The decision to become an organ donor involves considering both self-relevant risks and the needs of others. This study applied prospect theory to examine how message frames that focus on the possible survival or death of a potential organ transplant recipient affect participants' willingness to become organ donors. Perceived personal risk and ambivalence were examined as moderating variables. Results indicate that risk, rather than ambivalence, played an instrumental role in participants' decisions to donate. Although no main effects or interactions related to message frame emerged in initial analyses, a supplemental analysis revealed a modest persuasive advantage for the loss-framed message among low-risk participants. Additional analyses revealed that for low-risk participants, perceived benefits of organ donation were higher for the loss frame than the gain frame, whereas the opposite pattern was found for high-risk participants. Findings suggest that decisions about organ donation may be associated with unique responses to message frames.

In many areas of Artificial Intelligence (AI), we are interested in helping people make better decisions. This help can result in two advantages. First, computers can process large amounts of data and perform quick calculations, leading to better decisions. Second, if a user does not have to think about some decisions, they have more time to focus on other things they find important. Since users' preferences are private, in order to make intelligent decisions, we need to elicit an accurate model of the users' preferences for different outcomes. We are specifically interested in outcomes involving a degree of risk or uncertainty. A common goal in AI preference elicitation is minimizing regret, or loss of utility. We are often interested in minimax regret, or minimizing the worst-case regret. This thesis examines three important aspects of preference elicitation and minimax regret. First, the standard elicitation process in AI assumes users' preferences follow the axioms of Expected Utility Theory (EUT). However, there is strong evidence from psychology that people may systematically deviate from EUT. Cumulative prospect theory (CPT) is an alternative model to expected utility theory which has been shown empirically to better explain humans' decision-making in risky settings. We show that the standard elicitation process can be incompatible with CPT. We develop a new elicitation process that is compatible with both CPT and minimax regret. Second, since minimax regret focuses on the worst-case regret, minimax regret is often an overly cautious estimate of the actual regret. As a result, using minimax regret can often create an unnecessarily long elicitation process. We create a new measure of regret that can be a more accurate estimate of the actual regret. Our measurement of regret is especially well suited for eliciting preferences from multiple users. Finally, we examine issues of multiattribute preferences. Multiattribute preferences provide a natural way for people to reason about preferences. Unfortunately, in the worst-case, the complexity of a user's preferences grows exponentially with respect to the number of attributes. Several models have been proposed to help create compact representations of multiattribute preferences. We compare both the worst-case and average-case relative compactness.

Investmentföretag har funnits sedan urminnes tider men har under senare år ofta fått stå tillbaka som investeringsalternativ till fördel för aktiefonder. Detta är lite motsägelsefullt då svenska investmentföretagen historiskt har haft en högre avkastning än den svenska aktiefondförvaltaren. Större delen av forskningen kring investmentföretag har fokuserat på substansrabatten. Vi fann väldigt få studier som berört investmentföretagens risktagande, speciellt ur ett portföljperspektiv. För att underlätta för den individuella investeraren ville vi använda ett riskmått som är lätt att förstå. Valet föll därför på Value at Risk (VaR) som vi anser ger ett lättförståeligt mått på risken i en portfölj samtidigt som det valideras genom Basel II. Då investmentföretagen är väldigt heterogena med avseende på deras portföljsammansättningar och investeringsstrategier valde vi att genomföra en fallstudie på Industrivärden och Svolder. Valet av dessa företag möjliggjorde också en jämförelse mellan ett större och mindre investmentföretag. Vi ville undersöka och jämföra hur deras risktagande påverkas och förklaras utifrån olika faktorer, med utgångspunkt från den tidigare omkringliggande forskningen. De teoretiska utgångspunkterna hämtades från fyra olika områden, risk och portföljvalsteori, Behavioural Finance, Corporate Governance och makroekonomisk statistik. Vi valde att genomföra en kvantitativ studie för att undersöka Industrivärdens och Svolders risktagande. Studien är baserad på investmentföretagens kvartalsrapporter mellan 2000 till 2011. Utifrån vår referensram definierade vi 13 olika variabler som statistiskt prövades mot risktagandet med hjälp av multipla regressioner. Från våra resultat kunde vi konstatera att den makroekonomiska statistiken förklarade mest av investmentföretagens risktagande. Gemensamt för båda investmentföretagen var att industriproduktionen, Fed fund rate och konjunkturbarometern visade på ett signifikant samband med risktagande. Vi fann även indikationer på att den geografiska exponeringen för deras portföljer hade betydelse för att förklara risktagandet. Vår studie pekade också på att investmentföretagens risktagande visade upp en trend och korrelerade negativt med börsmarknaden.

none

A recent debate has identified a description– experience gap, where the non-linear weighting function identified in prospect theory reverses when probabilities are discovered through experience rather than by description (probabilities). This thesis will explore the role of experience and probabilities theoretically and empirically. It is argued that both behaviors are compatible on a theoretical basis given a preference for the status quo, but produce opposing decision weights due to different cognitive and motivational factors. Probabilities focus a decision on the potential for rare events creating a preference for certain outcomes and reduced risk taking consistent with loss aversion. Experience overweighs customary outcomes consistent with sensitivity to a reference point or the status quo. Experience in the form of loss, however, moderates the effect of probabilities on risk taking. An experimental game of dice supports this hypothesis, suggesting ambiguity seeking in the face of loss and raising the possibility that the use of probabilities may not be always be maximizing behavior.

