Academic journal article European Journal of Tourism Research

Car Use in Ski Resort: The Moderating Role of Perceived Lack of Facilities

Academic journal article European Journal of Tourism Research

Car Use in Ski Resort: The Moderating Role of Perceived Lack of Facilities

Article excerpt


Tourism's impacts on the global environment have long been identified (Dubois & Ceron, 2006; L?pez-Sanchez & Pulido-Fernandez, 2014). But, "although transport is clearly a fundamental part of the tourism system, both as a facilitator of access to tourism destinations and as a fundamental part of the tourism experience itself, sustainable transport for tourism is not a well understood topic and is certainly under-researched" (Dallen, 2007: 180). Transport is by far the element of a tourism product that contributes the most to greenhouse gas emissions (Peeters & Schouten, 2006; Verbeek & Mommaas, 2008). Although aviation is an increasing concern regarding these emissions, the car still dominates short-distance tourism travel (Dickinson, Lumsdon & Robbins, 2011). Peeters & Schouten (2006: 158) distinguish origin-destination transport and local transport. The present study focuses on the latter, less researched than the former as regards its negative impact on the environment (Dickinson & Dickinson, 2006). From this very point of view, there is certainly a need for a shift from cars to more sustainable forms of transport in tourism destinations (Dickinson, Lumsdon & Robbins, 2011).

Transport research at large shows that "hard" and "soft" policies have been implemented to encourage that shift. This article is a contribution to the research stream that advocates "soft" transport policies, as opposed to "hard" policies, in order to reduce car use (e.g. Möser & Bamberg, 2008; Richter, Friman & Gärling, 2010, 2011; Bamberg, Fujii, Friman & Gärling, 2011; Friman, Larhult & Gärling, 2013). Hard transport policy measures involve for instance physical improvements of infrastructure whereas soft transport policy measures use techniques of information dissemination and persuasion in order to motivate individuals to voluntarily reduce car use or to switch to sustainable travel modes (e.g. workplace or school travel plans, car sharing schemes, marketing of public transport, travel awareness campaigns, etc.) (Bamberg et al., 2011). Research shows that in general soft transport policy measures are effective, though the heterogeneity of the results makes it difficult to infer why the measures are effective (Richter, Friman & Gärling, 2010, 2011).

To our knowledge, few studies have yet focused on soft transport in the context of tourism. This research is one of the first attempts at bridging this gap. It aims at exploring the effect of some psycho-sociological variables on reduced car use in ski resorts. Faced with international competition, many ski resort stakeholders have understood the importance of environmentally responsible management. Since the development of the French 'National Charter for Sustainable Development' in 2006, some ski resorts have conducted carbon footprint evaluations. Results show that fifty-seven percent of greenhouse gas emissions by ski resorts are due to the transportation of holidaymakers to the resort, around the resort during their stay, and back home (source: tations_2014.pdf). In response, some ski resorts have implemented free shuttle services (e.g. Alpe d'Huez, Valloire, Combloux, Saint-Gervais). However, they have noted that traffic has not decreased and therefore question the effectiveness of their approach.

The Theory of Planned Behavior (Ajzen, 1991) is probably the most widely used theoretical framework to identify the determinants of environmental behavior, including car use (e.g. Aarts, Verplanken & Van Knippenberg, 1998; Bamberg & Schmidt, 2003; Bamberg, Azjen & Schmidt, 2003; Knussen et al., 2004; Knussen & Yule, 2008; Bamberg et al., 2011). The first aim of this article is to show the relevance of this theoretical framework applied to automobile use in ski resorts.

A second aim of our research is to enrich the planned behavior perspective by adding a moderator in the model. …

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