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What We Know about Demand Surge: Brief Summary
Abstract
Demand surge is a process resulting in a higher cost to repair building damage after large disasters than to repair the same damage after a small disaster; this higher cost can be an additional 20% or more. It is of interest to insurers, regulators, property owners, and others. Despite its importance, demand surge has no standard definition or generally accepted predictive theory of its mechanisms and quantitative effects. By studying the circumstances of natural disasters that did and did not cause demand surge, common explanatory themes emerge from these historical events that may describe why and how much losses increase in some disasters. The themes are: total amount of repair work; timing of reconstruction; costs of materials, labor, and equipment; contractor overhead and profit; the general economic situation; insurance claims handling; and decisions of an insurance company. The development of these themes will aid in constructing a mechanistic, empirically supported approach to modeling demand surge.
... The academic literature dealing with the impact of natural disasters on reconstruction labor wages and insured loss inflation is rather scarce. An overview is provided by Olsen and Porter [9,10] and Döhrmann et al. [8]. In this context, approaches for considering wage increases after catastrophe events are based on simulation studies [11] or focus primarily on physical variables, such as the wind speed of a hurricane, to predict cost changes of constructed baskets of repairs [12]. ...
... To segregate the relative wage increase caused by a catastrophe from alternative influencing factors, we apply equation (10). Thus, we first calculate the relative change in wages in the catastrophe-affected region (A), i.e., (p no− cat (0) based on the assumption that the two abovementioned effects are both contained in the nationwide index. ...
... We compute the percentage increase of the retail labor price index in West Palm Beach (p cat ) and the entire US (p no-cat ) starting directly before the landfall of Hurricane Frances in West Palm Beach in Q3 2004. In a second step, we calculate the difference between both time series of percentage increases according to equation (10). Finally, we calculate the average/ maximum value over differing time periods of 1, 2, and 3 years. ...
The need for reconstruction in the aftermath of natural disasters can lead to increased reconstruction labor wages, resulting in considerably inflated insured and uninsured losses. Based on a difference-in-differences approach using 9,009 catastrophe regions in the United States, we segregate catastrophe induced wage effects from the business cycle development and find a wage surge of up to 50%. In addition to catastrophe-specific factors, wage surge is substantially influenced by local labor market characteristics such as growth stage of the economy, workload per employee, and local wage differentials. We illustrate implications for (re)insurance companies, catastrophe-linked securities and their respective investors, building companies, and governments.
... Loss amplification broadly describes temporary increases in postdisaster repair and reconstruction project costs, measured as direct economic losses (e.g., physical infrastructure replacement value) and indirect economic losses (e.g., disrupted community social cohesion, production losses, disrupted transportation routes, supply chain upheaval, and power supply) (Hallegatte 2014;Hallegatte and Ghil 2008). A key concept of loss amplification is demand surge, associated with postdisaster labor and material shortages (Olsen and Porter 2011). Demand surge has been viewed as a socioeconomic phenomenon characterized by the inflation of prices and wages, temporarily and locally, after a disaster (Choi et al. 2019;Comes et al. 2020). ...
... Fluctuations in postdisaster labor prices tend to be more pronounced (compared to material pricing) due to the disparate and regional nature of construction labor markets, the need to quickly import laborers from surrounding regions, and additional costs associated with overtime (Döhrmann et al. 2013). Among various broad themes of demand surge proposed by Olsen and Porter (2011), this study focuses on the heavy civil construction labor market involved in postdisaster infrastructure reconstruction. The authors define demand surge for this study as the temporary and local increase in construction labor wages in the highways, roads, and bridges construction sector after a large-scale disaster. ...
... Increases in construction costs following large scale disasters are a well-observed phenomenon and have been documented following hurricanes, earthquakes, and cyclones (Olsen 2012;Olsen and Porter 2011). During the postdisaster recovery phase, there is a rush to quickly restore damaged infrastructure while maintaining project schedules for other ongoing construction activities. ...
The swift and cost-efficient postdisaster reconstruction of highways, roads, and bridges is a necessary component of resilient transportation infrastructure systems. However, the US construction industry often reports temporary increases in construction labor wages following large-scale disasters due to a gap between labor supply and demand, a concept known as demand surge. Utilizing publicly available big data related to the construction labor market and postdisaster infrastructure repair expenditures, this study seeks to (1) measure construction labor demand surge in the highways, roads, and bridges construction sector following federally-declared disasters in US metro-areas and (2) identify when such postdisaster demand surge occurs. A total of 118 US metro-areas were analyzed for demand surge following federally-declared disaster events from 2004 to 2017. Findings highlight inflated postdisaster construction labor wages in metro-areas, with the demand surge spiking within six months after a disaster. This data-driven study is the first to quantitatively measure postdisaster demand surge in the US highways, roads, and bridges sector following multihazard disaster events. Knowledge of the demand surge can guide predisaster planning and decision-making processes for local, state, and national agencies and inform postdisaster best practices for contractors and engineers coordinating transportation system construction projects.
... The construction industry is in the maelstrom of the aftermath of the disasters, as they deal with damage to buildings and infrastructures that must be repaired immediately [9,10,11]. Disaster recovery made without knowledge of effective strategies results in an increase of losses [6,12,13,14,15], while studying natural catastrophes facilitates better decision-making regarding the timing and planning for reconstruction materials for future disasters [16,17]. ...
... The 11 challenges observed through a thorough review of the literature are depicted in Table 2 and are discussed below. Increase in overhead cost and profit margins [17] C2 Disruption of transportation network (logistics) [18] C3 Psychological and environmental factors [19] C4 Damages to machinery [20] C5 Inflation of construction labor charges [21] C6 Increase in demand for labor and equipment [21,22,23] C7 Loss of lives and impact on neighboring communities [24] C8 Damages to materials in construction site [25] C9 Stability of structural components [26] C10 Project schedule [27] C11 Interdependent utilities [28] ...
... All the above mentioned tasks require additional labor and equipment that incur Percentage of articles additional cost and time [22,33]. For instance, the material cost of strand board increased up to 30% and tarpaulin sheets increased up to 2000% after the Sydney hailstorm [17]. Contractors often increase the overhead and profit margins and may change the bidding values in the aftermath of disasters. ...
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.
... The second was to examine one of the proposed benefits of decentralized wastewater systems, namely that vulnerability and loss are dispersed by decentralization by assuming that failures of decentralized systems are independent (Booz Allen Hamilton and Rocky Mountain Institute 2014; Weirich et al. 2015b). However, in a regional disaster when loss of function is widespread and simultaneous, restoration of decentralized infrastructure such as buildings or OWTS may be far more difficult, impeding recovery and increasing associated costs (Olsen and Porter 2011). ...
... The 10% increase over the pre-flood repair cost was the minimum increase reported in a survey of five Boulder County OWTS installers who suggested costs increased between 10% and 20% after the flood (Kohler 2016). Olsen and Porter similarly found that demand surge from a widespread extreme event increased building reconstruction cost by 20% or more (Olsen and Porter 2011). ...
... Floods impact not only OWTS but also other infrastructure systems and stress the resources available both directly after the event and for several years into the future. Olsen and Porter (2011) describe these and consequent cost increases as "demand surge" where the supply-for materials and services-is overburdened by a sudden and widespread demand when multiple systems fail simultaneously. Two methods for estimating the costs associated with resourcefulness were described previously. ...
In September 2013 an extreme (1000-year) storm event in north central Colorado produced over 40 cm rainfall in four days, resulting in widespread flooding. Along with damage to roads, bridges, housing, and sewers, many of the 14,300 on-site wastewater treatment systems (OWTS) in the county sustained significant damage, with more than 400 owners reporting "failures," requiring a county-issued permit for repair in the months following the storm. Post-storm resilience of OWTS was analyzed using a random sample of 123 OWTS which required repairs after the flood compared to pre-storm repairs in a second sample of 150 OWTS. The resilience dimensions used were fragility (extent of loss of function), rapidity (time required to restore function), and resourcefulness (costs of repairs and related losses due to time of disrupted service). The storm and flooding significantly increased two measures of the fragility: Frequency of total permitted repairs increased from 48/150 to 83/123 for the two years prior to and after the storm. The median time to restoration of service increased from 53 days pre-storm to 112 days during the two years following the flood.
... In many cases, the overwhelming reconstruction workload forces organisations to rely on unskilled workforces, leading to compromised recovery efforts due to poor workmanship and the subsequent need for remedial work [19,20]. This issue is further exacerbated by post-disaster demand surges, which can drive costs upward by 20 % or more [21]. Collectively, these challenges render human resource constraints a persistent and formidable obstacle to timely and efficient post-disaster recovery. ...
