Behavioural adaptation to climate change among

Journal of Sustainable Tourism

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Behavioural adaptation to climate change among winter alpine tourists: an analysis of tourist motivations and leisure substitutability Nicole Cocolas, Gabrielle Walters & Lisa Ruhanen To cite this article: Nicole Cocolas, Gabrielle Walters & Lisa Ruhanen (2015): Behavioural adaptation to climate change among winter alpine tourists: an analysis of tourist motivations and leisure substitutability, Journal of Sustainable Tourism, DOI: 10.1080/09669582.2015.1088860 To link to this article: http://dx.doi.org/10.1080/09669582.2015.1088860

Published online: 11 Nov 2015.

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Date: 06 March 2016, At: 00:00

Journal of Sustainable Tourism, 2015 http://dx.doi.org/10.1080/09669582.2015.1088860

Behavioural adaptation to climate change among winter alpine tourists: an analysis of tourist motivations and leisure substitutability Nicole Cocolas*, Gabrielle Walters and Lisa Ruhanen

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Tourism Cluster, UQ Business School, University of Queensland, St. Lucia, QLD 4072 Australia (Received 12 January 2015; accepted 25 August 2015) Understanding market responses to climate change impacts has important implications for the sustainability of Australia’s winter tourism destinations. Utilising a framework incorporating push pull tourist motivations and the theory of leisure substitutability, this study sought to explore how winter tourists in Australia will adapt to changes in snow cover in Australia’s alpine regions under future climate change scenarios. The results of a questionnaire completed by 231 respondents indicated that tourist motivations were related to behavioural adaptation, and that there is a general preference among the current winter market for spatial substitution in the event of poor snow. Those motivated by recreation specialisation or snow-related attributes were likely to opt for spatial substitution, while tourists motivated by self-expression and apres ski activities displayed resilience to poor snow conditions. The results demonstrate a clear division between leisure-driven tourists who valued participation in sport, and experience-driven tourists, who displayed higher resilience to reduced snow under projected climate change scenarios. These results have practical implications for winter tourism destinations, both in terms of targeting experiencedriven tourists in the case of reduced snow as well as the longer term sustainability and viability of winter tourism destinations. Keywords: climate change; behavioural adaptation; tourist motivations; leisure substitutability; winter tourism; alpine tourism

Introduction Climate change has been identified as one of the biggest challenges facing the tourism industry and the sustainability of destinations worldwide (UNWTO, 2008). The tourism industry is inextricably linked to the natural environment, and tourism activities are often dependent on qualities of the natural environment, such as snow conditions (G€ossling, 2011). As such, the tourism industry is expected to be affected directly by predicted climatic changes (Becken & Hay, 2007, 2012; Hall & Higham, 2005; Schott, 2010; Scott, Hall, & G€ ossling, 2012; UNWTO, 2008). Alpine regions have been identified as highly susceptible to the physical impacts of climate change through loss of biodiversity, changes in water availability, and projected declines in natural snowfall (Scott et al., 2012; Scott & McBoyle, 2007; UNWTO, 2008). The sustainability of the winter alpine sports sector is, therefore, highly compromised due to its vulnerability to such changes (Dawson, Havitz, & Scott, 2011). With regard to the context of this study, Hendrikx, Zammit, Hreinsson, and Becken (2013) identified the heightened vulnerability of Australian alpine regions to warming scenarios, predicting that snow cover would reduce by 39% 96% of its current level by *Corresponding author. Email: [email protected] Ó 2015 Taylor & Francis


