The influence of conversational agent embodiment and conversational relevance on socially desirable responding
Open accessAbstract
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.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previous research indicated that youths exhibit improved responsiveness and greater openness to CAs that possess virtual or physical representation, in contrast to disembodied CAs.
“previous research indicated that youths exhibit improved responsiveness and greater openness to CAs that possess virtual or physical representation, in contrast to disembodied CAs47”
From Use of automated conversational agents in improving young population mental health: a scoping review (2024) · cites this paper as [47]
Prior work shows that virtual agents mitigate social-desirability bias by reducing perceived judgement from human evaluators.
“Prior work further shows that virtual agents mitigate such bias by reducing perceived judgement from human evaluators (Schuetzler et al., 2018).”
From Countering dis/misinformation sharing by hindering moral disengagement in adolescence: the role of prosocial conversational modeling (2026) · cites this paper as Schuetzler et al., 2018
Cites
Grice, H. P. (1975) · Speech Acts · doi:10.1163/9789004368811_003 · Cited by 23,221 · see citing works
Organizational Information Requirements, Media Richness and Structural Design
Daft, R. L., & Lengel, R. H. (1986) · Management Science · doi:10.1287/mnsc.32.5.554 · Cited by 9,868 · see citing works
A new scale of social desirability independent of psychopathology.
Crowne, D. P., & Marlowe, D. (1960) · Journal of Consulting Psychology · doi:10.1037/h0047358 · Cited by 8,686 · cited 1× · see citing works
“Social desirability describes the way in which people would like to be seen by others [38].”
BackgroundEstimation of Relationships for Limited Dependent Variables
Tobin, J. (1958) · Econometrica · doi:10.2307/1907382 · Cited by 6,996 · see citing works
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3702 · Cited by 4,870 · see citing works
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · cited 2× · see citing works
“Early implementations of CAs were novelties designed to play speci fi c roles such as the Rogerian psychotherapist ELIZA [2], and PARRY — a paranoid patient [3].”
BackgroundThe social psychology of telecommunications
Short, J., Williams, E., & Christie, B. (1976) · Cited by 4,435 · see citing works
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · cited 1× · see citing works
“Prior research has found that people often treat computer systems as if they were human [1,29] — for example, by applying politeness norms [30], re-ciprocating self-disclosure [31], and expressing a feeling of connection [32].”
BackgroundThe social psychology of telecommunications
Gray, G. (1977) · Telecommunications Policy · doi:10.1016/0308-5961(77)90016-7 · Cited by 3,486 · see citing works
Sensitive questions in surveys.
Tourangeau, R., & Yan, T. (2007) · Psychological Bulletin · doi:10.1037/0033-2909.133.5.859 · Cited by 3,057 · cited 3× · see citing works
“Sensitive questions may result in either nonresponse or high measurement error compared to non-sensitive questions [45], and may elicit less truthful responses as answering them truthfully may cause negative consequences such as shame or punishment [46].”
BackgroundDeterminants of social desirability bias in sensitive surveys: a literature review
Krumpal, I. (2013) · Quality & Quantity · doi:10.1007/s11135-011-9640-9 · Cited by 2,860 · cited 1× · see citing works
“Sensitivity can be measured through nonresponse on survey items, or through separate ratings from people indicating their willingness to answer truthfully [47,48].”
BackgroundELIZA — a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1983) · Communications of the ACM · doi:10.1145/357980.357991 · Cited by 2,765 · see citing works
Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017) · JMIR Mental Health · doi:10.2196/mental.7785 · Cited by 2,730 · cited 2× · see citing works
“…in CAs taking on more serious roles such as serving as virtual personal assistants [8], conducting medical interviews [9,10], providing therapy for depression and anxiety [11], disseminating emergency response information [12], and conducting interviews to detect fraud and deception [13,14].”
BackgroundMethods of coping with social desirability bias: A review
Nederhof, A. J. (1985) · European Journal of Social Psychology · doi:10.1002/ejsp.2420150303 · Cited by 2,340 · cited 1× · see citing works
“Techniques such as indirect questioning [42] and self-and computer-administration of surveys [43], as opposed to human interviewing, are often used to mitigate the e ff ects of social desirability.”
MethodGefen, D., & Straub, D. W. (2004) · Omega · doi:10.1016/j.omega.2004.01.006 · Cited by 2,025 · cited 1× · see citing works
“On the positive side, social presence can increase trust [33], potentially making people feel more comfortable disclosing.”
BackgroundMcDonald, J. F., & Moffitt, R. A. (1980) · The Review of Economics and Statistics · doi:10.2307/1924766 · Cited by 1,874 · cited 1× · see citing works
“Because the drinks measure was skewed, we used a Tobit model [62,63] for drinks and a generalized linear model for health to test whether the interview type a ff ected disclosure.”
MethodWechsler, H. (1994) · JAMA · doi:10.1001/jama.272.21.1672 · Cited by 1,713 · see citing works
Wechsler, H., Lee, J. E., Kuo, M., Seibring, M., Nelson, T. F., & Lee, H. (2002) · Journal of American College Health · doi:10.1080/07448480209595713 · Cited by 1,457 · cited 1× · see citing works
“Alcohol use is a particularly sensitive topic for college student populations, as alcohol use and abuse on college campuses are salient and controversial topics [59].”
BackgroundBukimi no tani [the uncanny valley]
Mori, M. (1970) · Energy · Cited by 1,457 · see citing works
Tourangeau, R., & Smith, T. (1996) · Public Opinion Quarterly · doi:10.1086/297751 · Cited by 1,325 · cited 2× · see citing works
“Information being disclosed about oneself may present the discloser in a positive, negative, or neutral way, and questions may or may not be viewed by the discloser as being sensitive [37].”
BackgroundSocial Desirability Bias in CATI, IVR, and Web Surveys: The Effects of Mode and Question Sensitivity
Kreuter, F., Presser, S., & Tourangeau, R. (2008) · Public Opinion Quarterly · doi:10.1093/poq/nfn063 · Cited by 1,225 · cited 2× · see citing works
“This is consistent with previous research showing that social desirability e ff ects of question administration mode are stronger for undesirable rather than for desirable actions [46].”