... Moreover, in the wake of disasters, the sudden surge in demand for skilled labour intensifies competition among sectors, including reconstruction, emergency response, and infrastructure maintenance. This competition can lead to wage inflation and a shortage of specialised expertise [21]. Financial constraints associated with recruiting, relocating, and integrating international talent further exacerbate these challenges, particularly in economically vulnerable communities [64]. ...
Demand surge phenomenon as a result of shortages of human resources needed for post-disaster recovery and reconstruction can be detrimental to recovery outcomes. To quantify the impact of human resource constraints on the recovery of an urban environment, this research introduces a novel Dynamic Stochastic Queuing (DSQ) model, revealing such dynamic interplays over time. Central to this model is the incorporation of a spectrum of socioeconomic factors to formulate optimal recovery strategies under different dynamic resource mobilisation patterns. A recovery efficiency index is defined and employed as a proxy to facilitate comparisons across diverse recovery strategies. A case study is presented to illustrate the application of the model by simulating the building recovery of a portfolio of residential buildings in New Zealand following the 2010-2011 Canterbury Earthquake Sequence (CES). The findings indicate that proactive resource mobilisation strategies can significantly enhance both recovery efficiency and speed. It becomes possible to shorten the post-disaster recovery time significantly by strategically sequencing repairs of damaged structures while taking into account resource mobilisation strategies.
... An abnormal shortage of skilled labor or materials can occur after a large-scale disaster. Demand surge is a process resulting in a higher cost to repair building damage after large disasters, compared with the same repair for damage after a small disaster (Olsen and Porter, 2011). Adjusting repair/replacement costs due to a likely demand surge was beyond the scope of this project. ...
... It does not factor in demand surge, which occurs following large disasters and results in higher costs to repair building damage compared with comparable damage observed in smaller disasters (described previously in section 2.3 ). Olsen and Porter (2011) reported demand surges ranging from 10% to 40% from several large-scale disasters. Adjusting repair/replacement costs due to a likely demand surge was beyond the scope of this project. ...
Coastal earthquake and tsunami risk assessment. Assesses the potential economic and societal impacts of a Cascadia earthquake and tsunami impacting the Oregon coast. Includes individual community profiles for three tsunami inundation scenarios: M1, L1, XXL1.
... There is a surge in pricing for building services and materials as demand for limited supply is significantly increased in the post-event emergency period. See Olsen and Porter (2011), for a recent review of how demand surge is estimated. When cost escalation in the time period after the earthquake is not important, then issue 3 can be ignored. ...
... For example, 20th Century Insurance, based in the Los Angeles area, was nearly bankrupted by claims following the 1994 Northridge Earthquake, a disaster that produced a reported 20% demand surge. (Olsen and Porter 2011). Often this item is estimated by multiplying the calculated cost by a factor representing the expected increase of costs where demand far exceeds the supply of both skilled manpower and materials. ...
Seismic performance and loss assessments are required in areas of Insurance, Finance and Public Policy. Providers are Structural Engineers and Risk Management Firms. There are no current procedures to evaluate the epistemic and aleatory uncertainties for such assessments. The essential issue is whether or not there is sufficient reliability in the result to use the result as the basis for risk management decisions and actions. For a single building this may be whether or not a prescribed earthquake performance level is met, life safety or if a portfolio’s vulnerability level is acceptable, whether the. loss for a given time period is less than a stated value. A method based in part on Federal Emergency Management Agency P-695, is developed for evaluating the reliability of performance and/or loss assessments for both individual and portfolios of buildings. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the building evaluation, the technical validity of the assessment procedure or model and what computational reliabilities are presented. The method characterizes the uncertainty of each component of the assessment procedure for each building by qualitative determined assignments. The resulting reliability measure is likely to be most useful for determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low loss risk over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.
... The increase in repair costs following large-scale natural hazards is often measured as the percentage increase in construction costs due to the interrupted supply of construction materials and labor (Kuzak and Larsen 2005). Historical postdisaster construction cost increases have varied from 10% to 40% in the aftermath of Hurricane Katrina (Olsen and Porter 2011b) to 50% following Cyclone Larry (Australian Securities and Investments Commission 2007). ...
... The increased cost of construction materials is one of the most common explanations for postdisaster construction cost increases, and therefore, it is a good first choice for an in-depth study (Olsen and Porter 2011a). Studying natural hazards will help individuals make better decisions regarding timing and budgeting for reconstruction materials for future catastrophes (Olsen and Porter 2011b). ...
The postdisaster survival of communities and cities largely depends on their capabilities to rapidly reconstruct damages. Temporary increases in construction costs following natural hazards, also known as demand surge, impede the rapid postdisaster reconstruction process. Existing methods for quantifying postdisaster construction cost escalations do not consider seasonal patterns and inflation of costs under normal conditions. Therefore, it is not clear whether the quantified construction cost increases are due to a disaster or merely associated with seasonal patterns and inflation. The objectives of this study are to (1) create an approach to statistically quantify postdisaster construction material cost fluctuations considering regional seasonal patterns and inflation of construction material costs in normal condition (no disaster); and (2) apply the approach to identify the most vulnerable construction materials following Hurricane Katrina in New Orleans, Louisiana. The authors created an approach based on cumulative sum (CUSUM) control charts and seasonal autoregressive integrated moving average (seasonal ARIMA) models to measure postdisaster construction material cost fluctuations. This approach is applied to quantify construction material cost fluctuations following Hurricane Katrina in New Orleans, Louisiana. The results indicate three different patterns in the postdisaster cost movements: (1) a statistically significant increase in the cost of materials such as I-beams and channel beams, (2) a statistically significant decrease in the cost of materials such as pine lumber, and (3) no statistically significant changes in the cost of materials such as reinforced concrete pipes. These findings are expected to help property insurers, capital planners, and construction engineers to estimate postdisaster cost fluctuations more accurately. They also help identify the most vulnerable construction materials to disasters.
... I n today's precarious world, physical retailers must adapt to an uncertain operational environment (Biggs et al., 2023;Verschueren et al., 2021). Natural disasters and human-caused accidents can induce a variety of external changes, which may signify both threats and opportunities for physical retailers (Olsen and Porter, 2011). To cope with this type of shock, digital transformation has been leveraged by a large number of physical retailers to build the capabilities of absorbing shock-induced losses, adapting to shock-driven disruption, and transforming to anticipate future shocks (Boh et al., 2023;Torres and Augusto, 2019). ...
This paper explores the mapping from specific digitalization practices to specific resilient performance against a great shock. Based on an adapted structure–conduct–performance framework, this paper hypothesizes by theoretically analyzing how the pre-shock establishment of digital retailing practices could trigger physical retailers’ bounce-back and bounce-forward performance against the COVID-19 crisis. Using a difference-in-differences strategy, the hypotheses are examined with a sample including 549 observations of 50 Chinese listed retailers from the first quarter of 2018 to the third quarter of 2020. The empirical results mainly indicate the following binary findings. First, regardless of the differences in triggering bounce-back performance, different digital retailing practices are found to be effective in triggering physical retailers’ bounce-forward performance against the COVID-19 crisis. This somewhat addresses the concern about the temporality of digitalization-enabled resilience by revealing the generality across digital retailing practices in the sense of triggering resilient performance. Second, it is shown that physical retailers’ bounce-back performance at a specific stage of the COVID-19 crisis could only be triggered by digital retailing practices that coincidentally apply to the shock-induced market structure changes at the stage. The results emphasize each digitalization practice’s individuality in triggering resilient performance. This justifies the non-negligibility of the direct mapping from specific digitalization practices to specific resilient performance in digitalization-enabled resilience evaluation.
... Another issue that compounds to increased housing reconstruction costs and leads to underinsurance is demand surge after disasters due to an imbalance between supply and demand for construction materials and workforce (Olsen (2011), Hallegatte (2010), Chang (2010)). Estimates suggest that demand surges increased average repair costs between 10% and 40% after Hurricane Katrine (Guy Carpenter 2005), and 50% after Cyclone Larry (Australian Securities and Investments Commission (ASIC), 2007). ...
