies possible hurdles in acquiring likely material and labor and prospective thresholds that might affect the housing recovery process. This research addresses gaps in strategic humanitarian recovery decision-making by modeling housing damage costs through granular-level housing reconstruction activities. In addition, these models provide constructive insight into how cost and completion time are dependent upon supply uncertainties.
Disasters impact the delivery of infrastructure services and disrupt the normal functioning of communities. A primary goal of recovery is to restore patterns of activity to pre-disaster levels in the shortest time possible with minimum performance loss. Resourcing strategies (amounts and allocations) in the post-disaster period should be efficient to maximize benefits with minimum resources and effectively ensure the desired results. Limited resources force recovery planners to choose among multiple competing priorities across infrastructures and populations (e.g., tourism, transportation, workforce, businesses, public health, residents). Optimal resource sequencing, amounts, and timing to improve recovery depend on the capacities of these interdependent community sectors, which interact through multiple delayed feedback loops. Understanding how the structure of community infrastructure systems impacts recovery can improve recovery resource planning by identifying dominant causal structures and high leverage points in the community recovery process. This research combines system dynamics and design structure matrix (DSM) modeling to build, test, and apply a feedback theory of community disaster recovery. The model is used to investigate optimal resource loading and sequencing strategies using a simplified sector model. Initial results, implications, and opportunities for future research are discussed.
The importance of community resilience has become increasingly recognized in emergency management and post-disaster community well-being. To this end, three seismic resilience planning initiatives have been conducted in the U.S. in the last decade to envision the current state of community resilience. Experts who participated in these initiatives confronted challenges that must be addressed for future planning initiatives. We interviewed eighteen participants to learn about the community resilience planning process, its characteristics, and challenges. Conducting qualitative content analysis, we identify six main challenges to community resilience planning: complex network systems; interdependencies among built environment systems; inter-organizational collaboration; connections between the built environment and social systems; communications between built environment and social institutions' experts; and communication among decision-makers, social stakeholders, and community members. To overcome the identified challenges, we discuss the capability of human-centered simulation modeling as a combination of simulation modeling and human-centered design to facilitate community resilience planning.
Housing plays a primary role in post-earthquake recovery because all sectors of the economy rely on residents having healthy living conditions so that they will remain in the affected region. Therefore, understanding the time-dependent effects of earthquake events on housing is critical for improving post-earthquake trends through policy and planning interventions. This study develops an integrated framework for modeling post-earthquake housing recovery that combines probabilistic building performance with the decisions, actions and socioeconomic vulnerability of the affected populations. Building performance is characterized using limit states such as post-earthquake occupiability and repairability, which are explicitly linked to community functionality and recovery. Fragility functions are used to link the probability of exceeding these limit states to ground shaking intensities. Household decisions are modeled using empirical probabilistic utility models. Probabilistic discrete state models are implemented to represent post-earthquake recovery trajectories at the building, neighborhood and community scales. These models, which are inherently stochastic, can be purely empirical, such that the temporal parameters are sampled from an appropriate probability distribution. Alternatively, a simulation-based model can be employed to explicitly account for the effect of resource-availability on the time to complete relevant recovery activities. Socioeconomic vulnerability and other exogenous (external to household) and endogenous (external to household) factors are statistically linked to the temporal recovery parameters. The proposed model can be used to assist policy-makers, municipal governments and planners in understanding the possible interdependencies, interventions, and tradeoffs associated with post-earthquake housing recovery.
Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery.
This conference paper is incomplete and outdated. Please refer to my: 'Formal aspects of model validity and validation on in system dynamics' in System Dynamics Review, 1996
The need to manage disasters through construction industry and its wide role in achieving successful reconstruction projects has gained importance in recent years. Hence, construction industry development through capacity building is becoming inevitable to successful management of disasters. This study aims to explore the capacity of construction industry in post disaster housing reconstruction during the recent past. A questionnaire survey was conducted among contracting organizations involved in post disaster housing reconstruction to explore existing capacities. The study found that contractors place more emphasis on human, finance and management aspects in capacity building. Contractors' financing base changed by a considerably smaller proportion in response to reconstruction circumstances and credit facilities indicates an increase. Main challenges faced in reconstruction are shortage of labourers and materials. This study dentities of existing capacities and highlights areas which need capacity building to successfully face challenges of future post disaster housing reconstruction.
