Sozialunternehmen haben mindestens zwei Ziele: die Erfüllung ihrer sozialen bzw. ökologischen Mission und finanzielle Ziele. Zwischen diesen Zielen können Spannungen entstehen. Wenn sie sich in diesem Spannungsfeld wiederholt zugunsten der finanziellen Ziele entscheiden, kommt es zum Mission Drift. Die Priorisierung der finanziellen Ziele überlagert dabei die soziale Mission. Auch wenn das Phänomen in der Praxis mehrfach beobachtet und in Einzelfallanalysen beschrieben wurde, gibt es bislang wenig Forschung zu Mission Drift. Der Fokus der vorliegenden Arbeit liegt darauf, diese Forschungslücke zu schließen und eigene Erkenntnisse für die Auslöser und Treiber des Mission Drifts von Sozialunternehmen zu ermitteln. Ein Augenmerk liegt auf den verhaltensökonomischen Theorien und der Mixed-Gamble-Logik. Dieser Logik zufolge liegt bei Entscheidungen immer eine Gleichzeitigkeit von Gewinnen und Verlusten vor, sodass Entscheidungsträger die Furcht vor Verlusten gegenüber der Aussicht auf Gewinne abwägen müssen. Das Modell wird genutzt, um eine neue theoretische Betrachtungsweise auf die Abwägung zwischen sozialen und finanziellen Zielen bzw. Mission Drift zu erhalten. Mit einem Conjoint Experiment werden Daten über das Entscheidungsverhalten von Sozialunternehmern generiert. Im Zentrum steht die Abwägung zwischen sozialen und finanziellen Zielen in verschiedenen Szenarien (Krisen- und Wachstumssituationen). Mithilfe einer eigens erstellten Stichprobe von 1.222 Sozialunternehmen aus Deutschland, Österreich und der Schweiz wurden 187 Teilnehmende für die Studie gewonnen. Die Ergebnisse dieser Arbeit zeigen, dass eine Krisensituation Auslöser für Mission Drift von Sozialunternehmen sein kann, weil in diesem Szenario den finanziellen Zielen die größte Bedeutung zugemessen wird. Für eine Wachstumssituation konnten hingegen keine solche Belege gefunden werden. Hinzu kommen weitere Einflussfaktoren, welche die finanzielle Orientierung verstärken können, nämlich die Gründeridentitäten der Sozialunternehmer, eine hohe Innovativität der Unternehmen und bestimmte Stakeholder. Die Arbeit schließt mit einer ausführlichen Diskussion der Ergebnisse. Es werden Empfehlungen gegeben, wie Sozialunternehmen ihren Zielen bestmöglich treu bleiben können. Außerdem werden die Limitationen der Studie und Wege für zukünftige Forschung im Bereich Mission Drift aufgezeigt.

Information in der vorvertraglichen Phase – das heißt, Informationspflichten sowie Rechtsfolgen von Informationserteilung und -nichterteilung – in Bezug auf Kaufvertrag und Wahl des optionalen Instruments hat im Vorschlag der Europäischen Kommission für ein Gemeinsames Europäisches Kaufrecht (GEK; KOM(2011) 635) vielfältige Regelungen erfahren. Die vorliegende Arbeit betrachtet diese Regelungen auch in ihrem Verhältnis zu den Textstufen des Europäischen Privatrechts – Modellregeln und verbraucherschützende EU-Richtlinien – und misst sie an ökonomischen Rahmenbedingungen, die die Effizienz von Transaktionen gebieten und Grenzen des Nutzens von (Pflicht-)Informationen aufzeigen. Vom Grundsatz der