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DC Field | Value | Language |
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dc.contributor.author | Nagendrakumar, N. | - |
dc.contributor.author | Lokeshwara, A.A. | - |
dc.contributor.author | Gunawardana, S.A.D.C.K. | - |
dc.contributor.author | Kodikara, U.P. | - |
dc.contributor.author | Rajapaksha, R.W.N.H. | - |
dc.contributor.author | Rathnayake, K.R.M.C.S. | - |
dc.date.accessioned | 2022-03-14T09:33:28Z | - |
dc.date.available | 2022-03-14T09:33:28Z | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 2682-695X | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/1622 | - |
dc.description.abstract | The Sri Lankan tourism industry contributes significantly to economic development through diversified mechanisms of revenue generation and for creation of employment opportunities. The tourism industry is volatile and easily affected by man-made or natural catastrophes: terrorism, financial crisis, and tsunamis. The racial dispute among Sri Lankan government forces and Liberation Tigers of Tamil Elam, which started in the 1980s spanned over thirty years and adversely affected the development of the tourism sector. However, with the conclusion of the ethnic strife in 2009, tourism started to boom. The objective is to estimate and forecast tourist arrivals for the tourism industry from August 2021 to August 2025. This study used monthly tourist arrivals from January 2000 to July 2021 to predict values for August 2021 to August 2025 and evaluates against the actual, based on the number of visitor arrivals. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) was used to model the visitor arrivals to Sri Lanka by evaluating the study period and have applied the Standard ARIMA model to achieve the research purpose. Monthly tourist arrival data obtained from the Sri Lankan Tourism Development Authority and diagnostic test statistics, including autocorrelation and partial correlation, were used to examine the parameters of ARIMA. The results revealed civil was has impacted on tourist arrivals and was further noted that terrorism affected tourist arrivals negatively. In addition, the findings showed that the forecasted tourist arrivals were substantially less than the actual, which indicated that the Sri Lankan tourism industry rebounced shortly after the three-decade long civil war. Hence, this analysis highlights the potential of the Sri Lankan tourism industry to recover rapidly from shock events. Moreover, it is advantageous for policymakers, academia, society, and the government of Sri Lanka to set up the national tourism framework and also align the crisis management process effectively. | en_US |
dc.language.iso | en | en_US |
dc.publisher | SLIIT Business School | en_US |
dc.relation.ispartofseries | Vol. 01, No. 02;pp. 95-120 | - |
dc.subject | Autoregressive Integrated Moving Average | en_US |
dc.subject | Civil war | en_US |
dc.subject | Tourism industry performance | en_US |
dc.subject | Tourist Arrivals | en_US |
dc.title | Modelling and Forecasting Tourist Arrivals in Sri Lanka | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.54389/GKED9337 | en_US |
Appears in Collections: | 14th SLIIT Business School Students’ Research Conference (SBSSRC 2021) Research Papers - Dept of Business Research Papers - SLIIT Staff Publications SLIIT Business Review |
Files in This Item:
File | Description | Size | Format | |
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Volume 01 No 02 SBS Review_2022_03_12_5.pdf Until 2050-12-31 | 453.64 kB | Adobe PDF | View/Open Request a copy | |
Volume 01 No 02 SBS Review_2022_03_12_Intro.pdf | 171.22 kB | Adobe PDF | View/Open |
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