The uncertainty posed by natural and human-made disasters arises from both known risks and a range of unforeseeable risks, some of which may be novel, not having been observed before. These interconnected risks may evolve over short periods of time and may feed into one another. In a network of multiple causes and effects, such risks may not be foreseeable at the disaster preparedness level, and may only be observed at the time of disaster response. This creates a higher level of complexity and requires new approaches with individual organizations and members needing to make decisions outside predefined frameworks and hierarchical command-control structures while still operating in the ethos of their organizations.
This study advocates the need for disaster preparedness strategies to go beyond linear approaches to risk management. This is necessary in order to better address complex interdependent risks where such risks may be novel or unforeseen and which may connect in a cascading manner. The resulting causal network needs to be addressed with a networked approach to enrich existing linear approaches by recognizing the need for an interconnected holistic approach to deal appropriately with interconnected risk factors.
This paper takes an interpretive perspective rather than the more typical positivist one. System of Systems (SoS) and complex systems thinking were used to inform a sense-making framework to distinguish between approaches to known/knowable and unknown risks.
Finally, the paper reports on how this framework was used in South Australia on three different scales of the SoS: community, NGOs and government.
Purpose
The purpose of this paper is to understand the resourcing issues that concern the provision of resources required for reconstruction projects after a disaster and to enable them to be integrated into a holistic planning process.
Design/methodology/approach
Triangulation methodology is adopted in this paper including both quantitative and qualitative methods. The quantitative approach, namely statistic analysis with the aid of questionnaires and SPSS is employed to identify the key factors affecting resource availability in post‐disaster reconstruction situations. The qualitative semi‐structured interviews and desk reviews of government and media documents are conducted to further interpret outcomes in the questionnaire session.
Findings
Based on empirical research, the major finding of the paper is that in order to arrive at a resilient and sustainable built environment after a disaster, resourcing efforts should be made around four components – resourcing facilitator: legislation and policy; resourcing implementer: construction industry; resourcing platform: construction market; and resourcing access: transportation system.
Originality/value
The original part of this paper is in raising the importance of resourcing for achieving a resilient post‐disaster built environment, and in presenting a thorough overhaul of the resourcing components. The paper also offers a vision of comprehensive planning and preparedness to facilitate resourcing operations in post‐disaster reconstruction; pinpoints possible constraints inherent in post‐disaster resourcing environment; and provides a direction‐setting framework to achieve the vision with built environment resilience considerations incorporated.
2008 NZSEE Conference ABSTRACT: The 8th October 2005 Kashmir Earthquake was one the largest earthquakes in Northern Pakistan in its recorded history. It caused an unprecedented level of damage and destruction in Pakistan Administered Kashmir (PAK) and the North Western Frontier Province (NWFP). It damaged or collapsed more than 0.6 million buildings - leaving 3.5 million people shelter less as winter approached. A large part of the earthquake-affected area is difficult to access and highly snow-prone, with rugged terrain and scattered settlements. It posed unique challenges and efforts on a massive- scale for reconstruction. For residential buildings, the Pakistan government adopted a house-owner driven approach. The reconstruction policy stated that the government and other agencies would provide equal technical assistance and subsidy to each family, without differentiating between who lost what. To increase capacity in earthquake- resistant construction, there was large-scale training of artisans, technicians, engineers, and community mobilisers. Campaigns to "build back better" have raised awareness in the communities. Local Housing Reconstruction Centres have been established for training, advice, and dissemination of earthquake-resistant technology. This decentralised approach has helped in achieving reconstruction smoothly. This paper will present the authors' first-hand experience in the reconstruction effort, and the opportunities and unique challenges faced.
Post-disaster housing reconstruction is likely to suffer project deficiencies in relation to the availability of resources. Inefficiencies in dealing with resource shortages in the aftermath of a catastrophe can trigger economic and environmental impacts on the affected areas. Based on data collected from field research in China, Indonesia, and Australia, three types of resource-led reconstruction strategies are compared: government driven, donor driven, and market driven. Conventional interventions from the Chinese government (e.g. price restrictions and discouraging profiteering to regulate the market) were unable to meet the long-term reconstruction needs after the Wenchuan earthquake (2008). Complexity inherent in both internal and external environments in Indonesia compromised donors' efforts in post-tsunami (2004) resource procurement. Market-oriented resourcing processes in Australian bushfire (2009) reconstruction are unlikely to succeed without facilitated solutions from the government and institutions. The answer to effective resource management for post-disaster reconstruction lies in the appropriateness of the responses and improvements to address resourcing challenges. The success of resourcing depends on multi-stakeholder collaboration and the development of polices, plans, and tools to allow market flexibility, donor management, and government intervention.
