Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/29351
Title: Grey modelling based forecasting system for return flow of end-of-life vehicles
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
Ene, Seval
Öztürk, Nursel
AAG-8949-2021
AAG-9336-2021
48461146800
7005688805
Keywords: Business & economics
Public administration
End-of-life vehicles
Forecasting
Grey modelling
Product returns
Reverse logistics
Product returns
Supply chain
Prediction
Consumption
Design
Time
Turkey
Fourier series
Markov processes
Supply chains
System theory
Vehicles
End-of-life vehicles
Forecasting problems
Forecasting system
Grey system theory
Parameter optimization
Product returns
Reverse supply chains
Strategic tool
Flow modeling
Forecasting method
Fourier transform
Markov chain
Optimization
Profitability
Forecasting
Issue Date: Feb-2017
Publisher: Elsevier
Citation: Ene, S. ve Öztürk, N. (2017). ''Grey modelling based forecasting system for return flow of end-of-life vehicles''. Technological Forecasting and Social Change, 115, 155-166.
Abstract: Due to legislation and economic reasons, firms in most industries are forced to be responsible and manage their products at the end of their lives. Management of product returns is critical for the stability and profitability of a reverse supply chain. Forecasting the return amounts and timing is beneficial. The purpose of this paper is to develop a forecasting system for discarded end-of-life vehicles and to predict the number of end-of-life vehicles that will be generated in the future. To create the forecasting system, grey system theory, which uses a small amount of the most recent data, is employed. The accuracy of the grey model is improved with parameter optimization, Fourier series and Markov chain correction. The proposed models are applied to the case of Turkey and data sets of twelve regions in Turkey are considered. The obtained results show that the proposed forecasting system can successfully govern the phenomena of the data sets, and high accuracy can be provided for each region in Turkey. The proposed forecasting system can be used as a strategic tool in similar forecasting problems, and supportive guidance can be achieved.
URI: https://doi.org/10.1016/j.techfore.2016.09.030
https://www.sciencedirect.com/science/article/pii/S0040162516303675
http://hdl.handle.net/11452/29351
ISSN: 0040-1625
1873-5509
Appears in Collections:Scopus
Web of Science

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