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The thesis comprises three essays on the reasons for and consequences of poorly-informed decision-making. Chapter 1 investigates active avoidance of information as a source of uninformed decision-making. Next to providing input for subsequent decisions information may trigger undesirable emotional responses. An optimal decision on information acquisition then weighs benefits from better decision-making against the costs of an inferior emotional well-being. The model is applied to the context of medical testing. The availability of effective cure and the timing of testing are predicted to be significant determinants of test uptake. This is in line with empirical evidence on barriers to testing. Chapter 2 proposes a model of limited attention. Given limited cognitive capabilities a decision-maker may simply be unable to make a fully-informed decision. Thus, the resulting decision neglects some of the available information. The model is applied to investigate the question of optimal product design when customers have limited attention. It is shown that a firm can increase its profit by introducing goods that have the sole function of manipulating consumer attention. In addition, the chapter discusses how a firm can profitably employ such manipulating goods. Chapter 3 presents an analysis of how customers with limited attention value and choose among health plans. It shows how the model can accommodate four observations regarding plan choice.First, people tend to overweight the premium and thus underappreciate the value of health insurance. Second, insurance companies have a strong incentive to reduce quality and to hide the shortcomings in the fine print while attracting customers with insufficiently lower premiums. Third, customers may choose dominated alternatives. Finally, the willingness-to-pay for insurance is subadditive creating an incentive for providers to unbundle comprehensive plans. It is discussed how these effects may result in a fundamental dilemma for policy makers.

The purpose of the current study is to explore barriers influencing consumers' intention to adopt sustainable electric vehicles (EV) based on the modified theory of planned behavior (TPB) model. Structural equation modeling (SEM) and confirmatory factor analysis (CFA) were employed to analyze the research model, using 262 valid responses. The findings of the current study explored how attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC) significantly influenced users' sustainable consumption intentions. The finding also explored ways in which environmental concern significantly influenced ATT, SN, PBC, and sustainable consumption intention of the users. Not only measurements of vehicle performance, namely safety, reliability, and range, but other factors, such as purchasing price, charging facility, and maintenance and battery cost also influenced consumers' sustainable consumption intentions. The predictive power of the proposed model (R2 = 63.5) was better than the original TPB (R2 = 53.6). Results also indicated that Taiwanese are primarily concerned about the greenhouse effects on the environment, which reflected their sustainable consumption intentions. The conclusions of the current study could assist government and policymakers in designing sustainable programs, which could improve consumers' sustainable consumption intentions to prevent further air pollution and reduce CO2 emissions from the transportation sector.

Protecting the climate is one of the greatest challenges our society is currently facing. In view of the heated political and social discussions surrounding this topic, the question naturally arises as to whether behavioral-economic insights can be used to sensitize German society to the dangers of climate change and to motivate it towards more sustainability. The field of behavioral economics provides empirical evidence of psychological factors that influence and even hinder sustainable behavior, ultimately leading to a gap between the will to act sustainably and actual behavior. Cognitive barriers, different social factors and group affiliations result in a complex system of diverse behavioral patterns, environmental attitudes, needs and expectations that must be considered when designing environmental policy instruments. People can be motivated to behave more ecologically without restricting their freedom of choice by the intelligent and effective use of green nudges rather than prohibitions. Identifying an effective, target-group-specific and ethical policy for counteracting climate change and encouraging more sustainable behavior requires an interdisciplinary approach combining behavioral-economic empiricism with ethical insights. ; Der Klimawandel zählt zu den größten Herausforderungen unserer Zeit. Angesichts der kontroversen politischen und gesellschaftlichen Diskussionen rund um Verbote oder höhere Umweltsteuern für mehr Klimaschutz stellt sich die Frage, inwiefern verhaltensökonomische Erkenntnisse genutzt werden können, um das Klima mit weniger drastischen Eingriffen in die Freiheit und die finanziellen Ressourcen der Menschen zu schützen. Die Verhaltensökonomik liefert empirische Belege für eine Vielzahl an psychologische Faktoren (Heuristiken und Biases), die (nachhaltiges) Verhalten beeinflussen. Moderne verhaltensökonomische Anreizsysteme nutzen diese Erkenntnisse rund um den Einfluss von Einstellungen, Bedürfnissen und Erwartungen sowie die soziologischen Milieuzugehörigkeiten bei der Gestaltung von umweltpolitischen Instrumenten. Mithilfe von intelligenten und effektiven Green Nudges kann durch zielgruppenspezifische und moralisch vertretbare Maßnahmen Nachhaltigkeit bei Verbrauchern effektiv und effizient erreicht werden: DefaultEinstellungen, soziale Vergleiche, Feedback-Prozesse oder Vereinfachungen richten sich differenziert an verschiedene Milieus, um den größtmöglichen Effekt zu erreichen.

Odors emitted by mammalian mothers have an important influence on the behavioral and physical development of newborn offspring. Adaptive responses by nurslings to maternal odors include arousal reduction, directional movement to the odor source, localization of the nipple and initiation of effective sucking. The manner in which young animals respond to specific odors often reflects prior experience with those cues. Newborn rodents rapidly become familiar with odors associated with their mother. Olfactory learning may actually begin before birth through fetal contact with aromatic substances in the amniotic fluid. Investigations of mother-infant olfactory communication in our own species have been modeled closely after earlier relevant findings from research with non-human mammals.