Large scale disasters such as earthquakes can cause significant damage to the housing stock in a community. Insurance plays an important role in market-driven post-disaster housing recovery. However, insurance premiums are often defined based on costs defined before a disaster. Thus, reconstruction costs increase due to an imbalanced demand for services or due to a requirement of rebuilding to a higher standard can lead to the problem of underinsurance. This study presents an agent-based model for housing recovery simulation that can capture the influence of price surges and build-back-better requirements on housing reconstruction in an earthquake-struck community. This novel methodology is presented and applied to a case study of a hypothetical earthquake striking the city of Alameda, California. The model evaluates how cost increases and underinsurance affect the likelihood that homeowners will rebuild or sell their homes. Case study results show that up to 2,000 homeowners could find that selling their homes and leaving Alameda is a more economically viable alternative to repairing and staying. Moreover, most of these home sales is expected to happen among low-to-moderate income homeowners. This, the methodology can also provide insights into gentrification potential for an earthquake-struck community.
... In many cases, the substantial workload associated with reconstruction compels organisations to rely on unskilled labourers, further compromising the recovery efforts due to the prevalence of poor workmanship and the subsequent need for rework (Silva, 2010;Muxlow, 2017). This challenge is further compounded by soaring costs driven by demand surges, which can inflate expenses by 20% or more (Olsen & Porter, 2011), turning resource constraints into a persistent and formidable obstacle in post-disaster recovery scenarios. ...
Human resource constraints and the associated demand surge after a major earthquake affect the pace of post-earthquake recovery. To quantify the impact of these constraints on building recovery, this research developed a dynamic framework that integrates asset-level building performance assessment with community-level resource dynamic mobilisations. Central to this framework is a Dynamic Stochastic Queuing (DSQ) model, which incorporates a spectrum of socioeconomic factors to formulate optimal recovery strategies leveraging the Priority Index (PRI) and allocating resources while accounting for dynamic resource mobilisation patterns. A recovery efficiency index is defined and employed as a proxy to facilitate comparisons across diverse recovery strategies. A case study is presented to illustrate the application of the framework in modelling the building recovery process for a portfolio of residential buildings in New Zealand following the 2010-2011 Canterbury Earthquake Sequence (CES). The findings indicate that proactive resource mobilisation strategies can significantly enhance both recovery efficiency and speed. The results also reveal that it is possible for a reduction of recovery time by over one decade when an optimised recovery sequence of damaged structures is paired with proactive resource mobilisation strategies. The proposed framework provides a pragmatic tool for recovery agencies and stakeholders to evaluate the efficiency of various recovery strategies and their impact on the recovery process.
... This urgency demands a rapid mobilization of reconstruction resources, such as construction labor and materials, often at a pace that leads to disparities in the rebuilding process. Pre-disaster shortages of skilled labor (Chang-Richards et al., 2017) are exacerbated by time compression in the context of post-disaster reconstruction, resulting in demand surge (i.e., sudden increases in the price of labor) (Olsen & Porter, 2011), making rebuilding a challenging process. This has implications for the local labor market, especially if the affected area previously did not have a surplus of construction labor . ...
Wildfires in recent years have posed a great threat to residential properties and local economies in communities located near the wildland-urban interface (WUI), particularly in the state of California. Wildfires destroy residential properties, disrupting the residential construction supply chains. When the residential housing stock is destroyed by wildfires, rebuilding must quickly begin to avoid disrupting the local community and economy. This process intensifies the demand for residential construction material resources and requires the local construction labor market to sustain the demand for construction labor over time and manage the influx of workers. Using an interrupted time series analysis, this study investigates the dynamic impacts of wildfires on the residential construction sector, utilizing residential permits and labor employment data from a case study of the 2018 Camp Fire in Butte County, California. Results indicate that the wildfire promoted a sustained increase in residential construction activity (average post-fire permit valuations increased by 67%), matched by a consistent rise in labor employment (average post-fire labor concentration increased by 25%). The findings provide insights into the resilience of residential construction sectors in the face of wildfires.
... Disregarding this effect might lead to inaccurate comparisons between observed and estimated impacts. In this context, several studies have investigated how PLA should be defined, what should be included, its possible causes, how to measure it, and how to model it (Do¨hrmann et al., 2013;General Insurance Practice Committee, 2015;Olsen and Porter, 2010, 2011a, 2011b. Olsen and Porter (2010) developed a remarkable basis on this topic, describing the main definitions that have been used in the insurance, academic, and governmental sectors since 1970. ...
The impact of destructive earthquakes might exceed the local capacity to cope with disasters and lead to an increase in the reconstruction costs. This phenomenon is commonly termed as post-loss amplification, and its main causes include the increase in the cost of construction materials and labor due to the sudden demand, the need to reconstruct following higher standards, or other unexpected costs. We reviewed 70 past earthquakes to identify events where post-loss amplification was observed, and collected a set of seismogenic, socio-economic, geographical, and impact variables for those events. Using this database, we developed two models to predict post-loss amplification, using a composite indicator that reflects the level of destruction in the region, or a parameter that characterizes the frequency of the event. This study indicates increased costs (>10%) for events where the economic losses exceed 1% of the regional gross domestic product, or for events with an estimated return period of at least 10 years. These models can be applied directly in the amplification of economic losses in earthquake scenarios or in probabilistic seismic risk assessment.
... The loss estimation in Equation (6) does not account for demand surges. Demand surge is a common phenomenon after disasters due to an imbalance between supply and demand for construction materials and workforce (e.g., Chang et al., 2010;Hallegatte & Przyluski, 2010;Olsen & Porter, 2011). Consequently, Equation (6) will likely underestimate the true repair costs. ...
In the United States, assistance from the Department of Housing and Urban Development (HUD) plays an essential role in supporting the postdisaster recovery of states with unmet housing needs. HUD requires data on unmet needs to appropriate recovery funds. Ground truth data are not available for months after a disaster, however, so HUD uses a simplified approach to estimate unmet housing needs. State authorities argue that HUD's simplified approach underestimates the state's needs. This article presents a methodology to estimate postdisaster unmet housing needs that is accurate and relies only on data obtained shortly after a disaster. Data on the number of damaged buildings are combined with models for expected repair costs. Statistical models for aid distributed by the Federal Emergency Management Agency (FEMA) and the Small Business Administration (SBA) are then developed and used to forecast funding provided by those agencies. With these forecasts, the unmet need to be funded by HUD is estimated. The approach can be used for multiple states and hazard types. As validation, the proposed methodology is used to estimate the unmet housing needs following disasters that struck California in 2017. California authorities suggest that HUD's methodology underestimated the state's needs by a factor of 20. Conversely, the proposed methodology can replicate the estimates by the state authorities and provide accounts of losses, the amount of funding from FEMA and SBA, and the total unmet housing needs without requiring data unavailable shortly after a disaster. Thus, the proposed methodology can help improve HUD's funding appropriation without delays.
... Other types of infrastructure assetshomes, buildings, bridges, drainage structures, communications, etc.that are in the disaster area are also damaged and in need of repair. This "demand surge" of repairs needed on so many levels causes construction material and labor costs to rise disproportionately (up to 20% or more) after a natural disaster just due of scarcity (Olsen & Porter, 2011). As such, the costs associated with a rapid repair strategy would be much higher than anticipated. ...
Future climate conditions are not going to resemble the past. Temperatures will be hotter, and storms will get stronger. However, pavements are still being designed under the assumption that past conditions are going to resemble the future. This is a bad assumption. Furthermore, when climate change and pavement resilience are discussed, people often focus on the immediate and local impacts of the natural disaster, such as a washout during flooding. While this is important, one also needs to recognize that pavement damage can occur the natural disaster (termed secondary damage) when rescue, emergency response, recovery and rebuilding activities are taking place and the pavement, often in a weakened state, is subjected to increased volume of heavier traffic. This paper will define how resiliency concepts can be applied to pavements, using pavement flooding as an example. It will cover the need for resiliency and the events we need to be resilient against (flood, fire, etc.); it will define a resiliency framework to account for both initial and secondary impacts; it will provide some approaches to mitigate pavement damage using concrete and cement-based products; and finally, it will describe a process that could be used to assess different pavement resilience options.
KEY WORDS CLIMATE CHANGE / RESILIENCE / FLOOD / SEA LEVEL RISE
... While the coastal flood loss projections presented are undoubtedly significant, they likely represent an underestimate of overall costs. In an event where there is significant and widespread damage to the transit network, system restoration and repair costs are liable to be subject to macroeconomic forcings that could significantly increase overall repair costs (e.g., supply chain or labor availability constraints ;Olsen & Porter, 2011;Golan et al., 2021). Furthermore, the analysis presented here assumes that infrastructure managers will opt to fully repair assets or replace in-kind, rather than upgrading with more modern or expensive equipment. ...