We live in an era where internationalization and globalization are two extremely attractive concepts. People aim to create a society where limits and restrictions are erased and a thriving society is a reality. Numerous transformations have occurred in order to realize this and one of the most vital ones is the globalization of the economy. The globalization was made possible through the discovery on the capital market. This market enables people to trade with each other, no matter place or time. Thus, a more efficient solution is offered for rapid and significant transfers such as loans and investment. According to various researchers, the capital market determines, in a way, which company will grow and which will stagnate in development. However, the capital market needs to be efficient in order to offer the services intended. The aim of this dissertation is to explain how efficient the capital market is when incorporating information regarding football player transfers. By examining the empirical findings, it will also be able to establish if assets of the same market value cause different share price fluctuations depending on if they are acquired or sold.

In many areas of Artificial Intelligence (AI), we are interested in helping people make better decisions. This help can result in two advantages. First, computers can process large amounts of data and perform quick calculations, leading to better decisions. Second, if a user does not have to think about some decisions, they have more time to focus on other things they find important. Since users' preferences are private, in order to make intelligent decisions, we need to elicit an accurate model of the users' preferences for different outcomes. We are specifically interested in outcomes involving a degree of risk or uncertainty. A common goal in AI preference elicitation is minimizing regret, or loss of utility. We are often interested in minimax regret, or minimizing the worst-case regret. This thesis examines three important aspects of preference elicitation and minimax regret. First, the standard elicitation process in AI assumes users' preferences follow the axioms of Expected Utility Theory (EUT). However, there is strong evidence from psychology that people may systematically deviate from EUT. Cumulative prospect theory (CPT) is an alternative model to expected utility theory which has been shown empirically to better explain humans' decision-making in risky settings. We show that the standard elicitation process can be incompatible with CPT. We develop a new elicitation process that is compatible with both CPT and minimax regret. Second, since minimax regret focuses on the worst-case regret, minimax regret is often an overly cautious estimate of the actual regret. As a result, using minimax regret can often create an unnecessarily long elicitation process. We create a new measure of regret that can be a more accurate estimate of the actual regret. Our measurement of regret is especially well suited for eliciting preferences from multiple users. Finally, we examine issues of multiattribute preferences. Multiattribute preferences provide a natural way for people to reason about preferences. Unfortunately, in the worst-case, the complexity of a user's preferences grows exponentially with respect to the number of attributes. Several models have been proposed to help create compact representations of multiattribute preferences. We compare both the worst-case and average-case relative compactness.

Hochsch. für Wirtschafts-, Rechts- und Sozialwiss., Diss.--St. Gallen, 2007.

Pain has a significant burden on individuals and society; however challenges remain in the measurement of pain-related utility. Research was conducted to design a measurement framework for valuing pain states, for use in policy making. Within the theoretical framework of utility theory, the bio-psychosocial model of pain was used to select co-variates impacting the pain-utility relationship. The applicability of two utility theories (prospect theory and hedonist theory) to pain was evaluated, with EQ-5D-5L and utility values for scenarios of different pain intensities elicited using time-trade-off (TTO) and willingness-to-pay (WTP). Prospect theory was tested using the pain-utility relationship in 600 members of the general population (‘genpop’) by examining the presence of a reference point and the relationship between pain decreases/increases (gains/losses) and utility. Hedonist theory was tested through examination of predicted, experienced and remembered utilities, and ‘peak-end’ effects, principally using data from 56 university athletes experiencing training pain. Pain intensity had the greatest influence on EQ-5D values, with present and worst pain showing additive effects. Duration of the pain episode, general health, mood, age and gender also had significant impacts. In addition to pain intensity, TTO ‘genpop’ models included age, income, experienced pain and general health; WTP ‘genpop’ models included residual pain, age and income. The TTO and WTP models did not fit the athletes’ data well and alternative models were developed. The data did not confirm prospect theory: a reference point could not be identified (‘genpop’ and athletes) and the shape of the utility curve contradicted theory (athletes). Results for hedonist theory were inconclusive: predicted utility was consistently higher than experienced utility in athletes but the relationship depended on pain levels in ‘genpop’; remembered and experienced utility differed despite being consistent for pain levels; peak-end effects were not found. Further research in controlled environments is recommended for further theory testing.

abstract: This thesis presents a model for the buying behavior of consumers in a technology market. In this model, a potential consumer is not perfectly rational, but exhibits bounded rationality following the axioms of prospect theory: reference dependence, diminishing returns and loss sensitivity. To evaluate the products on different criteria, the analytic hierarchy process is used, which allows for relative comparisons. The analytic hierarchy process proposes that when making a choice between several alternatives, one should measure the products by comparing them relative to each other. This allows the user to put numbers to subjective criteria. Additionally, evidence suggests that a consumer will often consider not only their own evaluation of a product, but also the choices of other consumers. Thus, the model in this paper applies prospect theory to products with multiple attributes using word of mouth as a criteria in the evaluation. / Dissertation/Thesis / Masters Thesis Applied Mathematics 2014