Internal audit departments strive to control risk within an organization. To do this they choose specific audit areas to include in an audit plan. In order to select areas, they usually focus on those areas with the highest risk. Even though high risk areas are considered, there are various other restrictions such as resource constraints (in terms of funds, manpower and hours) that must also be considered. In some cases, management might also have special requirements. Traditionally this area selection process is conducted using manual processes and requires significant decision maker experience. This makes it difficult to take all possibilities into consideration while also catering for all resource constraints and special management requirements. In this study, mathematical techniques used in capital budgeting problems are explored to solve the IT audit area selection problem. A DSS is developed which implements some of these mathematical techniques such as a linear programming model, greedy heuristic, improved greedy heuristic and evolutionary heuristic. The DSS also implements extensions to the standard capital budgeting model to make provision for special management requirements. The performance of the mathematical techniques in the DSS is tested by applying different decision rules to each of the techniques and comparing those results. The DSS, empirical experiments and results are also presented in this research study. Results have shown that in most cases a binary 0-1 model outperformed the other techniques. Internal audit management should therefore consider this model to assist with the construction of an IT internal audit plan. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2015

Internal audit departments strive to control risk within an organization. To do this they choose specific audit areas to include in an audit plan. In order to select areas, they usually focus on those areas with the highest risk. Even though high risk areas are considered, there are various other restrictions such as resource constraints (in terms of funds, manpower and hours) that must also be considered. In some cases, management might also have special requirements. Traditionally this area selection process is conducted using manual processes and requires significant decision maker experience. This makes it difficult to take all possibilities into consideration while also catering for all resource constraints and special management requirements. In this study, mathematical techniques used in capital budgeting problems are explored to solve the IT audit area selection problem. A DSS is developed which implements some of these mathematical techniques such as a linear programming model, greedy heuristic, improved greedy heuristic and evolutionary heuristic. The DSS also implements extensions to the standard capital budgeting model to make provision for special management requirements. The performance of the mathematical techniques in the DSS is tested by applying different decision rules to each of the techniques and comparing those results. The DSS, empirical experiments and results are also presented in this research study. Results have shown that in most cases a binary 0-1 model outperformed the other techniques. Internal audit management should therefore consider this model to assist with the construction of an IT internal audit plan. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2015

<p dir="ltr">Climate change hazards are becoming more frequent and severe and their impact on Department of Defense installations has become a matter of national security. This thesis investigates the intricate relationship between climate change hazards and the Department of Defense (DoD) by examining the multifaceted impacts of environmental shifts on military operations, infrastructure, and strategic planning. As the global climate continues to undergo unpredictable changes, the DoD faces evolving challenges that extend beyond traditional security concerns.</p><p dir="ltr">The research employs a multidisciplinary approach, integrating environmental science and analysis with military strategy to assess the current and anticipated hazards posed by climate change. As the beginning of a multi-year project, this thesis examines extreme weather events in relation to their potential to disrupt critical military assets and installations in Yuma County Arizona.</p><p dir="ltr">Additionally, decision support systems were created and analyzed as part of this thesis in order to provide Department of Defense decision-makers with a tool to create personalized and up to date visuals and data. This support tool could have positive implications for force readiness, mission effectiveness, and strategic planning, recognizing climate change as a pervasive and dynamic threat.</p><p dir="ltr">The study also delves into the strategic response of the DoD to climate change hazards, evaluating adaptation measures, resilience-building initiatives, and the integration of climate considerations into defense planning processes. By examining historical and future conditions, the research identifies areas where these installations could implement changes in order to enhance climate resilience and efficiency within the defense framework.</p><p dir="ltr">In conclusion, this thesis provides an understanding of the intricate interplay between climate change hazards and national security, focusing on their direct and indirect impacts on two military installations in Arizona. By shedding light on the complexities of this relationship, it contributes to the growing body of knowledge essential for developing adaptive strategies and policies that ensure the readiness and effectiveness of the military in the face of a changing climate.</p>

Decline in both visual acuity and visual performance is a fact of life for older people and their increasing share of the population requires that buildings be designed with their visual needs in mind. As their field of vision decreases, people find it harder to identify an objects location, distance, and orientation. Elderly people with vision impairments usually find it harder to perform daily activities such as navigation through indoor spaces. Functional vision can be improved by modifying the design of spaces, for example, with better lighting. However, architects typically do not know how to take the needs of the visually impaired into account in their design process, or simply do not think of doing so. The researcher designed and feasibility-tested a prototype person-centered tool to help architects judge how appropriate a designed space will be for visually impaired people. The study was conducted as a qualitative mixed-methodology research analysis. The researcher used knowledge from literature interpretation to rationalize the development of a person-centered prototype. The researcher immersed design PhD students and vision science experts to inform the prototyping process. Along with an expert group of design and vision science professionals, the researcher beta-tested the prototype during a mock design-process scenario. The researcher also selected a small group of industry experts to participate in open-ended interviews on post-use demonstrations to qualitatively triangulate the findings on the prototypes usability. The study summarizes the feasibility including the challenges of using the prototype for professional purposes and suggests improvement. / Ph. D.