BackgroundResultThe Relationship of Social Presence and Interaction in Online Classes
Tu, C., & McIsaac, M. S. (2002) · American Journal of Distance Education · doi:10.1207/s15389286ajde1603_2 · Cited by 1,196 · cited 1× · see citing works
“In addition to the richness of the medium, the way in which the medium is used and the information conveyed — i.e., the conversational capability of one's partner — also in fl uence perceptions of social presence [26,27].”
BackgroundNowak, K. L., & Biocca, F. (2003) · Presence - Teleoperators and Virtual Environments · doi:10.1162/105474603322761289 · Cited by 1,162 · see citing works
Perkins, H. W., & Berkowitz, A. D. (1986) · International Journal of the Addictions · doi:10.3109/10826088609077249 · Cited by 1,017 · cited 1× · see citing works
“For example, individuals who are under the legal age to consume alcohol tend to overestimate drinking behaviors of their peers, potentially increasing the perceived desirability of this behavior within that group [49].”
BackgroundBinge Drinking Among US Adults
Naimi, T. S., Brewer, R. D., Mokdad, A., Denny, C., Serdula, M. K., & Marks, J. S. (2003) · JAMA · doi:10.1001/jama.289.1.70 · Cited by 987 · see citing works
Hassanein, K., & Head, M. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.11.018 · Cited by 986 · cited 1× · see citing works
“Social presence is frequently manipulated via attributes of the communication medium, such as its richness [22,23].”
BackgroundIt's only a computer: virtual humans increase willingness to disclose
Lucas, G. M., Gratch, J., King, A., & Morency, L.-P. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.043 · Cited by 977 · see citing works
Health and Behavioral Consequences of Binge Drinking in College
Wechsler, H. (1994) · JAMA · doi:10.1001/jama.1994.03520210056032 · Cited by 917 · see citing works
Intimate Exchanges: Using Computers to Elicit Self-Disclosure from Consumers
Moon, Y. (2000) · Journal of Consumer Research · doi:10.1086/209566 · Cited by 842 · cited 1× · see citing works
“Prior research has found that people often treat computer systems as if they were human [1,29] — for example, by applying politeness norms [30], re-ciprocating self-disclosure [31], and expressing a feeling of connection [32].”
BackgroundRichman, W. L., Kiesler, S. B., Weisband, S. P., & Drasgow, F. (1999) · Journal of Applied Psychology · doi:10.1037/0021-9010.84.5.754 · Cited by 821 · cited 2× · see citing works
“Interactions with lower social presence, such as computeradministered surveys, have been found to result in responses that are less biased by social desirability than those in face-to-face interviews [20].”
BackgroundSocial desirability scales: More substance than style.
McCrae, R. R., & Costa, P. T. (1983) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.51.6.882 · Cited by 735 · cited 1× · see citing works
“The e ff ect of social desirability in survey responses has been studied extensively, as it presents a serious threat to the validity of survey measures [19,40,41].”
BackgroundYoo, Y., & Alavi, M. (2001) · MIS Quarterly · doi:10.2307/3250922 · Cited by 679 · cited 1× · see citing works
“As a communication medium allows for richer content, the media evokes a greater sense of social presence compared to less rich media [24] and can give additional context to communication [25], thus increasing social presence.”
BackgroundHo, A., Hancock, J., & Miner, A. S. (2018) · Journal of Communication · doi:10.1093/joc/jqy026 · Cited by 629 · cited 1× · see citing works
“Prior research has found that people often treat computer systems as if they were human [1,29] — for example, by applying politeness norms [30], re-ciprocating self-disclosure [31], and expressing a feeling of connection [32].”
BackgroundNass, C., Steuer, J., & Tauber, E. R. (1994) · Conference companion on Human factors in computing systems - CHI '94 · doi:10.1145/259963.260288 · Cited by 579 · see citing works
Social desirability biases in self-reported alcohol consumption and harms
Davis, C. G., Thake, J., & Vilhena, N. (2010) · Addictive Behaviors · doi:10.1016/j.addbeh.2009.11.001 · Cited by 524 · cited 1× · see citing works
“However, if an authority fi gure, such as a parent or teacher, asks the same underage individual about drinking, the question may be deemed sensitive and of negative valence, thus leading the re-spondent to hide or underreport drinking to avoid punishment [50].”
BackgroundBente, G., Rüggenberg, S., Krämer, N. C., & Eschenburg, F. (2008) · Human Communication Research · doi:10.1111/j.1468-2958.2008.00322.x · Cited by 509 · cited 1× · see citing works
“Research on embodiment e ff ects on social presence have often used avatars — digital representations of a human — compared to no visual representation of the communicator [56].”
BackgroundSelf-Deception and Impression Management in Test Responses
Paulhus, D. L. (1986) · Springer eBooks · doi:10.1007/978-3-642-70751-3_8 · Cited by 468 · cited 1× · see citing works
“This follows the methodology used in previous research on socially desirable responding [60,61].”
MethodSocial desirability and response to perceived situational demands.
Marlow, D., & Crowne, D. P. (1961) · Journal of Consulting Psychology · doi:10.1037/h0041627 · Cited by 457 · cited 1× · see citing works
“This follows the methodology used in previous research on socially desirable responding [60,61].”
MethodPosey, C., Lowry, P. B., Roberts, T., & Ellis, S. (2010) · European Journal of Information Systems · doi:10.1057/ejis.2010.15 · Cited by 435 · see citing works
Bailenson, J., Swinth, K. R., Hoyt, C. L., Persky, S., Dimov, A., & Blascovich, J. (2005) · Presence - Teleoperators and Virtual Environments · doi:10.1162/105474605774785235 · Cited by 428 · cited 1× · see citing works
“Social presence may also be manipulated through embodiment — the visual representation of an agent [55].”
BackgroundAre People Polite to Computers? Responses to Computer‐Based Interviewing Systems1
Nass, C., Moon, Y., & Carney, P. (1999) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1999.tb00142.x · Cited by 408 · cited 1× · see citing works
“Given our understanding of how users perceive computers as social actors [28], the in fl uence of social presence on disclosure should apply whether the conversation partner is a human or a computer.”
BackgroundSproull, L., Subramani, M., Kiesler, S., Walker, J., & Waters, K. (1996) · Human-Computer Interaction · doi:10.1207/s15327051hci1102_1 · Cited by 399 · cited 1× · see citing works
“When a CA is given a facial representation, it makes the CA appear more humanlike [57] and increases the naturalness of the communication [58].”
