Browsing by Subject "Risk perception"
Now showing 1 - 4 of 4
- Results Per Page
- Sort Options
Item Exploring the role of emotion and risk-benefit perceptions in information seeking and avoidance(2021-08-09) Wang, Wan, Ph. D.; Kahlor, LeeAnn; Atkinson, Lucy; Pounders, Kathrynn; Dudo, Anthony; Whittaker, TiffanyPeople interact with information to form their risk evaluations and seek guidance to respond to hazards. Their information behaviors, as with many other risk responses, are compounds of cognitive and affective decisions. As with many evolving technologies, the application of nanotechnology presents downsides and benefits. Therefore, when evaluating a novel technology, particularly nanotechnology, risk and benefit perceptions, as well as negative and positive emotions, can coexist. To understand the mechanism of how cognitive and affective risk evaluations impact individuals’ technology risk-related information behaviors, this study explores the main effects and interactions effects of risk perception, benefit perception, negative emotions, and positive emotions on information seeking and avoidance behaviors. With the collected survey data, this study conducted eight structural equation modeling analyses. The main findings include: negative emotions and risk perception were better predictors of information seeking, and positive emotions and benefit perception were better predictors of information avoidance. The interaction effects between cognitive and affective risk evaluations were presented and discussed as well.Item Measures of risk in economics and finance(1988) Laurence, Antoine, 1965-; Not availableItem Perceptions of risk in increasingly capital-intensive electricity grids : measuring the impacts of accurate cost of capital representation on investment planning for future energy systems(2022-05-11) Corcoran, James Sean; Leibowicz, Benjamin D.The U.S. electric grid is experiencing unprecedented change as the system continues a path toward a more diversified and decarbonized generation mix, with increased investment in wind, solar, storage and other energy transition technologies. Concurrently, market structures continue their evolution away from highly regulated monopolies and towards competitive markets, expanding the share of deployable capital that engages with the power sector and introducing a broader range of investor classes and preferences. These two factors create complex financing dynamics that ultimately determine which set of technologies are deployed onto the grid. However, many of the leading tools used by stakeholders to guide long-term system planning do not sufficiently account for these dynamics with oversimplified financing cost representations. Through the modeling of the ERCOT electric grid using the Regional Energy Deployment System (ReEDS), this study assesses the significance of improved representation of financing costs for the various stakeholders who interact with large-scale capacity expansion models. This is achieved through the exploration of two distinct but connected research objectives, the first being relevant to energy modelers and the second to policymakers. First, the impacts of representing financing costs in a more sophisticated manner across technologies and over time are measured through the investigation into empirically observed financing dynamics, including (1) the general level of risk associated with the electric power sector, (2) differences in technology-specific risk perception, (3) financing improvements as investors gain familiarity with specific technologies, and (4) operational risk priced into financing “hurdle rates.” ReEDS analysis finds that general system risk does matter, as a system modeled with a uniform 10% discount rate deploys 44% less renewable energy capacity compared to one with a market-weighted uniform 6.02% discount rate. Implementing financing learning rates can also have a material effect on system outcomes, increasing wind and solar deployment significantly through 2050. Secondly, a policy analysis, enabled by the improved financing representation developed in the first objective, is completed to predict system outcomes from a move to Direct Pay in a 10-year tax credit extension, recently proposed as part of the Biden Administration’s Build Back Better infrastructure package. Through the construction of a Discounted Cash Flow (DCF) model to measure the impact of a switch to refundable tax credits on a project’s debt capacity, the study demonstrates how the policy would increase renewable technologies’ access to lower-cost capital, enabling further deployment. ReEDS modeling finds that Direct Pay’s primary advantage lies in accelerating the deployment of wind and solar over the period 2022-2030, which in turn accelerates the decarbonization of the power sector. This switch to Direct Pay results in cumulative emissions reductions of 24% through 2050, compared to current nonrefundable tax credits, due to the reduction in financing costs alone. This reduction increases to 35% when including the reductions in soft costs that are possible from the move to a more simplified capital structureItem Understanding the factors that influence women's decisions to use hormone replacement therapy during menopause using the Theory of Planned Behavior(2002-08) Adamus, Andrea Taylor; Shepherd, Marvin D.The purpose of this study was to determine the factors that influence women's decisions to use hormone replacement therapy (HRT) during menopause. Using the Theory of Planned Behavior and constructs of risk perception, this study was able to explore the beliefs and attitudes of women about HRT use during menopause. The study was also able to explore how risk perception of HRT and the conditions that affect women during midlife impact their decision to use HRT during that time. Focus groups were conducted to develop the questionnaire used in the larger study. A community-based sample of women from Houston area churches participated in the study. The major theme that emerged from the focus groups was the weighing of cancer risks and the protection benefits of HRT. The most interesting factor that emerged as a barrier to HRT use was "negative publicity" and myths toward taking HRT. Results from the larger study demonstrated that the construct of attitude was the predominate predictor of intention when direct measures were used in a model to predict intention. Meaning that women's attitudes towards HRT use during menopause (whether they are safe, wise to use, good or bad, beneficial, risky, pleasant, or valuable) played a significant role in their intention. In contrast when the belief-based measures were used in the model, subjective norm and perceived behavioral control were significant predictors of intention. Meaning that the intention to use HRT was based more on the influence of their husbands, physicians, and families. This also meant that the dosage form, cost, negative publicity, family history of cancer, personal fear of developing cancer, and education about HRT would affect their intention to use HRT during menopause more than the advantages and disadvantages of using HRT (advantages such as protection from osteoporosis, relief from hot flashes; or, disadvantages such as risk of breast cancer). Finally, women's perception of risk with regards to HRT was highest for breast cancer followed by heart disease, endometrial cancer, and osteoporosis. This study found that there are many factors that may affect the decision to use HRT during menopause and that overall these factors affect women’s attitudes towards HRT and their intention to use it.