New Zealand faces a range of food safety hazards. Microbial hazards alone were estimated to cause over 2,000 years of lost healthy life in 2011 (Cressey, 2012) and $62m in medical costs and lost productivity in 2009 (Gadiel & Abelson, 2010). Chemical hazards are thought to be well managed through existing controls (Vannoort & Thomson, 2009) whereas microbial hazards are considered harder to control, primarily due to their ability to reproduce along the food production chain. Microbial hazards are thought to cause the majority of acute foodborne gastroenteritis. This research reviewed food safety literature and official documentation, and conducted 55 interviews, mostly with food safety experts from different stakeholder groups, to examine the food safety decision-making environment in New Zealand. This research explores the concept of the ‘stakeholder’ in the context of food safety decision-making and proposes an inclusive ‘stakeholder’ definition as any group which is able to affect, or be affected by, the decision-making process. Utilising this definition, and guided by interviews, New Zealand stakeholders in food safety decision-making were identified and classified as follows: •Regulators •Public health authorities •Food safety scientists/academics •Consumers •Māori •Food Businesses (further classified as): o Farmers o Processors o Food retailers o Exporters Interviews with stakeholders from these groups highlighted twelve criteria as being relevant to multiple groups during food safety intervention evaluation: •Effectiveness •Financial cost •Market Access •Consumer Perceptions •Ease of Implementation •Quality or Suitability •Quality of Science •Equity of Costs •Equity of Benefits •Workplace Safety •Cultural Impact •Animal Welfare There are a number of different ways to measure or assess performance on these criteria. Some are able to be quantitatively measured, while others may require the use of value judgements. This thesis used the Disability-Adjusted Life Year (DALY) metric for quantifying effectiveness during the testing of different MCDA models. This thesis reviews the MCDA process and the food safety specific MCDA literature. There are different ways of conducting MCDA. In particular, there are a large number of models available for the aggregation phase; the process of converting model inputs, in the form of criteria scores and weights, into model recommendations. This thesis has described and reviewed the main classes of model. The literature review and interview process guided the construction and testing of three classes of MCDA model; the Weighted Sum, Analytic Hierarchy Process (AHP) and PROMETHEE models. These models were selected due to their having different characteristics and degrees of complexity, as well as their popularity in the food safety and Health Technology Assessment (HTA) literature. Models were tested on the problem of selecting the most appropriate intervention to address the historic Campylobacter in poultry problem in New Zealand during the mid-2000s. Experimentation was conducted on these models to explore how different configurations utilise data and produce model outputs. This experimentation included: •Varying the format of input data •Exploring the effects of including/excluding criteria •Methods for sensitivity analysis •Exploring how data inputs and outputs can be elicited and presented using visual tools • Creating and using hybrid MCDA models The results of this testing are a key output of this thesis and provide insight into how such models might be used in food safety decision-making. The conclusions reached throughout this research phase can be classified into one of two broad groups: •Those relating to MCDA as a holistic process/methodology for decision-making •Those relating to the specific models and mathematical procedures for generating numerical inputs and outputs This thesis demonstrates that food-safety decision-making is a true multi-criteria, multi-stakeholder problem. The different stakeholders in food-safety decision-making do not always agree on the value and importance of the attributes used to evaluate competing intervention schemes. MCDA is well suited to cope with such complexity as it provides a structured methodology for the systematic and explicit identification, recording and aggregation of qualitative and quantitative information, gathered from a number of different sources, with the output able to serve as a basis for decision-making. The MCDA models studied in this thesis range from models that are simple and quick to construct and use, to more time consuming models with sophisticated algorithms. The type of model used for MCDA, the way these models are configured and the way inputs are generated or elicited can have a significant impact on the results of an analysis. This thesis has identified a number of key methodological considerations for those looking to employ one of the many available MCDA models. These considerations include: •Whether a model can accommodate the type and format of input data •The desired degree of compensation between criteria (i.e. full, partial or no compensation) •Whether the goal of an analysis is the identification of a ‘best’ option(s), or the facilitation of discussion, and communication of data •The degree of transparency required from a model and whether an easily understood audit trail is desired/required •The desired output of a model (e.g. complete or partial ranking). This thesis has also identified a number of practical considerations when selecting which model to use in food safety decision-making. These include: •The amount of time and energy required of stakeholders in the generation of data inputs (elicitation burden) •The degree of training required for participants •How data inputs are to be elicited and aggregated in different group decision-making environments •The availability of MCDA software for assisting an analysis Considering the above points will assist users in selecting a suitable MCDA model that meets their requirements and constraints. This thesis provides original and practical knowledge to assist groups or individuals looking to employ MCDA in the context of food-safety intervention decision-making. This research could also serve as a guide for those looking to evaluate a different selection of MCDA models.

