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The influence of conversational agent embodiment and conversational relevance on socially desirable responding
Decision Support Systems
  • Ryan M. Schuetzler, University of Nebraska at Omaha
  • Justin Scott Giboney, Brigham Young University
  • G. Mark Grimes, University of Houston
  • Jay F. Nunamaker, Jr., University of Arizona
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Conversational agents (CAs) are becoming an increasingly common component in a wide range of information systems. A great deal of research to date has focused on enhancing traits that make CAs more humanlike. However, few studies have examined the influence such traits have on information disclosure. This research builds on self-disclosure, social desirability, and social presence theories to explain how CA anthropomorphism affects disclosure of personally sensitive information. Taken together, these theories suggest that as CAs become more humanlike, the social desirability of user responses will increase. In this study, we use a laboratory experiment to examine the influence of two elements of CA design—conversational relevance and embodiment—on the answers people give in response to sensitive and non-sensitive questions. We compare the responses given to various CAs to those given in a face-to-face interview and an online survey. The results show that for sensitive questions, CAs with better conversational abilities elicit more socially desirable responses from participants, with a less significant effect found for embodiment. These results suggest that for applications where eliciting honest answers to sensitive questions is important, CAs that are “better” in terms of humanlike realism may not be better for eliciting truthful responses to sensitive questions.


© 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (

Citation Information
Ryan M. Schuetzler, Justin Scott Giboney, G. Mark Grimes and Jay F. Nunamaker. "The influence of conversational agent embodiment and conversational relevance on socially desirable responding" Decision Support Systems Vol. 114 Iss. October 2018 (2018) p. 94 - 102
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