Sea level rise (SLR) and associated increases in the frequency and intensity of coastal flooding pose a significant threat to coastal communities and the critical infrastructure upon which they rely. In coastal cities, rail transit systems are particularly sensitive to such increases in coastal flood exposure. Transit agencies, infrastructure managers, and planners are increasingly cognizant of these risks, yet current literature and practice lack methods for quantifying the costs of flooding for rail transit infrastructure. Consequently, current literature lacks methods for valuing transit-specific investments in climate change adaptation and provides little guidance on how transit agencies can decide between potential adaptation strategies, given prevailing uncertainties and their institutional priorities.
This thesis aims to address these gaps in literature and practice by first developing a coupled hydraulic and hydrodynamic model to assess the severity of coastal flood exposure (i.e., flood depths) for rail rapid transit systems (inclusive of their underground spaces) under present and future SLR conditions. Relying on novel transit-specific depth-damage curves collected via structured expert judgement, we translate event-specific flood depth estimates into direct damage costs via a novel flood damage cost estimation framework, considering uncertainty and variability in damage outcomes. We next estimate how expected annualized losses (EAL) increase over time with uncertain future SLR. Recognizing that future flood damage costs are less consequential than present damage costs, we propose a novel fair market value (FMV) discounting approach and demonstrate flood risk-related cash flows exhibit low correlation to the market and can therefore be discounted near the risk-free rate. Applying this finding in conjunction with the flood damage cost estimation model, we value investments in climate adaptation projects and explore the benefits of flexibly implementing proposed projects via real options analysis (ROA). Lastly, moving beyond valuation, we explore the tradeoffs inherent in planning adaptation investment across a rail rapid transit system given institutional priorities and objectives via a multi-criteria decision analysis (MCDA) framework.
Applying these methods to the Massachusetts Bay Transportation Authority (MBTA) rail rapid transit network, we find unprotected tunnel portals responsible for a disproportionate volume of tunnel inflow. Hydraulic connectivity of the central tunnel network allows flooding from one ingress location to propagate across the network. Consequently, we find effective adaptation measures protecting the central tunnel must function cohesively as a system to ensure a uniform level of protection. Absent adaptation, we observe coastal flood risk (measured by EAL) has more than doubled from 2008 to 2022 and is expected to grow 16% annually over the next decade under all SLR scenarios. Through a case study considering a regional adaptation pathway proposed by Climate Ready Boston, we demonstrate significant benefits to MBTA rail transit infrastructure, particularly when investments follow a flexible implementation pathway. Lastly, through a Blue Line case study, we find implementation of shore-based measures to be more favorable than transit-specific adaptation alternatives, when considering sampled institutional priorities.
... Additionally, one of the major problems faced by business owners whose buildings suffer extensive damage after a large-scale disaster occurs is the "demand surge" effect, that is, the temporary increase in the cost of rehabilitation or replacement of damaged property. It has been observed that the increase in demand is a function of the total amount of rehabilitation works, the time of reconstruction, the costs of materials, equipment and labor, the general expenses and profits of the contractor, the general economic situation, the handling of insurance claims and the decisions of insurance companies (Olsen and Porter 2011). Despite all these uncertainties, methodologies have been proposed to determine recovery times for buildings damaged by earthquakes (Gutiérrez et al. 2019; Morales and Lázaro 2019). ...
Los sismos ocurridos el 7 y 19 de septiembre de 2017 en México propiciaron grandes afectaciones a muchos negocios. Debido a que el sistema estructural, los elementos no estructurales y contenidos de los edificios se dañaron, las unidades económicas dejaron de operar por un determinado tiempo, por lo tanto, registraron pérdidas económicas considerables. No obstante, la paralización de las actividades empresariales también se derivó de efectos indirectos en los inmuebles, tales como la suspensión de servicios públicos de suministro, los efectos de vecindario, las afectaciones al personal y la interrupción de negocios contingente.
Con base en distintas técnicas de recolección de datos, tales como la aplicación de encuestas y la observación directa, en esta investigación se identifican las razones de cierre de los negocios a causa de estos sismos, además de que se determina el tiempo de interrupción de las operaciones y se estiman las pérdidas económicas suscitadas durante dicho período. Asimismo, se registran las estrategias que se implementaron para mantener o aumentar el nivel de ganancias habitual, se indican los incentivos recibidos para la reactivación empresarial y se estudia la recuperación de la productividad tras la reapertura. A partir de esto, se plantean ecuaciones sencillas para determinar de forma aproximada el tiempo de interrupción de un negocio tras un sismo y se aplican a locales comerciales hipotéticos.
El presente estudio permitirá mostrar que en la actualidad sigue habiendo construcciones altamente vulnerables sísmicamente, las cuales al dañarse no sólo pueden propiciar elevadas pérdidas económicas directas, sino que también grandes pérdidas por interrupción. Se pretende entonces ayudar a alertar a los negocios acerca de este peligro, así como generar conocimientos que sean útiles para formular estrategias que minimicen las pérdidas por sismo. Una de las conclusiones de esta tesis es que, aunque el tiempo de interrupción de las unidades económicas depende de múltiples factores, la participación de los Ingenieros Estructuristas es trascendental para poder minimizarlo, especialmente en la evaluación de la seguridad de los edificios y en el diseño de la rehabilitación de las distintas infraestructuras.
... In contrast, the marketdriven resourcing model requires homeowners to individually obtain private sector capital (e.g., personal savings, insurance, and home loans) to secure the construction resources necessary for post-disaster housing repair and reconstruction (Talbot et al. 2020). Within this capitalistic system, demand and pricing for local construction market resources (e.g., building materials and labor) temporarily spike following a disaster, a concept known as demand-surge (Olsen and Porter 2011). Disasters also exacerbate pre-existing socioeconomic inequities, creating barriers for homeowners trying to access financial capital and construction resources (Peacock et al. 2014). ...
... While the coastal flood loss projections presented are undoubtedly significant, they likely represent an underestimate of overall costs. In an event where there is significant and widespread damage to the transit network, system restoration and repair costs are liable to be subject to macroeconomic forcings that could significantly increase overall repair costs (e.g., supply chain or labor availability constraints 32,45,46 . Furthermore, the analysis presented here assumes that infrastructure managers will opt to fully repair assets or replace in-kind, rather than upgrading with more modern or expensive equipment. ...
Future sea level rise (SLR) and associated increases in the frequency and intensity of coastal flooding poses significant threats to coastal communities and transit systems. Yet current literature and practice lack methods for estimating flood damage costs to transit systems. Here, we construct an event-specific flood damage cost estimation framework for transit systems, simulating separately flood ingress into underground spaces. We apply this framework to the MBTA rail transit system in Boston, estimating damages under several coastal flood events with SLR and project expected annualized losses (EAL) through 2100 with uncertain SLR. We estimate EALs to the MBTA system have doubled since 2008 to 58 M/year by 2030 under all SLR scenarios. Our results suggest that absent adaptation schemes, particularly at tunnel ingress locations, coastal flood risk will continue to accelerate, potentially resulting in permanent inundation of underground and low-lying sections of the transit system.
... Maybe counter-intuitively, indirectly disasters can also generate benefits. For example, a demand surge for (re)construction services can lead to a boom in this sector for several years in the aftermath of a disaster Olsen and Porter (2011). Positive long-term dynamics can also occur when technological innovation and investment in better planning and design are generated by the shock event Hallegatte and Dumas (2009). ...
We investigate whether disasters can lead to innovation. We construct a US county-level panel of hurricane damages using climate data, hurricane tracks, and a wind field model and match these to patent applications by the location of their inventor over the last century in the United States. We examine both general innovation and patents that explicitly mention the terms ’hurricane’ or ’storm.’ In line with the current literature that hypothesizes innovative activity driven by shocks, in particular innovation intended to mitigate future shocks, we find that hurricanes lead to temporary boost in damage-mitigating patents a few years after the event. However, we also show there is long-term, lasting over two decades, general reduction of innovation after a damaging storm. We conclude that hurricanes, and possibly other types of disasters, cannot be viewed as a ’benefit in disguise,’ and that these events are unlikely to generate longer-term beneficial dynamics in an adversely affected location.
... Beyond production capacity reductions, situations of demand exceeding supply (i.e., excess demand) during reconstruction and recovery can also cause shortages. In particular, in many large-scale disasters, extensive property damage leads to substantial increases in household spending on durable goods, as has been documented for example following the 1995 Kobe Earthquake (Sawada andShimizutani, 2011), 2005 Hurricane Katrina, and other disasters (Olsen and Porter, 2011). ...
