Experiment on the effectiveness of link structure for convenient cybershopping

Byunggon Yoo, Jinwoo Kim

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Designing an effective link structure for customer interfaces is critical for the success of cybermalls. The link structure comprises various types of links that connect a hypertext page with other pages. Links can be classified as either basic links based on the structure of the malls or add-on links to provide additional paths. Providing appropriate add-on links is essential for the convenience of navigation in a mall. In this study, we focus on the relation between the links and mental model, and maintain that combinations of add-on links according to the mental model of customers will increase the convenience and pleasure of cybershopping. For the study, add-on links were classified into next-to-peer links, up-to-parent links, and up-to-top links, and 8 different versions of experimental malls were constructed according to the combination of 3 add-on links. A total of 174 participants were involved in the experiment, they performed 9 shopping tasks, and were measured in terms of the rate of add-on links recalled and the convenience of navigation. The result of the experiment shows that the rate of recalled links has a significant relation to the convenience of navigation, although the convenience of navigation does not increase linearly with the number of add-on links in a cybermall. To construct the optimal add-on navigation structure, it is essential to construct links that fit customers' mental models.

Original languageEnglish
Pages (from-to)241-256
Number of pages16
JournalJournal of Organizational Computing and Electronic Commerce
Issue number4
Publication statusPublished - 2000

Bibliographical note

Funding Information:
This study was supported by the Soft Science Research Grant from the Korean Ministry of Science and Technology. We thank members of Human Computer Interaction Lab for their contribution in gathering information and analyzing data presented in this article.

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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