Browse by author
Lookup NU author(s): Professor Stephanie Glendinning, Professor Claire Walsh, Dr Mark Powell
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Abstract This paper explores the potential for learning from infrastructure shocks to develop strategic visions of infrastructure. The paper departs from theories of systems innovation, which understand infrastructure transitions as socio-technical re-configurations over long periods of time. The paper presents a complementary hypothesis to those theories about the possibility to catalyze systems change during or as a result of infrastructure shocks. According to this hypothesis, this change is possible because shocks enable higher order learning about infrastructure, which is learning involving a critical evaluation of existing principles and their suitability to complex situations. The hypothesis is examined empirically by studying the association between different types of infrastructure shock and different types of learning that emerge from those shocks using a meta-analysis of published work on infrastructure shocks. The analysis suggests that while there is considerable evidence of social learning from shocks, the context in which they occur will influence whether or not this is higher order learning. Further research is needed to develop feasible and practical ways to maximize the learning opportunities emerging from infrastructure shocks towards a transition to sustainable and resilient infrastructure.
Author(s): Castán Broto V, Glendinning S, Dewberry E, Walsh CL, Powell M
Publication type: Article
Publication status: Published
Journal: Technological Forecasting and Social Change
Year: 2014
Volume: 84
Pages: 186-196
Print publication date: 01/05/2014
Online publication date: 02/09/2013
Acceptance date: 05/08/2013
ISSN (print): 0040-1625
ISSN (electronic): 1873-5509
Publisher: Elsevier
URL: http://dx.doi.org/10.1016/j.techfore.2013.08.002
DOI: 10.1016/j.techfore.2013.08.002
Altmetrics provided by Altmetric
