Fuzzy approach to supply chain management
During recent years, the supply chain performance management has become a key strategic consideration. Many manufacturers seek to collaborate with their suppliers and customers in order to upgrade their competitiveness and management performance. Because of complexity, uncertainty and vagueness inherent in supply chains, performance measurement using fuzzy approach was also identified as a new research direction. The main aim of the paper is focused on evaluation of logistic dimensions (sets of logistic indicators) in supply chain, where the uncertainty arises from the inability to perform adequate measurement, and deals with application of fuzzy approach, that provides a formal method for modeling imprecise, vagueness or incomplete relationships inherent in supply chains. Gathered data from questionnaires are analyzed by cluster analysis. Afterwards fuzzy methods are used evaluations of basic five dimensions, which contain several numbers of logistic indicators. The new methodology adopted from Soyer, Kabak, & Asan (2007) research based on the intersection of fuzzy sets and fuzzy entropy method has been applied to evaluations in a case study. Results are afterwards modified by a applying of different membership functions, and changes of dimensions measures are analyzed. Finally supply chain modifying by adding new companies with capability of bind to supply chain are examined. New results of evaluation are compared according to new companies’ membership to different clusters.
|Date of creation:||Jan 2011|
|Date of revision:|
|Contact details of provider:|| Postal: Studentská 13, 370 05 České Budĕjovice|
Web page: http://ewp.ef.jcu.cz/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1999. "Supply chain modelling using fuzzy sets," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 443-453, March.
- Martinez-Olvera, Cesar, 2008. "Entropy as an assessment tool of supply chain information sharing," European Journal of Operational Research, Elsevier, vol. 185(1), pages 405-417, February.
- Wu, Y. & Frizelle, G. & Efstathiou, J., 2007. "A study on the cost of operational complexity in customer-supplier systems," International Journal of Production Economics, Elsevier, vol. 106(1), pages 217-229, March.
- Shuiabi, Eyas & Thomson, Vince & Bhuiyan, Nadia, 2005. "Entropy as a measure of operational flexibility," European Journal of Operational Research, Elsevier, vol. 165(3), pages 696-707, September.
- Chang, Sheng-Lin & Wang, Reay-Chen & Wang, Shih-Yuan, 2006. "Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle," International Journal of Production Economics, Elsevier, vol. 100(2), pages 348-359, April.
- Jaroslava Smolová, 2009. "Analysis of metrics used for storage process evaluation," Acta Universitatis Bohemiae Meridionales, University of South Bohemia in Ceske Budejovice, vol. 12(3), pages 111-118.
When requesting a correction, please mention this item's handle: RePEc:boh:wpaper:01_2011. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Martin Pech)
If references are entirely missing, you can add them using this form.