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Agent-based modeling as a tool for program design and evaluation

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  • Lawlor, Jennifer A.
  • McGirr, Sara

Abstract

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field.

Suggested Citation

  • Lawlor, Jennifer A. & McGirr, Sara, 2017. "Agent-based modeling as a tool for program design and evaluation," Evaluation and Program Planning, Elsevier, vol. 65(C), pages 131-138.
  • Handle: RePEc:eee:epplan:v:65:y:2017:i:c:p:131-138
    DOI: 10.1016/j.evalprogplan.2017.08.015
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    References listed on IDEAS

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    6. Gates, Emily F., 2016. "Making sense of the emerging conversation in evaluation about systems thinking and complexity science," Evaluation and Program Planning, Elsevier, vol. 59(C), pages 62-73.
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    8. Patton, Michael Quinn & Horton, Douglas, 2008. "Utilization-focused evaluation for agricultural innovation," ILAC Briefs 52533, Institutional Learning and Change (ILAC) Initiative.
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    Cited by:

    1. Ran Sun & James Nolan & Suren Kulshreshtha, 2022. "Agent-based modeling of policy induced agri-environmental technology adoption," SN Business & Economics, Springer, vol. 2(8), pages 1-26, August.

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