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Comparing Basic Design Options for Management Accounting Systems with an Agent-Based Simulation

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Distributed Computing and Artificial Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 217))

Abstract

The paper applies an agent-based simulation to investigate the effectiveness of basic design options for management accounting systems. In particular, different settings of how to improve the information base by measurement of actual values in the course of adaptive walks are analyzed in the context of different levels of complexity and coordination modes. The agent-based simulation is based on the idea of NK fitness landscapes. Results provide broad, but no universal support for conventional wisdom that lower inaccuracies of information lead to more effective adaptation processes. Furthermore, results indicate that the effectiveness of improving judgmental information by actual values subtly depends on the complexity of the decisions and the coordination mode applied.

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Author information

Authors and Affiliations

  1. Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, 9020, Klagenfurt, Austria

    Friederike Wall

Authors
  1. Friederike Wall
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Correspondence to Friederike Wall .

Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Sakai, Osaka, Japan

    Sigeru Omatu

  2. Department of Computing Science, University of Minho, Braga, Portugal

    José Neves

  3. Dept. of Computing Science and Control, University of Salamanca, Salamanca, Spain

    Juan M. Corchado Rodriguez

  4. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Juan F Paz Santana

  5. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez Gonzalez

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Wall, F. (2013). Comparing Basic Design Options for Management Accounting Systems with an Agent-Based Simulation. In: Omatu, S., Neves, J., Rodriguez, J., Paz Santana, J., Gonzalez, S. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-00551-5_50

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  • DOI: https://doi.org/10.1007/978-3-319-00551-5_50

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00550-8

  • Online ISBN: 978-3-319-00551-5

  • eBook Packages: EngineeringEngineering (R0)

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