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Auf dem Friedhof der Kirche St. Matthias im Süden Triers befinden sich vier Kammern, die bis in jüngste Zeit als die Untergeschosse selbstständiger römischer Grabbauten angesprochen wurden. Bei dem Areal handelte es sich um einen Teil der südlichen Nekropole des römischen Triers, der vor allem mit Körperbestattungen belegt worden ist. Dieses Körpergräberfeld wird in der vorliegenden Arbeit zum ersten Mal anhand der archäologischen Funde und Befunde beschrieben.
Nach früheren, kleineren Untersuchungen fanden im Umfeld der Kammern 1931 umfangreiche Grabungen statt; weitere folgten in den 1960er Jahren. Die im Rahmen dieser Maßnahmen erstellten Unterlagen wurden vom Autor zusammengestellt und aufgearbeitet. Ergänzend kamen eigene Beobachtungen am noch sichtbaren Befund hinzu.
So ließ sich erschließen, dass die meisten Grabkammern nicht Reste eigenständiger Bauten waren, sondern Teile eines bisher nicht erkannten größeren Baukomplexes. Dieser bestand aus einem großen Rechteckbau, der das Untergeschoss eines älteren Grabbaus inkorporierte. Dieser bildete einen kellerartigen Raum, der mit einem Wasseranschluss versehen war. Innerhalb des Rechteckbaus konnten Reste eines festen Fußbodens zu ebener Erde, sowie farbige Wandmalerei beobachtet werden. Kurz nach seiner Errichtung wurde der Rechteckbau mit zwei unterirdischen Kammern versehen und im Osten durch drei Anbauten mit unterschied-lichen Grundrissen erweitert: Im Süden entstand so ein Apsidenbau mit einer großen unterirdischen Kammer, in der sich bis heute ein Reliefsarkophag befindet.
Die Befundauswertung ergab, dass der Baukomplex in konstantinischer Zeit errichtet worden ist und offenbar schon um die Mitte des 5.Jhs. n. Chr. aufgegeben wurde.
Zu diesem Baubefund ließ sich in den benachbarten römischen Provinzen keine direkte Parallele finden. Am ehesten vergleichbar scheint ein weiterer Baukomplex aus der nördlichen Nekropole Triers, der unter der Kirche St. Maximin aufgedeckt wurde. Er ist ab der Mitte des 4. Jhs. n. Chr. errichtet und von der christlichen Gemeinde genutzt worden. Dieser Bau ähnelt in seinem Grundriss dem Baukomplex von St. Matthias, unterschiedet sich aber in der Bestattungspraxis: Während zahlreiche Sarkophag-Bestattungen im Hauptbau und teilweise auch den Anbauten in den unbefestigten Boden eingelassen worden sind, fand sich bei St. Matthias sowohl im Hauptbau als auch den Anbauten ein fester Boden. Innerhalb dieses Baukomplexes kann nur der oben beschriebene Reliefsarkophag der Nutzungszeit zugeordnet werden. Demnach könnte hier die Schaffung separater Bestattungsräume bedeutsam gewesen sein – neben anderen Funktionen, wie der Bereitstellung von Wasser und überdachtem Raum zur Begehung der Totenfeiern. Die stärkere Berücksichtigung solch funktionaler Elemente scheint demnach eine wichtige Ergänzung zur weiterführenden Deutung römischer Sepulkralarchitektur zu sein.
With two-thirds to three-quarters of all companies, family firms are the most common firm type worldwide and employ around 60 percent of all employees, making them of considerable importance for almost all economies. Despite this high practical relevance, academic research took notice of family firms as intriguing research subjects comparatively late. However, the field of family business research has grown eminently over the past two decades and has established itself as a mature research field with a broad thematic scope. In addition to questions relating to corporate governance, family firm succession and the consideration of entrepreneurial families themselves, researchers mainly focused on the impact of family involvement in firms on their financial performance and firm strategy. This dissertation examines the financial performance and capital structure of family firms in various meta-analytical studies. Meta-analysis is a suitable method for summarizing existing empirical findings of a research field as well as identifying relevant moderators of a relationship of interest.
First, the dissertation examines the question whether family firms show better financial performance than non-family firms. A replication and extension of the study by O’Boyle et al. (2012) based on 1,095 primary studies reveals a slightly better performance of family firms compared to non-family firms. Investigating the moderating impact of methodological choices in primary studies, the results show that outperformance holds mainly for large and publicly listed firms and with regard to accounting-based performance measures. Concerning country culture, family firms show better performance in individualistic countries and countries with a low power distance.
Furthermore, this dissertation investigates the sensitivity of family firm performance with regard to business cycle fluctuations. Family firms show a pro-cyclical performance pattern, i.e. their relative financial performance compared to non-family firms is better in economically good times. This effect is particularly pronounced in Anglo-American countries and emerging markets.
In the next step, a meta-analytic structural equation model (MASEM) is used to examine the market valuation of public family firms. In this model, profitability and firm strategic choices are used as mediators. On the one hand, family firm status itself does not have an impact on firms‘ market value. On the other hand, this study finds a positive indirect effect via higher profitability levels and a negative indirect effect via lower R&D intensity. A split consideration of family ownership and management shows that these two effects are mainly driven by family ownership, while family management results in less diversification and internationalization.
