SI Baviour Scenarios
In line with its interdisciplinary and innovative approach, SIMPACT will make use of advanced methods in economics.
In terms of foresight, simulation and scenario building supports social innovation stakeholders in coping with
innovation-related uncertainties. These methods contribute to understanding the various factors influencing the
evolutionary process of social innovation and defining favourable conditions by considering alternative development
paths and outcomes of social innovation. However, traditional econometric and innovation models have not provided
a comprehensive perspective that integrates
- 1 social, economic and environmental concerns;
- 2 heterogeneous agents' behaviours, roles and
Building a quantitative model with a focus on the interactions in the social innovation system is crucially important to reduce complexity
to an extent that allows for guiding our thinking and providing an idea how certain changes in the system would affect its dynamics and outcome.
The overall objective is to test and verify the findings, concepts, models and instruments developed throughout
the project by simulating different scenarios of how social innovation works in an economic «efficient» way.
To this end agent-based modelling is applied and - with the aim going beyond theoretical models - complementary
small-scale Go to Dialoguestakeholder experiments
will be carried out.
Given a strong focus on the heterogeneity of stakeholders (agents) in the social innovation system as well as the importance and complexity of
interaction between stakeholders, an agent-based modelling (ABM) approach will be used to model and test the economic dimensions of social
innovation elaborated during the project term. Rarely applied to social innovation, ABM is a promising method for studying innovation
processes and capturing economic complexities including micro-foundations and macro-outcomes. The models will characterise agents, environments,
decision rules and dynamic interaction processes. Moreover, the behaviours of specific social innovation stakeholders will be modelled in ways
which reflect the emergence of those tendencies from the interactions between individuals.
ABM will therefore allow us to specify a certain set of assumptions about reality and to predict the outputs to which they lead. In this way
we can help understand how public policy can facilitate social innovation and how social innovation can work successfully. To go beyond
modelling and integrate social innovation reality, participatory action research in form of stakeholder experiments will involve intermediaries
representing the target groups, policy makers and innovators in modelling and testing.