Urban Big Data: City Management and Real Estate Markets
Name
Barkham-2019-UrbanDataAndRealEstate.pdf
Description
Accepted version
Size
1.13 MB
Format
Adobe PDF
Checksum (MD5)
05b972f1988d75eb13373bd2c67802a0
Author(s)
Barkham, Richard
Bokhari, Sheharyar
Saiz, Albert
Date Issued
2022
Publisher
Springer International Publishing
Citation
Barkham, R., Bokhari, S., Saiz, A. (2022). Urban Big Data: City Management and Real Estate Markets. In: Pardalos, P.M., Rassia, S.T., Tsokas, A. (eds) Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities. Springer Optimization and Its Applications, vol 186. Springer, Cham.
Version
Author's final manuscript
Abstract
In this chapter we discuss recent trends in the application of urban big data and their impact on real estate markets. We expect such technologies to improve quality of life and the productivity of cities over the long run.
We forecast that smart city technologies will reinforce the primacy of the most successful global metropolises at least for a decade or more. A few select metropolises in emerging countries may also leverage these technologies to leapfrog on the provision of local public services. In the long run, all cities throughout the urban system will end up adopting successful and cost-effective smart city initiatives. Nevertheless, smaller scale interventions are likely to crop up everywhere, even in the short run. Such targeted programs are more likely to improve conditions in blighted or relatively deprived neighborhoods, which could generate gentrification and higher valuations there.
It is unclear whether urban information systems will have a centralizing or suburbanizing impact. They are likely to make denser urban centers more attractive, but they are also bound to make suburban or exurban locations more accessible.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. Center for Real Estate
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Creative Commons Attribution-Noncommercial-ShareAlike
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DOI of Published Version
https://doi.org/10.1007/978-3-030-84459-2_10