Finally, the dissertation examines the capital structure of public family firms. Univariate meta-analyses indicate on average lower leverage ratios in family firms compared to non-family firms. However, there is significant heterogeneity in mean effect sizes across the 45 countries included in the study. The results of a meta-regression reveal that family firms use leverage strategically to secure their controlling position in the firm. While strong creditor protection leads to lower leverage ratios in family firms, strong shareholder protection has the opposite effect.
Die vorgelegte Dissertation trägt den Titel Regularization Methods for Statistical Modelling in Small Area Estimation. In ihr wird die Verwendung regularisierter Regressionstechniken zur geographisch oder kontextuell hochauflösenden Schätzung aggregatspezifischer Kennzahlen auf Basis kleiner Stichproben studiert. Letzteres wird in der Fachliteratur häufig unter dem Begriff Small Area Estimation betrachtet. Der Kern der Arbeit besteht darin die Effekte von regularisierter Parameterschätzung in Regressionsmodellen, welche gängiger Weise für Small Area Estimation verwendet werden, zu analysieren. Dabei erfolgt die Analyse primär auf theoretischer Ebene, indem die statistischen Eigenschaften dieser Schätzverfahren mathematisch charakterisiert und bewiesen werden. Darüber hinaus werden die Ergebnisse durch numerische Simulationen veranschaulicht, und vor dem Hintergrund empirischer Anwendungen kritisch verortet. Die Dissertation ist in drei Bereiche gegliedert. Jeder Bereich behandelt ein individuelles methodisches Problem im Kontext von Small Area Estimation, welches durch die Verwendung regularisierter Schätzverfahren gelöst werden kann. Im Folgenden wird jedes Problem kurz vorgestellt und im Zuge dessen der Nutzen von Regularisierung erläutert.
Das erste Problem ist Small Area Estimation in der Gegenwart unbeobachteter Messfehler. In Regressionsmodellen werden typischerweise endogene Variablen auf Basis statistisch verwandter exogener Variablen beschrieben. Für eine solche Beschreibung wird ein funktionaler Zusammenhang zwischen den Variablen postuliert, welcher durch ein Set von Modellparametern charakterisiert ist. Dieses Set muss auf Basis von beobachteten Realisationen der jeweiligen Variablen geschätzt werden. Sind die Beobachtungen jedoch durch Messfehler verfälscht, dann liefert der Schätzprozess verzerrte Ergebnisse. Wird anschließend Small Area Estimation betrieben, so sind die geschätzten Kennzahlen nicht verlässlich. In der Fachliteratur existieren hierfür methodische Anpassungen, welche in der Regel aber restriktive Annahmen hinsichtlich der Messfehlerverteilung benötigen. Im Rahmen der Dissertation wird bewiesen, dass Regularisierung in diesem Kontext einer gegen Messfehler robusten Schätzung entspricht - und zwar ungeachtet der Messfehlerverteilung. Diese Äquivalenz wird anschließend verwendet, um robuste Varianten bekannter Small Area Modelle herzuleiten. Für jedes Modell wird ein Algorithmus zur robusten Parameterschätzung konstruiert. Darüber hinaus wird ein neuer Ansatz entwickelt, welcher die Unsicherheit von Small Area Schätzwerten in der Gegenwart unbeobachteter Messfehler quantifiziert. Es wird zusätzlich gezeigt, dass diese Form der robusten Schätzung die wünschenswerte Eigenschaft der statistischen Konsistenz aufweist.
Das zweite Problem ist Small Area Estimation anhand von Datensätzen, welche Hilfsvariablen mit unterschiedlicher Auflösung enthalten. Regressionsmodelle für Small Area Estimation werden normalerweise entweder für personenbezogene Beobachtungen (Unit-Level), oder für aggregatsbezogene Beobachtungen (Area-Level) spezifiziert. Doch vor dem Hintergrund der stetig wachsenden Datenverfügbarkeit gibt es immer häufiger Situationen, in welchen Daten auf beiden Ebenen vorliegen. Dies beinhaltet ein großes Potenzial für Small Area Estimation, da somit neue Multi-Level Modelle mit großem Erklärungsgehalt konstruiert werden können. Allerdings ist die Verbindung der Ebenen aus methodischer Sicht kompliziert. Zentrale Schritte des Inferenzschlusses, wie etwa Variablenselektion und Parameterschätzung, müssen auf beiden Levels gleichzeitig durchgeführt werden. Hierfür existieren in der Fachliteratur kaum allgemein anwendbare Methoden. In der Dissertation wird gezeigt, dass die Verwendung ebenenspezifischer Regularisierungsterme in der Modellierung diese Probleme löst. Es wird ein neuer Algorithmus für stochastischen Gradientenabstieg zur Parameterschätzung entwickelt, welcher die Informationen von allen Ebenen effizient unter adaptiver Regularisierung nutzt. Darüber hinaus werden parametrische Verfahren zur Abschätzung der Unsicherheit für Schätzwerte vorgestellt, welche durch dieses Verfahren erzeugt wurden. Daran anknüpfend wird bewiesen, dass der entwickelte Ansatz bei adäquatem Regularisierungsterm sowohl in der Schätzung als auch in der Variablenselektion konsistent ist.
