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How entrepreneurs become successful with their business ideas has been a topic of discussion within entrepreneurial research circles for many years. Business success has been related to psychological characteristics and many research findings have explained how people become entrepreneurs and furthermore, how they find success in regards to their business ventures. People always wanted to know what defines an entrepreneur and more importantly, what is needed to become a successful entrepreneur. Curious minds began to search for the recipe for success. Personality Traits have been researched for years, leading to the discovery of many diverse and distinct forms which are still recognized today. Researchers compared the Behavioral Approach or the analysis of demographical characteristics to success.
This raises the question of what an entrepreneur needs to become successful which is made more difficult due to the fact that entrepreneurship and who an entrepreneur is can be difficult do define exactly. Entrepreneurs are diverse and distinct individuals that each possess their own characteristics, behavior and reasons for starting a business. Many people assume that it is just someone who starts their own business. While partially correct, this only scratches the surface of what it is to be an entrepreneur.
This thesis answers the following three research questions: 1. Which personality traits were found in the almost sixty years of researching? 2. What triggers do entrepreneurs need for starting a new business? 3. Which factor makes the entrepreneur successful with their business idea? Also, reading the thesis, one may gain a better understanding of what entrepreneurship is, what defines an entrepreneur and what one needs to become a successful entrepreneur.
In this thesis the reviewing literature method developed by Wolfswinkel et al. (2011) was used to identify suitable literature and references for the main chapters. For that the five stages of the grounded-theory method for reviewing the literature were used in an iterative fashion. In step one inclusion and exclusion criterias for literature were defined. Then literature was searched matching the criterias of step one. In step three the samples were refined. Then in step four the found literature was analyzed and coded before the results of this research was presented in the following text. Many entrepreneurial personality traits were discovered and confirmed during the studies conducted over the last sixty years, these include but are not limited to Need for Achievement, Locus of Control, or risk taking propensity. Motivation is clearly the main trigger to start your own business. During the studies reasons were discovered of how and why an entrepreneur may become successful outside of posessing the right combination of traits. For example: having human, financial and social capital, an entrepreneurial behavior and the right economic conditions to start a business that will survive for more than five years.
This thesis presents novel approaches for integrating context information into probabilistic models. Data from social media is typically associated with metadata, which includes context information such as timestamps, geographical coordinates or links to user profiles. Previous studies showed the benefits of using such context information in probabilistic models, e.g.\ improved predictive performance. In practice, probabilistic models which account for context information still play a minor role in data analysis. There are multiple reasons for this. Existing probabilistic models often are complex, the implementation is difficult, implementations are not publicly available, or the parameter estimation is computationally too expensive for large datasets. Additionally, existing models are typically created for a specific type of content and context and lack the flexibility to be applied to other data.
This thesis addresses these problems by introducing a general approach for modelling multiple, arbitrary context variables in probabilistic models and by providing efficient inference schemes and implementations.
In the first half of this thesis, the importance of context and the potential of context information for probabilistic modelling is shown theoretically and in practical examples. In the second half, the example of topic models is employed for introducing a novel approach to context modelling based on document clusters and adjacency relations in the context space. They can cope with areas of sparse observations and These models allow for the first time the efficient, explicit modelling of arbitrary context variables including cyclic and spherical context (such as temporal cycles or geographical coordinates). Using the novel three-level hierarchical multi-Dirichlet process presented in this thesis, the adjacency of ontext clusters can be exploited and multiple contexts can be modelled and weighted at the same time. Efficient inference schemes are derived which yield interpretable model parameters that allow analyse the relation between observations and context.
The application of pesticides to agricultural areas can result in transport to adjacent non-target environments. In particular, surface water systems are likely to receive agricultural pesticide input. When pesticides enter aquatic environments, they may pose a substantial threat to the ecological integrity of surface water systems. To minimize the risk to non-target ecosystems the European Union prescribes an ecotoxicological risk assessment within the registration procedure of pesticides, which consists of an effect and an exposure assessment.
This thesis focuses on the evaluation of the exposure assessment and the implications to the complete regulatory risk assessment, and is based on four scientific publications. The main part of the thesis focuses on evaluation of the FOCUS modelling approach, which is used in regulatory risk assessment to predict pesticide surface water concentrations. This was done by comparing measured field concentrations (MFC) of agricultural insecticides (n = 466) and fungicides (n = 417) in surface water to respective predicted environmental concentrations (PEC) calculated with FOCUS step 1 to step 4 at two different levels of field relevance. MFCs were extracted from the scientific literature and were measured in field studies conducted primarily in Europe (publications 1 and 3).
