768
Views
53
CrossRef citations to date
0
Altmetric
Original Articles

Adaptation and adaptability in logistics networks

&
Pages 143-157 | Published online: 15 Aug 2006
 

Abstract

Most logistics and supply chain management studies take a “systems view”, where all elements are to be understood by how they affect/are affected by other elements with which they interact. Supply chain integration requires that elements be adapted to each other. However, the literature suggests that there may be trade-offs between previous and present adaptations and future adaptability. A case is used to illustrate such trade-offs and the relevance of choice of system borders when such trade-offs are analysed. In logistics, the view on what the relevant system borders are has changed over the years, from local optimisations to a “network view”. The paper contributes to the understanding of system boundaries, integration problems and complementarities between chain and network approaches in logistics. Conclusions regarding further research are drawn. In particular, the paper challenges the optimisation question and change of management levels, comparing the prevailing chain view with a wider network view.

Acknowledgements

The authors would like to acknowledge and thank the Norwegian Research Council and the Norwegian companies Bama, Unitor, Norsk Hydro, Posten, Tine, Tomra and Kitron for their financial support of this research. We also sincerely appreciate comments and suggestions received from Prof. Lars-Gunnar Mattson and anonymous reviewers.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 235.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.