MethodMEDIA EQUATION: HOW PEOPLE TREAT COMPUTERS, TELEVISION, AND NEW MEDIA LIKE REAL PEOPLE AND PLACES
Soash, R. L. (1999) · Collection Management · doi:10.1300/j105v24n03_14 · Cited by 348 · see citing works
Wallace, R. S. (2007) · Springer eBooks · doi:10.1007/978-1-4020-6710-5_13 · Cited by 335 · cited 1× · see citing works
“As technological capabilities have advanced, these “ toy ” CAs have given way to the emergence of sophisticated and generalizable frameworks that parse user responses and mimic understanding by responding to pre-de fi ned phrases or keywords (e.g., A.L.I.C.E. [4] and ChatScript [5]) [6].”
BackgroundSocial desirability is the same in offline, online, and paper surveys: A meta-analysis
Dodou, D., & de Winter, J. C. F. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.005 · Cited by 325 · see citing works
Embodied Conversational Agent-Based Kiosk for Automated Interviewing
Nunamaker, J. F., Derrick, D. C., Elkins, A. C., Burgoon, J. K., & Patton, M. W. (2011) · Journal of Management Information Systems · doi:10.2753/mis0742-1222280102 · Cited by 280 · cited 2× · see citing works
“…in CAs taking on more serious roles such as serving as virtual personal assistants [8], conducting medical interviews [9,10], providing therapy for depression and anxiety [11], disseminating emergency response information [12], and conducting interviews to detect fraud and deception [13,14].”
BackgroundSelf-citationFacial expression of emotion and perception of the Uncanny Valley in virtual characters
Tinwell, A., Grimshaw, M., Nabi, D. A., & Williams, A. B. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.10.018 · Cited by 269 · cited 1× · see citing works
“It has been suggested that CAs that are perceived as more humanlike may have the unintended consequence of increasing discomfort in users [17,18].”
BackgroundKlopfenstein, L. C., Delpriori, S., Malatini, S., & Bogliolo, A. (2017) · Designing Interactive Systems Conference · doi:10.1145/3064663.3064672 · Cited by 257 · cited 1× · see citing works
“This increase in pervasiveness and utility has resulted in CAs taking on more serious roles such as serving as virtual personal assistants [8], conducting medical interviews [9,10], providing therapy for depression and anxiety [11], disseminating emergency response information [12], and conducting…”
BackgroundUsing a human face in an interface
Walker, J. H., Sproull, L. S., & Subramani, R. (1994) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/191666.191708 · Cited by 228 · cited 1× · see citing works
“Conversely, greater social presence can also result in negative outcomes as people consider the social desirability of their responses and how their responses might influence their communication partner's opinion of them [34].”
Assessment of suicide ideation and parasuicide: Hopelessness and social desirability.
Linehan, M. M., & Nielsen, S. L. (1981) · Journal of Consulting and Clinical Psychology · doi:10.1037//0022-006x.49.5.773 · Cited by 227 · see citing works
Pearce, W. B., & Sharp, S. M. (1973) · Journal of Communication · doi:10.1111/j.1460-2466.1973.tb00958.x · Cited by 204 · cited 1× · see citing works
“Self-disclosure is the extent to which individuals share information about themselves purposely and voluntarily [35,36].”
BackgroundPersonality Assessment via Questionnaires
Angleitner, A., & Wiggins, J. S. (1986) · Springer eBooks · doi:10.1007/978-3-642-70751-3 · Cited by 195 · see citing works
Epstein, R., Roberts, G., & Beber, G. (2008) · DIAL (Catholic University of Leuven) · doi:10.1007/978-1-4020-6710-5 · Cited by 171 · see citing works
Krysan, M., & Couper, M. P. (2003) · Social Psychology Quarterly · doi:10.2307/1519835 · Cited by 169 · cited 1× · see citing works
“The e ff ect of social desirability in survey responses has been studied extensively, as it presents a serious threat to the validity of survey measures [19,40,41].”
BackgroundAssessment of suicide ideation and parasuicide: Hopelessness and social desirability.
Linehan, M. M., & Nielsen, S. L. (1981) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.49.5.773 · Cited by 164 · cited 1× · see citing works
“…scenarios, the information being solicited may be considered sensitive and individuals may be unwilling or hesitant to disclose the information — not necessarily for nefarious reasons, but rather to avoid providing answers society would deem unacceptable or con-fessing undesirable behavior [15].”
BackgroundPickard, M. D., Roster, C. A., & Chen, Y. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.08.004 · Cited by 157 · see citing works
Colby, K. M., Hilf, F. D., Weber, S., & KRAEMER, H. C. (1972) · Artificial Intelligence · doi:10.1016/0004-3702(72)90049-5 · Cited by 155 · cited 1× · see citing works
“Early implementations of CAs were novelties designed to play speci fi c roles such as the Rogerian psychotherapist ELIZA [2], and PARRY — a paranoid patient [3].”
MethodPerceiving artificial social agents
Holtgraves, T. M., Ross, S. J., Weywadt, C. R., & Han, T. L. (2007) · Computers in Human Behavior · doi:10.1016/j.chb.2006.02.017 · Cited by 131 · cited 1× · see citing works
“When a CA is given a facial representation, it makes the CA appear more humanlike [57] and increases the naturalness of the communication [58].”
MethodHumanizing self-administered surveys: experiments on social presence in web and IVR surveys
Tourangeau, R., Couper, M. P., & Steiger, D. M. (2003) · Computers in Human Behavior · doi:10.1016/s0747-5632(02)00032-8 · Cited by 129 · cited 2× · see citing works
“Techniques such as indirect questioning [42] and self-and computer-administration of surveys [43], as opposed to human interviewing, are often used to mitigate the e ff ects of social desirability.”
BackgroundMethodDiscourse coherence and theory of relevance: Stumbling blocks in search of a unified theory
Giora, R. (1997) · Journal of Pragmatics · doi:10.1016/0378-2166(95)00065-8 · Cited by 112 · cited 1× · see citing works
“Conversational relevance is present when the response to a message is related to the current topic of conversation [52,53].”
BackgroundSakshaug, J. W., Yan, T., & Tourangeau, R. (2010) · Public Opinion Quarterly · doi:10.1093/poq/nfq057 · Cited by 108 · cited 1× · see citing works
“When people are asked to disclose socially undesirable information about themselves social de-sirability bias can have a strong e ff ect on reporting [39].”
