The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Systematic Review: Trust-Building Factors and Implications for Conversational Agent Design
Open accessAbstract
Minjin Rheua*, Ji Youn Shina, Wei Penga & Jina Huh-Yooba Media and Information, Michigan State University, East Lansing, Michigan, USAb Department of Information Science, Drexel University, Philadelphia, Pennsylvania, USAMinjin Rheu is a Ph.D. candidate in the Department of Media and Information at Michigan State University. Her research delves into how specific designs or features of communication technology influences users’ motivational and cognitive processes through which people change or adopt their health and prosocial behaviors.Ji Youn Shin is a Ph.D. student in the Department of Media and Information at Michigan State University. Her research includes human-computer interaction, human-centered design, and health communication. She designs and evaluates technologies for supporting individuals’ health and wellness in various health contexts, including family caregiving and pediatric chronic illnesses.Wei Peng is a Professor in the Department of Media and Information, Michigan State University. Her research focuses on the psychological and social mechanisms of behavior change and their application in the design of interactive media for health and wellness promotion.Jina Huh-Yoo is an Assistant Professor of Human-Computer Interaction at Drexel University's College of Computing & Informatics. Her research areas include human-computer interaction, health informatics, and research ethics of health informatics technologies. She was a PI of NIH and NSF-funded projects in promoting health and wellness through consumer-facing technologies.CONTACT Minjin Rheu rheuminj@msu.edu Media and Information, Michigan State University, 404 Wilson Rd, Room 414, East Lansing, MI 48823, USAABSTRACTOff-the-shelf conversational agents are permeating people’s everyday lives. In these artificial intelligence devices, trust plays a key role in users’ initial adoption and successful utilization. Factors enhancing trust toward conversational agents include appearances, voice features, and communication styles. Synthesizing such work will be useful in designing evidence-based, trustworthy conversational agents appropriate for various contexts. We conducted a systematic review of the experimental studies that investigated the effect of conversational agents’ and users’ characteristics on trust. From a full-text review of 29 articles, we identified five agent design-themes affecting trust toward conversational agents: social intelligence of the agent, voice characteristics and communication style, look of the agent, non-verbal communication, and performance quality. We also found that participants’ demographic, personality, or use context moderate the effect of these themes. We discuss implications for designing trustworthy conversational agents and responsibilities around on stereotypes and social norm building through agent design.
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“The number of studies analyzed in literature reviews ranges from 29 articles (Rheu et al., 2021) to 262 articles (Diederich et al., 2022).”
From Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers (2024) · cites this paper as Rheu et al., 2021
In the citing paper
“Our keyword results show that the research focus on CA personalization and anthropomorphization to create a more natural and effortless interaction can, in turn, affect important outcome variables, including usage, satisfaction, and trust (Rheu et al., 2021;Abedin et al., 2022).”
From Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers (2024) · cites this paper as Rheu et al., 2021
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Cited by
Sorted by citations
Trust in AI and Its Role in the Acceptance of AI Technologies
Choung, H., David, P., & Ross, A. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2050543 · Cited by 963
“Many recent studies on trust in AI have focused on exploring factors that contribute to trustworthy AI (Gillath et al., 2021; Lockey et al., 2021; Rheu et al., 2021).”
BackgroundSchepman, A., & Rodway, P. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2085400 · Cited by 503
A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective
Bach, T. A., Khan, A. N., Hallock, H., Beltrão, G., & Sousa, S. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2138826 · Cited by 506
Nicolescu, L., & Tudorache, M. T. (2022) · Electronics · doi:10.3390/electronics11101579 · Cited by 280
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Metadata
- Authors
- Rheu, M., Shin, J. Y., Peng, W., & Huh-Yoo, J.
- Affiliations
- Michigan State University (US)
- Department of Information Science, Drexel University, Philadelphia, Pennsylvania, USA
- Corresponding author
- Rheu, Minjin
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2020-09-02
- Volume
- 37
- Issue
- 1
- Pages
- 81-96
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W3082818995
- Semantic Scholar
- 824e392846e1b38787c39d8318d5f1e44e9a6c5b
- Cited by
- 360
- References
- 83
- Citations by year
- 2026: 76 · 2025: 99 · 2024: 70 · 2023: 50 · 2022: 42 · 2021: 22 · 2020: 1
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Figshare (cc-by)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- chatbots, trust, agent design, voice characteristics, communication styles, nonverbal communication, agent appearance, social intelligence, performance quality, user personality, demographic moderators, social norms, stereotypes, health communication, human-computer interaction
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