Significant progress has been made in recent years for modeling spatial economic impacts of disasters in a regional context (for example, Okuyama and Chang eds. Modeling the Spatial Economic Impacts of Disasters, forthcoming). While these advancements are more toward modeling strategies based on conventional frameworks, little has been dealt with the theory on economics of disasters, since the pioneering work by Dacy and Kunreuther (The Economics of Natural Disasters, 1969). In this paper, "The Economics of Natural Disasters" is reviewed and updated for providing a theoretical perspective toward disaster related research. The review is carried our through restructuring the framework of Dacy and Kunreuther with new findings from the recent studies and extending it to a regional context. In addition, the paper proposes the research directions for constructing further the theory on economics of disaster. Abstract: Significant progress has been made in recent years for modeling spatial economic impacts of disasters in a regional context (for example, Okuyama and Chang eds. Modeling the Spatial Economic Impacts of Disasters, forthcoming). While these advancements are more toward modeling strategies based on conventional frameworks, little has been dealt with the theory on economics of disasters, since the pioneering work by Dacy and Kunreuther (The Economics of Natural Disasters, 1969). In this paper, "The Economics of Natural Disasters" is reviewed and updated for providing a theoretical perspective toward disaster related research. The review is carried our through restructuring the framework of Dacy and Kunreuther with new findings from the recent studies and extending it to a regional context. In addition, the paper proposes the research directions for constructing further the theory on economics of disaster.
Community involvement in post disaster re‐construction is an important ingredient to the overall success of housing and infrastructure redevelopment. Implementing Agencies and governments need to design post disaster re‐construction programs which promote the involvement of beneficiaries and communities in post disaster re‐construction programs, to the extent allowed by the scale and context of any given situation. By extension, the management and organisational capacities which enable community involvement in a post disaster re‐construction project need to be identified and developed to facilitate this process. The British Red Cross Maldives post – tsunami recovery program is presented as a case study to identify successes, limitations, and lessons learnt from one such project. The case study is examined to identify capacity building opportunities for community involvement in future post disaster re‐construction projects. These opportunities are presented in terms of the project procurement model chosen for implementation, active and passive methods of community involvement, and the personal skills and management structure required to facilitate community involvement in post disaster re‐construction projects.
Santruka
Bendruomenes indelis i aplinkos atstatyma po stichiniu nelaimiu ‐ svarbus komponentas, padedantis sekmingai atkurti būstus ir infrastruktūra. Tai igyvendinančioms istaigoms ir vyriausybems būtina kurti atstatymo po stichiniu nelaimiu programas, skatinančias nukentejusiuosius ir bendruomenes dalyvauti tokiose programose, kiek tai imanoma, atsižvelgiant i konkrečios situacijos masta ir konteksta. Platesne prasme, norint išplesti ši procesa, reikia nustatyti ir išpletoti vadybos bei organizacines galimybes, leidžiančias bendruomenei dalyvauti atstatymo po stichiniu nelaimiu projekte. Atvejui tirti pasirinkta atkūrimo po cunamio programa, kuria Maldyvuose vykdo Didžiosios Britanijos Raudonasis kryžius. Tyrimu siekiama nustatyti konkretaus projekto sekmes, apribojimus, jo metu išmoktas pamokas. Atvejis nagrinejamas siekiant nustatyti, ar imanoma sukurti salygas, kurios leistu bendruomenei dalyvauti būsimuosiuose atstatymo po stichines nelaimes projektuose. Tokios galimybes pristatomos imant igyvendinti pasirinkta projekto pirkimu modeli, aktyvius ir pasyvius bendruomenes dalyvavimo metodus bei asmeninius igūdžius ir vadybos struktūra, kurie būtini, idant bendruomene galetu dalyvauti atstatymo po stichiniu nelaimiu projektuose.
This paper extends the Diamond-Mortensen-Pissarides (DMP) matching model with endogenous job destruction by introducing post-match labor turnover costs (PMLTC). We consider training and separation costs which create heterogeneity among workers. In particular, there are two types of employed workers: (i) new entrants who need training in order to become fully productive, and (ii) incumbents who are fully productive and whose departure from the firm imposes costs on it. We find that our calibrated model, relative to the standard DMP model, comes closer to the data regarding the volatility of vacancies and unemployment without introducing unrealistic sensitivity to policy changes. Moreover, our extended model nearly reproduces the downward-sloping Beveridge curve, which is unusual when there exists endogenous job destruction in this type of models.
