Abstract
Metaverses are 3-dimentional (3D) virtual environments that allow people to interact with each other through software agents without physical limitations. There is great interest in the use of Metaverses for health and medical education. This paper examines the application of metaverses for supporting effective collaboration and knowledge sharing in virtual teams. Virtual teams have been used in health/medical area, such as home healthcare. However, the management of virtual teams is challenging. This study proposes that metaverses have the potential to provide socioemotional environments where individuals socially interact with others. Such socioemotional environments have the potential to facilitate effective collaboration and knowledge sharing in virtual teams. Building on previous research, we developed a conceptual model for understanding how metaverses enable the development of social-emotional environments in virtual teams.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Powell, A., Piccoli, G., Ives, B.: Virtual teams: A review of current literature and directions for future research. Database for Advances in Information Systems 35(1), 6–36 (2004)
Pitsillides, A., et al.: DITIS: Virtual collaborative teams for home healthcare. Journal of Mobile Multimedia 2(1) (2006)
Khazanchi, D., Zigurs, I.: Patterns for effective management of virtual projects: Theory and evidence. International Journal of Electronic Collaboration 2(3), 25–49 (2006)
Majchrzak, A., et al.: Technology adaptation: The case of a computer supported inter-organizational virtual team. MIS Quarterly 24(4), 569–600 (2000)
Brodkin, J.: Sun building collaborative, virtual world (2007)
Davis, A., et al.: Avatars, people, and metaverses: Foundations for research in metaverses. Journal of the Association for Information Systems 10(2), 99–117 (2009)
Bainbridge, W.S.: The scientific research potential of virtual worlds. Science 317, 472–476 (2007)
Owens, D., et al.: An empirical investigation of virtual world projects and metaverse technology capabilities. The DATA BASE for Advances in Information Systems 42(1), 74–101 (2011)
Biocca, F., Harms, C., Burgoon, J.: Criteria and scope conditions for a theory and measure of social presence. In: Presence 2001, 4th Annual International Workshop, Philadelphia, PA (2001)
Schroeder, R., Heldal, I., Tromp, J.: The usability of collaborative virtual environments and methods for the analysis of interaction. Presence 16(5), 655–667 (2006)
Sempsey, J.J., Johnston, D.A.: The psychological dynamics and social climate of text-based virtual reality. Journal of Virtual Environments 5(1) (2000)
Anderson, A., Dossick, C.S., Iorio, J.: Avatars, Text, and Miscommunication: The Impact of Communication Richness on Global Virtual Team Collaboration. Working Paper (2011)
Magnenat-Thalmann, N., Kim, H., Egges, A., Garchery, S.: Believability and Interaction in Virtual Worlds. In: Proceedings of the 11th International Multimedia Modelling Conference, Melbourne, Australia (2005)
Bente, G., et al.: Avatar-mediated networking: Increasing social presence and interpersonal trust in net-based collaborations. Human Communication Research 34(2), 287–318 (2008)
Redfern, S., Naughton, N.: Collaborative virtual environments to support communication and community in internet-based distance education. Journal of Information Technology Education 1(3) (2002)
Tanis, M., Postmes, T.: Social cues and impression formation in CMC. Journal of Communication 53, 676–693 (2003)
Sheridan, T.B.: Musings on telepresence and virtual presence. Presence: Teleoperators and Virtual Environments 1, 120–126 (1992)
Slater, M., Usoh, M.: Representations systems, perceptual position, and presence in immersive virtual environments. Presence: Teleoperators and Virtual Environments 2, 221–233 (1993)
Rheingold, H.: Virtual reality. Summit Books, New York (1991)
Lee, K.M.: Presence, Explicated. Communication Theory 14(1), 27–50 (2004)
