No description available.

No description available.

Successfully managing interpersonal relationships requires both pursuing desirable bonds and forgoing those that could be costly. Balancing these goals might be more difficult for some than for others, especially for those with low self-esteem who are motivated to connect, yet stifled by their lack confidence in their abilities to attract desirable dating partners. So, when a potential date’s romantic interest is unambiguous, will they eagerly seize any opportunity to connect, or will the desirability of the person making the request influence their decision? In three laboratory experiments, single, female participants were randomly assigned to receive a romantic overture from an ostensible, single, male who was presented as a desirable or an undesirable dating partner. Independent of whether they accepted or rejected the target’s advances, lower, relative to higher, self-esteem individuals experienced more emotional and cognitive uncertainty and distress before and after making their decision. Desirability of the target moderated some of these effects, such that high self-esteem individuals appropriately distinguished between desirables and undesirables, whereas low self-esteem participants experienced distress at the thought of accepting or rejecting either target. Notably, the actual decisions participants made were unaffected by self-esteem, and driven instead by the extent to which the target was presented as possessing desirable social commodities. Results are discussed with reference to potential mechanisms driving self-esteem differences in balancing the pursuit of quality interpersonal bonds while avoiding costly relations.

Due to the nature of survey design, the estimation of parameters associated with small areas is extremely problematic. In this study, techniques for the estimation of small area proportions are proposed and implemented. More specifically, empirical Bayes estimation methodologies, where random effects which reflect the complex structure of a multi-stage sample design are incorporated into logistic regression models, are derived and studied. / The proposed techniques are applied to data from the 1950 United States Census to predict local labor force participation rates of females. Results are compared with those obtained using unbiased and synthetic estimation approaches. / Using the proposed methodologies, a sensitivity analysis concerning the prior distribution assumption, conducted with a view toward outlier detection, is performed. The use of bootstrap techniques to correct measures of uncertainty is also studied.

Progressive Neuromuscular Diseases (PNDs) are relentless, debilitating, incurable diseases that cause nerves and muscles to atrophy. A large portion of the population who experience PNDs are adolescents. These adolescents progressively lose physical abilities and increasingly rely on caregivers at a time in their life when, paradoxically, normative adolescent development prescribes a move towards independence and autonomy. There is little research examining this experience from the adolescents’ perspectives. The purpose of this interpretive phenomenology study was to understand the experience of adolescents with PNDs when making decisions in relation to their health. Data collection consisted of 10 semi-structured interviews with 5 adolescents, 16-19 years of age, who were living with a PND (two interviews with each of the 5 participants). These interviews lasted an average of 60 minutes. Data were analysed using interpretive strategies, including the development of themes using exemplars, and paradigm cases. Findings revealed that the adolescents separated health decisions into two distinct categories, Big and Small, based upon level of perceived risk and physician involvement. Big referred to high-risk decisions, included physicians, and involved a medical/surgical procedure or intervention. Small referred to lower risk decisions, did not include physicians, and involved personal care. An expert emerged with each category of decision. In Big Decisions, the physician was perceived as the expert who made recommendations, provided information, and introduced the decision. In Small Decisions, the adolescent perceived himself as the expert. With Big Decisions, the physician expertise was typically respected, and the recommendations were followed. With Small Decisions, parents typically respected adolescent expertise. However, the adolescents commonly experienced not having their expertise respected by health professionals. In the context of Big and Small decisions, the theme Joint Ownership captured the sense that with the progressive loss of abilities and resulting dependence, the physical disability and illness were not experienced solely by the adolescent but by the adolescent and his parent(s). As the parent(s) and adolescent shared these experiences, the decisions, ownership of the physical body, and the responsibility for the care of the body also became shared. The findings suggest that health care professionals need to include the adolescents in the Small Decisions, and also acknowledge that adolescents may desire parental involvement in Big Decisions.

