Motivation This poster aims to present fragility functions for pipelines buried in liquefaction-prone soils. Existing fragility models used to quantify losses can be based on old data or use complex metrics. Addressing these issues, the proposed functions are based on the Christchurch network and soil and utilizes the Canterbury earthquake sequence (CES) data, partially represented in Figure 1. Figure 1 (a) presents the pipe failure dataset, which describes the date, location and pipe on which failures occurred. Figure 1 (b) shows the simulated ground motion intensity median of the 22nd February 2011 earthquake. To develop the model, the network and soil characteristics have also been utilized.
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.
Voluntary turnover has been the subject of scholarly inquiry for more than 100 years and much is understood about the drivers of turnover, and the decision-making processes involved. To date most models of voluntary turnover have assumed a rational and sequential decision process, initiated primarily by dissatisfaction with the job and the perceived availability of alternatives. Operating within a strong predictive research agenda, countless studies have sought to validate, extend and refine these traditional models through the addition of distal antecedents, mediators, moderators, and proximal antecedents of turnover. The net result of this research is a large body of empirical support for a somewhat modest relationship between job dissatisfaction, perceived alternatives, turnover intentions, job search behaviour and actual turnover. Far less scholarly attention has been directed at understanding shock-induced turnover that is not necessarily derived from dissatisfaction. Moreover, almost no consideration has been given to understanding how a significant and commonly experienced extra-organisational shock, such as natural disaster, might impact turnover decision making. Additionally, the dynamic and cumulative impacts of multiple shocks on turnover decision making have to date not been examined by turnover researchers. In addressing these gaps this thesis presents a leaver-centric theory of employee turnover decision making that is grounded in the post-disaster context. Data for the study were collected from in-depth interviews with 31 leavers in four large organisations in Christchurch, New Zealand; an area that experienced a major natural disaster in the form of the Canterbury earthquake sequence. This context provided a unique setting in which to study turnover as the primary shock was followed by a series of smaller shocks, resulting in a period of sustained disruption to the pre-shock status quo. Grounded theory methods are used to develop a typology of leaving which describes four distinct patterns of turnover decision making that follow a significant extra-organisational shock. The proposed typology not only addresses the heterogeneous and complex nature of turnover decision making, but also provides a more nuanced explanation of the turnover process explicating how the choice of decision path followed is influenced by four contextual factors which emerged from the data: (1) pre-shock motivational state; (2) decision difficulty; (3) experienced shock magnitude; and (4) the availability of resources. The research findings address several shortcomings in the extant literature on employee turnover, and offer practical recommendations for managers seeking to retain employees in a post-disaster setting.
