Forecasting is an essential analytical tool for tourism policy and planning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q). Secondary data was used to produce forecasts of international tourists’ expenditures in Thailand for the period 2009-2010. The results...

Forecasting is an essential analytical tool for tourism policy and planning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q). Secondary data was used to produce forecasts of the number of international tourist arrivals to Thailand for the period of 2009-2010....

There has been growing interest in studying behaviour of long memory process in tourism market. In this research examine the behaviour of India’s international tourism market based on long-memory analysis. The international tourism market of India combined with nine countries. For example,...

In order to ensure some quality consulting services within the activity “Providing consultancy services to develop applications for European funding with focus on the SOP HRD 2007-2013”, in order to identify the organisations’ consultancy needs, the problems they face in elaborating the...

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....

This article considers the performance of countries at the Olympic Games as a public good. Firstly, it is argued that, at the national level, Olympic success meets the two key conditions of a public good: non-rivalry and non-excludability. Secondly, it is demonstrated that standard income...

It is expected that what people are searching for today is predictive of what they have done recently or will do in the near future. This research will analyze the eligibility of Google search data to nowcast tourist arrivals to Prague. The present research will report whether Google data is...

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....

The paper makes an attempt to provide estimation of foreign tourism demand by 2014, by investigating the case of Macedonia. The author applies the Box-Jenkins methodology and tests several alternative specifications in the modeling of original time series. Upon the outcomes of standard...