This study explores the nature of smaller businesses’ resilience following two major earthquakes that severely disrupted their place of doing business. Data from the owners of ten smaller businesses are qualitative and longitudinal, spanning the period 2011 through 2018, providing first-hand narrative accounts of their responses in the earthquakes’ aftermath. All ten owners showed some individual resilience; six businesses survived through to 2018, of which three have recovered strongly. All three owned their premises; operated business-tobusiness models; and were able to adapt and continue to follow path-extension strategies. All the other businesses had direct business-to-customer models operating from leased premises, typically in major retail malls. Four eventually recognised path-exhaustion at different times and so did not survive through to 2018. We conclude however that post-disaster recovery is best explained in terms of business model resilience. Even the most resilient of individual owners will struggle to survive if their business model is either not resilient or cannot be made so. Individual resilience is necessary but not sufficient.
Small, tight-knit communities, are complex to manage from outside during a disaster. The township of Lyttelton, New Zealand, and the communities of Corsair Bay, Cass Bay, and Rapaki to the east, are especially more so difficult due to the terrain that encloses them, which caused them to be cut-off from Christchurch, the largest city in the South Island, barely 10 km away, after the Mw 7.1 Darfield Earthquake and subsequent Canterbury Earthquake Sequence. Lyttelton has a very strong and deep-rooted community spirit that draws people to want to be a part of Lyttelton life. It is predominantly residential on the slopes, with retail space, service and light industry nestled near the harbour. It has heritage buildings stretching back to the very foundation of Canterbury yet hosts the largest, modern deep-water port for the region. This study contains two surveys: one circulated shortly before the Darfield Earthquake and one circulated in July 2011, after the Christchurch and Sumner Earthquakes. An analytical comparison of the participants’ household preparedness for disaster before the Darfield Earthquake and after the Christchurch and Sumner Earthquakes was performed. A population spatiotemporal distribution map was produced that shows the population in three-hourly increments over a week to inform exposure to vulnerability to natural hazards. The study went on to analyse the responses of the participants in the immediate period following the Chrsitchurch and Sumner Earthquakes, including their homeward and subsequent journeys, and the decision to evacuate or stay in their homes. Possible predictors to a decision to evacuate some or all members of the household were tested. The study also asked participants’ views on the events since September 2010 for analysis.
In this thesis, focus is given to develop methodologies for rapidly estimating specific components of loss and downtime functions. The thesis proposes methodologies for deriving loss functions by (i) considering individual component performance; (ii) grouping them as per their performance characteristics; and (iii) applying them to similar building usage categories. The degree of variation in building stock and understanding their characteristics are important factors to be considered in the loss estimation methodology and the field surveys carried out to collect data add value to the study. To facilitate developing ‘downtime’ functions, this study investigates two key components of downtime: (i) time delay from post-event damage assessment of properties; and (ii) time delay in settling the insurance claims lodged. In these two areas, this research enables understanding of critical factors that influence certain aspects of downtime and suggests approaches to quantify those factors. By scrutinising the residential damage insurance claims data provided by the Earthquake Commission (EQC) for the 2010- 2011 Canterbury Earthquake Sequence (CES), this work provides insights into various processes of claims settlement, the time taken to complete them and the EQC loss contributions to building stock in Christchurch city and Canterbury region. The study has shown diligence in investigating the EQC insurance claim data obtained from the CES to get new insights and build confidence in the models developed and the results generated. The first stage of this research develops contribution functions (probabilistic relationships between the expected losses for a wide range of building components and the building’s maximum response) for common types of claddings used in New Zealand buildings combining the probabilistic density functions (developed using the quantity of claddings measured from Christchurch buildings), fragility functions (obtained from the published literature) and cost functions (developed based on inputs from builders) through Monte Carlo simulations. From the developed contribution functions, glazing, masonry veneer, monolithic and precast concrete cladding systems are found to incur 50% loss at inter-storey drift levels equal to 0.027, 0.003, 0.005 and 0.011, respectively. Further, the maximum expected cladding loss for glazing, masonry veneer, monolithic, precast concrete cladding systems are found to be 368.2, 331.9, 365.0, and 136.2 NZD per square meter of floor area, respectively. In the second stage of this research, a detailed cost breakdown of typical buildings designed and built for different purposes is conducted. The contributions of structural and non- structural components to the total building cost are compared for buildings of different usages, and based on the similar ratios of non-structural performance group costs to the structural performance group cost, four-building groups are identified; (i) Structural components dominant group: outdoor sports, stadiums, parkings and long-span warehouses, (ii) non- structural drift-sensitive components dominant group: houses, single-storey suburban buildings (all usages), theatres/halls, workshops and clubhouses, (iii) non-structural acceleration- sensitive components dominant group: hospitals, research labs, museums and retail/cold stores, and (iv) apartments, hotels, offices, industrials, indoor sports, classrooms, devotionals and aquariums. By statistically analysing the cost breakdowns, performance group weighting factors are proposed for structural, and acceleration-sensitive and drift-sensitive non-structural components for all four building groups. Thus proposed building usage groupings and corresponding weighting factors facilitate rapid seismic loss estimation of any type of building given the EDPs at storey levels are known. A model for the quantification of post-earthquake inspection duration is developed in the third stage of this research. Herein, phase durations for the three assessment phases (one rapid impact and two rapid building) are computed using the number of buildings needing inspections, the number of engineers involved in inspections and a phase duration coefficient (which considers the median building inspection time, efficiency of engineer and the number of engineers involved in each assessment teams). The proposed model can be used: (i) by national/regional authorities to decide the length of the emergency period following a major earthquake, and estimate the number of engineers required to conduct a post-earthquake inspection within the desired emergency period, and (ii) to quantify the delay due to inspection for the downtime modelling framework. The final stage of this research investigates the repair costs and insurance claim settlement time for damaged residential buildings in the 2010-2011 Canterbury earthquake sequence. Based on the EQC claim settlement process, claims are categorized into three groups; (i) Small Claims: claims less than NZD15,000 which were settled through cash payment, (ii) Medium Claims: claims less than NZD100,000 which were managed through Canterbury Home Repair Programme (CHRP), and (iii) Large Claims: claims above NZD100,000 which were managed by an insurance provider. The regional loss ratio (RLR) for greater Christchurch for three events inducing shakings of approximate seismic intensities 6, 7, and 8 are found to be 0.013, 0.066, and 0.171, respectively. Furthermore, the claim duration (time between an event and the claim lodgement date), assessment duration (time between the claim lodgement day and the most recent assessment day), and repair duration (time between the most recent assessment day and the repair completion day) for the insured residential buildings in the region affected by the Canterbury earthquake sequence is found to be in the range of 0.5-4 weeks, 1.5- 5 months, and 1-3 years, respectively. The results of this phase will provide useful information to earthquake engineering researchers working on seismic risk/loss and insurance modelling.
