The coordination of actors has been a major focus for much of the research in the disaster relief humanitarian logistics discipline. While much of this literature focuses on the initial response phase, little has been written on the longer term recover phase. As the response phase transitions into the longer term recover phase the number and types of actors change from predominantly disaster relief NGOs to more commercial entities we argue that humanitarian values should still be part of the rebuild phase. It has been noted that humanitarian actors both cooperate and compete at the same time (Balcik, Beamon, Krejci, Muramatsu and Ramirez, 2010), in a form of behavior that can be described as ‘co-opetition’ (Nalebuff and Brandenburger, 1996). We use a case study approach to examine an organizational model used to coordinate civil and commercial actors for the rebuild of the civil infrastructure for Christchurch, New Zealand following a series of devastating earthquakes in 2010/11. For the rebuild phase we argue that ‘co-opetition’ is a key behaviour that allows the blending of humanitarian and commercial values to help communities rebuild to a new normal. While at this early stage our contribution is limited, we eventually hope to fully elaborate on an organisational model that has been created specifically for the tight coordination of commercial actors and its relevance to the rebuild phase of a disaster. Examining the behaviour of co-opetition and the structures that incentivise this behaviour offers insights for the humanitarian logistic field.
The disastrous earthquakes that struck Christchurch in 2010 and 2011 seriously impacted on the individual and collective lives of Māori residents. This paper continues earlier, predominantly qualitative research on the immediate effects on Māori by presenting an analysis of a survey carried out 18 months after the most destructive event, on 22 February 2011. Using a set-theoretic approach, pathways to Māori resilience are identified, emphasising the combination of whānau connectivity and high incomes in those who have maintained or increased their wellbeing post-disaster. However, the results show that if resilience is used to describe a “bounce back” in wellbeing, Māori are primarily enduring the post-disaster environment. This endurance phase is a precursor to any resilience and will be of much longer duration than first thought. With continued uncertainty in the city and wider New Zealand economy, this endurance may not necessarily lead to a more secure environment for Māori in the city.
The Christchurch earthquakes brought to an abrupt halt a process of adaptive reuse and gentrification that was underway in the south eastern corner of the central business district. The retail uses that were a key to the success of this area pre-earthquake could be characterised as small, owner operated, quirky, bohemian, chaotic and relatively low rent. This research reports on the progress of a long term, comprehensive case study that follows the progress of these retailers both before and after the earthquakes. Findings include the immediate post-earthquake intentions to resume business in the same location as soon as possible were thwarted by government imposed cordons of the CBD that were only lifted nearly three years later. But, businesses were resilient and generally reinvented themselves quickly in alternative suburban locations where government “rebuild” restrictions were absent. It remains to be seen if this type of retail will ever return to the CBD as government imposed plans and the rents demanded for retail space in new buildings appear to preclude small owner-operated businesses.
Prognostic modelling provides an efficient means to analyse the coastal environment and provide effective knowledge for long term urban planning. This paper outlines how the use of SWAN and Xbeach numerical models within the ESRI ArcGIS interface can simulate geomorphological evolution through hydrodynamic forcing for the Greater Christchurch coastal environment. This research followed the data integration techniques of Silva and Taborda (2012) and utilises their beach morphological modelling tool (BeachMM tool). The statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 were examined to determine whether these requirements are currently being complied with when applying the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013), and it would appear that it does not meet those requirements. This is because coastal hazard risk has not been thoroughly quantified by the installation of the Canterbury Earthquake Recovery Authority (CERA) residential red zone. However, the Christchurch City Council’s (CCC) flood management area does provide an extent to which managed coastal retreat is a real option. This research assessed the effectiveness of the prognostic models, forecasted a coastline for 100 years from now, and simulated the physical effects of extreme events such as storm surge given these future predictions. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon similar to the CCC’s flood management area. There are complex interactions at the Waimakariri River mouth with very high rates of accretion and erosion within a small spatial scale due to the river discharge. There is domination of the marine environment over the river system determined by the lack of generation of a distinct river delta, and river channel has not formed within the intertidal zone clearly. The Avon-Heathcote ebb tidal delta aggrades on the innner fan and erodes on the outer fan due to wave domination. The BeachMM tool facilitates the role of spatial and temporal analysis effectively and the efficiency of that performance is determined by the computational operating system.