Cette thèse vise à contribuer à la compréhension des cycle de vie d’une opération humanitaire (HOLC). Gestion de la chaîne d'approvisionnement humanitaire (HSCM) dans un contexte de mise en perspective et dans l’objectif de proposer un modèle décisionnel qui s'applique aux phases de HOLC lors d’une situation réelle. Cela inclut la mise en oeuvre du modèle proposé pour concevoir et développer un outil d'aide à la décision afin d'améliorer les performances de la logistique humanitaire tant dans les opérations de secours nationaux qu’internationaux.Cette recherche est divisée en trois phases. La première partie vise à présenter le sens de l'étude ; la zone de recherche prise en compte pour la gestion de la chaîne d'approvisionnement (SCM) doit être clairement définie. La première phase consiste à clarifier et définir le HSCM HL, la gestion de la chaîne d'approvisionnement commerciale (CSCM) et le SCM, ainsi que la relation entre ces différents éléments. La gestion du cycle de vie du projet (PLCM) et les différentes approches sont également présentés. La compréhension de la différence entre la gestion du cycle de vie du projet (PLM) et la PLCM est également nécessaire, cela ne peut être abordé dans la phase de cycle de vie de l'opération humanitaire. De plus, les modèles Multiple-Criteria Decision Making (MCDM) et l’aide à la décision concernant le HL sont analysés pour établir le fossé existant en matière de recherche. Les approches MCDM qui mettent en oeuvre le système d'aide à la décision (DSS) et la manière dont le MAS a été utilisé dans le contexte HSCM sont étudiées.La deuxième phase consiste en la proposition d’un modèle décisionnel fondé sur l’approche MCDM à l'appui de la décision du décideur avant qu'il/elle prenne des mesures. Ce modèle prévoit le classement des alternatives concernant l'entrepôt, le fournisseur et le transport au cours des phases de HOLC. Le modèle décisionnel proposé est réalisée en 3 scénarios. I. La décision en 4phases HOLC – opération de secours internationale de la Croix-Rouge Française (CRF). II. La décision en3phases HOLC – opération nationale dela Croix-Rouge thaïlandaise (TRC). III. La décision au niveau de la phase de réponse HOLC – opération internationale du TRC dans quatre pays. Dans cette phase, le scénario I et II sont réalisés étape par étape au travers de calculs numériques et formules mathématiques. Le scénario III sera présenté dans la troisième phase. Pour établir trois scénarios, les données internes recueillies lors des entretiens avec le chef de la logistique de la Croix-Rouge Française, et le vice-président de la fondation de la Coix-Rouge thaïlandaise, seront utilisées. Les données externes proviennent de chercheurs qui sont des experts dans le domaine HL ou le champ du HSCM, de la littérature, et de sources issues des organismes humanitaires (documents d’ateliers, rapports, informations publiées sur leurs sites officiels).Dans la troisième phase, une application Internet multi-critères (decision support system MCDSS WB) mettant en oeuvre le modèle proposé est élaborée. Afin d'atteindre une décision appropriée en temps réel, le WB-MCDSS est développé sur la base d’un protocole client-serveur et est simple à utiliser. Le dernier mais non le moindre ; une application de validation du modèle est réalisée à l'aide de l'approche de l'analyse de sensibilité. / This thesis aims to contribute to the understanding of HOLC in context of the HSCM and to propose a decision model which applies to the phases of HOLC the decision making regarding a real situation . This include the implementation of the proposed model to design and develop a decision support tool in order to improve the performance of humanitarian logistics in both national and international relief operations.This research is divided into three phases; the first phase is to clarify and define HL among HSCM, commercial supply chain management (CSCM) and SCM and their relationship. Project Life Cycle Management (PLCM) approaches are also presented. The difference between project life cycle management (PLM) and PLCM is also required to distinguish a clear understanding which can be addressed in the phase of humanitarian operation life cycle. Additionally, the literature of Multiple-Criteria Decision Making (MCDM) models and existing decision aid system for HL are analyzed to establish the research gap. The MCDM approaches which implement the decision support system (DSS) and lastly how DSS has been used in the HSCM context.The second phase is to propose a decision model based on MCDM approaches to support the decision of the decision maker before he/she takes action. This model provides the ranking alternatives to warehouse, supplier and transportation over the phases of HOLC. The proposed decision model is conducted in 3 scenarios; I. The decision in 4-phase HOLC, international relief operation of French Red Cross (FRC). II. The decision on 3-phase HOLC, national operation by the Thai Red Cross (TRC). III. The decision on response phase HOLC, international operation by the FRC in four countries. In this phase, the scenario I and II are performed step by step though numerical calculation and mathematical formulas. The scenario III will be presented in the third phase.In the third phase, an application of web-based multi-criteria decision support system (WB-MCDSS) which implement the proposed model is developed. The web-based multi-criteria decision support system is developed based on the integration of analytical hierarchy process (AHP) and TOPSIS approaches. In order to achieve an appropriate decision in a real time response, the WB-MCDSS is developed based on server-client protocol and is simple to operate. Last but not least, a validation application of the model is performed using the sensitivity analysis approach.

