Modelling and forecasting the demand for Hong Kong tourism

The main objectives of this paper are to identify the factors which contribute to the demand for Hong Kong tourism with the aid of econometric models and to generate forecasts of international tourism arrivals to Hong Kong for the period 2001–2008. The general-to-specific modelling approach is followed to model and forecast the demand for Hong Kong tourism by residents from the 16 major origin countries/regions and the empirical results reveal that the most important factors that determine the demand for Hong Kong tourism are the costs of tourism in Hong Kong, the economic condition (measured by the income level) in the origin countries/regions, the costs of tourism in the competing destinations and the ‘word of mouth’ effect. The demand elasticities and forecasts of tourism arrivals obtained from the demand models form the basis of policy formulations for the tourism industry in Hong Kong.     

Implications of a long-term increase in oil prices for tourism

It is expected that global oil prices will increase in the future. Assessing the overall economic impacts on tourism is difficult, as oil price rises will be concomitant with global changes in other commodity prices, exchange rates, and incomes. A general equilibrium perspective is therefore presented in this paper. The model couples a global general equilibrium model with a purpose-built CGE model of New Zealand, which focuses on describing tourism supply and demand in some detail. The results indicate a decrease in real gross national disposable income of 1.7% for a doubling of oil price and a 9% reduction in the real value of tourism exports. As a result of segment-specific price increases and differing income and exchange rate effects and elasticities, the reduction in demand for tourism in New Zealand by 18 segments differs substantially. The greatest reduction in demand is observed for tourists from the United Kingdom.     

Productivity growth and income in the tourism sector: Role of tourism demand and human capital investment

This paper proposes a model for the demand for tourism in the context of a developing country. The parameters of the model are a tourist sector characterised by monopolistic competition, where human capital is the main factor of production and hotels have market power. Additionally land use is marked by demand from both agricultural and tourism sectors. From the household side, a simplified OLG approach is developed to consider consumption, human activity and the number of children. A dynamic framework is therefore identified to investigate the long-run consequences of increasing labor productivity and lowering the fertility rate. If the supply-side policy leads to economic growth, the tourism led growth hypothesis is theoretically confirmed. It is concluded that an increase in labor productivity generates positive growth effects only if the demand for tourism is elastic, otherwise negative results arise.     

Immigration and international inbound tourism: Empirical evidence from Australia

Immigration can potentially influence tourism flows. However, in spite of the vast number of studies on tourism demand modelling, the immigration-tourism linkage has not received much attention in the empirical literature. This paper seeks to address this gap. A dynamic demand model is developed and estimated using data from 1980 to 2008 for the 15 main markets of Australia. The explanatory variables included are income, own price, price of a substitute destination, airfare and immigration. The estimation results empirically establish the connection between immigration and inbound tourism. The short run and long-run immigration elasticities generated are 0.028 and 0.09 respectively. Additionally this paper demonstrates that omission of prices of substitutes affects the value of the own price elasticity of demand. The results have implications for future research and for stakeholders who can improve the efficiency of their planning exercises by taking into account additional information on immigration trends.     

Monitoring tourism flows and destination management: Empirical evidence for Portugal

We propose the use of a tool recently introduced by Gayer (2010), known as the “economic climate tracer”, to analyze and monitor the cyclical evolution of tourism source markets to Portugal. Considering the period 1987–2015, we evaluate how tourism to Portugal has been affected by economic cycles. This tool is useful as it clearly illustrates the evolutionary patterns of different markets, and allows us to identify close relationships with economic fluctuations. We found that German tourism plays a leading role, since its movements are followed with delays by tourism flows from other countries, and exhibits higher resilience to shocks. Also, domestic and Spanish tourism have both displayed less irregular behaviors than tourism from other source markets. On the contrary, tourism from the Netherlands and the UK, have displayed irregular patterns, which demonstrates the urgency to diversify tourism source markets to reduce the country's vulnerability to external shocks and economic cycles.     

The price competitive position of Mediterranean countries in tourism: Evidence from the Thomson brochure

Tourism in the Mediterranean region is highly dependent on the few, large, mass market tour operators situated in the North European tourist originating countries. Price competition is intense both between the tour operators and between the Mediterranean countries themselves. This paper uses the hotel package prices listed in the Thomson summer and winter brochures to develop relative price indexes of each Mediterranean country with respect to the Mediterranean average. Indexes are developed in the 3 star, 4 star, 5 star, 7 nights and 14 nights, half-board holiday packages. The prices in the Thomson brochure can be regarded as a unified, internally consistent, set of price data, compiled by the largest UK tour operator and offered to UK tourists desiring a Thomson summer holiday. The change through time of the competitive relative price ranking of hotels, regions and countries listed in the Thomson brochure, may be regarded as an important competitive indicator by industry operators and national policy makers concerned about tourism development.     

