Infrastructure projects, based on the Build-Operate-Transfer, (BOT), method, have been of interest to governments of developed and developing countries for some time, resulting in their worldwide use. Using the BOT method enables governments to reallocate risks and rewards to the private sector for larger infrastructure projects throughout the projects' operating life. In order to implement a BOT infrastructure project successfully, one of the essential requirements is to carry out a thorough analysis of risks relating to the project including the social, economic, environmental, political, legal, and the financial aspects. Due to the fact that the type of risk study required for large-scale projects is so sophisticated, and therefore expensive and time consuming, the government, due to lack of expertise and time, often obtains a project viability study from the private sector. This can cause problems in that the private sector may incur financial losses or even bankruptcy, unless the host government guarantees compensation to the losers of the bid. Because all parties have different targets which they wish to achieve from the project, a may conflict arise and cause lengthy negotiations, sometimes lasting for years which often result in the death of the project. The greatest opportunity for a successful outcome for a BOT project is obtained when the extensive efforts and costs involved in the risk study process are shared by all parties. The responsibility of the decision maker is to identify, understand and analyze the many risk factors both, qualitative, (linguistic in nature) and quantitative, that will affect funding, procurement, developing, construction and operation, before proceeding with the build stage of the project. Firstly, it is necessary to evaluate the quantitative Risk Factors subjectively, and list them in order of importance. Secondly, conduct an evaluation of the qualitative factors and since the consideration of qualitative factors is subjective, the decision maker will often limit the number of factors being evaluated possibly resulting in inconsistent results. This study proposes a decision framework, which would be useful in determining the influence of the qualitative Risk Factors on the project management of BOT infrastructure projects. A methodology is provided to enable the identification of interrelationships between the Risk Factors and their influence on the project. Using Analytical Hierarchy Process (AHP) techniques, which model the relationships between the Risk Factors, a validation of this approach will be sought using a decomposed evaluation method and also information obtained from three existing case studies, (the Channel Tunnel, Sulaibiya Wastewater Treatment and Reclamation Plant and Marsa Allam Airport). The results of the decomposed approach were compared to experts' holistic evaluations for the same case studies mentioned above. The findings indicate that the decomposed approach showed a strong correlation to the holistic approach. An evaluation of the risks for the Sulaibiya Wastewater Treatment and Reclamation Plant study is provided and suggestions made to highlight risks attached to such a project before it is actually undertaken. Using the decomposed approach enables the decision maker to see the contribution of each risk compared to all of the risks in the total project and will help to determine and subsequently minimize or preventing any risk factors and so considerably improving the risk management of the project.

In this study the dynamics of risk perceptions about BSE held by Canadian consumers and cow-calf operators are evaluated. Since the BSE outbreak in 2003, Canadian consumers and cow-calf operators may have had various different reactions to BSE. These reactions may be related to their different levels of risk perception about BSE, risk perceptions which may have evolved over time and may be affected by BSE media information. These reactions may also be the result of factors other than BSE. An analysis of behavioural models of consumers and cow-calf producers is required to reveal the impacts of both BSE risk perceptions and non-BSE related factors. In this study, the risk perceptions about BSE are specified applying a Social Amplification of Risk Framework (SARF) and a Prospective Reference Theory (PRT), and evaluated through market observed behaviour of Canadian consumers and cow-calf producers, an approach which is different than the traditional stated preference approach to eliciting risk perception measures. Parametric and non-parametric structural break tests associated with the BSE outbreak (May 2003) are employed to evaluate changes in consumers or cow-calf operators behaviour. The results show that SARF is supported by both panel data and time series data on Canadian consumers and cow-calf producers, suggesting that their risk perceptions about BSE are amplified by both the quantity and quality of BSE information. Risk perceptions about BSE have led to a decrease in beef demand and an increase in slaughter cow supply, which in turn, exacerbated losses in Canadian beef sector. Structural break tests related to the BSE outbreak in May 2003 confirm changes in both consumers and cow-calf producers behaviour. Consumers with different profiles had different levels of risk perceptions about BSE and different demand and substitution elasticities. Cow-calf producers from different regions also had different levels of risk perceptions about BSE and different supply elasticities, suggesting the need for more analysis of market segmentation. Simulation analyses over the North American beef sector further confirmed the impact of BSE risk perceptions of Canadian consumers and cow-calf producers in the North American beef and live cattle market. / Agricultural and Resource Economics

