Social network analysis to understand the dynamics of global supply chains

Autor: Carlos A. Meisel, Jose D. Meisel, Helga Bermeo-Andrade, Laura Carranza, Helmut Zsifkovits
Rok vydání: 2022
Předmět:
Zdroj: Kybernetes.
ISSN: 0368-492X
DOI: 10.1108/k-02-2022-0191
Popis: PurposeThe aim of this study is to increase the understanding of collaborative relationships and assess according to the project size, the influence of the contributory factors in shaping collaboration network structure in projects developed in global supply chains (GSC).Design/methodology/approachThe paper used a case study methodology applied to eight global projects developed by an Austrian company leader in global market intra-logistics solutions and warehouse automation. The cases were studied by two approaches in network analysis. First, visual and descriptive analysis to describe structural aspects of the network. Second, stochastic network analysis to evaluate the influence of contributory factors in the structure of the collaboration network.FindingsThe results evidence that independently of the project size and project manager influence, project team roles (PTR) who have a reciprocal communication among other PTR tend to have a higher collaboration intensity (CI). Additionally, the results highlight the influence of the project manager in shaping the collaboration network in standard projects (STP) and small projects (SMP). According to the project size, the results show that the PTR that form complete triangles or cluster or who communicate frequently among each other tend to have a high CI, being more evident these tendencies in large-scale projects than STP and SMP.Originality/valueThis research provides a framework to identify the key actors and contributory factors in shaping collaborative relationships in GSC. The findings could be used to support the decision-making process and formulation strategies for effective collaborative relationship management in GSC.
Databáze: OpenAIRE