Sustainable consumption is seen as a crucial political issue on the global agenda by politicians, the scientific community, and citizens who are worried about unsustainable consumption. However, several studies have shown that some consumers with "green" values do not consume sustainably – there is often a gap between attitude and behavior. One explanation is that the commitment to sustainable consumption is discouraged by barriers to action. For example, the supply of sustainable goods may be inadequate or the products too expensive. Such goods may be perceived as ineffective in their purpose to promote sustainable development, or perhaps it is believed that there are not enough other people who consume sustainably to make the individual effort worthwhile. However, some studies have indicated that there are also "reverse gaps". That is, there are people who are not particularly motivated to engage in sustainable consumption, but who do so anyway. The study examines why consumers sometimes engage in sustainable consumption (operationalized as a choice of environmental and Fairtrade certified products) but do not at other times. Research questions include which individual prerequisites (motivation and resources) are important for sustainable consumption, how they are distributed among citizens in Sweden, and finally whether perceived opportunities for sustainable consumption can form not only barriers but also "bridges" for engagement and how these are formed. The latter could explain the "reverse gaps" mentioned above. The author builds on the discussion about the challenges that sustainable development poses for the concept of citizenship. Researchers argue that sustainable development requires a transformation of traditional citizenship theory into a "sustainable citizenship". This is not limited by nation-state borders, takes into account past and future generations, and is open to the idea that responsibility-taking can, and sometimes should, be carried out in the private sphere. The dissertation is based on quantitative analysis of a (Swedish) representative survey and shows how consumers can be divided into different clusters based on their individual prerequisites: "Capable Critics", "Capital Weak Critics", "Conditionals" and ”Skeptics". Even if it is only the Capable Critics who have both the high motivation and a high level of resources that theoretically could be assumed to be necessary, there are a significant amount of consumers who choose environmental and Fairtrade labeled goods regularly across all clusters. These types of consumers encounter bridges to action by particularly positive perceived opportunities that make the engagement a little less demanding on individual prerequisites. The bridges are not the same for all clusters though. Their particular approach to sustainable consumption determines which factors are most important. / Det hållbara medborgarskapet

Following the significant transition from the traditional production industry to an informationbased economy, the telecommunications industry was faced with an explosion of innovation, resulting in a continuous change in user behaviour. The industry has made efforts to adapt to a more datadriven future, which has given rise to larger and more complex systems. Therefore, troubleshooting systems such as anomaly detection and root cause analysis are essential features for maintaining service quality and facilitating daily operations. This study aims to explore the possibilities, benefits, and drawbacks of implementing cluster analysis for anomaly detection in hybrid fibercoaxial networks. Based on the literature review on unsupervised anomaly detection and an assumption regarding the anomalous behaviour in hybrid fibercoaxial network data, the kmeans, SelfOrganizing Map, and Gaussian Mixture Model were implemented both with and without Principal Component Analysis. Analysis of the results demonstrated an increase in performance for all models when the Principal Component Analysis was applied, with kmeans outperforming both SelfOrganizing Map and Gaussian Mixture Model. On this basis, it is recommended to apply Principal Component Analysis for clusteringbased anomaly detection. Further research is necessary to identify whether cluster analysis is the most appropriate unsupervised anomaly detection approach. / Följt av övergången från den traditionella tillverkningsindustrin till en informationsbaserad ekonomi stod telekommunikationsbranschen inför en explosion av innovation. Detta skifte resulterade i en kontinuerlig förändring av användarbeteende och branschen tvingades genomgå stora ansträngningar för att lyckas anpassa sig till den mer datadrivna framtiden. Större och mer komplexa system utvecklades och således blev felsökningsfunktioner såsom anomalidetektering och rotfelsanalys centrala för att upprätthålla servicekvalitet samt underlätta för den dagliga driftverksamheten. Syftet med studien är att utforska de möjligheterna, för- samt nackdelar med att använda klusteranalys för anomalidetektering inom HFC- nätverk. Baserat på litteraturstudien för oövervakad anomalidetektering samt antaganden för anomalibeteenden inom HFC- data valdes algritmerna k- means, Self- Organizing Map och Gaussian Mixture Model att implementeras, både med och utan Principal Component Analysis. Analys av resultaten påvisade en uppenbar ökning av prestanda för samtliga modeller vid användning av PCA. Vidare överträffade k- means, både Self- Organizing Maps och Gaussian Mixture Model. Utifrån resultatanalysen rekommenderas det således att PCA bör tillämpas vid klusterings- baserad anomalidetektering. Vidare är ytterligare forskning nödvändig för att avgöra huruvida klusteranalys är den mest lämpliga metoden för oövervakad anomalidetektering.