Identification and evaluation of collaborative relationships of internal project stakeholders: a social network analysis approach

Abstract

Purpose

The present research is trying to construct the network of relationships between different department of an organization during the design and development of car engine. Analyzing the structure of the network, finding the patterns of collaborations, and determining the important departments are the main purposes of the present research.

Design/methodology/approach

Improving relationships during a project life is an effective way to enhance employee performance in project-oriented organizations. This paper examines the collaborative relationships between internal project stakeholders through social network analysis (SNA) in a project for the design and development of car engine. In the first step of the research, the network of internal stakeholders was studied based on collaboration in the common activities performed by the resources. Then, the network of correspondences between internal stakeholders was studied. Finally, the two networks were integrated into a single network.

Findings

In the integrated network, the “fuel and combustion department” had the largest degree centrality (i.e. highest collaboration with others). The “integration department” was found to have the highest closeness centrality (i.e. more rapid access to other nodes). Furthermore, the “procurement department” had the highest betweenness centrality (i.e. the most strategic department). Our results revealed the potential capabilities of SNA method for the project management in the vehicle industry.

Originality/value

The obtained results of the present research show us the value of applying SNA methods and concepts to analyze the inter-organizational network of the Project Stakeholders relationship.

Citation

Fallah, M.A., Agha Mohammad Ali Kermani, M., Moini, A. and Mashayekh, J. (2023), "Identification and evaluation of collaborative relationships of internal project stakeholders: a social network analysis approach", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-12-2022-1648