In the aftermath of Hurricane Katrina, a rapid succession of plans put forward a host of recovery options for the Upper and Lower Ninth Ward in New Orleans. Much of the debate focused on catastrophic damage to residential structures and discussions of the capacity of low-income residents to repair their neighbourhoods. This article examines impediments to the current recovery process of the Upper and Lower Ninth Ward, reporting results of an October 2006 survey of 3,211 plots for structural damage, flood damage and post-storm recovery. By examining recovery one year after Hurricane Katrina, and by doing so in the light of flood and structural damage, it is possible to identify impediments to recovery that may disproportionately affect these neighbourhoods. This paper concludes with a discussion of how pre- and post-disaster inequalities have slowed recovery in the Lower Ninth Ward and of the implications this has for post-disaster recovery planning there and elsewhere.
System dynamics models are becoming increasingly common in the analysis of policy and managerial issues. The usefulness of these models is predicated on their ability to link observable patterns of behavior to micro-level structure and decision-making processes. This paper posits that model calibration––the process of estimating the model parameters (structure) to obtain a match between observed and simulated structures and behaviors––is a stringent test of a hypothesis linking structure to behavior, and proposes a framework to use calibration as a form of model testing. It tackles the issue at three levels: theoretical, methodological, and technical. First, it explores the nature of model testing, and suggests that the modeling process be recast as an experimental approach to gain confidence in the hypothesis articulated in the model. At the methodological level, it proposes heuristics to guide the testing strategy, and to take advantage of the strengths of automated calibration algorithms. Finally, it presents a set of techniques to support the hypothesis testing process. The paper concludes with an example and a summary of the argument for the proposed approach.
In the aftermath of Hurricane Katrina, a rapid succession of plans put forward a host of recovery options for the Upper and Lower Ninth Ward in New Orleans. Much of the debate focused on catastrophic damage to residential structures and discussions of the capacity of low-income residents to repair their neighbourhoods. This article examines impediments to the current recovery process of the Upper and Lower Ninth Ward, reporting results of an October 2006 survey of 3,211 plots for structural damage, flood damage and post-storm recovery. By examining recovery one year after Hurricane Katrina, and by doing so in the light of flood and structural damage, it is possible to identify impediments to recovery that may disproportionately affect these neighbourhoods. This paper concludes with a discussion of how pre- and post-disaster inequalities have slowed recovery in the Lower Ninth Ward and of the implications this has for post-disaster recovery planning there and elsewhere.
Disaster recovery is a phase in the emergency management cycle that frequently overlaps with the emergency response. Its goal is to restore normal community activities that were disrupted by disaster impacts through a process involving both activities that were planned before disaster impact and those that were improvised after disaster impact. Disaster recovery is most rapidly and effectively achieved when communities engage in a preimpact planning process that addresses the major recovery functions and incorporates hazard mitigation and hazard insurance into a recovery operations plan.
In this paper we discuss verification and validation of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate verification and validation to the model development process are presented; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are discussed; a way to document results is given; a recommended procedure for model validation is presented; and model accreditation is briefly discussed.
Purpose
The purpose of this paper is to identify resourcing challenges that face housing rebuild following the 2009 Victorian “Black Saturday” bushfires in Australia and to examine the impacts of resource shortages on longer term community recovery.
Design/methodology/approach
The research methodology included a longitudinal study which consists of a questionnaire survey, field‐based interviews and observations to track trends evident in the survey.
Findings
A total of 28 months after the bushfires, reconstruction in the worst‐affected area, the Shire of Murrindindi, was proceeding slowly despite the institutions and procedures set up for recovery. This slow reconstruction was due to the unavailability of building resources. Changed Building Standards, increased building markets outside the bushfire zone, lack of economic incentives, combined with home owners’ socio‐economic vulnerabilities, created a chain of impacts on households’ ability to get resources.
Research limitations/implications
The evidence in this paper points to emergent resource issues that impeded recovery progress in the bushfire zone. These issues primarily come from technical decisions on building controls, economic conditions, and risk perceptions of construction professionals. Findings from this longitudinal study will inform the recovery planning of government agencies in future events.
Originality/value
This paper makes the case for a new approach to looking at resourcing problems following a major disaster. This study demonstrates that recovery planning needs to include a resource perspective which explains both impacts of recovery polices on resource availability and impacts of resourcing dynamics on the wider recovery environment.
