Forecasting international tourist arrivals in formulating tourism strategies and planning: The case of Sri Lanka

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Thushara, SC
Su, JJ
Bandara, JS
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2019
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Abstract

In some developing countries, tourism-led growth strategy has been used to accelerate growth, generate employment opportunities and increase foreign exchange earnings. To maximise benefits from the tourism industry, appropriate policy decisions, infrastructure development and conducive business environments need to be developed. For that, accurate forecasting of international arrivals is vital. Tourism has been identified, as a driving force of post-war economic development in Sri Lanka. The main purpose of this study is to develop accurate forecasting models for total international arrivals in Sri Lanka and its top 10 source countries using SARIMA method. Monthly data from January 1984 to December 2016 were used as the training sample and data from January 2017 to December 2017 were used to evaluate the accuracy of the selected models. Results demonstrate that (a) achieving Sri Lankan Government’s forecast of four million tourist arrivals by 2020 is highly unlikely, (b) accurate forecasting is necessary for tourism strategies and planning, and (c) the SARIMA method provides accurate forecasts in the presence of seasonality. Finally, the findings in this study will be useful for government agencies and private establishments in the industry in their policymaking, designing promotional campaigns, and planning infrastructure.

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Cogent Economics and Finance

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7

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1

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© 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Commerce, management, tourism and services

Tourism

Tourism forecasting

Tourism management

Tourism marketing

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Thushara, SC; Su, JJ; Bandara, JS, Forecasting international tourist arrivals in formulating tourism strategies and planning: The case of Sri Lanka, Cogent Economics and Finance, 2019, 7 (1), pp. 1699884

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