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2070. Given that low-elevation resorts are more vulnerable than higher elevation resorts (Dawson & Scott, 2007; Falk, 2010) the low altitude of the Australian Alps mountain range makes the entire winter tourism industry particularly vulnerable. Considering the highest skiable peak in Australia has an elevation of 2054m above sea level, the entire Australian Alps mountain range is considered “low-elevation” by Falk’s (2010) definition. The implications of these studies support other predictions of severe impacts for Australian winter ski resorts in terms of reduced natural snow cover (Hendrikx et al., 2013; Hennessey et al., 2008). In an attempt to ensure the sustainability of this sector, it is, therefore, important for the Australian winter alpine tourism sector to understand the implications of climate change in terms of the markets’ behavioural responses to poor snow conditions expected under future climate change scenarios. This study responds directly to the identified need for further research on the behavioural adaptation strategies of tourists who currently frequent alpine regions vulnerable to climatic change (Dawson et al., 2011; G€ ossling, Scott, Hall, Ceron, & Dubois, 2012; Scott & McBoyle, 2007). In particular, the study aims to develop a comprehensive understanding of how the domestic ski market is likely to respond to diminishing snow conditions in Australia by looking at their substitution behaviour and push pull motivations. These findings, while specific to an Australia context, provide insights for other winter tourism destinations, particularly those that are identified as highly vulnerable due to their low elevation where climate change impacts will be felt much sooner. Background Increasing recognition of the inevitability of climate change has led to a stronger focus on adaptation and adaptive strategies (IPCC, 2014). It is widely accepted that adaptation to climate change in alpine regions is necessary in response to projections of warming (G€ ossling et al., 2012). Scott and McBoyle (2007) demonstrated two key points in their identification of the adaptation options available for the ski industry. First, the options for supply-side adaptation are more extensive, yet more resource intensive to implement (e.g. snowmaking). Demand-side adaptation, however, requires behavioural change on behalf of individuals, and therefore has more immediate consequences for alpine resorts. Thus, tourists have a high adaptive capacity as behavioural change requires minimal effort (Dawson et al., 2011). While supply-side adaptation has received the majority of attention in the literature, there is recognition that more research is needed to understand the likelihood and potential of tourist adaptation to climate change (Dawson et al., 2011; Dawson, Scott, & Havitz, 2013; G€ ossling et al., 2012; Pickering, Castley, & Burtt, 2010; Scott & McBoyle, 2007). Moreover, research is needed to deconstruct why and at what point behavioural adaptation will occur. In order to understand these processes, it is necessary to understand what motivates tourists to take a winter holiday. Behavioural adaptation to climate change in alpine regions Adaptation to climate change is generally identified in the literature as a necessary action, and has been a focal point of tourism research in alpine areas (Scott & McBoyle, 2007). As noted, demand-side adaptation refers to the behavioural change of individuals in response to the impacts of climate change. In the context of winter alpine tourists, this entails visitor responses to changes in snow cover (Dawson et al., 2011). The extent of the impact of reduced snow has been contested in the literature, with evidence of a linear relationship between snow cover and visitation patterns (Fukushima, Kureha, Fujimori,