BackgroundAvatar e-mail versus traditional e-mail: Perceptual difference and media selection difference
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2008) · Decision Support Systems · doi:10.1016/j.dss.2007.11.008 · Cited by 68 · cited 1× · see citing works
“As a communication medium allows for richer content, the media evokes a greater sense of social presence compared to less rich media [24] and can give additional context to communication [25], thus increasing social presence.”
BackgroundWhy Do Survey Respondents Disclose More When Computers Ask the Questions?
Lind, L. H., Schober, M. F., Conrad, F. G., & Reichert, H. (2013) · Public Opinion Quarterly · doi:10.1093/poq/nft038 · Cited by 65 · see citing works
Schumaker, R. P., Ginsburg, M., Chen, H., & Ying, L. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.07.001 · Cited by 42 · cited 1× · see citing works
“As technological capabilities have advanced, these “ toy ” CAs have given way to the emergence of sophisticated and generalizable frameworks that parse user responses and mimic understanding by responding to pre-de fi ned phrases or keywords (e.g., A.L.I.C.E. [4] and ChatScript [5]) [6].”
BackgroundComprehension and engagement in survey interviews with virtual agents
Conrad, F. G., Schober, M. F., Jans, M., Orlowski, R. A., Nielsen, D., & Levenstein, R. M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01578 · Cited by 39 · see citing works
MP15-03 NOVEL APPLICATION FOR SEXUAL TRANSMITTED INFECTION SCREENING WITH AN AI CHATBOT
Kobori, Y., Osaka, A., Soh, S., & Okada, H. (2018) · Journal of Urology · doi:10.1016/j.juro.2018.02.516 · Cited by 29 · see citing works
Leveraging Question Answer technology to address terrorism inquiry
Schumaker, R. P., & Chen, H. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.04.007 · Cited by 23 · cited 1× · see citing works
“…in CAs taking on more serious roles such as serving as virtual personal assistants [8], conducting medical interviews [9,10], providing therapy for depression and anxiety [11], disseminating emergency response information [12], and conducting interviews to detect fraud and deception [13,14].”
BackgroundPickard, M. D., Burns, M. B., & Moffitt, K. C. (2013) · Journal of Information Systems · doi:10.2308/isys-50561 · Cited by 20 · cited 1× · see citing works
“…in CAs taking on more serious roles such as serving as virtual personal assistants [8], conducting medical interviews [9,10], providing therapy for depression and anxiety [11], disseminating emergency response information [12], and conducting interviews to detect fraud and deception [13,14].”
BackgroundPickard, M. D. (2012) · UA Campus Repository (The University of Arizona) · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
An Emerging Theory of Avatar Marketing
Miao, F., Kozlenkova, I. V., Wang, H., Xie, T., & Palmatier, R. W. (2022) · Journal of Marketing · doi:10.1177/0022242921996646 · Cited by 688 · see citing works
“For example, Bickmore, Pfeifer, and Jack (2009) found that an avatar nurse incorporating social content in its scripted conversations produced better patient experiences, but Schuetzler et al. (2018) reported that a scripted, task-focused avatar interviewer elicits more socially biased responses.”
BackgroundInfluentialThe impact of chatbot conversational skill on engagement and perceived humanness
Schuetzler, R. M., Grimes, G. M., & Scott Giboney, J. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1790204 · Cited by 357 · see citing works
Self-citationMariani, M. M., Hashemi, N., & Wirtz, J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113838 · Cited by 378 · see citing works
Chandra, S., Shirish, A., & Srivastava, S. C. (2022) · Journal of Management Information Systems · doi:10.1080/07421222.2022.2127441 · Cited by 325 · see citing works
“However, it must be noted that efforts to enhance user engagement can also be used by unscrupulous agents to commit fraud and deception [109, 110].”
BackgroundYen, C., & Chiang, M.-C. (2021) · Behaviour & Information Technology · doi:10.1080/0144929x.2020.1743362 · Cited by 297 · see citing works
“Admittedly, one of the fast rising AI trends nowadays involves utilising applications that interact with users in a conversational format, mimicking human conversation; these are ‘ chat-bots ’ , ‘ conversational agents ’ , or simply ‘ bots ’ (Schuetzler et al. 2018).”
BackgroundMethodInfluentialRobots do not judge: service robots can alleviate embarrassment in service encounters
Holthöwer, J., & van Doorn, J. (2022) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-022-00862-x · Cited by 297 · see citing works
“Further, more human-like conversational agents elicit more socially desirable responses, and less honest answers, to sensitive questions (Schuetzler et al., 2018).”
BackgroundSomeone out there? A study on the social presence of anthropomorphized chatbots
Konya-Baumbach, E., Biller, M., & von Janda, S. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107513 · Cited by 283 · see citing works
Zhang, J.-B., Chen, Q., Lu, J.-D., Wang, X., Liu, L.-N., & Feng, Y.-Q. (2023) · Tourism Management · doi:10.1016/j.tourman.2023.104835 · Cited by 223 · see citing works
Ebadi, S., & Amini, A. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2022.2096638 · Cited by 235 · see citing works
“Furthermore, fi ndings have revealed that having a conversation with a human-like chatbot would inject higher levels of willingness to share their personal information, learning queries, and more provoked self-disclosure (Murgia et al., 2016; Schuetzler et al., 2018).”
BackgroundTexting with Humanlike Conversational Agents: Designing for Anthropomorphism
Seeger, A.-M., University of Mannheim, G., Pfeiffer, J., Justus Liebig University Giessen, G., Heinzl, A., & University of Mannheim, G. (2021) · Journal of the Association for Information Systems · doi:10.17705/1jais.00685 · Cited by 200 · see citing works
“Static avatar images can be used as a profile image for CAs (Schuetzler et al., 2018), while fully animated avatars can be used in ECAs (Nunamaker et al., 2011).”
BackgroundMethodInfluentialMental models and expectation violations in conversational AI interactions
Grimes, G. M., Schuetzler, R. M., & Giboney, J. S. (2021) · Decision Support Systems · doi:10.1016/j.dss.2021.113515 · Cited by 184 · see citing works
Self-citationDo you mind if I ask you a personal question? How AI service agents alter consumer self-disclosure
Kim, T. W., Jiang, L., Duhachek, A., Lee, H., & Garvey, A. (2022) · Journal of Service Research · doi:10.1177/10946705221120232 · Cited by 177 · see citing works
“2019), (3) voice (Powers and Kiesler 2006), and (4) language and interaction style (Araujo 2018; Sah and Peng 2015; Schuetzler et al. 2018; Schuetzler, Grimes, and Giboney 2020).”
