Designing a simulation-supported learning process for decision makers in the Mekong region

Abstract

Hydropower development, expansion of rubber plantations, large scale irrigated agriculture and sea level rise represent some of the key opportunities and risks perceived by decision makers in the Mekong region. Using opportunities wisely and responding effectively to risks without compromising a sustainable future demands insights into complex system responses. This paper describes a participatory learning process for decision makers and decision influencers in five countries located in the wider Mekong region. Structured engagement processes and mixed methods address the learning challenges associated with high levels of system complexity and the values of competing interests. The mixed methods approach involved a suite of disciplinary specific models, household surveys and an agent-based simulation model. Learning was facilitated by challenging beliefs articulated by stakeholders during the participatory process. In the context of the wider Mekong region modelling was an essential element and this paper is focused on the role of agent-based modelling and its effectiveness. A key insight from this study is that the potential to introduce doubt and challenge prevailing beliefs - and thereby to facilitate learning - increases with the complexity of the particular method implemented. Overall, this work emphasises the relevance of process design to effectively address cognitive barriers encountered at the science-policy interface and achieve targeted learning outcomes.