This paper compares economic recovery in the COVID-19 pandemic with other types of disasters, at the scale of businesses. As countries around the world struggle to emerge from the pandemic, studies of business impact and recovery have proliferated; however, pandemic research is often undertaken without the benefit of insights from long-standing research on past large-scale disruptive events, such as floods, storms, and earthquakes. This paper builds synergies between established knowledge on business recovery in disasters and emerging insights from the COVID-19 pandemic. It first proposes a disaster event taxonomy that allows the pandemic to be compared with natural hazard events from the perspective of economic disruption. The paper then identifies five key lessons on business recovery from disasters and compares them to empirical findings from the COVID-19 pandemic. For synthesis, a conceptual framework on business recovery is developed to support policy-makers to anticipate business recovery needs in economically disruptive events, including disasters.
Findings from the pandemic largely resonate with those from disasters. Recovery tends to be more difficult for small businesses, those vulnerable to supply chain problems, those facing disrupted markets, and locally-oriented businesses in heavily impacted neighborhoods. Disaster assistance that is fast and less restrictive provides more effective support for business recovery. Some differences emerge, however: substantial business disruption in the pandemic derived from changes in demand due to regulatory measures as well as consumer behaviour; businesses in high-income neighborhoods and central business districts were especially affected; and traditional forms of financial assistance may need to be reconsidered.
... Many studies have addressed the surge in demand. Olsen and Porter [20] reviewed demand surges and discussed their definitions, models, and common research themes. Huang et al. [9] pointed out that demand surges are significant demand increments in addition to regular demand. ...
With the rapid development of e-commerce, customers could order online to ensure timeliness. Therefore, e-commerce enterprises need to pick and distribute customers’ orders. These two operations are interdependent. Order picking needs to consider the vehicle route planning. At the same time, the vehicle route planning is also based on the batching of orders. Considering the demand surge scenario of food cold chain, with the shortest time and lowest cost to complete all distribution tasks as the objective, this paper aims at the integrated optimization of distribution scheduling and route planning, and establishes a mixed integer programming mathematical model. Finally, we design a three-stage heuristic algorithm to solve this problem, and use the actual data to carry out numerical experiments to verify the reliability and effectiveness of the mathematical model and heuristic algorithm.
... Oil and gas prices can also be affected. Demand surge can be quite substantial: commercial disaster modelers estimate a range of 20-50 percent, but it can be even greater [35,36]. ...
Impact Forecasting has developed a catastrophe flood model for Czechia to estimate insurance losses. The model is built on a dataset of 12,066 years of daily rainfall and temperature data for the European area, representing the current climate (LAERTES-EU). This dataset was used as input to the rainfall–runoff model, resulting in a series of daily river channel discharges. Using analyses of global and regional climate models dealing with the impacts of climate change, this dataset was adjusted for the individual RCP climate scenarios in Europe. The river channel discharges were then re-derived using the already calibrated rainfall–runoff models. Based on the changed discharges, alternative versions of the standard catastrophe flood model for the Czechia were created for the various climate scenarios. In outputs, differences in severity, intensity, and number of events might be observed, as well as the size of storms. The effect on the losses might be investigated by probable maximum losses (PML) curves and average annual loss (AAL) values. For return period 1 in 5 years for the worst-case scenario, the differences can be up to +125 percent increase in insurance losses, while for the return period 1 in 100 years it is a −40 percent decrease. There is no significant effect of adaptation measures for the return period 1 in 100 years, but there is a −20 percent decrease in the return period 1 in 5 years.
... Additionally, one of the major problems faced by business owners whose buildings suffer extensive damage after a large-scale disaster occurs is the "demand surge" effect, that is, the temporary increase in the cost of rehabilitation or replacement of damaged property. It has been observed that the increase in demand is a function of the total amount of rehabilitation works, the time of reconstruction, the costs of materials, equipment and labor, the general expenses and profits of the contractor, the general economic situation, the handling of insurance claims and the decisions of insurance companies (Olsen and Porter 2011). Despite all these uncertainties, methodologies have been proposed to determine recovery times for buildings damaged by earthquakes (Gutiérrez et al. 2019; Morales and Lázaro 2019). ...
After an earthquake, a business often stops operating temporarily or permanently due to direct effects on the building (Initial security protocols and Physical damage to building components) or indirect effects (Suspension of public services, Neighborhood effects, Direct affectations to owner or employees and Contingent business interruption). In this research, we collected data from surveys applied in October and November 2019 to 227 micro-businesses established predominantly in buildings made of masonry or adobe of one and two storyes and located in three of the most damaged areas of Oaxaca by the earthquake of September 7th, 2017 to find out how this incident affected them. It has been observed that, out of the total of the surveyed businesses, 44% had to close for more than three months and that the two main sources of interruption were damages in the structural system or in the non-structural elements of the building and the absence of customers, and that 31% of the businesses that were already in operation considered that they had not yet recovered their productivity. Based on the information obtained from the surveys, it was possible to propose equations to determine the Business Interruption time. Finally, these equations are exemplified with a hypothetical business and the importance of the actions that the owners must take in a timely manner to potentially reduce the interruption time of their economic unit in the event of an earthquake is shown.
... This value is larger than the cost of a new building since the costs of demolishment and of debris removal should be added to the original cost. Moreover, the occurrence of a natural disaster often leads to higher repair costs for the same damage and hence to an increase of monetary losses [57]. ...
p>This study investigates the structural vulnerability of an old reinforced concrete dual wall-frame building structure, in Lisbon, Portugal. The building presents non-ductile behaviour and detailing typical of buildings designed before the introduction of modern seismic codes (pre– 1980). An analytical methodology is adopted in which multiple stripe analysis are performed on a three- dimensional model of the building. Fragility and vulnerability functions are developed for this structure, representative of a typology of old RC buildings. The fragility is derived taking into account the brittle shear failures of RC vertical members, i.e. columns and shear walls. The nonlinear dynamic analyses clearly indicate that these failure modes have a critical influence on the seismic performance of the structure. The results of this study can be used for seismic loss assessment and for the identification of appropriate mitigation strategies for this typology of existing RC buildings.</p
... Reconstruction after a disaster comes with the notion of building back better, with resiliency against future disasters, which increases the reconstruction costs even more [22,23]. One of the best strategies for completing a reconstruction project within budget is to identify the factors that affect its cost [24,25]; however, few studies have investigated these factors and limited literature is available on the subject. In addition, not all disasters damage transportation infrastructures at the same level [26], which means that the resources and financial needs are different for the various levels of damage. ...
With the increase in frequency and intensity of natural disasters, the number of transportation infrastructures needing reconstruction is also increasing. Insufficient financial resources and cost overruns
are among the major limitations that affect the reconstruction works of the transportation infrastructure after a disaster; however, there are few resources to help practitioners monitor the cost of reconstruction
and keep it within the allocated budget. This study aims to provide a comprehensive list of the critical factors that affect the reconstruction cost (CFRC) of transportation infrastructures after a disaster, and to
categorize them, based on the level of damage incurred. A survey was conducted to determine the importance of 30 potential CFRCs, and the survey results were statistically analyzed. It was found that effective coordination plays a critical role in completing a project within the budget limitations, a slow
decision-making process slows the reconstruction efforts and increases the probability of cost overruns, and the reconstruction cost of transportation infrastructures with a high level of damage are dependent on more factors than infrastructures with a low level of damage. For example, when the damage level is low, fewer disruptions to traffic are necessary during the reconstruction than if the damage level is high. When the damage level is high, the likelihood of more traffic disturbance is greater, which has the potential to create unforeseen costs and/or cost overruns. The outcome of this paper will be of value to the authorities who are responsible for controlling budget overruns during post-disaster reconstruction projects.
... In reality, postreconstruction economies are sometimes notably different from predisaster ones 53 . In addition, postdisaster demand surge, which can increase the cost of repairs by 20% or more 54 , has not been considered. Finally, the macro-economic impact of the disaster depends on the stage of the business cycle. ...
Natural disaster risk assessments typically consider environmental hazard and physical damage, neglecting to quantify how asset losses affect households’ well-being. However, for a given asset loss, a wealthy household might quickly recover, while a poor household might suffer major, long-lasting impacts. This research proposes a methodology to quantify disaster impacts more equitably by integrating the three pillars of sustainability: environmental (hazard and asset damage), economic (macro-economic changes in production and employment) and social (disaster recovery at the household level). The model innovates by assessing the impacts of disasters on people’s consumption, considering asset losses and changes in income, among other factors. We apply the model to a hypothetical earthquake in the San Francisco Bay Area, considering the differential impact of consumption loss on households of varying wealth. The analysis reveals that poorer households suffer 19% of the asset losses but 41% of the well-being losses. Furthermore, we demonstrate that the effectiveness of specific policies varies across cities (depending on their built environment and social and economic profiles) and income groups.
