Time Series Analysis for Modelling and Forecasting Tourist Arrivals in Sri Lanka
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Date
2019
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Uva Wellassa University of Sri Lanka
Abstract
For centuries, Sri Lanka has been a popular place for foreign travelers. Tourism and Hospitality industry is one of major source of income in Sri Lanka which directly contribute to Country’s economy. Therefore, understanding and forecasting the upcoming trends of tourist’s arrivals is really important and it will be beneficial and important for stakeholders and interesting parties of the country. The purpose of this research study is to investigate and forecast the tourist’s arrival in Sri Lanka using time series modelling based on past available data from January 1995 to January 2018. The data has been analyzed based on the two sets: pre-war (1995-2010) and post-war (2010-2018) due to major variations in the Tourism and Hospitality industry after the civil war in 2009 in Sri Lanka. In this study Auto Regressive Integrated Moving Average (ARIMA) method and Multiplicative Decomposition Approach (MDA), are proposed for forecasting. When the forecasts from these models were validated, post-war data has more accurate results having low mean absolute percentage error for MDA than ARIMA approach. Furthermore, Comparison between predicted and actual data also confirmed that the MDA model from post-war data represent high predictive ability.
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Tourism Management, Hospitality Management, Human Resource Development