The following dissertation contains two unique empirical studies that contribute to the overall literature in the field of Financial Economics in the areas of mutual fund investing and financial intermediation and regulation. The first Chapter, entitled “The Impact of Macroeconomic Stress on the U.S. Financial Sector”, examines the relative impact of macroeconomic stress on financial and non-financial U.S. firms. Empirical results show that macroeconomic shocks appear to have a larger impact on financial firms. Additionally, the sensitivity of financial firms to macroeconomic events can be traced to the influence of non-depository institutions, or “shadow banks”, like finance and investment companies, which are less regulated than depository institutions. The results coincide with several trends in the financial sector including increased competition, complexity and interconnectedness and highlight the need for governance mechanisms that account for the risks associated with these factors. The second chapter, entitled “Partial Adjustment Towards Equilibrium Mutual Fund Allocations: Evidence from U.S.-based Equity Mutual Funds”, examines the relative efficiency of equity mutual funds in terms of speed of portfolio adjustment by applying a partial adjustment model. Empirical results show that mutual fund managers are able and willing to quickly adjust their portfolios when results have been sub-optimal, implying that the cost of persistent poor performance is perceived as being high. Managers can offset about 106 percent of the deviation within one period. Additionally, results show that funds that typically engage in the costly production of specialized information, like emerging market and sector funds have more efficient speeds of portfolio adjustment than more passive funds, like market index funds. The results imply that actively managed funds may have efficiency advantages that have been previously ignored in the empirical literature.

La Performance Sociétale de l’Entreprise (PSE) a reçu une attention croissante tant au plan théorique qu’empirique. Pourtant, elle reste souvent réduite à sa dimension « résultats », centrée sur la mesure. Par opposition, sa dimension managériale a été largement ignorée et le management des Parties Prenantes (PP), notion vague et indéterminée, constitue toujours l’unique levier managérial de la PSE proposé par la littérature. Cette thèse cherche à combler ce manque et propose une modélisation de la PSE qui considère explicitement le rôle des PP vis-à-vis de sa dimension managériale. Cette dernière est saisie à travers un ensemble de leviers managériaux situés à trois niveaux – stratégique, tactique et opérationnel. L’applicabilité du modèle aux stations de montagne est discutée à l’aide d’une revue systématique de la littérature pour rendre compte d’éventuelles spécificités propres à cette unité d’analyse. La méthodologie empirique, de nature exploratoire et confirmatoire, repose sur l’étude de 4 cas de stations de montagne situées dans les alpes françaises. Les données primaires issues de 71 entretiens semi-directifs et de questionnaires auprès de PP représentatives des sphères civile, politique et économique des stations ont été complétées par des données secondaires. Malgré le constat d’un certain « tropisme économique » dans les 4 stations étudiées, les résultats indiquent que les PP des stations ont un rôle à jouer aux trois niveaux du management de la performance sociétale et que l’intensité de ce rôle varie en fonction de leur légitimité et pouvoir. Ils montrent également que l’intégration des PP au management de la performance sociétale est une condition nécessaire pour permettre une réelle prise en compte de leurs responsabilités sociétales. Au plan théorique, cette thèse contribue à l’approche de la PSE par les PP par la prise en compte explicite de sa dimension managériale à côté de sa dimension « résultats ». Au plan managérial, elle débouche sur des recommandations utiles pour aider les stations de montagne à se saisir d’une performance élargie à ses composantes économiques, sociales et environnementales en réponse aux enjeux sociétaux auxquels elles font face / Corporate Social Performance (CSP) has received a significant attention from scholars and practitioners. However, the study of the concept is often limited to its “results” dimension, focusing on measurement only. On the other hand, its managerial dimension has mostly been ignored and the concept of “stakeholders management”, a rather vague and ambiguous one, remains as CSP only managerial lever in the literature. This research seeks to fill that gap and develops a new CSP model. Its new managerial dimension comprises a set of managerial levers at strategic, tactic and operational levels and explicitly takes stakeholders’ role into account. As this research focuses on mountain resorts, the model’s relevance for such a unit of analysis has been assessed by confronting it to mountain resorts’ specificities identified through a systematic literature review. From a methodological point of view, 4 mountain resorts located in the French Alps have been studied through two (exploratory and confirmatory) case study methodologies. Primary data consists of transcripts of the 71 semi-directive interviews conducted with stakeholders from the political, civilian and economic spheres in the 4 resorts. Secondary data has also been collected. Despite the “economic tropism” observed in all 4 resorts, results show that stakeholders have a role to play on each three levels of social performance management and that this role may vary according to stakeholders’ power and legitimacy in the resort. They also show that integrating stakeholders in social performance management is a mean, for them, to better take their social responsibilities into account. From a theoretical perspective, the research contributes to the stakeholders’ approach of CSP by explicitly taking its managerial dimension into account and replacing it next to its “results” dimension. From a managerial point of view, we propose recommendations to help mountain resorts to embrace a wider – economic, social and environmental – view of performance

