808
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Avatar-Mediated Communication and Social Identification

ORCID Icon, ORCID Icon & ORCID Icon
Pages 1171-1201 | Published online: 11 Dec 2023
 

ABSTRACT

Avatar-mediated communication (AMC), commonly used in online environments such as games and the emerging metaverse, is different from traditional computer-mediated communication in that it is a human-object-object-human relationship mediated by the individual’s avatar and the avatar of the person with whom they are communicating. We conceptualize AMC by using three key concepts: user-avatar identification (i.e., how a user perceives their avatar as themselves), avatar-avatar identification (i.e., how a user perceives their avatar as part of a community of avatars), and social presence (i.e., how a user perceives the other avatar as a representation of the other person). We tested this model using 778 individuals who responded to three waves of data collection. The results show that the three factors of AMC influence users’ social identification with their community and strengthen its impact on loyalty. From a theoretical perspective, our research adds two novel constructs—user–avatar identification and avatar–avatar identification—that play key roles in AMC in addition to the well-known effects of social presence. From a practical perspective, our research helps developers better design online games and virtual worlds such as the metaverse.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/07421222.2023.2267320.

Additional information

Funding

C.I. Teng is thankful to the Ministry of Science and Technology, Taiwan (MOST 109-2410-H-182-011-MY2) for financial support for this study.

Notes on contributors

Ching-I Teng

Ching-I Teng ([email protected] or [email protected]) is a Professor at Chang Gung University, Taiwan. He has been a visiting scholar to Academia Sinica, Taiwan, University of Washington, Seattle, The Hong Kong Polytechnic University, and Indiana University, Bloomington. Dr. Teng has published in Decision Support Systems, Information & Management, Information Systems Research, International Journal of Electronic Commerce, Journal of Service Research and other journals.

Alan R. Dennis

Alan R. Dennis ([email protected]) is Professor of Information Systems and holds the John T. Chambers Chair of Internet Systems in the Kelley School of Business at Indiana University. His research focuses on four main themes: team collaboration; fake news on social media; cybersecurity; and artificial intelligence. A 2020 analysis of citation data placed him in the top 1 percent of the most influential researchers in the world, across all scientific disciplines. Dr. Dennis’s research has been reported in the popular press almost 1000 times, including in the Wall Street Journal, Forbes, USA Today, The Atlantic, CBS, Fox Business Network, PBS, Canada’s CBC and CTV, and the UK’s Daily Mail and the Telegraph. He is a Past President, Fellow, and LEO awardee of the Association for Information Systems.

Alexander S. Dennis

Alexander S. Dennis ([email protected]) is an Assistant Professor of Information Systems and Business Analytics at the Ivy College of Business, Iowa State University. His research focuses on virtual teams, social media, and identity within the sphere of technology. He employs a variety of methodologies in his research, including experimental designs, field observations, and leveraging archival data.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 640.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.