Microclimatic Volatility and Elasticity of Glacier Skiing Demand

Abstract

The effects of climate conditions and weather on ski tourism have become a hot topic as the negative impacts of climate change on ski tourism become increasingly visible. This study aims at measuring the significance and magnitude of long-term diurnal and daily weather conditions on lift frequentation at an Austrian glacier ski area in terms of the winter and the summer skiing offers. In doing so, it utilizes an autoregressive conditional heteroskedasticity (ARCH) model to reveal and quantify any volatility associated with ski area visitation and then employs regression models to account for any microclimatic elasticity of glacier skiing demand. The main findings reveal a significant volatility in ski area visitation, especially during the summer seasons. While this study does not aim for an ultimate determination on the reasons for such volatility, skiing demand models illustrate the importance of thermal comfort, especially wind chill factor (WCF), as a major determinant of demand sensitivity for glacier skiing as well as non-skier visits during the summer season. Significant, albeit inelastic, relationships between other microclimatic characteristics, such as snow depth and relative humidity, with visitation and lift frequentation are also identified. Based on these findings, implications according to a changing climate and practical suggestions on the sustainability of winter and summer skiing activities are provided.

Overloaded! Critical revision and a new conceptual approach for snow indicators in ski tourism

“…Ski area managers may start the operation early, i.e., before the desired snow depth is reached, because they have to compete with neighboring ski areas (or to cash in during high-demand periods), and they may end it early because the demand is lacking and costs can be reduced (Scott et al 2007 ). This is often the case towards spring when people prefer summertime activities although there is still a lot of snow in the ski areas (Mayer et al 2018 ).…”

Estimation of the Spatial Suitability of Winter Tourism Destinations Based on Copula Functions

“…There are also large differences in seasons. Climate change causes a lot of losses to the tourism industry in some regions while improving the suitability of tourism in other regions [64]. Combined with the change of 10 cm snow depth contour map (Figure 5) and the average temperature in winter in Jilin Province (Figure 3), it can conclude that the mean temperature in winter in Jilin Province showed an increasing trend (0.29 °C/10a).…”

The Ski Climate Index (SCI): fuzzification and a regional climate modeling application for Turkey

“…Future studies on the SCI and its applications could focus on further iterations with the field experts, as well as the growing econometric studies on the demand side (see Mayer et al 2018 for a review), to incorporate other components such as visibility, defined in terms of the number of fog events. Indeed, a domestic tour operator in Turkey has already introduced a mobile application to interact with its consumers on a real-time basis and alerts them based on a scale of 1 to 10, measured by inputs on snow depth, cloud cover, and windiness.…”