<div>Every year power outages cost billions of dollars and affect millions of people. Historical data shows that between 2000 and 2016, 75% of power outages (in terms of duration) were caused due to severe weather events. Due to climate change these severe weather events are becoming more frequent. The National Association of Regulatory Commissioners have recently emphasized on the importance of building electricity sector's resilience thus ensuring long term reliability and economic benefits for the stakeholders. These severe weather events are called High Impact Low Frequency (HILF) events, which means that these events may not occur every year, but when they happen, the impact is likely to be severe. So, it is imperative that the risk of power outages due to severe weather events and their economic impact is persistent. To mitigate the risk, utilities need to invest heavily so that the impacts due to these HILF events can be minimized. Under this situation, utilities face three key questions (1) where to invest (2) how much to invest and (3) how to justify the investment. Therefore, there is a need to develop a framework for investment related decision-making, which can identify the optimal strategies for minimizing the economic impacts of severe weather induced power outages under different budget conditions. It is equally important to understand the cascading impacts of the sustained power outages during natural disasters before investment can be planned for building resilience in electricity sector. The existing frameworks to access the costs of severe weather induced power outages grossly undermines the overall economic impacts. This research has (1) assessed the economic loss due to severe weather induced power outages in terms of loss of Gross Domestic Product (GDP) and (2) developed a framework for identifying the optimal risk reduction strategies to minimize the economic impact. For assessing the economic impact, this research has adopted Inoperability Input-Output Model (IIM) using 20 years of historical data from the Bureau of Economic Analysis (BEA). The proposed framework has the flexibility to accommodate the risk appetite of the decision maker. The framework can be used by the Investor Owned Utilities (IOUs) for the rate approvals from the State Utility Regulatory Commissions by justifying the importance of their resilience building projects to the State's economy. <br></div>

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This dissertation examines a major policy change in the context of energy decision-making for shale gas development in the province of New Brunswick, Canada. After a long series of public engagement exercises aimed at regulating and promoting the safe development of shale gas resources in New Brunswick, the provincial government implemented a moratorium on hydraulic fracturing in 2014 and extended it indefinitely in 2016. The dissertation is interested in how policy-oriented learning may have influenced this policy change from both an empirical and a theoretical perspective. Theoretically, in line with recent scholarship on policy learning, this study trains its sites on the nature of policy learning and how it may influence change. To this end, the dissertation is grounded in the Advocacy Coalition Framework (ACF), a theoretical approach with (i) clearly defined mechanisms of learning, and (ii) significant application to resource development and to case studies of resource development in jurisdictions across North America and globally. The study builds on the ACF by proposing a conception of learning drawing on post-positivist literature. The study argues that learning is too narrowly focused on policy elites in the ACF and should be expanded to consider the role of non-traditional actors. The analysis questions the notion that learning can be isolated to rational and technical understandings amongst policy elites, and aims to integrate interactive knowledge into the analysis as a fundamental component of learning. The research aims to contextualize learning and understand the factors that shape policy learning and policy change. The dissertation focuses on the role of three factors - public engagement, uncertainty and trust - in shaping policy actors' learning. Empirically, the study examines the case of New Brunswick between 2007 and 2017. The province undertook multiple public engagement exercises regarding shale gas development in the context of unknown risks and uncertainty associated with the practice of hydraulic fracturing, an emerging technology that enabled the production of shale gas on a large scale. Two major coalitions emerged that advocated for and against shale development in the province, with the dominant pro-development coalition asserting that shale gas could proceed safely through stringent regulation. Through documentary analysis, interviews and a media analysis, the research reveals that interactive knowledge was a key component of how people learned in the case. The anti-shale coalition in New Brunswick brought its lived experience - notably its lack of trust in public authorities to successfully regulate fracking - to bear on decision-making, and was able to undermine and question the pro-development coalition's position that the risks associated with hydraulic fracturing could be managed. The anti-shale coalition mobilized this knowledge through the government's public engagement exercises and successfully contested the dominant coalition's beliefs. Fundamentally, the study demonstrates that public engagement, uncertainty and trust are three key factors that can shape policy learning and change.

