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Sustainable pavement management implies maintaining acceptable condition of pavements while also considering the tradeoff between cost, environmental impacts and social impacts of pavement investments. Typical pavement management practices only consider economic considerations, and environmental mitigation techniques are employed after the selection of the maintenance action is complete. This dissertation presents a series of papers that demonstrate the impact of decision making on the environmental impact of the pavements both at the project and network levels of pavement management. An analysis was conducted of two models that relate pavement properties to vehicle rolling resistance and fuel consumption. These models were used, along with other tools to evaluate the impact of including the use phase of a pavement into pavement lifecycle assessments. A detailed project level lifecycle assessment was conducted, and it was found that the vehicles on the pavement during the use phase contribute the most to environmental pollutants by a significant margin over other phases of the lifecycle. Thus, relatively small improvements in the factors which contribute to rolling resistance may significantly influence the environmental impacts of the pavement. Building on this, a network level lifecycle assessment method was proposed to probabilistically quantify energy consumption for a given set of expected maintenance actions. It was shown that, although maintenance actions require a certain amount of energy consumption, this energy can be offset by improved road conditions leading to reduced rolling resistance. However, this tradeoff of reduced energy consumption also includes increased costs for a given network condition. In other words, the lowest energy consumption values did not tend to fall along the line defined by minimizing the cost divided by the pavement condition. In order to demonstrate how this tradeoff should be addressed, a novel decision analysis framework was developed, and implemented on a specific pavement network. Finally, a survey of transportation professionals was evaluated to determine their optimal points within the solution space defined by minimizing costs and energy consumption while maximizing pavement condition. It was found that the solution space could be greatly reduced by implementing their responses using the proposed decision analysis framework. / Ph. D.

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Yes / Social media usage in evacuations and emergency management represents a rapidly expanding field of study. Our paper thus provides quantitative insight into a serious practical problem. Within this context a behavioural approach is key. We discuss when facilitators should consider model-based interventions amid further implications for disaster communication and emergency management. We model the behaviour of individual people by deriving optimal contrarian strategies. We formulate a Bayesian algorithm which enables the optimal evacuation to be conducted sequentially under worsening conditions. / Supported by EPSRC (IDEAS Factory - Game theory and adaptive networks for smart evacuations, EP/I005765/1)

Currently several disparate and incomplete approaches are being used to analyse and make decisions on the complex methodology of carbon capture and storage (CCS). A literature review revealed that, as CCS is a new and complex technology, there is no agreed-upon thorough assessment method for high-level CCS decisions. Therefore, a risk model addressing these weaknesses was created for assessing complex CCS decisions using a multi-criteria decision analysis approach (MCDA). The model is aimed at transparently and comprehensively assessing a wide variety of heterogeneous CCS criteria to provide insights into and to aid decision makers in making CCS-specific decisions. The risk model includes a variety of tools to assess heterogeneous CCS criteria from the environmental, social, economic and engineering fields. The model uses decision trees, sensitivity analysis and Monte Carlo simulation in combination with utility curves and decision makers’ weights to assess decisions based on data and situational uncertainties. Elements in the model have been used elsewhere but are combined here in a novel way to address CCS decisions. Three case studies were developed to run the model in scenarios using expert opinion, project-specific data, literature reviews, and engineering reports from Alberta, Saskatchewan and Europe. In collaboration with Alberta Innovates Technology Futures, a pilot study was conducted with CCS experts in Alberta to assess how they would rank the importance of CCS criteria to a project selection decision. The MCDA model was run using experts’ criteria weights to determine how CCS projects were ranked by different experts. The model was well received by the CCS experts who believed that it could be adapted and commercialized to meet many CCS decision problems. The survey revealed a wide range in experts’ understanding of CCS criteria. Experts also placed more emphasis on criteria from within their field of expertise, although economic criteria dominated weights overall. The results highlight the benefit of a model that clearly demonstrates the trade-offs between projects under uncertain conditions. The survey results also revealed how simple decision analyses can be improved by including more transparent methods, interdisciplinary criteria and sensitivity analysis to produce more comprehensive assessments.

