2018
DOI: 10.3390/mti2030048
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The Impact of Multimodal Communication on a Shared Mental Model, Trust, and Commitment in Human–Intelligent Virtual Agent Teams

Abstract: There is an increasing interest in the use of intelligent virtual agents (IVAs) to work in teams with humans. To achieve successful outcomes for these heterogeneous teams, many of the aspects found in successful human teams will need to be supported. These aspects include behavioural (i.e., multimodal communication), cognitive (i.e., a shared mental model (SMM)), and social (trust and commitment). Novelly, this paper aims to investigate the impact of IVA’s multimodal communication on the development of a SMM b… Show more

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Cited by 23 publications
(8 citation statements)
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“…The present study showed a high correlation between trust and SMM, which is in line with previous findings ( Hanna and Richards, 2018 ). While both SMM and CLC were related to team processes, trust was not.…”
Section: Discussionsupporting
confidence: 94%
“…The present study showed a high correlation between trust and SMM, which is in line with previous findings ( Hanna and Richards, 2018 ). While both SMM and CLC were related to team processes, trust was not.…”
Section: Discussionsupporting
confidence: 94%
“…The design of IVAs focuses on different user-centred aspects such as dialogue, emotion, appearance, presence and behaviour, but design decisions do not always reflect the design goals or the qualities valued by the users [16]. Research on cross-platform (multi-modal) IVA design or development tends to refer to systems/platforms that combine aspects of an IVA (e.g, [10,35]) or the integration of an IVA platform with another platform such as VR or augmented reality (e.g., [2,13]). We have in this design study presented a somewhat novel and interesting concept of a cross-platform IVA where the agent is able to adapt to different embodiments, be it physical (robot) or virtual (on screen), and provide seamless interaction.…”
Section: Discussionmentioning
confidence: 99%
“…In a review and analysis of 24 studies that measured trust in HAT ( O’Neill et al, 2020 ), higher levels of agent autonomy ( Azhar and Sklar, 2017 ), and higher levels of transparency ( Boyce et al, 2015 ; Sharifheravi et al, 2020 ), had a positive effect on trust. When an autonomous agent’s personality ( Hanna and Richards, 2018 ), values ( Mehrotra et al, 2021 ), and work style are similar to participants, they trust agents more, even preferring to work with an agent over a human in low-risk situations ( You and Robert, 2018 ). Other factors influencing higher levels of trust in autonomous agents include experience with similar computers or computers that employ independent agents ( Chen et al, 2011 ), team training ( Walliser et al, 2019 ), and agent reputation ( Hafizoglu and Sen, 2018 ).…”
Section: Introductionmentioning
confidence: 99%