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Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review

Jadeja, N., Zhu, N. J., Lebcir, R. M. , Sassi, F., Holmes, A. & Ahmad, R. ORCID: 0000-0002-4294-7142 (2022). Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review. PLoS One, 17(2), e0263299. doi: 10.1371/journal.pone.0263299


Decision-makers for public policy are increasingly utilising systems approaches such as system dynamics (SD) modelling, which test alternative interventions or policies for their potential impact while accounting for complexity. These approaches, however, have not consistently included an economic efficiency analysis dimension. This systematic review aims to examine how, and in what ways, system dynamics modelling approaches incorporate economic efficiency analyses to inform decision-making on innovations (improvements in products, services, or processes) in the public sector, with a particular interest in health.

Methods and findings
Relevant studies (n = 29) were identified through a systematic search and screening of four electronic databases and backward citation search, and analysed for key characteristics and themes related to the analytical methods applied. Economic efficiency analysis approaches within SD broadly fell into two categories: as embedded sub-models or as cost calculations based on the outputs of the SD model. Embdedded sub-models within a dynamic SD framework can reveal a clear allocation of costs and benefits to periods of time, whereas cost calculations based on the SD model outputs can be useful for high-level resource allocation decisions.

This systematic review reveals that SD modelling is not currently used to its full potential to evaluate the technical or allocative efficiency of public sector innovations, particularly in health. The limited reporting on the experience or methodological challenges of applying allocated efficiency analyses with SD, particularly with dynamic embedded models, hampers common learning lessons to draw from and build on. Further application and comprehensive reporting of this approach would be welcome to develop the methodology further.

Publication Type: Article
Additional Information: © 2022 Jadeja et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Subjects: H Social Sciences > HC Economic History and Conditions
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HJ Public Finance
Departments: School of Health & Psychological Sciences > Healthcare Services Research & Management
Text - Published Version
Available under License Creative Commons: Attribution International Public License 4.0.

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