Ports play a critical role in transportation infrastructure, but are vulnerable to seismic hazards. Downtime and reduced throughput from seismic damage in ports results in significant business interruption losses for port stakeholders. Current risk management practices only focus on the effect of seismic hazards on individual port structures. However, damage and downtime of these structures has a significant impact on the overall port system's ship handling operations and the regional, national, and even international economic impacts that result from extended earthquake-induced disruption of a major container port. Managing risks from system-wide disruptions resulting from earthquake damage has been studied as a central element of a Grand Challenge project sponsored by the National Science Foundation Network for Earthquake Engineering Simulation (NEES) program. The following thesis presents the concepts and methods developed for the seismic risk management of a port-wide system of berths. In particular the thesis discusses the framework used to calculated port losses: the use of spatially correlated ground motion intensity measures to estimate damage to pile-supported marginal wharves and container cranes of various configurations via fragility relationships developed by project team members, repair costs and downtimes subsequently determined via repair models for both types of structures, and the impact on cargo handling operations calculated via logistical models of the port system. Results are expressed in the form of loss exceedance curves than include both repair/replacement costs and business interruption losses. The thesis also discusses how the results from such an analysis might be used by port decision makers to make more informed decisions in design, retrofit, operational, and other seismic risk management options.

No description available.

This study attempted to establish a tax risk framework (TRF) with guidelines to equip parties concerned in a business environment with the necessary tax risk management (TRM) skills and knowledge .Countries obtain a significant part of their financing from taxes. Regardless of normal risks within a business environment, there are also payable taxes to be dealt with. Existing procedures in businesses do not have a TRM-function. Control Environments in businesses do not necessarily have a TRM component. As tax is the single main contributing expense on the income statement bottom-line, it is imperative that it should be included in the risk assessments. TRM is the process of understanding, interpreting and implementing tax laws in order to mitigate tax risks. The basic definition of TRM is to apply tax laws to such an extent that the minimum amount of tax is paid, whilst adhering to the law. A TRM-framework must comply with international reporting standards and governance. Existing frameworks, guidelines and policies available on risk management do not cover the specific area of tax, which complicate the establishment of a single framework. SARS is changing its auditing approach and joining hands with taxpayers, trying to determine their ways in managing tax risks. Grey areas in legislation cause loopholes and misinterpretations – leading to incorrect calculations, risks and incorrect amounts of taxes being paid. More companies in South Africa expand their business activities to Africa from which export/import tax issues arise. A proper TRM framework will enable persons to estimate risks the moment they make a new deal. This will save a great deal of time and money. AFRIKAANS : Die doel van hierdie voorlegging is om ‘n raamwerk vir belastingrisiko met riglyne aan betrokke partye in besighede voor te stel. Dit sal hulle toerus met die nodige vaardighede om belastingrisiko’s te identifiseer en te hanteer. Lande se enkele grootste bron van finansiering is vanuit belasting. Afgesien van normale risiko’s in `n besigheid is daar ook die kwessie van betaalbare belasting wat bestuur moet word waarvoor huidige besigheidstelsels nie voorsiening maak nie. Vanweë die feit dat belasting die enkele grootste uitgawe op die inkomstestaat is, is dit van kardinale belang dat dit deel vorm van die risiko assesserings proses in besigheid. Belastingrisikobestuur behels die begrip, interpretasie en implementering van belastingwette om risiko’s te verminder. Die minimum belasting moet betaal word, maar belastingwetgewing moet steeds nagekom word. Hierdie raamwerk vir belastingrisikobestuur moet egter steeds aan internasionale verslagdoening standaarde voldoen ten einde finansiële inligting aan te meld en te reguleer deur middel van goeie korporatiewe beheer. Bestaande raamwerke, riglyne en beleide rakende risikobestuur maak nie spesifiek vir belastingrisiko’s voorsiening nie wat die daarstel van ‘n afsonderlike belastingraamwerk bemoeilik. Die Suid-Afrikaanse Inkomste Diens is besig om die benadering van oudits te hersien en ‘n nouer verwantskap met belastingbetalers te sluit ten einde hul bestuur van belastingrisiko’s te bepaal. Grys areas in wetgewing veroorsaak skuiwergate en verkeerde interpretasie met foutiewe berekenings, risiko’s en betalings. Al hoe meer besighede in Suid-Afrika brei hul sakebelange na Afrikalande uit, waaruit invoer-/uitvoerkwessies rakende belasting ontstaan. ‘n Deeglike risikobestuursplan wat belastingkwessies aanspreek, sal die rolspelers instaatstel om risiko’s onmiddellik te bepaal sodra ‘n transaksie gesluit word. Sodoende kan tyd en geld bespaar word. / Dissertation (MCom)--University of Pretoria, 2013. / Taxation / unrestricted

