Computational modelling for decision-making: where, why, what, who and how

Calder, M., Craig, C., Culley, D., de Cani, R., Donnelly, C. A., Douglas, R., Edmonds, B., Gascoigne, J., Gilbert, N., Hargrove, C., Hinds, D., Lane, D. C. ORCID: https://orcid.org/0000-0001-6658-7041, Mitchell, D., Pavey, G., Robertson, D., Rosewell, B., Sherwin, S., Walport, M. and Wilson, A. (2018) Computational modelling for decision-making: where, why, what, who and how. Royal Society Open Science, 5 (6). 172096. ISSN 2054-5703 doi: 10.1098/rsos.172096

Abstract/Summary

In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/77926
Identification Number/DOI	10.1098/rsos.172096
Refereed	Yes
Divisions	Henley Business School > Digitalisation, Marketing and Entrepreneurship
Publisher	The Royal Society
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