In addition, an alternative fugacity-based multimedia mass-balance model, which needs fewer input parameters and less computing effort, was used to calculate PECs for the same insecticide MFC dataset and compared to the FOCUS predictions (publication 3). Furthermore, FOCUS predictions were also conducted for veterinary pharmaceuticals in runoff from an experimental plot study, to assess the FOCUS predictions for a different class of chemicals with a different relevant entry pathway (publication 2).
In publication 4, the FOCUS step-3 approach was used to determine relevant insecticide exposure patterns. These patterns were analysed for different monitoring strategies and the implications for the environmental risk assessment (publication 4).
The outcome of this thesis showed that the FOCUS modelling approach is neither protective nor appropriate in predicting insecticide and fungicide field concentrations. Up to one third of the MFCs were underpredicted by the model calculations, which means that the actual risk might be underestimated. Furthermore, the results show that a higher degree of realism even reduces the protectiveness of model results and that the model predictions are worse for highly hydrophobic and toxic pyrethroids.
In addition, the absence of any relationship between measured and predicted concentrations questions the general model performance quality (publication 1 and 3). Further analyses revealed that deficiencies in protectiveness and predictiveness of the environmental exposure assessment might even be higher than shown in this thesis, because actual short-term peak concentrations are only detectable with an event-related sampling strategy (publication 4). However, it was shown that the PECs of a much simpler modelling approach are much more appropriate for the prediction of insecticide MFC, especially for calculations with a higher field relevance (publication 3). The FOCUS approach also failed to predict concentrations of veterinary pharmaceuticals in runoff water (publication 2). In conclusion, the findings of this thesis showed that there is an urgent need for the improvement of exposure predictions conducted in the environmental risk assessment of pesticides as a group of highly relevant environmental chemicals, to ensure that the increasing use of those chemicals does not lead to further harmful effects in aquatic ecosystems.
The establishment of aquatic alien species can strongly affect community and food web structure of the invaded systems and thus represents a major threat to native biodiversity. One of the most important aquatic invasive species in European rivers is the Ponto-Caspian amphipod Dikerogammarus villosus. The species invaded most of the major European waterways within two decades, often associated with a decline of many other macroinvertebrate species, including other amphipods. Based on laboratory results predation by the so called ‘killer shrimp’ is often regarded as the key driver for observed displacement effects, but recent studies indicated a minor relevance of predation by D. villosus in the field. To allow the determination of exact predator-prey interactions from field samples, I established 22 group-specific rDNA primers for freshwater taxa suitable for prey species identification in dietary samples (Chapter II) and an approach for the screening of D. villosus gut contents using 16 of these primers. Combining genetic gut content analyses, with one of these primers, and stable isotope analyses, I examined the importance of intraguild predation (IGP) by D. villosus, which is often assumed the key driver for the displacement of native amphipod species, at an invasion front of the species in Switzerland (Chapter III). The results of this study revealed a low importance of IGP during this particular D. villosus invasion and indicated an overall sparsely predacious feeding behaviour of the species. As the feeding behaviour of D. villosus is supposed to differ between habitats and this study was only conducted at a few sampling sites of one river, I also investigated the role of predation by D. villosus at multiple sites of the River Rhine system, covering a broad range of microhabitats (Chapter IV). In keeping with the results from the invasion front results of this study strongly indicated a sparsely predacious feeding but rather a flexible feeding behaviour of D. villosus even within the same microhabitat.
However, established populations of D. villosus have changed aquatic food webs and can be expected to affect aquatic-terrestrial energy fluxes. In Chapter V of my thesis, I present a field study investigating the impact of D. villosus on the diet of two riparian spider taxa. The results of this study indicate an effect of D. villosus on the terrestrial food web via cross-ecosystem resource flow.
In conclusion, D. villosus influences terrestrial food webs by altering cross-ecosystem resource fluxes, but it is rather an opportunistic omnivore than a predator in the field.
In order to enhance the company’s appeal for potential employees and improve the satisfaction of already salaried workers, it is necessary to offer a variety of work-life balance measures. But as their implementation causes time and financial costs, a prioritization of measures is needed. To express a recommendation for companies, this study is led by the questions if there are work-life balance measures which have more impact on employee satisfaction than others, how big the relative impact of work-life balance measures on job satisfaction in comparison to other work and private life variables is, if there is a relation between the effectiveness of measures and their use and if there is a difference between the measures which are most important from the employees’ perspective and the companies’ offers.
