Capturing Local Behavioural Feedbacks in Large Scale Models for Resource Optimization

Large-scale resource management and planning models have significantly advanced in the last few decades. Moreover, it is widely considered a valuable tool for resource management and planning at regional and global scales. However, they are limited in capturing behavioural feedbacks generated at the individual level, leading to policy resistance to large-scale interventions. In particular, we focus on interventions that enhance resource use efficiency for the purpose of conservation. Local behavioural feedbacks from consumers result in increased demand, leading to a reduction in the expected gain from the intervention, which affects the resource management and planning on a large scale. To address this limitation, in this paper, we integrate the local behaviour of the individual into the large-scale resource planning model. We present a conceptual interface between both models that is not only intuitive but also harmonizes the different spatial and temporal scales of the models. We run the model for a simplified example to understand the occurrence of the rebound effect due to the consumer's behaviour after the increased resource use efficiency. Finally, we show how the central planner may restrict rebounds by appropriately adjusting the resource allocations to individual processes.