An agent-based model to simulate the public acceptability of social innovations

Abstract

The successful adoption of social innovations, such as renewable energy systems or pollution reduction plans in cities, depends, to a large extent, on the willingness and participation of the population in their development and implementation. We present an agent-based model (ABM) to analyze the process of citizen acceptability of a social innovation that uses a variety of agents to represent individual citizens and relevant groups of citizens. Citizen agents make use of the HUMAT cognitive decision-making model, based on psychosocial theories, to decide on their support for the social innovation considering how their needs will be satisfied if they decide to support (or not) the innovation project, and the influence exerted by the agents in their environment. The ABM was initially developed to represent the urban and transport planning superblock project in the city of Vitoria-Gasteiz (Spain). The ABM simulations make it possible to study the evolution of public acceptance of social innovation, with the results providing insights to the social dynamics and individual factors that affect the acceptance of the project, enabling an evaluation of how to devise new policies that increase public acceptance. Sufficiently generic to be easily adaptable to different types of social innovations, the ABM is a powerful tool to explore different scenarios and design strategies that foster the acceptance and sustainable adoption of social innovations.