Das dritte Problem ist Small Area Estimation von Anteilswerten unter starken verteilungsbezogenen Abhängigkeiten innerhalb der Kovariaten. Solche Abhängigkeiten liegen vor, wenn eine exogene Variable durch eine lineare Transformation einer anderen exogenen Variablen darstellbar ist (Multikollinearität). In der Fachliteratur werden hierunter aber auch Situationen verstanden, in welchen mehrere Kovariate stark korreliert sind (Quasi-Multikollinearität). Wird auf einer solchen Datenbasis ein Regressionsmodell spezifiziert, dann können die individuellen Beiträge der exogenen Variablen zur funktionalen Beschreibung der endogenen Variablen nicht identifiziert werden. Die Parameterschätzung ist demnach mit großer Unsicherheit verbunden und resultierende Small Area Schätzwerte sind ungenau. Der Effekt ist besonders stark, wenn die zu modellierende Größe nicht-linear ist, wie etwa ein Anteilswert. Dies rührt daher, dass die zugrundeliegende Likelihood-Funktion nicht mehr geschlossen darstellbar ist und approximiert werden muss. Im Rahmen der Dissertation wird gezeigt, dass die Verwendung einer L2-Regularisierung den Schätzprozess in diesem Kontext signifikant stabilisiert. Am Beispiel von zwei nicht-linearen Small Area Modellen wird ein neuer Algorithmus entwickelt, welche den bereits bekannten Quasi-Likelihood Ansatz (basierend auf der Laplace-Approximation) durch Regularisierung erweitert und verbessert. Zusätzlich werden parametrische Verfahren zur Unsicherheitsmessung für auf diese Weise erhaltene Schätzwerte beschrieben.
Vor dem Hintergrund der theoretischen und numerischen Ergebnisse wird in der Dissertation demonstriert, dass Regularisierungsmethoden eine wertvolle Ergänzung der Fachliteratur für Small Area Estimation darstellen. Die hier entwickelten Verfahren sind robust und vielseitig einsetzbar, was sie zu hilfreichen Werkzeugen der empirischen Datenanalyse macht.
In dem Gebiet der Informationsextraktion angesiedelt kombiniert diese Arbeit mehrere Verfahren aus dem Bereich des maschinellen Lernens. Sie stellt einen neuen Algorithmus vor, der teil-überwachtes Lernen mit aktivem Lernen verknüpft. Ausgangsbasis ist die Analyse der Daten, indem sie in mehrere Sichten aufgeteilt werden. Hier werden die Eingaben verschiedener Personen unterteilt. Jeweils getrennt voneinander erzeugt der Algorithmus mittels Klassifizierern Modelle, die aus den individuellen Auszeichnungen der Personen aufgebaut werden. Um die dafür benötigte Datenmenge zu erhalten wird Crowdsourcing genutzt, dass es ermöglicht eine große Anzahl an Personen zu erreichen. Die Personen erhalten die Aufgabe, Texte zu annotieren. Einerseits wird dies initial für einen historischen Textkorpus vorgenommen. Dabei wird aufgeführt, welche Schritte notwendig sind, um die Annotationsaufgabe in Crowdsourcing-Portalen zur Bearbeitung anzubieten und durchzuführen. Andererseits wird ein aktueller Datensatz von Kurznachrichten genutzt. Der Algorithmus wird auf diese Beispieldatensätze angewandt. Durch Experimente wird die Ermittlung der optimalen Parameterauswahl durchgeführt. Außerdem werden die Ergebnisse mit den Resultaten bisheriger Algorithmen verglichen.
Hypothalamic-pituitary-adrenal (HPA) axis-related genetic variants influence the stress response
(2019)
The physiological stress system includes the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic-adrenal-medullary system (SAM). Parameters representing these systems such as cortisol, blood pressure or heart rate define the physiological reaction in response to a stressor. The main objective of the studies described in this thesis was to understand the role of the HPA-related genetic factors in these two systems. Genetic factors represent one of the components causing individual variations in physiological stress parameters. Five genes involved in the functioning of the HPA axis regarding stress responses are examined in this thesis. They are: corticotropin-releasing hormone (CRH), the glucocorticoid receptor (GR), the mineralocorticoid receptor (MR), the 5-hydroxytryptamine-transporter-linked polymorphic region (5-HTTLPR) in the serotonin transporter (5-HTT) and the brain-derived neurotrophic factor (BDNF) gene. Two hundred thirty-two healthy participants were genotyped. The influence of genetic factors on physiological parameters, such as post-awakening cortisol and blood pressure was assessed, as well as the influence of genetic factors on stress reactivity in response to a socially evaluated cold pressor test (SeCPT). Three studies tested the HPA-related genes each on three different levels. The first study examined the influences of genotypes and haplotypes of these five genes on physiological as well as psychological stress indicators (Chapter 2). The second study examined the effects of GR variants (genotypes and haplotypes) and promoter methylation level on both the SAM system and the HPA axis stress reactivity (Chapter 3). The third study comprised the characterization of CRH promoter haplotypes in an in-vitro study and the association of the CRH promoter with stress indicators in vivo (Chapter 4).
