Forecasting British Tourist Arrivals in the Balearic Islands Using Meteorological Variables

Álvarez‐Díaz, Marcos; Nadal, Jaume Rosselló

doi:10.5367/000000010790872079

Cited by 53 publications

(21 citation statements)

References 39 publications

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“…Few studies include a broader set of economic variables that affect winter tourism demand, such as the real income of visitor countries and relative prices. However, in the tourism economics literature it is generally agreed that meteorological variables and economic variables should be included simultaneously in the regression model (Taylor and Ortiz, 2009;Álvarez-Díaz and Rosselló-Nadal, 2010;Otero-Giráldez et al, 2012). In addition, very few studies have been carried out at the level of individual ski-lift companies (for some rare examples, see Fukushima et al, 2002;Bark et al, 2010;Pickering, 2011;Steiger 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

The Demand for Winter Sports: Empirical Evidence for the Largest French Ski-Lift Operator

Falk

2015

Tourism Economics

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This paper investigates the determinants of long-run winter tourism demand for French ski resorts. The data are based on skier visits to the largest ski-lift operator in the world (Compagnie des Alpes) for the winter seasons 1993/1994 to 2011/2012. Using dynamic panel data models for six ski resorts, the study finds relatively low income and price elasticities in absolute terms, with long-run elasticities of 0.64 and -0.40, respectively. Furthermore, the study finds that snow depth measured at the weather station Col de Porte -located at the medium elevation of 1,325 metres above sea level -is a significant predictor of skier days in the high-elevation ski areas. However, the magnitude of the effect of poor snow years is very small: on average, low-snow winter seasons (such as 1989/1990 or 2006/2007) will lead to a reduction in skier visits of about 2.5%. The results are not sensitive with respect to the measurement and timing of snow depth.

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Section: Literature Reviewmentioning

confidence: 99%

The Demand for Winter Sports: Empirical Evidence for the Largest French Ski-Lift Operator

Falk

2015

Tourism Economics

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“…Jeuring and Becken (2013) recognized the adverse effects of severe weather on tourism and examined how tourists protected themselves when facing the risk of potentially severe weather. A growing body of tourism literature has extended the concept of weather to include specific climatic variables, such as temperature, rainfall, and sunshine (Alegre and Cladera 2006; Álvarez-Díaz and Rosselló-Nadal 2010; Becken 2013; Eugenio-Martin and Campos-Soria 2010). These studies have offered deeper insights into the impacts of specific aspects of weather or climate on tourism demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Tourists and Air Pollution: How and Why Air Pollution Magnifies Tourists’ Suspicion of Service Providers

Zhang

Hou

et al. 2019

Journal of Travel Research

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Air pollution is becoming a serious socio-environmental problem in many modern societies and poses significant economic threats to popular tourism destinations. Despite the documented consequences of air pollution on tourism demand, studies have seldom examined its impact on individuals’ psychological states, especially in the tourism context. Through a correlational study and two experiments, our findings indicate that tourists are more likely to be suspicious of local service providers when travelers perceive a destination as having heavy air pollution (vs. one without such pollution). This relationship presumably exists because tourists experience greater pessimism in an environment with high air pollution, which in turn influences their evaluations of service providers. Following this logic, we show that the effect diminishes when tourists are cognizant of (and thus rely less on) their pessimistic feelings when evaluating service providers. Finally, we offer theoretical and practical implications of this effect in tourism.

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“…In a more general framework, it is proposed that, using a monthly time series model, on the one hand, the cyclical-trend component can be captured through an ARIMA model (Rosselló et al, 2011) or even including prices, and other economic determining variables (Álvarez and Rosselló, 2010;Rosselló, 2011). On the other hand, because meteorological variables can present a high variability and are not present in the long-run, it is hypothesized that affect the short run of the time series and consequently can not be captured though ARIMA or Economic factors, and remain in the error term.…”

Section: Time Series Analysismentioning

confidence: 99%

Quantitative Models Evaluating the Effect Climate Change Effects on Tourism - State of the Art

Rosselló¹

2013

Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications

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In a context of climate change, many destinations are considering what effects can be predicted on the tourist demand and how they should be tackled. This work analyses the most relevant perspectives presented in the literature evaluating the effect of climate change on tourism. A review is made by showing the results that rise from a triple point of view: the consideration of physical changes, the analysis of the tourist attractiveness through climatic indexes and modeling tourism demand. The review suggests that, although some methodologies are on a primary stage of development, results from the different perspectives agree in presenting a similar map of the main affected areas (positively and negatively) in terms of tourism demand and/or tourism attractiveness.

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Forecasting British Tourist Arrivals in the Balearic Islands Using Meteorological Variables

Cited by 53 publications

References 39 publications

The Demand for Winter Sports: Empirical Evidence for the Largest French Ski-Lift Operator

The Demand for Winter Sports: Empirical Evidence for the Largest French Ski-Lift Operator

Tourists and Air Pollution: How and Why Air Pollution Magnifies Tourists’ Suspicion of Service Providers

Quantitative Models Evaluating the Effect Climate Change Effects on Tourism - State of the Art

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