The application of environmental performance indicators (EPIs) has received increasing attention by both governments and international organisations as a tool for assessing complex environmental scenarios in national and local decision making processes. However, at the regional scale there is a gap in the application of EPIs, as this has not been well understood and defined due to a limited theoretical foundation and often insufficient data from all participant countries. The regional scale is important because it can incorporate natural ecosystems which often transcend national boundaries. A case study is developed for the Lower Mekong Subregion (LMS), where four riparian Southeast Asian countries (Lao PDR, Thailand, Cambodia, and Viet Nam) share the Lower Mekong River. The research proposes a conceptual framework to identify approaches for developing criteria for acceptable and appropriate EPIs which can be used to support and implement decision making processes by relevant organisations at the regional level. This research evaluates the application of environmental performance indicators using methodologies that assess cross-national quantitative and qualitative data and existing decision support systems. In addition, global and national indicators are examined for application and relation to the regional context. The research finds that the application of EPIs varies according to spatial scale, and is diverse among the four countries. Data availability is also identified as a major problem encountered during the development and selection of EPIs. The study finds that the governance of the existing regional body is ineffective due to differing agendas pursued by each participating country. This is because the current regional body is structured only to facilitate information exchange and cooperation in a limited manner, focusing so far only on water management issues. LMS regional goals need to be set in order to guide the stakeholders in identifying an appropriate set of EPIs. Most importantly, the research is intended to be a catalyst for encouraging the participants to integrate methods and other species of EPIs proposed in this research in their environmental assessment policies.

<p>The internal and external challenges construction companies face such as variability, low productivity, inefficient processes, waste, uncertainties, risks, fragmentation, adversarial contractual relationships, competition, and those resulting from internal and external challenges such as cost overruns and delays negatively affect company performance and profitability. Though research publications abound, these challenges persist, which indicates that the following gaps exist. Lean construction, process improvement, and performance improvement research have been conducted wherein improvement principles, and best practices are used to ameliorate performance issues, but several knowledge gaps exist. Few companies use these improvement principles and best practices. For those companies applying improvements, there is no established link between these improvements and performance/profitability to guide companies. Further, even when companies use improvement principles and best practices, they apply only one or two, whereas an integrated application of these improvement principles and best practices would be more effective. The other gap the author identified is the lack of strategic tools that construction companies can use to improve and manage their profitability. This thesis tried to fill the knowledge gap, at least partially, by developing a two-part excellence model for profitability improvement of construction companies. The excellence model lays out strategies that would enable companies to overcome the challenges and improve their profitability. The excellence model also gives an iterative and recursive continuous improvement model and flowchart to improve the profitability of construction companies. The researcher used high impact principles, guidelines, and concepts from the literature on organizational effectiveness, critical success factors, strategic company profitability growth enablers, process improvement, and process maturity models, performance improvement, and organizational excellence guidelines to develop the two-part excellence model.</p> <p>The author also translated the two-part excellence model into the diagnostic tool and Decision Support System (DSS) by use of process diagrams, fishbone diagrams, root cause analysis, and use of improvement principles, countermeasures and best practices at the most granular (lowest intervention) levels to do away with root causes of poor performance. The author developed the diagnostic tool and Decision Support System (DSS) in Access 2016 to serve as a strategic tool to improve and manage the profitability of construction companies. The researcher used improvement principles, and best practices from scientific and practitioner literature to develop company and project process flow diagrams, and fishbone (cause and effect) diagrams for company, department, employee, interactions and project performance for the profitability improvement, which are the engines of the diagnostic tool and DSS. The diagnostic tool and DSS use continuous improvement cycles iteratively and recursively to improve the profitability of construction companies from the current net profit of 2-3 percent to a higher value.</p>