Social Network Analysis in Project Management

Social Network Analysis (SNA) has emerged as a transformative lens in project management, offering quantitative and visual tools to map and assess the interrelations of stakeholders, tasks and resources. By modelling participants as nodes and their interactions as ties, SNA reveals the structural patterns that underpin communication flows, decision-making paths and power dynamics across the project lifecycle. Centrality measures such as degree and betweenness identify influential actors, while network density gauges overall connectivity and the potential for information diffusion. These insights enable practitioners to pinpoint critical collaboration clusters, pre-empt bottlenecks and mitigate relational risks, enhancing cost, time and quality performance. Recent advancements have extended SNA beyond descriptive mapping to predictive modelling, integration with machine learning and application to emergent domains including building information modelling, open innovation networks and sustainable supply chains. Global case studies from construction, information technology and energy sectors illustrate the practical utility of SNA in identifying success factors, governing complex networks in megaprojects and embedding regulatory and environmental values in stakeholder engagement. As digital tools proliferate, SNA is poised to become a core component of project intelligence, supporting data-driven decision making and resilient governance in an interconnected world.

Research from Nature Portfolio

No recent Nature Portfolio content available.

Research from all publishers

Several recent studies published outside Nature Portfolio have advanced the application of SNA in project management. One study integrates machine learning with network analytics to model cost, time and quality outcomes, demonstrating that stakeholder network attributes significantly enhance predictive accuracy and offering a replicable framework for performance forecasting. Another work proposes a heuristic model to uncover project collaboration types and corresponding critical success factors by combining SNA with risk management principles; it provides managers with actionable guidance on communication, collaboration and knowledge-sharing dynamics throughout the project lifecycle. A third investigation examines formal and informal relations within BIM-enabled supply-chain partnerships, revealing that balance between formal contractual ties and informal peer-learning networks optimises knowledge diffusion and integration in construction projects. Together, these contributions underscore a shift towards data-driven, integrative approaches that harness network structures to improve project governance, stakeholder engagement and adaptive capacity across disciplines and geographical contexts.

Social Network Analysis in Project Management publication trend

The graph below shows the total number of articles in social network analysis in project management across all publications each year (not limited to Nature Index journals).

Technical terms

Social Network Analysis (SNA): A methodological approach that represents stakeholders or entities as nodes and their relationships as ties to analyse structural patterns and interactions.

Centrality: A metric indicating the influence or importance of a node within a network, commonly measured by degree, betweenness or closeness.

Network Density: The proportion of actual connections relative to all possible connections in a network, reflecting overall connectivity.

Stakeholder Network: The pattern of formal and informal relationships among individuals or organisations involved in a project.

Tie Strength: A measure of the intensity or frequency of interaction between two nodes within a network.

References

1. Integrating machine learning and network analytics to model project cost, time and quality performance. Production Planning & Control (2023).
2. Formal and informal relations within BIM-enabled supply chain partnerships. Construction Management and Economics (2017).
3. Managing Open Innovation Project Risks Based on a Social Network Analysis Perspective. Sustainability (2020).