Context. Large-scale software development projects are those consisting of a large number of teams, maybe even spread across multiple locations, and working on large and complex software tasks. That means that neither a team member individually nor an entire team holds all the knowledge about the software being developed and teams have to communicate and coordinate their knowledge. Therefore, teams and team members in large-scale software development projects must acquire and manage expertise as one of the critical resources for high-quality work. Objectives. We aim at understanding whether software teams in different contexts develop transactive memory systems (TMS) and whether well-developed TMS leads to performance benefits as suggested by research conducted in other knowledge-intensive disciplines. Because multiple factors may influence the development of TMS, based on related TMS literature we also suggest to focus on task allocation strategies, task characteristics and management decisions regarding the project structure, team structure and team composition. Methods. We use the data from two large-scale distributed development companies and 9 teams, including quantitative data collected through a survey and qualitative data from interviews to measure transactive memory systems and their role in determining team performance. We measure teams’ TMS with a latent variable model. Finally, we use focus group interviews to analyze different organizational practices with respect to team management, as a set of decisions based on two aspects: team structure and composition, and task allocation. Results. Data from two companies and 9 teams are analyzed and the positive influence of well-developed TMS on team performance is found. We found that in large-scale software development, teams need not only well-developed team’s internal TMS, but also have well- developed and effective team’s external TMS. Furthermore, we identified practices that help of hinder development of TMS in large-scale projects. Conclusions. Our findings suggest that teams working in large-scale software development can achieve performance benefits if transactive memory practices within the team are supported with networking practices in the organization.

This document deals with process approach and it´s use in measuring companies performance. It presents an overview of individual approaches, from traditional containing only financial indicators to modern ones using non-financial indicators and incorporating into the measurement the areas related to customers employees and more. The work also mentions the Quality Management System contained in ISO 9001: 2015 and it´s approach to performance measurement. The chapter about metrics covers performance measures, in particular key performance indicators, their purpose, properties and distribution. Here are also presented the procedures for their determination and the pitfalls to be taken into consideration in their selection and use. Next chapters are devoted to the compilation of a metric system of specific companies.

With rapidly advancing technologies and digital innovations, companies face the need to adapt to the new digital world and to digitally transform their business models. For executing the digital transformation process, more and more companies decide to entrust a new C-level manager with all challenges and complexity arising from digital transformation, the Chief Digital Officer (CDO). As the CDO position is still fairly new, research in this field is limited and requires further attention by scholars. Therefore, this study aims to address three fundamental research questions concerning the nature of the CDO position and corresponding implications not only to inform practitioners but also to enrich the scholarly discussion on CDOs. By understanding existing literature on CDOs based on a systematic literature review, this thesis answers the first research question regarding what characterizes the CDO position. Building on these insights and drawing from a comprehensive theoretical framework consisting of upper echelons theory, contingency theory, human capital theory and the resource-based view, hypotheses are developed for answering research questions two and three. While the second research question focuses on factors, which influence CDO presence within a company, the third research question addresses the impact of a CDO on company performance. Based on a large-scale sample of panel data comprised of S&P 500 companies, generalized estimating equations models, propensity score matching and fixed effects regression models are exploited in order to derive answers for both research questions two and three. As influencing factors for CDO presence, the results show that especially early tenure CEOs and CEOs of larger companies are more likely to employ a CDO. Although no evidence can be observed for positive performance implications of CDOs, also given different company contingencies, the insights of this study's analyses show that certain CDO characteristics as well as in combination with CIO presence and varying CEO characteristics are more favorable over others in terms of company performance measured by return on assets and Tobin's Q.

Diploma thesis deals with the proposal of the Balanced Scorecard for a selected company. The theoretical part of this thesis includes research of available literature, which is focused on company performance measurement in general, financial statements, financial analysis, strategic analysis and the BSC method. In the practical part, after financial and strategic analysis, proposal of the four BSC perspectives (financial, customer, internal process, learning and growth) is presented, based on the strategy of the company.

