Original Research Article
Year: 2016 | Month: November | Volume: 3 | Issue: 11 | Pages: 69-79
Patterns of Tourist Arrivals to Sri Lanka from Asian Countries
Konarasinghe Mudiyanselage Udaya Banda Konarasinghe
Institute of Mathematics and Management, Nugegoda. Sri Lanka.
ABSTRACT
The pattern recognition is the key to success in time series forecasting. This study was focused on pattern recognition of tourist arrivals from leading Asian countries to Sri Lankan tourism market. Monthly time series data from January 2008 to December 2014 were used in this study. The regions selected for the study were the top five in market position in the Asian region. They are; India, Maldives, China, Japan, and Pakistan. Descriptive statistics, Time Series plots and Auto-Correlation Functions (ACF) were used for pattern identification and one way- Analysis of Variance (ANOVA) was used for mean comparison of tourist arrivals from selected countries. The average arrivals from India and Maldives were 13036 and 4000 consecutively. A number of arrivals from India were normally distributed. Data series of all five were non-stationary. There is a significant difference of tourist arrival from India and Maldives compared to other Asian countries. The arrivals of India, Maldives, Japan and Pakistan show the seasonal patterns. It is recommended to test Moving Average methods, Exponential Smoothing techniques, Holt’s Winter’s three parameter models, Decomposition techniques, Seasonal Auto Regressive Integrated Moving Average (SARIMA), Circular Model, linear and non-linear trend models for forecasting arrivals in short term and long term.
Keywords: Auto-Correlation Function; Analysis of Variance; Non-stationary.
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