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Time Series Patterns Of Tourist Arrivals To Sri Lanka
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Book Synopsis Time Series Patterns of Tourist Arrivals to Sri Lanka by : Udaya Konarasinghe
Download or read book Time Series Patterns of Tourist Arrivals to Sri Lanka written by Udaya Konarasinghe and published by . This book was released on 2016 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study focused on pattern recognition of tourist arrivals to Sri Lanka from various regions in the world. Monthly time series data from January 2008 to December 2014 are used in this study. The regions selected for the study were the top four in market position. They are; Asia, Western Europe, Eastern Europe and the Middle East. 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 regions. The average arrivals of Asia and Western Europe are the highest 29361 and 25982 respectively. There is no significant difference between these two regions. Eastern Europe and the Middle East have 5866 and 4300 of average respectively. Arrivals from Asia, Western Europe, and Eastern Europe were not normally distributed, all were positively skewed. Data series of all four regions were non-stationary. There is a significant difference of tourist arrival from Asian and Western Europe compared to other regions. It is recommended to test Moving Average Methods, Exponential Smoothing techniques, Decomposition techniques, linear and non-linear trend models and Circular model for forecasting arrivals.
Book Synopsis Decomposition Techniques on Forecasting Tourist Arrivals from Western European Countries to Sri Lanka by : Udaya Konarasinghe
Download or read book Decomposition Techniques on Forecasting Tourist Arrivals from Western European Countries to Sri Lanka written by Udaya Konarasinghe and published by . This book was released on 2017 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: The forecasting tourist arrival is an essential discipline in planning, resource management, and other decision-making processes in micro and macro level. It facilitates to ensure the sustainable development by minimizing the risk to all aspects. There is a growth of arrivals from all the regions to Sri Lanka. Increasing of tourist arrivals could cause a positive or negative effect on the country. To get the maximum benefits from the positive impacts and to overcome the negative impacts, it is vital to forecast arrivals. This study focuses on identifying the highest tourist producing Western European countries and to forecast the arrivals from them. Monthly tourist arrival data from the UK, Germany, France, Netherland, and Italy for the period of, January 2008 to December 2014 was obtained from Sri Lanka Tourism Development Authority (SLTDA). Time Series plots and AutoCorrelation Functions (ACF) were used for pattern recognition of arrivals. It revealed that the arrivals have both trend and seasonal patterns. As such, the Decomposition Techniques were tested for forecasting arrivals. The Residual plots and the Anderson-Darling test were used as the goodness of fit tests in model validation. The residuals of both; additive and multiplicative models for all the countries were found normally distributed and independent. The best fitting model was selected by comparing the relative measurements of errors and the absolute measurements of errors. Measurement errors of all the fitted models were satisfactorily small. Among them, the models with least errors were selected for forecasting. It is concluded that the Additive Decomposition models are the most suitable models for forecasting arrivals from Western European countries. However, arrivals show wave-like patterns with the trend. The Circular Model is a newly introduced technique for modeling wave-like patterns. It is recommended to test the Circular Model on de-trended data to see whether the forecasting accuracy increases.
Book Synopsis Time Series Behaviour of Burgeoning International Tourist Arrivals in Sri Lanka by : Nisantha Kurukulasooriya
Download or read book Time Series Behaviour of Burgeoning International Tourist Arrivals in Sri Lanka written by Nisantha Kurukulasooriya and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research provides a comprehensive study of time series behavior of the postwar international tourist arrivals. The empirical study is carried out based on outbound tourist arrivals from all origins that create a demand for tourism in Sri Lanka. The time span is covers from July 2009 to June 2013. In the modeling exercise, classical time series decomposition approach is employed. Mann-Kendall test evidenced for existing linear trend while Kruskal-Wallis tests confirmed the seasonality in tourism. Thus, linear trend component and seasonal fluctuations are the two prominent components whereas multiplicative model is comparatively the most accurate model in forecasting. Tourism sector is booming after the war in Sri Lanka with an approximate increase of 1200 tourists per month. Seasonality accounts for over 85 percent of seasonal variation in arrivals and the seasonal pattern which prevailed within the war period has considerably changed to a new behaviour. According to the Gini coefficient, seasonality reached to an equilibrium after the war and hence June, July and October are tourism months. Since the seasonality is a prominent component in international tourist arrivals, the results of the study recommend necessary arrangements to minimize the negative impact of seasonality in arrivals in respective months. Therefore, different categories of travellers should be focused in low demand periods to alleviate negative impact of seasonality.
