The maintenance strategy “predictive maintenance”, which is characterized by predicting the failure behavior of technical units based on modern sensor technology, plays a key role in smart factories against the background of an industry 4.0. This paper contains an evaluation of the current state of research on this strategy and gives an overview of the areas of application to date. With the aid of a qualitative video analysis, the implementation in the industries and company divisions involved and the type of goods monitored are examined. The analyzed video clips were uploaded to YouTube for example for marketing purposes by various companies with different perspectives on predictive maintenance. The video analysis was realized by applying a previously defined coding plan to the video material. The results show a predominant application in the manufacturing industry, in which predictive maintenance is used to monitor plants and machines. In addition, the strategy is also mainly applied to means of transport used for freight and passenger transport in various infrastructures. As a result of the video analysis, the currently high need for explanation of predictive maintenance becomes visible. By looking at these explanations, one also learns something about the special features that distinguish it from other maintenance strategies.

Digitalisation and further media development are core processes of the current digital age. In order for companies to benefit from technical progress, their employees must have or are expected to acquire the relevant skills. Companies therefore are faced with the task of not being overwhelmed with the mass of innovations and opportunities and, in the best-case scenario, of being able to use them to improve their own performance. Small and medium-sized enterprises represent 99% of all enterprises in Germany. Though, it has not been further established, how the majority of small enterprises and their employees participate in this development. The research question therefore consists of two parts. On the one hand: "Is the promotion of employees' skills taken care of in micro-enterprises?" and on the other hand: "Where are the opportunities and challenges for companies of this size?” In order to answer the research question, a qualitative research method was used, the guideline-based interview. The interviewed companies were all in the media and IT sector. Thus, the recorded and transcribed data provided a real insight into the current situation in micro-enterprises. The responses to the interviews showed that companies with very small numbers of employees are more dependent on their employees than others. So, the commitment of the employees is decisive for the success of the company itself. It is the management's task to promote this and ensure employee satisfaction. Companies that pay more attention to employee development are therefore more recommendable for career starters who need and/or want to develop themselves and their entire horizon of experience.

In der vorliegenden Arbeit wird die Integration einer Business Intelligence-Lösung in eine bestehende Social Software beschrieben. Dafür wird zunächst der Begriff Business Intelligence und Social Software, der Aufbau sowie deren Bestandteile näher erläutert. Danach erfolgt eine Analyse der IST-Situation der Zielgruppe durch Interviews, deren Auswertungen in der SOLL-Konzeptionierung in eine Anforderungsliste transformiert werden. Abschließend werden die herausgearbeiteten Anforderungen an der finalen Installation geprüft und getestet, um festzustellen ob die Erwartungen der Zielgruppe und ihre Vorstellungen von Business Intelligence realisierbar sind. Das Ergebnis dieser Arbeit soll eine installierte Business Intelligence-Lösung in einer Social Software sein. Diese soll einen Überblick darüber geben, was mit der aktuellsten Version der Software bereits möglich ist und kritisch aufzeigen, wo es Stärken und Schwächen gibt, die bei zukünftigen Versionenrnbedacht werden sollten.

Despite the inception of new technologies at a breakneck pace, many analytics projects fail mainly due to the use of incompatible development methodologies. As big data analytics projects are different from software development projects, the methodologies used in software development projects could not be applied in the same fashion to analytics projects. The traditional agile project management approaches to the projects do not consider the complexities involved in the analytics. In this thesis, the challenges involved in generalizing the application of agile methodologies will be evaluated, and some suitable agile frameworks which are more compatible with the analytics project will be explored and recommended. The standard practices and approaches which are currently applied in the industry for analytics projects will be discussed concerning enablers and success factors for agile adaption. In the end, after the comprehensive discussion and analysis of the problem and complexities, a framework will be recommended that copes best with the discussed challenges and complexities and is generally well suited for the most data-intensive analytics projects.

Social entrepreneurship is a form of entrepreneurship that marries a social mission to a competitive value proposition. Notably, social entrepreneurship fosters a more equitable society by addressing social issues and trying to achieve an ongoing sustainable impact through a social mission rather than purely profit maximization. The topic of social entrepreneurship has appealed considerably to many different streams of research. The focus on understanding how and why entrepreneurs think and act is a significant justification for future research. Nevertheless, the theoretical examination of this phenomenon is in its infancy. Social entrepreneurship research is still largely phenomenon-driven. Specifically, Social Entrepreneurial Intention is in an early stage and lacks quantitative research. Therefore, this thesis proposes to address this need. The thesis’ objectives are twofold: (1) develop a formation model for Social Entrepreneurial Intentions in general and (2) test the model by conducting an empirical study. Based on these objectives, the two research questions guiding the thesis are (1) what factors influence the intention of a person to become a social entrepreneur and (2) what relationships exist among these factors. In order to answer these two research questions, this thesis uses purposeful research design, which is a combination of literature review and empirical study. The literature review is based on a comprehensive range of books, articles, and research papers published in leading academic journals and conference proceedings in different disciplines such as entrepreneurship, social entrepreneurship, entrepreneurship education, management, social psychology, and social economics. The empirical study is conducted via a survey of 600 last-year students from four universities in three regions in Vietnam: Hanoi, Da Nang, and Ho Chi Minh. The data are analyzed with SPSS-AMOS version 24, using screening data, scale development, exploratory factor analysis, and confirmation factor analysis. The thesis ascertains that Entrepreneurship Experience/Extra-curricular Activity, Role Model, Social Entrepreneurial Self-Efficacy, and Social Entrepreneurial Outcome Expectation directly and positively affect the intention of the Vietnamese students to be social entrepreneurs. Entrepreneurship Education also influences the Social Entrepreneurial Intention, but not directly, otherwise indirectly via Social Entrepreneurial Self-Efficacy and Social Entrepreneurial Outcome Expectation. Similarly, Perceived Support has no direct relationship to Social Entrepreneurial Intention; however, it shows an indirect link via the mediator ‘Social Entrepreneurial Outcome Expectation’. Furthermore, the dissertation brings new insights to the social entrepreneurship literature and provides important implications for practice. Limitations and future directions are also provided in the thesis.