• 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