Cognitive absorption and trust for workplace collaboration in virtual worlds: An information processing decision making perspective
Open accessAbstract
Virtual worlds (VWs) are media-rich cognitively engaging technologies that geographically dispersed organizations can use as a cost effective workplace collaboration tool. Using an information processing decision making perspective and building on unique characteristics of VWs, this paper proposes a nomological net for adaptive use intention (AUI) of VWs for workplace collaborations. AUI implies intention to use a technology in a setting different from the one for which it was initially designed. We study the AUI of VWs as a workplace collaboration tool which were originally conceived as recreational gaming platforms. Decision-making literature directs us to reduction of perceived cognitive burden and minimization of risk as the two key motivations for VWs’ AUI. Building on these motivations, the paper identifies cognitive absorption and user trust in VWs as the mechanisms leading to individual-level AUI decision. Drawing on social cognitive theory and literature on trust, the proposed model not only re-specifies the concept of cognitive absorption in the context of VWs but also relates it to the level of trust and usage intention for VWs. We empirically tested the proposed model via data collected from 197 VW users in Singapore. Results demonstrate the significant roles that cognitive absorption’ and user trust play in VW’s usage as a collaboration tool. Further, through a series of post-hoc analyses, we demonstrate the imperative need for considering both cognitive absorption and user trust together in the proposed research model for theoretical parsimony. We also discuss implications for research and practice emerging out of this study.
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Cognitive absorption is an important predictor of learning in a variety of contexts related to new IT.
“Studies have shown IS research to be an important predictor of learning in a variety of contexts related to new IT [5], such as online virtual communities [39,95].”
From Absorbed in technology but digitally overloaded: Interplay effects on gig workers’ burnout and creativity (2021) · cites this paper as [39]
Section 2.3 describes cognitive absorption as influencing IT usage intentions and cites its significance for acceptance of online learning systems and participation in virtual communities. That supports its relevance across new-IT contexts, but the passage concerns acceptance and usage—not learning outcomes—so it does not establish cognitive absorption as a predictor of learning. The indexed passages provide no page number. (LLM, conf=0.82)
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- Authors
- Nanyang Technological University, Chandra, S., Srivastava, S., HEC School of Management, P., Theng, Y.-L., & Nanyang Technological University
- Affiliations
- Nanyang Technological University (SG)
- HEC Paris (FR)
- Venue
- Journal of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2012-10
- Volume
- 13
- Issue
- 10
- Pages
- 797-835
- ISSN
- 1536-9323 (ISSN-L)
- OpenAlex
- W2120230739
- Cited by
- 90
- References
- 126
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 13 · 2023: 7 · 2022: 5 · 2021: 14 · 2020: 6 · 2019: 5 · 2018: 5 · 2017: 3 · 2016: 7 · 2015: 6 · 2014: 3 · 2013: 4
- FWCI
- 8.48
- Type
- journal article
- Language
- en
- Open access
- green
- aisel.aisnet.org
- Locations
- Journal of the Association for Information Systems (publishedVersion)
- DR-NTU (Nanyang Technological University) (submittedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Social Sciences › Communication › Knowledge Management and Sharing
- Keywords
- virtual worlds, workplace collaboration, cognitive absorption, user trust, risk perception, social cognitive theory, nomological network, technology adoption
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.
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