Demand elasticities of tourism in Singapore

In 1983 the UN Economic and Social Commission for Asia and the Pacific set up a study to investigate the relationship between prices of tourist goods and tourist inflow in Singapore. The analysis was carried out on a “world” level using amalgamated data for 15 nations, also individually for each of the five major tourist-generating countries. Determinants of demand considered were - income, exchange rates, shopping and hotel prices, and local disturbances. Tourism demand is found to be highly income elastic whereas effects of prices and exchange rate movements vary between countries. Two out of three disturbance factors significantly reduced demand.     

Boat-based tourism and bottlenose dolphins in Doubtful Sound,New Zealand: The role of management in decreasing dolphin-boat interactions

Indirect non-lethal effects of wildlife tourism have the potential to compromise the long-term health of animal populations. While appropriate management of impacts is clearly necessary, such management is rarely reported to be effective. Doubtful Sound (New Zealand) has boat-based scenic cruises running year-round. This fjord is also home to an endangered population of bottlenose dolphins, a natural asset for the local tourism industry. A voluntary code of management (COM) was implemented in 2008 to alleviate vessel impacts, establishing guidelines to leave dolphin encounters to chance and restricting vessel traffic in areas of critical habitat. The frequency and duration of interactions decreased substantially since the implementation of the COM. This evidence shows that a science-based voluntary agreement has the potential to mitigate tourism impacts. Nevertheless, due to the small size of the population and its history of low calf survival, a precautionary approach is necessary to further reduce current anthropogenic impacts.     

Density tourism demand forecasting revisited

This study used scoring rules to evaluate density forecasts generated by different time-series models. Based on quarterly tourist arrivals to Hong Kong from ten source markets, the empirical results suggest that density forecasts perform better than point forecasts. The seasonal autoregressive integrated moving average (SARIMA) model was found to perform best among the competing models. The innovation state space models for exponential smoothing and the structural time-series models were significantly outperformed by the SARIMA model. Bootstrapping improved the density forecasts, but only over short time horizons.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field.     

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.     

Comovement amongst the demand for New Zealand tourism

Tourism research is replete with applications of univariate time-series decomposition techniques: multivariate frameworks have been largely ignored. In this paper, we employ a common-feature-based, multivariate trend-cycle decomposition approach to examine common trends and common cycles amongst the demand for New Zealand tourism originating in Australia, China, the US, the UK, as well as other tourism-importing countries considered as one group: Others. Upon isolating trends and cycles in tourism demand from these countries, we find evidence of strong long-term comovement: they share one common trend. We also find evidence of short-term comovement, albeit to a lesser extent: four common cycles emerge; the cyclical patterns in tourism demand from Australia, China, the US, and Others are strongly correlated.     

Towards sustainable tourism planning in New Zealand: Monitoring local government planning under the Resource Management Act

In the light of the increasing pace and scale of tourism activity in New Zealand, the concept of sustainable tourism has become a key ingredient in the nation's tourism strategy. This paper explores sustainable tourism planning in New Zealand at the level of local government, and in particular, focuses on the implementation of the Resource Management Act 1991 (RMA) as a mechanism for achieving sustainable tourism. Using the findings of a survey of Regional Councils and Territorial Local Authorities, the paper explores public sector planning responses to tourism impacts and sustainability concerns in New Zealand. The paper extends the earlier work of Page and Thorn (1997. Towards sustainable tourism planning in New Zealand: public sector planning responses. Journal of Sustainable Tourism 5(1): 59-77; 2002. Towards sustainable tourism development and planning in New Zealand: the public sector response revisited. Journal of Sustainable Tourism 10(3): 222-238), which identified major issues of concern at local council level with regard to tourism impacts and argued the need for a national vision for tourism to ensure that the RMA achieved its original goals. Since then, a national tourism strategy has been published and changes in legislation have further empowered local authorities to further progress the sustainability agenda. This paper examines these developments and the ensuing implications, concluding that significant progress has been made in developing tourism policies at the local level, but that a number of constraints and issues limit the development of New Zealand as a sustainable destination.     

The use of odd-ending numbers in the pricing of five tourism services in three different cultures

The study measured the extent to which the 1 through 9 digits were used as price endings by suppliers of five tourism services in three different cultures represented by New York City, Seoul, and Shanghai. Four results emerged. The first confirmed the hypothesis, but the other three results were contrary to expectations. First, 9 and 8-ending prices were dominant in New York City and in Shanghai, respectively. Second, these culture specific endings were complemented by the universality of the 0 and 5- digit endings of prices which were ranked first and second, respectively, in Seoul, second and third in Shanghai, and third and second in New York. Third, 9-ending prices were not used more frequently when they resulted in a lowering of the leftmost digit. Fourth, dominant cultural specific price endings were not used more frequently in lower than in higher priced tourism services.     

