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Agent-based Computational Economics in Management Accounting Research: Opportunities and Difficulties

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  • Friederike Wall
  • Stephan Leitner

Abstract

Agent-based computational economics (ACE) - while adopted comparably widely in other domains of managerial science - is a rather novel paradigm for management accounting research (MAR). This paper provides an overview of opportunities and difficulties that ACE may have for research in management accounting and, in particular, introduces a framework that researchers in management accounting may employ when considering ACE as a paradigm for their particular research endeavor. The framework builds on the two interrelated paradigmatic elements of ACE: a set of theoretical assumptions on economic agents and the approach of agent-based modeling. Particular focus is put on contrasting opportunities and difficulties of ACE in comparison to other research methods employed in MAR.

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  • Friederike Wall & Stephan Leitner, 2020. "Agent-based Computational Economics in Management Accounting Research: Opportunities and Difficulties," Papers 2011.03297, arXiv.org.
    • Handle: RePEc:arx:papers:2011.03297
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ravshanbek Khodzhimatov & Stephan Leitner & Friederike Wall, 2021. "Interactions between social norms and incentive mechanisms in organizations," Papers 2102.12309, arXiv.org.
    2. Ravshanbek Khodzhimatov & Stephan Leitner & Friederike Wall, 2021. "On the effect of social norms on performance in teams with distributed decision makers," Papers 2104.05993, arXiv.org, revised Apr 2021.
    3. Dario Blanco-Fernandez & Stephan Leitner & Alexandra Rausch, 2022. "Interactions between the individual and the group level in organizations: The case of learning and autonomous group adaptation," Papers 2203.09162, arXiv.org.
    4. Stephan Leitner, 2021. "On the Role of Incentives in Evolutionary Approaches to Organizational Design," Papers 2105.04514, arXiv.org, revised May 2021.
    5. Leitner, Stephan & Wall, Friederike, 2022. "Micro-level dynamics in hidden action situations with limited information," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 372-393.
    6. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Effects of limited and heterogeneous memory in hidden-action situations," Papers 2105.12469, arXiv.org.
    7. Ravshanbek Khodzhimatov & Stephan Leitner & Friederike Wall, 2022. "Controlling replication via the belief system in multi-unit organizations," Papers 2206.03786, arXiv.org.
    8. Edgard Bruno Cornacchione & Luciane Reginato & Joshua Onome Imoniana & Marcelo Souza, 2023. "Dynamic Pricing Models and Negotiating Agents: Developments in Management Accounting," Administrative Sciences, MDPI, vol. 13(2), pages 1-16, February.
    9. Iris Lorscheid & Matthias Meyer, 2021. "Toward a better understanding of team decision processes: combining laboratory experiments with agent-based modeling," Journal of Business Economics, Springer, vol. 91(9), pages 1431-1467, November.

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