Book Synopsis Sama Circular Model on Forecasting Tourist Arrivals to Sri Lanka by : W. G. Samanthi Konarasinghe
Download or read book Sama Circular Model on Forecasting Tourist Arrivals to Sri Lanka written by W. G. Samanthi Konarasinghe and published by . This book was released on 2019 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Circular Model (CM) is univariate statistical technique, which is applied in modeling wave like patterns. Development of the CM was based on; Newton's Law of Circular Motion, Fourier Transformation and Multiple Regression Analysis. Most important property of the CM is that; the model is capable in capturing both seasonal and cyclical patterns of a time series. However, applicability of the CM is restricted to trend free series. As such, the differencing technique was used to mitigate the limitation of the CM. The improved Circular Model, named as the "Sama Circular Model (SCM)” is tested on forecasting tourist arrivals to Sri Lanka. Time Series plots were used for pattern recognition. The Auto Correlation Functions of residuals and Ljung-Box Q statistics (LBQ) were used to test the independence of residuals. The Anderson Darling test was used to test the normality of residuals. Forecasting ability of the models was assessed by Mean Square Error and Mean Absolute Deviation. Forecasting ability of SCM was compared with the Decomposition models and Seasonal Auto Regressive Moving Average models. It is concluded that the SCM is capable in forecasting tourist arrivals to Sri Lanka and the SCM is superior to the other tested models for the purpose. It is recommended to test the SCM for various fields of study, such as; Agriculture, Meteorology, Economics, Finance etc. for optimum benefits.
Book Synopsis Modeling and Predicting Foreign Tourist Arrivals to Sri Lanka: A Comparison of Three Different Methods by : Hemantha Premakumara Diunugala
Download or read book Modeling and Predicting Foreign Tourist Arrivals to Sri Lanka: A Comparison of Three Different Methods written by Hemantha Premakumara Diunugala and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Forecasting Employment of Tourism Industry in Sri Lanka by : Udaya Konarasinghe
Download or read book Forecasting Employment of Tourism Industry in Sri Lanka written by Udaya Konarasinghe and published by . This book was released on 2019 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tourism industry in Sri Lanka is growing over the recent past; increasing arrivals from various destinations. As a result, the employment in the industry also shows a rapid growth, but there were very few attempts in forecasting employment in the tourism industry in Sri Lanka. Hence, the objective of the study was to find out the suitable forecasting techniques for total employment of tourism industry in Sri Lanka. Annual employment data for the period of 1970 to 2015 were obtained from the Sri Lanka Tourism Development Authority (SLTDA). Karl Pearson's correlation used to test the correlation between total employment and tourist arrivals. Time series plots used for pattern identification. Simple Regression Model (SRM) and Auto Distributed Lag Model (ADLM) tested for forecasting. The Anderson-Darling test used to test the normality of data and residuals. Ljung-Box Q test, Auto-Correlation Functions (ACF) and Durbin-Watson (DW) test used to test the independence of residuals. Augmented Dickey-Fuller (ADF) test used to test the stationary of the series. Forecasting ability of the models was assessed by both relative and absolute measurements of errors. The SRM was not successful, but the ADLM satisfied the validation criterion. Both relative and absolute measurements of ADLM were very low. Hence, the ADLM is recommended for forecasting total employment of tourism industry in Sri Lanka. The results of this study will be facilitating for decision making and various strategy development related to overcome the surplus and shortfall of employment. It will be useful for workforce planning in both public and the private sector in the tourism industry. It is useful for developing various training programs such as workshops, academic and professional courses related to hospitality management. Further, the finding of the study can be used to assess the economic benefits to the host community in various tourism areas in Sri Lanka.
