Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104559
PIRA download icon_1.1View/Download Full Text
Title: Information system selection for a supply chain based on current trends : the BRIGS approach
Authors: Samvedi, A 
Jain, V
Chan, FTS 
Chung, SH 
Issue Date: Sep-2018
Source: Neural computing and applications, Sept 2018, v. 30, no. 5, p. 1619-1633
Abstract: Information systems are very crucial in today’s organizations, and hence the selection of the right system has become a very critical decision. As time has progressed, with new issues affecting the supply chain and the performance metrics being continually rewritten, the responsibility of the information systems has increased manifold. Nowadays, information systems are expected to perform a number of functions such as information security, big data handling, green supply chain and risk management and thus the basic problem of system selection is now more complex. Also, adding to the complexity is the fact that these new issues are interdependent and most of the times influence other issues in a variety of direct or indirect ways. This study addresses this problem by proposing a new model for information system selection by incorporating the latest trends in the supply chain. It also proposes an integrated methodology, to solve such a problem where interdependence between criteria exists. The advantages of this methodology over other existing techniques are delinking the evaluation of interdependent criteria weights from performance evaluation, flexibility of inputs, ability to handle vagueness and uncertainty in judgements. The methodology is illustrated using a numerical example.
Keywords: Big data
Fuzzy DEMATEL
Fuzzy TOPSIS
Green supply chain
Information security
Information systems
Supply chain management
Publisher: Springer UK
Journal: Neural computing and applications 
ISSN: 0941-0643
EISSN: 1433-3058
DOI: 10.1007/s00521-016-2776-8
Rights: © The Natural Computing Applications Forum 2016
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s00521-016-2776-8.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Chan_Information_System_Selection.pdfPre-Published version1.55 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

70
Last Week
2
Last month
Citations as of Nov 30, 2025

Downloads

40
Citations as of Nov 30, 2025

SCOPUSTM   
Citations

4
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

4
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.