O arrependimento é uma emoção negativa comum no cotidiano do ser humano. A busca pela redução desse sentimento foi objeto de diversos estudos da área comportamental. Uma situação em que o consumidor escolheu um prestador de serviço e não obteve o resultado desejado, devido a falhas ocorridas, gera arrependimento tanto para satisficers como para maximizadores. Para que haja redução nesse arrependimento, as empresas podem oferecer uma compensação financeira. Nesse viés, a presente pesquisa analisa como a interação entre a tendência à maximização do consumidor – a qual consiste na sua disposição em obter o melhor resultado possível e não apenas um resultado suficientemente bom – e a compensação financeira oferecida pela empresa devido a uma falha na prestação de serviço impacta no arrependimento do consumidor com a decisão tomada. Através de sete experimentos, é demonstrado que: 1) em casos de compensação parcial (i.e., 50% de desconto), satisficers indicam redução no seu nível de arrependimento em comparação a situações em que não há compensação. No entanto, os satisficers possuem níveis semelhantes de arrependimento ao receberem compensação parcial ou total (i.e., 100% de desconto). Já para maximizadores, uma compensação parcial gera redução no arrependimento, se comparada à situação sem compensação; entretanto, um nível ainda menor de arrependimento é percebido após compensação total. Percebe-se que, para maximizadores, ao aumentar a compensação, há redução no nível de arrependimento, enquanto que para satisficers uma compensação parcial já é suficiente para reduzir essa emoção. 2) O impacto da tendência à maximização e da compensação no arrependimento gera consequências na intenção de recompra, boca a boca online positivo e confiança do consumidor. Assim, quanto menor o nível de arrependimento, maior a intenção de recompra, boca a boca online positivo e confiança do consumidor no prestador de serviço. Dessa forma, ao gerenciar eventuais falhas em situação de consumo, uma empresa é capaz de gerar impacto positivo tanto para o consumidor (através da redução de sua emoção negativa), quanto para a própria empresa (por meio de variáveis comportamentais e confiança na organização). 3) Os resultados são consistentes entre as duas formas de abordagem da tendência à maximização utilizadas; isto é, estado mental gerado por fatores situacionais e traço individual – medido pelas escalas de Diab et al. (2008) e Schwartz et al. (2002). Além disso, foram utilizados dois contextos de serviços: restaurante e turismo. Esta pesquisa destaca-se, também, pela investigação do arrependimento em uma situação de recuperação de prestação de serviço. Embora o arrependimento seja uma emoção vastamente estudada, devido ao seu significativo impacto e intensidade na vida das pessoas, estudos visando a reduzir essa emoção em situação de falhas são insuficientes. Logo, esta é uma das contribuições da pesquisa realizada. / Regret is a common negative emotion in everyday life. Past studies have focused on how to reduce this negative emotion. For instance, situations in which the consumer has chosen a service provider and, due to its failures, did not get the desired outcome, generate regret for both satisficers and maximizers. In order to reduce regret, companies may offer financial compensations to their customers. This study focuses on the impact of the interaction between the consumer’s maximizing tendency (which consists in the willingness to be a satisficer or a maximizer while decision making) and the financial compensation offered by the company (due to a failure in service delivery) on consumer’s regret. Results of the seven experiments conducted demonstrate that: 1) in situations where there is partial compensation (i.e., 50% discount), satisficers indicate reduction in their level of regret when compared to a situation where there is no compensation (i.e., 0% discount). However, satisficers have similar levels of regret when they receive either partial or total compensation (i.e., 100% discount). To maximizers, on the other hand, even though a partial compensation generates a reduction in regret if compared to a situation without any compensation, a far lower level of regret is perceived when a total compensation (i.e., 100% compensation) is offered. It may be realized that, for maximizers, regret is reduced by increasing the compensation, whereas for satisficers a partial compensation is enough to reduce this negative emotion. 2) The impact of the maximizing tendency and compensation on regret generates consequences on repurchase intention, online word of mouth and trust. As the level of regret decreases, repurchase intention, online word of mouth and consumer’s trust in the service provider increase. Thus, when managing failures in a situation of consumption, companies may generate a positive impact both for the consumer (by reducing their negative emotion) and to the company (regarding behavioral variables and trust in the organization). 3) These results are consistent between both approaches of maximizing tendencies used; which is to say, state of mind generated by situational factors and individual traits – measured by the scales of Diab et al. (2008) and Schwartz et al. (2002). Besides that, the research used two different service providers: restaurant and tourism agency. This study differentiates from others by studying regret in a situation of recovering from service failure. Although regret is a vastly studied emotion, due to its significant impact and intensity in people’s lives, studies that aim at analyzing this emotion in a negative failure situation are insufficient, which makes this one of the contributions of this research.

