This thesis consists of four highly related chapters examining China’s rise in the aluminium industry. The first chapter addresses the conditions that allowed China, which first entered the market in the 1950s, to rise to world leadership in aluminium production. Although China was a latecomer, its re-entry into the market after the oil crises in the 1970s was a success and led to its ascent as the world’s largest aluminium producer by 2001. With an estimated production of 40.4 million tonnes in 2022, China represented almost 60% of the global output. Chapter 1 examines the factors underlying this success, such as the decline of international aluminium cartels, the introduction of innovative technology, the US granting China the MFN tariff status, Chinese-specific factors, and supportive government policies. Chapter 2 develops a mathematical model to analyze firms’ decisions in the short term. It examines how an incumbent with outdated technology and a new entrant with access to a new type of technology make strategic decisions, including the incumbent’s decision whether to deter entry, the production choice of firms, the optimal technology adoption rate of the newcomer, and cartel formation. Chapter 3 focuses on the adoption of new technology by firms upon market entry in four scenarios: firstly, a free market Cournot competition; secondly, a situation in which the government determines technology adoption rates; thirdly, a scenario in which the government controls both technology and production; and finally, a scenario where the government dictates technology adoption rates, production levels, and also the number of market participants. Chapter 4 applies the Spencer and Brander (1983) framework to examine strategic industrial policy. The model assumes that there are two exporting firms in two different countries that sell a product to a third country. We examine how the domestic firm is influenced by government intervention, such as the provision of a fixed-cost subsidy to improve its competitiveness relative to the foreign company. Chapter 4 initially investigates a scenario where only one government offers a fixed-cost subsidy, followed by an analysis of the case when both governments simultaneously provide financial help. Taken together, these chapters provide a comprehensive analysis of the strategic, technological, and political factors contributing to China’s leadership in the global aluminium industry. Chapter 1: The Rise of China as a Latecomer in the Global Aluminium Industry This chapter examines China’s remarkable transformation into a global leader in the aluminium industry, a sector in which the country accounted for approximately 58.9% of worldwide production in 2022. We examine how China, a latecomer to the aluminium industry that started off with labor-intensive technology in 1953, grew into the largest aluminium producer with some of the most advanced smelters in the world. This analysis identifies and discusses several opportunities that Chinese aluminium producers took advantage of. The first set of opportunities happened during the 1970s oil crises, which softened international competition and allowed China to acquire innovative smelting technology from Japan. The second set of opportunities started at about the same time when China opened its economy in 1978. The substantial demand for aluminium in China is influenced by both external and internal factors. Externally, the US granted China’s MFN tariff status in 1980 and China entered the World Trade Organization (WTO) in 2001. Both events contributed to a surge in Chinese aluminium consumption. Internally, China’s investment-led growth model boosted further its aluminium demand. Additional factors specific to China, such as low labor costs and the abundance of coal as an energy source, offer Chinese firms competitive advantages against international players. Furthermore, another window of opportunity is due to Chinese governmental policies, including phasing out old technology, providing subsidies, and gradually opening the economy to enhance domestic competition before expanding globally. By describing these elements, the study provides insights into the dynamic interplay of external circumstances and internal strategies that contributed to the success of the Chinese aluminium industry. Chapter 2: Technological Change and Strategic Choices for Incumbent and New Entrant This chapter introduces an oligopoly model that includes two actors: an incumbent and a potential entrant, that compete in the same market. We assume that two participants are located in different parts of the market: the incumbent is situated in area 1, whereas the potential entrant may venture into the other region, area 2. The incumbent exists in stage zero, where it can decide whether to deter the newcomer’s entry. A new type of technology exists in period one, when the newcomer may enter the market. In the short term, the incumbent is trapped with the outdated technology, while the new entrant may choose to partially or completely adopt the latest technology. Our results suggest the following: Firstly, the incumbent only tries to deter the new entrant if a condition for entry cost is met. Secondly, the new entrant is only interested in forming a cartel with the incumbent if a function of the ratio of the variable to new technology’s fixed-cost parameters