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Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods

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  • Moallemi, Enayat A.
  • Elsawah, Sondoss
  • Ryan, Michael J.

Abstract

Uncertainty in model-based decision support is commonly addressed using mixed methods rather than a single method. Different mixes of methods result in different modelling and processes for robust decision support, and subsequently different decision outcomes. This article focuses on the notion of ‘good’ modelling practice and develops a reporting guideline to make the use of multiple methods in robust decision support transparent. The guideline raises awareness about the characteristics of methodological and mixing design choices made throughout the modelling process. While not intending to be universally applicable, the guideline represents a move towards the development of universal standards to promote the generalisability, reproducibility, and comparability of different practices of robust decision support and to improve the recognition of the values of specific robust decision support frameworks. The article demonstrates the process for the use of mixed methods in an illustrative case in asset life cycle planning. The case study explains choices made at each step of this mixing process and presents justifications for the choices made, using the suggested guideline. The illustrative case also demonstrates generated decision insights resulted from the choices made.

Suggested Citation

  • Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    • Handle: RePEc:eee:matcom:v:175:y:2020:i:c:p:3-24
    DOI: 10.1016/j.matcom.2019.05.002
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