The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters
Open accessAbstract
By performing tasks traditionally fulfilled by service personnel and having a humanlike appearance, virtual customer service agents bring classical service elements to the web, which may positively influence customer satisfaction through eliciting social responses and feelings of personalization. This paper sheds light on these dynamics by proposing and testing a model drawing upon the theories of implicit personality, social response, emotional contagion, and social interaction. The model proposes friendliness, expertise, and smile as determinants of social presence, personalization, and online service encounter satisfaction. An empirical study confirms the cross-channel applicability of friendliness and expertise as determinants of social presence and personalization. Overall, the study underlines that integration between technology and personal aspects may lead to more social online service encounters.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Service Encounter: Diagnosing Favorable and Unfavorable Incidents
Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990) · Journal of Marketing · doi:10.2307/1252174 · Cited by 4,860
Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction
WALTHER, J. B. (1996) · Communication Research · doi:10.1177/009365096023001001 · Cited by 4,798
Relationship Quality in Services Selling: An Interpersonal Influence Perspective
Crosby, L. A., Evans, K. R., & Cowles, D. (1990) · Journal of Marketing · doi:10.1177/002224299005400306 · Cited by 4,763
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 6×
“Adding more fundamental human characteristics to the humancomputer interaction, like use of language, interactivity, and conversing using social roles, were shown to evoke more social responses (Nass & Moon, 2000).”
BackgroundInfluentialSocial presence as a predictor of satisfaction within a computer‐mediated conferencing environment
Gunawardena, C. N., & Zittle, F. J. (1997) · American Journal of Distance Education · doi:10.1080/08923649709526970 · Cited by 2,005
SERVICE WITH A SMILE: EMOTIONAL CONTAGION IN THE SERVICE ENCOUNTER.
Pugh, S. D. (2001) · Academy of Management Journal · doi:10.2307/3069445 · Cited by 1,393 · cited 1×
“Journal of Computer-Mediated Communication”
The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents1
Komiak, S. Y. X., & Benbasat, I. (2006) · MIS Quarterly · doi:10.2307/25148760 · Cited by 1,374
Qiu, L., & Benbasat, I. (2009) · Journal of Management Information Systems · doi:10.2753/mis0742-1222250405 · Cited by 737
Can a Retail Web Site Be Social?
Wang, L. C., Baker, J., Wagner, J. A., & Wakefield, K. (2007) · Journal of Marketing · doi:10.1509/jmkg.71.3.143 · Cited by 672
Cited by
AI-based chatbots in customer service and their effects on user compliance
Adam, M., Wessel, M., & Benlian, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00414-7 · Cited by 1,195
“…research has shown that few cues are sufficient for users to identify with computer agents (Xu and Lombard 2017) and virtual service agents (Verhagen et al. 2014), we hypothesize that even verbal ADCs, which are not as directly and easily observable as nonverbal cues like embodiments, can…”
BackgroundAraujo, T. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.03.051 · Cited by 1,156
A Systematic Review of Social Presence: Definition, Antecedents, and Implications
Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00114 · Cited by 1,032
“…interpersonal evaluations (e.g., similarity attraction, social penetration theory, social identity theory, preference for consistency, etc.) to technology-mediated contexts to explore their relevance in interpersonal perceptions (e.g., Reeves and Nass, 1996; Jin, 2012; Verhagen et al., 2014).”
BackgroundAn 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
Jiang, H., Cheng, Y., Yang, J., & Gao, S. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107329 · Cited by 362
Metadata
- Authors
- Verhagen, T., van Nes, J., Feldberg, F., & van Dolen, W.
- Venue
- Journal of Computer-Mediated Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-02-17
- Volume
- 19
- Issue
- 3
- Pages
- 529-545
- ISSN
- 1083-6101 (ISSN-L)
- OpenAlex
- W2091954440
- Cited by
- 403
- References
- 9
- FWCI
- 6.93
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters. https://app.cochat.ai/papers/10.1111/jcc4.12066
- The paper
- Verhagen, T., van Nes, J., Feldberg, F., & van Dolen, W. (2014). Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters. Journal of Computer-Mediated Communication. https://doi.org/10.1111/jcc4.12066
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.