3

& Harasawa, 2002; Pickering, 2011; Shih, Nicholls, & Holecek, 2009), and also suggestions that other factors may influence tourists’ decisions to visit, such as leisure involvement or place loyalty and attachment (Dawson et al., 2011). Studies investigating the behavioural adaptation of tourists to reduced snow cover in Australia’s alpine winter destinations are particularly limited. K€onig (1998) first explored the potential impact of retracting snow on the local alpine economy, through surveying downhill skiers on their expected behaviour in the event of a season with poor snow. The author reported that, in a scenario of reduced natural snow cover in Australia, 75% of the market would ski less often. Pickering et al. (2010) in their follow-up study utilised the same questions to measure changed attitudes over the time period, reporting that this figure increased to 90% by 2007, demonstrating an increased sensitivity among Australian domestic skiers to situations of poor snow quality. These exploratory studies shed light on the impact of reduced snow on visitation to alpine destinations in Australia, and provide opportunities for further research into behavioural adaptation among winter tourists. In particular, research is needed to better understand these behavioural changes and determine the likelihood and reasoning behind adaptation choice. Scott and McBoyle (2007) identify three adaptation options that are available to winter alpine tourists change the timing or location of participation, or substitute for another activity; all of which align with Iso-Ahola’s (1986) dimensions of leisure substitutability. Theory of leisure substitutability Iso-Ahola’s (1986) theory of leisure substitutability provides a useful framework within which three demand-side adaptation options are explained. According to Iso-Ahola, “… substitution means that the originally intended or desired behaviour is no longer possible and must therefore be replaced by another behaviour if the leisure involvement is to be initiated or continued…” (1986, p. 369). Further, the theory posits that if a person can find another activity through which they receive equal fulfilment, they are likely to be more willing to substitute. The theory has been utilised in a previous study of demandside adaptation options in alpine settings (Dawson et al., 2013), thus supporting its relevance to the context of the current study. The concept of substitution is not only representative of changes in activity, but can also be extended to explain temporal (time) and spatial (place) substitution. According to Hall and Shelby (2000), individuals may substitute the place or timing of participation in an activity if their experience goals are likely to be equally accomplished elsewhere. These three substitution options align with the behavioural adaptation options identified in Scott and McBoyle’s (2007) framework of stakeholder responses to climate change. Hence, the relevance of the theory of leisure substitution in behavioural adaptation becomes evident. Dawson et al. (2013) argued that alpine tourists specifically can adapt their behaviour through spatial, temporal, and activity dimensions. Their study predicted that “lack of snow” will become increasingly important in the decision-making process behind demand-side adaptation to climate change (Dawson et al., 2013). Dawson et al. (2013) also identified that demand is not likely to decrease proportionally to supply; suggesting reduced snow cover will not necessarily translate into fewer skier days. Hall and Shelby (2000) suggested that other factors, such as place loyalty, will also impact substitution choice. For instance, Dawson et al. (2011) analysed the impact of activity involvement and place loyalty on skier’s substitution behaviour. Their findings suggest that skiers with


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a higher involvement in the activity are more likely to act on substitution in response to poor snow, indicating that other factors may influence substitution choice. The literature points to the need for further exploration of behavioural adaptation in response to climate change in a winter sport context (Dawson et al., 2011; G€ossling, et al., 2012; Scott & McBoyle, 2007), specifically research has yet to progress from understanding adaptation options to integrating other factors such as motivation, place loyalty, or recreation specialisation. Further, there is little evidence in the winter sport adaptation literature of the relationship between demographics and potential substitution behaviour with the exception of Dickson and Faulk’s (2007) study that revealed a significant difference between how males and females substitute their ski activities in response to poor snow. This significant finding, accompanied by the fact that demographic background is a key segmentation base across a range of consumer behaviour studies, suggests that this explanatory background information should be incorporated into studies seeking to explore any form of visitor behaviour. Given the limited information surrounding the behaviour of the current winter market in Australia, the impact of demographics on substitution choice is an area in need of further research. The broader literature in behavioural adaptation in alpine tourism explores whether substitution occurs and how (Dawson, et al., 2011, 2013; Fukushima et al., 2002; K€onig, 1998; Morrison & Pickering, 2013; Pickering, 2011; Pickering & Buckley, 2010; Shih et al., 2009). Drawing on a review of this literature, further research is needed to reveal the point at which substitution becomes a viable option and further explain the reasons behind tourists’ substitution behaviour. A tourist’s motivation to take a winter holiday contributes to their substitution choice and is of particular interest to the current study, as discussed in the following. Tourist motivations The push pull motivational theory is one of a number of theories in tourism that attempts to explain tourist motivations. The theory has been utilised in numerous studies, which have focused on cultural backgrounds (Baloglu & Uysal, 1996; Cha, McCleary, & Uysal, 1995; Oh, Uysal, & Weaver, 1995; Yuan & McDonald, 1990), market segmentation (Baloglu & Uysal, 1996; Cha et al., 1995; Dolnicar & Leisch, 2003; Konu, Laukkanen, & Komppula, 2011; Oh et al., 1995), and the interrelated nature of push and pull motivations (Kim, Lee, & Klenosky, 2003). Drawing on motivation from the psychology literature, Dann (1977) argued that a need to travel has to be present before a person chooses to travel, defining such psychological needs as push motivations. Thus, push factors are the key drivers in a tourist’s motivations to travel, while pull factors reflect the attractiveness of a particular destination, or the tourist’s belief that a destination will satisfy their push needs (Dann, 1977). Push and pull motives are context-specific, with different motives emerging in the literature depending on the destination’s characteristics and activities available (see e.g. Crompton, 1979; Kim & Lee, 2002; Kim et al., 2003; Uysal & Jurowski, 1994). That is, push motivations align with site-specific destination attributes, and this alignment may vary depending on the sample and context of the study (Kim & Lee, 2002; Kim et al., 2003; Uysal & Jurowski, 1994). Incorporating the push pull motivational theory into the current study’s framework enables an in-depth analysis of substitution choices, based on an individual’s perception of the attractiveness of an alpine resort to satisfy their intrinsic needs, and in turn the likelihood of sacrificing activity over place or vice versa based on the intrinsic needs that a person wishes to satisfy by travelling to alpine destinations.


