TY - GEN
T1 - Effects of the User-Need State for Online Shopping
T2 - 14th International Conference on Information in Contemporary Society, iConference 2019
AU - Yu, Hsin Kai
AU - Wu, I. Chin
N1 - Funding Information:
Acknowledgments. This research was financially supported by the Ministry of Education (MOE) of Taiwan under Grant MOST 105-2410-H-003-153-MY3 & the Institute for Research Excellence in Learning Sciences of National Taiwan Normal University (NTNU) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the MOE in Taiwan are gratefully acknowledged.
Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - With the fast growth of e-commerce and the emerging trend of “New Retail”—that is, online and offline integration—the important research issues are how to know the best ways to collect and analyze users’ search behaviors online for a streamlined shopping process. Accordingly, we proposed a search pattern analytical method to analyze users’ search behavior in the entire shopping process on the target website from the perspective of the users’ need states. We have focused on the recommendation functions (RFs) and the search functions on Taobao.com to evaluate the effectiveness of each RF to support the online shopping process in different user-need states, namely in a goal-oriented or an exploratory-based approach to online shopping. We first adopted zero-order state transition matrices and then used lag sequential analysis (LSA) to derive the significant repeating search patterns. The results show that the goal-oriented shoppers tend to search directly, whereas exploratory shoppers tend to explore the categories of products as their initial RFs. In addition, goal-oriented users have much more simple search paths compared to the exploratory-based users when engaged in online shopping. Furthermore, based on the results of the LSA, there are two typical search patterns for goal-oriented users and no search pattern for the exploratory ones. Interestingly, the results reveal that exploratory-based users are easily stimulated by context even if they have moved to specific stores. The aim of this research is to summarize users’ search paths and patterns with different need states to help the e-store design the website.
AB - With the fast growth of e-commerce and the emerging trend of “New Retail”—that is, online and offline integration—the important research issues are how to know the best ways to collect and analyze users’ search behaviors online for a streamlined shopping process. Accordingly, we proposed a search pattern analytical method to analyze users’ search behavior in the entire shopping process on the target website from the perspective of the users’ need states. We have focused on the recommendation functions (RFs) and the search functions on Taobao.com to evaluate the effectiveness of each RF to support the online shopping process in different user-need states, namely in a goal-oriented or an exploratory-based approach to online shopping. We first adopted zero-order state transition matrices and then used lag sequential analysis (LSA) to derive the significant repeating search patterns. The results show that the goal-oriented shoppers tend to search directly, whereas exploratory shoppers tend to explore the categories of products as their initial RFs. In addition, goal-oriented users have much more simple search paths compared to the exploratory-based users when engaged in online shopping. Furthermore, based on the results of the LSA, there are two typical search patterns for goal-oriented users and no search pattern for the exploratory ones. Interestingly, the results reveal that exploratory-based users are easily stimulated by context even if they have moved to specific stores. The aim of this research is to summarize users’ search paths and patterns with different need states to help the e-store design the website.
KW - Lag sequential analysis
KW - Need state
KW - Recommendation function
KW - Search patterns
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U2 - 10.1007/978-3-030-15742-5_53
DO - 10.1007/978-3-030-15742-5_53
M3 - Conference contribution
AN - SCOPUS:85064043923
SN - 9783030157418
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 554
EP - 561
BT - Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings
A2 - Martin, Michelle H.
A2 - Nardi, Bonnie
A2 - Taylor, Natalie Greene
A2 - Christian-Lamb, Caitlin
PB - Springer Verlag
Y2 - 31 March 2019 through 3 April 2019
ER -