Topic models are a popular tool to extract concepts of large text corpora. These text corpora tend to contain hidden meta groups. The size relation of these groups is frequently imbalanced. Their presence is often ignored when applying a topic model. Therefore, this thesis explores the influence of such imbalanced corpora on topic models. The influence is tested by training LDA on samples with varying size relations. The samples are generated from data sets containing a large group differences i.e language difference and small group differences i.e. political orientation. The predictive performance on those imbalanced corpora is judged using perplexity. The experiments show that the presence of groups in training corpora can influence the prediction performance of LDA. The impact varies due to various factors, including language-specific perplexity scores. The group-related prediction performance changes for groups when varying the relative group sizes. The actual change varies between data sets. LDA is able to distinguish between different latent groups in document corpora if differences between groups are large enough, e.g. for groups with different languages. The proportion of group-specific topics is under-proportional to the share of the group in the corpus and relatively smaller for minorities. ; Topic Models sind ein beliebtes Werkzeug um Themen in großen Textkorpora zu identifizieren. Diese Textkorpora enthalten oft versteckte Meta-Gruppen. Das Größenverhältnis zwischen diesen Gruppen variiert meist stark. Die Präsenz dieser Gruppen wird in der Praxis oft ignoriert. Diese Masterarbeit erforscht daher, ob diese Gruppen Einfluss auf ein Topic Model haben. Um den Einfluss zu testen, wird LDA auf Samples mit unterschiedlichen Gruppengrößen trainiert. Die Samples werden von Textkorpora mit großen Gruppenunterschieden (d.h. Sprachunterschieden) und kleinen Gruppenunterschieden (d.h. Unterschiede in der politische Orientierung) generiert. Die Leistungsfähigkeit von LDA wird per "Perplexity" evaluiert. Der Einfluss von Gruppen auf die generelle Leistungsfähigkeit von Topic Models hängt von verschiedenen Faktoren der Gruppen ab, z.B. der Vorhersagbarkeit der Sprache generell. Die Leistungsfähigkeit der Topic Models für die einzelnen Gruppen wird von der Variation der relativen Gruppengrößen beeinflusst. Allerdings ist der Effekt für alle Datensätze verschieden. LDA kann die Gruppen intern unterscheiden, wenn die Unterschiede der Gruppen groß genug sind (z.B. Sprachunterschiede). Der Anteil der Topics, die explizit für eine Gruppe gelernt werden, ist jedoch unterproportional zu dem Anteil der Gruppe im Trainingskorpus. Dieser Effekt verstärkt sich für kleinere Minderheiten.

In this article, the authors develop a model that details how individuals come to prefer one candidate over others during the presidential nomination campaign. The model places the forces that influence nomination preferences into a simultaneous and dynamic framework. Empirical tests using the 1980 NES panel data indicate that the model performs well.

Administrative reforms encode a set of behavioral expectations for bureaucrats to follow. The authors argue that scholars can usefully contribute to understanding accountability by studying whether bureaucrats follow these expectations and what factors encourage such responsiveness to reform values. To demonstrate this approach, the authors examine performance infor‐mation use as a behavioral measure of responsiveness to results‐based reforms. Using a sample of Texas school superintendents, they find that general openness to the environment goes hand in hand with responsiveness to reform values. The authors propose that such a pattern will hold when reform values align with environmental preferences. The perceived influence of stakeholders, networking with stakeholders, and reliance on partnerships all positively predict performance information use. Environments marked by student diversity and stakeholder conflict also correlate with higher use of performance data, while capacity, less managerial experience, and a unified organizational culture correlate positively with higher reported performance information use.

AbstractInterventions that change the food environment, provide nutrition education, and employ behavioral economics strategies can potentially contribute to healthier diets and reduce the risk of chronic disease, but no attempt has been made to integrate these into the same conceptual framework. We present case studies of three multilevel, integrated interventions implemented by Johns Hopkins University between 2004–2011. We develop a conceptual model based on these case studies. Interventions and policies should effectively maximize opportunities to nudge healthier behaviors. We believe that the integration of educational, environmental, and behavioral economic strategies will balance the strengths and limitations of each approach.

Explores possibilities for simulating the effects of continuous disruptions to an economy using a multi‐sector social accounting model. The underlying thesis for the model is that disruptions (due to events ranging from potholes to earthquakes) are a constant and unavoidable aspect of development and that all institutions and production activities are structured and adapt over time so as to balance performance and protection. The first sections explain the role of input‐output tables, especially social accounts, as the basic framework for evaluating systemic vulnerability to disaster. The next sections explain the underlying behavioral components of the model: how the profile of protection versus disruption and costs of protection are determined, and how adaptation of the protection profile to changing events and societal discounting affects protection. In the final sections, these elements are integrated into a multi‐sector social accounting model of the Niagara Frontier region of New York State – affected by industrial decline and currency fluctuations is dependent on a major hydro‐electric power facility that is considered vulnerable to a variety of unscheduled events. Results focus on how disruptions and responses to them propagate over time and between actors.

This research work investigates the influence of the use of Ball-and-Stick Models in teaching nomenclature to SS 3 chemistry students in Sabon Gari Local Government Area of Kaduna State. In this study, a Quasi-experimental research design was used with a nomenclature achievement test (NAT) as data collection instrument with two hundred and eighty five (285) respondents from six selected secondary schools with a total population of one thousand and ninety six (1096) students from Sabon Gari Local Government Area of Kaduna state chosen as sample using Sample Size Calculator with 5% confidence interval which is a public service of Creative Research Systems survey software. The analytical tools used for data analysis was the statistical package for social sciences (SPSS, Version 22). The result obtained shows that there is a significant difference between the performance of students taught naming organic compounds using ball-and-stick and that those taught with the chart, There is a significant difference in the performance of students taught naming organic compounds using ball-and-stick in respect to gender since the P value is of the alpha level of significance ≤0.05. The significant improvement in students' understanding can be attributed to their increased exposure to virtual and physical models and the active learning these students were engaged in. It is recommended that the government should inculcate incorporating a combination of virtual and physical models in chemistry teaching/learning as a means to foster meaningful learning and spatial understanding of molecular structure.