This paper introduces a mixed-method research design for investigating complexity of social reality. The research design integrates grounded theory (Glaser and Strauss, 1967) and social simulation and is therefore called grounded simulation (GS). GS starts with in-depth investigations of complex social phenomena from perspectives of people who experience them. These investigations follow principles of grounded theory and enquire into contexts that research participants describe and the way they make sense of action in these contexts. Data analysis progresses inductively and outwards, from narratives of people who are at the centre of the phenomena to emerging constructs and theories. While the grounded theory fieldwork would have its own research outputs, its selected findings can be then carried to agent-based models for further investigation of social complexity. By representing social and economic agents, their contexts and actions as closely as possible, GS shortens the distance between research participants, who have real life experiences of the subject being modelled, and the virtual agents. Knowledge production in social simulation progresses generatively and upwards, moving from interactions at the individual level to emergent properties at the macro-level. GS experiments are thus suitable for studying the societal implications of meanings that emerge from the data collected in grounded theory. The paper illustrates how this research design can be used, by referring to a GS study on diffusion of innovations.
|Journal||Journal of Artificial Societies and Social Simulation|
|Publication status||Published - 31 Jan 2015|