These questions are formulated in eight research hypotheses which are examined in a quantitative research design with online survey data from 289 employees of fifteen different German companies. The formation of a hierarchy of the effectiveness of measures towards job satisfaction as well as the investigation of the relative impact in comparison to other variables is performed using a multiple regression analysis, whilst the differences between employees’ expectations and the availability of offers are examined with t-tests.
Support in childcare, support in voluntary activities and teambuilding events have a significantly higher impact on job satisfaction than other work-life balance measures, and their potential use is higher than the actual use which leads to the conclusion that there is yet potential for companies to improve their employees’ satisfaction by implementing these measures. In addition, flexible work hours, flexible work locations and free time and overtime accounts are the most important measures from the employees’ point of view and already widely offered by the surveyed companies. In general, the overall use of the available measures and the quantity of offered measures are more important with regard to job satisfaction than the specific kind of measure. In addition, work-life balance measures are more important towards job satisfaction for younger people.
The purpose of this research is to examine various existing cloud-based Internet of Things (IoT) development platforms and evaluate one platform (IBM Watson IoT) in detail using a use case scenario. Internet of Things IoT is an emerging technology that has a vision of interconnecting the virtual world (e.g. clouds, social networks) and the physical world (e.g. device, cars, fridge, people, animals) through the Internet technology. For example, the IoT concept of smart cities which has the objectives to improve the efficiency and development of business, social and cultural services in the city, can be achieved by using sensors, actuators, clouds and mobile devices (IEEE, 2015). A sensor (e.g. temperature sensor) in the building (global world) can send the real-time data to the IoT cloud platform (virtual world), where it can be monitored, stored, analysed, or used to trigger some action (e.g. turn on the cooling system in the building if temperature exceeds a threshold limit). Although, the IoT creates vast opportunities in different areas (e.g. transportation, healthcare, manufacturing industry), it also brings challenges such as standardisation, interoperability, scalability, security and privacy. In this research report, IoT concepts and related key issues are discussed.
The focus of this research is to compare various cloud-based IoT platforms in order to understand the business and technical features they offer. The cloud-based IoT platforms from IBM, Google, Microsoft, PTC and Amazon have been studied.
To design the research, the Design Science Research (DSR) methodology has been followed, and to model the real-time IoT system the IOT-A modelling approach has been used.
The comparison of different cloud based IoT development platforms shows that all of the studied platforms provide basic IoT functionalities such as connecting the IoT devices to the cloud based IoT platform, collecting data from the IoT devices, data storage and data analytics. However, the IBM’s IoT platform appears to have an edge over the other platforms studied in this research because of the integrated run-time environment which also makes it more developer friendly. Therefore, IBM Watson IoT for Bluemix is selected for further examination of its capabilities. The IBM Watson IoT for Bluemix offerings include analytics, risk management, connect and information management. A use case was implemented to assess the capabilities that IBM Watson IoT platform offers. The digital artifacts (i.e. applications) are produced to evaluate the IBM’s IoT solution. The results show that IBM offers a very scalable, developer and deployment friendly IoT platform. Its cognitive, contextual and predictive analytics provide a promising functionality that can be used to gain insights from the IoT data transmitted by the sensors and other IoT devices.
Conversion of natural vegetation into cattle pastures and croplands results in altered emissions of greenhouse gases (GHG), such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Their atmospheric concentration increase is attributed the main driver of climate change. Despite of successful private initiatives, e.g. the Soy Moratorium and the Cattle Agreement, Brazil was ranked the worldwide second largest emitter of GHG from land use change and forestry, and the third largest emitter from agriculture in 2012. N2O is the major GHG, in particular for the agricultural sector, as its natural emissions are strongly enhanced by human activities (e.g. fertilization and land use changes). Given denitrification the main process for N2O production and its sensitivity to external changes (e.g. precipitation events) makes Brazil particularly predestined for high soil-derived N2O fluxes.
In this study, we followed a bottom-up approach based on a country-wide literature research, own measurement campaigns, and modeling on the plot and regional scale, in order to quantify the scenario-specific development of GHG emissions from soils in the two Federal States Mato Grosso and Pará. In general, N2O fluxes from Brazilian soils were found to be low and not particularly dynamic. In addition to that, expected reactions to precipitation events stayed away. These findings emphasized elaborate model simulations in daily time steps too sophisticated for regional applications. Hence, an extrapolation approach was used to first estimate the influence of four different land use scenarios (alternative futures) on GHG emissions and then set up mitigation strategies for Southern Amazonia. The results suggested intensification of agricultural areas (mainly cattle pastures) and, consequently, avoided deforestation essential for GHG mitigation.
