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Maximizing the value from data has become a key challenge for companies as it helps improve operations and decision making, enhances products and services, and, ultimately, leads to new business models. While enterprise architecture (EA) management and modeling have proven their value for IT-related projects, the support of enterprise architecture for data-driven business models (DDBMs) is a rather new and unexplored field. The research group argues that the current understanding of the intersection of data-driven business model innovation and enterprise architecture is incomplete because of five challenges that have not been addressed in existing research: (1) lack of knowledge of how companies design and realize data-driven business models from a process perspective, (2) lack of knowledge on the implementation phase of data-driven business models, (3) lack of knowledge on the potential support enterprise architecture modeling and management can provide to data-driven business model endeavors, (4) lack of knowledge on how enterprise architecture modeling and management support data-driven business model design and realization in practice, (5) lack of knowledge on how to deploy data-driven business models. The researchers address these challenges by examining how enterprise architecture modeling and management can benefit data-driven business model innovation. The mixed-method approach of this thesis draws on a systematic literature review, qualitative empirical research as well as the design science research paradigm. The investigators conducted a systematic literature search on data-driven business models and enterprise architecture. Considering the novelty of data-driven business models for academia and practice, they conducted explorative qualitative research to explain "why" and "how" companies embark on realizing data-driven business models. Throughout these studies, the primary data source was semi-structured interviews. In order to provide an artifact for DDBM innovation, the researchers developed a theory for design and action. The data-driven business model innovation artifact was inductively developed in two design iterations based on the design science paradigm and the design science research framework.
Entwicklungen und Potenziale der Kultur- und Kreativwirtschaft im ländlichen Raum - Der Kreis Höxter
(2014)
In der vorliegenden Thesis wird ein interdisziplinäres, exploratives und handlungsorientiertes Problemgerüst durchleuchtet. Als übergeordneter Forschungsgegenstand wird zum einen der Stadt-Land-Unterschied im Rahmen kultur- und kreativwirtschaftlicher Strukturentwicklung betrachtet. Zum anderen werden konkrete Handlungsoptionen zur Förderung der Wirtschaftsbranche für regionalpolitisch Verantwortliche in ländlichen Räumen entworfen und aufgezeigt. Folgende Leitfragen werden herangezogen: Welche standortfaktoriellen Vorteile bezüglich der wirtschaftlichen, sozialen und kulturellen Rahmenbedingungen bieten ländliche Räume für die Kultur- und Kreativwirtschaft (im Gegensatz zu städtischen Räumen)? Welche Handlungsspielräume haben regional- und wirtschaftspolitisch Verantwortliche im Hinblick auf die kulturelle Entwicklung von ländlichen Räumen? Wie lässt sich konkret eine im Sinne der Standortattraktivität agierende Wirtschaftsförderung mit einer Stärkung der Kulturlandschaft vereinbaren?
Analysis of User Behavior
(2020)
Online behaviors analysis consists of extracting patterns from server-logs. The works presented here were carried out within the "mBook" project which aimed to develop indicators of the quantity and quality of the learning process of pupils from their usage of an eponymous electronic textbook for History. In this thesis, the research group investigates several models that adopt different points of view on the data. The studied methods are either well established in the field of pattern mining or transferred from other fields of machine learning and data mining. The authors improve the performance of archetypal analysis in large dimensions and apply it to unveil correlations between visibility time of particular objects in the e-textbook and pupils' motivation. They present next two models based on mixtures of Markov chains. The first extracts users' weekly browsing patterns. The second is designed to process essions at a fine resolution, which is sine qua non to reveal the significance of scrolling behaviors. The authors also propose a new paradigm for online behaviors analysis that interprets sessions as trajectories within the page-graph. In this respect, they establish a general framework for the study of similarity measures between spatio-temporal trajectories, for which the study of sessions is a particular case. Finally, they construct two centroid-based clustering methods using neural networks and thus lay the foundations for unsupervised behaviors analysis using neural networks.