The South African (SA) sugar industry supports approximately 50,940 small and large scale producers who collectively produce 22 million tons of sugarcane seasonally, on average. SA farmers face many challenges that lead to an uncertain decision making environment. Despite a general consensus among agricultural economists that risk constitutes a prevalent feature of the production and marketing environment, various authors have recently stated that risk-related research has failed to provide a convincing argument that risk matters in farmers' decisions. The various shortcomings of previous research have been identified and recommendations for the future proposed. Recommendations include that the focus of future risk research should be on holistic risk management. This study firstly identified the perceived importance of 14 separate sources of risk for a sample of 76 large-scale commercial sugarcane farmers in KwaZulu-Natal. Once a sufficient understanding of the risk perceptions of respondents had been attained, their use of 12 risk-related management strategies was determined. Principal components analysis (PCA) was used to investigate how individual management instruments are grouped together by respondents into choice brackets in order to make use of complementary and substitution effects. The study then proposed and demonstrated a technique that may be used in future research to isolate the effects of risk on individual risk-related management responses by modelling the management strategies contained within individual choice brackets with two-stage least squares regression analysis (2SLS). The most important risk sources were found to be the threats posed by land reform, minimum wage legislation and the variability of the sugar price, in that order. PCA identified seven risk dimensions, collectively explaining 78% of the variance in all 14 risk sources considered. These dimensions were: the "Crop Gross Income Index", "Macroeconomic and Political Index", "Legislation Index", "Labour and Inputs Index", "Human Capital and Credit Access Index", "Management Index" and the "Water Rights Index". Respondents were also asked questions regarding risk-related management strategies, including diversification of on-farm enterprises, investments and management time. PCA identified six management response brackets, collectively explaining 77% of the variance in the 12 responses considered. These response indexes were: the "Mechanisation and Management Bracket", "Enterprise and Time Diversification Bracket", "Insurance and Credit Reserve Bracket", "Geographic and Investment Diversification Bracket", "Land Trade Bracket" and the "Labour Bracket". Lastly, the study proposed a methodology for investigating the role of individuals' risk preferences in decision making. The recommended technique involves the simultaneous modelling of the major risk-related management strategies within each management response bracket, using 2SLS. A measure of risk preference was included in the 2SLS analysis to establish the influence of risk on decision making. By applying this methodology to the data obtained in this study, respondents were shown to be taking advantage of various complementary and substitution effects that exist between management responses. This was evident from the PCA and confirmed for the first previously identified management response bracket using 2SLS regression analysis. Risk attitude was shown to be a significant determinant of management decisions regarding the extent to which back-up management is kept in reserve. Important policy recommendations stemming from this study include that government review restrictive labour legislation and decrease the uncertainty surrounding new land redistribution legislation. Farmers need to make better use of available information by considering the effects of any single management decision on separate decisions, enabling them to take further advantage of substitution and complementary effects that may exist between management strategies previously considered in separate decision brackets. The fact that mechanisation and labour use occur in separate risk-related management response brackets in this study is an example of one such substitution effect that farmers do not seem to be utilising in terms of their management decision making. Future research using time series data is important in order to identify how risk perceptions and management portfolios change over time. Also, further research using the methodology proposed in this study may prove to be a useful means of more adequately addressing the question "Does risk matter in farmers' decisions?" / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.

A gap exists in the methods used in industry and available in academia that prevents customers and engineers from having a voice when considering engineering risk appetite in the dynamic shaping of early-phase conceptual design trade study outcomes. Current methods used in Collaborative Design Centers either collect risk information after a conceptual design has been created, treat risk as an afterthought during the trade study process, or do not consider risk at all during the creation of conceptual designs. This dissertation proposes a risk-informed decision making framework that offers a new way to account for risk and make decisions based upon risk information within conceptual complex system design trade studies. A meaningful integration of the consideration of risk in trade studies is achieved in this framework thus elevating risk to the same level as other important system-level design parameters. Trade-offs based upon risk appetites of individuals are explicitly allowed under the framework, enabled by an engineering-specific psychometric risk survey that provides aspirational information to use in utility functions. This dissertation provides a novel framework and supporting methodologies for risk-informed design decisions and trades to be made that are based upon engineering risk appetites in conceptual design trade studies. / Graduation date: 2012