The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). Initiated by recognition of drivers, including water demand, increasing risk of ground-water pollution and flooding, the value of RWH is filtering across the academic-policy boundary. However, in Nigeria, implementation of sustainable water management (SWM), such as RWH systems, is inefficient social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of 1067 household respondents, 135 Nigerian Architects and Civil Engineers and focus group discussion with Stakeholders. A total of 1042 sets of data were collected through a questionnaire survey and analysed using SPSS, Excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were selected to collect data for hydrological modelling using the RainCycle model. From the results it is found that the most important barrier constraining sustainable RWH regime in Ibadan was obsolete and insufficient operational equipment, followed by poor renumeration of water corporation staff and misuse of available funds. In addition, the measure of importance of storage capacity was established, with the highest score of 4.5 which reflects the general inadequacy of storage as a major barrier to the adoption of RWH as a sustainable water management method. Further, respondents’ major health hazards associated with drinking contaminated water was established. A larger proportion (61.2%) of respondents chose prevalence of typhoid fever; some have a prevalence of diarrhea (19.4%), while few of respondents’ water sources is free from water-borne diseases (2.3%). The tool developed is an integrated platform of related evaluation techniques, including Whole Life Cycle Cost Analysis and Multi-Attribute Utility Theory. The tool uses data including cost and quantities of materials for building a RWH storage system and quantifies the cost and benefits of alternative RWH-based systems that can improve project management. This tool is novel, given its integration of the analytical techniques mentioned above and application for selecting the most appropriate RWH-based SWM systems. The implementation of the tool is envisaged to provide an objective platform for the quantification of the costs and benefits of RWH-based systems prior to implementation.

The backbone of our industrialised society and economy is electricity. To avoid a catastrophic situation, a plan for how to act during a power shortage is crucial. Previous research shows that decision models provide support to decision makers providing efficient energy rationing during power shortages in the Netherlands, United States and Canada. The existing research needs to be expanded with a group decision model to enable group decisions. This study is conducted with a case study approach where the Swedish emergency preparedness plan in case of power shortage, named Styrel, is explored and used to evaluate properties of a proposed group decision model. The study consist of a qualitative phase and a quantitative phase including a Monte Carlo simulation of group decisions in Styrel evaluated with correlation analysis. The qualitative results show that participants in Styrel experience the group decisions as time-consuming and unstructured. The current decision support is not used in neither of the two counties included in the study, with the motivation that the preferences provided by the decision support are misleading. The proposed group decision model include a measurable value function assigning values to priority classes for electricity users, an additive model to represent preferences of individual decision makers and an additive group decision model to aggregate preferences of several individual decision makers into a group decision. The conducted simulation indicate that the proposed group decision model evaluated in Styrel is sensitive to significant changes and more robust to moderate changes in preference differences between priority classes.

The current application of logistics in the construction industry is relatively inefficient when compared with other industries such as retail and manufacturing. The factors attributed to this inefficiency include the fragmented and short-term nature of construction process and inadequate tracking facilities on site. The inefficiency of construction logistics creates inter alia loss of materials and equipment, waste, construction delay, excessive cost and collision accident on site. Meanwhile, several information and communication technologies (ICT) have been proposed and developed by researchers to improve logistics functions such as tracking and monitoring of resources through the supply chain to the construction site. Such technologies include global positioning system (GPS), radio frequency identification devices (RFID), wireless sensors network (WSN) and geographical information system (GIS). While considerable research has been undertaken to develop the aforementioned systems, limited work has so far been done on investment justification prior to implementation. In this research, a framework has been developed to assess the extent of construction logistics problems, measure the significances of the problems, match the problems with existing ICT-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several ICT-based construction logistics systems. The tool is an integrated platform of related evaluation techniques such as Fault Tree Analysis, Decision Tree Analysis, Life Cycle Cost Analysis and Multi-Attribute Utility Theory. Prior to the development of this tool, data was collected through questionnaire survey and analysed by means of statistical analysis in order to derive some foundational parameters of the tool. Quantitative research method was adopted for data collection because the processes of the tool for which the data was required are quantitative. The implementation of this tool is novel given the integration of the analytical techniques mentioned above and the application of the tool for selecting ICT-based construction logistics systems. The tool takes in data such as cost and quantities of materials for a building project and quantifies the cost and benefits of alternative ICT-based tracking systems that can improve the logistics functions of the project. The application of the tool will eliminate guesswork on the benefits of ICT-based tracking systems by providing an objective platform for the quantification of cost and benefits of the systems prior to implementation.

Although Operational Research (OR) has successfully provided many methodologies to address complex decision problems, in particular based on the rationality principle, there has been too little discussion regarding their limited consideration in IT evaluation practice and associated decision making satisfaction levels in an organisational context. The aim of this paper is to address these issues through providing a current account of diffusion and infusion of OR methodologies in IT decision making practice, and by analysing factors affecting decision making satisfaction from a Technological, Organisational, and Environmental (TOE) framework in the context of IT induced business transformations. We developed a structural equation model and conducted an empirical survey, which supported four out of five developed research hypotheses. Our results show that while Decision Support Systems (DSS), holistic IT evaluation methods, and management support seem to positively affect individual satisfaction, legislative regulation has an adverse effect. Results also revealed a persistent methodology diffusion and infusion gap. The paper discusses implications in each of these aspects and presents opportunities for future work. (authors' abstract)