Technological development made it possible to store and process data on a scale not imaginable decades ago — a development that also includes network data. A particular characteristic of network data is that, unlike standard data, the objects of interest, called nodes, have relationships to (possibly all) other objects in the network. Collecting empirical data is often complicated and cumbersome, hence, the observed data are typically incomplete and might also contain other types of errors. Because of the interdependent structure of network data, these errors have a severe impact on network analysis methods. This cumulative dissertation is about the impact of erroneous network data on centrality measures, which are methods to assess the position of an object, for example a person, with respect to all other objects in a network. Existing studies have shown that even small errors can substantially alter these positions. The impact of errors on centrality measures is typically quantified using a concept called robustness. The articles included in this dissertation contribute to a better understanding of the robustness of centrality measures in several aspects. It is argued why the robustness needs to be estimated and a new method is proposed. This method allows researchers to estimate the robustness of a centrality measure in a specific network and can be used as a basis for decision making. The relationship between network properties and the robustness of centrality measures is analyzed. Experimental and analytical approaches show that centrality measures are often more robust in networks with a larger average degree. The study of the impact of non-random errors on the robustness suggests that centrality measures are often more robust if missing nodes are more likely to belong to the same community compared to missingness completely at random. For the development of imputation procedures based on machine learning techniques, a process for the evaluation of node embedding methods is proposed.
Zusammenfassung Der vorliegende Bericht informiert über die Ergebnisse einer empirischen Studie zur Personalarbeit in wissenschaftlichen Buchverlagen. Als Grundlage der Erhebung dienten verschiedene theoretische Konzepte, die sich mit der Frage befassen, welche Grundmuster das Personalgeschehen von Unternehmen prägen. Das primäre Ziel unserer Studie bestand entsprechend darin, zu erkunden, inwieweit es gelingen kann – mit Hilfe einer Unternehmensbefragung – etwas über diese Grundmuster zu erfahren. Das Ergebnis stimmt zuversichtlich. Die theoretische Fundierung unserer Umfrage erwies sich als sehr tragfähig und empfiehlt sich für weiterführende und branchenübergreifende Vergleichsstudien. Leider war es uns an dieser Stelle noch nicht möglich, eine „großzahlige“ Erhebung durchzuführen, die Datenbasis, auf der unsere Ergebnisse beruhen, ist mit 12 Unternehmen denn auch einigermaßen schmal. Angesichts unserer Zielsetzung ist dies aber nur bedingt ein Mangel. Inhaltlich zeigt sich, dass die Personalpolitik der Verlage im Großen und Ganzen einem Schema folgt, das sich aus den branchentypischen Anforderungen ableitet. Andererseits findet man aber auch verlagsspezifische Akzentuierungen. In manchen Verlagen dominiert eher eine gemeinschaftliche Orientierung (in ihren jeweiligen Varianten), in anderen werden die leistungs- und managementorientierten Aspekte der Personalarbeit stärker betont.
This cumulative dissertation deals with the association between corporate governance, corporate finance and corporate tax avoidance in four scientific articles. The aim of this dissertation is to explain corporate tax avoidance by (a) focusing on corporate governance institutions as determinants of tax avoidance and (b) focusing on financial consequences of tax avoidance. Due to the close association between corporate governance and the concept of corporate social responsibility (CSR), the relationship between CSR and tax avoidance is also addressed. The first article using structured literature review methodology, analyzes extant research on the association between corporate governance and tax avoidance based on stakeholder-agency theory. However, also classical principal-agent theory is taken into account as its classical foundation. The first article identifies a number of open research questions and thereby serves as a theoretical basis for the subsequent articles. The second article also using structured literature review methodology, analyzes extant research on the association between CSR and tax avoidance. This article is also based on stakeholder-agency theory and identifies open research questions. The third article based on results of the first article, investigates tax avoidance by German private family firms as a specific variant of corporate governance, using an empirical quantitative approach. The article finds that (a) German private family firms avoid more tax than non-family firms, that (b) tax avoidance is positively associated with the capital stake of the family and that (c) tax avoidance is positively associated with the number of shareholders in both family and non-family firms. Results reinforce that corporate tax avoidance is associated to conflicts among the shareholders of private firms. The fourth article investigates the cost of debt of German public firms as a function of tax avoidance and tax risk. The article finds that (a) tax avoidance is negatively associated to the cost of debt, that (b) tax risk is positively associated to the cost of debt and that (c) the association between tax avoidance and the cost of debt becomes negative when a high level of tax risk is present.
