Modeling Tourist Flows to Indonesia and Malaysia

Summary

The purpose of this study was to examine the major factors that influence the flow patterns of tourists from six important tourist-generating countries to Indonesia and Malaysia. The primary determinants included in the demand models were income, prices, and time trend. Two models that employed different indicators for the price variable were estimated; one with exchange rates in addition to relative prices, whereas the other included only an exchange rate adjusted-relative price variable. Annual time-series data covering the period 1980 to 1997 were used for estimation. The results generally indicated that the factors provide reasonably good explanations for the demand for Indonesian and Malaysian tourism. The measure of thejoint effect of the changes in exchange rates and relative prices also seems to be a better indicator for the price variable for both destination countries. The study has important marketing implications for the tourism industries in Indonesia and Malaysia.     

Tourism forecast combination using the CUSUM technique

Forecast combination in tourism has emerged as an important research area due to its relevance to tourism decision making. This paper further investigates the impact of forecast combination on forecast accuracy by applying a quadratic programming approach to determine the combination weights for individual forecasts. In particular, we introduce three novel ideas which have not been found in previous tourism forecasting studies. First, we introduce a quality control technique, CUSUM, to determine the time for updating the weights. Next, we develop a hybrid method (using quadratic programming) to combine the forecasts to reduce forecasting errors. Thirdly, we investigate whether different performance measures yield different results. Thus, instead of comparing different weighting methods using only one performance measure, we introduce several indicators for performance comparisons. The empirical results suggest that the controlled weighting method both saves time in updating the combination weights and improves the overall performance of the combined forecasts. The method is also easy-to-implement and should be used to improve forecasting accuracy in practice.     

Econometric forecasts of tourism demand to 2005

A complete system of demand equations which was developed previously to generate forecasts of tourism imports and exports is modified to allow for destination-specific demand structures in the tourism export functions. The new model is shown to be considerably more realistic than the original one, and represents a major conceptual improvement. Furthermore, the modified complete system of demand equations yields more accurate outof-sample forecasts, across both varying time horizons and types of forecast. The new model is used to generate forecasts of tourism imports and exports for 18 countries and various major geographical areas, including the recently expanded European Union, for the period up to 2005 for different scenarios.     

The determinants of Chinese visitors to Australia: A dynamic demand analysis

Although China has progressively become an important inbound tourism market for Australia, its demand elasticities have been little studied to date. This study examines the determinants of Chinese visitors to Australia using a dynamic time-series estimator. Interesting findings include a high income elasticity as a source of the continuous doubledigit growth rates in Chinese arrivals that Australia has experienced over the past two decades, together with relatively high total trip price elasticities for both short run and long run. A trend of Chinese outbound to Australia is also identified. From a policy perspective, the results confirm that keeping a low cost of visiting Australia, both ground and travel costs, is a good strategy to secure greater numbers of Chinese tourists.     

Modelling Australian domestic and international inbound travel: a spatial–temporal approach

In this paper Australian domestic and international inbound travel are modelled by an anisotropic dynamic spatial lag panel Origin-Destination (OD) travel flow model. Spatial OD travel flow models have traditionally been applied in a single cross-sectional context, where the spatial structure is assumed to have reached its long run equilibrium and temporal dynamics are not explicitly considered. On the other hand, spatial effects are rarely accounted for in traditional tourism demand modelling. We attempt to address this dichotomy between spatial modelling and time series modelling in tourism research by using a spatial-temporal model. In particular, tourism behaviour is modelled as travel flows between regions. Temporal dependencies are accounted for via the inclusion of autoregressive components, while spatial autocorrelations are explicitly accounted for at both the origin and the destination. We allow the strength of spatial autocorrelation to exhibit seasonal variations, and we allow for the possibility of asymmetry between capital-city neighbours and non-capital-city neighbours. Significant temporal and spatial dynamics have been uncovered for both domestic and international tourism demand. For example we find strong seasonal temporal autocorrelations, significant trends and significant spatial autocorrelations at both the origin and the destination. Moreover, the spatial patterns are found to be most significant during peak holiday seasons. Understanding these patterns in tourist behaviour has important implications for tourism operators.     