Vertragsfreiheit ausgehend ist jeder Partei das Risiko zugewiesen, unzureichend informiert zu sein, während die Gegenseite nur punktuell zur Information verpflichtet ist. Zwischen Unternehmern bleibt es auch nach dem GEK hierbei, doch zwischen Unternehmer und Verbraucher wird dieses Verhältnis umgekehrt. Dort gelten, mit Differenzierung nach Vertragsschlusssituationen, umfassende Kataloge von Informationspflichten hinsichtlich des Kaufvertrags. Als Konzept ist dies grundsätzlich sinnvoll; die Pflichten dienen dem Verbraucherschutz, insbesondere der Informiertheit und Transparenz vor der Entscheidung über den Vertragsschluss. Teilweise gehen die Pflichten aber zu weit. Die Beeinträchtigung der Vertragsfreiheit des Unternehmers durch die Pflichten und die Folgen ihrer Verletzung lässt sich nicht vollständig mit dem Ziel des Verbraucherschutzes rechtfertigen. Durch das Übermaß an Information fördern die angeordneten Pflichten den Verbraucherschutz nur eingeschränkt; sie genügen nicht verhaltensökonomischen Maßstäben. Es empfiehlt sich daher, zwischen Unternehmern und Verbrauchern bestimmte verpflichtende Informationsinhalte ganz zu streichen, auf im konkreten Fall nicht erforderliche Information zu verzichten, erst nach Vertragsschluss relevante Informationen auf diese Zeit zu verschieben und die verbleibenden vorvertraglichen Pflichtinformationen in einer für den Verbraucher besser zu verarbeitenden Weise zu präsentieren. Von den einem Verbraucher zu erteilenden Informationen sollte stets verlangt werden, dass sie klar und verständlich sind; die Beweislast für ihre ordnungsgemäße Erteilung sollte generell dem Unternehmer obliegen. Neben die ausdrücklich angeordneten Informationspflichten treten ungeachtet der Verbraucher- oder Unternehmereigenschaft sowie der Käufer- oder Verkäuferrolle stark einzelfallabhängige Informationspflichten nach Treu und Glauben, die im Recht der Willensmängel niedergelegt sind. Hier ist der Grundsatz verwirklicht, dass mangelnde Information zunächst das eigene Risiko jeder Partei ist; berechtigtes Vertrauen und freie Willensbildung werden geschützt. Diese Pflichten berücksichtigen auch das Ziel der Effizienz und achten die Vertragsfreiheit. Das Vertrauen auf jegliche erteilten Informationen wird zudem dadurch geschützt, dass sie den Vertragsinhalt – allerdings in Verbraucherverträgen nicht umfassend genug – mitbestimmen können und dass ihre Unrichtigkeit sanktioniert wird. Die Verletzung jeglicher Arten von Informationspflichten kann insbesondere einen Schadensersatzanspruch sowie – über das Recht der Willensmängel – die Möglichkeit zur Lösung vom Vertrag nach sich ziehen. Das Zusammenspiel der unterschiedlichen Mechanismen führt allerdings zu Friktionen sowie zu Lücken in den Rechtsfolgen von Informationspflichtverletzungen. Daher empfiehlt sich die Schaffung eines Schadensersatzanspruchs für jede treuwidrig unterlassene Informationserteilung; hierdurch wird das Gebot von Treu und Glauben auch außerhalb des Rechts der Willensmängel zu einer eigentlichen einzelfallabhängigen Informationspflicht aufgewertet.