Whittaker, S.: Theories and methods in mediated communciation. In: Graesser, M.G.A., Goldman, S. (eds.) The Hand Book of Discourse Processes, pp. 243–286. Lawrence Erlbaum Associates, Mahwah (2002)
Foster, D., Meech, J.: The social dimensions of virtual reality. In: Carr, K., England, R. (eds.) Simulated and Virtual Realities: Elements of Perception. Taylor and Francis, London (1995)
Blascovich, J.: A theoretical model of social influence for increasing the utility of collaborative virtual environments. In: Proceedings of the 4th International Conference on Collaborative Virtual Environments 2002, Bonn, Germany. ACM, New York (2002)
Shi, Y., Zhang, X., Wan, J., Kou, G., Peng, Y., Guo, Y.: Comparison study of two kernel-based learning algorithms for predicting the distance range between antibody interface residues and antigen surface. International Journal of Computer Mathematics 84, 690–707 (2007)
Shi, Y., Zhang, X., Wan, J., Wang, Y., Ying, W., Cao, Z., Guo, Y.: Predicting the Distance between Antibody’s Interface Residue And Antigen To Recognize Antigen Types By Support Vector Machine. Neural Computing & Applications 16, 481–490 (2007)
Zheng, J., Zhuang, W., Yan, N., Kou, G., Erichsen, D., McNally, C., Peng, H., Cheloha, A., Shi, C., Shi, Y.: Classification of HIV-1 Mediated Neuronal Dendritic and Synaptic Damage Using Multiple Criteria Linear Programming. Neuroinformatics 2, 303–326 (2004)
Chen, Z.Y., Li, J.P., Wei, L.W.: A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue. Artificial Intelligence in Medicine 41(2), 161–175 (2007)
Kou, G., Peng, Y., Chen, Z., Shi, Y.: Multiple criteria mathematical programming for multi-class classification and application in network intrusion detection. Information Sciences 179(4), 371–381 (2009)
Shi, Y., Tian, Y., Chen, X., Zhang, P.: Regularized Multiple Criteria Linear Programs for Classification. Science in China Series F: Information Sciences 52, 1812–1820 (2009)
Peng, Y., Kou, G., Shi, Y., Chen, Z.: A Descriptive Framework for the Field of Data Mining and Knowledge Discovery. International Journal of Information Technology and Decision Making 7(4), 639–682 (2008)
Peng, Y., Kou, G., Shi, Y., Chen, Z.: A Multi-Criteria Convex Quadratic Programming Model for Credit Data Analysis. Decision Support Systems 44, 1016–1030 (2008)
Cheng, S., Dai, R., Xu, W., Shi, Y.: Research on Data Mining and Knowledge Management and Its Applications in China’s Economic Development: Significance and Trend. International Journal of Information Technology and Decision Making 5(4), 585–596 (2006)
Shi, Y., Peng, Y., Kou, G., Chen, Z.: Classifying Credit Card Accounts for Business Intelligence and Decision Making: A Multiple-Criteria Quadratic Programming Approach. International Journal of Information Technology and Decision Making 4, 581–600 (2005)
Kou, G., Peng, Y., Shi, Y., Wise, M., Xu, W.: Discovering Credit Cardholders’ Behavior by Multiple Criteria Linear Programming. Annals of Operations Research 135, 261–274 (2005)
He, J., Liu, X., Shi, Y., Xu, W., Yan, N.: Classifications of Credit Cardholder Behavior by using Fuzzy Linear Programming. International Journal of Information Technology and Decision Making 3, 633–650 (2004)
Zheng, J., Zhuang, W., Yan, N., Kou, G., Erichsen, D., McNally, C., Peng, H., Cheloha, A., Shi, C., Shi, Y.: Classification of HIV-1 Mediated Neuronal Dendritic and Synaptic Damage Using Multiple Criteria Linear Programming. Neuroinformatics 2, 303–326 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, X., Owens, D., Khazanchi, D. (2012). Building Socioemotional Environments in Metaverses for Virtual Teams in Healthcare: A Conceptual Exploration. In: He, J., Liu, X., Krupinski, E.A., Xu, G. (eds) Health Information Science. HIS 2012. Lecture Notes in Computer Science, vol 7231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29361-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-29361-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29360-3
Online ISBN: 978-3-642-29361-0
eBook Packages: Computer ScienceComputer Science (R0)