Library and Information Service >
Product Information Seeking Behavior of Multi-session Online Shopping Tasks
Received date: 2015-06-02
Revised date: 2015-06-25
Online published: 2015-07-20
[Purpose/significance] This research aims to explore users' browsing, search and sequence patterns in multi-session online shopping tasks.[Method/process] We examined 1993 users' click-through logs of 11514 shopping tasks, and conducted statistical, sequence and clustering analysis.[Result/conclusion] When there were less than 8 sessions in the shopping process, the users' browsing and searching behavior showed obvious patterns, and the first 4 sessions seemed to be the key stage for users; we found 6 typical kinds of information seeking behavior patterns. Results from this research can help us better understand the complex behavior of online shoppers and can be used in improving navigation design and recommendation strategy of online shopping sites.
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 . DOI: 10.13266/j.issn.0252-3116.2015.14.017
[1] 艾瑞咨询.2015年中国网络购物用户调研报告完整版[EB/OL].[2015-05-20]. http://report.iresearch.cn/2361.html.
[2] Moe W W, Fader P S. Uncovering patterns in cybershopping[J]. California Management Review, 2001, 43(4):106-117.
[3] 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.
[4] 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.
[5] 徐贇, 张盼, 丁婕. 只逛不买的电子商务用户分析——以淘宝网为例[J]. 信息系统学报, 2012 (2):64-75.
[6] 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, 31(3):67-74.
[7] Montgomery A L, Li Shibo, Srinivasan K, et al. Modeling online browsing and path analysis using clickstream data[J]. Marketing Science, 2004, 23(4):579-595.
[8] Lee J, Podlaseck M, Schonberg E, et al. Visualization and analysis of clickstream data of online stores for understanding Web merchandising[A]//Kohavi R, Provost F. Applications of Data Mining to Electronic Commerce. Springer:2001:59-84.
[9] 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.
[10] Lin Shin-jeng, Belkin N J. Modeling multiple information seeking episodes[C]//Proceedings of the ASIS Annual Meeting. Chicago:ASIS, 2000:133-147.
[11] 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.
[12] 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.
[13] Komlodi A, Soergel D. Attorneys interacting with legal information systems:Tools for mental model building and task integration[C]//Proceedings of the Annual Meeting of American Society for Information Science and Technology. Hoboken:Wiley,2002, 39(1):152-163.
[14] Nicosia F M, Choice B. Toward behavioral-behavioristic models[A]//Davis H L, Silk A J, Cook V J. Behavioral and Management Science in Marketing. New York:Wiley, 1978:12-55.
[15] Engel J F, Blackwell R D, Miniard P W. Consumer behavior[M]. New York:Dryder, 1995.
[16] Häubl G, Trifts V. Consumer decision making in online shopping environments:The effects of interactive decision aids[J]. Marketing Science, 2000, 19(1):4-21.
[17] Chen Su-Jane, Chang T Z. A descriptive model of online shopping process:Some empirical results[J]. International Journal of Service Industry Management, 2003, 14(5):556-569.
[18] 王实, 高文, 李锦涛,等. 路径聚类:在Web站点中的知识发现[J]. 计算机研究与发展, 2001, 38(4):482-486.
[19] 马力,焦李成,刘国营.一种基于路径聚类的Web用户访问模式发现算法[J].计算机科学,2004,31(8):140-141.
[20] 马晓艳, 唐雁. 一种基于用户浏览路径的Web用户聚类方法[J]. 西南师范大学学报(自然科学版), 2009, 34(3):93-97.
[21] 王微微, 夏秀峰, 李晓明. 一种基于用户行为的兴趣度模型[J]. 计算机工程与应用, 2012, 48(8):148-151.
[22] 张波,巫莉莉, 周敏.基于Web使用挖掘的用户行为分析[J]. 计算机科学,2006,33(8):213-214.
[23] Spink A, Ozmutlu H C, Ozmutlu S. Multitasking information seeking and searching processes[J]. Journal of the American Society for Information Science and Technology, 2002, 53(8):639-652.
[24] Mackay B, Watters C. Exploring multi-session Web tasks[C]//Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York:ACM, 2008:1187-1196.
[25] Gillenson M L, Sherrell D L. Enticing online consumers:An extended technology acceptance perspective[J]. Information & Management, 2002, 39(8):705-719.
[26] 朱志国. Web用户使用模式与兴趣挖掘方法研究[M]. 北京:北京师范大学出版社, 2012.
[27] 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.
[28] Wang Hongning, Song Yang, Chang Mingwei, et al. Learning to extract cross-session search tasks[C]//Proceedings of the 22nd International Conference on World Wide Web. New York:ACM, 2013:1353-1364.
[29] Microsoft. Microsoft sequence clustering algorithm technical reference [EB/OL].[2015-05-20]. https://msdn.microsoft.com/zh-cn/library/cc645866.aspx.
/
| 〈 |
|
〉 |
