 Fair weather forecasting? The shortcomings of big data for sustainable development, a case study from Hubballi‐Dharwad, IndiaAndrew Sudmant, Vincent Viguié (), Quentin Lepetit, Lucy Oates, Abhijit Datey, Andy Gouldson and David Watling Sustainable Development, 2021, vol. 29, issue 6, 1237-1248 Abstract: Sustainable urban mobility is an essential component of sustainable development but requires careful planning in rapidly growing urban areas. This paper investigates the value and limitations of Big Data for evaluating transport policies, plans, and projects in Hubballi‐Dharwad, India. Results show how Big Data can enable the outcomes of transport interventions to be evaluated more readily than conventional transport analysis. However, the analysis also found that this data may be less able to detect the impacts of travel behaviours in informal settlements, and the impact of extreme weather events. These potential shortcomings, as well as a lack of transparency around the methodology and data sources used by sources of Big Data, could generate unintended consequences and biases in transport planning. Reflecting on these challenges, and the wider implications for urban governance, we conclude that there is an urgent need for Big Data and other technical advances in urban modelling to be seen as compliments to, rather than substitutes for, wider methods of knowledge generation in urban areas. Date: 2021 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:wly:sustdv:v:29:y:2021:i:6:p:1237-1248 Access Statistics for this article Sustainable Development is currently edited by Richard Welford More articles in Sustainable Development from John Wiley & Sons, Ltd. |
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