is sufficiently high. Thirdly, if the newcomer asks to form a cartel, the incumbent will always accept this request. Finally, we can obtain the optimal new technology adoption rate for the newcomer. Chapter 3: Technological Adoption and Welfare in Cournot Oligopoly This study examines the difference between the optimal technology adoption rates chosen by firms in a homogeneous Cournot oligopoly and that preferred by a benevolent government upon firms’ market entry. To address the question of whether the technology choices of firms and government are similar, we analyze several different scenarios, which differ in the extent of government intervention in the market. Our results suggest a relationship between the number of firms in the market and the impact of government intervention on technology adoption rates. Especially in situations with a low number of firms that are interested in entering the market, greater government influence tends to lead to higher technology adoption rates of firms. Conversely, in scenarios with a higher number of firms and a government that lacks control over the number of market players, the technology adoption rate of firms will be highest when the government plays no role. Chapter 4: International Technological Innovation and Industrial Strategies Supporting domestic firms when they first enter the market may be seen as a favorable policy choice by governments around the world thanks to their ability to enhance the competitive advantage of domestic firms in non-cooperative competition against foreign enterprises (infant industry protection argument). This advantage may allow domestic firms to increase their market share and generate higher profits, thereby improving domestic welfare. This chapter utilizes the Spencer and Brander (1983) framework as a theoretical foundation to elucidate the effects of fixed-cost subsidies on firms’ production levels, technological innovations, and social welfare. The analysis examines two firms in different countries, each producing a homogeneous product that is sold in a third, separate country. We first examine the Cournot-Nash equilibrium in the absence of government intervention, followed by analyzing a scenario where just one government provides a financial subsidy for its domestic firm, and finally, we consider a situation where both governments simultaneously provide financial assistance for their respective firms. Our results suggest that governments aim to maximize social welfare by providing fixed-cost subsidies to their respective firms, finding themselves in a Chicken game scenario. Regarding technology innovation, subsidies lead to an increased technological adoption rate for recipient firms, regardless of whether one or both firms in a market receive support, compared to the situation without subsidies. The technology adoption rate of the recipient firm is higher than of its rival when only the recipient firm benefits from the fixed-cost subsidy. The lowest technology adoption rate of a firm occurs when the firm does not receive a fixed-cost subsidy, but its competitor does. Furthermore, global welfare will benefit the most in case when both exporting countries grant fixed-cost subsidies, and this welfare level is higher when only one country subsidizes than when no subsidies are provided by any country.

Today, almost every modern computing device is equipped with multicore processors capable of efficient concurrent and parallel execution of threads. This processor feature can be leveraged by concurrent programming, which is a challenge for software developers for two reasons: first, it introduces a paradigm shift that requires a new way of thinking. Second, it can lead to issues that are unique to concurrent programs due to the non-deterministic, interleaved execution of threads. Consequently, the debugging of concurrency and related performance issues is a rather difficult and often tedious task. Developers still lack on thread-aware programming tools that facilitate the understanding of concurrent programs. Ideally, these tools should be part of their daily working environment, which typically includes an Integrated Development Environment (IDE). In particular, the way source code is visually presented in traditional source-code editors does not convey much information on whether the source code is executed concurrently or in parallel in the first place. With this dissertation, we pursue the main goal of facilitating and supporting the understanding and debugging of concurrent programs. To this end, we formulate and utilize a visualization paradigm that particularly includes the display of interactive glyph-based visualizations embedded in the source-code editor close to their corresponding artifacts (in-situ). To facilitate the implementation of visualizations that comply with our paradigm as plugins for IDEs, we designed, implemented and evaluated a programming framework called CodeSparks. After presenting the design goals and the architecture of the framework, we demonstrate its versatility with a total of fourteen plugins realized by different developers using the CodeSparks framework (CodeSparks plugins). With focus group interviews, we empirically investigated how developers of the CodeSparks plugins experienced working with the framework. Based on the plugins, deliberate design decisions and the interview results, we