Team Size as a Moderating Factor in Remote Project Management: Evidence From Saudi Arabia
Year: 2025
Type: article
Study design: Observational Study
Abstract: This study investigates the moderating effect of team size on remote project management outcomes in Saudi Arabian organizations, addressing a critical gap in understanding optimal virtual team configurations in emerging markets. Through quantitative analysis of data collected from 289 project professionals across multiple sectors in Saudi Arabia, the research examines how varying team sizes influence project completion rates, resource utilization, and coordination efficiency in remote work environments. Using structural equation modeling and hierarchical regression analysis, the findings reveal that medium-sized teams (8-12 members) demonstrate optimal performance metrics in remote settings. In comparison, larger teams (>15 members) show diminishing returns in coordination efficiency and project completion rates. The study also identifies critical thresholds where increasing team size begins to negatively impact virtual collaboration effectiveness. Results indicate that team size explains 34% of the variance in project completion rates when controlling for project complexity and industry type. These findings contribute to project management theory by establishing team size as a significant moderating variable in remote project success, particularly within the Saudi Arabian context. The research provides practical implications for project managers in optimizing team configurations for remote work, offering evidence-based recommendations for team sizing based on project scope and complexity. This study advances our understanding of virtual team dynamics in emerging markets and provides a foundation for future research on team size optimization in remote project management.
Source: Social science and management.
DOI: 10.61784/ssm3038
Author: Nofal Abdulhadi
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4410786100