Effects of Geographic and Demographic Dispersion on the Performance of Systems Engineering Teams Open Access
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Effects of Geographic and Demographic Dispersion on the Performance of Systems Engineering TeamsGlobalization 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 along each phase of the SE life cycle, and which dispersion factors have more influence on the performance of an SE team for each life cycle phase.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 analysis (MLR) was conducted for each SE life cycle phase, to predict team performance (dependent variable) based on geographic and demographic variables (independent variables). The results of MLR show that independent variables statistically significantly predicted team performance along each phase of the SE life cycle, except for the Retirement phase, which was excluded from the model due to low amount of data collected about team performance for this phase (only 26.66% of the identified projects reached the Retirement phase at the time of data collection).Considering the MLR results, this research study identified the geographic and demographic dispersion factors for each SE Life Cycle phase that are high predictors of team performance. Additionally, Age and Primary Language were identified as the demographic dispersion factors that added statistically significantly to the prediction of team performance during all phases of the SE Life Cycle.