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Policy Making and Modelling in a Complex World

In: Policy Practice and Digital Science

Author

Listed:
  • Wander Jager

    (University Groningen)

  • Bruce Edmonds

    (Manchester Metropolitan University)

Abstract

In this chapter, we discuss the consequences of complexity in the real world together with some meaningful ways of understanding and managing such situations. The implications of such complexity are that many social systems are unpredictable by nature, especially when in the presence of structural change (transitions). We shortly discuss the problems arising from a too-narrow focus on quantification in managing complex systems. We criticise some of the approaches that ignore these difficulties and pretend to predict using simplistic models. However, lack of predictability does not automatically imply a lack of managerial possibilities. We will discuss how some insights and tools from “complexity science” can help with such management. Managing a complex system requires a good understanding of the dynamics of the system in question—to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible. Agent-based simulation will be discussed as a tool that is suitable for this task, and its particular strengths and weaknesses for this are discussed.

Suggested Citation

  • Wander Jager & Bruce Edmonds, 2015. "Policy Making and Modelling in a Complex World," Public Administration and Information Technology, in: Marijn Janssen & Maria A. Wimmer & Ameneh Deljoo (ed.), Policy Practice and Digital Science, edition 127, chapter 4, pages 57-73, Springer.
    • Handle: RePEc:spr:paitcp:978-3-319-12784-2_4
    DOI: 10.1007/978-3-319-12784-2_4
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    Cited by:

    1. Kolkman, Daan, 2020. "The usefulness of algorithmic models in policy making," SocArXiv hpma8, Center for Open Science.

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