Aim: The aim of this study was to investigate the structure of social marketing within a collaboration between non-profit organisations (NPOs) and business organisations as well as whether this collaboration facilitates the process of social marketing for the NPOs. For this purpose, Austin and Seitanidi´s (2012a, 2012b, 2014) Collaborative Value Creation (CVC) framework was applied to social marketing as value outcome by combining it with Andreasen and Kotler´s (2003) model of the social marketing process in NPOs. Method: A qualitative study was conducted based on secondary and primary data. Hereby, primary data was gathered from a total of seven NPOs and twelve respondents across Sweden by the use of face-to-face and phone interviews. Result & Conclusions: Two main findings were identified in this study. Firstly, within the process of social marketing in a corporate-NPO collaboration the NPOs predominantly plan and design the campaigns independently. Hereby, it is shown that the NPO´s organisational model of operation influences the collaboration structure. Secondly, it is demonstrated that the corporate-NPO collaboration facilitates the NPOs social marketing process. Suggestions for future research: Further investigations of NPOs could be undertaken by distinguishing between their organisational model and area of operation in order to complement the presented theoretical model of the social marketing process in the corporate-NPO collaboration. Additionally, the perspective of business organisations could be considered. Contribution of the thesis: The present study contributes to literature by providing a theoretical model based of the social marketing process in the corporate-NPO collaboration. It demonstrates that this collaboration facilitates the social marketing process of the NPOs.

Analyzing a huge amount of data becomes a tricky challenge and an opportunity for data miners and businessmen today. Knowledge management processes can deal with big knowledge source to find tacit intelligence making businesses more agile and effective. Data mining is a powerful tool working with big data to create capabilities of forecasting and analysis. Yet there is a lack of research on where and how data mining can add value in knowledge management processes in organizations to maximize valuable knowledge for innovation and business management. The knowledge management processes of a psychiatry section in a Swedish hospital was used as a case study for this thesis. Interviews with manager, psychiatrist, auxiliary nurse and data scientists are conducted. Collected data is analyzed to create values of data mining based on a value creation framework through the knowledge management processes of psychiatry section in the hospital. Relying on this process, the limitations and strengths are exposed; whereby, a data mining implementing framework is formulated, and potentials of data mining for the process are suggested to support for all employees of psychiatry section in the hospital in decision making and caring for patients.