Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22578
Title: Fuzzy time series forecasting for supply chain disruptions
Authors: Chan, FTS 
Samvedi, A 
Chung, SH
Keywords: Forecasting
Fuzzy time series forecasting
Simulation
Supply chain risk management
Issue Date: 2015
Publisher: Emerald Group Publishing Limited
Source: Industrial management and data systems, 2015, v. 115, no. 3, p. 419-435 How to cite?
Journal: Industrial management and data systems 
Abstract: Purpose: The purpose of this paper is to test the effectiveness of fuzzy time series (FTS) forecasting Ac system in a supply chain experiencing disruptions and also to examine the changes in performance as the authors move across different tiers. Design/methodology/approach: A discrete event simulation based on the popular beer game model is used for these tests. A popular ordering management system is used to emulate the behavior of the system when the game is played with human players. Findings: FTS is tested against some other well-known forecasting systems and it proves to be the best of the lot. It is also shown that it is better to go for higher order FTS for higher tiers, to match auto regressive integrated moving average. Research limitations/implications: This study fills an important research gap by proving that FTS forecasting system is the best for a supply chain during disruption scenarios. This is important because the forecasting performance deteriorates significantly and the effect is more pronounced in the upstream tiers because of bullwhip effect. Practical implications: Having a system which works best in all scenarios and also across the tiers in a chain simplifies things for the practitioners. The costs related to acquiring and training comes down significantly. Originality/value: This study contributes by suggesting a forecasting system which works best for all the tiers and also for every scenario tested and simultaneously significantly improves on the previous studies available in this area.
URI: http://hdl.handle.net/10397/22578
ISSN: 0263-5577
EISSN: 1758-5783
DOI: 10.1108/IMDS-07-2014-0199
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

5
Last Week
0
Last month
0
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

3
Last Week
0
Last month
1
Citations as of Aug 15, 2017

Page view(s)

41
Last Week
5
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



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