... Causes for under and non-insurance are diverse, ranging from affordability and accessibility (TAGT 2018;Victorian Council of Social Services 2017), to distrust in the insurance industry (Booth and Tranter 2018), and price hikes associated with demand surge post disaster (Olsen and Porter 2011). More recently, a new source of underinsurance has emerged with changes to Australian building regulations: Bushfire Attack Level (BAL) rating. ...
Home and contents insurance is integral to household and community resilience against disasters. Yet many households are underinsured. While causes for underinsurance have been widely researched, changes to Australian building regulations in the last decade has established a new source of insurance miscalculations. Bushfire Attack Level (BAL) ratings can inflate rebuilding costs by 20% or more, yet BAL ratings remain obfuscated to homeowners and are notoriously confusing to navigate. After the October 2013 bushfires in New South Wales, the Blue Mountains Local Recovery Steering Group found that ‘information on the BAL process, the guidelines, the expected costs, the consulting experts and a property’s bushfire-prone status is literally all over the place’. This paper aims to provide clarity on the subject, tracing the precise socio-technical means through which disaster risk is perceived and assessed. The paper conceptualises insurance and risk ratings as calculative devices that provide both a technical solution to reduce financial losses and a philosophical tool for risk rationalisation. It then builds on interviews conducted with residents in the Blue Mountains affected by the 2013 bushfires, to ascertain how such calculative devices practically affect communities at risk. The paper concludes by outlining potential solutions to a confusing and costly problem in Australia, highlighting critical public awareness issues surround BAL ratings, which have profound insurance and wellbeing implications for people rebuilding and recovering from bushfire.
... This value is larger than the cost of a new building since the costs of demolishment and of debris removal should be added to the original cost. Moreover, the occurrence of a natural disaster often leads to higher repair costs for the same damage and hence to an increase of monetary losses [57]. ...
... Affordability issues are amplified by insufficient market competition and a history of ''inefficient'' government taxes and levies (Coppel and Chester 2014;Tooth 2015). Other well-documented factors have included difficulties understanding insurance products (Enright 2013), a lack of consumer awareness of supplementary costs such as temporary accommodation and landscaping (Teague et al. 2010), cost deviations such as demand surges and changes to building regulations (Olsen and Porter 2011;Legal Aid 2014), problems calculating ''sum insured'' (ASIC 2014), and risk misunderstandings (Box et al. 2016). As insurance decision making is not simply based on an individual's rational calculation of potential risks, households implicitly or explicitly bring social and material concerns to bear when purchasing a policy and this can also contribute to Government (2010) underinsurance (Booth and Harwood 2016;Booth and Tranter 2017). ...
Australian households are increasingly vulnerable to natural hazard-related disasters. To manage disaster risk, government commissioned inquiries have called for greater investment in mitigation. This article critically examines the call for a shift in funding priority towards pre-disaster mitigation measures, in the context of growing concerns around the ability of households to access and afford insurance. It examines mitigation measures in the context of three prominent Australian disasters: the Black Saturday bushfires (Victoria, 2009), the Queensland floods (2010–2011), and Cyclone Yasi (Queensland, 2011). We argue that as a mode of disaster security, mitigation operates as a complex assemblage of logics and practices of protection, preparedness, and resilience, which problematizes simplistic protection/resilience binaries. On the one hand, mitigation serves as a mode of protection, which underscores the dominant maladaptive rationality of insurance. It promises a collective solution to uninsurability that is limited by government fiscal constraints and growing employment of risk-reflective insurance pricing. On the other hand, there is evidence of an emergent rationality of household insurance as a path to resilience and preparedness—for example, in the development of insurance systems that price household retrofitting technologies and in the development of policyholder education campaigns. This resilience rationality holds the promise of securing individuals previously excluded from insurance. However, for householders lacking the necessary physical, cognitive, and financial capacities to make themselves and their properties resilient, the transition to a pre-disaster mitigation mode of security will likely do little to alleviate disadvantage and marginalization.
... Consumer spending and economic conditions such as wages and employment are major drivers of retail sales. In the immediate aftermath of a disaster, the demand for products and services often exceeds the regional capacity to efficiently supply them and therefore drives up prices (Olsen and Porter 2011). Demand surge, as it is often referred to, tends to be temporary in nature and adds extra financial burden to individuals and organizations during recovery. ...
This paper focuses on exploring the capability of the recently developed Hurricane Resiliency Index (HRI) to predict future changes in sales tax revenues at the local level. Monthly data for Houston metropolitan statistical area (MSA) is used to forecast sales tax revenue in retail, utility, and construction industry sectors. With variants of the vector autoregressive (VAR) model, we compare the predictive power of using the HRI to the Federal Reserve Bank of Dallas's Metro Business Cycle Index. The VAR model augmented with the HRI generally provides better forecasts than the model with the Metro Business Cycle Index. The findings indicate that the HRI is a useful and reliable revenue-forecasting tool for local governments and policymakers in the wake of extreme events like hurricanes.
... For example, after the Indonesian tsunami several studies noted that timely supplies in Ache were inadequate so timber had to be imported from abroad (Silva, 2010); however, international actors did not have the appropriate skill sets to import timber. Also, it was identified that at the peak of reconstruction after the Sichuan earthquake, the price of bricks rose 127%, aggregate 125% and cement 30% due to lack of supply (Amaratunga and Haigh, 2011), and after Hurricane Katrina, reconstruction costs increased between 10% and 40% (Olsen and Porter, 2011). Post-disaster response and recovery may therefore increase demand for goods and services, creating shortage of supply and excess of demand resulting in higher inflation rates, national budget deficit, and imbalances in foreign trade. ...
Disasters' costs have risen dramatically in the last two decades, suggesting an increase in economic vulnerability. In 2011 alone worldwide disaster costs reached 380 billion dollars. Meanwhile, liberalisation of international trade has greatly increased economic interdependencies between countries. It is highly likely that trade liberalisation is linked to increased hazard vulnerability and costs but also represents opportunities for disaster recovery and reconstruction. This paper explores the nexus between international trade and disaster reconstruction. The focus is on the reconstruction market and how this relates to global trade arrangements. A review of international trade and disaster management literature was conducted and common themes were identified. The results were then applied to the case study of Pakistan. Almost no papers exist that specifically analyse how a country's trade situation impacts their capacity for post-disaster reconstruction. However, there is evidence that reconstruction costs rise following a disaster, quality of materials falls, and there are multiple resourcing challenges that delay reconstruction and increase costs. International trade could guarantee quality materials at international standards, stabilise costs, and speed up reconstruction. However, the evidence shows that international trade is rarely considered in the disaster management field, and disaster management is rarely considered in the formulation of trade policies. Therefore, mechanisms are needed to facilitate an international trade-based response to disasters. To be effective, these mechanisms need to be formulated and agreed upon prior to a disaster occurrence.
... Firms will build up reactive specie in order to mitigate the disruptive impact of sudden demand surge (Huang et al., 2016). Olsen and Porter (2011) review demand surge and discuss its definitions, models, and common research topics. In general, many scholars focus on the demand surge in product supply chains. ...
This paper studies a two-echelon logistics service supply chain (LSSC) composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP). We develop a two-period service capacity procurement model where market demand surges in the second period. The LSI, as the Stackelberg game leader, tends to be overconfident when market demand surges. The results show that when the demand surges in the second period, if the overconfident purchasing capacity of LSI cannot meet the market demand, the overconfidence behaviour will negatively affect LSI's optimal pricing. Besides, the overconfidence behaviour leads to the lowest service level of the FLSP in the second period under demand surge. However, such negative impacts can be reduced or even eliminated in certain conditions through the FLSP-led mechanism and the dynamic wholesale price mechanism. The numerical simulation and the case study from China are used to illustrate the model and draw some conclusions.
Big data has become omnipresent since most human activities are recorded using various technologies, thus generating huge databases on various platforms such as social media. Human activity has become reflected in these databases, making them suitable for various research that used to be conducted based on more traditional research approaches, such as survey research. Labour markets research is also affected by big data since social media has become one of the most dominant means of communication in various areas, being employed as one of them. This paper aims to map the research field of big data and labor markets using a systematic literature review and bibliography. Web of Science database has been searched using the keywords "big data" and "labo(u)r market". The most relevant papers for the area of big data for labour analysis have been selected, using transparent and consistent criteria. Papers have been analysed using a bibliometric approach supported by the VOSviewer and R bibliometrix, which has been used for detecting various research trends, such as research topics. The assessment of the current research in big data for the labour market has been compiled to detect the research gaps and generate future research directions.
