Energy security is a dynamic term with many alterating aspects, some more frequently used than others. Furthermore, humankind is becoming increasingly dependent on energy to sustain today's modern lifestyle and therefore the topic of energy security is becoming more important than ever. The trend of validating energy security is also expanding from an exclusively national context to the inclusion of, for example, the operations of a single organization. One of these organizations is the housing company, Uppsalahem, with their ambition to transform their energy system in line with their aspiration to reduce environmental impact and assure that it withstands the threats of tomorrow. This thesis aims to explore the adaptation of energy security validation from a national perspective to a company perspective with Uppsalahem as the main actor. With this in mind, the validation methodology was constructed. It included a risk analysis, indicators of energy security and a correlation analysis. The combination of these three were selected with the ambition to shed light upon several aspects of energy security. Uppsalahem's electrical and heat supply systems were then subjected to the validation and the results implied that Uppsalahem is situated in a state of dependency with its suppliers. Therefore, it is in Uppsalahem's best interest that their operations are sustained and external and internal defects are avoided. This thesis presents serveral measures that can be implemented in order for Uppsalahem to minimize its dependecy on external suppliers as well as reduce the risk of malfunction within its internal operations.

Spelar finansiering roll och hur bör fördelningen mellan eget kapital och skulder se ut? Kapitalstruktur har studerats i många års tid och forskare har försökt finna de faktorer som kan påverka kapitalstruktur och om skuldsättningsgraden påvisar samband mellan olika betydande variabler. Syftet med denna studie är att undersöka kapitalstrukturen hos företag inom olika branscher i avseende på skuldsättningsgrad, tillväxt, företagsstorlek och företagsålder. Undersökningen är genomförd utifrån en kvantitativ ansats som omfattar 50 företag på NASDAQ OMX Stockholm. Korrelation- samt regressionsanalyser genomfördes för att undersöka sambandet mellan företagsstorlek, företagsålder samt tillväxttakt som oberoende variabler och skuldsättningsgrad som beroende variabel. Studien har visat att företagsålder är en branschspecifik variabel som påverkar skuldsättningsgraden på olika sätt beroende på bransch. Samtidigt som företagsstorlek och tillväxttakt har visat sig vara icke branschspecifika variabler. Studien har även kunnat klargöra att vissa branscher är mer homogena än andra i avseende på kapitalstruktur. / How important is the capital structure and how should equity and debt be divided within a company? Capital structure has been studied for many years, and researchers have attempted to identify the factors that can affect the capital structure and if the leverage ratio shows significant correlations between different variables. The purpose of this study is to examine the capital structure of companies in different industries in terms of leverage, growth, company size and company age. The survey was conducted based on a quantitative approach, which includes 50 companies on NASDAQ OMX Stockholm. Correlation-and regression analyzes were conducted to examine the relationship between company size, company age and growth rate as independent variables and leverage as the dependent variable.  The study has shown that business age is an industry-specific variable affecting leverage in different ways depending on the industry. While firm size and growth rate has been found to be non-industry-specific variables. The study was also able to clarify that some industries aremore homogenous than others in terms of capital structure.

I det moderna samhället har internet och spelande av olika slag som sker genom internet blivit alltmer populära aktiviteter. I takt med den explosionsartade utvecklingen har även problematiskt beteende följt i form av onlinespelsmissbruk, som blivit ett så pass omfattande problem att det idag omnämns som diagnosen ”Internet Gaming Disorder”, IGD. Företeelsen har dock inte enbart blivit mer framträdande vad gäller aktiviteten i sig utan också gällande mängden forskning som görs inom området. Den population som studeras flitigast och där onlinespelandet är som mest framträdande är bland yngre människor och främst bland pojkar och män. Mycket av den forskning som genomförts har behandlat onlinespelandets påverkan på individen samt dess inverkan på skola och utbildning. Syftet med denna studie är därför att undersöka huruvida onlinespelandet hos tredjeårselever på gymnasiet samvarierar med dennes självupplevda sociala umgänge samt skolprestation. Studien är genomförd utifrån en kvantitativ metod där en enkätundersökning utfördes inom åtta olika program på fyra av Norrköpings gymnasieskolor. Totalt besvarade 99 gymnasieelever enkäten. Studien analyseras med ett socialkonstruktivistiskt perspektiv för att söka förstå bakomliggande aspekter av onlinespelandet genom att diskutera sociala grupperingar och kategoriseringar som sker genom social interaktion. Studiens resultat stämmer ur flera avseenden överens med tidigare forskning där det tydligt går att se att killar spelar mer än tjejer. Studien visar även ett samband mellan onlinespelande och skola på så sätt att individer engagerade i spel bland annat visar en tendens till minskat intresse för studier.

The aim of this study is to ensure the tender phase in its total price in a construction project. Today many construction projects is unmanageable and rejected mainly because of the price. By developing controlling key figures the companies can be more secure of the future costs during the project and therefore set a fair price.  This study is committed in corporation with an industrialized construction company. The company has a building system that is predefined which includes the heavy part in the total costs of the project.  The key figures are developed based on the actual price data from previous project that is divided in different cost items. Every cost item will have a control key figure. For the development of the figures a statistical method is used called regression analysis. The method requires a parameter that has a correlation to the cost items. The method will then generate a fitted function that can predict the costs of each item due to the parameter or parameters. And from the function a key indicator will be produced to function as an indicator to each cost item.

