Infrastructure decision-making: Opening up governance futures within techno-economic modelling
Katherine Lovell,
Jim Watson and
Ralitsa Hiteva
Technological Forecasting and Social Change, 2022, vol. 174, issue C
Abstract:
Techno-economic modelling is an important tool in evidence-building, futures assessment and decision-making in policy for socio-technical systems. However, critical assessment of the fit of sophisticated models into a decision-making context is often hidden or overlooked. Using the case of a national infrastructure systems model, this paper connects conceptions of infrastructure governance to techno-economic modelling assessing future infrastructure performance. Analysis of modelling input to a UK national level infrastructure policy process demonstrates the importance of governance understanding within infrastructure modelling for policy and it highlights the risks of not explicitly considering governance assumptions. Going on to pursue a more integrated approach to infrastructure modelling and governance, socio-technical researchers embedded within a model development research project are able to observe model development, analyse an early policy application, and facilitate discussions and co-development work with modellers. A methodological framework, building on recent transitions research ‘bridging’ socio-technical and techno-economic approaches, for connecting infrastructure governance understanding into techno-economic modelling analyses is presented and its use within this UK infrastructure modelling project is discussed. The integrated approach taken and the methodological framework developed are potential tools for researchers working with techno-economic models to support policy decisions; they show potential for further research on infrastructure futures.
Keywords: Infrastructure; Governance; Policy decisions; Techno-economic modelling; Socio-technical systems (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006417
DOI: 10.1016/j.techfore.2021.121208
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