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Opposing Effects of Response Time in Human–Chatbot Interaction

Author

Listed:
  • Ulrich Gnewuch

    (Karlsruhe Institute of Technology)

  • Stefan Morana

    (Saarland University)

  • Marc T. P. Adam

    (University of Newcastle)

  • Alexander Maedche

    (Karlsruhe Institute of Technology)

Abstract

Research has shown that employing social cues (e.g., name, human-like avatar) in chatbot design enhances users’ social presence perceptions and their chatbot usage intentions. However, the picture is less clear for the social cue of chatbot response time. While some researchers argue that instant responses make chatbots appear unhuman-like, others suggest that delayed responses are perceived less positively. Drawing on social response theory and expectancy violations theory, this study investigates whether users’ prior experience with chatbots clarifies the inconsistencies in the literature. In a lab experiment (N = 202), participants interacted with a chatbot that responded either instantly or with a delay. The results reveal that a delayed response time has opposing effects on social presence and usage intentions and shed light on the differences between novice users and experienced users – that is, those who have not interacted with a chatbot before vs. those who have. This study contributes to information systems literature by identifying prior experience as a key moderating factor that shapes users’ social responses to chatbots and by reconciling inconsistencies in the literature regarding the role of chatbot response time. For practitioners, this study points out a drawback of the widely adopted “one-design-fits-all” approach to chatbot design.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:binfse:v:64:y:2022:i:6:d:10.1007_s12599-022-00755-x
    DOI: 10.1007/s12599-022-00755-x
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    References listed on IDEAS

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    1. Song, Mengmeng & Zhang, Huixian & Xing, Xinyu & Duan, Yucong, 2023. "Appreciation vs. apology: Research on the influence mechanism of chatbot service recovery based on politeness theory," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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