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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. [ABSTRACT FROM AUTHOR]

Internet+ecosystems, big data applications, customers' specific demands, and internal and external values integration of enterprises pose new challenges to inter-organizational collaborations in supply chain networks. To confront these challenges, this paper integrates computational experiment and data analysis, and proposes a methodology for data-driven computational experiments for inter-organizational collaborations in supply chain networks. It explores a paradigm shift to the development of data-driven computational experiments that supports decision making in the domain of inter-organizational collaborations. A basic principle for integrated solutions generation in the parallel worlds of virtual reality interaction is studied and the corresponding key issues in the paradigm are analyzed. To support the paradigm and solve key issues, a six-layered framework with four viewpoints for data-driven computational experiments is proposed. This framework systematically presents conceptual and technical solutions for data-driven computational experiments and decision support in the domain of inter-organizational collaborations in supply chain networks. The effectiveness of the framework is verified by theoretical analysis and a case study. [ABSTRACT FROM AUTHOR]