Effects of geographic and demographic dispersion on the performance of systems engineering teams

Article type: Research Article

Authors: Segura, Marco | Sarkani, Shahram | Mazzuchi, Thomas

Affiliations: The George Washington University, Washington, DC, USA

Note: [] Corresponding author: Marco Segura, The George Washington University, Washington, DC, USA. Tel.: +1 202 251 8418; E-mail: msegura@gwu.edu

Abstract: Globalization and the increasing complexity of systems require collaboration across multidisciplinary teams. Systems Engineering (SE) teams are often geographically and demographically dispersed; such dispersion might affect the ability of the teams to produce their desired outcomes. The main objective of this research study was to determine how geographic and demographic dispersion affect the performance of a SE team, and which phases of the SE life cycle are more susceptible to positive or negative effects caused by team dispersion. This research study started with an exhaustive review of the literature related to team dispersion and team performance. The next step was building a conceptual model grounded in theory, which allowed the measurement of geographic and demographic dispersion through the use of well-established indices recognized by the scientific community. The data collection process successfully gathered information about projects geographically distributed throughout 57 cities in 38 countries. Finally, multiple linear regression (MLR) and structural equation modeling (SEM) were selected as data analysis techniques for this study. The results of MLR show that geographic and demographic dispersion factors (independent variables) statistically significantly predicted team performance along each phase (dependent variables) of the SE life cycle. The results of SEM show a moderate positive relationship between dispersion and team performance. It was also found that the SE life cycle phases of Development and Production are the higher predictors of team performance.

Keywords: Geographic dispersion, demographic dispersion, team performance, systems engineering, structural equation modeling

DOI: 10.3233/IKS-130222

Journal: Information Knowledge Systems Management, vol. 12, no. 2, pp. 149-166, 2013