DocumentCode
2300599
Title
Determining Supply Chain Flexibility Using Statistics and Nueral Networks: A Comparative Study
Author
Jeeva, Ananda ; Guo, William
Author_Institution
Fac. of Arts, Bus., Inf. & Educ., Central Queensland Univ., Rockhampton, QLD, Australia
fYear
2009
fDate
19-21 Oct. 2009
Firstpage
506
Lastpage
509
Abstract
The purpose of this paper is to examine the application of neural networks as a flexibility and performance measure in supplier-manufacturer activities. The dimensions of information exchange, supplier integration, product delivery, logistics, and organisational structure are used as determinants factors affecting this supply chain flexibility. The data set was collected from more than 200 Australian manufacturing firms evaluating their suppliers. Our study shows that neural networks can accurately determine a supplier´s flexibility with an error within 1%, which is more accurate than the conventional multivariate regression can.
Keywords
logistics; neural nets; organisational aspects; statistical analysis; supply chains; information exchange; logistics; neural network; organisational structure; product delivery; statistics; supplier integration; supplier-manufacturer activity; supply chain flexibility; Art; Artificial neural networks; Informatics; Logistics; Manufacturing; Multivariate regression; Neural networks; Statistics; Stochastic processes; Supply chains;
fLanguage
English
Publisher
ieee
Conference_Titel
Network and System Security, 2009. NSS '09. Third International Conference on
Conference_Location
Gold Coast, QLD
Print_ISBN
978-1-4244-5087-9
Electronic_ISBN
978-0-7695-3838-9
Type
conf
DOI
10.1109/NSS.2009.87
Filename
5319324
Link To Document