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
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;
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
DOI :
10.1109/NSS.2009.87