96 resultados para 150602 Tourism Forecasting
Resumo:
Marine reserves are increasingly being established as a mechanism to protect marine biodiversity and sensitive habitats. As well as providing conservation benefits, marine reserves provide benefits to recreational scuba divers who dive within the reserve, as well as to recreational and commercial fishers outside the reserve through spill-over effects. To ensure benefits are being realised, management of marine reserves requires ongoing monitoring and surveillance. These are not costless, and many marine reserve managers impose an entry fee. In some countries, dive tourism is major income source to coastal industries, and a concern is that high entry fees may dissuade divers. In this paper, the price elasticity of demand for dive tourism in three countries in South East Asia – Indonesia, Thailand and Malaysia – is estimated using a travel-cost model. From the model, the total non-market use value associated with diving in the area is estimated to be in the order of US$4.5 billion a year. The price elasticity of demand in the region is highly inelastic, such that increasing the cost of diving through a management levy would have little impact on total diver numbers.
Resumo:
Tourism plays an important role in the development of Cook Islands. In this paper we examine the nexus between tourism and growth using quarterly data over the period 2009Q1–2014Q2 using the recently upgraded ARDL bounds test to cointegration tool, Microfit 5.01, which provides sample adjusted bounds and hence is more reliable for small sample size studies. We perform the cointegration using the ARDL bounds test and examine the direction of causality. Using visitor arrival and output in per capita terms as respective proxy for tourism development and growth, we examine the long-run association and report the elasticity coefficient of tourism and causality nexus, accordingly. Using unit root break tests, we note that 2011Q1 and 2011Q2 are two structural break periods in the output series. However, we note that this period is not statistically significant in the ARDL model and hence excluded from the estimation. Subsequently, the regression results show the two series are cointegrated. The long-run elasticity coefficient of tourism is estimated to be 0.83 and the short-run is 0.73. A bidirectional causality between tourism and income is noted for Cook Islands which indicates that tourism development and income mutually reinforce each other. In light of this, socio-economic policies need to focus on broad-based, inclusive and income-generating tourism development projects which are expected to have feedback effect.
Resumo:
We theoretically analyze the impact of changes in foreign income from tourism source countries on the growth of tourism dependent small island economies. Using a general theoretical construct, we attempt to answer the question of how price elasticity of demand, income elasticity of tourist and the degree of competition in the service sector influence the economic development of small economies. One of the main results is that politicians may consider applying policies which lead to a competitive environment in the service sector to maximize growth and the consequent labor income share.
Resumo:
Today national and regional tourism organizations look to sophisticated cultural tourism programs to enhance the visitor experience for tourists of their particular city. Yet research indicates that a challenge exists in designing and implementing programs that take full advantage of a city’s historical and emergent literary cultures. In this paper we offer critical insights into how literary cultural heritage can foster the development of an integrated and dynamic approach and provide the experience sought by local and global tourists. International exemplars are cited together with an analysis of the Australian city of Brisbane that describes itself as a ‘new world city.’ The findings of our research show that programs that harness diverse literary cultures, rather than adhering to a single literary representation, are better equipped to build identity and thus extend cultural tourism potential.
Resumo:
Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.
Resumo:
The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.