Two-player zero-sum games of infinite duration and their quantitative versions are used in verification to model the interaction between a controller (Eve) and its environment (Adam). The question usually addressed is that of the existence (and computability) of a strategy for Eve that can maximize her payoff against any strategy of Adam: a winning strategy. It is often assumed that Eve always knows the exact state of the game, that is, she has full observation. In this dissertation, we are interested in two variations of quantitative games. First, we study a different kind of strategy for Eve. More specifically, we consider strategies that minimize her regret: the difference between her actual payoff and the payoff she could have achieved if she had known the strategy of Adam in advance. Second, we study the effect of relaxing the full observation assumption on the complexity of computing winning strategies for Eve. Regarding regret-minimizing strategies, we give algorithms to compute the strategies of Eve that ensure minimal regret against three classes of adversaries: (i) unrestricted, (ii) limited to positional strategies, or (iii) limited to word strategies. These results apply for quantitative games defined with the classical payoff functions Inf, Sup, LimInf, LimSup, mean payoff, and discounted sum. For partial-observation games, we continue the study of energy and mean- payoff games started in 2010 by Degorre et al. We complement their decidability result for a particular problem related to energy games (the Fixed Initial Credit Problem) by giving tight complexity bounds for it. Also, we show that mean-payoff games are undecidable for all versions of the mean-payoff function. Motivated by the latter negative result, we define and study several decidable sub-classes of mean-payoff games. Finally we extend the newly introduced window mean-payoff objectives to the partial observation setting. We show that they are conservative approximations of partial-observation mean-payoff games and we classify them according to whether they are decidable. Furthermore, we give a symbolic algorithm to solve them. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

This thesis investigates sequential decision making tasks that fall in the framework of reinforcement learning (RL). These tasks involve a decision maker repeatedly interacting with an environment modeled by an unknown finite Markov decision process (MDP), who wishes to maximize a notion of reward accumulated during her experience. Her performance can be measured through the notion of regret, which compares her accumulated expected reward against that achieved by an oracle algorithm always following an optimal behavior. In order to maximize her accumulated reward, or equivalently to minimize the regret, she needs to face a trade-off between exploration and exploitation. The first part of this thesis investigates combinatorial multi-armed bandit (MAB) problems, which are RL problems whose state-space is a singleton. It also addresses some applications that can be cast as combinatorial MAB problems. The number of arms in such problems generically grows exponentially with the number of basic actions, but the rewards of various arms are correlated. Hence, the challenge in such problems is to exploit the underlying combinatorial structure.For these problems, we derive asymptotic (i.e., when the time horizon grows large) lower bounds on the regret of any admissible algorithm and investigate how these bounds scale with the dimension of the underlying combinatorial structure. We then propose several algorithms and provide finite-time analyses of their regret. The proposed algorithms efficiently exploit the structure of the problem, provide better performance guarantees than existing algorithms, and significantly outperform these algorithms in practice. The second part of the thesis concerns RL in an unknown and discrete MDP under the average-reward criterion. We develop some variations of the transportation lemma that could serve as novel tools for the regret analysis of RL algorithms. Revisiting existing regret lower bounds allows us to derive alternative bounds, which motivate that the local variance of the bias function of the MDP, i.e., the variance with respect to next-state transition laws, could serve as a notion of problem complexity for regret minimization in RL. Leveraging these tools also allows us to report a novel regret analysis of the KL-UCRL algorithm for ergodic MDPs. The leading term in our regret bound depends on the local variance of the bias function, thus coinciding with observations obtained from our presented lower bounds. Numerical evaluations in some benchmark MDPs indicate that the leading term of the derived bound can provide an order of magnitude improvement over previously known results for this algorithm. / <p>QC 20171215</p>

Huss M. Is a woman aloud to regret her motherhood?. A qualitative study about social workers perception of women who regret having children. Degree project in social work 15 credits. Malmö University: Faculty of Health and Society, Department of Social Work, 2018.A common opinion is that having children is a choice you can’t regret. But what happens when women deviate from this norm and regret that they were having children? The purpose of this study was to investigate how social workers perceive women who regret that they were having children and how this perception affects their social work. The empirical material was collected by semi-structured interview questions in combination with the vignette method. Six social workers, which are working with children and families, were interviewed and then the material was processed by using coding and categorization. Eight categories were identified and analysed from a norm critical perspective, a psychological cultural perspective and Goffman’s theory about stigma. The study result showed that the social workers tended to explain the women’s feelings of regret as caused by reasons like postpartum depression, mental illness and attachment problems. The study results also showed that norms about motherhood influenced how the social workers viewed the topic. This was expressed in the discussions about how the children could be affected by the mothers’ feelings of regret. The discussions also gave an indication that the social workers had a different way of reasoning, depending on the gender of the parent who was feeling regret in these situations.Keywords: Motherhood, norms, regret, stigma, social work.

