Navigating complexity for next generation infrastructure: integrating governance and modelling analysis

Lovell, Katherine, Watson, Jim and Hiteva, Ralitsa (2017) Navigating complexity for next generation infrastructure: integrating governance and modelling analysis. International Symposium for Next Generation Infrastructure, One Great George Street, London, 11th-13th September 2017. Published in: ISNGI Conference Proceedings 2017. 250-260.

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A key theme within the delivery of next generation infrastructure, in the UK and around the world, can be a focus upon the provision of infrastructure services rather than upon reinforcing existing technologically centred systems (e.g. appropriate mobility rather than a series of transport systems). This user-centred approach to infrastructure offers the potential to remove some of the assumptions and inefficiencies present in the existing bounding of infrastructure provision within sectoral siloes. However, it also presents challenges over infrastructure decision-making and governance arrangements. One way to work with the complexity involved in navigating interdependencies between systems is the use of modelling tools to examine the effects of infrastructure needs across sectors. However, the centralised, birds-eye view possible within techno-economic infrastructure models is rarely reproduced within infrastructure governance. In practice, except in a very local context, the information processing and knowledge requirements, as well as a need to create checks and balances and meaningful connections to key stakeholders, would overwhelm the capacity of centralised, single point decisionmaking. The reality of decision making about infrastructures is that it is complex and distributed involving many actors and levels of authority. As a result, an awareness of the remits, priorities and processes of actors that are shaping both the performance requirements and development decisions taken in infrastructure is an important corollary to centralised techno-economic modelling analysis. The research presented here brings together modelling and governance thinking on infrastructure decision-making. This paper takes a governance perspective to analyse the use of the NISMOD model developed by the Infrastructure Transitions Research Consortium (ITRC) within the National Needs Assessment (NNA) process concluded in 2016. The different strategies explored within the NNA process and used to structure the use of the NISMOD model are analysed to consider what they could mean for governance – what governance processes are assumed? What requirements might these strategies place upon governance actors? This analysis is illustrated for three UK infrastructure sectors: Energy, Transport and Water. This paper highlights limitations within the application of this infrastructure model from a governance perspective. It also identifies several key areas of opportunity for improved treatment of governance within the modelling process. Further, points for the potential development of co-constituted modelling and governance analysis are suggested. This work is the first step in exploring possibilities for the systematic and rigorous incorporation and use of governance knowledge within infrastructure modelling.

Item Type: Conference Proceedings
Keywords: Infrastructure governance, innovation, infrastructure modelling
Schools and Departments: University of Sussex Business School > SPRU - Science Policy Research Unit
Subjects: H Social Sciences > HD Industries. Land use. Labour > HD2350.8 Large industry. Factory system. Big business > HD3611 Industrial policy. The state and industrial organisation Including licensing of occupations and professions, subsidies, inspection, government ownership, municipal services
T Technology > T Technology (General) > T0173.2 Technological change
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Depositing User: Katherine Lovell
Date Deposited: 05 Sep 2018 16:30
Last Modified: 15 Oct 2021 13:18

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Project NameSussex Project NumberFunderFunder Ref
MISTRAL: Multi-scale Infrastructure Systems AnalyticsG1927EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/N017064/1