DocumentCode :
1323863
Title :
A Framework to Model the Topological Structure of Supply Networks
Author :
Xuan, Qi ; Du, Fang ; Li, Yanjun ; Wu, Tie-Jun
Author_Institution :
Dept. of Autom., Zhejiang Univ. of Tech nology, Hangzhou, China
Volume :
8
Issue :
2
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
442
Lastpage :
446
Abstract :
Topological structure is considered more and more important in managing a supply network or predicting its development. In this paper, a new framework is proposed to model the topological structure of supply networks, where different types of supply networks can be created just by introducing different supplier-customer connecting rules. Generally, the networks created in the framework are much different from the random networks with the same degree sequences. The revealed phenomenon suggests that real-world supply networks may benefit from its intrinsic mechanism on flexibility, efficiency, and robustness to target attacks. Note to Practitioners-The topological structure of supply networks is considered more and more important in managing a supply network or predicting its development. In this paper, we introduce a framework to model and analyze the topological structure of supply networks. This work aims to characterize supply networks by statistical methods and can help researchers better understand the material dynamics on supply networks and further conveniently create their own supply networks by summarizing practical supplier-customer connecting rules or analyzing real-world supply network data. The work should be further expanded in other aspects, such as simulating material dynamics on supply networks, designing optimal structure by introducing proper supplier-customer connecting rules, rearranging local connections to enhance the competi tiveness and further ensure the long-term benefit of a target firm, and so on, all of which are of much interest for governors, investors, and managers and can be studied in the present framework in the future.
Keywords :
statistical analysis; supply chain management; statistical methods; supplier-customer connecting rules; supply network management; supply network material dynamics; supply network topological structure; Adaptation model; Complex networks; Complexity theory; Joining processes; Raw materials; Robustness; Complex network; logistics; modeling; self-organized system; supply network;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2010.2071414
Filename :
5570951
Link To Document :
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