京都大学 / 0048 / 新制・課程博士 / 博士(人間・環境学) / 甲第22535号 / 人博第938号 / 新制||人||223(附属図書館) / 2019||人博||938(吉田南総合図書館) / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)准教授 櫻川 貴司, 教授 立木 秀樹, 教授 日置 尋久 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DGAM

In the master thesis, we present theoretically-critical analysis of current academic knowledge about the paradox of choice and related selected personality characteristics. In the theoretical part, we examine the topic of desition-making. First part defines concept of the paradox of choice. The next part also includes previous research related to paradox of choice and related factors. In addition, we examine the phenomenon of post-decision regret in the context of the paradox of choice. In final section we elaborate relevant personality characteristics. The empirical part investigates the effect of paradox of choice, its relation to personality characteristics and post-decision regret. The research includes experiment, which is extended with personality questionnaire measuring maximization tendency, decisiveness and optimism. Those traits are measured by using Maximization scale Lai (2010), Life Orientation Test- Revised (LOT-R) and Bochum Personality Questionnaire (BIP). In the discussion, we further explore features of maximization tendency. Results does not show presence of the paradox of choice. Nevertheless participants from group with the most choices showed significantly more satisfaction with choice compared to participants from group with least choices which suggests opposite effect. In...

Thesis advisor: Uzi Segal / The dissertation studies the property of transitivity in the social choice theory. I explain why we should care about transitivity in decision theory. I propose two social decision theories: redistribution regret and ranking regret, study their properties of transitivity, and discuss the possibility to find a best choice for the social planner. Additionally, in the joint work, we propose a general method to construct a consistent estimator given two parametric models, one of which could be incorrectly specified. In “Why Transitivity”, to explain behaviors violating transitivity, e.g., preference reversals, some models, like regret theory, salience theory were developed. However, these models naturally violate transitivity, which may not lead to a best choice for the decision maker. This paper discusses the consequences and the possible extensions to deal with it. In “Redistribution Regret and Transitivity”, a social planner wants to allocate resources, e.g., the government allocates fiscal revenue or parents distribute toys to children. The social planner cares about individuals' feelings, which depend both on their assigned resources, and on the alternatives they might have been assigned. As a result, there could be intransitive cycles. This paper shows that the preference orders are generally non-transitive but there are two exceptions: fixed total resource and one extremely sensitive individual, or only two individuals with the same non-linear individual regret function. In “Ranking Regret”, a social planner wants to rank people, e.g., assign airline passengers a boarding order. A natural ranking is to order people from most to least sensitive to their rank. But people's feelings can depend both on their assigned rank, and on the alternatives they might have been assigned. As a result, there may be no best ranking, due to intransitive cycles. This paper shows how to tell when a best ranking exists, and that when it exists, it is indeed the natural ranking. When this best does not exist, an alternative second-best group ranking strategy is proposed, which resembles actual airline boarding policies. In “Over-Identified Doubly Robust Identification and Estimation”, joint with Arthur Lewbel and Jinyoung Choi, we consider two parametric models. At least one is correctly specified, but we don't know which. Both models include a common vector of parameters. An estimator for this common parameter vector is called Doubly Robust (DR) if it's consistent no matter which model is correct. We provide a general technique for constructing DR estimators (assuming the models are over identified). Our Over-identified Doubly Robust (ODR) technique is a simple extension of the Generalized Method of Moments. We illustrate our ODR with a variety of models. Our empirical application is instrumental variables estimation, where either one of two instrument vectors might be invalid. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

