Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response.
This study is a qualitative investigation into the decision-making behaviour of commercial property owners (investors and developers) who are rebuilding in a city centre after a major disaster. In 2010/2011, Christchurch, the largest city in the South Island of New Zealand, was a site of numerous earthquakes. The stronger earthquakes destroyed many buildings and public infrastructure in the commercial inner city. As a result, affected property owners lost all or most of their buildings, a significant proportion of which were old and in the last phase of their life span. They had to negotiate pay-outs with insurance companies and decide, once paid out, whether they should rebuild in Christchurch or sell up and invest elsewhere. The clear majority of those who decided to reinvest in and rebuild the city are ‘locals’, almost all of whom had no prior experience of property development. Thus, in a post-disaster environment, most of these property owners have transitioned from being just being passive investors to active property developers. Their experience was interpreted using primary data gathered from in-depth and semi-structured interviews with twenty-one “informed property people” who included commercial property owners; property agents or consultants; representatives of public-sector agencies and financial institutions. The study findings showed that the decision-making behaviour of property investors and developers rebuilding after a major disaster did not necessarily follow a strict financial or profit motive as prescribed in the mainstream or neo-classical economics property literature. Rather, their decision-making behaviour has been largely shaped by emotional connections and external factors associated with their immediate environment. The theoretical proposition emerging from this study is that after a major disaster, local urban property owners are faced with two choices “to stay” or “to go”. Those who decide to stay and rebuild are typically very committed individuals who have a feeling of ownership, belonging and attachment to the city in which they live and work. These are people who will often take the lead in commercial property development, proactively making decisions and seeking positive investment outcomes for themselves which in turn result in revitalised commercial urban precincts.
This thesis describes the management process of innovation through construction infrastructure projects. This research focuses on the innovation management process at the project level from four views. These are categorised into the separate yet related areas of: “innovation definition”, “Project time”, “project team motivation” and “Project temporary organisation”. A practical knowledge is developed for each of these research areas that enables project practitioners to make the best decision for the right type of innovation at the right phase of projects, through a capable project organisation. The research developed a holistic view on both innovation and the construction infrastructure project as two complex phenomena. An infrastructure project is a long-term capital investment, highly risky and an uncertain. Infrastructure projects can play a key role in innovation and performance improvement throughout the construction industry. The delivery of an infrastructure project is affected in most cases by critical issues of budget constraint, programme delays and safety Where the business climate is characterized by uncertainty, risk and a high level of technological change, construction infrastructure projects are unable to cope with the requirement to develop innovation. Innovation in infrastructure projects, as one of the key performance indicators (KPI) has been identified as a critical capability for performance improvement through the industry. However, in spite of the importance of infrastructure projects in improving innovation, there are a few research efforts that have developed a comprehensive view on the project context and its drivers and inhibitors for innovation in the construction industry. Two main reasons are given as the inhibitors through the process of comprehensive research on innovation management in construction. The first reason is the absence of an understanding of innovation itself. The second is a bias towards research at a firm and individual level, so a comprehensive assessment of project-related factors and their effects on innovation in infrastructure projects has not been undertaken. This study overcomes these issues by adopting as a case study approach of a successful infrastructure project. This research examines more than 500 construction innovations generated by a unique infrastructure alliance. SCIRT (Stronger Christchurch Infrastructure Rebuild Team) is a temporary alliancing organisation that was created to rebuild and recover the damaged infrastructure after the Christchurch 2011 earthquake. Researchers were given full access to the innovation project information and innovation systems under a contract with SCIRT Learning Legacy, provided the research with material which is critical for understanding innovations in large, complex alliancing infrastructure organisation. In this research, an innovation classification model was first constructed. Clear definitions have been developed for six types of construction innovation with a variety of level of novelties and benefits. The innovation classification model was applied on the SCIRT innovation database and the resultant trends and behaviours of different types of innovation are presented. The trends and behaviours through different types of SCIRT innovations developed a unique opportunity to research the projectrelated factors and their effect on the behaviour of different classified types of innovation throughout the project’s lifecycle. The result was the identification of specific characteristics of an infrastructure project that affect the innovation management process at the project level. These were categorised in four separate chapters. The first study presents the relationship between six classified types of innovation, the level of novelty and the benefit they come up with, by applying the innovation classification model on SCIRT innovation database. The second study focused on the innovation potential and limitations in different project lifecycle phases by using a logic relationship between the six classified types of innovation and the three classified phases of the SCIRT project. The third study result develops a holistic view of different elements of the SCIRT motivation system and results in a relationship between the maturity level of definition developed for innovation as one of the KPIs and a desire though the SCIRT innovation incentive system to motivate more important innovations throughout the project. The fourth study is about the role of the project’s temporary organisation that finally results in a multiple-view innovation model being developed for project organisation capability assessment in the construction industry. The result of this thesis provides practical and instrumental knowledge to be used by a project practitioner. Benefits of the current thesis could be categorized in four groups. The first group is the innovation classification model that provides a clear definition for six classified types of innovation with four levels of novelty and specifically defined outcomes and the relationship between the innovation types, novelty and benefit. The second is the ability that is provided for the project practitioner to make the best decision for the right type of innovation at the right phases of a project’s lifecycle. The third is an optimisation that is applied on the SCIRT innovation motivation system that enables the project practitioner to incentivize the right type of innovation with the right level of financial gain. This drives the project teams to develop a more important innovation instead of a simple problemsolving one. Finally, the last and probably more important benefit is the recommended multiple-view innovation model. This is a tool that could be used by a project practitioner in order to empower the project team to support innovation throughout the project.