Book Synopsis Forecasting International Tourism Income of Sri Lanka by : Udaya Konarasinghe
Download or read book Forecasting International Tourism Income of Sri Lanka written by Udaya Konarasinghe and published by . This book was released on 2019 with total page 3 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growth of the tourism industry in Sri Lanka shows the historical development in mainly in two ways. That is the growth of tourist arrivals and income.Tourism impact on the economy of Sri Lanka, which rely heavily on foreign exchange earnings. This has been a general interest of the government. Therefore government needs reliable forecasting to cope with uncertain situations and developing sound strategies to maintain the growth of tourism industry. This study was focused to identify suitable trend model for forecasting international tourism income of Sri Lanka. Monthly income data from 2009 to 2013 were obtained from statistical reports of 2012 and 2013 of Sri Lanka Tourism Development Authority (SLTDA). Study concern the period of post war, which is after year 2009. Model fitting was done by utilizing data from January 2009 to April 2012 and data from May 2012 to May 2013 utilized for model verification. Four trend models were tested with log transformation including one linear and three non linear models. Residual plots and Anderson Darling tests for residuals were used as model validation criterion. Forecasting ability of the models was assessed by considering Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE) and Mean Absolute Deviation (MAD). Box and whisker plot showed no outliers in the data set. Results revealed that Quadratic Trend Model has least MAPE's in model fitting and verification: 0.90% and 1.12 % respectively. MAD and MSE also confirmed the smallest deviation compared with other trend models. Residual plots and Anderson Darling test confirmed the normality of residuals. Also residuals Vs fits confirmed the independence of residuals. It was concluded that the Quadratic Trend Model with log transformation is suitable for forecasting international tourism income in Sri Lanka. It is recommended to try other time series techniques namely decomposition techniques, Auto Regressive Integrated Moving Average (ARIMA) models etc. to capture the seasonal behavior of the series.
Book Synopsis Forecasting Foreign Guest Nights in Hill Country of Sri Lanka by : K.M.U.B Konarasinghe
Download or read book Forecasting Foreign Guest Nights in Hill Country of Sri Lanka written by K.M.U.B Konarasinghe and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past years, tourist arrivals to Sri Lanka show increasing trend. Hill Country is one of the highest occupied regions which are located in the Central province of Sri Lanka. Hill country consist many UNESCO world heritage sites namely; Kandy city, Knuckles Mountain Range, Adam's Peak and Horton Plains. The natural beauty and the cultural value increase the demand for international tourist for Hill country. It creates high demand for accommodation of all types of hotels in the region. An increasing occupancy will increase the demand for accommodation; hence the competition in hotel industry also will increase. Therefore the hotel industry should adopt various management practices to maximize profits and optimize operations. This can be achieved by accurate forecasting of occupancy by tourist. But it was hard to find attempts of forecasting occupancy guest nights in Hill Country of Sri Lanka. On the view of the above, the study was focused on forecasting occupancy guest nights of international tourist in Hill Country of Sri Lanka. Monthly data of foreign guest nights for the period of January 2008 to December 2016 were obtained from annual reports of 2008-2016 published by SLTDA. Time series plots and Auto-Correlation Function (ACF) were used for pattern identification. The Decomposition, SARIMA, and Holt-Winters models were tested for forecasting. The Anderson-Darling test, ACF, and Ljung-Box Q (LBQ)-test were used to test the validation criterion and fit the model. Forecasting ability of the models was assessed by both relative and absolute measurements are very low in model fitting. Decomposition and Holt-Winters models do not satisfy the model validation criterion. But the relative and absolute measurements of errors of the model ARIMA(2,0,1)(2,1,1)4 are very low in model fitting. The Anderson-Darling Normality test confirmed the normality of residuals; the LBQ- test confirmed the independence of residuals (h=0). The results of the study concluded that the SARIMA is suitable for forecasting occupancy guest nights in Hill Country of Sri Lanka.The results of this study can be used for planning to manage and controlling the business operations of the tourism industry in Hill Country of Sri Lanka. Planning new products to create demand, the volume of products can decide suitable periods for promotional campaigns can be decided with the help of the results of this study. The decomposition and Holt's Winters three parameter approaches were not successful in this study, while, the SARIMA was highly successful. However, a wave-like pattern may contain both seasonal and cyclical variation, but the SARIMA is unable to separate them. The Circular Model is a recently developed univariate forecasting technique, which can be used to capture both seasonal and cyclical patterns. Therefore, it is recommended to test the Circular Model for de-trended data, in order to see whether it improves the forecasting.
