Abstract
There is optimism that government use of »big data» will improve the outcomes of public policies. Despite such optimism, however, little evidence exits on the role big data can play in improving government service. In this study, we undertake one of the first quantitative studies showing the potential utility and limitations of »big data-based policymaking.» We explore the recent use of big data in the policymaking of the Seoul Metropolitan Government. In 2013, the government introduced the »Owl Bus» - a late night bus system - whose routes were selected based on government analyses of big data relating to citizens' late night taxi and mobile phone use. The findings suggest that the average number of passengers on the Owl Bus routes was significantly greater than on other daytime bus routes with comparable characteristics. That said, we also present the potential limitations of evidence-based policymaking in general, especially when politics and equity considerations are factored into the policymaking.
Original language | English |
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Title of host publication | Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 |
Editors | Yang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4492-4500 |
Number of pages | 9 |
ISBN (Electronic) | 9781538650356 |
DOIs | |
Publication status | Published - 2019 Jan 22 |
Event | 2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States Duration: 2018 Dec 10 → 2018 Dec 13 |
Publication series
Name | Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 |
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Conference
Conference | 2018 IEEE International Conference on Big Data, Big Data 2018 |
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Country/Territory | United States |
City | Seattle |
Period | 18/12/10 → 18/12/13 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Information Systems