The present paper aims to assess the importance of different factors influencing demand conditions for a tourist destination on the basis of individual stakeholder perceptions. The relationship between the tourist demand conditions and individual influential factors, such as inherited resources,...

It is natural to turn to the richness of panel data to improve the precision of estimated tourism demand elasticities. However, the likely presence of common shocks shared across the underlying macroeconomic variables and across regions in the panel has so far been neglected in the tourism...

We analyse how German tourists react to unanticipated shocks that alter their risk perception of selected tourism destinations. Using a difference-in-difference strategy which flexibly accounts for macroeconomic conditions and also addresses potential problems of serial correlation, we isolate...

A data set of the holiday destination choices of German tourists is segmented using phase in the life cycle; second, holiday motivation and holiday activities and third, the region of residency. For each segment demand is estimated using data on environmental and economic characteristics of...

The literature on tourism and climate change lacks an analysis of the global changes in tourism demand. Here a simulation model of international tourism is presented that fills that gap. The current pattern of international tourist flows is modelled using 1995 data on departures and arrivals for...

The attractiveness of a tourist destination is partly dependent on its environmental and climatic resource base. Climate change can be expected to have an effect on this attractiveness and will subsequently alter patterns of demand. An application of the pooled travel cost model using survey...

This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in tourist arrivals form all visitor markets to a specific destination in a multiple-input multiple-output (MIMO) structure. While most tourism forecasting research focuses on univariate...

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....

We analyse how German tourists react to unanticipated shocks that alter their risk perception of selected tourism destinations. Using a difference-in-difference strategy which flexibly accounts for macroeconomic conditions and also addresses potential problems of serial correlation, we isolate...

The objective of this paper is to analyze the demand for tourist arrivals to the United States, using the panel cointegration technique. The study attempts to identify and measure the impact of the main determinants of inbound international tourism flows to the United States. The study uses...