discuss to what extent we achieved our design goals. We found that the framework is largely target programming-language independent and that it supports the development of plugins for a wide range of source-code-related tasks while hiding most of the details of the underlying plugin development API. In addition, we applied our visualization paradigm to thread-related runtime data from concurrent programs to foster the awareness of source code being executed concurrently or in parallel. As a result, we developed and designed two in-situ thread visualizations, namely ThreadRadar and ThreadFork, with the latter building on the former. Both thread visualizations are based on a debugging approach, which combines statistical profiling, thread-aware runtime metrics, clustering of threads on the basis of these metrics, and finally interactive glyph-based in-situ visualizations. To address scalability issues of the ThreadRadar in terms of space required and the number of displayable thread clusters, we designed a revised thread visualization. This revision also involved the question of how many thread clusters k should be computed in the first place. To this end, we conducted experiments with the clustering of threads for artifacts from a corpus of concurrent Java programs that include real-world Java applications and concurrency bugs. We found that the maximum k on the one hand and the optimal k according to four cluster validation indices on the other hand rarely exceed three. However, occasionally thread clusterings with k > 3 are available and also optimal. Consequently, we revised both the clustering strategy and the visualization as parts of our debugging approach, which resulted in the ThreadFork visualization. Both in-situ thread visualizations, including their additional features that support the exploration of the thread data, are implemented in a tool called CodeSparks-JPT, i.e., as a CodeSparks plugin for IntelliJ IDEA. With various empirical studies, including anecdotal usage scenarios, a usability test, web surveys, hands-on sessions, questionnaires and interviews, we investigated quality aspects of the in-situ thread visualizations and their corresponding tools. First, by a demonstration study, we illustrated the usefulness of the ThreadRadar visualization in investigating and fixing concurrency bugs and a performance bug. This was confirmed by a subsequent usability test and interview, which also provided formative feedback. Second, we investigated the interpretability and readability of the ThreadFork glyphs as well as the effectiveness of the ThreadFork visualization through anonymous web surveys. While we have found that the ThreadFork glyphs are correctly interpreted and readable, it remains unproven that the ThreadFork visualization effectively facilitates understanding the dynamic behavior of threads that concurrently executed portions of source code. Moreover, the overall usability of CodeSparks-JPT is perceived as "OK, but not acceptable" as the tool has issues with its learnability and memorability. However, all other usability aspects of CodeSparks-JPT that were examined are perceived as "above average" or "good". Our work supports software-engineering researchers and practitioners in flexibly and swiftly developing novel glyph-based visualizations that are embedded in the source-code editor. Moreover, we provide in-situ thread visualizations that foster the awareness of source code being executed concurrently or in parallel. These in-situ thread visualizations can, for instance, be adapted, extended and used to analyze other use cases or to replicate the results. Through empirical studies, we have gradually shaped the design of the in-situ thread visualizations through data-driven decisions, and evaluated several quality aspects of the in-situ thread visualizations and the corresponding tools for their utility in understanding and debugging concurrent programs.

This dissertation focusses on research into the personality construct of action vs. state orientation. Derived from the Personality-Systems-Interaction Theory (PSI Theory), state orientation is defined as a low ability to self-regulate emotions and associated with many adverse consequences – especially under stress. Because of the high prevalence of state orientation, it is a very important topic to investigate factors that help state-oriented people to buffer these adverse consequences. Action orientation, in contrast, is defined as a high ability to self-regulate own emotions in a very specific way: through accessing the self. The present dissertation demonstrates this theme in five studies, using a total of N = 1251 participants with a wide age range, encompassing different populations (students, non-student population (people from the coaching and therapy sector), applying different operationalisations to investigate self-access as a mediator or an outcome variable. Furthermore, it is tested whether the popular technique of mindfulness - that is advertised as a potent remedy for bringing people closer to the self -really works for everybody. The findings show that the presumed remedy is rather harmful for state-oriented individuals. Finally, an attempt to ameliorate these alienating effects, the present dissertation attempts to find theory-driven, and easy-to-apply solution how mindfulness exercises can be adapted.

