Model-Based Analysis of International Tourist Flow to Sri Lanka

Sri Lanka entered the international tourism market in the late 1960s. Forecasting of international tourist arrivals to Sri Lanka is immensely important and it’s a timely requirement. Hence, finding the mostappropriate forecasting technique is essential. In view of the above, objective of the study is to forecasting international tourism flows to Sri Lanka. Annual data on arrivals obtained from annual statistical report2013 of Sri Lanka Tourist Development Authority from 1968 to 2013. Moving Average smoothing model, Single Exponential Smoothing (SES) model and Double Exponential Smoothing (DES) models are tested o monthly arrivals. The best fitting model was selected by comparing Mean Absolute Percentage Errors (MAPE). Results revels that the single Moving Average of order 2 (MA 2) model has the least MAPE whichis 19%. SES of Alpha 0.9 has the least MAPE which is 17%.But the residuals were not normally distributed.Double Exponential of Alpha 0.8, Beta 0.9 and Alpha 0.9, Beta 0.9 has the least MAPE which is 17%. In these model residuals were normally distributed. Double Exponential of Alpha 0.8, Beta 0.9 and Alpha 0.9,Beta 0.9 are the suitable models for forecasting international tourist arrivals to Sri Lanka. Smoothin techniques can be used only for forecasting one period ahead. Therefore, it is recommended to test various trend models on forecasting tourist arrivals.KEYWORDS: Smoothing techniques, MAPE, Double Exponential Smoothin

Determinants of Demand for International Tourism Industry in Sri Lanka

From 1968 to 1982 Sri Lankan tourism industry shows continuous growth ofarrivals and then it fluctuates till 2009 as a result of the deteriorated security situation ofthe country, due to the war. Since the end of the war in May 2009, again it showsdramatic improvement. By the end of the year 2011, Sri Lanka has recorded the highestever total of tourist arrivals, but total income from tourism industry does not tally withthe boom as there is an income drop from 2010 to 2011. As such it is of vitalimportance to ascertain as to why the income dropped.Demand of international tourist to Sri Lanka is the dependent variable andindependent variables are transportation cost, income of tourist, prices of the productsand services, attraction of the country, facilities and infrastructure and security of thecountry. Both primary and secondary data are used in the study.Descriptive statistics reveals that about three fourth of the tourists are newclients who have come to Sri Lanka for the first time. More than 99% of all therespondents are satisfied about the tour; however some of the Sri Lankan attractions arenot promoted properly. Hence right strategies have to be in place to make Sri Lanka apopular tourist designation on the one hand, and to generate more income for theindustry on the other. However the results of the study have to be confirmed by thesignificance testing which are ongoing.Key words: Demand, Variable, Significance, Testin

Model-Based Analysis of International Tourist Flow to Sri Lanka

Sri Lanka entered the international tourism market in the late 1960s. Forecasting of international tourist arrivals to Sri Lanka is immensely important and it’s a timely requirement. Hence, finding the mostappropriate forecasting technique is essential. In view of the above, objective of the study is to forecasting international tourism flows to Sri Lanka. Annual data on arrivals obtained from annual statistical report2013 of Sri Lanka Tourist Development Authority from 1968 to 2013. Moving Average smoothing model, Single Exponential Smoothing (SES) model and Double Exponential Smoothing (DES) models are tested o monthly arrivals. The best fitting model was selected by comparing Mean Absolute Percentage Errors (MAPE). Results revels that the single Moving Average of order 2 (MA 2) model has the least MAPE whichis 19%. SES of Alpha 0.9 has the least MAPE which is 17%.But the residuals were not normally distributed.Double Exponential of Alpha 0.8, Beta 0.9 and Alpha 0.9, Beta 0.9 has the least MAPE which is 17%. In these model residuals were normally distributed. Double Exponential of Alpha 0.8, Beta 0.9 and Alpha 0.9,Beta 0.9 are the suitable models for forecasting international tourist arrivals to Sri Lanka. Smoothin techniques can be used only for forecasting one period ahead. Therefore, it is recommended to test various trend models on forecasting tourist arrivals.KEYWORDS: Smoothing techniques, MAPE, Double Exponential Smoothin