Abstract
Literature on analysis of inter-organizational networks mentions the benefits that collaboration networks can provide to firms, in terms of managerial decision-making, although rarely analysed in terms of their overall performance. This paper aims to identify the existence of common factors of evolutionary patterns in the networks that determine its performance and evolution through a Multiple Factor Analysis (MFA). Subsequently, a hierarchical clustering procedure was performed on the factors that determine these networks, trying to find similarities in the evolutionary behavior. Data were collected on twelve real collaboration networks, characterized by four variables: Operational Result, Stock of Knowledge, Operational Costs and Technological Distance. The hierarchical clustering allowed the identification and distinction of the networks with the worst and best performances, as well as the variables that characterize them, allowing to recognize poorly defined strategies in the constitution of some networks.
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Notes
- 1.
The collaboration networks identified for this paper are the following: Continental Lemmerz (Portugal); Comportest; Nokia Siemens Networks U.S; Valindo - Têxteis, S.A; Renault-Nissan; Renault-Nissan-Daimler; Sony Mobile Communications Ab; Trützschler-Marzoli; Spairliners Gmbh; Lufthansa Bombardier Aviation Services Gmbh; N3 Engine Overhaul Services Gmbh & Co. Kg; Vanpro - Assentos, Lda; for more details concerning the data and the variables involved, see [28].
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Duarte, P., Campos, P. (2020). Evolution of Business Collaboration Networks: An Exploratory Study Based on Multiple Factor Analysis. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: Complexity of Decisions and Decisions for Complexity. DECON 2019. Advances in Intelligent Systems and Computing, vol 1009. Springer, Cham. https://doi.org/10.1007/978-3-030-38227-8_33
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