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Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods

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dc.contributor.author Diunugala, H.P
dc.contributor.author Mombeuil, C
dc.date.accessioned 2022-01-24T04:43:51Z
dc.date.available 2022-01-24T04:43:51Z
dc.date.issued 2020
dc.identifier.citation Diunugala, H.P., Mombeuil, C.(2020). Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods, Journal of Tourism, Heritage & Services Marketing, Vol. 6, No. 3, 2020, pp. 3-13 en_US
dc.identifier.uri http://dr.lib.sjp.ac.lk/handle/123456789/9751
dc.description.abstract Purpose: This study compares three different methods to predict foreign tourist arrivals (FTAs) to Sri Lanka from top-ten countries and also attempts to find the best-fitted forecasting model for each country using five model performance evaluation criteria. Methods: This study employs two different univariate-time-series approaches and one Artificial Intelligence (AI) approach to develop models that best explain the tourist arrivals to Sri Lanka from the top-ten tourist generating countries. The univariate-time series approach contains two main types of statistical models, namely Deterministic Models and Stochastic Models. Results: The results show that Winter’s exponential smoothing and ARIMA are the best methods to forecast tourist arrivals to Sri Lanka. Furthermore, the results show that the accuracy of the best forecasting model based on MAPE criteria for the models of India, China, Germany, Russia, and Australia fall between 5 to 9 percent, whereas the accuracy levels of models for the UK, France, USA, Japan, and the Maldives fall between 10 to 15 percent. Implications: The overall results of this study provide valuable insights into tourism management and policy development for Sri Lanka. Successful forecasting of FTAs for each market source provide a practical planning tool to destination decision-makers. en_US
dc.language.iso en en_US
dc.publisher Journal of Tourism Heritage & Services Marketing en_US
dc.subject foreign tourist arrivals, winter’s exponential smoothing, ARIMA, simple recurrent neural network, Sri Lanka en_US
dc.title Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods en_US
dc.type Article en_US


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