Entrepreneurs make decisions that influence subsequent decisions and future performance. The dissertation studies such sequences of decisions by using dynamic programming. This approach allows one to describe the decision process over time and, in some cases, it prescribes how business performance can be improved. An analytical approach helps to contribute a new dimension to entrepreneurship research and it encourages multidisciplinary work by allowing existing methodologies from various (analytical) disciplines to be applied to entrepreneurial problems. The dissertation focuses on research questions that invoke effort allocation in sequential decision-making at early development stages of a new venture creation. The dissertation is composed of three separate research studies. What dominates the entrepreneur's decision process initially is the effort allocation problem in sharing time between an existing job and committing to the new venture. The first study describes how this time-sharing is done and characterizes when is the best time to leave the wage job and become a full-time entrepreneur. I also show that the optimal time-allocation policy is driven by the entrepreneur's tolerance for work and by how returns behave with respect to time allocation in the venture. It is important to understand resource allocations to internal activities such as product development and customer recruitment. The second study focuses on new product development and it investigates how the flow of a new venture's funding affects the development of a new product. I prescribe the optimal release time for the new product and describe how this strategy is affected by the expected amount of funding and its uncertainty. I also identify industrial and entrepreneurial characteristics that generate various behaviors for the rate of change in the return on product quality as investment in the product is increased. The newly developed product must be bought to make the business start-up successful. The third study investigates how an entrepreneur makes decisions over time in allocating effort to building and exploiting a customer base so as to maximize profit. I study what a rational entrepreneur will do when faced with the allocation of effort to different customer categories. I also provide guidelines for improving the performance of an entrepreneur who may not be acting optimally. In these three investigations a dynamic programming approach is utilized to study various sequential decision processes of an entrepreneur during the development process of new venture creation.

In practical people activity (in economy, control, projection of constructive and so on) there are often cases when you have to chose one solution from several. Inherently arises the task to find the best solution. Most of solutions in persons life and organisations are done in series. It means, that they can make the last solution at any moment or suspend it for later time, in the hope of better times. Part of consistent statistical solutions shows not clear events in the future and limited plausibility of our observations. Dynamic programming is simple way for optimizing consistent solutions. Dynamic programming is applied when specific problems arise, such as development of specific algorithms. There are analyzed two types of tasks in this work: one-off consistent solution and multifold consistent solutions. There are two appointed tasks, one is engineering type (technological process braking), other economic type (purchase of flat).

Can only a subset of individuals – those higher on the ability to understand the sources of emotions – determine whether to disregard or allow the effects of emotions when making decisions? I test two central predictions. First, I test whether individuals high on emotion understanding ability (EUA), one of the key dimensions of emotional intelligence, are less affected by incidental anxiety when making decisions involving risk than their lower ability counterparts. The rationale for this prediction is that individuals who have high EUA are able to correctly identify their source of anxiety and, based on perceived irrelevance, disregard incidental anxiety when making risky decisions, whereas individuals who have low EUA are confused about the source of anxiety and are more influenced by incidental anxiety when making risky decisions. Second, I test whether individuals high on EUA are more affected by integral anxiety when making risky decisions than their lower ability counterparts. The rationale for this prediction is that individuals who have high EUA are able to correctly identify their source of anxiety and, based on perceived relevance, use their integral anxiety to inform their risky decision making whereas those who have low EUA misattribute their anxiety and are less likely to incorporate their integral anxiety into their decision making. In Experiment 1, incidental anxiety reduced risk-taking among individuals with low EUA, but not among their higher ability counterparts. In Experiment 2, the interactive effect of EUA and incidental anxiety on risk-taking was eliminated when I identified the irrelevance of anxiety to the present decision, but it remained when the irrelevance was not identified. To explore the role of EUA in using the adaptive function of emotion in decision making, Experiment 3 assessed whether emotionally intelligent individuals who have high EUA incorporate integral anxiety, as measured by skin conductance responses, into their risk-taking, compared to those with low EUA. Contrary to expectations, the results of Experiment 3 showed that, when EUA was high, there was a negative effect of integral anxiety on risk-taking that was not significant. When EUA was low, there was a significant positive effect of integral anxiety on risk-taking.

This study sought to provide a theory driven model to explain how consumers make their purchasing decisions between genuine products and products they know are counterfeit. The influences of Goal-Driven Theory, Morality, and Prospect Theory were included as purchase decisions considerations. To measure their influence, while accounting for product attributes, purchasing decisions were assessed in choice sets as provided by Discrete Choice Experiment. Results found support for using Goal-Driven Theory and Prospect Theory to explain consumer purchasing decisions between genuine and counterfeit products. Morality was not a significant factor in the findings. Theoretical contributions and Managerial implications are discussed.

Neuromuscular diseases are difficult to diagnose, requiring specialized equipment and training. A decision support system facilitates this by visualizing the data produced by a classification system, allowing users to make a diagnosis. This thesis explores the development of a specific component of the decision support system; a comparison tool which allows the user to explore the visualization by making comparisons between assertions derived from the underlying classification system. After studying the impact of the comparison tool upon the performance of volunteer users, we provide recommendations on the utility of a particular decision exploration strategy and give guidance for the correct course for the future development of this system. This document illustrates some of the unique challenges associated with the evaluation of a decision support system which relies not only upon the computational power of the computer, but also upon a human’s innate ability to solve problems.