Towards three-stage recommender support for online consumers: Implications from a user study

Li Chen*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

4 Citations (Scopus)

Abstract

In this paper, a three-stage recommender support was implied from a user study. The purpose of the user study was to understand how to best utilize different types of social information (e.g., product popularity, user reviews) for facilitating online consumers' decision-making process in the e-commerce environment. Through both of in-depth tracking users' objective behavior and qualitative interviewing their reflective thoughts, we have not only refined a traditional two-stage decision process into a more precise three-stage process, but also identified at each stage what information users are inclined to seek for. Based on the study's results, suggestions were made to related recommender systems about their practical roles in the three-stage framework and how they can more effectively support users' information needs.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering, WISE 2010 - 11th International Conference, Proceedings
Pages365-375
Number of pages11
DOIs
Publication statusPublished - 2010
Event11th International Conference on Web Information Systems Engineering, WISE 2010 - Hong Kong, China
Duration: 12 Dec 201014 Dec 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6488 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Web Information Systems Engineering, WISE 2010
Country/TerritoryChina
CityHong Kong
Period12/12/1014/12/10

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • complex decision making
  • e-commerce
  • Flickr camera finder
  • high-value products
  • recommender supports
  • user study
  • users' information needs

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