BackgroundInfluentialAnthropomorphism and OTA chatbot adoption: a mixed methods study
Cai, D., Li, H., & Law, R. (2022) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2022.2061672 · Cited by 175 · see citing works
“…elements through an avatar, giving the chatbot a human name, applying politeness norms, and increasing self-disclosure during a self-introduction could strengthen chatbots’ social presence (Go & Shyam Sundar, 2019; Kuligowska, 2015; Moon, 2000; Qiu & Benbasat, 2009; Schuetzler et al., 2018).”
BackgroundAlexa, Can I Trust You? Exploring Consumer Paths to Trust in Smart Voice-Interaction Technologies
Foehr, J., & Germelmann, C. C. (2019) · Journal of the Association for Consumer Research · doi:10.1086/707731 · Cited by 144 · see citing works
“In doing so, consumers make inferences about the voice’s gender and attribute different personalities, accents, race, and ethnicity (Nass and Brave 2005; Phan 2018) and confer social presence to the computer voice’s perceived personality (Schuetzler et al. 2018).”
BackgroundFrick, N. R. J., Mirbabaie, M., Stieglitz, S., & Salomon, J. (2021) · Journal of Decision Systems · doi:10.1080/12460125.2020.1870065 · Cited by 138 · see citing works
“Nevertheless, organisations need to invest in AI and introduce applications to remain competitive (Benbya & Leidner, 2018; Schuetzler et al., 2018; Yan et al., 2018).”
BackgroundVaritimiadis, S., Kotis, K., Pittou, D., & Konstantakis, G. (2021) · Applied Sciences · doi:10.3390/app11199160 · Cited by 109 · see citing works
“Chatbots or so called ‘conversational agents’ are interactive user interfaces that mimic human ‐ to ‐ human communication using NLP, ML, and other AI technology [39].”
BackgroundMirbabaie, M., Stieglitz, S., Brünker, F., Hofeditz, L., Roß, B., & Frick, N. (2020) · Business & Information Systems Engineering · doi:10.1007/s12599-020-00672-x · Cited by 99 · see citing works
“Moreover, embodiment does not necessarily affect social behavior (Schuetzler et al. 2018).”
BackgroundSun, Y., Zhong, Y., Zhang, Z., Wang, Y.-G., & Zhu, M.-Y. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114189 · Cited by 82 · see citing works
Engagement and attrition in digital mental health: current challenges and potential solutions
Smith, K., Ward, T., Lambe, S., Ostinelli, E. G., Blease, C., Gant, T., Gold, S. M., Holmes, E. A., Paccoud, I., Vinnikova, A., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01778-w · Cited by 71 · see citing works
“Transdisciplinary expertiseindigitalempathyisneededtomaximiseeffectiveengagement – a degree of humanising the interface can improve engagement, but if ‘ too human ’ this may discourage disclosure of negative or embarrassing information 55,56 .”
The effect of conversational agent skill on user behavior during deception
Schuetzler, R. M., Grimes, G. M., & Giboney, J. S. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.03.033 · Cited by 95 · see citing works
Self-citationIndian customers’ acceptance of service robots in restaurant services
Pande, S., & Gupta, K. P. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2103734 · Cited by 61 · see citing works
Validity of Chatbot Use for Mental Health Assessment: Experimental Study
Schick, A., Feine, J., Morana, S., Maedche, A., & Reininghaus, U. (2022) · JMIR mhealth and uhealth · doi:10.2196/28082 · Cited by 71 · see citing works
“If chatbots are perceived as human actors [42,45], this may lead individuals to believe that their responses are immediately reviewed and evaluated.”
BackgroundResultInfluentialPapneja, H., & Yadav, N. (2024) · Personal and Ubiquitous Computing · doi:10.1007/s00779-024-01823-7 · Cited by 73 · see citing works
“Out of the three studies in this sub-category, two offer evidence that non-personified or faceless conversational technologies elicit greater self-disclosure than personified or those with a face [35, 42], while one study found an insignificant effect of embodiment on self-disclosure [36].”
InfluentialKornfield, R., Meyerhoff, J., Studd, H., Bhattacharjee, A., Williams, J. J., Reddy, M. C., & Mohr, D. C. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502046 · Cited by 55 · see citing works
“For example, one study of avatar-delivered motivational interviewing for perinatal drug use found that users preferred a less human-sounding voice [86], which may relate to the greater “social presence” activated by human-like agents [116].”
BackgroundResultUse of automated conversational agents in improving young population mental health: a scoping review
Balan, R., Dobrean, A., & Poetar, C. R. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01072-1 · Cited by 56 · see citing works
“This aspect holds particular signi fi cance, as previous research ,incontrasttodis-embodiedCAs 47 .”
Zhang, J., Lu, J., Wang, X., Liu, L., & Feng, Y. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114314 · Cited by 57 · see citing works
Pickard, M. D., & Roster, C. A. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106197 · Cited by 52 · see citing works
Impact of auditory sense on trust and brand affect through auditory social interaction and control
Poushneh, A. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102281 · Cited by 53 · see citing works
“Yet, it is still unclear how the auditory sense of voice assistants influences their auditory embodiment and consumers ’ responses (Deng et al., 2019; Schuetzler et al., 2018; Kramer et al., 2009).”
BackgroundInfluentialLiu, N., Pu, Q., Shi, Y., Zhang, S., & Qiu, L. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2074667 · Cited by 46 · see citing works
“Voice can help intelligent agents build a trustworthy and reliable social image or personality trait (Schuetzler et al., 2018).”
BackgroundThe role of recommendation sources and attribute framing in online product recommendations
Yang, Y., Zheng, J.-H., Yu, Y.-N., Qiu, Y., & Wang, L. (2024) · Journal of business research · doi:10.1016/j.jbusres.2024.114498 · Cited by 36 · see citing works
Hu, Q., & Pan, Z. (2024) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2024.101398 · Cited by 44 · see citing works
Innovative Accounting Interviewing: A Comparison of Real and Virtual Accounting Interviewers
Pickard, M. D., Schuetzler, R. M., Valacich, J. S., & Wood, D. A. (2020) · The Accounting Review · doi:10.2308/tar-2017-0235 · Cited by 45 · see citing works
“Evidence suggests that virtual agent characteristics influence how honest people are with their virtual interviewers (Schuetzler et al., 2018).”