This article presents an integrated framework for portfolio seismic risk assessment. The framework includes a systematic approach to the collection and categorization of exposed assets, and a robust method that combines vulnerabilities of different levels of resolution, including detailed vulnerabilities based on Federal Emergency Management Agency (FEMA) P-58 and REDi analyses, to produce efficient portfolio-level assessment. The vulnerability information encodes risk information that directly addresses the decision-support needs of stakeholders, including the benefits of seismic retrofit. The proposed framework is applied to a spatially distributed infrastructure portfolio composed of over 1000 public school buildings across Makati and Quezon City, in the Metro Manila region in Philippines, to demonstrate the value of portfolio-level seismic risk mitigation strategies. This study illustrates that the proposed regional seismic risk assessment approach can provide more reliable regional risk assessments in a computationally efficient manner and is able to quantify different risk contributors and identify cost-drivers that can be targeted for performance-based risk management of large portfolios.
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.
New Zealand is a hazard-prone country and experiences one of the highest rates of seismic activity in the world. While a wide range of tools have been developed in previous decades to support strategic and tactical decisions for post-disaster recovery, a challenge exists in identifying critical human resources to meet the demand of post-disaster infrastructure rebuild. Based on two case studies of the 2010–2011 Canterbury earthquakes and 2016 Kaikōura earthquake, this paper aims to explore whether relevant professionals involved in the infrastructure recovery from 2010 to 2011 earthquakes were mobilised to the 2016 earthquake and what mechanisms employed and challenges faced to utilise their expertise in a systematic way. This research highlights that a gap remains in incorporating expertise and advisory capacities from the former event to the latter one due to rapid staff turnover in recovery organisations and lack of information regarding infrastructure recovery experts. Addressing these issues is important, as such expertise and advisory capacities may set the tone for disaster management and significantly impact the quality of infrastructure rebuild in New Zealand and many other countries.
The United States is one of the top five countries in the world prone to natural hazards. Natural hazards could have a significant impact on the construction industry. In a large-scale disaster, labor cost fluctuation is known to be an important driving factor in the construction cost increases. Labor cost fluctuation could increase the reconstruction cost by 20 to 50 percent after a large-scale disaster. Although the effect of disaster’s scale on construction cost has been determined in the literature, the role of construction market conditions on the post-disaster construction labor wage fluctuations has not been studied. The objective of this study is to quantify the relationship between pre-disaster construction market conditions and post-disaster construction labor wage fluctuations in the construction industry considering time dependency, using panel data models. Four commonly used construction market indicators are used within panel data models to explore this relationship. Historical county-level data of 532 counties impacted by weather-related disasters (flood, tornado, and storm) from 2014 to 2017 are collected to conduct the analysis. This study showed that there is a significant relationship between the construction employment level, construction contribution, and average weekly wage with post-disaster construction labor wage fluctuations. The results indicated that both, construction contribution, and average weekly wage have a negative effect on the labor wage increase after a natural disaster. This study helps construction companies, property owners, regulators, insurers, and cost engineers to have a better understanding of post-disaster construction cost variations aftermath of a natural disaster.
Purpose
The primary objectives of this study are to (1) highlight subsectors and industry groups of the construction sector that are most vulnerable to weather-related disasters (with highest labor cost escalation) and (2) analyze how immediate this labor wage escalation happens in different subsector of the construction sector.
Design/methodology/approach
The research methodology consists of three steps: (i) integrating various data sources to enable measurement of the county-level labor wage changes following large-scale weather-related disasters; (ii) measuring postdisaster labor wage changes at the county level; and (iii) comparing amount and timing of postdisaster labor wage changes among all sub-sectors (and industry groups) of the construction sector.
Findings
The results show that among the three construction subsectors (Heavy and Civil Engineering Construction subsector, Construction of Buildings subsector, and Specialty Trade Contractors sub-sector), Heavy and Civil Engineering Construction subsector is the most vulnerable to weather-related disasters. The industry groups under the Heavy and Civil Engineering Construction subsector showed the same vulnerability level; however, under the Construction of Buildings subsector, Industrial Building Construction industry group showed to be the most vulnerable; and under the Specialty Trade Contractors subsector, the Building Foundation and Exterior Contractors industry group is the most vulnerable. The results also showed that in approximately 75% of the damaged counties, there were increases in wages of all construction labors, over the following three quarter after the disasters. In average, labor wages in Construction of Buildings subsector and the Specialty Trade Contractors subsector decreased by 0.6% and 0.8%, respectively, in the quarter of disaster and gradually increased by 4.4% and 4.6%, respectively, in the following three quarters. On the other hand, Heavy and Civil Engineering Construction’s labor wages did not experience this decrease right after the disasters; wages increased immediately after disasters hit the counties and continually increased by 8.6% in three quarters after the disasters. It is expected that the results of this study will help policy makers, cost estimators and insurers to have a better understanding of the post-disaster construction labor wage fluctuations.
Originality/value
This study is unique in the way it used construction labor wage data. All data are location quotient, which makes the comparison among the affected counties (with different construction size) feasible.
The postdisaster survival of communities and cities largely depends on their capabilities to rapidly reconstruct damages. Temporary increases in construction costs following natural hazards, also known as demand surge, impede the rapid postdisaster reconstruction process. Existing methods for quantifying postdisaster construction cost escalations do not consider seasonal patterns and inflation of costs under normal conditions. Therefore, it is not clear whether the quantified construction cost increases are due to a disaster or merely associated with seasonal patterns and inflation. The objectives of this study are to (1) create an approach to statistically quantify postdisaster construction material cost fluctuations considering regional seasonal patterns and inflation of construction material costs in normal condition (no disaster); and (2) apply the approach to identify the most vulnerable construction materials following Hurricane Katrina in New Orleans, Louisiana. The authors created an approach based on cumulative sum (CUSUM) control charts and seasonal autoregressive integrated moving average (seasonal ARIMA) models to measure postdisaster construction material cost fluctuations. This approach is applied to quantify construction material cost fluctuations following Hurricane Katrina in New Orleans, Louisiana. The results indicate three different patterns in the postdisaster cost movements: (1) a statistically significant increase in the cost of materials such as I-beams and channel beams, (2) a statistically significant decrease in the cost of materials such as pine lumber, and (3) no statistically significant changes in the cost of materials such as reinforced concrete pipes. These findings are expected to help property insurers, capital planners, and construction engineers to estimate postdisaster cost fluctuations more accurately. They also help identify the most vulnerable construction materials to disasters.
The postdisaster survival of communities and cities largely depends on their capabilities to rapidly reconstruct damages. Temporary increases in construction costs following natural hazards, also known as demand surge, impede the rapid postdisaster reconstruction process. Existing methods for quantifying postdisaster construction cost escalations do not consider seasonal patterns and inflation of costs under normal conditions. Therefore, it is not clear whether the quantified construction cost increases are due to a disaster or merely associated with seasonal patterns and inflation. The objectives of this study are to (1) create an approach to statistically quantify postdisaster construction material cost fluctuations considering regional seasonal patterns and inflation of construction material costs in normal condition (no disaster); and (2) apply the approach to identify the most vulnerable construction materials following Hurricane Katrina in New Orleans, Louisiana. The authors created an approach based on cumulative sum (CUSUM) control charts and seasonal autoregressive integrated moving average (seasonal ARIMA) models to measure postdisaster construction material cost fluctuations. This approach is applied to quantify construction material cost fluctuations following Hurricane Katrina in New Orleans, Louisiana. The results indicate three different patterns in the postdisaster cost movements: (1) a statistically significant increase in the cost of materials such as I-beams and channel beams, (2) a statistically significant decrease in the cost of materials such as pine lumber, and (3) no statistically significant changes in the cost of materials such as reinforced concrete pipes. These findings are expected to help property insurers, capital planners, and construction engineers to estimate postdisaster cost fluctuations more accurately. They also help identify the most vulnerable construction materials to disasters.
