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Identifying dynamical instabilities in supply networks using Generalized Modeling

Demirel, G�ven; Maccarthy, Bart; Ritterskamp, Daniel; Champneys, Alan R.; Gross, Thilo


G�ven Demirel

Daniel Ritterskamp

Alan R. Champneys

Thilo Gross


Supply networks need to exhibit stability in order to remain functional. Here, we apply a Generalized Modeling (GM) approach, which has a strong pedigree in dynamical systems, to study the stability of real world supply networks. It goes beyond purely structural network analysis approaches by incorporating material ows, which are dening characteristics of supply networks. The analysis focuses on the network of interactions between material ows, providing new conceptualizations to capture key aspects of production and inventory policies. We provide stability analyses of two contrasting real world networks-that of an industrial engine manufacturer and an industry-level network in the luxury goods sector. We highlight the criticality of links with suppliers that involve the dispatch, processing and return of parts or sub-assemblies, cyclic motifs that involve separate paths from a common supplier to a common rm downstream, and competing demands of dierent end products at specic nodes. Based on a critical discussion of our ndings in the context of the supply chain management literature, we generate ve propositions to advance knowledge and understanding of supply network stability. We discuss the implications of the propositions for the eective management, control, and development of supply networks. The GM approach enables fast screening to identify hidden vulnerabilities in extensive supply networks


Demirel, G., Maccarthy, B., Ritterskamp, D., Champneys, A. R., & Gross, T. (2019). Identifying dynamical instabilities in supply networks using Generalized Modeling. Journal of Operations Management, 65(2), 136-159.

Journal Article Type Article
Acceptance Date Feb 11, 2019
Online Publication Date Mar 18, 2019
Publication Date Mar 18, 2019
Deposit Date Feb 13, 2019
Publicly Available Date Feb 13, 2019
Journal Journal of Operations Management
Print ISSN 0272-6963
Electronic ISSN 1873-1317
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 65
Issue 2
Pages 136-159
Keywords Supply chain; Complex networks; Nonlinear dynamics; Stability
Public URL
Publisher URL


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