International tourism demand to Finnish Lapland in the early winter season

Abstract

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Microclimatic Volatility and Elasticity of Glacier Skiing Demand

“…In Finland, snow depth was revealed to be a major estimator for ski lift revenues by Falk and Vieru [30], but the sensitivity turned out to be minimal in the north, partly confirming the insignificance of SWE levels on overnight stays as identified by Damm et al [26]. The same study also reports that early snowfall had positive impacts on ski lift revenues for the whole season, and a positive impact was also confirmed for accommodation demand for the Lapland region from the neighbors Sweden and Russia [31]. In Sweden, similar results were reached, such that early season snowfall led to increased skier visits [27].…”

“…The relationship of weather and climate with ski area/resort/destination performance had been reported in a total of 22 papers at the time of the preparation of this manuscript. These studies provide us with statistical and econometric models for France [19], Switzerland [20], Austria [21][22][23][24], Italy [25], Germany, and Slovenia in the Alps [26], Sweden [27,28], Norway [29], and Finland [30,31] in Nordic Europe [26], Czechia, Slovakia [32], and Romania [33,34] in Eastern Europe [26], Spain in Western Europe [26], the USA [13,[35][36][37], Australia [6], and Japan [38].…”

“…In Nordic Europe, several recent studies [27][28][29][30][31] provided findings for a traditional, yet under-researched, ski tourism region. In Finland, snow depth was revealed to be a major estimator for ski lift revenues by Falk and Vieru [30], but the sensitivity turned out to be minimal in the north, partly confirming the insignificance of SWE levels on overnight stays as identified by Damm et al [26].…”

“…As evident in the state of the art research on climate and skiing relationship, most models, so far [6,13,[19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38], have utilized indicators based on weather and climate variables such as snow depth, snow water equivalent, snowfall, snow density, avalanche index, temperature, wind chill, visibility, and cloudiness as the main regressors, whereas other variables such as precipitation (rain, freezing rain, etc.) and wind speed have also been mentioned as important in consumer surveys with winter [49] and summer [50] skiers.…”

“…and wind speed have also been mentioned as important in consumer surveys with winter [49] and summer [50] skiers. Additionally, many studies, especially those based on long-term aggregate data [13,19,21,[24][25][26][27][28]31,37], have attempted to control for changes in economic variables such as income, consumer prices, gas and airfare prices, exchange rates, unemployment rates, and changes in ski tourism supply in question. Regarding the calendar effects, especially in models with daily data [13,26,27,31,32,36], dummy variables have been inserted to identify peak times from weekends, holidays such as Christmas, New Year, and Easter, and school breaks at the market origins.…”