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Using big data to map the relationship between time perspectives and economic outputs

Published online by Cambridge University Press:  20 November 2019

Christopher Y. Olivola Open the ORCID record for Christopher Y. Olivola [Opens in a new window] ,
Helen Susannah Moat Open the ORCID record for Helen Susannah Moat [Opens in a new window]  and
Tobias Preis Open the ORCID record for Tobias Preis [Opens in a new window]
Christopher Y. Olivola
Affiliation:
Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213olivola@cmu.eduhttps://sites.google.com/site/chrisolivola/ Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213
Helen Susannah Moat
Affiliation:
Data Science Lab, Behavioural Science Group, Warwick Business School, University of Warwick, Coventry CV4 7AL, United KingdomSuzy.Moat@wbs.ac.ukTobias.Preis@wbs.ac.ukhttp://www.wbs.ac.uk/about/person/suzy-moat/http://www.wbs.ac.uk/about/person/tobias-preis/ The Alan Turing Institute, British Library, London NW1 2DB, United Kingdom.
Tobias Preis
Affiliation:
Data Science Lab, Behavioural Science Group, Warwick Business School, University of Warwick, Coventry CV4 7AL, United KingdomSuzy.Moat@wbs.ac.ukTobias.Preis@wbs.ac.ukhttp://www.wbs.ac.uk/about/person/suzy-moat/http://www.wbs.ac.uk/about/person/tobias-preis/ The Alan Turing Institute, British Library, London NW1 2DB, United Kingdom.
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Abstract

Recent studies have shown that population-level time perspectives can be approximated using “big data” on search engine queries, and that these indices, in turn, predict the per-capita Gross Domestic Product of countries. Although these findings seem to support Baumard's suggestion that affluence makes people more future-oriented, they also reveal a more complex relationship between time perspectives and economic outputs.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e206
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Copyright
Copyright © Cambridge University Press 2019 

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References

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