The aim of this diploma thesis is to devise general evaluation procedure of current accounts for associations and then to compare the theoretical results with the results of the questionnaire survey. The aim of the questionnaire survey is to find out what accounts the associations use and why. The theoretical part of this thesis is focused on the scientific discipline called multi-criteria decision making, its basic terminology, the methods of setting the criterions' weights and selected multi-criteria decision making methods. Finally, the associations are described according to valid legislation. In the practical part, selected accounts for specific clients are evaluated by using three multi-criteria decision making methods and the questionnaire survey is evaluated too. The conclusion is dedicated a comparison of the theoretical evaluation results with the questionnaire survey results and the author's own view of this issue. Familiarization of the author with the associations' activities during a personal meeting with them is the main benefit of this thesis for the author. The finding that the accounts of some of them are not as advantageous as they were before is the benefit for the associations. Some of them decided to visit their bank and change the account to the account recommended by the author.

The aim of this thesis is by using methods and practices of managerial decision-making process to choose suitable supplier and propose measures to reduce risk. The first section of the theoretical part deals with the different phases of the decision-making process. The second part is devoted to the procurement as one of the corporate functions. The practical part applies the managerial decision-making process on the current situation of a company producing fast moving consumer goods is looking for a new supplier of packaging material. Choice of supplier was performed by using a multi-criteria decision-making, first the decision criteria was defined, followed by a description of the alternatives and their consequences. Evaluation of the alternatives was based on the additive multi-criteria utility function, to determine the weights of the criteria was used method determining weights by preferential arrangements. From five potential vendors was recommended supplier A. The end of the practical part is devoted to proposals of measures to reduce the risk which company may face in the process of selection and also in the process of delivering of the material.

The increasing global deficit of healthcare resources makes efficiency improvements in the healthcare industry a complete necessity to assure safe and available healthcare for everyone. Digitalization is expected to play a fundamental role in this transition and digital primary healthcare providers have in recent years developed into a substantial part of the Swedishprimary care sector. Several of those have built solutions for automated triage, where the role of a triage officer in traditional primary care is replaced by an automated process, in which an triage algorithm directly refers the patient to the appropriate level of care. Despite the rise of digital healthcare providers and automated primary care triage systems in particular, research on the implications of automating the triage process in primary healthcare is scarce. This study aims to assess the potential of using MCDM models for automated triage in digital primary care, by conducting a single case study at one of the leading digital healthcare providers. The study is separated into two phases. In phase one, interviews are conducted to qualitatively determine what set of factors to include in an automated MCDM triage model.In phase two, the resulting model is simulated to evaluate the performance compared to the traditional triage model in which all patient journeys start with an initial nurse meeting. The study shows that an automated MCDM triage model can improve cost efficiency in terms of clinician salary costs and productivity in terms of fewer consultations per patient, compared to the traditional triage model. However, the traditional triage model is shown to be more efficient in terms of only utilizing doctor resources for patients in absolute need of doctor care. / Det ökande underskottet av sjukvårdsresurser gör effektivitetsförbättringar i sjukvårdsbranschen nödvändigt för att säkerställa säker och tillgänglig sjukvård för alla. Digitalisering förväntas fylla en fundamental roll i denna transformation och digitala vårdgivare i primärvården har under de senaste åren växt till en betydande del av den svenska primärvårdssektorn. Flertalet av dessa har byggt lösningar för automatiserat triage, där triagefunktionärens roll ersätts av en automatiserad process där en triagealgoritm direkt hänvisar patienten till den lämpliga vårdnivån. Trots tillväxten av digitala vårdgivare i primärvården och deras automatiserade triagesystem i primärvården är forskning kring effekterna av att automatisera triageprocessen i primärvården begränsad. Denna studie strävar efter att utvärdera potentialen i att använda MCDM-modeller för automatiserat triage i den digitala primärvården genom en casestudie på en av de ledande digitala vårdgivarna i primärvården. Studien är uppdelad i två delar. I del ett genomförs intervjuer för att kvalitativt fastställa vilka faktorer som bör inkluderas i en automatiserad MCDM-modell för triage. I del två simuleras den resulterande MCDM-modellen för att utvärdera dess resultat jämfört med den traditionella triagemodellen i vilken alla patienter har ett inledande möte med en sjuksköterska. Studien visar att en automatiserad MCDM-modell för triage kan förbättra kostnadseffektiviteten i termer av lönekostnader och produktivitet i termer av färre konsultationer per patient, jämfört med den traditionella triagemodellen. Däremot visar den traditionella triagemodellen högre effektivitet i termer av att enbart utnyttja läkarresurser för patienter i absolut behov av läkarvård.