<p><strong>Introduction:</strong> Interplay between all the different subsystems of the financial markets is currently considered as an important internal force in the market. In a financially liberalized economy exchange rate stability is a basis for a wellbeing stock market. If these interactions between all the different subsystems of the financial markets are not detected, this means that there is information inefficiency in the markets.</p><p><strong>Problem:</strong> Can we find any correlation between changes in currency, interest rate and bonds with the stock market index? If so, how do these changes affect the Stockholm Stock Exchange?</p><p><strong>Purpose:</strong> The purpose of this study is to examine if there is any linkage between the interest rate, currency and bonds with the stock market. The researchers wanted to find out how these variables affect the stock market index OMX S30 which consists of the 30 largest companies on the Stockholm Stock Exchange.</p><p><strong>Method:</strong> This research has been based on a quantitative approach. Three variables were selected to determine their possible linkage with the stock market index. We have collected the quantitative data from the CMC Markets and Swedish central bank in order to obtain the necessary statistical information. We have then examined the information in SPSS and Excel.</p><p><strong>Empirical and analytical:</strong> The result shows that the government bonds which are one of the independent variables are significant explanatory variable for OMX S30. Interest rate contributes significantly to the model and is a significant explanatory variable for stock market. However, the currency has a weak contribution to the model which means that the currency is not a significant explanatory variable for OMX S30.</p>

Introduction: Interplay between all the different subsystems of the financial markets is currently considered as an important internal force in the market. In a financially liberalized economy exchange rate stability is a basis for a wellbeing stock market. If these interactions between all the different subsystems of the financial markets are not detected, this means that there is information inefficiency in the markets. Problem: Can we find any correlation between changes in currency, interest rate and bonds with the stock market index? If so, how do these changes affect the Stockholm Stock Exchange? Purpose: The purpose of this study is to examine if there is any linkage between the interest rate, currency and bonds with the stock market. The researchers wanted to find out how these variables affect the stock market index OMX S30 which consists of the 30 largest companies on the Stockholm Stock Exchange. Method: This research has been based on a quantitative approach. Three variables were selected to determine their possible linkage with the stock market index. We have collected the quantitative data from the CMC Markets and Swedish central bank in order to obtain the necessary statistical information. We have then examined the information in SPSS and Excel. Empirical and analytical: The result shows that the government bonds which are one of the independent variables are significant explanatory variable for OMX S30. Interest rate contributes significantly to the model and is a significant explanatory variable for stock market. However, the currency has a weak contribution to the model which means that the currency is not a significant explanatory variable for OMX S30.

Studien undersöker olika dimensioner av det omdiskuterade begreppet kundengagemang i ett online brand community på Facebook, i förhållande till tidigare konsumtion och köpintention “offline”. Webbaserade enkäter användes som metod för att undersöka vilka dimensioner av kundengagemang som förekommer i det studerade online brand communityt på Livrustkammarens Facebooksida. Vidare användes en korrelationsanalys för att se om det fanns ett samband mellan de olika dimensionerna av kundengagemang i förhållande till tidigare konsumtion samt köpintention. Slutligen användes logistisk regressionsanalys för att se om någon av engagemangsdimensionerna kunde vara en predikator för tidigare konsumtion respektive köpintention. Resultatet av korrelationsanalysen visade på ett positivt, statistiskt signifikant samband mellan kognitivt engagemang gentemot varumärket i förhållande till tidigare konsumtion. Ett positivt och statistiskt signifikant samband förelåg också mellan alla engagemangsdimensioner i förhållande till köpintention. Regressionsanalyserna visade på endast ett statistiskt signifikant resultat, där kognitivt engagemang gentemot varumärket var en predikator för tidigare konsumtion. Troligtvis berodde avsaknaden av statistiskt signifikanta resultat i regressionsanalyserna på multikollinearitet (korrelation) mellan de oberoende variablerna. Denna korrelation gör det också svårt att undersöka alla tre dimensionerna av engagemang samtidigt i en kvantitativ studie. Framtida forskning kan därför använda sig av en kvalitativ metod, exempelvis netnografi, för att studera de antecedents som lämnats utanför studiens ramar. Resultatet visar också på vikten av att praktiker värdesätter det kognitiva engagemanget gentemot varumärket istället för endast det beteendemässiga, då detta var den enda predikatorn som framkom i förhållande till tidigare konsumtion. Resultatet tyder också på att engagemang i sociala medier har en betydelse för köpintention, då ett samband återfanns mellan alla former av engagemang i communityt ”online” och en intention att besöka museet ”offline”.

