Addressing urgent societal challenges like climate change requires large-scale sustainability transitions. These transitions are interdisciplinary, evolving within complex socio-technical systems where relationships among technological, ecological, institutional, and infrastructural elements continually change. Successful energy transitions demand public support, meticulous government planning, and coordination across various sectors.
Additionally, such socio-technical systems are multi-scalar, with properties across spatial, temporal, and administrative scales. Understanding how these characteristics evolve and how policy impacts cascade is crucial, necessitating the use of modelling and simulation (M&S) in analyzing such systems to aid effective decision-making.
Models, defined as instructions or equations representing real-world systems, aid understanding by accepting input trajectories and generating corresponding outputs. However, the complexity of sustainability transitions surpasses the capabilities of single models. Interacting components within socio-technical systems require diverse modelling methodologies at different scales. In addition, it is extremely challenging to encapsulate this complexity cost-effectively and credibly within a single model.
One way to overcome these challenges is to use multi-models, which we define as a composition of multiple (stand-alone) models, each of which may use a modelling methodology and scale most well-suited to capture relevant aspects within the system of interest.