Physically-based distributed rainfall-runoff models as the standard analysis tools for hydro-logical processes have been used to simulate the water system in detail, which includes spa-tial patterns and temporal dynamics of hydrological variables and processes (Davison et al., 2015; Ek and Holtslag, 2004). In general, catchment models are parameterized with spatial information on soil, vegetation and topography. However, traditional approaches for eval-uation of the hydrological model performance are usually motivated with respect to dis-charge data alone. This may thus cloud model realism and hamper understanding of the catchment behavior. It is necessary to evaluate the model performance with respect to in-ternal hydrological processes within the catchment area as well as other components of wa-ter balance rather than runoff discharge at the catchment outlet only. In particular, a consid-erable amount of dynamics in a catchment occurs in the processes related to interactions of the water, soil and vegetation. Evapotranspiration process, for instance, is one of those key interactive elements, and the parameterization of soil and vegetation in water balance mod-eling strongly influences the simulation of evapotranspiration. Specifically, to parameterize the water flow in unsaturated soil zone, the functional relationships that describe the soil water retention and hydraulic conductivity characteristics are important. To define these functional relationships, Pedo-Transfer Functions (PTFs) are common to use in hydrologi-cal modeling. Opting the appropriate PTFs for the region under investigation is a crucial task in estimating the soil hydraulic parameters, but this choice in a hydrological model is often made arbitrary and without evaluating the spatial and temporal patterns of evapotran-spiration, soil moisture, and distribution and intensity of runoff processes. This may ulti-mately lead to implausible modeling results and possibly to incorrect decisions in regional water management. Therefore, the use of reliable evaluation approaches is continually re-quired to analyze the dynamics of the current interactive hydrological processes and predict the future changes in the water cycle, which eventually contributes to sustainable environ-mental planning and decisions in water management. Remarkable endeavors have been made in development of modelling tools that provide insights into the current and future of hydrological patterns in different scales and their im-pacts on the water resources and climate changes (Doell et al., 2014; Wood et al., 2011). Although, there is a need to consider a proper balance between parameter identifiability and the model's ability to realistically represent the response of the natural system. Neverthe-less, tackling this issue entails investigation of additional information, which usually has to be elaborately assembled, for instance, by mapping the dominant runoff generation pro-cesses in the intended area, or retrieving the spatial patterns of soil moisture and evapotran-spiration by using remote sensing methods, and evaluation at a scale commensurate with hydrological model (Koch et al., 2022; Zink et al., 2018). The present work therefore aims to give insights into the modeling approaches to simulate water balance and to improve the soil and vegetation parameterization scheme in the hydrological model subject to producing more reliable spatial and temporal patterns of evapotranspiration and runoff processes in the catchment. An important contribution to the overall body of work is a book chapter included among publications. The book chapter provides a comprehensive overview of the topic and valua-ble insights into the understanding the water balance and its estimation methods. Moreover, the first paper aimed to evaluate the hydrological model behavior with re-spect to contribution of various sources of information. To do so, a multi-criteria evaluation metric including soft and hard data was used to define constraints on outputs of the 1-D hydrological model WaSiM-ETH. Applying this evaluation metric, we could identify the optimal soil and vegetation parameter sets that resulted in a “behavioral” forest stand water balance model. It was found out that even if simulations of transpiration and soil water con-tent are consistent with measured data, but still the dominant runoff generation processes or total water balance might be wrongly calculated. Therefore, only using an evaluation scheme which looks over different sources of data and embraces an understanding of the local controls of water loss through soil and plant, allowed us to exclude the unrealistic modeling outputs. The results suggested that we may need to question the generally accept-ed soil parameterization procedures that apply default parameter sets. The second paper attempts to tackle the pointed model evaluation hindrance by getting down to the small-scale catchment (in Bavaria). Here, a methodology was introduced to analyze the sensitivity of the catchment water balance model to the choice of the Pedo-Transfer Functions (PTF). By varying the underlying PTFs in a calibrated and validated model, we could determine the resulting effects on the spatial distribution of soil hydraulic properties, total water balance in catchment outlet, and the spatial and temporal variation of the runoff components. Results revealed that the water distribution in the hydrologic system significantly differs amongst various PTFs. Moreover, the simulations of water balance components showed high sensitivity to the spatial distribution of soil hydraulic properties. Therefore, it was suggested that opting the PTFs in hydrological modeling should be care-fully tested by looking over the spatio-temporal distribution of simulated evapotranspira-tion and runoff generation processes, whether they are reasonably represented. To fulfill the previous studies’ suggestions, the third paper then aims to focus on evalu-ating the hydrological model through improving the spatial representation of dominant run-off processes. It was implemented in a mesoscale catchment in southwestern Germany us-ing the hydrological model WaSiM-ETH. Dealing with the issues of inadequate spatial ob-servations for rigorous spatial model evaluation, we made use of a reference soil hydrologic map available for the study area to discern the expected dominant runoff processes across a wide range of hydrological conditions. The model was parameterized by applying 11 PTFs and run by multiple synthetic rainfall events. To compare the simulated spatial patterns to the patterns derived by digital soil map, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability with regard to land use, topography, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions. The three published manuscripts proceeded towards the model evaluation viewpoints that ultimately attain the behavioral model outputs. It was performed through obtaining information about internal hydrological processes that lead to certain model behaviors, and also about the function and sensitivity of some of the soil and vegetation parameters that may primarily influence those internal processes in a catchment. Accordingly, using this understanding on model reactions, and by setting multiple evaluation criteria, it was possi-ble to identify which parameterization could lead to behavioral model realization. This work, in fact, will contribute to solving some of the issues (e.g., spatial variability and modeling methods) identified as the 23 unsolved problems in hydrology in the 21st century (Blöschl et al., 2019). The results obtained in the present work encourage the further inves-tigations toward a comprehensive model calibration procedure considering multiple data sources simultaneously. This will enable developing the new perspectives to the current parameter estimation methods, which in essence, focus on reproducing the plausible dy-namics (spatio-temporal) of the other hydrological processes within the watershed.

