With the influx of state-funded business development programs and organizations, it is of increasing relevance to understand the success and value creation of said programs and organizations. Sweden is one of the states in the world with the highest number of incubators per capita, and has an extensive knowledge network surrounding incubation. However, the success of them is hard to predict at best, owing to different incubator practices and selection processes for different industries, for example. This creates the question of whether incubators are a worthwhile investment strategy to create growth, and how this should be assessed. Prior literature on the field have used a range of different measures, such as survival rate over time, but we are more interested in the long-term growth caused by incubators by their graduated firms. Thus, this study’s purpose is to assess whether Northern Swedish incubator graduates see stronger growth than comparable non-incubated firms over time. The approach taken has been to study the 5-year cumulative average employee and turnover growth rates of firms in IT & non-digital technology in Northern Sweden. Quantitative firm data was analyzed deductively in accordance to hypotheses developed on prior theory on the field. The incubator firm sample had been affiliated with either Uminova Innovation or Arctic Business Incubator (ABI), as the 3rd incubator in Northern Sweden, Bizmaker, had no suitable firms for our study. The comparable reference firms were from all counties related to Northern Sweden, Norrland Land. Analyzing the data revealed a significantly higher turnover growth rate for incubator graduates in the region, as opposed to the numbers of non-incubated firms. Incubated IT firms seemed to have a quicker turnover growth than that of incubated non-digital technology firms as well. However, this was not the case regarding employee growth, where no significant relation was between that and incubation, or lack thereof. The data suggests that incubators create some lasting economic growth, at the very least, but cannot show to great growth in things such as employment, societal growth, and creation of other kinds of value like environmental and social. The suggested course of action for further actors in the field is to expand the study, e.g. by using different time spans, regions and researched types of value. Incubators do seem to have an effect on their firms, but it is difficult to pinpoint and harder to assign a value to in comparison to the resources spent on them.

The task of predicting start-up growth has been an item of institutional as wellas widespread individual research and acclaim of those successful. This workis an attempt to distill the alleged factors of prediction in the large body ofwork that has already been documented, as well as investigating reasonable butyet untested variables. Conclusions are built with a multiple regression model,exploring 7 regressors with data spanning 2014-2019 to avoid the potentiallyabnormal impact of the Covid-19 crisis.Due to the choice of non-predictive regressors, the final result is an explanatorymodel, highlighting the importance of rigorousness in the process of model-building and outlining of data collection in regression analysis. Most regres-sors had a non-significant or weak relationship with the response variable, butconcludes an explanatory degree of 51%. Even if it can not be utilised as apredictive model, it may provide some interesting insight. In the final model,every regressor except one had an unexpected beta value, contradicting earlierresearch. / Åtagandet att förutsäga 'start-up' tillväxt har varit ämne för institutionellsåväl som utbredd individuell undersökning och följaktligen hyllning för de som varit framgångsrika. Denna studieär ett försök att destillera de påstådda faktorerna för förutsägelse utifrån den redan dokumenterade litteraturen, samt utreda rimliga men ännu outforskade variabler. Slutsatser byggs med en multipel regressionsmodell,som utforskar 7 regressorer med data som sträcker sig 2014-2019 för att undvika de potentiellt atypiska effekterna av covid-19-krisen.På grund av valet av vissa icke-prediktiva regressorer är slutresultatet en förklarandemodell, som belyser vikten av noggrannhet i processen för modell-uppbyggnad och planeringen av datainsamling i regressionsanalys. De flesta regressorer hade ett icke-signifikant eller svagt samband med svarsvariabeln, men den slutgiltiga modellen påvisar en förklaringsgrad på 51 %. Även om den inte kan användas som en prediktiv modell, så bidrar den med betydande insikter. Alla regressorer utom en visade ett oväntat beta-värde, vilket motsäger tidigare forskning.

The aim of the graduation thesis is to evaluate the current development in the field of SDN and the possibility of programmability of SDN elements using the application programming interface. The first theoretical chapter describes the following: the basic architecture of SDN, the traffic within SDN between its individual layers, the communication protocols Southbound interface and Northbound interface. The second chapter of the thesis deals with the programmability of SDN elements with the help of API. The third theoretical chapter describes the current development in the field of SDN. The practical part of the thesis is devoted to creation of two laboratory tasks dealing with the programming of the SDN API. Laboratory tasks include BIG-IP programming from F5 Network and routers from Arista Network. Programming is done using Python via REST API for BIG-IP, or eAPI for Arista EOS. The Ansible setup tool is also used for the same purpose.

Bioprinting is one of the most promising technologies for future healthcare as it may benefit the repairing of wounds and injuries, disease modeling and development, transplantation of organs and reduce animal testing. This thesis aim to investigate this industry further, as there is no excessive literature on how to handle the innovation in regards to entrepreneurial and biotechnological knowledge. Hence, a research gap can be spotted and the purpose of the conducted research questions should contribute to this gap. In order to fully understand the bioprinting industry, an outline of the technology is made as part of the research. In addition to this, secondary data for patents, market valuation and annual growth rates are collected to support arguments from previous literature. Also, interviews are conducted to gather specific knowledge. As a result, bioprinting may be presented as a disruptive innovation in an uncertain market, which places certain demands on companies to act more in line with the complexity of the technology. Such companies must think more strategically and design more complex and long-term strategies. The patent data shows that there has been a decline in the technological development as patent applications have decreased significantly. Even though the technology (regarding the patents) has started to slowly decline, there is still hope for some technological improvements to come. It can be concluded that developments in bioink, scaffolds, expansion of cells and diffusion is expected, and that the use of bioprinting is increasing and will most likely continue to do so.