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

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.

The role of active teaching, academic self-efficacy, and learning behaviors in student performance

“…positive or negative) and strength of the relationship among the study’s variables. Despite evidence of correlations among the independent variables, the use of summated scales and SPSS tolerance and variance inflation scores suggested that multicollinearity was not an issue in this study (Segura et al , 2013). Descriptive statistics and bivariate correlations among the variables are reported in the correlation table presented in Table 2.…”

Empirical study of communication structures and barriers in geographically distributed teams

“…The difficulty with exchanging information is defined as an inconsistency of attributes between the sender and receiver, thereby the effective exchange of information between units requires that each team provide and receive similar information attributes [16]. Distributed teams are allocated to complex, interdependent tasks using technology to tackle three commonly known boundaries known as relational, temporal and spatial [17]. Communication and coordination: Conway's law explicitly recognises that communication patterns of an organisation are imprinted as an ineffaceable mark on the product built [4, 5].…”

“…The benefits of establishing a more cohesive organisational structure can enable an increased efficiency in the exchange and flow of information between two teams in different environments. Ever‐changing global environments and progressively cost‐effective communication technologies have increased communication amongst geographically distributed teams [17]. There are greater benefits for information management and product development when processes are automated.…”