Der Wandel des Energiesystems ist eine der zentralen Nachhaltigkeitstransformationen, denen sich die Forschung widmet. Wie für die Transition-Forschung verschiedentlich festgestellt, besteht allerdings eine gewisse Lücke bei der Frage, wie Nachhaltigkeitstransformationen organisiert und finanziert werden. Insbesondere fehlt es an einer Ausdifferenzierung und vertieften Analyse einzelner institutionell-organisatorischer Lösungen und an einer Darstellung im Zusammenhang der komplexen sozio-ökologisch-technischen Systeme, in die konkrete Organisationslösungen für eine nachhaltige Energieversorgung eingebunden sind. In der vorliegenden Arbeit werden mit genossenschaftlichen Ansätzen, also Organisationslösungen mit (Teil-)Eigentum der Bürger an den Anlagen, spezifische hybride finanzielle Arrangements im Energiesektor in den Fokus gerückt. Dem institutionenanalytischen Ansatz der Bloomington School folgend wird im Rahmenpapier und insgesamt sechs Fachartikeln der Frage nachgegangen, welche Formen genossenschaftlicher Ansätze im Globalen Norden und Globalen Süden anzutreffen sind und welche Rolle diesen in den Transformationsprozessen des jeweiligen Energiesystems zukommt. Für die Analyse wird auf das Social-Ecological Systems Framework zurückgegriffen, das für die einzelnen Untersuchungen modifiziert bzw. konkretisiert wird. Im Einzelnen wird in den Fachartikeln ein Überblick über die Erkenntnisse zu genossenschaftlichen Ansätzen im Globalen Süden gegeben, auf der Makroebene den wechselnden politischen Prozessen von Koordination und Contestation nachgegangen, auf der Mesoebene die Entwicklungen von Windenergiegenossenschaften in Belgien, Dänemark, Deutschland und dem Vereinigten Königreich vergleichend analysiert, der Zusammenhang von Finanz- und Energiesystem untersucht und für diesen Kontext Gerechtigkeitsnormen konkretisiert und schließlich auf der Mikroebene die Inklusivität von Bürgerenergieinitiativen näher betrachtet und Unterschiede in den Investitionsmotiven verschiedener Bürgerenergieakteure herausgearbeitet.
The dissertation analyzes the role of large banks in the context of financial (in)stability. Based on the underlying "too big to fail"-problem (TBTF), the three included papers investigate the reasons for the instability of banking systems on a national and international level. Already in advance, but at least since the years 2007/2008 with the escalation of the financial crisis, especially large banks are under critical supervision of regulators and the society. There exist numerous aspects that should to be taken into account when addressing TBTF which complicates the finding of a solution to the problem. In particular, the thesis investigates three major issues in this context: (1) The contribution of the size of a bank to the development of financial crises or the exposure of large banks to systematic risk and contagious spillovers. (2) The spillover effects from one banking system to another and the importance of banks' foreign asset holdings for the transmission of sovereign risk on foreign banks. (3) The impact of the degree of competition in the German banking market on the stability of the banking system.
This paper-based dissertation deals with capital structures and tax policies of German family businesses. Family firms as the predominant company form in Germany are mainly characterized by the overlapping of the two spheres family and business, both having different goal systems and preferences. This also has an impact on decision making with regard to corporate finance including the application of tax avoidance policies. In Germany, bank finance is the dominant financing source for family firms but there is a preference for internal finance since it comes along with more external independency. Extant research usually bases its results on samples of publicly listed companies. These studies come up with different results regarding family firms' actual financing preferences and capture their heterogeneity only to a very little extent. In this light, the present dissertation and its three papers examine different research questions in the context of capital structure decisions and tax avoidance in family firms. All the three papers apply a quantitative empirical research design. The first paper is a comparison between capital structures of family firms and non-family firms. The paper examines differences in bank debt and trade credit ratios. Overall, the findings show that family firms have significantly higher overall and long-term debt levels compared to their non-family counterparts. The identity as a family firm, which leads to a leap of faith by banks, can be a possible explanation for these results. The second paper is an in-depth examination of drivers of bank debt levels within the group of family firms. Further, it addresses heterogeneity amongst family firms and combines survey results and corresponding financial information. This represents a first attempt to capture family firm heterogeneity and its link to financial issues. The study shows that the more power in the company is exerted via management or supervisory board by the family, the less bank debt is used. Paper three is an extension of the previous two studies as it sheds light on tax avoidance, a significant instrument to strengthen the internal financing capability of a firm. This also takes up a research gap as there is very little research on taxation in family firms. Contrary to the expectation, the study reveals that private family firms might pay less tax than their non-family peers.