Improving scenario methods in infrastructure planning: a case study of long distance travel and mobility in the uk under extreme weather uncertainty and a changing climate

Zanni, A.M., Goulden, M., Ryley, T. and Dingwall, R. ORCID: 0000-0002-1588-3796, 2016. Improving scenario methods in infrastructure planning: a case study of long distance travel and mobility in the uk under extreme weather uncertainty and a changing climate. Technological Forecasting and Social Change. ISSN 0040-1625

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Abstract

This paper develops a mixed method approach to infrastructure planning through a United Kingdom (UK) case study examining the impact of a changing climate on long distance travel and mobility between London and Glasgow. A novel combination of a qualitative method - Systematic Qualitative Foresight (SQF) - and quantitative simulation using discrete choice stated preference methods is applied. The main dataset is a travel behaviour survey of over 2,000 residents of London and Glasgow. Three illustrative SQF-based scenarios are developed incorporating society, technology and climate dimensions. For each scenario, the choice of long-distance travel mode by two groups of respondents generated by cluster analysis is simulated using stated preference survey data to describe the choices likely to be made by actors within each scenario. We demonstrate the importance of considering a wide range of variables when creating instruments for infrastructure planning decisions. Our results show that weather-related disruption has consequences for travel behaviour, with a considerable number of travellers deciding not to travel despite the importance of their trip. However, the vast majority of travellers would still travel. This should be considered by policy makers, and those responsible for transport infrastructure, in order to increase its resilience to extreme weather and demand, and better devise contingencies plans to contain, and minimise, the effect of the disruptions on the users. The method described has wider implications for infrastructure planning, particularly in its ability to engage a broader range of stakeholders and to avoid linear models of prediction. By emphasising the creation of a plausible decision space, it offers the possibility of increased robustness and resilience in infrastructure planning.

Item Type: Journal article
Publication Title: Technological Forecasting and Social Change
Creators: Zanni, A.M., Goulden, M., Ryley, T. and Dingwall, R.
Publisher: Elsevier
Date: 15 October 2016
ISSN: 0040-1625
Identifiers:
NumberType
10.1016/j.techfore.2016.10.002DOI
Divisions: Schools > School of Social Sciences
Depositing User: Jonathan Gallacher
Date Added: 25 Oct 2016 10:57
Last Modified: 09 Jun 2017 14:07
URI: http://irep.ntu.ac.uk/id/eprint/28939

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