Forecasting turning points in tourism growth

Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.     

Modeling Tourism Demand

SUMMARY

Most of the existing studies on tourism demand forecasting apply economic models that use mathematical functions, which require many statistical assumptions and limitations. This paper presents a new approach that applies the rough sets theory to form a forecasting model for tourism demand. The objective of this research is to create patterns which are able to distinguish between the classes of arrivals in terms of volume, based upon differences in the characteristics in each arrival. The information about the arrivals was organized in an Information Table where the number of arrivals corresponds to condition attributes, and the classification was defined by a decision attribute that indicated the forecast categorical value of future arrivals. Utilizing Japanese arrivals data in Hong Kong, empirical results showed the induced decision rules could accurately forecast (86.5%) of the test data.     

Dynamic heterogeneous panel data analysis of tourism demand for Singapore

The objective of this study is to investigate tourism demand for Singapore using heterogeneous dynamic panel estimation methods. A binary variable representing the operation of Integrated Resorts (IRs), as well as income and real exchange rate, are included as determinants of tourism demand growth. Using seasonally adjusted and actual/raw quarterly data of 16 origin countries, our study shows that the pooled mran group (PMG) estimator is able to provide consistent and efficient estimates of long-run relationships between tourism demand and the determinants. The PMG results show that the long-run income (price) elasticity is positively (negatively) significant, with an elasticities range between 0.915 and 3.05 (?0.275 and ?0.34). In addition, the study reveals that the IRs contribute to tourism demand growth, especially in attracting tourists from Asia. In the long term, tourism demand by the Asian markets is less income-sensitive than that of the non-Asian counterparts.     

The impacts of international tourism demand on economic growth of small economies dependent on tourism

This paper studies the impacts on economic growth of a small tourism-driven economy caused by an increase in the growth rate of international tourism demand. We present a formal model and empirical evidence. The ingredients of the dynamic model are a large population of intertemporally optimizing agents and an AK technology representing tourism production. The model shows that an increase in the growth of tourism demand leads to transitional dynamics with gradually increasing economic growth and increasing terms of trade. In our empirical application, an econometric methodology is applied to annual data of Antigua and Barbuda from 1970 to 2008. We perform a cointegration analysis to look for the existence of a long-run relationship among variables of economic growth, international tourism earnings and the real exchange rate. The exercise confirms the theoretical findings.     

Optimal targeting of latent tourism demand segments

This paper identifies for the first time the optimal target markets employing the latent tourism demand expenditure, a novel concept in tourism literature. The study quantifies latent tourism demand between each pair of origin-destination through distinguishing by type of tourism and seasonality. It works with market shares that are estimated via a fractional regression model. Moreover, latent demand is clustered using a market segmentation approach based on a latent class regression. Finally, the optimal target markets are chosen depending on the expected latent tourism expenditure. The result has clear policy implications in terms of which markets are promoted, the optimal channels of communication and the maximum budget for each marketing campaign.     

Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data

The purpose of this study is to compare the predictive accuracy of various uni- and multivariate models in forecasting international city tourism demand for Paris from its five most important foreign source markets (Germany, Italy, Japan, UK and US). In order to achieve this, seven different forecast models are applied: EC-ADLM, classical and Bayesian VAR, TVP, ARMA, and ETS, as well as the naïve-1 model serving as a benchmark. The accuracy of the forecast models is evaluated in terms of the RMSE and the MAE. The results indicate that for the US and UK source markets, univariate models of ARMA(1,1) and ETS are more accurate, but that multivariate models are better predictors for the German and Italian source markets, in particular (Bayesian) VAR. For the Japanese source market, the results vary according to the forecast horizon. Overall, the naïve-1 benchmark is significantly outperformed across nearly all source markets and forecast horizons.     

Overcoming information asymmetry in tourism carbon management: The application of a new reporting architecture to Aotearoa New Zealand

Responding to the United Nations Sustainable Development Goals and Paris Climate commitments are urgent priorities facing many governments. Meeting these commitments will require new industry management architectures that align measures of progress (economic, environmental, human and social) with government structures, datasets, and reporting. Comprehensive emissions quantification and reduction targets for tourism must be a part of this new architecture. In this paper we propose a comprehensive Tourism Carbon Information System (TCIS), comprising four essential information components: national tourism carbon footprint, the carbon-economic linkage, drivers and decarbonization progress, and benchmarking. The TCIS is then tested and applied to Aotearoa New Zealand (2007–2013) to track tourism carbon performance and its decarbonization speed, compared to the national average across sectors. This critical information sheds light on future growth in tourism relative to the national greenhouse gas inventory and establishes the required mitigation trajectory for destinations to move onto a sustainable emissions pathway.