Purpose: The study aims to show if there is a significant relationship between the CEOs recompense and the size of the company between the industries. The goal is to compare the size of a company with the variable that shows performance and which of them who has the strongest connection to the recompense. Method: The essay stands on a quantitative approach where secondary data has been gathered from the year of 2015 annual reports. The population includes all the Swedish companies in the real estate-, finance- and pharmaceutical industry that are listed on the stock exchange. Selection has been made on 30 of these companies, 10 in each industry. With the statistical analyses the methods that have been used are multiple regression model and correlation analysis. Results: The results show that the company that paid the highest recompense in the real estate industry was Kungsleden. The company in the finance industry was Kinnevik and in the pharmaceutical industry it was Pfizer. Conclusion: After analyzing the result the conclusion can be made that there is a significant relationship between the CEOs recompense and the size of the company only in the real estate industry. When comparing the variable that dictates the size of the company (net sales)  and the performance variable (MVA), the conclusion that can be made is that MVA has a stronger connection to the CEOs total recompense in the pharmaceutical industry in relation to the other industries. Within the finance industry there was no significant relationship with the CEOs recompense and the selected variables.

In this thesis, we explore two different approaches to causal inferences. The traditional approach models the theoretical relationship between the outcome variables and their explanatory variables, i.e., the science, at the same time as the systematic differences between treated and control subjects are modeled, i.e., the assignment mechanism. The alternative approach, based on Rubin's Causal Model (RCM), makes it possible to model the science and the assignment mechanism separately in a two-step procedure. In the first step, no outcome variables are used when the assignment mechanism is modeled, the treated students are matched with similar control students using this mechanism, and the models for the science are determined. Outcome variables are only used in the second step when these pre-specified models for the science are fitted. In the first paper, we use the traditional approach to evaluate whether a husband is more prone to quit smoking when his wife quits smoking than he would have been had his wife not quit. We find evidence that this is the case, but that our analysis must rely on restrictive assumptions. In the subsequent two papers, we use the alternative RCM approach to evaluate if a Harvard freshman who does not smoke (observed potential outcome) is more prone to start smoking when he shares a suite with at least one smoker, than he would have been had he shared a suite with only smokers (missing potential outcomes). We do not find evidence that this is the case, and the small and insignificant treatment effect is robust against various assumptions that we make regarding covariate adjustments and missing potential outcomes. In contrast, we do find such evidence when we use the traditional approach previously used in the literature to evaluate peer effects relating to smoking, but the treatment effect is not robust against the assumptions that we make regarding covariate adjustments. These contrasting results in the two latter papers allow us to conclude that there are a number of advantages with the alternative RCM approach over the traditional approaches previously used to evaluate peer effects relating to smoking. Because the RCM does not use the outcome variables when the assignment mechanism is modeled, it can be re-fit repeatedly without biasing the models for the science. The assignment mechanism can then often be modeled to fit the data better and, because the models for the science can consequently better control for the assignment mechanism, they can be fit with less restrictive assumptions. Moreover, because the RCM models two distinct processes separately, the implications of the assumptions that are made on these processes become more transparent. Finally, the RCM can derive the two potential outcomes needed for drawing causal inferences explicitly, which enhances the transparency of the assumptions made with regard to the missing potential outcomes. / Diss. Stockholm : Handelshögskolan, 2006 S. 1-13: sammanfattning, s. [15]-161: 4 uppsatser

Technical advances in network communication systems (e.g. radio access networks) combined with evolving concepts based on virtualization (e.g. clouds), require new management algorithms in order to handle the increasing complexity in the network behavior and variability in the network environment. Current network management operations are primarily centralized and deterministic, and are carried out via automated scripts and manual interventions, which work for mid-sized and fairly static networks. The next generation of communication networks and systems will be of significantly larger size and complexity, and will require scalable and autonomous management algorithms in order to meet operational requirements on reliability, failure resilience, and resource-efficiency. A promising approach to address these challenges includes the development of probabilistic management algorithms, following three main design goals. The first goal relates to all aspects of scalability, ranging from efficient usage of network resources to computational efficiency. The second goal relates to adaptability in maintaining the models up-to-date for the purpose of accurately reflecting the network state. The third goal relates to reliability in the algorithm performance in the sense of improved performance predictability and simplified algorithm control. This thesis is about probabilistic approaches to fault management that follow the concepts of probabilistic network management (PNM). An overview of existing network management algorithms and methods in relation to PNM is provided. The concepts of PNM and the implications of employing PNM-algorithms are presented and discussed. Moreover, some of the practical differences of using a probabilistic fault detection algorithm compared to a deterministic method are investigated. Further, six probabilistic fault management algorithms that implement different aspects of PNM are presented. The algorithms are highly decentralized, adaptive and autonomous, and cover several problem areas, such as probabilistic fault detection and controllable detection performance; distributed and decentralized change detection in modeled link metrics; root-cause analysis in virtual overlays; event-correlation and pattern mining in data logs; and, probabilistic failure diagnosis. The probabilistic models (for a large part based on Bayesian parameter estimation) are memory-efficient and can be used and re-used for multiple purposes, such as performance monitoring, detection, and self-adjustment of the algorithm behavior. / <p>QC 20140509</p>