Entrepreneurial exit can be considered one of the most important moments in the entrepreneurial life cycle. However, within the literature, this importance was only recognized recently. Research regarding entrepreneurial exit went through a few stages; Firstly, the focus was on re-defining entrepreneurial exit and giving it a place in the life cycle. Entrepreneurial exit used to be an event that was associated with failure. Right now, not perse. It’s an event with many choices and can be studied on many levels. Within this study, exit will be looked at the level of the entrepreneur. Secondly, the role of the entrepreneur was considered; this includes variables such as intentions and personality traits. Lastly, state-of-the-art research seems to be looking at team dynamics. Currently, the main focus points were on homogeneity within the team. This study is an exploratory research which tries to link team dynamics and entrepreneurial exit. The found connections can be used for further studies. To achieve this, the main research question for this study is formulated as follows: How do team-dynamics in technical firms affect the entrepreneur's intention to exit the start-up and the chosen exit strategy? To answer the research question, a qualitative method was used, namely the comparative case study by using contrasting cases. The case studies are created by conducting interviews with management team members of technological start-ups/scale-ups. This contrast between cases is created by using a quadrant that divides the cases into “entrepreneurial exit incidents” and starting and more developed start-ups/scale-ups. Furthermore, the semi-structured interview is created by doing a literature review. Out of this literature review, multiple propositions were derived, and a conceptual model was formed. Afterwards, the propositions and conceptual model were the guidelines for the interviews. Lastly, the literature review was based on the sub-research questions. 12 case studies were formed, which were analyzed first individually and second cross-case. For the individual analyses, an open code method was used. For the cross-case, axial coding. Lastly, to find something coherent, selective coding was used. The conceptual model created with the literature cannot be supported by the case studies. However, out of the cross-case analysis, new interesting hypothesis have been formed. Such as 1. The friendship of the founding team and how they met are directly correlated with the homogeneity of the team. 2. Conflict in the early stages most happens because of a lack of entrepreneurial experience and an unclear separation of tasks. Furthermore, homogenous teams are more likely to have an unclear separation of tasks. 3. Conflict in the later stages of the companies is mostly related to different core values between management team members. Each of these relationships could be interesting for future research, such as how fast certain milestones are reached within a homogenous founding team and a heterogenous founding team. How could this early unclear separation of tasks be improved? This could be a bigger issue for homogenous teams where people have similar skills and interests. Lastly, how could management team members be selected for long-term value and minimal conflict?

This master's thesis addresses a common problem of the adoption of IT automation; the nonoptimal use of the technology due to ineffective managerial communication. It searches for a solution by using the Design Science Research methodology to create a design artifact in the form of a managerial communication framework. This framework provides values to all stakeholders in the IT automation adoption process; the managerial level, the employees, and the technology provider. It improves managerial communication during the adoption process and identifies actionable guidelines for managers. Narrowing down the scope of the thesis to the adoption of Robotic Process Automation (RPA) within the recruitment industry allows the research to be manageable within the constraints of a master's thesis. A literature review is used to investigate the knowledge base of the topic of the thesis. Additionally, semi-structured interviews with managers and employees are used as a means of collecting data from the environment. Combining these inputs, this research designs a model that explains the role of managerial communication in the effective adoption of IT automation. The model consists of four main components: managerial communication, motivation & vision, impact awareness, and the effective adoption of IT automation. It explains the constructs that were found relevant in this process and how they relate to each other. Several root constructs are used as a basis to create actionable guidelines to facilitate an effective adoption process. Together with the explanatory model, these guidelines form the managerial communication framework. The main goal of the framework is to bridge the gap between the manager's and the employee's views on the nature of the change. This study finds that managers often view the change as a process optimization, whereas employees view it as an organizational change. The managerial communication framework allows to identify these differences and act upon them. This study not only designs the communication framework, but also evaluates its defined objectives with several experts. The results of these evaluation interviews demonstrate the validity and usability of the research conducted and the design artifact. Future research can extend the framework to other domains & technologies and tailor it to specific problem cases. Furthermore, the framework can be researched and evaluated in practice by conducting a case study.

Explainable AI is the field concerned with trying to make AI understandable to humans. While efforts have resulted in significant improvement in research and practical methods of Explainable AI, there is an urgent need for additional research and empirical studies. The academic research gaps identified in this thesis show that Explainable AI is still in its infancy and is mostly approached with a technocentric perspective while not being focused on the audience the explainability is actually intended for. Next to this, there is no structured approach to defining and establishing explainability in dynamic complex systems that involve people, institutional, and organizational elements. Lastly, there are limited empirical studies that investigate the needs, usage, and risk of explainability in complex systems. The research tries to define and address explainability in the socio-technical context within the Machine Learning decision support systems of Transaction Monitoring. It does so by performing an extensive literature review and by conducting semi-structured that try to collect empirical knowledge within local practice. The goal of this research is to expand the definitions and view on explainability by incorporating the social, organizational, and institutional elements that influence explainability. Next, the goal is to develop a method that can help practitioners approach explainability in a structured manner taking the audience into account while applying this socio-technical perspective. The user-centered method for operationalizing explainability takes on a socio-technical perspective and can provide requirements for design choices, in addition to this the method shows how these requirements can be satisfied and controlled by instantiating control structures. The method has been demonstrated and evaluated within the bank by providing a workshop using a Toy Case during a focus group. Practitioners experienced the method as useful and actionable, also the method provides broader perspectives and insights on explainability and invites the discussion of dilemmas and questions. The practitioners added that the method could be further refined by focusing on additional guidance on the control structure because the method assumes prerequisite knowledge of systems theory and system safety theory.

In recent years, there has been a growing interest in entrepreneurial education among students, emphasizing the significance of an entrepreneurial mindset. Introducing the EnteComp framework in 2016 has provided a standardized approach for evaluating interdisciplinary competences in students. This study aims to address this issue by examining the optimal utilization and integration of the EntreComp framework in the educational practices of Delft Center for Entrepreneurship (DCE). By conducting a comprehensive literature review and analyzing data from a large-scale survey involving 119 questions among DCE students, the research investigates the most effective methods for measuring the development of entrepreneurship competences among students. The findings indicate EntreComp offers a shared language and a holistic approach for assessing entrepreneurial competences. The analysis also reveals a lack of consensus and practical implementation in utilizing the EntreComp framework. Therefore, it is crucial to focus on the longitudinal development of EntreComp competencies over time and to employ various survey types and statistical tests to make the use of EntreComp more common.

Corporate venturing practices have been one of the most successful practices in terms of shared innovation or leveraging outside talent to further one’s competitive edge in the rapidly growing and evolving industry of technology. Since, technology has been one of the main driving factors in providing solutions for achievement of short term and long term goals in the space, organizations are interested in finding out potential research findings and data that will enable them to maximize their probabilities of success for the particular venture. Streamlining such points of interest will improve the innovative capabilities of all participating organizations. A repository of literature was combed for identification of key factors that influence success in ventures. For this research BWM methodology has been employed to assess the importance therefore the prioritization of these factors and their impact through a set of curated list of respondents from the industry.