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Dealing with soft variables and data scarcity: lessons learnt from quantification in a participatory system dynamics modelling process

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  • Irene Pluchinotta
  • Ke Zhou
  • Nici Zimmermann

Abstract

System dynamics (SD) models are commonly used for structuring complex problems to support decision‐making. They are used to investigate areas in which limited knowledge is available, describing nonlinear relationships and including intangible elements. Although this explorative nature is one of the key advantages, it also represents a challenge for quantifying the intangible, i.e. more qualitative aspects of an SD model, especially when it is not possible to apply conventional analytical methods due to data scarcity. Procedures to obtain and analyse information using participatory approaches are limited. First, this article outlines existing quantification methods and related open questions when dealing with soft variables and data scarcity. Secondly, it summarises the quantification process developed during a participatory SD process, describing how we dealt with data scarcity and soft variables. Lastly, we suggest a quantification framework in relation to data availability and level of stakeholder engagement. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Suggested Citation

  • Irene Pluchinotta & Ke Zhou & Nici Zimmermann, 2024. "Dealing with soft variables and data scarcity: lessons learnt from quantification in a participatory system dynamics modelling process," System Dynamics Review, System Dynamics Society, vol. 40(4), October.
    • Handle: RePEc:bla:sysdyn:v:40:y:2024:i:4:n:e1770
    DOI: 10.1002/sdr.1770
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    References listed on IDEAS

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