TY - CHAP A1 - Bresinsky, Markus A1 - Schroeder, Johanna A1 - Viscardi, Valerio T1 - Asymmetry in Trust Building – different perspectives in gains and losses explained via Prospect Theory T2 - Common Effort Conference, The Hague: 19 – 22 October 2020 N2 - Building trust within conflicts situations is a required process to establish a suitable environment for peace keeping and state building processes. However, it remains unclear what are the best ways to foster trusts between actors in a conflict environment. This study draws insights from the literature on trust and from Kahneman’s Prospect Theory to analyse the decision-making dynamics of the actors involved in a conflict and how these dynamics could affect the trust levels between those actors. To this purpose, the fourfold pattern of preferences I applied to a thought experiments where opposing actors in a conflict in the Sahel face the decision to accept or refuse a peace agreement when either one of the two actors face huge gains or catastrophic losses. The main findings is that, in those extreme situations, the actors involved tend to take unnational decisions that undermine the trust building process in the country. Therefore, it would be recommendable to boost situations where actors are negotiating in a more balanced environment. To this purpose, further research should be conducted on the ways to create such suitable environment for trust building. Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-24778 SP - 1 EP - 9 ER - TY - CHAP A1 - Bresinsky, Markus A1 - Schroeder, Johanna A1 - Viscardi, Valerio T1 - Strategic Forecasting with Machine Learning for Regional Geopolitical Analysis T2 - Η Περιφερειακή Επιστήμη, το μέλλον της και οι προκλήσεις στα πεδία της έρευνας και της εφαρμογής : 21ο Επιστημονικό Συνέδριο του Συνδέσμου Ελλήνων Περιφερειολόγων Ελληνικό Μεσογειακό Πανεπιστήμιο, Ηράκλειο Κρήτης, 16-17 Οκτωβρίου 2020 - Challenges for the Future of Regional Science: Research and Applications; 21st Conference: Heraklion, Crete, Oktober 2020 N2 - Strategic forecasting of regional geopolitical development is important for early warning and contingency planning. Open source data and machine learning can help to identify indicators for effective scenario development. Using data of the Bertelsmann Transformation Index (BTI) and the machine learning software Waikato Environment for Knowledge Analysis (WEKA), this paper gives an insight into the generation of a decision tree to provide indicators for forecasting regional development across parts of Northern and Western Africa. Results show that machine learning with open source data can support redefining indicator development but does not replace critical thinking. Y1 - 2020 UR - https://drive.google.com/file/d/1o2qAxcnq5srRr8r8okibHWwb4O0c69Oz/view SN - 978-618-00-2351-0 SP - 267 EP - 276 ER -