<p dir="ltr">Conservation conflicts, commonly defined as “situations that occur when two or more parties with strongly held opinions clash over conservation objectives, and when one party is perceived to assert its interests at the expense of another” (Redpath et al., 2013) are expected within the realm of public land management. Conservation conflicts have been an increasing issue worldwide as the consumption of natural resources can directly oppose conservation efforts. Quantitative and qualitative approaches have been adopted in similar studies to mitigate or resolve conservation conflicts. This thesis focuses on a 2017 conflict over logging in Yellowwood State Forest in Indiana. The Social Multi-Criteria Evaluation (SMCE) framework was applied in this thesis to examine economic, ecological, and recreational criteria from multiple stakeholders' perspectives and understand how a retrospective assessment can contribute to improved conflict resolution. The study follows four steps: conducting an institutional analysis, defining criteria and potential alternative scenarios, generating an impact matrix through surveys and interviews, and aggregating results for cross-scenario comparison. The design of these steps attempts to engage stakeholders in the decision-making process and increase transparency. The ranking results reveal a clear preference for the “Shelterwood Cuts” alternative, indicating that different actions may have been a better solution. Although the methodology alone cannot make decisions, it can aid the decision-maker in creating a solution to a conservation conflict by providing guidance and bringing attention to the aspects of a conflict that require change.</p>

<p dir="ltr">Highway safety continues to pose a serious challenge to the social sustainability of transportation systems, and initiatives are being pursued at all levels of government to reduce the high fatality count of 42,000. At the same time, it is sought to ensure higher travel efficiency in order to increase economic productivity. The emergence of automated transportation provides great promise to mitigate these ills of the transportation sector that have persisted for so many decades. With regards to safety, such promise is rooted in the capability of autonomous vehicles to self-drive some or all of the time, thus reducing the impact of inherently errant human driving to which 95% of all crashes have been attributed. With regards to mobility, such promise is guided by the capability of the autonomous vehicle to carry out path planning, navigation, and vehicle controls in ways that are far more efficient than the human brain, thereby facilitating mobility and reducing congestion-related issues such as delay, emissions, driver frustration, and so on.</p><p dir="ltr">Unfortunately, the two key outcomes (safety and mobility) are reciprocal in the sense that navigation solutions that enhance safety generally tend to reduce mobility, and vice versa. As such, there is a need to assign values explicit to these performance criteria in order to develop balanced solutions for AV decisions. Most existing machine-learning-based path planning algorithms derive these weights using a learning approach. Unfortunately, the stability of these weights across time, individuals, and trip types, is not guaranteed. It is necessary to develop weights and processes that are trip situation-specific. Secondly, user trust in automation remains a key issue, given the relatively recent emergence of this technology and a few highly-publicized crashes, which has led to reservations among potential users.</p><p dir="ltr">To address these research questions, this thesis identifies various situational contexts of the problem, identifies the alternatives (the viable trajectories by fitting curves between the vehicle maneuver’s initial and final positions), develops the decision criteria (safety, mobility, comfort), carries out weighting of the criteria to reflect their relative significance, and scales the criteria to develop dimensionless equivalents of their raw values. Finally, a process for amalgamating the overall impacts of each driving decision alternative is developed based on the weighted and scaled criteria, to identify the best decision (optimal trajectory path). This multi-criteria decision making (MCDM) problem involves the collection of data through questionnaire surveys.</p><p dir="ltr">The weights obtained early in the MCDM process could be integrated into any one of two types of planning algorithms. First, they could be incorporated into interpolating curve-based planning algorithms, to identify the optimal trajectory based on human preferences. Additionally, they can be integrated into optimization-based planning algorithms to allocate weights to the various functions used.</p><p dir="ltr">Overall, this research aims to align the behavior of autonomous vehicles closely with human-driven vehicles, serving two primary purposes: first, facilitating their seamless coexistence on mixed-traffic roads and second, enhancing public acceptance of autonomous vehicles.</p>