A piecewise linear approach to modeling and forecasting demand for Macau tourism

In this paper, we construct and use a piecewise linear method to model and forecast, on a monthly basis, the demand for Macau tourism. Data over the period January 1991–December 2005 and a seasonally adjusted series for tourism demand are used. The study examines 4 forecasting horizons ranging from 6 to 24 months in advance. Mean absolute percentage errors and root mean square errors are adopted as criteria for evaluating the accuracy of the forecasting exercises. Finally, the forecasts of piecewise linear model are compared with those of autoregressive trend model, seasonal autoregressive integrated moving average and its arch-rival fractionally integrated autoregressive moving average models. The piecewise linear model is more accurate than the three benchmark models tested and the improvement is practically significant.     

Performance of French destinations: Tourism attraction perspectives

In this paper, we assess and compare the performance of French tourism destinations, using the Data Envelopment Analysis (DEA) two-stage procedure, where in the first stage the efficiency score are calculated, and then followed in the second stage by a bootstrapped truncated regression model. In the context of France such analysis takes an additional importance, especially as the country is expected to face a decrease in its tourism competitiveness. A discussion in terms of D-attraction and E-attraction is also proposed and policy recommendations are derived.     

Mapping time series into networks as a tool to assess the complex dynamics of tourism systems

This paper contributes to filling two gaps: i) the presence of a limited amount of studies focused on tourism demand turning points, ii) the prevalent recourse to linear models in demand analysis, disregarding the complex structure of tourism destinations. The paper uses the Horizontal Visibility Graph Algorithm, a technique able to transform a time series of observations into a network whose topology preserves some fundamental characteristics of the system examined. The empirical work focuses on Livigno, an Italian alpine destination.Findings reveal four turning points in the last 50 years; these changes are built around shifts in the origin market segments. The network's degree distribution confirms the complex structure of the destination and reconfirms the importance of non-linear models and methods for the analysis of tourism demand.     

Impact of financial/economic crisis on demand for hotel rooms in Hong Kong

The main objectives of this study are (1) to identify the factors that influence the demand for hotel rooms in Hong Kong and (2) to generate quarterly forecasts of that demand to assess the impact of the ongoing financial/economic crisis. The demand for four types of hotel room from the residents of nine major origin countries is considered, and forecasts are generated from the first quarter of 2009 to the fourth quarter of 2015. Econometric approaches are employed to calculate the demand elasticities and their corresponding confidence intervals, which are then used to generate interval demand predictions. The empirical results reveal that the most important factors in determining the demand for hotel rooms in Hong Kong are the economic conditions (measured by income level) in the origin markets, the price of the hotel rooms and the ‘word of mouth’ effect. Demand for High Tariff A and Medium Tariff hotel rooms is estimated to have experienced negative annual growth in 2009 due to the influence of the financial/economic crisis, whereas that for High Tariff B hotel rooms is thought to have grown in 2009 after having decreased in 2008. The demand for tourist guesthouse rooms is expected to be the least affected by the crisis. Overall demand is predicted to recover gradually from 2010 onwards.     

Demand elasticity estimates for New Zealand tourism

Demand elasticities for New Zealand tourism are estimated for 16 different international visitor segments. Segments are differentiated by origin, purpose of visit, and travel style. Elasticities for both international visitor arrivals and on-the-ground expenditure per arrival are estimated for each segment using time-series data. In general, on-the-ground consumption per arrival is more price sensitive than number of arrivals, and Asian market segments are found to be more price sensitive, both in terms of arrivals and on-the-ground expenditure, compared to international visitors from other regions. An application of the results is presented giving the total effect of exchange rate changes on expenditure by international visitors in New Zealand, and management implications are discussed.