Mining consumer impulsivity from offline and online behavior

Zhang, Fuzheng, Yuan, Nicholas Jing, Zheng, Kai, Lian, Defu, Xie, Xing and Rui, Yong (2015). Mining consumer impulsivity from offline and online behavior. In: UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, (1281-1292). 7-11 September 2015. doi:10.1145/2750858.2805828

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Author Zhang, Fuzheng
Yuan, Nicholas Jing
Zheng, Kai
Lian, Defu
Xie, Xing
Rui, Yong
Title of paper Mining consumer impulsivity from offline and online behavior
Conference name ACM International Joint Conference on Pervasive and Ubiquitous Computing
Conference location Osaka, Japan
Conference dates 7-11 September 2015
Convener ACM
Proceedings title UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Journal name UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Place of Publication New York, NY, United States
Publisher ACM
Publication Year 2015
Sub-type Fully published paper
DOI 10.1145/2750858.2805828
Open Access Status Not Open Access
ISBN 9781450335744
Start page 1281
End page 1292
Total pages 12
Language eng
Formatted Abstract/Summary
Consumer impulsivity is a psychological feature characterizing the impulsive buying tendency. In this paper, by bridging consumer behavior with perceived stimuli on social networks, we present a computational framework, termed Consumer Impulsivity Model (CIM), for exploring a consumer's impulsivity in both offline and online context: consumption-related location visit indicating consumption patterns in the physical realm, and online shopping behavior indicating economic activities on the Internet. To demonstrate the effectiveness of CIM, we conduct extensive experiments, with a large dataset we have collected from thousands of consumers. The results show that 1) for 103 subjects, the inferred consumer impulsivity has a positive Pearson correlation with survey results in the situation of product and product category, respectively. 2) females inferred impulsivity is higher than males on average in the situation of product and product category, respectively. Age has a negative Pearson correlation with inferred impulsivity in the situation of POI, POI category and product category, respectively. 3) for next behavior prediction, our model defeats several presented baselines. These results suggest that our framework CIM offers a powerful paradigm for 1) presenting an effective measurement for consumer impulsivity. 2) uncovering the correlation between consumer impulsivity and demographic factors and 3) revealing that the introduction of impulsivity is effective in predicting consumer behavior.
Keyword Consumer impulsivity
Check-in
Online shopping
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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