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With reference to behavioural adaptation to climate change, this includes the identification of push motives that align with snow-dependent destination attributes. Push factors Through a review of studies undertaken on push pull tourism motivation studies, some common psychologically driven push factors are evident. Push factors are inherent psychological needs and not destination-specific, and those commonly presented in the literature include escape, relaxation, novelty and adventure, family togetherness, and travel bragging, to name a few (Kim & Lee, 2002; Oh et al., 1995; Uysal & Jurowski, 1994; Yuan & McDonald, 1990). Participation in sport, described by Dolnicar and Leisch (2003) as an inherent need to partake in sport activities, is an additional push factor adopted for this particular study. Pull factors A number of studies exploring tourist responses to climate change in alpine destinations have identified the importance of snow cover as a pull factor, finding reduced visitation in the event of reduced snow (Fukushima et al., 2002; Gilbert & Hudson, 2000; K€onig, 1998; Pickering, 2011; Pickering & Buckley, 2010; Pickering et al., 2010; Shih et al., 2009), with some suggesting a direct relationship between snow quality and visitation (Fukushima et al., 2002; Shih et al., 2009). While these studies demonstrate the impact of snow quality as a pull factor, they omit the influence of both external variables and push factors in a tourist’s decision to travel; hence, snow quality is just one of a number of attributes which must be considered within the current study. For instance, Konu et al. (2011) identified the variety and number of slopes as well as apres ski facilities in their segmentation study of the Finnish winter alpine market, whereas Klenosky, Gengler, and Mulvey (1993) found crowding, grooming of slopes, and availability of hills and trails as important factors in travelling to alpine regions, along with entertainment and local culture. Dawson et al. (2011) measured the influence of place loyalty on substitution behaviour. Within the push pull motivational framework of the current study, place attachment was identified as a relevant pull factor in need of consideration. Place attachment is recognised as a dichotomous construct, consisting of place dependence, or the usefulness of a place as a facilitator of leisure participation (Williams & Roggenbuck, 1989), and place identity, representing a psychological or emotional connection to place (Williams & Roggenbuck, 1989; Williams & Stewart, 1998). Place attachment has previously been applied to the context of recreation in alpine settings (Alexandris, Kouthouris, & Meligdis, 2006). Alexandris et al. (2006) examined the impact of place attachment and service quality on loyalty at a ski resort. The study found that place attachment was highly correlated with customer loyalty, suggesting the propensity of place attachment to represent the likelihood of loyalty among tourists at a ski destination. Incorporating this into the framework of the current study, the potential relationship between place attachment and loyalty suggests tourists with high place attachment may be more likely to opt for activity substitution over spatial substitution. Drawing on Hall and Shelby’s (2000) study that predicted a preference for activity or temporal substitution over spatial substitution among people with high place loyalty, it is implied that place attachment may have some implications for substitution behaviour. The association between the push motivation of sport participation and the pull factors that represent an alpine destination’s ability to facilitate one’s participation in winter


