Journal article
Social bridges in urban purchase behavior
- Abstract:
- The understanding and modeling of human purchase behavior in city environment can have important implications in the study of urban economy and in the design and organization of cities. In this article, we study human purchase behavior at the community level and argue that people who live in different communities but work at close-by locations could act as “social bridges” between the respective communities and that they are correlated with similarity in community purchase behavior. We provide empirical evidence by studying millions of credit card transaction records for tens of thousands of individuals in a city environment during a period of three months. More specifically, we show that the number of social bridges between communities is a much stronger indicator of similarity in their purchase behavior than traditionally considered factors such as income and sociodemographic variables. Our findings also suggest that such an effect varies across different merchant categories, that the presence of female customers in social bridges is a stronger indicator compared to that of their male counterparts, and that there seems to be a geographical constraint for this effect, all of which may have implications in the studies of urban economy and data-driven urban planning.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 3.3MB, Terms of use)
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- Publisher copy:
- 10.1145/3149409
Authors
- Publisher:
- Association for Computing Machinery
- Journal:
- ACM Transactions on Intelligent Systems and Technology More from this journal
- Volume:
- 9
- Issue:
- 3
- Article number:
- 33
- Publication date:
- 2017-12-11
- Acceptance date:
- 2017-09-26
- DOI:
- EISSN:
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2157-6912
- ISSN:
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2157-6904
- Language:
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English
- Keywords:
- Pubs id:
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pubs:937122
- UUID:
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uuid:5b87c480-0a37-44e1-abf0-5f9c0c02fafb
- Local pid:
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pubs:937122
- Source identifiers:
-
937122
- Deposit date:
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2019-01-19
- ARK identifier:
Terms of use
- Copyright holder:
- Association for Computing Machinery
- Copyright date:
- 2017
- Notes:
- © 2017 ACM. This is the accepted manuscript version of the article. The final version is available online from the Association for Computing Machinery at: 10.1145/3149409
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