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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/3411
Title: The Mind's Eye on Personal Profiles - How to inform trustworthiness assessments in virtual project teams
Authors: Rusman, Ellen
Keywords: trust
trustworthiness
virtual team
identity
profile
impression formation
Issue Date: 29-Jun-2011
Series/Report no.: SIKS Dissertation Series;2011–19
Abstract: The central research question of this thesis is: How to inform trustworthiness assessments of virtual project team members in the initial phase of collaboration?
There is common agreement that the availability of personal information and the possibility to interact informally at the start of a project accelerates the trust formation process. This goes for face-to-face as well as for virtual project teams. However, there is no shared understanding as to what information is critical for this acceleration and why it is so. Acceleration of the trust formation process is beneficial, as interpersonal trust is one of the key factors influencing performance in face-to-face as well as virtual teams. When little or no trust exists within a team, serious collaboration problems are bound to occur. Virtual project teams experience more problems with interpersonal trust formation than face-to-face teams. This is likely to be due to the diminished availability of information and its computer-mediated character. Once we know what information is important for trustworthiness assessments and why it is so, we could use it for the design of measures to accelerate the formation of interpersonal trust. To investigate the central research question we combined a theoretical (top-down) with a practical, design-oriented (bottom-up) research approach. We concluded our research with an evaluation.
Description: Rusman, E. (2011). The Mind's Eye on Personal Profiles - How to inform trustworthiness assessments in virtual project teams (Doctoral dissertation). June, 17, 2011, Open University in the Netherlands (CELSTEC), Heerlen, The Netherlands.
URI: http://hdl.handle.net/1820/3411
ISBN: 9789079447503
Appears in Collections:PhD Learning Networks Research
1. LN: Publications and Preprints

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