CQUniversity
Browse

Determining supply chain flexibility using statistics and neural networks : a comparative study

Download (378.3 kB)
conference contribution
posted on 2017-12-06, 00:00 authored by Ananda Jeeva, Wanwu GuoWanwu Guo
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.

History

Start Page

506

End Page

509

Number of Pages

4

Start Date

2009-01-01

ISBN-13

9780769538389

Location

Gold Coast, Queensland, Australia

Publisher

IEEE Computer Society

Place of Publication

Los Alamitos, USA

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

Faculty of Arts, Business, Informatics and Education; Institute for Resource Industries and Sustainability (IRIS);

Era Eligible

  • Yes

Name of Conference

International Conference on Network and System Security