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sports relates to recreation specialisation. According to Scott and Schafer (2001), recreation specialisation represents the progression of participation in an activity on a spectrum ranging from novice to expert. When exploring the association between recreation specialisation and destination choice in an alpine context, Won, Bang, and Shonk (2008) found a positive correlation between the importance of snow quality and recreation specialisation and a negative relationship between specialisation and the importance placed on non-sport-related amenities when choosing a ski destination. McFarlane’s (2004) finding that an individual’s destination choice may depend on the ability of that destination to facilitate their participation also reinforces this association. The question remains, however, as to how one’s level of specialisation as a motivational force influences their behavioural adaptation to changes in snow conditions. This review of the literature has revealed two primary research gaps. First, there is a need for more research on demand-side adaptation in situations of reduced snow expected under predicted climate change scenarios to understand the likelihood of behavioural adaptation, including whether demographics influence substitution choice. Second, research to date has not applied the push pull motivational framework, nor included place attachment or recreational specialisation, to determine how tourist behaviours may change if their needs are not met through their original destination choice. Therefore, the aim of the current study is to address these knowledge gaps through an exploration of substitution as an example of a behavioural adaptation strategy of Australia’s domestic ski market in the case of diminishing snow conditions. The research aim is explored through the following questions: (1) How is the Australian domestic ski market likely to adapt to reduced snow quality through substitution? (2) How can push and pull motivations influence substitution choice? (3) Does recreation specialisation influence substitution choice? (4) Do demographics influence substitution choice? Methodology A quantitative approach was adopted for the study. Data were collected through a survey questionnaire which was distributed using a snowball sampling technique via online social media channels to Australians who had previously visited the Australian Alps. This technique was adopted due to limitations associated with the timing and budget of the research. Potential bias and representation issues associated with snowball sampling were addressed through validity and reliability tests, which were conducted throughout the data collection process to ensure the sample had adequate representation from various demographic groups (Babbie, 2010; Veal, 2006). Consistency was maintained where possible to ensure the survey link was preceded by a statement asking participants if they have skied or snowboarded in Australia, thus ensuring only people interested in the topic would respond. The questionnaire comprised three main sections motivations, substitution and demographics. The scale used for the three sections was standardized as a seven-point Likert scale. The motivations section comprised four sections push items, pull items, place attachment, and recreation specialisation. The push items were guided by the literature on tourist motivations, while the pull items were drawn from the alpine tourism literature (see Klenosky et al., 1993; Konu et al., 2011). Place attachment was measured as a dichotomous construct of place dependence and place identity (Williams & Roggenbuck,


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Table 1. Scenarios of reduced snow cover. Scenario 1: There was some heavy snowfall early on in the season but not much since. The weather is warm, the snow is icy on the top and slushy down the bottom. Snowmaking has produced a skiable amount of snow on some of the main runs, but other areas and all off-piste areas (i.e. unmarked trails) are not accessible. The terrain park is open.


Scenario 2: It has been an unusually warm winter with insignificant snowfall, just a few scatterings but not enough to provide a skiable base. Over half of the mountain trails are not open due to lack of snow, and all the chairlifts are closed except for one or two. The snow on the few available runs is entirely from snow machines, and the terrain park is closed. Scenario 3: There is not enough snow to open the mountain for skiing/snowboarding activities. The snow guns cannot meet the capacity needed to open the resort. There is one chairlift open for scenic opportunities only. All of the bars, restaurants, spas, and other non-skiing-related amenities are open.