Social entrepreneurship is a successful activity to solve social problems and economic challenges. Social entrepreneurship uses for-profit industry techniques and tools to build financially sound businesses that provide nonprofit services. Social entrepreneurial activities also lead to the achievement of sustainable development goals. However, due to the complex, hybrid nature of the business, social entrepreneurial activities are typically supported by macrolevel determinants. To expand our knowledge of how beneficial macro-level determinants can be, this work examines empirical evidence about the impact of macro-level determinants on social entrepreneurship. Another aim of this dissertation is to examine the impact at the micro level, as the growth ambitions of social and commercial entrepreneurs differ. At the beginning, the introductory section is explained in Chapter 1, which contains the motivation for the research, the research question, and the structure of the work. There is an ongoing debate about the origin and definition of social entrepreneurship. Therefore, the numerous phenomena of social entrepreneurship are examined theoretically in the previous literature. To determine the common consensus on the topic, Chapter 2 presents the theoretical foundations and definition of social entrepreneurship. The literature shows that a variety of determinants at the micro and macro levels are essential for the emergence of social entrepreneurship as a distinctive business model (Hartog & Hoogendoorn, 2011; Stephan et al., 2015; Hoogendoorn, 2016). It is impossible to create a society based on a social mission without the support of micro and macro-level-level determinants. This work examines the determinants and consequences of social entrepreneurship from different methodological perspectives. The theoretical foundations of the micro- and macro-level determinants influencing social entrepreneurial activities were discussed in Chapter 3. The purpose of reproducibility in research is to confirm previously published results (Hubbard et al., 1998; Aguinis & Solarino, 2019). However, due to the lack of data, lack of transparency of methodology, reluctance to publish, and lack of interest from researchers, there is a lack of promoting replication of the existing research study (Baker, 2016; Hedges & Schauer, 2019a). Promoting replication studies has been regularly emphasized in the business and management literature (Kerr et al., 2016; Camerer et al., 2016). However, studies that provide replicability of the reported results are considered rare in previous research (Burman et al., 2010; Ryan & Tipu, 2022). Based on the research of Köhler and Cortina (2019), an empirical study on this topic is carried out in Chapter 4 of this work. Given this focus, researchers have published a large body of research on the impact of microand macro-level determinants on social inclusion, although it is still unclear whether these studies accurately reflect reality. It is important to provide conceptual underpinnings to the field through a reassessment of published results (Bettis et al., 2016). The results of their research make it abundantly clear that the macro determinants support social entrepreneurship. In keeping with the more narrative approach, which is a crucial concern and requires attention, Chapter 5 considered the reproducibility of previous results, particularly on the topic of social entrepreneurship. We replicated the results of Stephan et al. (2015) to establish the trend of reproducibility and validate the specific conclusions they drew. The literal and constructive replication in the dissertation inspired us to explore technical replication research on social entrepreneurship. Chapter 6 evaluates the fundamental characteristics that have proven to be key factors in the growth of social ventures. The current debate reviews and references literature that has specifically focused on the development of social entrepreneurship. An empirical analysis of factors directly related to the ambitious growth of social entrepreneurship is also carried out. Numerous social entrepreneurial groups have been studied concerning this association. Chapter 6 compares the growth ambitions of social and traditional (commercial) entrepreneurship as consequences at the micro level. This study examined many characteristics of social and commercial entrepreneurs' growth ambitions. Scholars have claimed to some extent that the growth of social entrepreneurship differs from commercial entrepreneurial activities due to objectivity differences (Lumpkin et al., 2013; Garrido-Skurkowicz et al., 2022). Qualitative research has been used in studies to support the evidence on related topics, including Gupta et al (2020) emphasized that research needs to focus on specific concepts of social entrepreneurship for the field to advance. Therefore, this study provides a quantitative, analysis-based assessment of facts and data. For this purpose, a data set from the Global Entrepreneurship Monitor (GEM) 2015 was used, which examined 12,695 entrepreneurs from 38 countries. Furthermore, this work conducted a regression analysis to evaluate the influence of various social and commercial characteristics of entrepreneurship on economic growth in developing countries. Chapter 7 briefly explains future directions and practical/theoretical implications.