In order to investigate the psychobiological consequences of acute stress under laboratory conditions, a wide range of methods for socially evaluative stress induction have been developed. The present dissertation is concerned with evaluating a virtual reality (VR)-based adaptation of one of the most widely used of those methods, the Trier Social Stress Test (TSST). In the three empirical studies collected in this dissertation, we aimed to examine the efficacy and possible areas of application of the adaptation of this well-established psychosocial stressor in a virtual environment. We found that the TSST-VR reliably incites the activation of the major stress effector systems in the human body, albeit in a slightly less pronounced way than the original paradigm. Moreover, the experience of presence is discussed as one potential factor of influence in the origin of the psychophysiological stress response. Lastly, we present a use scenario for the TSST-VR in which we employed the method to investigate the effects of acute stress on emotion recognition performance. We conclude that, due to its advantages concerning versatility, standardization and economic administration, the paradigm harbors enormous potential not only for psychobiological research, but other applications such as clinical practice as well. Future studies should further explore the underlying effect mechanisms of stress in the virtual realm and the implementation of VR-based paradigms in different fields of application.
Entrepreneurship has become an essential phenomenon all over the world because it is a major driving force behind the economic growth and development of a country. It is widely accepted that entrepreneurship development in a country creates new jobs, pro-motes healthy competition through innovation, and benefits the social well being of individuals and societies. The policymakers in both developed and developing countries focus on entrepreneurship because it helps to alleviate impediments to economic development and social welfare. Therefore, policymakers and academic researchers consider the promotion of entrepreneurship as essential for the economy and research-based support is needed for further development of entrepreneurship activities.
The impact of entrepreneurial activities on economic and social development also varies from country to country. The effect of entrepreneurial activities on economic and social development also varies from country to country because the level of entrepreneur-ship activities also varies from one region to another or one country to another. To under-stand these variations, policymakers have investigated the determinants of entrepreneur-ship at different levels, such as the individual, industry, and country levels. Moreover, entrepreneurship behavior is influenced by various personal and environmental level factors. However, these personal-level factors cannot be separated from the surrounding environment.
The link between religion and entrepreneurship is well established and can be traced back to Weber (1930). Researchers have analyzed the relationship between religion and entrepreneurship from various perspectives, and the research related to religion and entrepreneurship is diversified and scattered across disciplines. This dissertation tries to explain the link between religion and entrepreneurship, specifically Islamic religion and entrepreneurship. Technically this dissertation comprises three parts. The first part of this dissertation consists of two chapters that discuss the definition and theories of entrepreneurship (Chapter 2) and the theoretical relationship between religion and entrepreneur-ship (Chapter 3).
The second part of this dissertation (Chapter 4) provides an overview of the field with a purpose to gain a better understanding of the field’s current state of knowledge to bridge the different views and perspectives. In order to provide an overview of the field, a systematic literature search leading to a descriptive overview of the field based on 270 articles published in 163 journals Subsequently, bibliometric methods are used to identify thematic clusters, the most influential authors and articles, and how they are connected.
The third part of this dissertation (Chapter 5) empirically evaluates the influence of Islamic values and Islamic religious practices on entrepreneurship intentions within the Islamic community. Using the theory of planned behavior as a theoretical lens, we also take into account that the relationship between religion and entrepreneurial intentions can be mediated by individual’s attitude towards entrepreneurship. A self-administrative questionnaire was used to collect the responses from a sample of 1895 Pakistani university students. A structured equation modeling was adopted to perform a nuanced assessment of the relationship between Islamic values and practices and entrepreneurship intentions and to account for mediating effect of attitude towards entrepreneurship.
The research on religion and entrepreneurship has increased sharply during the last years and is scattered across various academic disciplines and fields. The analysis identifies and characterize the most important publications, journals, and authors in the area and map the analyzed religions and regions. The comprehensive overview of previous studies allows us to identify research gaps and derive avenues for future research in a substantiated way. Moreover, this dissertation helps the research scholars to understand the field in its entirety, identify relevant articles, and to uncover parallels and differences across religions and regions. Besides, the study reveals a lack of empirical research related to specific religions and specific regions. Therefore, scholars can take these regions and religions into consideration when conducting empirical research.
Furthermore, the empirical analysis about the influence of Islamic religious values and Islamic religious practices show that Islamic values served as a guiding principle in shaping people’s attitudes towards entrepreneurship in an Islamic community; they had an indirect influence on entrepreneurship intention through attitude. Similarly, the relationship between Islamic religious practices and the entrepreneurship intentions of students was fully mediated by the attitude towards entrepreneurship. Furthermore, this dissertation contributes to prior research on entrepreneurship in Islamic communities by applying a more fine-grained approach to capture the link between religion and entrepreneurship. Moreover, it contributes to the literature on entrepreneurship intentions by showing that the influence of religion on entrepreneurship intentions is mainly due to religious values and practices, which shape the attitude towards entrepreneurship and thereby influence entrepreneurship intentions in religious communities. The entrepreneur-ship research has put a higher emphasis on assessing the influence of a diverse set of con-textual factors. This dissertation introduces Islamic values and Islamic religious practices as critical contextual factors that shape entrepreneurship in countries that are characterized by the Islamic religion.
