This thesis examines the research questions: does violence against peacekeepers have an impact on the peacekeeping mission? By building mainly on bunkerization and distancing theories, as well as mechanisms of peacekeeping effectiveness, a theory was formed that proposed that violence against peacekeepers would affect the mission outcome negatively. A hypothesis was derived from the theory, in which level of perception of security by local population was the dependent variable, and violence against peacekeepers was the independent variable. The hypothesis was tested using a qualitative within-case study comparing two different time-periods in the region of North Kivu in the Democratic Republic of the Congo. Due to lack of data, the results were inconclusive – evidence point to the presence of the proposed theory and mechanism, but no conclusion could be made confidently. Therefore, further research is needed. The thesis contributes to the field of peacekeeping research by being one of the first to use violence against peacekeepers as the independent variable, as well as expanding the concept of peacekeeping effectiveness by including the peacekept in the conceptualization and operationalization.

While peacekeeping operations have been researched for decades, due to a lack of data there are still many aspects of peacekeeping that remain unexplored. However, with the introduction of the Peacemakers at Risk dataset a wide array of dynamics and relationships can now be researched. This thesis uses this dataset and others in order to study the risk of violence towards peacekeepers and its effects on the peacekeepers’ ability to protect civilians. My main claim is that due to a shift in priorities, peacekeepers that are exposed to risks of violence have a decreased capacity to protect civilians which leads to increased civilian casualties. The study utilizes a time-series cross-sectional quantitative approach in order to study this relationship. After the introduction of control variables, drawn from the literature, to the multivariate regression, the study finds that there is no statistical significance to the relationship supported in the existing data. However, the study can ultimately not draw a generalizable conclusion due to a lack of observations.

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