This thesis examines how Europe sustains its leadership and competitiveness as a global center for foreign direct investment (FDI) and trade between 1991 and 2023. While EU membership historically functioned as the dominant determinant of inward FDI and trade integration, its relative influence has declined as new structural factors, based on trade dynamics and export-platform strategies, have emerged, together with the growing presence of Asian, especially Chinese, investors establishing production hubs in Central and Eastern Europe to serve the wider EU market. Lower trade costs within Europe have reinforced this shift, leading EU investors to focus on vertical FDI, while non-EU investors to adopt export-platform FDI patterns. Chinese investment has moved from infrastructure-focused projects to strategic-sector FDI, highlighting Europe’s exposure to evolving global industrial and geopolitical dynamics. Chapter 2 examines how traditional determinants of FDI, including EU membership, interact with emerging drivers, such as trade interdependence, export-platform strategies, and Asian influence, to shape investment patterns in Europe. It employs a gravity-based empirical framework augmented with newly developed indicators, comprising the Bilateral Trade Interdependence Index, the Export-Platform Indicator, and Belt and Road Initiative (BRI) participation, together with a functional integration approach, covering over 95% of European countries and their global partners from 2010 to 2023. The findings indicate that trade dependency with non-EU partners grew most rapidly, increasing by 55% between 2011 and 2023. Stronger bilateral trade interdependence is found to significantly predict higher FDI inflows. The BRI analysis and functional classification indicate a shift from infrastructure-focused Chinese investment to strategic sectors, including electric vehicles and semiconductors. Since 2018, export-platform strategies have expanded from Europe’s core economies into Central and Eastern Europe, forming emerging production hubs, and have subsequently moved toward the Western Balkans and Turkey, likely reflecting evolving EU regulations and broader supply-chain realignments. Chapter 3 expands the FDI analysis to cover a longer timeframe, from 1991 to 2017, focusing on the period when EU membership exerted a strong influence on FDI in Europe, transforming member countries from primarily cost-attractive destinations into global investment centers. Using an augmented gravity model covering 39 host and origin countries, the analysis finds that EU membership increased FDI inflows by 23%, with investments from core EU members expanding into new EU member states, while FDI from non-EU countries decreased. At the same time, EU membership may also be driven by trade, and EEA participation reflects non-FDI motivations. The chapter also highlights that EU accession strengthens both market-seeking (horizontal) and x efficiency-seeking (vertical) FDI motives and applies methods to address negative and zero FDI values issues, ensuring robust estimation. The inclusion of lagged and lead variables shows that the EU integration process is phased over time, affecting FDI inflows with lags of up to 10–15 years after accession. Chapter 4 expands the range of FDI determinants by deriving trade cost indices as a proxy for connectivity and extending the geographic scope of the analysis. In addition to EU members, the sample includes the Western Balkans, Turkey, and new EU candidates and applicants (Moldova, Ukraine, and Georgia) over the period 2000 to 2020, covering approximately 80% of European FDI flows. Trade costs are calculated for each country in the sample with its trade partners, not only within and between European subregions but also with non-EU partners such as China, and are combined with measures of FDI restrictiveness. The results show that China remains among the EU’s top three trading partners in goods and that trade costs significantly influence FDI inflows in Europe. The analysis also highlights that declining trade costs between European countries have reduced market-seeking (horizontal) FDI, while non-European investors, especially China, increasingly pursue export-platform FDI to serve third-country markets. A sharp reduction in trade costs between the Western Balkans and the EU (-45%) and a smaller decline with China (-35%) illustrates how regional integration reduces the need for local horizontal FDI while reinforcing Europe’s role as a hub for global production. Chapter 5 shows that despite concerns about increasing outside influence, developed European countries remain the dominant source of FDI in the region. The chapter focuses on China’s role, examining FDI patterns across advanced EU members, new member states, and Western Balkan economies between 2000 and 2019, while distinguishing the effects of EU integration and BRI participation on FDI. Chinese influence has expanded primarily through the Belt and Road Initiative, particularly in accession and neighboring countries. Although BRI participation does not significantly increase FDI on its own, reflecting the dominant part of loan-financed infrastructure rather than private investment, it has strengthened physical and digital connectivity, laying the groundwork for future, longer-term FDI. The analysis also shows that intra-EU trade costs declined significantly after the 2004 and 2007 enlargements, while trade costs between the Western Balkans and China have fallen steadily since the launch of the BRI in 2013. As a result, Chinese influence is more pronounced in new EU member states and Western Balkan economies than in Western Europe. Over time, enhanced connectivity and supply-chain integration may support more diversified FDI inflows.