Why they rebel peacefully: On the violence-reducing effects of a positive attitude towards democracy
Under the impression of Europe’s drift into Nazism and Stalinism in the first half of the 20th century, social psychological research has focused strongly on dangers inherent in people’s attachment to a political system. The dissertation at hand contributes to a more differentiated perspective by examining violence-reducing aspects of political system attachment in four consecutive steps: First, it highlights attachment to a social group as a resource for violence prevention on an intergroup level. The results suggest that group attachment fosters self-control, a well-known protective factor against violence. Second, it demonstrates violence-reducing influences of attachment on a societal level. The findings indicate that attachment to a democracy facilitate peaceful and prevent violent protest tendencies. Third, it introduces the concept of political loyalty, defined as a positive attitude towards democracy, in order to clarify the different approaches of political system attachment. A set of three studies show the reliability and validity of a newly developed political loyalty questionnaire that distinguishes between affective and cognitive aspects. Finally, the dissertation differentiates former findings with regard to protest tendencies using the concept of political loyalty. A set of two experiments show that affective rather than cognitive aspects of political loyalty instigate peaceful protest tendencies and prevent violent ones. Implications of this dissertation for political engagement and peacebuilding as well as avenues for future research are discussed.
This dissertation details how Zeami (ca. 1363 - ca.1443) understood his adoption of the heavenly woman dance within the historical conditions of the Muromachi period. He adopted the dance based on performances by the Ōmi troupe player Inuō in order to expand his own troupe’s repertoire to include a divinely powerful, feminine character. In the first chapter, I show how Zeami, informed by his success as a sexualized child in the service of the political elite (chigo), understood the relationship between performer and audience in gendered terms. In his treatises, he describes how a player must create a complementary relationship between patron and performer (feminine/masculine or yin/yang) that escalates to an ecstasy of successful communication between the two poles, resembling sexual union. Next, I look at how Zeami perceived Inuō’s relationships with patrons, the daimyo Sasaki Dōyo in chapter two and shogun Ashikaga Yoshimitsu in chapter three. Inuō was influenced by Dōyo’s masculine penchant for powerful, awe-inspiring art, but Zeami also recognized that Inuō was able to complement Dōyo’s masculinity with feminine elegance (kakari and yūgen). In his relationship with Yoshimitsu, Inuō used the performance of subversion, both in his public persona and in the aesthetic of his performances, to maintain a rebellious reputation appropriate within the climate of conflict among the martial elite. His play “Aoi no ue” draws on the aristocratic literary tradition of the Genji monogatari, giving Yoshimitsu the role of Prince Genji and confronting him with the consequences of betrayal in the form of a demonic, because jilted, Lady Rokujō. This performance challenged Zeami’s early notion that the extreme masculinity of demons and elegant femininity as exemplified by the aristocracy must be kept separate in character creation. In the fourth chapter, I show how Zeami also combined dominance (masculinity) and submission (femininity) in the corporal capacity of a single player when he adopted the heavenly woman dance. The heavenly woman dance thus complemented not only the masculinity of his male patrons with femininity but also the political power of his patrons with another dominant power, which plays featuring the heavenly woman dance label divine rather than masculine.
Theoretical and empirical research assumes a negative development of student achievement motivation over the course of their school careers (i.e., mean-level declines of achievement motivation). However, the exact magnitude of this motivational change remains elusive and it is unclear whether different motivational constructs show similar developmental trends. Furthermore, it is unknown whether motivational declines are related to a particular school stage (i.e., elementary, middle, or high school) or the school transition, and which additional changes are associated with motivational decreases (e.g., changes in student achievement). Finally, previous research has remained inconsistent regarding the question whether ability grouping of students helps prevent motivational declines or results in additional motivational “costs” for students.
This dissertation presents three articles that were designed to address these research questions. In Article 1, a meta-analysis based on 107 independent longitudinal studies investigated student mean-level changes in self-esteem, academic self-concept, academic self-efficacy, intrinsic motivation, and achievement goals from first to 13th grade. Article 2 comprised two longitudinal studies with German adolescents (Study: n = 745 students assessed in four waves in grades 5-7; Study 2: n = 1420 students assessed in four waves in grades 5-8). Both longitudinal studies investigated the separate and the joint development of achievement goals, interest, and achievement in math. In Article 3, a longitudinal study (n = 296 high-ability students assessed in four waves in grades 5-7) investigated the effects of full-time ability grouping on student development of academic self-concept and achievement in math.
The meta-analysis revealed significant decreases in math and language academic self-concept, intrinsic motivation, and mastery and performance-approach goals, whereas no significant changes in self-esteem, general academic self-concept, academic self-efficacy, and performance-avoidance goals were found. Interestingly, motivational declines were not related to school stage or school transition. In Article 2, decreases in interest and mastery, performance-approach, and performance-avoidance goals were indicated by both longitudinal studies. Development of mastery and performance-approach goals was positively related or unrelated to development in interest and achievement, whereas development of performance-avoidance goals was negatively related or unrelated to development of interest and achievement. Finally, the longitudinal study in Article 3 revealed no significant change in student academic self-concept in math over time. Ability grouping showed no positive or negative effects on student academic self-concept. However, high-ability students that were grouped together demonstrated greater gains in their achievement than high-ability students in regular classes.