The aim of this dissertation is to study two problems of distributed nearest neighbor classification (DiNN) systematically. The first one compares two DiNN classifiers based on different schemes: majority voting and weighted voting. The second one is an extension of the DiNN method to the crowdsourcing application, which allows each worker data has a different size and noisy labels due to low worker quality. Both statistical guarantees and numerical comparisons are studied in depth.<br><div><br></div><div><div>The first part of the dissertation focuses on the distributed nearest neighbor classification in big data. The sheer volume and spatial/temporal disparity of big data may prohibit centrally processing and storing the data. This has imposed a considerable hurdle for nearest neighbor predictions since the entire training data must be memorized. One effective way to overcome this issue is the distributed learning framework. Through majority voting, the distributed nearest neighbor classifier achieves the same rate of convergence as its oracle version in terms of the regret, up to a multiplicative constant that depends solely on the data dimension. The multiplicative difference can be eliminated by replacing majority voting with the weighted voting scheme. In addition, we provide sharp theoretical upper bounds of the number of subsamples in order for the distributed nearest neighbor classifier to reach the optimal convergence rate. It is interesting to note that the weighted voting scheme allows a larger number of subsamples than the majority voting one.</div></div><div><br></div><div>The second part of the dissertation extends the DiNN methods to the application in crowdsourcing. The noisy labels in crowdsourcing data and different sizes of worker data will deteriorate the performance of DiNN methods. We propose an enhanced nearest neighbor classifier (ENN) to overcome this issue. Our proposed method achieves the same regret as its oracle version on the expert data with the same size. We also propose two algorithms to estimate the worker quality if it is unknown in practice. One method constructs the estimators for worker quality based on the denoised worker labels through applying kNN classifier on expert data. Unlike previous worker quality estimation methods, which have no statistical guarantee, it achieves the same regret as the ENN with observed worker quality. The other method estimates the worker quality iteratively based on ENN, and it works well without expert data required by most previous methods.<br></div>

Denna uppsats syftar till att utforska hur mödrar som upplever ånger och tvivel i samband med att vara mamma blir bemötta. Hittills har undersökningar relaterade till ämnet främst analyserat olika chattrådar, men ingen från en svensk kontext. Av den anledningen studerar denna uppsats via en kritisk diskursanalys en chattråd på det svenska forumet Familjeliv. Vad som undersöks är vilka moderskapsdiskurser som framträder i chattinläggen och varför mammor upplever ånger och tvivel kopplat till modersrollen. Det teoretiska ramverket består av Berger och Luckmanns teori om institutioner, Hochschilds begrepp känsloregler, emotionellt arbete samt yt- och djupagerande, Goffmans term fasad och Butlers tolkning av termen genus. Resultatet visar på tre diskurser i datamaterialet; moderskapet som lyckligt, en fälla och inställningen till moderskapet. Ånger och tvivel uttrycks i förhållande till modersrollen när modern inte kan leva upp till diskursen om moderskapet som lyckligt. Då kan mamman känna sig inlurad i modersrollen, eftersom hennes förväntningar om moderskapet inte motsvarade den faktiska modersrollen. Av det skälet kan mamman börja uppleva moderskapet som en fälla. Om modern inte vill eller vet hur hon ska använda emotionellt arbete för att få “rätt” inställning till moderskapet kan hon även börja utveckla känslor av ånger och tvivel i relation till modersrollen. Vad som ligger till grund för förväntningarna om moderskapet är institutionen om familjen. Avslutningsvis har uppsatsarbetet enbart börjat fylla en kunskapslucka och därför kan inga absoluta svar presenteras till frågeställningarna. / This essay aims to explore how mothers who experience regret and doubt in connection with being a mother are treated. So far, studies related to the subject have mainly analysed chat threads, but none from a Swedish context. For this reason, this essay studies a chat thread on the Swedish forum Familjeliv using a critical discourse analysis. We investigate which motherhood discourses appear in the chat posts and why mothers experience regret and doubt linked to their role as a mother. The theoretical framework consists of Berger and Luckmann's theory of institutions, Hochschild's concepts of feeling rules, emotional work and surface and deep acting, Goffman's term facade, and Butler's interpretation of the term gender. The result shows three discourses in the data material; motherhood as joyful, a trap and the attitude towards motherhood. Regret and doubt are expressed in relation to the role as a mother when the mother cannot live up to the discourse of motherhood as joyful. Then the mother may feel tricked into her role as a mother, because her expectations of motherhood did not correspond to the actual role of being a mother. For that reason, the mother may begin to experience motherhood as a trap. If the mother does not want to, or know how to use emotional work, to get the "right" attitude towards motherhood, she can also begin to develop feelings of regret and doubt in relation to her role as a mother. The basis for the expectations about motherhood is the institution of the family. In conclusion, this essay has only begun to fill a knowledge gap and therefore no absolute answers can be given to the questions.

This paper examines the production and hedging decisions of the competitive firm under price uncertainty when the firm is not only risk averse but also regret averse. Regret-averse preferences are characterized by a modified utility function that includes disutility from having chosen ex-post suboptimal alternatives. The extent of regret depends on the difference between the actual profit and the maximum profit attained by making the optimal production and hedging decisions had the firm observed the true realization of the random output price. While the separation theorem holds under regret aversion, the prevalence of hedging opportunities may have perverse effect on the firm's optimal output level, particularly when the firm is sufficiently regret averse. The full-hedging theorem, however, does not hold. We derive sufficient conditions under which the regret-averse firm's optimal futures position is an under-hedge (over-hedge). We further show that the firm optimally increases (decreases) its futures position when the price risk possesses more positive (negative) skewness.