Die vorliegende Dissertation untersucht das Motiv der Freiheit als zentrales Thema in Werken des DDR-Autors Ulrich Plenzdorf. Ziel ist es, Plenzdorfs literarische Auseinandersetzung mit individuellen Freiheitsbestrebungen unter den Bedingungen der SED-Diktatur eingehend zu erschließen. Die Analyse erfolgt diachron und umfasst Texte aus den 1960er Jahren bis zum Ende der 1980er Jahre, wodurch Entwicklungslinien, thematische Verschiebungen und ästhetische Veränderungen im Werk sichtbar werden. Neben kanonisierten Werken werden auch bislang wenig beachtete Texte einbezogen, um ein vollständigeres Bild von Plenzdorfs literarischer Produktion zu gewinnen und Forschungslücken zu schließen. Methodisch orientiert sich die Studie an einem kulturwissenschaftlichen Ansatz im Sinne des New Historicism, der literarische Texte als Teil kultureller Praktiken und sozialer Machtverhältnisse versteht. Vor diesem Hintergrund wird gezeigt, wie Plenzdorf Freiheitsvorstellungen in unterschiedlichen historischen Phasen der DDR artikuliert und mit Alltagskultur, Subkulturen sowie gesellschaftlichen Konfliktfeldern verknüpft. Diese Dissertation leistet damit einerseits einen Beitrag zur Neubewertung Plenzdorfs und andererseits zur kulturhistorischen Kontextualisierung der DDR-Literatur.

From Gene to Ecosystem – Retrospective molecular biodiversity monitoring of plant-associated arthropod communities and abiotic stress on plants

This thesis serves as proof of concept for the tensile strength simulation-based nonwoven material design. Objective is the adjustment of the parameters of an underlying production process with regard to a desired tensile strength behavior (optimization). As an example, we focus on the nonwoven airlay production and consider a thermobonding procedure for the consolidation of the nonwoven fabrics. To be able to map production parameters to the associated tensile strength behavior, we present a model-simulation framework composed of a model for the nonwoven fiber structure generation and a model for the nonwovens’ mechanical behavior under vertical load. The model for the fiber structure generation replicates the stochastic fiber lay-down of the airlay production and results in a random three-dimensional fiber web. This web is consolidated using a virtual bonding procedure that mimics the thermobonding of the nonwoven material. The topology of the resulting adhered fiber structure can be described by a graph, which serves as basis for the subsequent tensile strength simulation. The model used for this purpose describes the mechanical behavior of the material at fiber network level. Therefore, the considered fiber structure sample is interpreted as truss and the fiber connections are equipped with a nonlinear material law, which allows to describe the elastic phase of the nonwovens’ tensile strength behavior. The existence and uniqueness of a solution to the model as well as its numerical treatment are discussed. Moreover, we present data reduction strategies that enable more efficient simulations by removing fiber structure parts that do not contribute to the tensile strength behavior. As it becomes evident from the numerical experiments, a single tensile strength simulation for a production-like virtual sample is already computational demanding. Costs accumulate further, since Monte-Carlo simulations are required to account for the randomness in the fiber structure generation. Thus, direct simulations provide an infeasible basis for the nonwoven material design. This motivates the use of a predictive surrogate for optimization. Therefore, we consider regression-based approaches at different levels of information within the simulation framework. It turns out that the coupling of a polynomial model, for the fiber structure feature inference, with a linear one, for the stress-strain curve inference, yields accurate predictions. Once trained, the regression models allow for efficient evaluations and thus represent a suitable surrogate for the nonwoven material design. In this context, we discuss two exemplary problems of interest for the application: First, a tracking-type problem that aims to find the production parameters that result in a desired tensile strength behavior, expressed in terms of stress-strain curves. Second, an in-corridor maximization problem, which aims to identify the production parameters that maximize the probability of ending up in a specified stress-strain corridor.