Date of Award
8-2013
Document Type
Thesis
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
First Advisor
Dr. Deepak Khazanchi
Abstract
Virtual teams (VT) consist of people who rely on information technology (IT) capabilities to interact and work from different geographic locations to accomplish explicit team goals. The virtual team has become an important building block in organizations to fulfill such purposes as generating new knowledge, managing a project, and delivering customer services. However, virtual teams continue to present many challenges to organizations. Developing shared mental models (SMM), which are team members’ shared understanding about key elements of the team’s environment, is one of the most significant challenges facing virtual teams. Despite the critical importance of IT in virtual teams, no study has empirically examined how virtual teams’ adaptive use of IT capabilities will influence the development of SMM in virtual teams. Drawing on theories from shared mental models and technology use research, this dissertation examines the interplay between the adaptive use of IT capabilities (AUITC) and the development of shared mental models in virtual teams. Using multiple longitudinal case studies within an educational setting, this dissertation examines this interplay relationship in detail through within-case analysis and cross-case analysis. Overall, study results showed that the degree to which virtual teams’ shared mental models converge is affected by the three dimensions of IT capabilities adaptive use: inclusiveness, usage experience, and fit. The findings suggest that managers of virtual teams should 1) encourage teams’ inclusive use of IT capabilities, 2) build an open and innovative culture, 3) choose knowledgeable, proactive, and responsible team leaders, 4) introduce technologies to support VTs that are compatible across heterogeneous platforms, and 5) set up clear team expectations about IT capabilities. Based on the results of this study, further research is provided.
Virtual teams (VT) consist of people who rely on information technology (IT)
capabilities to interact and work from different geographic locations to accomplish explicit team goals. The virtual team has become an important building block in organizations to fulfill such purposes as generating new knowledge, managing a project, and delivering customer services. However, virtual teams continue to present many challenges to organizations. Developing shared mental models (SMM), which are team members’ shared understanding about key elements of the team’s environment, is one of the most significant challenges facing virtual teams. Despite the critical importance of IT in virtual teams, no study has empirically examined how virtual teams’ adaptive use of IT capabilities will influence the development of SMM in virtual teams. Drawing on theories from shared mental models and technology use research, this dissertation examines the interplay between the adaptive use of IT capabilities (AUITC) and the development of shared mental models in virtual teams. Using multiple longitudinal case studies within an educational setting, this dissertation examines this interplay relationship in detail through within-case analysis and cross-case analysis. Overall, study results showed that the degree to which virtual teams’ shared mental models converge is affected by the three dimensions of IT capabilities adaptive use: inclusiveness, usage experience, and fit. The findings suggest that managers of virtual teams should 1) encourage teams’ inclusive use of IT capabilities, 2) build an open and innovative culture, 3) choose knowledgeable, proactive, and responsible team leaders, 4) introduce technologiestosupportVTsthatarecompatibleacrossheterogeneousplatforms, and 5) set up clear team expectations about IT capabilities. Based on theresults of
this study, further research is provided.
Recommended Citation
Yu, Xiaodan, "UNDERSTANDING THE ADAPTIVE USE OF IT CAPABILITIES AND DEVELOPMENT OF SHARED MENTAL MODELS IN VIRTUAL TEAMS" (2013). Student Work. 2891.
https://digitalcommons.unomaha.edu/studentwork/2891
Files over 3MB may be slow to open. For best results, right-click and select "save as..."
Comments
A DISSERTATION Presented to the Faculty of The College of Information Science and Technology at the University of Nebraska at Omaha In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy. Copyright 2013 Xiaodan Yu.