Insurance-linked securities provide capital market-based insurance against the risk of natural catastrophes. A challenge arising with the use of those instruments is their sponsor’s potential susceptibility towards moral hazard, which has not been studied in the empirical literature. This study examines whether the sponsors of CAT bonds with indemnity trigger – the currently most prominent type of insurance-linked security – are susceptible to ex-ante moral hazard (i.e., before the occurrence of a catastrophic event) and ex-post moral hazard (i.e., after a catastrophic event). Therefore, we apply panel regression and matching techniques to a comprehensive data set comprising US insurers’ annual statements and information on their activities as CAT bond sponsors. We propose a novel approach to measure moral hazard using the insurers’ loss adjustment expenses. Controlling for the unobserved heterogeneity and time-variant insurer characteristics, we find that sponsors using CAT bonds with indemnity trigger are susceptible to ex-ante moral hazard, but not affected by ex-post moral hazard. We further show that vertical loss retention has a positive effect on sponsors’ incentives to contain losses.
Quantifying the human influence on individual extreme weather events is a new and rapidly developing science. Understanding the influence of climate change on tropical cyclones poses special challenges due to their intensities and scales. We present a method designed to overcome these challenges using high-resolution hindcasts of individual tropical cyclones under their actual large-scale meteorological conditions, counterfactual conditions without human influences on the climate system, and scenarios of increased climate change. Two practical case studies are presented along with a discussion of the conditions and limitations of attribution statements that can be made with this hindcast attribution method.
An approach to assessing the damage potential of tropical cyclones (TCs) is developed using a combination of physical reasoning and results of previous studies. The key TC damage parameters of intensity, size, and translational speed are incorporated into a single index of Cyclone Damage Potential (CDP). The CDP is developed to represent offshore wind, wave, and current damage. Further testing is needed to establish the importance of each TC parameter for onshore wind and coastal surge damage. The CDP is applicable to individual TCs and to seasonal, global, and climatological assessments. Global climatological summaries reveal high damage potential pathways and the dominant contribution of the Northwest Pacific to total global damage potential. Assessing actual impact requires an additional step of combining the CDP with an exposure and vulnerability assessment derived from a range of local factors.
The postdisaster survival of cities and communities depends on their capabilities to reconstruct and repair damaged buildings following large-scale natural disasters. The socioeconomic phenomenon of increased construction costs following large-scale natural disasters, also called demand surge, cripples our capabilities to recover from disasters effectively. Labor cost fluctuation following natural disasters is known to be a driving factor in demand surge measurement. The relationship between construction labor wage fluctuations and disaster's magnitude has been defined in the literature. Despite the significant role of the construction industry in postdisaster labor cost fluctuations, the relationship between predisaster construction market conditions and postdisaster labor cost fluctuations has not been studied. The objective of this study is to quantify the relationship between predisaster residential construction market conditions and residential labor wage fluctuations following weather-related disasters. The historical county-level data on five construction market indicators (establishment count, contribution level, average weekly wages, employment level, and building permits) prior to disasters along with disaster magnitudes (property damage) were collected for more than 35 of the largest weather-related disasters (floods, storms, and tornadoes) in the United States. These disasters affected more than 400 counties from 2007 to 2014. Residential building labor cost changes were first measured for counties impacted by weather-related disasters. The multiple linear regression method was then utilized to quantify the relationship between predisaster residential construction market indicators and the percent change in residential building labor wages after weather-related disasters. The results show that changes in residential building labor wages following weather-related disasters depend on the predisaster level of construction market indicators and the interactions between indicators. It is expected that the results of this study will help cost engineers to prepare more accurate bids in the volatile postdisaster construction markets and help capital planners and postdisaster risk-mitigation agencies to identify the more vulnerable construction markets.
The quantification of economic losses from natural and manmade hazards is necessary to gauge individual and community vulnerability, evaluate the worthiness of mitigation, determine the appropriate level of disaster assistance, improve recovery decisions, and inform insurers of their potential liability. Several notable studies dealing with hazard loss estimation have recently been undertaken. These include chapters in surveys by the National Research Council (NRC, 1999; Mileti, 1999) and Heinz Center (2000), as well as various case studies (see, e.g., Cole, 1995; Tierney, 1997; Shinozuka et al., 1998; Gordon et al., 1998; Chang et al., 2001).
Will bring together collective wisdom of the three leading firms in this area (AIR Worldwide, EQECAT, RMS) with the Wharton team on how to assess the risk from natural hazards • Will explicitly address uncertainty in the context of catastrophe modeling, illustrating the nature of uncertainty in different case studies (e.g., Charleston, South Carolina region) • Will illustrate the linkage of risk assessment and risk management through insurance rate making, insurance portfolio management and risk financing • Will illustrate how uncertainty and risk transfer mechanisms affects the analysis of mitigation using three model cities (Oakland, Long Beach, Miami/Dade County) Audience for the Book The audience for this book is a sophisticated risk manager or policy maker who has some appreciation for the role that modeling and quantitative analysis can play in improving the decision making process. The September 11 th terrorist attacks and ensuing activities makes this book more relevant than before given the interest by the private and public sectors in risk analysis and risk management for extreme events. The book could also be used in courses in risk management.
Analyzing economic impacts of disasters has attracted interest from a wide audience in recent years, not only because of the frequent occurrence of large natural disasters worldwide but also because of the spread of terrorism to a global scale. This paper reviews past modeling studies for economic impact analysis of disasters, focusing especially on the input-output model and related modeling frameworks, such as the social accounting matrix and the computable general equilibrium model. The paper also discusses the issues of disaster modeling raised by the literature, and proposes some future directions.
The potential impact of Hurricane Katrina, which is expected to give inflation in the construction industry of US markets, is discussed. The major uncertainty relates to the price and availability of building materials, which means in the near term that the construction industry will continue to adjust to a higher cost structure. RISI predicts that OSB prices in the year 2006 will decline 34% to 32 less than what they were before the storm. RISI's forecast is based on an anticipated slowdown in the national housing market for economic reasons unrelated to Katrina.
The growth of prices and slow deliveries due to heavy demand for construction machines in the American economy is discussed. The region's need for equipment over the next 12 months is going to be twice the normal demand. Machinery analysts have forecasted per-unit sales of construction equipment to increase by a 8 to 10%. Hurricane Katrina is more likely to upset construction equipment supplies in the U.S. rather than on a global scale.
Big box stores, Home Depot and Lowe's, have an industry wide impact although their domain is non-professional do-it-yourself construction materials market. They have 50 percent of the do-it-yourself market and the traditional building materials distributors have been losing market share. After Katrina they presented just-in-time supply chains in the affected Gulf Coast. Wherever a big-box store opens it grows the market there by 20%. But still the market is firmly in the hands of wholesalers and distributors. Some contractors are not satisfied with big boxes' materials while some often turn to the big boxes when small volumes of materials are needed once a project is under way.
On August 24, 1992 Hurricane Andrew became the first major hurricane to attack south Florida in 57 years. Although adequate warnings were given as the storm approached, after the hurricane had passed, it was found that no plan was in place to provide a quick response for the victims. Workers and equipment needed to be repositioned and brought in from long distances. Hurricane-resistive building codes were found to be inadequate. Essential electrical power networks were lost. Manufactured homes were devastated. Obviously, changes would be needed to plan for the next major hurricane to hit the area.
Past information on Hurricane Iniki damage to Hawaii buildings of residential, commercial, and resort occupancies has been gathered and geo-referenced on GIS. Comprehensive reconstruction cost documentation has been combined with post-hurricane aerial photography and linked to a robust property tax database of construction type attributes and property valuation. Using the data available in the property tax records to define construction attributes, residential building fragilities and loss functions have been developed along with risk relativity factors. The resultant Damage Curves estimate hurricane damage to a wide variety of Hawaii building types as a function of peak gust windspeed.
This article proposes a new modeling framework to investigate the consequences of natural disasters and the following reconstruction phase. Based on input-output tables, its originalities are (1) the taking into account of sector production capacities and of both forward and backward propagations within the economic system; and (2) the introduction of adaptive behaviors. The model is used to simulate the response of the economy of Louisiana to the landfall of Katrina. The model is found consistent with available data, and provides two important insights. First, economic processes exacerbate direct losses, and total costs are estimated at 107 billion. When exploring the impacts of other possible disasters, it is found that total losses due to a disaster affecting Louisiana increase nonlinearly with respect to direct losses when the latter exceed 200 billion, for instance, total losses are twice as large as direct losses. For risk management, therefore, direct losses are insufficient measures of disaster consequences. Second, positive and negative backward propagation mechanisms are essential for the assessment of disaster consequences, and the taking into account of production capacities is necessary to avoid overestimating the positive effects of reconstruction. A systematic sensitivity analysis shows that, among all parameters, the overproduction capacity in the construction sector and the adaptation characteristic time are the most important.
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