Predicting how people will behave presents a challenge in urban development. Will congestion arise with a new roundabout? At what time of day is the playground most frequently used? Do more shops necessarily improve street activity? Glaeser says that Google Street View, Yelp, and even the “digital exhaust” generated by our personal online activity can be useful sources of information. Big Data processed with predictive algorithms can offer valuable support for city politicians and decision makers.
Data generated by our smartphones often produce more up-to-date and geographically precise information than official statistics. Therefore, official statistics can be improved by combining smartphone input with new sources of data.
These new and detailed data sets demonstrate the greatest potential when linked with unexpected changes within the cities, such as increased parking fees or the opening of a new office building. This presents new opportunities to assess causality and evaluate existing policy. However, Glaeser also highlights that Big Data can help in operating public services and predict future economic activity, such as unemployment rates or spending patterns.
Edward Glaeser is a world-renowned researcher in urban economics. Mia Horn af Rantzien, CEO of SNS, says, “We are delighted that he has compiled the result from some of his and his co-workers’ latest studies in this SNS Research Brief. We hope the report will spark a discussion about how different societal actors in Sweden can use the new data sources.”
The report is part of the SNS research project on Sustainable Urban and Rural Planning.
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