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Algorithms are part of most online activities but act largely in the background and remain hidden to the general public. They are programmed pieces of software that are designed to consume massive amounts of data and progress it into easy consumable pieces of information. Furthermore, that software is able to draw connections between pieces of information and filter it based on relevance or other criteria. What these criteria are and what they are based on often remains a well-kept secret. Companies such as Facebook, Google, Twitter and Netflix all use algorithms to make sense of the ever-increasing amount of Data and suggest posts, movies or search results. With more and more people getting their news stories trough social media platforms and search engines, algorithms play an important role in the way we receive news. That lead to the questions of what power algorithms have over the news we see and what power they have over news organisations and journalism. To answer these broad questions, it was decided to focus on one large news organisations and examine what role algorithms play. The news organisation chosen for this research was The Guardian. In order to investigate these how and if algorithms are used, interviews with eight experts working at The Guardian were conducted. The informants were developers, engineers, product managers, editors and journalists in order to get a broader spectrum of possible frames in place. So as to analyse the interviews, tables were created to understand the way algorithms in relation to the institution of The Guardian and the power of editors were framed by the interviewees. One of the results that could be observed through the interviews and analysis was that algorithms will play an increasingly large role in The Guardian and possibly share their influence with editors. It can also be found that technology and news organisations will become more and more intertwined and data from users will be collected and analysed. The last part of the thesis discusses the impact of the results in a broader context and what further research can be done.

Introduction: Nowadays firms must focus on maintaining healthy finished goods inventory stocks in order to be able to decrease inventory costs, meet customer requirements and to obtain competitive advantage. However large decentralized manufacturing companies often face the problem of sub-optimization in inventory management in subsidiaries due to several different reasons. As a result, company loses its competitiveness. Thus, there is a need to coordinate inventory activities of subsidiaries to prevent sub-optimization. Purpose: The purpose of this thesis is to investigate whether coordination mechanisms highlighted in academic literature are used in practice on the example of manufacturing company with decentralized decision-making structure for optimization finished goods inventory stocks. Frame of reference: This research is based on theoretical framework and empirical findings. Empirical data were collected through personal interviews and retrieved from organisational documents. Methodology: The research strategy for this paper is a single case study. This strategy allows investigating topic in its real life context. The deductive approach is used for this research based on qualitative data. The major source of data collection was semi-structured interviews and the company's documents. For analysing data categorisation approach was applied. Conclusion: The study found that most of coordination mechanisms presented in scientific literature are used in practice. To achieve better results these mechanisms should be applied simultaneously and consistently since they complement each other. We also observed that coordination mechanisms indeed give positive results and are able to optimize inventory management.

The effect of using the eventual consistency model is evaluated, compared to the effect of immediate consistency, by increasing the stabilization time in both models and using the immediate consistent system as a baseline for evaluations. The immediate consistent system performs better if the information and the decisions are replicated adequately fast throughout the system. When the stabilization time increases the effectiveness of eventual consistency emerges, which is most obvious when time constraints make it difficult to propagate information and decisions. By using a simulation to extract data for evaluations, it is verified in this research that as the stabilization time between different parts of a system increases, the eventual consistency will always outperform the immediate consistent system. This statement is valid in all situations where consistency models are useful. Of secondary importance in the research, by adding more decision layers to the eventual consistency model, the performance output is increased significantly, as swift and less well calculated decisions can be thwarted and corrected using the second decision layer.