Abu, Noratikah and Ismail, Zuhaimy (2019) A study on private vehicle demand forecasting based on Box-Jenkins method. In: AIP Conference Proceedings; 3rd International Conference on Automotive Innovation Green Energy Vehicle, AiGEV 2018 , 25 - 26 July 2018 , Kuantan, Pahang. 020005-1., 2059 (020005). ISSN 0094-243X ISBN 978-073541787-8
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Abstract
Demand forecasting has become a priority to an organisation in order to manage their operations. Literature reviews on car demand forecasting are rather limited and many methods used are confined to static approaches. Malaysia is a developing country and expected to be classified as a developed country in 2020. We envisage that the study on vehicle demand forecasting will yield fruitful results. Nevertheless, a proper study on private car demand forecasting is still limited due to heavy data requirements. In this study, we propose the development of suitable forecasting model for private vehicle demand in Malaysia based on the actual data from January 2000 until December 2009. The Box-Jenkins methodology will be used to analyse and forecast Malaysian private vehicle demand. Box-Jenkins method is by far one of the most efficient forecasting techniques, especially when dealing with univariate time series data. Standard procedure of identification, estimation and diagnostic checking are employed. Based on the diagnostic checking, we consider the seasonal ARIMA model and by using Minitab software, results show that SARIMA(2,1,0)(200)12 model is most suitable for forecasting. The results show that the Box-Jenkins method is applicable to forecast private vehicle demand in Malaysia.
Item Type: | Conference or Workshop Item (Lecture) |
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Additional Information: | Indexed by Scopus |
Uncontrolled Keywords: | Box-Jenkins method; Demand forecasting; ARIMA model; Forecasting |
Subjects: | Q Science > QA Mathematics |
Faculty/Division: | Faculty of Industrial Sciences And Technology Center for Mathematical Science |
Depositing User: | Dr. Noratikah Abu |
Date Deposited: | 01 Nov 2022 08:23 |
Last Modified: | 01 Nov 2022 08:23 |
URI: | http://umpir.ump.edu.my/id/eprint/35122 |
Download Statistic: | View Download Statistics |
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