1989), using the scale originally developed by Williams and Vaske (2003), which has subsequently been utilised extensively (Alexandris et al., 2006; Kyle, Graefe, & Manning, 2005; Kyle, Gaefe, Manning, & Bacon, 2004). Items were drawn directly from Alexandris et al. (2006), which adapted Williams and Vaske’s (2003) original scale to the context of winter holiday destinations, reporting good psychometric values of reliability. The recreation specialisation scale and items were derived from the broader recreation literature, with a higher score reflecting higher specialisation (McFarlane, 2004; Thapa, Graefe, & Meyer, 2006). The seven items were taken directly from previous studies which applied the scale to the context of snow sports, reporting good internal consistency, and included, for example, “Skiing/snowboarding says a lot about who I am” (Needham & Little, 2013; Won et al., 2008). The second section of the survey measured substitution as a type of behavioural adaptation. Three scenarios were presented, which described varying degrees of snow cover, and included one scenario of no snow cover in winter (see Table 1). The responses were standardized across the three scenarios for comparability in the analysis stage. The substitution items were modelled on the items in Dawson et al. (2013); however, these were adapted to be site-specific for the Australian Alps. Items which were potentially doublebarrelled (measuring both activity and spatial substitution) were extrapolated to reduce ambiguity. Temporal substitution was not included in the scale, as warming projections for the Australian Alps suggest the winter season could potentially last just a few weeks (Hennessy et al., 2008), thus limiting the opportunity for temporal substitution in Australia. Finally, the term “climate change” was purposefully omitted in the scenarios to avoid triggering any preconceived political ideals or personal dispositions among respondents. The final section of the questionnaire consisted of demographic questions and included sex, age, and state or territory of residence. A pretest was run to verify the face validity of the questionnaire and the scenarios (Babbie, 2010), resulting in a few minor changes to the questionnaire. The research population of interest to the study was Australian citizens who had previously travelled to the Australian Alps for a winter holiday experience. The online survey yielded 231 complete responses. While 292 participants attempted the survey, 61 did not complete, and their responses were not used in the analysis. Due to the design of the

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online survey, participants could not progress without answering all questions, and hence no response contained missing data. Data were analysed using the computer software program, IBM Statistical Package for the Social Sciences (SPSS) for Microsoft Windows, Version 22.


Results Respondents The sample had a moderately larger female representation (61.1%) than male (38.9%). A cross section of age groups was sampled, with the largest being 18 29 years accounting for 32.9% of the sample, followed by respondents aged 30 44 years (29.4%), 45 60 years (22.5%), and not surprisingly given the context of the study, respondents aged over 60 represented just 14.3%. This breakdown roughly mirrors the profile of the Australian ski market, with approximately 30% being aged between 18 and 29 years, 25% aged 30 50 years, 6% aged between 50 and 60, and the remainder either over 60 or less than 17 years (National Institute of Economic and Industry Research [NIEIR], 2012). The majority (96.5%) of respondents came from Queensland (36.8%), New South Wales (35.3%) or Victoria (24.2%). This representation reflected proximity to the Australian Alps, which are located in the eastern seaboard states of Victoria and New South Wales, and are the top three source markets for Australian alpine resorts in winter, accounting for 87.25% of total visitors in 2011 (NIEIR, 2012).