Book Synopsis Applied Time Series by : T. M. J. A. Cooray
Download or read book Applied Time Series written by T. M. J. A. Cooray and published by . This book was released on 2008 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Applied Time Series: Analysis and Forecasting provides the theories, methods and tools for necessary modeling and forecasting of time series. It includes a complete theoretical development of univariate time series models with each step demonstrated with an analysis of real time data series. The result is clear presentation, quantified subjective judgment derived from selected methods applied to time series observations."--Jacket
Book Synopsis Improved Circular Model on Forecasting Arrivals from Western European Countries to Sri Lanka by : W. G. S. Konarasinghe
Download or read book Improved Circular Model on Forecasting Arrivals from Western European Countries to Sri Lanka written by W. G. S. Konarasinghe and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Circular Model (CM) is a newly joined member to the family of Univariate Statistical Models. Development of the CM was based on; Newton's Law of Circular Motion, Fourier Transformation and Multiple Regression Analysis. Most important property of the CM is that; the model could be applied for either stationary or non-stationary series. Further, the model is capable in capturing both seasonal and cyclical patterns of a time series. However, the applicability of CM is restricted to trend free series. As such, it was intended to improve the CM, by using the differencing technique. The Improved Circular Model; named as, "Sama Circular Model, is tested on tourist arrival data from Western European countries to Sri Lanka. Monthly arrival data for the period of April 2008 to December 2016 were used for the analysis. Time Series plots and Auto Correlation Functions were used for pattern recognition. The Auto Correlation Functions (ACF) of residuals and Ljung-Box Q statistics (LBQ) were used to test the independence of residuals. The Anderson Darling test was used to test the normality of residuals. Forecasting ability of the models was assessed by Mean Square Error (MSE) and Mean Absolute Deviation (MAD). Forecasting ability of Sama Circular Model (SCM) was compared with the Decomposition techniques and Seasonal Auto Regressive Moving Average (SARIMA). It is concluded that the SCM is capable in forecasting arrivals from Western European countries and the SCM is superior to the other tested models. It is recommended to test the SCM for different fields; Agriculture, Meteorology, Economics, Financial markets and many more.
Book Synopsis Seasonality in Tourism by : Tom Baum
Download or read book Seasonality in Tourism written by Tom Baum and published by Routledge. This book was released on 2001-12-07 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seasonal variation in demand is a reality for most tourism destinations. This work provides a balanced overview of the evidence and issues relating to tourism seasonality using European, North American and Pacific Rim cases and research evidence.
Book Synopsis Annual Statistical Report by : Ceylon Tourist Board
Download or read book Annual Statistical Report written by Ceylon Tourist Board and published by . This book was released on 1980 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Short-Term Forecasting of Tourist Arrivals to Sri Lanka from Asian Region by : Udaya Konarasinghe
Download or read book Short-Term Forecasting of Tourist Arrivals to Sri Lanka from Asian Region written by Udaya Konarasinghe and published by . This book was released on 2017 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Tourism Demand Modelling and Forecasting by : Haiyan Song
Download or read book Tourism Demand Modelling and Forecasting written by Haiyan Song and published by Routledge. This book was released on 2000 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook for a graduate or final-year undergraduate course in tourism studies that might also find interest among researchers and practitioners who want to apply recent developments in econometric modeling and forecasting to tourism demand analysis. Song and Witt (both management in the service sector, U. of Surrey, Britain) begin with the fundamentals of tourism demand analysis, and the problems of traditional modeling and forecasting. Then they explore the general- to-specific approach, the time-varying parameter model, and the panel- data approach. Annotation copyrighted by Book News, Inc., Portland, OR
Book Synopsis Forecasting with Univariate Box - Jenkins Models by : Alan Pankratz
Download or read book Forecasting with Univariate Box - Jenkins Models written by Alan Pankratz and published by John Wiley & Sons, Incorporated. This book was released on 1983-08-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.
Book Synopsis Information and Communication Technologies in Tourism 2017 by : Roland Schegg
Download or read book Information and Communication Technologies in Tourism 2017 written by Roland Schegg and published by Springer. This book was released on 2017-01-03 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art research into the application of information and communication technologies to travel and tourism. The range of topics covered is broad, encompassing digital marketing and social media, mobile computing and web design, semantic technologies and recommender systems, augmented and virtual reality, electronic distribution and online travel reviews, MOOC and eLearning, eGovernment, and the sharing economy. There is a particular focus on the development of digital strategies, the impact of big data, and the digital economy. In addition to the description of research advances and innovative ideas, readers will find a number of informative industrial case studies. The contents of the book are based on the 2017 ENTER eTourism conference, held in Rome. The volume will be of interest to all academics and practitioners who wish to keep abreast of the latest developments in eTourism.
Book Synopsis Dynamic Capabilities Between Firm Organisation and Local Systems of Production by : Riccardo Leoncini
Download or read book Dynamic Capabilities Between Firm Organisation and Local Systems of Production written by Riccardo Leoncini and published by Routledge. This book was released on 2007-12-21 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Changes in technology and demand require firms to learn how to continuously reshape unique and non-imitable resources and competences. A firm‘s capacity to achieve this is captured by the concept of dynamic capabilities. This book offers an analysis of how firms manage to reconfigure their pool of idiosyncratic resources, skills and competencies to