The presented study investigates the role of Machine Learning in Regulatory Compliance software systems by conducting a case study in the maritime industry. There is a need to obtain a clear understanding of Machine Learning approaches for automating regulatory compliance.  Background: Organizations and software developers face different regulations in different domains that need to be satisfied by the requirements of systems. Trading across borders brings challenges in managing each country's regulatory requirements. Even though a large amount of effort from international and local organizations, an efficient AI-based system is not yet fully deployed for offering decision support in handling such complex issues as a viable solution. The increasing enforcement of sanctions and anti-money laundering by various institutions and countries poses a significant threat to many industries worldwide if they are not educated or aware of the legal and financial risks. therefore, Regulatory Compliance plays a critical role in this area. Regulatory Compliance is a guideline for laws or regulations related to the business that the stakeholders must abide by to promote a safer business environment and benefit society. Developing a Digital Compliance(DigiComp) system as a software service is a solution that involves both technical and organizational challenges which need a large amount of research. As a case study, an AI-based DigiComp system has been implemented in the port of Vordingborg for the EU-financed project "Connect2SmallPorts". A major Corporate challenge was the choice of appropriate and efficient approaches and tools for designing the automated regulatory compliance system. This study investigates the role of Machine Learning in regulatory compliance systems and its possible opportunities and limitations.  Objectives: The significant role of compliance management made it an interesting research topic since some highly regulated systems need to follow specific laws and guidelines. As the objectives of this study, the role of machine learning on regulatory compliance systems has been investigated by extracting the most popular ML approaches and their benefits and challenges from previous studies and then analyzing the related benefits and limitations in a real-world case. Methods: We have done a systematic literature review as the qualitative research method with database search and snowballing to collect the applied Machine Learning approaches and their benefits and challenges for Regulatory Compliance software systems. Then a case study was conducted for implementing a regulatory compliance system in the maritime industry and investigating the benefits and challenges in a real-world project. Also, Focus groups and interviews with the stakeholder and domain experts were held as data collection methods during the case study.  Results: After investigating the existing challenges in regulatory compliance and identifying the risk assessment framework based on Machine Learning as the most popular AI approach in this area, we implemented a risk assessment framework based on neural networks. It provides high accuracy and a low error rate in predicting the future state to prevent the non-compliance risk. Conclusions: Examining the proposed digital compliance system explores its similarity to the benefits and limitations extracted from SLR. This study has provided the development of a new AI-Based system that can inspire software companies to build more efficient regulatory compliance systems for different domains in the industry.