Factor analysis results for the motivation and substitution scales Principal components factor analyses were performed with Varimax rotation to explore the factorial structure of the motivation measurement scales used in this study. The factor analysis of the push motivation items produced a three-factor solution, accounting for 62.55% of the variance (Table 2). Five items cross-loaded onto two factors when a .4 cutoff was applied (Hair, Anderson, Tatham & Black, 1998), and upon review, the items were assigned to factors based on the higher loading values and face validity. The three resulting factors were titled novelty/adventure, self-expression, and rejuvenation. Reliability was also assumed for all three factors based on their respective Cronbach’s alphas which were above the acceptable level of .7 (de Vaus, 2014). The analysis of the pull motivation items produced a five-factor solution accounting for 68.02% of the variance (Table 3). Six items cross-loaded at the .4 cut-off, and were again assigned based on loading values and face validity. The five factors were titled (in order) snow-related, apres ski, budget and convenience, safe and reliable, and landscape. The final factor, landscape, retrieved a low Cronbach’s alpha of .270 (de Vaus, 2014), and upon closer review of the items a decision was made to omit landscape from further analysis. In contrast to Alexandris et al. (2006) whose study revealed place attachment to be a two-factor scale, the place attachment items produced a one-factor solution (eigenvalue of 3.866), with all items accounting for 77.32% of the variance, and a Cronbach’s alpha of .921. A one-factor solution was revealed for the recreation specialisation scale (eigenvalue of 5.620), explaining 80.29% of the variance and the reliability of this scale was confirmed with Cronbach’s alpha being .959 (de Vaus, 2014). Principal components factor analysis with Varimax rotation was also used to explore the factor solutions of the substitution items and examine their consistency across the three scenarios. As illustrated in Table 4, the items revealed a two-factor solution which


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Table 2. Push motivations factor loadings. Factor groupings


1 To do something adventurous To be able to say “I did that” To try something different To meet and interact with new people or experience a new culture To learn something new To push my limits To be entertained To re-live a fond experience or revisit a cherished memory To learn about myself To express my personal values To feel better about myself For the prestige of travel To relax To rest and rejuvenate To escape the everyday routine To spend quality time with my family or close friends Eigenvalue Cronbach’s alpha

.796 .751 .728 .705 .661 .618 .579 .427

.407

2

3

.422 .464 .868 .795 .758 .590

.488 6.886

1.691

.889 .859 .541 .520 1.431

.872

.826

.797

.401

remained relatively consistent across the three scenarios with the exception of two items. The first factor accounted for activity substitution and was characterised by reduced participation or focus on snow sports, and also by the scenario not impacting the decision to travel to the Australian Alps. The second factor, spatial substitution, included travelling to other Australian destinations or internationally to continue participation in snow sports. The two problematic items (“I would make fewer trips to the Australian Alps that winter”, and “I would not ski/snowboard at all that winter, in Australia or overseas”), however, were removed and the increase in variance explained as a result of their omission provided justification for the decision (Hair et al., 1998). The consistent low reliability for the second factor was noted; however, this is not unusual for factors consisting of only two items, and hence this result was not considered problematic (Peterson, 1994).

Adaptation to reduced snow quality through substitution To address the first research question relating to substitution in the event of reduced snow cover under predicted climate change scenarios, participants were asked to identify the likelihood of substitution in response to three scenarios of progressively worsening snow cover. Scenario one represented reduced snow cover yet a mostly functioning resort; scenario two presented minimal snow cover and minimal operating lifts and terrain; and scenario three entailed a winter of no snow cover (see Table 1). As presented in Table 5, respondents indicated a general preference for spatial substitution over activity substitution, as the three items with the highest means reflect reduced visitation to the Australian Alps in scenarios of poor snow quality. While the items ranked

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Table 3. Pull motivations factor loadings. Factor groupings


1 Number of runs Snow quality Variety of terrain Small lift line lengths Uncrowded slopes Different altitudes Closeness to the mountains Active nightlife Luxury facilities and accommodation options Drinking opportunities Spa services Great variety of restaurants Local shops and retail shopping opportunities State-of-the-art equipment hire or purchase shops Resort services Overall cost Value for money Lift ticket pricing Discount ski and stay packages offered by the resort Closeness and ease of access of the resort from nearby accommodation options Proximity and accessibility from my place of residence Reliable avalanche checks performed Active presence of ski patrol Family friendliness of the resort Regular “town” services available, such as supermarket or post office Terrain park Outdoor aspect, e.g. the clean mountain air Cronbach’s alpha