This dissertation investigates corporate acquisition decisions that represent important corporate development activities for family and non-family firms. The main research objective of this dissertation is to generate insights into the subjective decision-making behavior of corporate decision-makers from family and non-family firms and their weighting of M&A decision-criteria during the early pre-acquisition target screening and selection process. The main methodology chosen for the investigation of M&A decision-making preferences and the weighting of M&A decision criteria is a choice-based conjoint analysis. The overall sample of this dissertation consists of 304 decision-makers from 264 private and public family and non-family firms from mainly Germany and the DACH-region. In the first empirical part of the dissertation, the relative importance of strategic, organizational and financial M&A decision-criteria for corporate acquirers in acquisition target screening is investigated. In addition, the author uses a cluster analysis to explore whether distinct decision-making patterns exist in acquisition target screening. In the second empirical part, the dissertation explores whether there are differences in investment preferences in acquisition target screening between family and non-family firms and within the group of family firms. With regards to the heterogeneity of family firms, the dissertation generated insights into how family-firm specific characteristics like family management, the generational stage of the firm and non-economic goals such as transgenerational control intention influences the weighting of different M&A decision criteria in acquisition target screening. The dissertation contributes to strategic management research, in specific to M&A literature, and to family business research. The results of this dissertation generate insights into the weighting of M&A decision-making criteria and facilitate a better understanding of corporate M&A decisions in family and non-family firms. The findings show that decision-making preferences (hence the weighting of M&A decision criteria) are influenced by characteristics of the individual decision-maker, the firm and the environment in which the firm operates.
In the modeling context, non-linearities and uncertainty go hand in hand. In fact, the utility function's curvature determines the degree of risk-aversion. This concept is exploited in the first article of this thesis, which incorporates uncertainty into a small-scale DSGE model. More specifically, this is done by a second-order approximation, while carrying out the derivation in great detail and carefully discussing the more formal aspects. Moreover, the consequences of this method are discussed when calibrating the equilibrium condition. The second article of the thesis considers the essential model part of the first paper and focuses on the (forward-looking) data needed to meet the model's requirements. A large number of uncertainty measures are utilized to explain a possible approximation bias. The last article keeps to the same topic but uses statistical distributions instead of actual data. In addition, theoretical (model) and calibrated (data) parameters are used to produce more general statements. In this way, several relationships are revealed with regard to a biased interpretation of this class of models. In this dissertation, the respective approaches are explained in full detail and also how they build on each other.
In summary, the question remains whether the exact interpretation of model equations should play a role in macroeconomics. If we answer this positively, this work shows to what extent the practical use can lead to biased results.
Internet interventions have gained popularity and the idea is to use them to increase the availability of psychological treatment. Research suggests that internet interventions are effective for a number of psychological disorders with effect sizes comparable to those found in face-to-face treatment. However, when provided as an add-on to treatment as usual, internet interventions do not seem to provide additional benefit. Furthermore, adherence and dropout rates vary greatly between studies, limiting the generalizability of the findings. This underlines the need to further investigate differences between internet interventions, participating patients, and their usage of interventions. A stronger focus on the processes of change seems necessary to better understand the varying findings regarding outcome, adherence and dropout in internet interventions. Thus, the aim of this dissertation was to investigate change processes in internet interventions and the factors that impact treatment response. This could help to identify important variables that should be considered in research on internet interventions as well as in clinical settings that make use of internet interventions.
Study I (Chapter 5) investigated early change patterns in participants of an internet intervention targeting depression. Data from 409 participants were analyzed using Growth Mixture Modeling. Specifically a piecewise model was applied to model change from screening to registration (pretreatment) and early change (registration to week four of treatment). Three early change patterns were identified; two were characterized by improvement and one by deterioration. The patterns were predictive of treatment outcome. The results therefore indicated that early change should be closely monitored in internet interventions, as early change may be an important indicator of treatment outcome.
Study II (Chapter 6) picked up on the idea of analyzing change patterns in internet interventions and extended it by using the Muthen-Roy model to identify change-dropout patterns. A sligthly bigger sample of the dataset from Study I was analyzed (N = 483). Four change-dropout patterns emerged; high risk of dropout was associated with rapid improvement and deterioration. These findings indicate that clinicians should consider how dropout may depend on patient characteristics as well as symptom change, as dropout is associated with both deterioration and a good enough dosage of treatment.
Study III (Chapter 7) compared adherence and outcome in different participant groups and investigated the impact of adherence to treatment components on treatment outcome in an internet intervention targeting anxiety symptoms. 50 outpatient participants waiting for face- to-face treatment and 37 self-referred participants were compared regarding adherence to treatment components and outcome. In addition, outpatient participants were compared to a matched sample of outpatients, who had no access to the internet intervention during the waiting period. Adherence to treatment components was investigated as a predictor of treatment outcome. Results suggested that especially adherence may vary depending on participant group. Also using specific measures of adherence such as adherence to treatment components may be crucial to detect change mechanisms in internet interventions. Fostering adherence to treatment components in participants may increase the effectiveness of internet interventions.
Results of the three studies are discussed and general conclusions are drawn.
Implications for future research as well as their utility for clinical practice and decision- making are presented.