The outcomes of this study provide a very good basis for (a) further research on the understanding of underlying processes causing low N2O fluxes from Brazilian soils and (b) political attempts to avoid new deforestation and keep GHG emissions low.
In recent years head mounted displays (HMD) and their abilities to create virtual realities comparable with the real world moved more into the focus of press coverage and consumers. The reason for this lies in constant improvements in available computing power, miniaturisation of components as well as the constantly shrinking power consumption. These trends originate in the general technical progress driven by advancements made in smartphone sector. This gives more people than ever access to the required components to create these virtual realities. However at the same time there is only limited research which uses the current generation of HMDs especially when comparing the virtual and real world against each other. The approach of this thesis is to look into the process of navigating both real and virtual spaces while using modern hardware and software. One of the key areas are the spatial and peripheral perception without which it would be difficult to navigate a given space. The influence of prior real and virtual experiences on these will be another key aspect. The final area of focus is the influence on the emotional state and how it compares to the real world. To research these influences a experiment using the Oculus Rift DK2 HMD will be held in which subjects will be guided through a real space as well as a virtual model of it. Data will be gather in a quantitative manner by using surveys. Finally, the findings will be discussed based on a statistical evaluation. During these tests the different perception of distances and room size will the compared and how they change based on the current reality. Furthermore, the influence of prior spatial activities both in the real and the virtual world will looked into. Lastly, it will be checked how real these virtual worlds are and if they are sufficiently sophisticated to trigger the same emotional responses as the real world.
Reactive local algorithms are distributed algorithms which suit the needs of battery-powered, large-scale wireless ad hoc and sensor networks particularly well. By avoiding both unnecessary wireless transmissions and proactive maintenance of neighborhood tables (i.e., beaconing), such algorithms minimize communication load and overhead, and scale well with increasing network size. This way, resources such as bandwidth and energy are saved, and the probability of message collisions is reduced, which leads to an increase in the packet reception ratio and a decrease of latencies.
Currently, the two main application areas of this algorithm type are geographic routing and topology control, in particular the construction of a node's adjacency in a connected, planar representation of the network graph. Geographic routing enables wireless multi-hop communication in the absence of any network infrastructure, based on geographic node positions. The construction of planar topologies is a requirement for efficient, local solutions for a variety of algorithmic problems.
This thesis contributes to reactive algorithm research in two ways, on an abstract level, as well as by the introduction of novel algorithms:
For the very first time, reactive algorithms are considered as a whole and as an individual research area. A comprehensive survey of the literature is given which lists and classifies known algorithms, techniques, and application domains. Moreover, the mathematical concept of O- and Omega-reactive local topology control is introduced. This concept unambiguously distinguishes reactive from conventional, beacon-based, topology control algorithms, serves as a taxonomy for existing and prospective algorithms of this kind, and facilitates in-depth investigations of the principal power of the reactive approach, beyond analysis of concrete algorithms.
Novel reactive local topology control and geographic routing algorithms are introduced under both the unit disk and quasi unit disk graph model. These algorithms compute a node's local view on connected, planar, constant stretch Euclidean and topological spanners of the underlying network graph and route messages reactively on these spanners while guaranteeing the messages' delivery. All previously known algorithms are either not reactive, or do not provide constant Euclidean and topological stretch properties. A particularly important partial result of this work is that the partial Delaunay triangulation (PDT) is a constant stretch Euclidean spanner for the unit disk graph.
To conclude, this thesis provides a basis for structured and substantial research in this field and shows the reactive approach to be a powerful tool for algorithm design in wireless ad hoc and sensor networking.
This thesis is providing an overview over the current topics and influences of mobile components on Enterprise Content Management (ECM). With a literature review the core topics of enterprise mobility and ECM have been identified and projected on the context of using mobile Apps within the environment of ECM. An analysis of three ECM systems and their mobile software lead to an understanding of the functionalities and capabilities mobile systems are providing in the ECM environment. These findings lead to a better un- derstanding for the usage of mobile Enterprise Content Management and is preparation. The thesis focuses the most important topics, which need to be considered for the usage and adoption of mobile Apps in ECM.