Venture Capitals (VCs) are important providers of funds and competence to new technology-based firms (NTBFs) and VC-backed NTBFs are more likely to succeed than those that are not. Past researches into VC selection criteria suggested people-related criteria as being the most important out of all the criteria but as they were focused on ranking certain criteria against each other, they did not describe what they mean and how they are used and could have overlooked other criteria used that were not ranked. This research is addressing such gap by exploring people-related criteria used by VCs through collecting qualitative data from semi-structured interviews with Swedish VC investment managers. The results present 25 people-related criteria; what they mean, when they are used, and how they are assessed. Twelve of these criteria are new and have not been featured in past studies. In the screening stage, only a few people-related criteria are used while all but one people-related criteria identified are used in the assessment stage. The criteria most commonly used in the evaluation stage are new to this study. Themes arising from results are also discussed, such as coachable entrepreneurs as positive criterion and technical-driven NTBF teams as negative criterion. This research extends the knowledge in the area of entrepreneurship studies and provides practical implications for NTBFs seeking to raise funds.

This dissertation solves an optimization problem in the area of scheduling large-scale petroleum development projects under several resources constraints. The dissertation focuses on the application of a metaheuristic search Genetic Algorithm (GA) in solving the problem. The GA is a global search method inspired by natural evolution. The method is widely applied to solve complex and sizable problems that are difficult to solve using exact optimization methods. A classical resource allocation problem in operations research known under Knapsack Problems (KP) is considered for the formulation of the problem. Motivation of the present work was initiated by certain petroleum development scheduling problem in which large-scale investment projects are to be selected subject to a number of resources constraints in several periods. The constraints may occur from limitations in various resources such as capital budgets, operating budgets, and drilling rigs. The model also accounts for a number of assumptions and business rules encountered in the application that motivated this work. The model uses an economic performance objective to maximize the sum of Net Present Value (NPV) of selected projects over a planning horizon subject to constraints involving discrete time dependent variables. Computational experiments of 30 projects illustrate the performance of the model. The application example is only illustrative of the model and does not reveal real data. A Greedy algorithm was first utilized to construct an initial estimate of the objective function. GA was implemented to improve the solution and investigate resources constraints and their effect on the assets value. The timing and order of investment decisions under constraints have the prominent effect on the economic performance of the assets. The application of an integrated optimization model provides means to maximize the financial value of the assets, efficiently allocate limited resources and to analyze more scheduling alternatives in less time.

This study is focused on real estate funds formed in Germany and has two major purposes: first to investigate the liquidity crisis and followed change of the legal framework for German real estate funds and secondly to demonstrate the impact on investment selection criteria of German real estate investment companies . By both quantitative and qualitative methods the thesis approaches those two different purposes. The quantitative part provides theoretical background about the construct of open-end and closed-end real estate funds and about the triggers and effects of the liquidity crisis. The qualitative part consists of an online survey that was sent to German real estate investment companies in which respondents indicated their preferred criteria for real estate investment opportunities. Furthermore telephone interviews on this topic were conducted with four German real estate investment experts. In the end the findings from the survey and the interviews are applied to a case study about a trophy asset in Luxembourg, in order to analyze if this property meets the investment criteria of German real estate funds. The survey and the conducted interviews indicate that German real estate investment companies have adapted to the risk-averse investment behaviour of investors and preferably make safe haven investments in terms of the investment style, the location of the real estate asset and the characteristics of the property itself and its tenants. The case study as well confirms this result.