Using greater Christchurch as a case study, this research seeks to understand the key drivers of residential choice of families with children who live in recently developed, low-density greenfield subdivisions. In particular, the research examines the role that transport-related implications play in families’ choice of residence and location. It also explores the lived experience of the quotidian travel of these households, and the intrinsic value of their time in the car. While the research is situated in one particular location, it is designed to gain an understanding of urban processes and residents’ experiences of these as applicable to broader settings. Concerns about the pernicious environmental, fiscal, and wellbeing effects of sprawling urban form have been growing over the past few decades, inciting many cities including Christchurch to start shifting planning policies to try and achieve greater intensification and a denser development pattern. The 2010/2011 Christchurch earthquake sequence and its destruction of thousands of homes however created huge pressure for housing development, the bulk of which is now occurring on greenfield sites on the peripheries of Christchurch City and its neighbouring towns. Drawing on the insights provided by a wide body of both qualitative and quantitative literature on residential choice, transport and urban form, and mobilities literature as a basis, this research is interested in the attraction of these growing neighbourhoods to families, and puts the focus firmly on the attitudes, values, motivations, decisions, and lived experience of those who live in the growing suburbs of Christchurch.
The New Zealand city of Christchurch suffered a series of devastating earthquakes in 2010-11 that changed the urban landscape forever. A new rebuilt city is now underway, largely based on the expressed wishes of the populace to see Christchurch return to being a more people-oriented, cycle-friendly city that it was known for in decades past. Currently 7% of commuters cycle to work, supported by a 200km network of mostly conventional on-road painted cycle lanes and off-road shared paths. The new "Major Cycleways" plan aims to develop approximately 100km of high-quality cycling routes throughout the city in 5-7 years. The target audience is an unaccompanied 10-year-old cycling, which requires more separated cycleways and low-volume/speed "neighbourhood greenways" to meet this standard. This presentation summarises the steps undertaken to date to start delivering this network. Various pieces of research have helped to identify the types of infrastructure preferred by those currently not regularly cycling, as well as helping to assess the merits of different route choices. Conceptual cycleway guidelines have now been translated into detailed design principles for the different types of infrastructure being planned. While much of this work is based on successful designs from overseas, including professional advice from Dutch practitioners, an interesting challenge has been to adapt these designs as required to suit local road environments and road user expectations. The first parts of the new network are being rolled out now, with the hope that this will produce an attractive and resilient network for the future population that leads to cycling being a major part of the local way of life.
When disasters and crises, both man-made and natural, occur, resilient higher education institutions adapt in order to continue teaching and research. This may necessitate the closure of the whole institution, a building and/or other essential infrastructure. In disasters of large scale the impact can be felt for many years. There is an increasing recognition of the need for disaster planning to restructure educational institutions so that they become more resilient to challenges including natural disasters (Seville, Hawker, & Lyttle, 2012).The University of Canterbury (UC) was affected by seismic events that resulted in the closure of the University in September 2010 for 10 days and two weeks at the start of the 2011 academic year This case study research describes ways in which e-learning was deployed and developed by the University to continue and even to improve learning and teaching in the aftermath of a series of earthquakes in 2010 and 2011. A qualitative intrinsic embedded/nested single case study design was chosen for the study. The population was the management, support staff and educators at the University of Canterbury. Participants were recruited with purposive sampling using a snowball strategy where the early key participants were encouraged to recommend further participants. Four sources of data were identified: (1) documents such as policy, reports and guidelines; (2) emails from leaders of the colleges and academics; (3) communications from senior management team posted on the university website during and after the seismic activity of 2010 and 2011; and (4) semi-structured interviews of academics, support staff and members of senior management team. A series of inductive descriptive content analyses identified a number of themes in the data. The Technology Acceptance Model 2 (Venkatesh & Davis, 2000) and the Indicator of Resilience Model (Resilient Organisations, 2012) were used for additional analyses of each of the three cases. Within the University case, the cases of two contrasting Colleges were embedded to produce a total of three case studies describing e-learning from 2000 - 2014. One contrast was the extent of e-learning deployment at the colleges: The College of Education was a leader in the field, while the College of Business and Law had relatively little e-learning at the time of the first earthquake in September 2010. The following six themes emerged from the analyses: Communication about crises, IT infrastructure, Availability of e-learning technologies, Support in the use of e-learning technologies, Timing of crises in academic year and Strategic planning for e-learning. One of the findings confirmed earlier research that communication to members of an organisation and the general public about crises and the recovery from crises is important. The use of communication channels, which students were familiar with and already using, aided the dissemination of the information that UC would be using e-learning as one of the options to complete the academic year. It was also found that e-learning tools were invaluable during the crises and facilitated teaching and learning whilst freeing limited campus space for essential activities and that IT infrastructure was essential to e-learning. The range of e-learning tools and their deployment evolved over the years influenced by repeated crises and facilitated by the availability of centrally located support from the e-Learning support team for a limited set of tools, as well as more localised support and collaboration with colleagues. Furthermore, the reasons and/or rate of e-learning adoption in an educational institution during crises varied with the time of the academic year and the needs of the institution at the time. The duration of the crises also affected the adoption of e-learning. Finally, UC’s lack of an explicit e-learning strategy influenced the two colleges to develop college-specific e-learning plans and those College plans complemented the incorporation of e-learning for the first time in the University’s teaching and learning strategy in 2013. Twelve out of the 13 indicators of the Indicators of Resilience Model were found in the data collected for the study and could be explained using the model; it revealed that UC has become more resilient with e-learning in the aftermath of the seismic activities in 2010 and 2011. The interpretation of the results using TAM2 demonstrated that the adoption of technologies during crises aided in overcoming barriers to learning at the time of the crisis. The recommendations from this study are that in times of crises, educational institutions take advantage of Cloud computing to communicate with members of the institution and stakeholders. Also, that the architecture of a university’s IT infrastructure be made more resilient by increasing redundancy, backup and security, centralisation and Cloud computing. In addition, when under stress it is recommended that new tools are only introduced when they are essential.