Data fusions are becoming increasingly relevant in official statistics. The aim of a data fusion is to combine two or more data sources using statistical methods in order to be able to analyse different characteristics that were not jointly observed in one data source. Record linkage of official data sources using unique identifiers is often not possible due to methodological and legal restrictions. Appropriate data fusion methods are therefore of central importance in order to use the diverse data sources of official statistics more effectively and to be able to jointly analyse different characteristics. However, the literature lacks comprehensive evaluations of which fusion approaches provide promising results for which data constellations. Therefore, the central aim of this thesis is to evaluate a concrete plethora of possible fusion algorithms, which includes classical imputation approaches as well as statistical and machine learning methods, in selected data constellations. To specify and identify these data contexts, data and imputation-related scenario types of a data fusion are introduced: Explicit scenarios, implicit scenarios and imputation scenarios. From these three scenario types, fusion scenarios that are particularly relevant for official statistics are selected as the basis for the simulations and evaluations. The explicit scenarios are the fulfilment or violation of the Conditional Independence Assumption (CIA) and varying sample sizes of the data to be matched. Both aspects are likely to have a direct, that is, explicit, effect on the performance of different fusion methods. The summed sample size of the data sources to be fused and the scale level of the variable to be imputed are considered as implicit scenarios. Both aspects suggest or exclude the applicability of certain fusion methods due to the nature of the data. The univariate or simultaneous, multivariate imputation solution and the imputation of artificially generated or previously observed values in the case of metric characteristics serve as imputation scenarios. With regard to the concrete plethora of possible fusion algorithms, three classical imputation approaches are considered: Distance Hot Deck (DHD), the Regression Model (RM) and Predictive Mean Matching (PMM). With Decision Trees (DT) and Random Forest (RF), two prominent tree-based methods from the field of statistical learning are discussed in the context of data fusion. However, such prediction methods aim to predict individual values as accurately as possible, which can clash with the primary objective of data fusion, namely the reproduction of joint distributions. In addition, DT and RF only comprise univariate imputation solutions and, in the case of metric variables, artificially generated values are imputed instead of real observed values. Therefore, Predictive Value Matching (PVM) is introduced as a new, statistical learning-based nearest neighbour method, which could overcome the distributional disadvantages of DT and RF, offers a univariate and multivariate imputation solution and, in addition, imputes real and previously observed values for metric characteristics. All prediction methods can form the basis of the new PVM approach. In this thesis, PVM based on Decision Trees (PVM-DT) and Random Forest (PVM-RF) is considered. The underlying fusion methods are investigated in comprehensive simulations and evaluations. The evaluation of the various data fusion techniques focusses on the selected fusion scenarios. The basis for this is formed by two concrete and current use cases of data fusion in official statistics, the fusion of EU-SILC and the Household Budget Survey on the one hand and of the Tax Statistics and the Microcensus on the other. Both use cases show significant differences with regard to different fusion scenarios and thus serve the purpose of covering a variety of data constellations. Simulation designs are developed from both use cases, whereby the explicit scenarios in particular are incorporated into the simulations. The results show that PVM-RF in particular is a promising and universal fusion approach under compliance with the CIA. This is because PVM-RF provides satisfactory results for both categorical and metric variables to be imputed and also offers a univariate and multivariate imputation solution, regardless of the scale level. PMM also represents an adequate fusion method, but only in relation to metric characteristics. The results also imply that the application of statistical learning methods is both an opportunity and a risk. In the case of CIA violation, potential correlation-related exaggeration effects of DT and RF, and in some cases also of RM, can be useful. In contrast, the other methods induce poor results if the CIA is violated. However, if the CIA is fulfilled, there is a risk that the prediction methods RM, DT and RF will overestimate correlations. The size ratios of the studies to be fused in turn have a rather minor influence on the performance of fusion methods. This is an important indication that the larger dataset does not necessarily have to serve as a donor study, as was previously the case. The results of the simulations and evaluations provide concrete implications as to which data fusion methods should be used and considered under the selected data and imputation constellations. Science in general and official statistics in particular benefit from these implications. This is because they provide important indications for future data fusion projects in order to assess which specific data fusion method could provide adequate results along the data constellations analysed in this thesis. Furthermore, with PVM this thesis offers a promising methodological innovation for future data fusions and for imputation problems in general.

