TY - JOUR
T1 - Analyzing online consumer behavior in mobile and PC devices
T2 - A novel web usage mining approach
AU - Raphaeli, Orit
AU - Goldstein, Anat
AU - Fink, Lior
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/11
Y1 - 2017/11
N2 - We investigate and compare online consumer behavior on an e-retailer website in mobile versus PC devices, through the application of a web usage mining approach on clickstream data recorded in server-side log files. Online consumer behavior is characterized through both engagement measures and the discovery of common sequences of navigation patterns, using an innovative approach that combines footstep graph visualization with sequential association rule mining. We find that sessions conducted through mobile devices are more likely to consist of task-oriented behavior whereas sessions conducted through PC devices are characterized by a more exploration-oriented browsing behavior. Moreover, we find that certain sequence rules are associated with an increased likelihood of purchase in both mobile and PC sessions. The results demonstrate the value of our approach in analyzing online browsing behavior, across platforms, in the context of electronic retailing.
AB - We investigate and compare online consumer behavior on an e-retailer website in mobile versus PC devices, through the application of a web usage mining approach on clickstream data recorded in server-side log files. Online consumer behavior is characterized through both engagement measures and the discovery of common sequences of navigation patterns, using an innovative approach that combines footstep graph visualization with sequential association rule mining. We find that sessions conducted through mobile devices are more likely to consist of task-oriented behavior whereas sessions conducted through PC devices are characterized by a more exploration-oriented browsing behavior. Moreover, we find that certain sequence rules are associated with an increased likelihood of purchase in both mobile and PC sessions. The results demonstrate the value of our approach in analyzing online browsing behavior, across platforms, in the context of electronic retailing.
KW - E-commerce
KW - Footstep graph
KW - M-commerce
KW - Navigation patterns
KW - Online browsing behavior
KW - Sequential association rule mining
KW - Web usage mining
UR - http://www.scopus.com/inward/record.url?scp=85029576387&partnerID=8YFLogxK
U2 - 10.1016/j.elerap.2017.09.003
DO - 10.1016/j.elerap.2017.09.003
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AN - SCOPUS:85029576387
SN - 1567-4223
VL - 26
SP - 1
EP - 12
JO - Electronic Commerce Research and Applications
JF - Electronic Commerce Research and Applications
ER -