A Methodology to Develop Agent-Based Models for Policy Design in Socio-Technical Systems Based on Qualitative Inquiry

Vittorio Nespeca*, Tina Comes, Frances Brazier

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Agent-based models (ABM) for policy design need to be grounded in empirical data. While many ABMs rely on quantitative data such as surveys, much empirical research in the social sciences is based on qualitative research methods such as interviews or observations that are hard to translate into a set of quantitative rules, leading to a gap in the phenomena that ABM can explain. As such, there is a lack of a clear methodology to systematically develop ABMs for policy design on the basis of qualitative empirical research. In this paper, a two-stage methodology is proposed that takes an exploratory approach to the development of ABMs in sociotechnical systems based on qualitative data. First, a conceptual framework centered on a particular policy design problem is developed based on empirical insights from one or more case studies. Second, the framework is used to guide the development of an ABM. This step is sensitive to the purpose of the model, which can be theoretical or empirical. The proposed methodology is illustrated by an application for disaster information management in Jakarta, resulting in an empirical descriptive ABM.
Original languageEnglish
Title of host publicationAdvances in Social Simulation
Subtitle of host publicationProceedings of the 16th Social Simulation Conference, 20–24 September 2021
EditorsM. Czupryna, B. Kamiński
PublisherSpringer, Cham
Number of pages16
ISBN (Electronic)978-3-030-92843-8
ISBN (Print)978-3-030-92842-1
Publication statusPublished - Sept 2022

Publication series

SeriesSpringer Proceedings in Complexity


  • Agent-based modelling
  • Disaster information management
  • Exploratory research
  • Qualitative research

Cite this