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ABSTRACT
In this study, we used the hedonic price method to examine what affected one-day ski lift ticket prices in Norway in the winter season 2014/2015. The analysis was based on geographic information, supply-related characteristics and on climatic data of 83 alpine ski resorts. Additionally, we estimated which ski resorts were under- or overpriced. The results indicate that vertical drop, share of intermediate difficulty ski slopes, number of snow parks, travel distance to the nearest large ski resort in Sweden and price at the nearest ski resort in Norway positively affect prices. Travel distance to the nearest ski resort in Norway and to the nearest large urban area in Denmark or Sweden, a total lift capacity of less than 3000 persons per hour, location in western Norway and a location close to more than two other ski resorts significantly and negatively affect prices. The results suggest that, according to a price–quality relationship, the Hemsedal ski resort provided the highest quality of skiing experience. Overall, ski lift ticket prices were influenced by the pricing decisions of leading ski resorts in Norway. Managers can use the results of this study to make better pricing decisions to increase the profitability of their ski resorts.
Acknowledgements
The author gratefully acknowledges Erik Haugom, Gudbrand Lien and J. Brian Hardaker for their valuable comments and suggestions.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1. Originally, Rosen (Citation1974) defined hedonic prices as ‘the implicit prices of attributes and are revealed to the economic agent from observed prices of differentiated products and the specific amount of characteristics associated with them.
2. Hedonic pricing models are commonly applied to real estate and labor markets. Recently, there has been a growing interest in applying this method in tourism research. Most hedonic price studies in tourism have been done in the hotel and tour operating sectors (e.g. Chen & Rothschild, Citation2010; Espinet, Saez, Coenders, & Fluvià, Citation2003; Hamilton, Citation2007; Monty & Skidmore, Citation2003; Papatheodorou, Citation2002; Rigall-I-Torrent & Fluvià, Citation2011; Thrane, Citation2005).
3. http://www.skiinfo.no, http://www.alpinanleggene.no, http://www.skiresort.info, http://ski-resorts.wanderbat.com, http://www.alpepass.no, http://www.visitnorway.no, http://www.skiheis.as
4. Intermediate slopes, for more confident skiers and snowboarders are defined as RED runs (Skiing terminology, http://www.mechanicsofsport.com/terminology.html).
5. For example, Beitostølen, Kongsberg, Skeikampen, Oslo–Tryvann.
6. Optimal travel time to ski resort for one-day skiing (Kulturdepartementet, Citation2011).
7. The double-log model was chosen on the basis of Akaike’s information criterion (AIC) and the Bayesian information criterion (BIC).
8. A median regression analysis gave almost the same coefficients as the reported OLS model. Thus, the results appear robust. The Breusch–Pagan test was applied to determine whether there are problems of heteroskedasticity (Breusch & Pagan, Citation1979) and the Huber-White-sandwich estimator of variance was used to correct for heteroskedasticity.
9. We are indebted to an anonymous referee for pointing this out.