Decision support systems have increasingly played a critical role in disaster logistics. This study outlines the processes required to build an effective and reliable decision support system to assess the feasibility of public facilities during an evacuation after a disaster has occurred. The purpose of this study is to build a model of a web-aided decision support system to assess the extent to which public facilities can be used as evacuation centres for the victims of an earthquake and/or tsunami. An outcome from this research is an innovative system with direct web-based accessibility, involves many decision-makers and employsmultiple criteria and inputs. Even though the system has been specifically designed for evacuation scenarios in Indonesia, the system can used fordisaster scenarios in other countries. There are several stages in this study where the first stage identifies and selects attributes, assembles a comprehensive computer application, and employs object-oriented programming (OOP), verification and validation of the system. The role of information systems and decision support systems are critical when informing decision-makers about evacuation location alternatives and to assess their feasibility immediately after a disaster occurs. The results from this study confirm this system can provide critical and timely insights into complex evacuation scenarios. An additional benefit of this system is the user-friendly web-based application ensuring data access from any global location with internet access.
The Himalaya has been venerated by communities since antiquity and hence visited by a large number of pilgrims for paying tribute, annually. Uttarakhand state in the Indian Himalaya being the place of major Hindu shrines like Badrinath, Kedarnath, Gangotri and Yamunotri and also the place of origin of many sacred rivers including the Ganges, at present, is best known for the religious tourism. Though, the state population is about 10 million, over 25 million tourists visited here in 2011 despite the fact that the state remains under frequent natural hazards in the forms of landslides, earthquakes and flash floods mainly during monsoon. Recently, on 16 and 17 June 2013, the torrential downpour and subsequent flooding had wreaked havoc that not only swallowed vast swathes of Uttarakhand but also took life of thousands of pilgrims and tourists. The cloudburst, heavy rainfall and subsequent landslides are the natural disasters but this disaster in Uttarakhand is mainly attributed by masses as a man-made disaster due to unregulated tourism and unplanned construction. In this background, the major aim of this study is to explore and review the factors responsible for increased intensity and scale of disaster due to flash floods in the Uttarakhand state of India. The paper also reviews and discusses various options for disaster risk reductions in the sensitive ecosystem such as the Himalaya.
We investigate differences in quit, layoff and hiring rates in high versus low minimum wage regimes using Canadian data spanning 1979 to 2008. The data include consistent questions on job tenure and reason for job separation for the whole period. Over the same time frame, there were over 140 minimum wage changes in Canada. We find that higher minimum wages are associated with lower hiring rates but also with lower job separation rates. Importantly, the reduced separation rates are due mainly to reductions in layoffs, occur in the first 6 months of a job, and are present for unskilled workers of all ages. Our estimates imply that a 10% increase in the minimum wage generates a 3.9% reduction in the layoff rate. We present a search and matching model that fits with these patterns and test its implications. Overall, our results imply that jobs in higher minimum wage regimes are more stable but harder to get.
Hurricane Katrina was the greatest urban and regional disaster in U.S. history. The rebuilding of New Orleans and surrounding areas of Louisiana and Mississippi will require the largest and most complex planning effort in my lifetime. To succeed, we must learn from disasters of the past, while also applying the planning knowledge of the present. From past disasters, we know that successful reconstruction requires both outside funding and local citizen involvement. As planners, we know that the processes should be rich in data, imagination, communication, and participation, Optimistically, a new New Orleans will involve improved flood safety, revitalized neighborhoods, housing opportunities for all, and equitable treatment of all residents. Planners have an obligation to take an active role and advocate for the funding and full participation necessary to achieve these goals. The alternative would be a city that is poor, unsafe, and unequal. This is the greatest planning problem most of us have ever seen, and it warrants a correspondingly large response.
Storm surge and wind associated with Hurricane Katrina caused many deaths and the destruction of property and public infrastructure along the coasts of Louisiana, Mississippi, and Alabama. The devastation was predicted, and absent massive and immediate action, the next major storm will inevitably produce additional disastrous outcomes. Somewhat less predictable are the many social changes associated with the hurricane and public sector response to the event. We characterize some of the more salient human consequences across multiple sectors of the economy—including energy, finance, construction, housing, gaming, and commercial fisheries. We examine how preexisting social trends were amplified, otherwise-latent social and cultural distinctions were exacerbated, and national resources and funds intended for broad-scale “recovery” were converted into instruments of capital formation and further concentration of wealth. We conclude with a discussion exploring public policy and other implications of the disaster in a context of ever-increasing global, environmental, and social challenges.