Self-citationZarouali, B., Araujo, T., Ohme, J., & de Vreese, C. H. (2023) · Communication Methods and Measures · doi:10.1080/19312458.2022.2156489 · Cited by 38 · see citing works
Effects of Humanlikeness and Conversational Breakdown on Trust in Chatbots for Customer Service
Law, E. L., Følstad, A., & van As, N. (2022) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3546155.3546665 · Cited by 37 · see citing works
“[50]) or embodied emotions [23] could have led to a more substantial impact of humanlikeness.”
BackgroundSun, Z., Zang, G., Wang, Z., Zhao, H., & Liu, W. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122560 · Cited by 34 · see citing works
Weimann, T. G., Schlieter, H., & Brendel, B. (2022) · Business & Information Systems Engineering · doi:10.1007/s12599-022-00757-9 · Cited by 37 · see citing works
“Because of their higher media richness, allowing verbal and non-verbal social cues to be conveyed (Schuetzler et al. 2018), they can evoke a greater ‘‘sense of human contact embodied in a medium’’ (Gefen and Straub 1997) that is called social presence.”
BackgroundRelational cohesion between users and smart voice assistants
Ortega, B. H., Manzano, J. A., & Ferreira, I. (2021) · Journal of Services Marketing · doi:10.1108/jsm-07-2020-0286 · Cited by 35 · see citing works
Beyond the Game: Understanding Why People Enjoy Viewing Twitch
Speed, A., Burnett, A., Owens, C., & Parsons, M. (2022) · Entertainment Computing · doi:10.1016/j.entcom.2022.100545 · Cited by 30 · see citing works
Yuan, J., Peng, X., Liu, Y. H., & Wang, Q. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108501 · Cited by 28 · see citing works
The Power of Identity Cues in Text-Based Customer Service: Evidence from Twitter
Gao, Y. A., Rui, H., & Sun, S. (2023) · MIS Quarterly · doi:10.25300/misq/2022/17366 · Cited by 27 · see citing works
Functionality, Emotion, and Acceptance of Artificial Intelligence Virtual Assistants
Du, X., Zhao, X., Wu, C., & Feng, K. (2021) · Journal of Global Information Management · doi:10.4018/jgim.290418 · Cited by 29 · see citing works
“…two basic categories: one part of the research argues that perceived humanness positively facilitates the acceptance process (Gursoy et al., 2019; Schuetzler et al., 2018; Qiu & Benbasat, 2009); the other part of the research argues that perceived humanness’s positive facilitation effect does…”
BackgroundHendriks, F., Ou, C. X., Amiri, A. K., & Bockting, S. (2020) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2020.034 · Cited by 25 · see citing works
“It is however seen that if chatbots show similar anthropomorphistic traits a higher self-disclosure by the human interlocutor is provoked [33].”
BackgroundAn Empathetic Conversational Agent with Attentional Mechanism
Goel, R., Vashisht, S., Dhanda, A., & Susan, S. (2021) · International Conference on Computer Communication and Informatics (ICCCI) · doi:10.1109/iccci50826.2021.9402337 · Cited by 24 · see citing works
Social-Oriented Communication with AI Companions: Benefits, Costs, and Contextual Patterns
Bayor, L., Weinert, C., Maier, C., & Weitzel, T. (2025) · Business & Information Systems Engineering · doi:10.1007/s12599-025-00955-1 · Cited by 24 · see citing works
“…more closely with socioemotional objectives and may not be directly relevant to the completion of a specific functional goal fundraising (Zhou et al. 2022), or custom CAs built to fulfill a task and chat with the user in an experimental setting (e.g., Schuetzler et al. 2018; Gnewuch et al. 2022).”
Poser, M., Singh, S., & Bittner, E. A. C. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.144 · Cited by 23 · see citing works
“CAs are software systems, which interact with humans via natural language (voice, text or both) [6, 26, 27].”
BackgroundA narrative review of the active ingredients in psychotherapy delivered by conversational agents
Herbener, A. B., Klincewicz, M., & Damholdt, M. F. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100401 · Cited by 21 · see citing works
Tsekouras, D., Gutt, D., & Heimbach, I. (2024) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-024-01027-8 · Cited by 18 · see citing works
“Previous research has revealed how increases in perceived social presence generated with the use of a chatbot may lead to socially desirable responses (Schuetzler et al., 2018).”
Can bots help create knowledge? The effects of bot intervention in open collaboration
Kang, S., Liu, X., Kim, Y., & Yoon, V. (2021) · Decision Support Systems · doi:10.1016/j.dss.2021.113601 · Cited by 18 · see citing works
Oh, J., Sudarshan, S., Lee, J. A., & Yu, N. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.1921027 · Cited by 17 · see citing works
Designing Conversational Evaluation Tools
Wambsganß, T., Zierau, N., Söllner, M., Käser, T., Koedinger, K. R., & Leimeister, J. M. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555619 · Cited by 17 · see citing works
User Assistance for Intelligent Systems
Morana, S., Pfeiffer, J., & Adam, M. T. P. (2020) · Business & Information Systems Engineering · doi:10.1007/s12599-020-00640-5 · Cited by 17 · see citing works
Exploring the frontier of anthropomorphism in AI agents: Trends and way forward
Chaturvedi, R., Verma, S., Srivastava, V., & Khot, S. S. (2025) · Business and Society Review · doi:10.1111/basr.70002 · Cited by 19 · see citing works
Park, S. (., Chu, Y. (., & Chung, J.-H. (2025) · Journal of Advertising Research · doi:10.1080/00218499.2025.2497615 · Cited by 16 · see citing works
Gilles, M., & Bevacqua, E. (2021) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4053369 · Cited by 16 · see citing works
Yun, H. S., Arjmand, M., Sherlock, P., Paasche‐Orlow, M. K., Griffith, J. W., & Bickmore, T. (2024) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3652988.3673929 · Cited by 15 · see citing works
Cicco, R. D., Elmashhara, M. G., Silva, S. C. L. D. C. E., & Hammerschmidt, M. (2025) · European Journal of Marketing · doi:10.1108/ejm-01-2022-0066 · Cited by 14 · see citing works
Konijn, E. A., Preciado, D. F., & van Minkelen, P. (2025) · Communication Theory · doi:10.1093/ct/qtaf007 · Cited by 14 · see citing works
Rahman, M. S., Sabbir, M. M., Zhang, J., Taufique, K. M. R., & Rahman, M. M. (2024) · International Journal of Consumer Studies · doi:10.1111/ijcs.13096 · Cited by 14 · see citing works
Gatto, A., & Panarello, D. (2022) · Energy Research & Social Science · doi:10.1016/j.erss.2022.102813 · Cited by 14 · see citing works
From Humanoid to Virtual Humans: A Systematic Literature Review of Avatar Marketing
Qu, Y., Lo, C. K. Y., & Baek, E. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2464889 · Cited by 17 · see citing works
“Correspondingly, in a study conducted by Schuetzler et al. (2018), it was found that participants perceived no difference between human interviewers and avatars (i.e., conversational agents (CAs)) when disclosing nonsensitive information.”
