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New Technology of Library and Information Service  2016, Vol. 32 Issue (4): 1-7    DOI: 10.11925/infotech.1003-3513.2016.04.01
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Multi-session Product Information Seeking Behaviors, Motivation, and Influencing Factors
Liu Honglian,Zhang Pengyi(),Wang Jun
Department of Information Management, Peking University, Beijing 100871, China
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[Objective] This research aims to examine the information seeking behavior patterns and contextual factors of online shoppers’ multi-sessional activities. [Methods] First, we analyzed 1,409,160 logs of an online shopping Web site (generated by 4,285 users) to discover their information seeking behaviors. Second, we used in-depth interviews to explore the users’ motivations. [Results] We found that multi-session shoppers were more likely to check detailed introduction to the products than simply browsing. The average interval between each session was 3 to 4 days. Personal preferences, needs, financial ability and time might lead the users to restore their previous sessions. Searching, shopping carts, bookmarks, browsing and personalized recommendation services were the major channels for users to restore previous sessions. [Limitations] Because of the limited number of participants, results from the interviews might not be generalizable to the whole population. [Conclusions] This research helps us understand the complex online shopping behaviors as well as improve services and user experience of E-commence Web sites.

Key wordsMulti-session online shopping      Information seeking behavior      E-commerce Web site     
Received: 12 November 2015      Published: 13 May 2016

Cite this article:

Liu Honglian,Zhang Pengyi,Wang Jun. Multi-session Product Information Seeking Behaviors, Motivation, and Influencing Factors. New Technology of Library and Information Service, 2016, 32(4): 1-7.

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[1] 中国互联网络信息中心. 2014年中国网络购物市场研究报告[EB/OL].
[1] (CNNIC. The 2014 Report of China’s Online Shopping Market Research [EB/ OL]. )
[2] Senecal S, Kalczynski P J, Nantel J.Consumers’ Decision- Making Process and Their Online Shopping Behavior: A Clickstream Analysis[J]. Journal of Business Research, 2005, 58(11): 1599-1608.
[3] Moe W W.Buying, Searching, or Browsing: Differentiating Between Online Shoppers Using In-Store Navigational Clickstream[J]. Journal of Consumer Psychology, 2003, 13(1): 29-39.
[4] 袁兴福, 张鹏翼, 刘洪莲, 等. 基于点击流的电商用户会话建模[J]. 图书情报工作, 2015, 59(1): 119-126.
[4] (Yuan Xingfu, Zhang Pengyi, Liu Honglian, et al.Modeling E-commerce User Session Behaviors Based on Click-through Sequences[J]. Library and Information Service, 2015, 59(1): 119-126.)
[5] Lee J, Podlaseck M, Schonberg E, et al.Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising[A]. // Applications of Data Mining to Electronic Commerce[M]. Springer, 2001: 59-84.
[6] 王蕾. 基于信息需求的消费者网络信息搜寻行为研究[J]. 情报理论与实践, 2013, 36(7): 90-93.
[6] (Wang Lei.Information Seeking Behavior Research Based on Information Need of Consumers[J]. Information Studies: Theory & Application, 2013, 36(7): 90-93.)
[7] 张文君, 王军, 徐山川. 电商用户需求状态的聚类分析——以淘宝网女装为例[J]. 现代图书情报技术, 2015(3): 67-74.
[7] (Zhang Wenjun, Wang Jun, Xu Shanchuan.The Probing of E-commerce User Need States by Page Cluster Analysis —— An Empirical Study on Women’s Clothes from[J]. New Technology of Library and Information Service, 2015(3): 67-74.)
[8] Gillenson M L, Sherrell D L.Enticing Online Consumers: An Extended Technology Acceptance Perspective[J]. Information & Management, 2002, 39(8): 705-719.
[9] Engel J F, Blackwell R D, Miniard P W.Consumer Behavior[J]. Journal of Consumer Policy, 1986, 9(4): 481.
[10] Teo T S, Yeong Y D.Assessing the Consumer Decision Process in the Digital Marketplace[J]. Omega, 2003, 31(5): 349-363.
[11] H?ubl G, Trifts V.Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids[J]. Marketing Science, 2000, 19(1): 4-21.
[12] Lin S J, Belkin N J.Modeling Multiple Information Seeking Episodes [C]. In: Proceedings of the 63rd Annual Meeting of ASIS, 2000.
[13] Vakkari P.A Theory of the Task-Based Information Retrieval Process: A Summary and Generalisation of a Longitudinal Study[J]. Journal of Documentation, 2001, 57(1): 44-60.
[14] Spink A.Multiple Search Sessions Model of End‐User Behavior: An Exploratory Study[J]. Journal of the American Society for Information Science, 1996, 47(8): 603-609.
[15] Komlodi A, Soergel D.Attorneys Interacting with Legal Information Systems: Tools for Mental Model Building and Task Integration[J]. Proceedings of the American Society for Information Science and Technology, 2002, 39(1): 152-163.
[16] 刘洪莲, 张鹏翼, 王军. 多会话网络购物商品信息搜寻行为研究[J]. 图书情报工作, 2015, 59(14): 117-125.
[16] (Liu Honglian, Zhang Pengyi, Wang Jun.Product Information Seeking Behavior of Multi-session Online Shopping Tasks[J]. Library and Information Service, 2015, 59(14): 117-125.)
[1] Wu Dan, Xiang Xue. An Experimental Study on Collaborative Information Seeking Behavior in Community Environment[J]. 现代图书情报技术, 2014, 30(12): 1-9.
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