IntroductionThe impact of the 2008 Wenchuan earthquakeWenchuan earthquake reconstruction processResourcing for Wenchuan earthquake reconstructionKey resourcing problems and solutions adopted by the Chinese reconstruction teamsSummaryNotesReferences
The authors study vacancies, hires, and vacancy yields (success rate in generating hires) in the Job Openings and Labor Turnover Survey, a large representative sample of U.S. employers. The authors also develop a simple framework that identifies the monthly flow of new vacancies and the job-filling rate for vacant positions, the employer counterpart to the job-finding rate for unemployed workers. The job-filling rate moves counter to employment at the aggregate level but rises steeply with employer growth rates in the cross section. It falls with employer size, rises with the worker turnover rate, and varies by a factor of four across major industry groups. The authors' analysis also indicates that more than 1 in 6 hires occur without benefit of a vacancy, as defined by JOLTS. These findings provide useful inputs for assessing, developing, and calibrating theoretical models of search, matching, and hiring in the labor market.
The availability of resources allows for the rapid and cost-effective delivery of a construction project. For rebuilding programmes after a disaster, the need for better understanding of factors affecting resource availability and their potential impacts on resourcing outcomes can be of crucial importance to effective reconstruction performance. Drawing on an empirical survey in China following the 2008 Wenchuan earthquake, the critical factors affecting resource availability for post-quake reconstruction of housing are identified. Resource availability in a post-disaster situation is not only associated with (1) project-related factors such as quantity of resources required, project schedule, project resourcing plan, and resource procurement lead time; and (2) factors related to the reconstruction practitioners, including competency of resourcing manager and qualification of contractor; but is also related to (3) factors external to reconstruction projects including legislation and policy, general economic environment, and resource transportation cost and method. To address these factors, a multi-sector approach is needed for reconstruction decision makers and practitioners. A planned procurement strategy in the implementing contractors, a range of training initiatives for small and medium businesses, along with augmented regulatory, economic and transport infrastructure systems are likely to improve resource availability for post-disaster rebuilding projects.
This book sets out to develop a new framework for the analysis of disaster situations in developing countries. In doing so, it challenges many of the accepted wisdoms of disaster theory upon which policy prescriptions are built. The author insists that although disasters are a problem of development, they are not necessarily a problem for development. What we should be looking at are the underlying social and economic processes within developing countries which structure the impact of natural disasters, rather than at disasters as unforeseen events requiring large scale intervention.
It has been suggested that disasters might have positive economic consequences, through the accelerated replacement of capital. This possibility is referred to as the productivity effect. This effect is investigated using a model with embodied technical change. In this framework, disasters can influence the production level but cannot influence the growth rate, in the same way than the saving ratio in a Solow-like model. Depending on reconstruction quality, indeed, accounting for embodied technical change can either decrease or increase disaster costs, but is never able to turn disasters into positive events. Moreover, a better but slower reconstruction amplifies the short-term consequences of disasters, but pays off over the long-term. Regardless, the productivity effect cannot prevent the existence of a bifurcation when disaster damages exceed the reconstruction capacity, potentially leading to poverty traps.
The employment duration of workers in temporary help agencies is seen as an important indicator of their job quality. Most of the countries that regulate temporary agency employment do so to ensure at least a minimal level of employment stability. Over the past three decades Germany has repeatedly liberalized the law on temporary agency employment. These successive reforms should have affected the employment duration in the temporary employment sector. Applying a mixed proportional hazard rate model to administrative data, the authors examine whether employment duration changed in response to these reforms. They find that successive extensions of the maximum assignment period significantly increased average employment duration, while "liberalizing" legislation, such as that allowing fixed-term contracts, tended to reduce it.
This paper is, firstly, a reappraisal of the matching function, arguing that the proper specification of the relation between hirings (H), vacancies (V), and unemployment is the duration function, which shows how average recruitment times as measured by V/H depend on unemployment and other relevant variables. Secondly, indirect effects of longer recruitment times on employment through higher recruitment costs are studied by extending previous models to include both price formation and the distinction between vacancy costs and hiring costs. Thirdly, direct effects of longer recruitment times on employment through more unfilled jobs are explored and illustrated with data from Sweden since 2000 from a new business survey, which measures not only job vacancies but also unfilled jobs.