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Structuring Qualitative Data for Agent-Based Modelling

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Abstract

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data that was collected through an ethnographic process served as input to the agent-based model. We also used the theoretical analysis performed on the data to define outcome variables for the simulation. We conclude by proposing an initial methodology that describes the use of ethnography in modelling.

Suggested Citation

  • Amineh Ghorbani & Gerard Dijkema & Noortje Schrauwen, 2015. "Structuring Qualitative Data for Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-2.
    • Handle: RePEc:jas:jasssj:2013-140-3
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    1. Lu Yang & Nigel Gilbert, 2008. "Getting Away From Numbers: Using Qualitative Observation For Agent-Based Modeling," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 175-185.
    2. Crawford, Sue E. S. & Ostrom, Elinor, 1995. "A Grammar of Institutions," American Political Science Review, Cambridge University Press, vol. 89(3), pages 582-600, September.
    3. Amineh Ghorbani & Pieter Bots & Virginia Dignum & Gerard Dijkema, 2013. "MAIA: a Framework for Developing Agent-Based Social Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(2), pages 1-9.
    4. J. Kasmire & Igor Nikolic & Gerard Dijkema, 2013. "Evolving Greenhouses: An Agent-Based Model of Universal Darwinism in Greenhouse Horticulture," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(4), pages 1-7.
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    1. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    2. Ahmadreza Asgharpourmasouleh & Atiye Sadeghi & Ali Yousofi, 2017. "A Grounded Agent-Based Model of Common Good Production in a Residential Complex: Applying Artificial Experiments," SAGE Open, , vol. 7(4), pages 21582440177, October.
    3. Anna Borawska & Malgorzata Latuszynska, 2020. "Incorporating Neuroscience Data into Agent-Based Simulation Models of Buyer Behavior," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1197-1212.
    4. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).

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