Frick, N., Brünker, F., Roß, B., & Stieglitz, S. (2021) · Health Informatics Journal · doi:10.1177/1460458221994861 · Cited by 13 · see citing works
Liu, M., & Wu, X. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108778 · Cited by 13 · see citing works
Cox, S. R., Lee, Y., & Ooi, W. T. (2023) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3623809.3623875 · Cited by 14 · see citing works
“[60] found that people were less likely to disclose to chatbots that use more relevant responses to user utterances during a small-talk”
Moriuchi, E. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124004 · Cited by 13 · see citing works
Poushneh, A., & Gearhart, R. S. (2025) · Journal of Consumer Behaviour · doi:10.1002/cb.2496 · Cited by 14 · see citing works
Do cute language style chatbots make consumers more unethical?
Chen, J., Ke, W., Wu, Y., & Zhang, J. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102941 · Cited by 11 · see citing works
AI or human: How the type of information to be disclosed alters customer service agent preferences
Dai, X., Zhang, L., Huang, Z., & Wang, L. (2025) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2025.104621 · Cited by 11 · see citing works
So Close and Yet So Far: How Embodiment Shapes the Effects of Distance in Remote Collaboration
Kornfield, R., Rae, I., & Mutlu, B. (2021) · Communication Studies · doi:10.1080/10510974.2021.2011362 · Cited by 11 · see citing works
“…some work on embodiment and disclosure considers how users communicate with embodied computer agents (e.g., virtual humans, relational agents) (Schuetzler et al., 2018; Sproull et al., 1996), finding that an agent’s embodiment (e.g., via an animated face) can escalate socially desirable…”
BackgroundZaal, E., Ongena, Y., van der Velden, N., Loughnan, D., & Hoeks, J. C. J. (2026) · Quality & Quantity · doi:10.1007/s11135-026-02664-7 · Cited by 10 · see citing works
A Survey of Conversational Agents and Their Applications for Self-Management of Chronic Conditions
Park, M. S., Upama, P. B., Anik, A. A., Ahamed, S. I., Luo, J., Tian, S., Rabbani, M., & Oh, H. (2023) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac57700.2023.00162 · Cited by 12 · see citing works
Avatars and organizational knowledge sharing
Fehrenbacher, D. D., & Weisner, M. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114245 · Cited by 12 · see citing works
AI-enabled social support chatbot usage: flowing ambivalence and liminalities
Kéfi, H., Khelladi, I., Mani, Z., & Veg-Sala, N. (2024) · Journal of Decision System · doi:10.1080/12460125.2024.2443226 · Cited by 11 · see citing works
Effects of a computer's human likeness on disclosure in psychosocial assessments: A randomised trial
Zhu, T., & Broadbent, E. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108683 · Cited by 10 · see citing works
Human or Machine? A Study of Anthropomorphism Through an Affordance Lens
Lunberry, D., & Liebenau, J. M. (2020) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-47539-0_15 · Cited by 10 · see citing works
Law, E. L., van As, N., & Følstad, A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-42283-6_16 · Cited by 9 · see citing works
Alattas, A., Teepe, G. W., Leidenberger, K., Fleisch, E., Car, L. T., Salamanca-Sanabria, A., & Kowatsch, T. (2021) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0010413308010808 · Cited by 9 · see citing works
“Specifically, not only was it reported that face-to-face interviews garnered less accurate responses that are higher in social desirability compared to the same questions presented via CA, but that CAs that gave more relevant and tailored responses to user input also increased socially desirable response bias compared…”
BackgroundInfluentialSkvortsova, A., Rodrigues, T. C., de Buisonjé, D. R., Kowatsch, T., Santhanam, P., Veldhuijzen, D. S., van Middendorp, H., & Evers, A. W. M. (2021) · Journal of Medical Internet Research · doi:10.2196/32130 · Cited by 11 · see citing works
“Studies show that similar social desirability patterns occur in interactions with conversational agents, especially when the conversational agent is more human-like [62,63].”
The influence of communicating agent on users’ willingness to interact: A moderated mediation model
Zhou, Q., & Li, B. (2024) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2024-2-7 · Cited by 8 · see citing works
Anthropomorphic technology in everyday life: focus on chatbots and impacts on mental health
Monteith, S., Glenn, T., Geddes, J. R., Whybrow, P. C., Achtyes, E. D., & Bauer, M. (2025) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-025-02088-8 · Cited by 8 · see citing works
“In some cases, humanistic chatbots asking sensitive questions will elicit socially desirable but less honest answers [60].”
Kar, A. K., Mikalef, P., Nishant, R., Luo, X. (., & Gupta, M. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114456 · Cited by 8 · see citing works
Bucher, A. M., Dolata, M., Eckhardt, S., Staehelin, D., & Schwabe, G. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3633072 · Cited by 7 · see citing works
“Furthermore, CAs with a higher number of social cues increase discomfort in users, leading to reduced self-disclosure [63].”
BackgroundMethodEvaluating the success of a learning management system for supplemental learning in accounting
Bonilla-Priego, M. J., Fernandez‐Giordano, M., & Pacheco-Olivares, M.-D.-R. (2024) · Accounting Education · doi:10.1080/09639284.2024.2424269 · Cited by 7 · see citing works
“However, precautions were taken to mitigate this bias (Chung & Monroe, 2003; Kock et al., 2021; Schuetzler et al., 2018; Stantcheva, 2023).”