Abstract : The objective is to provide methods to improve the performance, or prediction accuracy of standard stacking approach, which is an ensemble method composed of simple, heterogeneous base models, through the integration of the diversity generation, combination and/or selection stages for regression problems. In Chapter 1, we propose to combine a set of level-1 learners into a level-2 learner, or ensemble. We also propose to inject a diversity generation mechanism into the initial cross-validation partition, from which new cross-validation partitions are generated, and sub-sequent ensembles are trained. Then, we propose an algorithm to select best partition, or corresponding ensemble. In Chapter 2, we formulate the partition selection as a Pareto-based multi-criteria optimization problem, as well as an algorithm to make the partition selection iterative with the aim to improve more the ensemble prediction accuracy. In Chapter 3, we propose to generate multiple populations or partitions by injecting a diversity mechanism to the original dataset. Then, an algorithm is proposed to select the best partition among all partitions generated by the multiple populations. All methods designed and implemented in this thesis get encouraging, and favorably results across different dataset against both state-of-the-art models, and ensembles for regression. / Résumé : L’objectif est de fournir des techniques permettant d’améliorer la performance de l’algorithme de stacking, une méthode ensembliste composée de modèles de base simples et hétérogènes, à travers l’intégration de la génération de la diversité, la sélection et combinaison des modèles. Dans le chapitre 1, nous proposons de combiner différents sous-ensembles de modèles de base obtenus au primer niveau. Nous proposons un mécanisme pour injecter de la diversité dans la partition croisée initiale, à partir de laquelle de nouvelles partitions de validation croisée sont générées, et les ensembles correspondant sont formés. Ensuite, nous proposons un algorithme pour sélectionner la meilleure partition. Dans le chapitre 2, nous formulons la sélection de la partition comme un problème d’optimisation multi-objectif fondé sur un principe de Pareto, ainsi que d’un algorithme pour faire une application itérative de la sélection avec l’objectif d’améliorer d’avantage la précision d’ensemble. Dans le chapitre 3, nous proposons de générer plusieurs populations en injectant un mécanisme de diversité à l’ensemble de données original. Ensuite, un algorithme est proposé pour sélectionner la meilleur partition entre toutes les partitions produite par les multiples populations. Nous avons obtenu des résultats encourageants avec ces algorithmes lors de comparaisons avec des modèles reconnus sur plusieurs bases de données.

