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Impacts of navigation structure, task complexity, and users’ domain knowledge on Web site usability—an empirical study

Author

Listed:
  • Xiang Fang

    (Miami University)

  • Clyde W. Holsapple

    (University of Kentucky)

Abstract

It is essential for designers of Web sites to understand what navigation structure results in better usability for knowledge acquisition tasks of varying complexity and the Web site users with different level of domain knowledge. Literature shows that multiple factors may exert influence on Web site usability. Navigation structure, task complexity, and user domain knowledge level are among of those factors. Hypotheses are developed about the usability of alternative navigation structures, with different task complexity and user domain knowledge level. Experiments are designed and conducted to test these hypotheses in terms of user performance (accuracy, speed) in accomplishing sets of simple and comparatively complex knowledge acquisition tasks. User perceptions of usability are also measured. Two rounds of experimentation are performed, one with participants who have been trained in the domain of production and operations management, the other with participants who have not been trained in this domain. The results show that a usage-oriented hierarchy or a combined hierarchy are navigation structures associated with statistically significantly higher performance usability than a subject-oriented hierarchy, for both simple and relatively complex knowledge acquisition task sets. A statistically significant effect of domain knowledge on the perception aspect of usability is identified. The study contributes to enhancing the comprehension of researchers, practitioners, and educators about design and usability of Web site navigation structures.

Suggested Citation

  • Xiang Fang & Clyde W. Holsapple, 2011. "Impacts of navigation structure, task complexity, and users’ domain knowledge on Web site usability—an empirical study," Information Systems Frontiers, Springer, vol. 13(4), pages 453-469, September.
  • Handle: RePEc:spr:infosf:v:13:y:2011:i:4:d:10.1007_s10796-010-9227-3
    DOI: 10.1007/s10796-010-9227-3
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    References listed on IDEAS

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    Cited by:

    1. R. Ramesh & H. Raghav Rao, 2011. "Editorial," Information Systems Frontiers, Springer, vol. 13(4), pages 451-452, September.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    3. César Guerra-García & Ismael Caballero & Mario Piattini, 2013. "Capturing data quality requirements for web applications by means of DQ_WebRE," Information Systems Frontiers, Springer, vol. 15(3), pages 433-445, July.

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