Auf der Grundlage einer Fragebogenstudie wurden unterschiedliche Elemente eines förderlichen Umgangs mit Gesundheitsinformationen betrachtet und ihre Zusammenhänge mit personspezifischen Merkmalen analysiert. Als zentrale Aspekte der Informationsprozesse wurden die drei Elemente Gesundheitsinformationskompetenz, Gesundheitsinteresse und gesundheitsspezifische Informationsgewohnheiten konzeptuell voneinander getrennt. Auf der Basis des bisherigen Forschungsstands wurde zunächst ein theoretisches Modell des Umgangs mit Gesundheitsinformationen entwickelt, das die Bedeutung der Kompetenz und des Interesses für gesundheitsbezogene Informationsgewohnheiten hervorhebt, individuelle Ausprägungen dieser drei Elemente mit soziodemografischen Faktoren, Persönlichkeitseigenschaften, Überzeugungen und dem Gesundheitszustand in Beziehung setzt sowie Verbindungen zu gesundheitsrelevanten Verhaltensweisen beschreibt. Dieses Modell wurde anschließend an einer Stichprobe von 352 Berufsschülerinnen und -schülern aus drei Berufsbereichen (Wirtschaft/Verwaltung, Technik und Gesundheit) empirisch überprüft. Über multiple Regressionsanalysen wurden bedeutsame Prädiktoren für die drei Hauptelemente Kompetenz, Interesse und Informationsgewohnheiten identifiziert, über logistische Regressionen und Korrelationen ihre Zusammenhänge mit dem Gesundheitsverhalten überprüft. Darüber hinaus wurden lineare Strukturgleichungsmodelle zur Vorhersage des Informationsverhaltens entwickelt. Die Ergebnisse bestätigen die konzeptionelle Trennung der drei Faktoren, die jeweils mit unterschiedlichen Prädiktoren verbunden waren. Auf der Basis der Befunde werden Ansatzpunkte für die weitere Forschung und die Förderung eines kompetenten Umgangs mit Gesundheitsinformationen diskutiert.
Bei Albert Dietz und Bernhard Grothe handelt es sich um zwei bedeutende Architekten im französisch-saarländischen Grenzgebiet. Sie gründeten 1952 eine Arbeitsgemeinschaft mit dem Ziel, auf gemeinschaftlicher Basis den nach dem Krieg entstandenen Bedarf an profanen und sakralen Wiederaufbau- und Neubaumaßnahmen in ihren Bauwerken möglichst effektiv reaslisieren zu können. Diese Arbeit befaßt sich ausschließlich mit den Sakralbauten, die deren künstlerische und architektonische Leistungen auf anschauliche Weise demonstrieren und belegen.
Global food security poses large challenges to a fast changing human society and has been a key topic for scientists, agriculturist, and policy makers in the 21st century. The United Nation predicts a total world population of 9.15 billion in 2050 and defines the provision of food security as the second major point in the UN Sustainable Development Goals. As the capacities of both, land and water resources, are finite and locally heavily overused, reducing agriculture’s environmental impact while meeting an increasing demand for food of a constantly growing population is one of the greatest challenges of our century. Therefore, a multifaceted solution is required, including approaches using geospatial data to optimize agricultural food production.
The availability of precise and up-to-date information on vegetation parameters is mandatory to fulfill the requirements of agricultural applications. Direct field measurements of such vegetation parameters are expensive and time-consuming. On the contrary, remote sensing offers a variety of techniques for a cost-effective and non-destructive retrieval of vegetation parameters. Although not widely used, hyperspectral thermal infrared (TIR) remote sensing has demonstrated being a valuable addition to existing remote sensing techniques for the retrieval of vegetation parameters.
This thesis examined the potential of TIR imaging spectroscopy as an important contribution to the growing need of food security. The main scientific question dealt with the extraction of vegetation parameters from imaging TIR spectroscopy. To this end, two studies impressively demonstrated the ability of extracting vegetation related parameters from leaf emissivity spectra: (i) the discrimination of eight plant species based on their emissivity spectra and (ii) the detection of drought stress in potato plants using temperature measures and emissivity spectra.
The datasets used in these studies were collected using the Telops Hyper-Cam LW, a novel imaging spectrometer. Since this FTIR spectrometer presents some particularities, special attention was paid on the development of dedicated experimental data acquisition setups and on data processing chains. The latter include data preprocessing and the development of algorithms for extracting precise surface temperatures, reproducible emissivity spectra and, in the end, vegetation parameters.
The spectrometer’s versatility allows the collection of airborne imaging spectroscopy datasets. Since the general availability of airborne TIR spectrometers is limited, the preprocessing and
data extraction methods are underexplored compared to reflective remote sensing. This counts especially for atmospheric correction (AC) and temperature and emissivity separation (TES) algorithms. Therefore, we implemented a powerful simulation environment for the development of preprocessing algorithms for airborne hyperspectral TIR image data. This simulation tool is designed in a modular way and includes the image data acquisition and processing chain from surface temperature and emissivity to the final at-sensor radiance data. It includes a series of available algorithms for TES, AC as well as combined AC and TES approaches. Using this simulator, one of the most promising algorithms for the preprocessing of airborne TIR data – ARTEMISS – was significantly optimized. The retrieval error of the atmospheric water vapor during the atmospheric characterization was reduced. As a result, this improvement in atmospheric characterization accuracy enhanced the subsequent retrieval of surface temperatures and surface emissivities intensely.