This thesis is the result of applying a novel methodology which I labelled ‘participative foresight scenario mapping’. This methodology couples participatory methods for building holistic foresight scenarios for sustainable development in Flores Island (Azores, Portugal) with a multi-criteria appraisal method, Multi-criteria mapping (Stirling, 1997), to assess these scenarios alongside five sector based regional scenarios (Secretaria Regional do Ambiente e do Mar, 2006). The main research question was to reflect on how small isolated societies, which have a distant relation with strategic decision-making centres, can define their transitions to sustainability. Small islands represent interesting cases to reflect on sustainability, these small territories distant from main decision-making centres challenge decision-making and require a consideration of the issues of scale. Islands have also been seen as small, manageable models of the world, providing the opportunity to explore innovative solutions at a scale that allows inclusion of as many different factors as possible. Small islands’ populations are especially linked to their island and they develop, by the effects of isolation, a strong particular relation to the place, the role of identity is then crucial in fostering sustainable practices adapted to the island. A succession of individual scoping interviews with twenty four regional and local decision-makers and key informants and seven focus groups with a total of thirty local lay citizens gave me the opportunity to develop two differentiated multi-sector scenarios for Flores Island which were identified as Standard and Balanced development scenarios. The Balanced development scenario reflects a desire to develop an island that bases its economy on greater self-sufficiency for agricultural products, quality and certified products, and natural conservation and valorisation. The Standard development scenario is based on economic growth through tourism and primary sector intensification, and public investment in infrastructures; this scenario can be summarized as the continuation of the actual model of development. The appraisal of both holistic narratives allows in depth exploration of the complex issues related to sustainability, such as the preference between weak and strong sustainability, that otherwise would have been too difficult to assess by such a variety of research participants. Working with holistic scenarios raised the limits of the capacity to show proficiency in a wide variety of fields. The research demonstrated the feasibility of applying the multi-criteria mapping method to support the analysis of holistic non-technical scenarios. The combination of qualitative and quantitative data brought depth to the analysis and improved the understanding of the desired sustainable futures in islands. But the quantitative appraisal was overshadowed by strong uncertainties that made difficult the identification of a best scenario. Uncertainty was explained by the risks inherent to the scenarios, the limited expertise in all the criteria, the complexity of the holistic scenarios, the time horizon (20 years), doubts on the effective implementation of the chosen scenario, and the existence of potentially disrupting external factors. The process was also the opportunity to understand the role that social capital might play in the transition to the desired future for this island. It is shown in the thesis that a successful transition to sustainable development can only be reached if the objectives are understood and shared by the population.

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.

Kuwait’s per capita electrical energy consumption is among the largest in the world, reaching 13,663 kWh per person in 2011. The electricity demand in Kuwait is increasing, which requires additional investments in power generation. A particular challenge in Kuwait is the peak demand in summer, when extreme heat increases air conditioning loads. Peak demand reached 11,220 MW in 2011, with a fast growth rate averaging 5.6% over the last decade and a maximum production capacity of around 14,720 MW. It is not possible to cope with this demand simply by increasing generation capacity. Therefore, the only alternative available to Kuwait is to control electricity demand via demand-side management. The main objective of this research is to assess and select the optimal demand- side management (DSM) technologies for buildings in the governmental sector (office, religious and school buildings) and to investigate the key factors in the evaluation process. To achieve the research objective, a model was proposed using multi-criteria decision-making techniques to enable the forecasting and comparison of DSM alternatives that are suitable for buildings. The developed model includes environmental, economic, technical and social considerations. The research methodology is based on three main phases. Phase 1: Data collection through a mail questionnaire that was sent to 42 experts for the identification of criteria and demand-side management alternatives. Phase 2: Screening and narrowing of the data collected in Phase 1 using a set of questionnaires, including the identification of potential DSM alternatives and criteria suitable for further analysis. This phase was performed through the Delphi process, taking into consideration the opinions of 28 experts. Phase 3: Use of Multi-criteria Decision Making (MCDM) techniques, namely the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP), to evaluate and rank the identified DSM alternatives and criteria. This was done using pairwise comparisons of 17 experts to evaluate the criteria and alternatives for the buildings (office, religious and school). The research showed that the experts identified six alternative technologies and five criteria for the selection and evaluation of governmental buildings (office, religious and school). After performing the three phases of this research project, a set of criteria and alternatives were ranked based on the information gathered from every group of experts. It was found that reduction in consumption, capital cost and ease of implementation were the three most recommended criteria for the selection of DSM technologies in Kuwait government buildings while high efficiency lighting and programmable thermostats were identified as the most recommended DSM technologies for these buildings. An important aspect of this research is that unlike engineering approaches which sometimes depend on expensive test equipment or, often for building design, expensive computer modelling exercises, the proposed framework can be easily adopted by anyone without any significant financial cost. The FAHP approach was also tested and its results compared with those of AHP. There was a slight difference between using AHP and FAHP in terms of ranking the criteria and alternatives but that the difference barely affects the ranking. It was found that the AHP provides a convenient MCDM approach for solving the complex problem of selecting the optimal DSM options for buildings. The contributions of this thesis are the development of a novel framework for systematic selection and ranking of DSM technologies in different types of buildings using the Delphi method and AHP; the identification of the most important DSM technologies and criteria for their selection for three types of governmental buildings in Kuwait; and establishing that results from using AHP and FAHP for the selection of appropriate DSM measures in these buildings are almost identical, so use of AHP is likely to be sufficient in most building studies of this type.