This thesis contains four parts that are all connected by their contributions to the Efficient Market Hypothesis and decision-making literature. Chapter two investigates how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020. The results show that lockdown restrictions led to different reactions in a sample of OECD and BRICS countries: there was a general negative effect resulting from the increase in lockdown restrictions, but the study finds strong evidence for underreaction during the lockdown announcement, followed by some overreaction that is corrected subsequently. This under-/overreaction pattern, however, is observed mostly during the first half of our time series, pointing to learning effects. Relaxation of the lockdown restrictions, on the other hand, had a positive effect on markets only during the second half of our sample, while for the first half of the sample, the effect was negative. The third chapter investigates the gender differences in stock selection preferences on the Taiwan Stock Exchange. By utilizing trading data from the Taiwan Stock Exchange over a span of six years, it becomes possible to analyze trading behavior while minimizing the self-selection bias that is typically present in brokerage data. To study gender differences, this study uses firm-level data. The percentage of male traders in a company is the dependent variable, while the company’s industry and fundamental/technical aspects serve as independent variables. The results show that the percentage of women trading a company rises with a company’s age, market capitalization, a company’s systematic risk, and return. Men trade more frequently and show a preference for dividend-paying stocks and for industries with which they are more familiar. The fourth chapter investigated the relationship between regret and malicious and benign envy. The relationship is analyzed in two different studies. In experiment 1, subjects had to fill out psychological scales that measured regret, the two types of envy, core self-evaluation and the big 5 personality traits. In experiment 2, felt regret is measured in a hypothetical scenario, and the subject’s felt regret was regressed on the other variables mentioned above. The two experiments revealed that there is a positive direct relationship between regret and benign envy. The relationship between regret and malicious envy, on the other hand, is mostly an artifact of core self-evaluation and personality influencing both malicious envy and regret. The relationship can be explained by the common action tendency of self-improvement for regret and benign envy. Chapter five discusses the differences in green finance regulation and implementation between the EU and China. China introduced the Green Silk Road, while the EU adopted the Green Deal and started working with its own green taxonomy. The first difference comes from the definition of green finance, particularly with regard to coal-fired power plants. Especially the responsibility of nation-states’ emissions abroad. China is promoting fossil fuel projects abroad through its Belt and Road Initiative, but the EU’s Green Deal does not permit such actions. Furthermore, there are policies in both the EU and China that create contradictory incentives for economic actors. On the one hand, the EU and China are improving the framework conditions for green financing while, on the other hand, still allowing the promotion of conventional fuels. The role of central banks is also different between the EU and China. China’s central bank is actively working towards aligning the financial sector with green finance. A possible new role of the EU central bank or the priority financing of green sectors through political decision-making is still being debated.

Left ventricular assist devices (LVADs) have become a valuable treatment for patients with advanced heart failure. Women appear to be disadvantaged in the usage of LVADs and concerning clinical outcomes such as death and adverse events after LVAD implant. Contrary to typical clinical characteristics (e.g., disease severity), device-related factors such as the intended device strategy, bridge to a heart transplantation or destination therapy, are often not considered in research on gender differences. In addition, the relevance of pre-implant psychosocial risk factors, such as substance abuse and limited social support, for LVAD outcomes is currently unclear. Thus, the aim of this dissertation is to explore the role of pre-implant psychosocial risk factors for gender differences in clinical outcomes, accounting for clinical and device-related risk factors. In the first article, gender differences in pre-implant characteristics of patients registered in The European Registry for Patients with Mechanical Circulatory Support (EUROMACS) were investigated. It was found that women and men differed in multiple pre-implant characteristics depending on device strategy. In the second article, gender differences in major clinical outcomes (i.e., death, heart transplant, device explant due to cardiac recovery, device replacement due to complications) were evaluated for patients in the device strategy destination therapy in the Interagency Registry for Mechanically Assisted Circulation (INTERMACS). Additionally, the association of gender and psychosocial risk factors with the major outcomes were analyzed. Women had similar probabilities to die on LVAD support, and even higher probabilities to experience explant of the device due to cardiac recovery compared with men in the destination therapy subgroup. Pre-implant psychosocial risk factors were not associated with major outcomes. The third article focused on gender differences in 10 adverse events (e.g., device malfunction, bleeding) after LVAD implant in INTERMACS. The association of a psychosocial risk indicator with gender and adverse events after LVAD implantation was evaluated. Women were less likely to have psychosocial risk pre-implant but more likely to experience seven out of 10 adverse events compared with men. Pre-implant psychosocial risk was associated with adverse events, even suggesting a dose response-relationship. These associations appeared to be more pronounced in women. In conclusion, women appear to have similar survival to men when accounting for device strategy. They have higher probabilities of recovery, but higher probabilities of device replacement and adverse events compared with men. Regarding these adverse events, women may be more susceptible to psychosocial risk factors than men. The results of this dissertation illustrate the importance of gender-sensitive research and suggest considering device strategy when studying gender differences in LVAD recipients. Further research is warranted to elucidate the role of specific psychosocial risk factors that lead to higher probabilities of adverse events, to intervene early and improve patient care in both, women and men