Although, the potential of hyperspectral TIR applications in ecology, agriculture, and biodiversity has been impressively demonstrated, a serious contribution to a global provision of food security requires the retrieval of vegetation related parameters with global coverage, high spatial resolution and at high revisit frequencies.
Emerging from the findings in this thesis, the spectral configuration of a spaceborne TIR spectrometer concept was developed. The sensors spectral configuration aims at the retrieval of precise land surface temperatures and land surface emissivity spectra. Complemented with additional characteristics, i.e. short revisit times and a high spatial resolution, this sensor potentially allows the retrieval of valuable vegetation parameters needed for agricultural optimizations. The technical feasibility of such a sensor concept underlines the potential contribution to the multifaceted solution required for achieving the challenging goal of guaranteeing global food security in a world of increasing population.
In conclusion, thermal remote sensing and more precisely hyperspectral thermal remote sensing has been presented as a valuable technique for a variety of applications contributing to the final goal of a global food security.
This dissertation deals with consistent estimates in household surveys. Household surveys are often drawn via cluster sampling, with households sampled at the first stage and persons selected at the second stage. The collected data provide information for estimation at both the person and the household level. However, consistent estimates are desirable in the sense that the estimated household-level totals should coincide with the estimated totals obtained at the person-level. Current practice in statistical offices is to use integrated weighting. In this approach consistent estimates are guaranteed by equal weights for all persons within a household and the household itself. However, due to the forced equality of weights, the individual patterns of persons are lost and the heterogeneity within households is not taken into account. In order to avoid the negative consequences of integrated weighting, we propose alternative weighting methods in the first part of this dissertation that ensure both consistent estimates and individual person weights within a household. The underlying idea is to limit the consistency conditions to variables that emerge in both the personal and household data sets. These common variables are included in the person- and household-level estimator as additional auxiliary variables. This achieves consistency more directly and only for the relevant variables, rather than indirectly by forcing equal weights on all persons within a household. Further decisive advantages of the proposed alternative weighting methods are that original individual rather than the constructed aggregated auxiliaries are utilized and that the variable selection process is more flexible because different auxiliary variables can be incorporated in the person-level estimator than in the household-level estimator.
In the second part of this dissertation, the variances of a person-level GREG estimator and an integrated estimator are compared in order to quantify the effects of the consistency requirements in the integrated weighting approach. One of the challenges is that the estimators to be compared are of different dimensions. The proposed solution is to decompose the variance of the integrated estimator into the variance of a reduced GREG estimator, whose underlying model is of the same dimensions as the person-level GREG estimator, and add a constructed term that captures the effects disregarded by the reduced model. Subsequently, further fields of application for the derived decomposition are proposed such as the variable selection process in the field of econometrics or survey statistics.
Thema dieser Dissertation ist das deutsche Selbstbildnis im 17. Jahrhundert. Ziel der Arbeit war es, das deutsche Selbstbildnis als eigene Gattung zu etablieren. Hierzu wurden die Selbstbildnisse deutscher Maler des 17. Jahrhunderts ausgewählt, gilt doch diese Zeit noch immer als ‚totes Jahrhundert‘. Grundlage der Untersuchung war eine Sammlung von 148 Objekten, die einer grundlegenden Analyse unterzogen wurden. Das früheste Selbstbildnis in dieser Sammlung stammt von 1600, das späteste wurde um 1700 angefertigt. Künstler aus dem gesamten Alten Reich, ob aus Schlesien und Böhmen, Nord-oder Süddeutschland oder aus den österreichischen wie schweizerischen Landen sind hier vertreten. Die Selbstbildnisse stammen von Malern in der gesamten breite ihrer Karriere. So sind gleichermaßen Selbstbildnisse von Gesellen wie Meistern, von Hofmalern bis hin zu Freimeistern vertreten. Besonders wichtig war es, nicht nur Selbstbildnisse im Gemälde oder Kupferstich in die Untersuchung aufzunehmen, sondern auch Stammbucheinträge.
Die ausführliche Betrachtung und Gegenüberstellung der deutschen Selbstbildnisse mit denen ihrer europäischen Kollegen hat gezeigt, dass auch deutsche Maler den gängigen Darstellungstypen wie etwa dem virtuoso folgten. Aber die deutschen Maler imitierten nicht nur, sondern experimentierten und gingen mit ihren Vorbildern spielerisch um. Daneben folgten sie natürlich auch den Trends der Selbstinszenierung. Sie drückten in ihren Selbstbildnissen ihren Wunsch nach sozialer und gesellschaftlicher Emanzipation des gesamten Berufsstandes aus. So war das deutsche Selbstbildnis eigenständiger Ausdruck des Aufbruches deutscher Künstler in eine neue Zeit.
Competitive analysis is a well known method for analyzing online algorithms.
Two online optimization problems, the scheduling problems and the list accessing problems, are considered in the thesis of Yida Zhu in the respect of this method.
For both problems, several existing online and offline algorithms are studied. Their performances are compared with the performances of corresponding offline optimal algorithms.
In particular, the list accessing algorithm BIT is carefully reviewed.
The classical proof of its worst case performance get simplified by adapting the knowledge about the optimal offline algorithm.
With regard to average case analysis, a new closed formula is developed to determine the performance of BIT on specific class of instances.
All algorithm considered in this thesis are also implemented in Julia.
Their empirical performances are studied and compared with each other directly.
This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.