In the West African country Ghana, which has a history of poor natural resource management, discovery of offshore petroleum resources in 2007 and subsequent commercial production in 2010 (with British multinational Tullow Oil as lead operator) is a potential source of potential wealth and inequality. Using the Cultural Theory of Risk, Social Amplification of Risk Framework, and the Corporate Sustainability Framework — a proposed model—as theoretical foundations, this dissertation examines corporate sustainability practices, communication, and their implications for local residents’ risk perceptions, corporate reputation, and risk management. The study also assesses how cultural worldviews and informational networks (e.g., an environmental group, opinion leaders, and media) amplify or attenuate residents’ risks perceptions. Data were collected via interviews with key actors including a non-governmental organization (NGO), a survey of a representative sample of Half Assini residents in one of the six coastal districts that adjoin Ghana’s offshore petroleum region, and analyses of Tullow’s corporate social responsibility (CSR) reports and other communication texts. Extant worldview and corporate reputation measures were also developed/adapted and tested. The study finds support for the view that cultural worldview and affect are associated with public risk perceptions. Thus, individuals who (a) do not subscribe to the worldview that government ought to regulate corporate behaviors, (b) show a relatively high sense of attachment to their communities, (c) rate the images associated with Ghana’s offshore oil production favorably, and (d) rate the images associated with Tullow Oil positively are more likely to be worried that Ghana’s offshore oil production poses significant risks for the country and their local communities. Regarding corporate sustainability communication, the study observes that Tullow uses a predominantly technical, expert-driven approach, which seeks to discursively position it as an aspirational, engaged, and responsible organization. While critiquing Tullow’s corporate sustainability and communication approach, the research also argues that corporate sustainability (CSR and risk) communication has the potential to constitute desirable corporate practices and could ultimately culminate in meaningful social change. Theoretical contributions to risk perception, risk management/communication, corporate reputation, and CSR communication are discussed. Practical implications for advocacy, corporate practices, and public participation in environmental decision-making are discussed.

No description available.

Research in risk awareness has been relatively neglected in the health informatics literature, which tends largely to examine project managers’ perspectives of risk awareness; very few studies explicitly address the perspectives held by senior executives such as directors. Another limitation evident in the current risk literature is that studies are often based on American data and/or they are restricted to American culture. Both factors highlight the need to examine how senior executives (i.e., directors) who oversee or direct eHealth projects in Canada perceive risk awareness. This research explores and discusses the perspectives of risk awareness (i.e., identification, analysis, and prioritization) held by directors and project managers who implement Canadian eHealth projects. Semi-structured interviews with nine directors and project managers uncovered six key distinctions in these two groups’ awareness of risk. First, all project managers valued transparency over anonymity, whereas directors believed that an anonymous reporting system for communicating risks had merit. Secondly, most directors emphasized the importance of evidence-based planning and decision making when balancing risks and opportunities, an aspect none of the project managers voiced. Thirdly, while project managers noted that the level of risk tolerance may evolve from being risk-averse to risk-neutral, directors believed that risk tolerance evolved toward risk-seeking. Directors also noted the importance of employing risk officers, a view that was not shared by project managers. Directors also believed the risk of too little end-user engagement and change management was the most important risk, whereas project managers ranked it as the least important. Finally, when directors and project managers were asked to identify and define the root cause(s) of eHealth risks, directors identified the complexity of health care industry, while project managers attributed it to political pressure and a lack of resources where eHealth projects are concerned. This research proposes that the varied perspectives of risk awareness held by directors and project managers must be considered and integrated to properly align expectations and build partnerships for successful eHealth project outcomes. Understanding risk awareness offers a means to systematically identify and analyze the complex nature of eHealth projects by embracing uncertainties, thereby enabling forward thinking (i.e., staying one step ahead of risks) and the ability to prevent avoidable risks and seize opportunities. / Graduate / 0723 / 0489 / 0454 / randbpark@gmail.com