2

3

4

5

.891 .836 .787 .785 .784 .704 .641

.411

.783 .762 .758 .739 .733 .709 .559 .493

.430 .416 .869 .850 .826 .672 .490

.405

.423 .773 .658 .637 .576

.406

.423 .916

.883

.873

.787

.602 ¡.523 .270

comparatively across the scenarios, the mean scores polarized as the scenarios progressed, indicating that as snow cover worsened, the likelihood of substitution increased. This was true for all of the items with the exception of “I would ski/snowboard somewhere else within Australia” for which the mean dropped as the snow cover scenarios worsened. The item “I would not ski/snowboard at all that winter, in Australia or overseas” had the largest shift in mean as the scenarios progressed, with a difference of .78 between scenarios one and three. The means of the lowest scoring items of no substitution behaviour dropped from the first to the second scenario, and was the lowest in the equivalent item in scenario three, suggesting poor snow cover was more likely to invoke substitution than not. It should be noted that the highest average among the responses is 4.97 on a seven-point Likert scale; hence, these results reflect some uncertainty regarding the participants’ response to scenarios of reduced snow.


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Table 4. Scenario factor analysis. Scenario 1


1 I would still travel to the Australian Alps to ski/snowboard but also do other activities while there This scenario would not affect my decision to holiday at the Australian Alps This scenario would not affect my decision to participate in winter sports at the Australian Alps I would still travel to the Australian Alps but ski/snowboard fewer days while there I would ski/snowboard somewhere else within Australia I would ski/snowboard somewhere outside of Australia Eigenvalue Cronbach’s alpha

2

Scenario 2 1

Scenario 3

2

1

2

.868

.906

.935

.833

.889

.919

.803

.887

.900

.759

.852

N/A N/A

.788 .859 .884 .755 ¡.439 .742 ¡.436 .691 2.845 1.447 3.401 1.323 2.798 1.222 .840 .469 .911 .490 .917 .442

Note: Extraction method: principal component analysis. Rotation method: varimax with Kaiser normalisation.

Table 5. Scenario substitution means. Scenario 1

Scenario 2

Scenario 3

Std. Std. Std. Mean deviation Mean deviation Mean deviation I would make fewer trips to the Australian Alps that winter I would ski/snowboard somewhere outside of Australia I would not ski/snowboard at all that winter, in Australia or overseas I would ski/snowboard somewhere else within Australia I would still travel to the Australian Alps but ski/snowboard fewer days while there I would still travel to the Australian Alps to ski/ snowboard but also do other activities while there This scenario would not affect my decision to holiday at the Australian Alps This scenario would not affect my decision to participate in winter sports at the Australian Alps This scenario would not affect my decision to participate in alpine activities in the Australian Alps

Items not presented in this scenario

4.91

1.587

4.97

1.774

4.91

1.916

4.45

1.871

4.67

1.901

4.69

1.955

3.90

1.666

4.49

1.786

4.68

1.853

3.86

1.517

3.68

1.745

3.55

1.862

3.85

1.681

3.22

1.825

N/A

N/A

3.75

1.805

3.05

1.711

3.06

1.880

3.49

1.817

2.99

1.790

2.88

1.916

3.31

1.688

2.81

1.662

N/A

N/A

N/A

N/A

N/A

N/A

2.63

1.739

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Table 6. Relationship between motivation and substitution behaviour. Substitution


Activity substitution

Spatial substitution

Regression model Push motivations, F(4, 216) D 6.652, r2 D 0.110, p < .001 Pull Motivations, F (5, 215) D 22.691, r2 D 0.345, p < .001 Push motivations, F(4, 216) D 10.827, r2 D 0.167, p < .001 Pull motivations, F(5, 215) D 7.024, r2 D 0.140, p < .001

Significant motivation factors

b

t

p

Self-expression Recreation specialisation

.309 ¡.195

3.957 ¡2.889