Wood, G., Castellar, E. N., & IJsselsteijn, W. A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93415-5_18 · Cited by 7 · see citing works
From efficiency to immersion: understanding generational differences in avatar interactions
Pawar, S. S., & Mishra, A. A. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108732 · Cited by 7 · see citing works
Integrating AI in Psychotherapy: An Investigation of Trust in Voicebot Therapists
Mühl, L., Stecker, L., Herter, E., Szczuka, J. M., Wischnewski, M., & Krämer, N. C. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3679318.3685353 · Cited by 7 · see citing works
“Supporting these claims, Schützler and colleagues found that users were indeed more ready to disclose sensitive information (here: questions regarding their drinking behavior) to a machine with a lower social presence rather than another human being due to the decreased social desirability [24].”
Use of Online Shop Chatbots: How Trust in Seller Moderates Brand Preference and Purchase Intention
Illescas-Manzano, M. D., Martínez, S., Cardoso, P. R., & López, C. S. (2024) · Springer proceedings in business and economics · doi:10.1007/978-3-031-70488-8_10 · Cited by 8 · see citing works
Hsu, C.-W., Gross, J., & Hayne, H. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.1966099 · Cited by 7 · see citing works
Uzan, S., Freud, D., & Elalouf, A. (2025) · Applied Sciences · doi:10.3390/app15179439 · Cited by 6 · see citing works
Conversational Agents in Healthcare: A Variability Perspective
May, R., & Denecke, K. (2024) · International Workshop on Variability Modelling of Software-Intensive Systems (VaMoS) · doi:10.1145/3634713.3634717 · Cited by 5 · see citing works
“The application technology usually has a strong impact on whether the CA is embodied [58].”
BackgroundBotmorphosis in E-commerce: exploring the impact of chatbot eeriness on purchase intentions
Abeden, A. Z. U., Wang, J., Ali, S., & Maqbool, M. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2547916 · Cited by 5 · see citing works
“This will be of substantial advantage to practitioners who employ CAs, as it enables developers to recognise when upgraded (computer-generated) more effective CAs are beneficial and when they lessen the effectiveness of the CA for their intended purpose (Schuetzler et al. 2018).”
Fontecha, J., Gónzalez, I., & Salas-Seguín, A. (2019) · International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI) · doi:10.3390/proceedings2019031032 · Cited by 5 · see citing works
“One of the main concerns about the natural interaction with CAs is the sense of context and their behavior in situations that require greater attention and rapid response, as well as the impact of this on people and consideration of sensitive issues [2,3].”
BackgroundAlbrecht, C., Archiwaranguprok, C., Poonsiriwong, R., Chen, A., Lertsutthiwong, M., Winson, K., Maes, P., Ersner-Hershfield, H., & Pataranutaporn, P. (2026) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3742413.3789455 · Cited by 4 · see citing works
Beyond the Machine: An Integrative Framework of Anthropomorphism in AI
Curșeu, P. L., & Radu, Ș. (2026) · Behavioral Sciences · doi:10.3390/bs16030358 · Cited by 4 · see citing works
“…human-like characteristics, and engages in behaviors such as self-disclosure, the user’s responses to sensitive questions tend to align more closely with socially desirable norms, and thus less honest, mirroring a phenomenon observable in human-to-human interactions (Schuetzler et al., 2018).”
Weimann, T. G., Schlieter, H., Konofalska, U., & Ziemssen, T. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2641598 · Cited by 5 · see citing works
“Conversely, research indicates that social presence diminishes anonymity (Tourangeau and Yan 2007), leading to decreased self-disclosure, particularly in untrusting environments (whether human or emulated by CAs) (Kang and Kang 2024; Schuetzler et al. 2018).”
InfluentialWang, Y., & Ngai, E. W. T. (2026) · Decision Support Systems · doi:10.1016/j.dss.2026.114688 · Cited by 4 · see citing works
Is seeing the same as doing? An evaluation of vicarious experiences in the metaverse
Krieger, C., Luse, A., Khani, G. A., & Sarathy, R. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114419 · Cited by 4 · see citing works
A comparative psychological evaluation of a robotic avatar in Dubai and Japan
Kamide, H., Horikawa, Y., Sato, M., Toyoda, A., Sakai, K., Minato, T., Miyashita, T., & Ishiguro, H. (2025) · Frontiers in Robotics and AI · doi:10.3389/frobt.2024.1426717 · Cited by 4 · see citing works
How virtual streamers controlling entities and product sensitivity shape consumer purchase intention
Gong, X., Jiang, X., & Wang, M. (2025) · Electronic Commerce Research · doi:10.1007/s10660-025-10037-9 · Cited by 4 · see citing works
“For example, consumers prefer to buy sex products from self-service stores and to communicate with AI agents regarding sensitive issues [ 30, 41].”
Artificial Intelligence in Mental Health
Ogilvie, L., Prescott, J., Hanley, T., & Carson, J. F. (2021) · Advances in psychology, mental health, and behavioral studies (APMHBS) book series · doi:10.4018/978-1-7998-7991-6.ch013 · Cited by 5 · see citing works
Stinkeste, C., & Skantze, G. (2025) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3765766.3765773 · Cited by 5 · see citing works
“Most research to date has focused on direct user–chatbot interactions [2, 3, 8, 15, 16, 18, 21, 22, 25, 26, 39, 40, 42, 50, 61, 62, 69, 70, 84],some studies have employed vignette-based designs [4], in which participants read pre-written transcripts rather than interacting directly [12, 13, 30, 32,…”
- Authors
- Schuetzler, R. M., Giboney, J. S., Grimes, G. M., & Nunamaker, J. F.
- Affiliations
- University of Nebraska at Omaha (US)
- Brigham Young University (US)
- University of Houston (US)
- University of Arizona (US)
- Corresponding author
- Schuetzler, Ryan M.
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 114
- Pages
- 94-102
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2889547446
- Cited by
- 154
- References
- 69
- Citations by year
- 2026: 35 · 2025: 28 · 2024: 32 · 2023: 12 · 2022: 16 · 2021: 19 · 2020: 8 · 2019: 4
- FWCI
- 10.49
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Decision Support Systems (publishedVersion, cc-by)
- DigitalCommons@UNO (submittedVersion, cc-by)
- ScholarsArchive (Brigham Young University) (submittedVersion)
- Funders
- National Science Foundation (1068026)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Keywords
- chatbots, embodiment, social desirability bias, self-disclosure, social presence, anthropomorphism, sensitive questions, information disclosure
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