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

There is no longer any doubt about the general effectiveness of psychotherapy. However, up to 40% of patients do not respond to treatment. Despite efforts to develop new treatments, overall effectiveness has not improved. Consequently, practice-oriented research has emerged to make research results more relevant to practitioners. Within this context, patient-focused research (PFR) focuses on the question of whether a particular treatment works for a specific patient. Finally, PFR gave rise to the precision mental health research movement that is trying to tailor treatments to individual patients by making data-driven and algorithm-based predictions. These predictions are intended to support therapists in their clinical decisions, such as the selection of treatment strategies and adaptation of treatment. The present work summarizes three studies that aim to generate different prediction models for treatment personalization that can be applied to practice. The goal of Study I was to develop a model for dropout prediction using data assessed prior to the first session (N = 2543). The usefulness of various machine learning (ML) algorithms and ensembles was assessed. The best model was an ensemble utilizing random forest and nearest neighbor modeling. It significantly outperformed generalized linear modeling, correctly identifying 63.4% of all cases and uncovering seven key predictors. The findings illustrated the potential of ML to enhance dropout predictions, but also highlighted that not all ML algorithms are equally suitable for this purpose. Study II utilized Study I’s findings to enhance the prediction of dropout rates. Data from the initial two sessions and observer ratings of therapist interventions and skills were employed to develop a model using an elastic net (EN) algorithm. The findings demonstrated that the model was significantly more effective at predicting dropout when using observer ratings with a Cohen’s d of up to .65 and more effective than the model in Study I, despite the smaller sample (N = 259). These results indicated that generating models could be improved by employing various data sources, which provide better foundations for model development. Finally, Study III generated a model to predict therapy outcome after a sudden gain (SG) in order to identify crucial predictors of the upward spiral. EN was used to generate the model using data from 794 cases that experienced a SG. A control group of the same size was also used to quantify and relativize the identified predictors by their general influence on therapy outcomes. The results indicated that there are seven key predictors that have varying effect sizes on therapy outcome, with Cohen's d ranging from 1.08 to 12.48. The findings suggested that a directive approach is more likely to lead to better outcomes after an SG, and that alliance ruptures can be effectively compensated for. However, these effects were reversed in the control group. The results of the three studies are discussed regarding their usefulness to support clinical decision-making and their implications for the implementation of precision mental health.

This thesis deals with the construction of investment screening mechanisms across the major economic powers in Europe and at the supranational level during the post-2015 period. The core puzzle at the heart of this research is how, in a traditional bastion of economic liberalism such as Europe, could a protectionist tool such as investment screening be erected in such a rapid manner. Within a few years, Europe went from a position of being highly welcoming towards foreign investment to increasingly implementing controls on it, with the focus on China. How are we to understand this shift in Europe? I posit that Europe’s increasingly protectionist shift on inward investment can be fruitfully understood using an economic realist approach, where the introduction of investment screening can be seen as part of a process of ‘balancing’ China’s economic rise and reasserting European competitiveness. China has moved from being the ‘workshop of the world’ to becoming an innovation-driven economy at the global technological frontier. As China has become more competitive, Europe, still a global economic leader, broadly situated at the technological frontier, has begun to sense a threat to its position, especially in the context of the fourth industrial revolution. A ‘balancing’ process has been set in motion, in which Europe seeks to halt and even reverse the narrowing competitiveness gap between it and China. The introduction of investment screening measures is part of this process.

Repeatedly encountering a stimulus biases the observer’s affective response and evaluation of the stimuli. Here we provide evidence for a causal link between mere exposure to fictitious news reports and subsequent voting behavior. In four pre-registered online experiments, participants browsed through newspaper webpages and were tacitly exposed to names of fictitious politicians. Exposure predicted voting behavior in a subsequent mock election, with a consistent preference for frequent over infrequent names, except when news items were decidedly negative. Follow-up analyses indicated that mere media presence fuels implicit personality theories regarding a candidate’s vigor in political contexts. News outlets should therefore be mindful to cover political candidates as evenly as possible.