Forecasting Tourist Arrival in the Province of Surigao del Sur, Philippines using Time Series Analysis

Ruby Mae Maliberan - Surigao del Sur State University, Tandag City, Philippines


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.3.3.268

Abstract


The study attempted to forecast the number of tourist arrival in the province of Surigao del Sur using the historical monthly tourist arrival data from 2012-2016 using three time series. Findings showed that the tourist arrival in the province is likely to be increasing. As more foreign and local tourist arrivals are expected as a result of forecast model. Furthermore, it showed that there was a long term increasing trend of the tourist arrival in the province. Results revealed that the Mean Absolute Percentage Error (MAPE) of the forecasted tourist arrival data yielded an error of 11 % which means that predicted data is closer to the actual data. Based on the findings of the study, the researcher recommends that this study can be adapted by other Tourism Office of CARAGA, Philippines.

 


Keywords


Forecasting;Multiplicative Decomposition;Regression;Tourist arrival;Time Series Analysis

Full Text:

PDF

References


P. Esmaquel, Signal 3 over Surigao del Sur, Rappler. Retrieved 2 March 2018, from https://www.rappler.com/nation/specialcoverage/weather-alert/17163-signal-no-3-over-surigao,-5-others, 2013.

K. Canedo, Tourist Arrival in Davao City down by 19 percent. SunStar Davao. Retrieved 1 March 2018, from http://www.sunstar.com.ph/davao/local news/2017/07/26/touristarrivals-davao-city-down-19-555023, 2017.

K. Mansor, and W. Ishak, Forecasting Tourist Arrivals to Langkawi Island Malaysia, Cross-Cultural Management Journal, vol. 17, no. 1, 2015.

X. Agaraj, and M. Murati, Tourism an Important Sector of Economy Development. Annals of The Constantin University Of Economy Series, vol. 25, no. 3, pp. 755-760, 2009.

C. Bunghez, The Importance of Tourism to a Destination's Economy. Journal of Eastern Europe Research In Business & Economics, vol. 2, no. 3, pp. 105-110, 2016.

S. Shakya, An Empirical Research on Monthly Tourism Forecasting for Nepal. Research Gate, vol. 28, no. 2, pp. 205-210, 2016.

R. Jimenez, ASEAN Tourism Strategic Plan, 2014-2025 [Ebook]. Quezon City: Department of Tourism (DOT), 2014.

R. Paje, National Ecotourism Strategy & Action Plan 2013-2022 [Ebook]. Quezon City: Department of Tourism (DOT), 2014.

B. Marcos, The Importance of Tourism for the Philippines. Bongbong Marcos. Retrieved 1 March 2018, from https://www.bongbongmarcos.com/news/post/the-importance-oftourism-for-the-philippines/, 2010.

H. Song, and G, Li, Tourism Demand Modelling and Forecasting – A Review of Recent Research. Tourism Management, vol. 29, pp. 203-220, 2008.

S. Goyal, and M. Kumar, Towards Tourism Demand Forecasting Methods Elements. Research Notes In Information Science (RNIS), vol. 1, no. 4, 2013.

D. Gounopoulos, D. Petmezas, and D. Santamaria, Forecasting Tourist Arrivals in Greece and the Impact of Macroeconomic Shocks from the Countries of Tourists’ Origin. Annals of Tourism Research, vol. 39, no. 2, pp. 641-666, 2012.

H. Song, G. Li, S. Witt, and G. Athanasopoulos, Forecasting Tourist Arrivals using Time Varying Parameter Structural Time Series Models. International Journal of Forecasting, vol. 27, no. 3, pp. 855-869, 2011.

S. Shakya, An Empirical Research on Monthly Tourism Forecasting for Nepal. Research Gate, 28(2), 205-210. 2016.

D. C. Montgomery, C. Jennings, and M. Kulahci, Introduction to Time Series Analysis and Forecasting. WILEY, 2015.

E. Kim, A. Sungil, and H. Kim, A New Metric of Absolute Percentage Error for Intermittent Demand Forecasts. International Journal of Forecasting, vol. 32, no. 3, pp. 669-679, 2016.

R. Tofallis, A Better Measure of Relative Prediction Accuracy for Model Selection and Model Estimation, Journal of the Operational Research Society, vol. 66, no. 8, pp.1352-1362, 2015.