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When the Wait Isn’t So Bad: The Interacting Effects of Website Delay, Familiarity, and Breadth

Author

Listed:
  • Dennis F. Galletta

    (Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260)

  • Raymond M. Henry

    (Department of Management, Clemson University, Clemson, South Carolina 29634)

  • Scott McCoy

    (School of Business, College of William & Mary, Williamsburg, Virginia 23187-8795)

  • Peter Polak

    (School of Business Administration, University of Miami, Coral Gables, Florida 33124-6540)

Abstract

Although its popularity is widespread, the Web is well known for one particular drawback: its frequent delay when moving from one page to another. This experimental study examined whether delay and two other website design variables (site breadth and content familiarity) have interaction effects on user performance, attitudes, and behavioral intentions. The three experimental factors (delay, familiarity, and breadth) collectively impact the cognitive costs and penalties that users incur when making choices in their search for target information. An experiment was conducted with 160 undergraduate business majors in a completely counterbalanced, fully factorial design that exposed them to two websites and asked them to browse the sites for nine pieces of information. Results showed that all three factors have strong direct impacts on performance and user attitudes, in turn affecting behavioral intentions to return to the site, as might be expected. A significant three-way interaction was found between all three factors indicating that these factors not only individually impact a user’s experiences with a website, but also act in combination to either increase or decrease the costs a user incurs. Two separate analyses support an assertion that attitudes mediate the relationship of the three factors on behavioral intentions. The implications of these results for both researchers and practitioners are discussed. Additional research is needed to discover other factors that mitigate or accentuate the effects of delay, other effects of delay, and under what amounts of delay these effects occur.

Suggested Citation

  • Dennis F. Galletta & Raymond M. Henry & Scott McCoy & Peter Polak, 2006. "When the Wait Isn’t So Bad: The Interacting Effects of Website Delay, Familiarity, and Breadth," Information Systems Research, INFORMS, vol. 17(1), pages 20-37, March.
    • Handle: RePEc:inm:orisre:v:17:y:2006:i:1:p:20-37
    DOI: 10.1287/isre.1050.0073
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    References listed on IDEAS

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    Cited by:

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    6. Ulrich Gnewuch & Stefan Morana & Marc T. P. Adam & Alexander Maedche, 2022. "Opposing Effects of Response Time in Human–Chatbot Interaction," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(6), pages 773-791, December.
    7. Dimitrios Tsekouras & Benedict G. C. Dellaert & Bas Donkers & Gerald Häubl, 2020. "Product set granularity and consumer response to recommendations," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 186-202, March.
    8. Xueming Luo & Michelle Andrews & Zheng Fang & Chee Wei Phang, 2014. "Mobile Targeting," Management Science, INFORMS, vol. 60(7), pages 1738-1756, July.
    9. Lai, Kim Piew & Chong, Siong Choy & Ismail, Hishamuddin Bin & Tong, David Yoon Kin, 2014. "An explorative study of shopper-based salient e-servicescape attributes: A Means-End Chain approach," International Journal of Information Management, Elsevier, vol. 34(4), pages 517-532.
    10. Damon E. Campbell & John D. Wells & Joseph S. Valacich, 2013. "Breaking the Ice in B2C Relationships: Understanding Pre-Adoption E-Commerce Attraction," Information Systems Research, INFORMS, vol. 24(2), pages 219-238, June.

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