Testing the effectiveness of UN peace support operations
This research uses data to explore links between multilateral interventions and de-escalation of cross-border conflict.
Few studies have thoroughly explored potential correlations between specific characteristics of UN peace support operations – such as coalition type, mission size, number of peacekeepers, equipment type, mandate length, etc. – and conflict de-escalation. This study aims to address this knowledge gap using machine learning and advanced statistical techniques, guided by specialists whose expertise covers conflict dynamics, state fragility, multilateral interventions in Africa, and use of AI-based technologies for conflict prevention.
This study, led by researchers at UN University (UNU) will focus on UN peace support operations in central Africa and the Sahel. Quantitative data relating to peace support operations and conflict dynamics will be sourced from UN and conflict data sets. UNU’s research will test the effectiveness of this type of method and could lead to new insights on how the UN should intervene in cross-border conflicts.