Malaysian tourism interest forecasting using Nonlinear Auto-Regressive (NAR) model

Author

Yassin, I.M. ; Zabidi, Azlee ; Salleh, M.K.M. ; Khalid, Noor Elaiza Abd

Author_Institution

Fac. of Electr. Eng., Univ. Teknol. Mara, Shah Alam, Malaysia

fYear

2013

fDate

19-20 Aug. 2013

Firstpage

32

Lastpage

36

Abstract

Tourism is an important industry for many nations including Malaysia. A tourism forecasting model is necessary in order to optimize resource allocation to maximize facilities and services to tourists. This paper proposes a Nonlinear AutoRegressive (NAR) model to forecast Malaysian tourism influx based on the volume of internet searches of the keyword `tourism Malaysia´. The volume of internet searches has been proven to correspond strongly with tourism in a particular area. Validation and fitting tests indicate valid model with a modest data fit ability.

Keywords

Internet; autoregressive processes; forecasting theory; information retrieval; travel industry; Internet search volume; Malaysian tourism influx forecasting; Malaysian tourism interest forecasting; NAR model; facilities maximization; nonlinear autoregressive model; resource allocation optimization; service maximization; tourism Malaysia keyword; tourists; Forecasting; Google; Internet; Market research; Predictive models; Testing; Training; Google Trends; Nonlinear Auto-Regressive (NAR) model; Tourism; forecasting; system identification;

fLanguage

English

Publisher

ieee

Conference_Titel

System Engineering and Technology (ICSET), 2013 IEEE 3rd International Conference on

Conference_Location

Shah Alam

Print_ISBN

978-1-4799-1028-1

Type

conf

DOI

10.1109/ICSEngT.2013.6650138

Filename

6650138