Cloud computing is an exciting concept that propels the development of technologies, the creation and expansion of businesses and the rapid prototyping of new ideas. Utilizing the advantages the cloud offers to their fullest potential is not a simple task and thus often users struggle with the technological aspects, lose revenue or do not attempt to benefit from this idea at all. In this dissertation, we identify the lack of standards for performance descriptions as well as the steep learning curve to get familiar with the cloud, which is further amplified by the abundance of available services, as the most prevalent issues that individuals and companies encounter. We further show the relevance of solving these issues by outlining the expected impact, which includes decreased time and financial detriments for individuals and companies as well as a negative effect on the environment. To solve the identified problems we propose the development of a cloud broker with three key components that utilize a performance oriented resource and application model to 1) compare arbitrary resources and applications in a fair manner based on general information, collected with standard benchmark tools 2) select the optimal infrastructure for any application by estimating its resource consumption and execution time and 3) automatically create and manage the selected infrastructure as well as the application deployment. Our contributions to this proposal include the development and test of prototypical proof-of-concept implementations for the three components, the design of the underlying resource and application performance model as well as the selection of appropriate, generic benchmark solutions, which we deployed on two major public clouds using our prototypes. In an extensive objective-based evaluation we assess that we contributed towards solving all the major issues that we identified to increase the usability and efficiency of cloud computing by enabling a better comprehension of resource and application performance in cloud environments and by reducing the necessary time and effort to deploy arbitrary applications in the cloud. We conclude by interpreting the evaluation results and providing an outlook towards future work.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform / Die Dissertation beschäftigt sich mit der effizienten Nutzung von Cloud Ressourcen zur Beschleunigung der Entwicklung neuer Technologien und Geschäftsmodellen sowie des Rapid Prototypings neuer Ideen. Auf Grund der Komplexität von Cloud Plattformen, stellt die Nutzung derer oft eine große Hürde, speziell für kleine und mittlere Unternehmen dar, weshalb oft Ressourcen verschwendet werden, Prozesse mehr Zeit in Anspruch nehmen als nötig oder erst gar kein Versuch unternommen wird, diese Technologie zu nutzen. In der Arbeit werden dazu drei Kernprobleme identifiziert und thematisiert. Dies sind Lücken in Bezug auf Standards zur Beschreibung der Performance von Cloud Ressourcen, die Fülle an existierenden Cloud Diensten, sowie die steile Lernkurze bei der Nutzung dieser Dienste. Zur Lösung der identifizierten Probleme, wird in der Arbeit die Entwicklung einer Cloud Broker Anwendung mit drei Kernkomponenten vorgeschlagen, die ein Performanz-orientiertes Ressourcen- und Anwendungsmodell verwenden, welches es ermöglicht: 1) beliebige Ressourcen und Anwendungen unterschiedlichster Anbieter mit der Hilfe von frei verfügbaren und standardisierten Benchmark Tools zu vergleichen, 2) die passende Infrastruktur für jede auszuführende Anwendung durch Schätzung des Ressourcenbedarfs und der Dauer der Ausführung auszuwählen und 3) die gewählte Infrastruktur automatisch in der Cloud erzeugt und die Anwendung selbstständig ausführt. Im Rahmen der Dissertation wurden dazu alle drei Kernkomponenten prototypisch implementiert, das zugrundeliegende Ressourcen und Anwendungsmodell designt, sowie geeignete Benchmark Lösungen ausgewählt und umfangreiche Benchmarks auf zwei großen, öffentlichen Cloud Plattformen mit Hilfe der entwickelten Prototypen durchgeführt. In einer umfassenden zielorientierten Evaluation, wird der Beitrag zur Lösung der im Vorfeld identifizierten Probleme bewertet und festgestellt, dass mit den entwickelten Komponenten sowohl die Nutzbarkeit als auch Effizienz von Cloud-Computing insgesamt erhöht werden kann. Dies wird ermöglicht durch ein besseres Verständnis der Ressourcen und Anwendungsperformanz, sowie durch Reduzierung der notwendigen Zeit und des Aufwands für eine Anwendungsausführung in der Cloud. Im Vortrag wird abschließend noch ein Ausblick auf weiterführende Arbeiten gegeben.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform