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Research in Transportation Economics 26 (2010) 66–73

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Research in Transportation Economics

journal homepage: www.elsevier .com/locate/retrec

Moving towards more eco-efficient tourist transportation to a resortdestination: The case of Whistler, British Columbia

Jennifer Reilly*, Peter Williams, Wolfgang HaiderCentre for Tourism Policy and Research, School of Resource and Environmental Management, Simon Fraser University, 8888 University Drive, Burnaby,British Columbia V5A 1S6, Canada

keywords:Tourism transportationModal choicePlanningEco-efficiencyWhistlerBritish Columbia

* Corresponding author. Tel./fax: þ1 604 892 9496E-mail addresses: wildreilly@gmail.com (J. Reilly), p

whaider@sfu.ca (W. Haider).

0739-8859/$ – see front matter � 2009 Elsevier Ltd.doi:10.1016/j.retrec.2009.10.009

a b s t r a c t

Transportation is not only a key component of the tourism value chain, but it is also a criticalmanagement consideration in shaping tourism’s environmental footprint. Transportation consumes thegreatest portion of the energy used in the tourism system. Most of this consumption is associated withtravel to and from the destination. Despite this situation, scant research has addressed ways in whichdestinations can play a role in reducing this energy use challenge. Strategies such as shifting visitors tomore energy-efficient modes have the potential to improve the eco-efficiency of tourist transportation.Using a case study of transportation management options and visitor responses in Whistler, BritishColumbia, Canada, this paper examines visitor reactions to a range of transportation strategies designedto shift skiers from private to public modes of transport. Respondents completed an online surveyemploying both traditional and stated choice questioning methods to examine tourists’ transportationchoice behaviour. Long-haul tourists were the most likely to shift transport modes based on themanagement options offered to them. Destination management strategies for moving this target groupto public modes of transportation are described.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

By definition, transportation is one of the key components oftourism. All tourists must eventually travel to and from thedestinations they choose. This reality makes most types of tourismparticularly energy intensive propositions, especially when long-haul air travel or automobile transportation is involved. Eventhough tourism is often considered a desirable form of economicdevelopment, its sustainability (especially from a travel relatedenergy consumption perspective) is challenging (Clark, Jager,Cavender-Bares, & Dickson, 2001). This is particularly the case fortourism destinations positioning themselves as environmentallyfriendly places that pro-actively practice less consumptive formsof energy use (Bates & Caton, 2002, Kelly & Williams, 2007a).While much research explores techniques for reducing internalenergy consumption within destinations, few investigations haveexplored consumer responses to methods of decreasing theenergy consumption of travel to and from such places. Thisresearch examines consumer responses to a range of destination

.williams@sfu.ca (P. Williams),

All rights reserved.

induced policies designed to reduce external travel related energyconsumption. As such its findings contribute to the growingliterature on destination sustainability in general, and a specificvoid related to the management of external energy consumptionassociated with travelling the final leg of the journey to thedestination.

Transportation is frequently identified as a growing concernwith respect to tourism-induced energy consumption. Researchhas shown that transportation typically accounts for the vastmajority (in some cases greater than 90%) of energy consumptionin the tourism system (e.g., Gossling et al., 2005; Kelly & Williams,2007b; Peeters & Schouten, 2006; Tabatchnaia-Tamirisa, Loke,Leung, & Tucker, 1997). In many cases, the transport mode choiceof visitors plays a key role in determining the overall eco-efficiency of tourism experiences. Indeed, several studies reportthe energy emission reductions to be gained by shifting tourists tomore eco-efficient modes of travel (Becken, 2005; Becken, Sim-mons, & Frampton, 2003; Gossling et al., 2005; Hoyer, 2000; Kelly& Williams, 2007b), particularly various forms of public trans-portation.

Eco-efficiency involves producing goods and services thatrequire diminishing levels of energy and material resources (WorldBusiness Council for Sustainable Development, 2000). In essence, itis about increasing resource productivity or ‘‘doing more with less’’

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–73 67

(DeSimone & Popoff, 1997, p. 2). Given the tourism industry’scurrent dependence and propensity for transport-related energyconsumption, it is increasingly becoming the focus for strategiesdesigned to produce eco-efficiency improvements. One key chal-lenge for tourism destination managers is to identify and imple-ment policies that effectively encourage visitors to select moreeco-efficient transportation options. This paper explores visitorresponses to a range of potential transport mode shifting options inthe context of a case study of Whistler, British Columbia (BC),Canada.

Whistler, BC is a four-season destination resort located about120 km north of Vancouver, BC. It hosts about two million visitorsannually with approximately 45% of the visits occurring during theshorter winter season (Resort Municipality of Whistler [RMOW],2004a). Over the past decade, Whistler has developed and/orinitiated a wide variety of sustainability policy, planning andprogramming initiatives designed to make it a more sustainabledestination (RMOW, 1999, 2004a, 2004b, 2005a, 2005b; Vance &Williams, 2005). Some of these strategies focus on reducingtransport-related fuel consumption and related emissions withinand beyond the municipality.

Whistler was the final destination for over 60% of all trips on theSea to Sky Highway, the route that connects Vancouver to Whistlerand other nearby communities (RMOW, 2004a). About 65% of non-resident visitors to Whistler arrived by air in Vancouver, and thentraveled to Whistler by various modes (TSi Consultants, 2002). Ofthe trips made on the Sea to Sky Highway, about 93% were by privateautomobile, 6% by bus and less than 1% by train (RMOW, 2004a).

The Resort Municipality of Whistler has outlined the commu-nity’s vision and strategic plan for moving towards sustainability inWhistler 2020: Comprehensive Sustainability Plan (RMOW, 2004b).The document considers the effects of transportation on climatechange and air quality in an intra-urban context only (RMOW,2005b). While the issue of tourist arrivals via single-occupancyvehicles is identified as an indicator of performance, no discussionaddresses inter-urban transportation strategies.

The Whistler 2020 Transportation Strategy (RMOW, 2005b)recognizes the necessity of transporting tourists to the resort withminimal environmental impact, addressing the viability of alter-native intra- and inter-urban transportation options. However,support for alternative transportation must exist outside of Whis-tler for these strategies to be successful. The provincial governmenthas a significant impact on transportation infrastructure decisionsfor inter-urban travel between Vancouver and Whistler.

Whistler’s Transportation Advisory Group [TAG], formed in1996, has contributed to inter-urban transportation planningthroughout the Sea to Sky Corridor (RMOW, 2004a). TAG aims toencourage more efficient forms of transportation in Whistler(RMOW, 1999). TAG’s current goal is to reduce the portion of visi-tors travelling between Vancouver and Whistler by private auto-mobile by 15% through alternative transportation strategies.However, other recommendations suggest that alternative andmore aggressive transportation demand management strategiesmight increase public transportation use amongst private auto-mobile traveller by 50% over a ten year period (RMOW, 2005a).

While several of Whistler’s planning and sustainability initia-tives are recognized as particularly proactive (Williams & Ponsford,2009), no comprehensive empirical research has tested the credi-bility of the modal shifts associated with the demand managementstrategies mentioned above. This research identifies a range ofthese energy reducing external transport options, and examinestheir influence on traveller mode choice. It does this by firstdeveloping a conceptual model that positions external transportwithin a broader destination transportation model. It then usesfindings emanating from a survey of destination visitors to explore

consumer responses to these options, and to suggest ways in whichdestinations can help shift travellers towards more eco-efficienttransport mode choices.

2. A conceptual model of destination transportation links

Transportation links tourists with travel destinations (Gunn,1988; Leiper, 1979, 2004), and tourism is impossible without it.Transportation is an essential and critical component in themanagement of tourism’s value chain. Value chains are the sets ofstructures and processes used to deliver goods and services toclients. They can help scope and identify the set and sequence offunctions needed to produce a good or service, as well as high-light the management activities needed to ensure that thecomponents collectively create value for consumers and theindustry (Porter, 1985). The service being delivered, in the case ofthe tourism industry, is the tourism experience. Transportationplays an important ‘flow’ function in the tourism value chain. Itlinks tourists at their origin with appealing stocks of environ-mental and cultural assets at the destination. Long term value iscreated when the flow of people to a destination creates positivelinkages with the environment. The management of trans-portation’s energy related emissions and impacts representchallenges to the tourism value chains of a growing range ofdestinations.

Several conceptual models highlight and describe the crucialposition of transportation in the international tourism system (e.g.,Hills & Lundgren, 1977; Leiper, 1979). Hills and Lundgren (1977)describe the functional mechanisms of tourist movement in a long-haul travel context (i.e., travel to the Caribbean) (Fig. 1). The modelshows how tourists move from their individual residential loca-tions to a centralized travel hub (airport) in their region. They arethen assembled to be transported in planes to the centralized hubsat their destination. After arriving at this central hub, they disperseto a number of different locations for their individual on-sitetourism experiences.

While Hills and Lundgren’s model goes beyond a simple focuson transportation to explain the fundamental structural charac-teristics of international travel, it clearly separates the long-haultravel component (likely by air) from the travel components to andfrom the respective airports. Although not pointed out by theauthors, the model identifies clearly the strategic points in thistravel process, at which travellers make crucial mode choices. Thequestion is how and to what extent travellers can be influenced byvarious destination transport management options.

In order to make this conceptual model applicable to the casestudy of Whistler, we adapted it to the specific long-haul trans-portation characteristics of typical winter destination resorts ingeneral, and the Vancouver – Whistler situation in particular(Fig. 2). Whistler also attracts a large number of short-haul visitorsfrom Vancouver’s nearby metropolitan area, and from other prox-imate urban centres such as Seattle, Washington. These short-haulskiers join the long-haul visitors when travelling on the final leg ofthe journey, in this case the Sea to Sky Highway.

In our adaptation of Hills and Lundgren’s model (Fig. 2), weplaced the destination of Whistler, British Columbia, at the secondlevel of the diagram. The left (A) and right (B) sides of the diagramare linked through transportation, corresponding to the Hills andLundgren model. The right side (B) of the model is the main focus ofthis investigation. It focuses on the dispersal of tourists upon arrivalat a central hub (YVR – Vancouver International Airport) to resortfacilities at the regional level (W – Whistler). On their arrival at theVancouver International Airport, tourists have several transportmode choices, represented by the multitude of arrows linkingthe international airport and Whistler. Currently, the only

3 International- national

2 National- regional

1 Regional- local

Levels

Product

- concentration - dispersal

Market

Tour

ist P

rodu

ct

A B

Fig. 1. Functional mechanism of tourist movement. Note: Reprinted from Annals of Tourism Research, Volume 4, Issue 5, T. L. Hills and J. Lundgren, The impact of tourism in theCaribbean, pages 248–267, Copyright 1977 with permission from Elsevier.

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–7368

transportation options available to travellers arriving at the Van-couver International Airport are rental car, bus and limousine. Onarrival at Whistler, many visitors have no requirement for intra-urban transportation due to the pedestrian-oriented nature ofWhistler Village (hence the removal of arrows depicting local travelbetween levels one and two on side B).

Long-haul tourists plan trip logistics from home prior todeparture, and consequently the transportation choices to be made

- - - - - - - -

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3 International - national

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A

Fig. 2. Functional mechanism of tourist movement to Whistler, BC for long-haul visitors.Lundgren, The impact of tourism in the Caribbean, pages 248-267, Copyright 1977 with pe

at the crucial nodes may not be as discretionary as one mightinitially believe. While some packages identify a specific trans-portation option between YVR and Whistler, many tour operatorsprovide a range of choices. However, these alternatives areconsidered by visitors at the time of booking. Relatively few trav-ellers make this choice after arrival at the Vancouver InternationalAirport. Our conceptual model provides a useful context for theensuing discussion of our findings.

- - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - -

- dispersal

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spor

tatio

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ode

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ist P

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- - - - - - - - - - - - - - - - - - - - - - -

YVR

W

B

Note: Adapted from Annals of Tourism Research, Volume 4, Issue 5, T. L. Hills and J.rmission from Elsevier.

1 Short-haul visitors are those who reside in British Columbia, Alberta, Wash-ington and Oregon. Long-haul visitors are those who reside elsewhere and traveledby plane to Vancouver before travelling on to Whistler.

2 For reasons of brevity, the word ‘‘skier’’ refers to both skiers and snowboardersfor the remainder of this document.

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–73 69

3. Methods

3.1. Data collection and analysis

This investigation of the transportation choice patterns ofWhistler’s winter visitors was part of a larger investigationexploring consumer response to a variety of sustainable destinationpolicy and planning initiatives (Kelly, Haider, & Williams, 2007). Atwo-part data collection process was employed to collect the datafor the project. This included an initial intercept survey, followed byan online visitor survey. These surveys collected visitor responsesto a range of socio-demographic, attitudinal and behaviouralquestions. In the context of this work, the online survey containeda set of traditional item by item questions as well as more complexdiscrete choice probes eliciting tourists’ preferences and trade-offchoices with respect to varying transportation options for travelbetween Whistler and Vancouver.

The intercept surveys were conducted systematically at varioustimes and strategic locations in Whistler’s main village during thewinter of 2005. Respondents were randomly selected on their wayto the destination’s two ski mountains. The intercept surveycollected basic visitor profile and travel behaviour information, aswell as email addresses from 1643 visitors to the resort. Uponcompletion of the intercept survey, respondents were invited tocomplete a follow-up online survey. Overall, 467 of these wintervisitors participated in the subsequent online survey. This moredetailed questionnaire explored a comprehensive set of socio-demographic, attitudinal and behavioural traits of the respondents.The response data collected were used to model the stated choicebehaviour of tourists, and to estimate visitors’ acceptance of andpreferences for different transportation policy alternatives.

The transportation choice experiment in the online surveyemployed an orthogonal fractional factorial design (Louviere,Hensher, & Swait, 2000; Raktoe, Hedayat, & Federer, 1981) togenerate the profiles of attributes and their corresponding levels forthe 54 choice sets required in the study. An orthogonal designimplies that each of the attributes is independent of the others. Onedrawback of these efficient designs is that no interaction effectsbetween attributes can be measured (Louviere et al., 2000). For anexample of a choice set, see Fig. 3.

Each respondent viewed four choice sets. Three of the choicesets were drawn from the experimental design. In addition, eachrespondent saw an identical fourth set, a so-called common set. Itpresented attribute levels that were pro-transit in nature in orderto explore their preferences when faced with a choice in whichpublic transit was presented as a very appealing option. No indi-vidual choice set was repeated for any respondent.

In all four choice sets, respondents could choose from fiveoptions as illustrated in Fig. 3. These included four modes oftransport (private automobile, rental automobile, bus and train) aswell as a fifth option of not taking the trip. Each respondent wasasked which mode they would be the mostly likely to use to travelbetween Vancouver and Whistler given the particular set ofattributes.

Each transport mode (i.e. the choice alternative) was describedby key travel related attributes (i.e., travel time, frequency, cost,locations of departure from Vancouver and arrival in Whistler, roadconditions). These attributes were selected for their relevance totourists and importance in determining modal choice for touristtravel. The levels selected for each attribute facilitated the simula-tion of current and ‘realistic’ hypothetical transportation condi-tions. Each attribute and its corresponding levels were determinedthrough a review of existing transportation literature (Asensio,2002; Ben-Akiva & Morikawa, 2002; Bhat, 1997, 1998; Horne, Jac-card, & Tiedemann, 2005; de Palma & Rochat, 2000), stakeholder

input, and feedback from and overlap with the results of a previoussurvey assessing summer tourists to Whistler (Kelly et al., 2007).

The choice analysis presented in this paper focuses predomi-nantly on respondents who indicated they skied or snowboardedduring their trip to Whistler in 2005. Short- and long-haul1 over-night skiers2 were compared. The choice model results are derivedfrom a maximum likelihood procedure run in LIMDEP 8.0 software(Greene, 2002) and all attributes were effects coded (Louviere et al.,2000). Descriptive analyses were also performed, using the Statis-tical Package for Social Science (SPSS) 13.0. Similarities and differ-ences between short- and long-haul overnight visitors wereexplored using independent samples t-tests and chi-square tests tocompare and contrast the different groups’ responses.

4. Results

In this section the results of the actual and stated mode choicesof respondents for travel between Vancouver and Whistler arepresented. Almost all long-haul visitors stayed in Whistler over-night. In order to ensure accurate comparisons, long-haul overnightvisitors were compared with short-haul overnight visitors, whileday visitors were omitted. Thus, the overall data set for this analysisincluded all overnight skiers (n ¼ 349), who were either (1) short-haul travellers including individuals from British Columbia (espe-cially from the proximate Lower Mainland region), Alberta, Oregonand Washington (n ¼ 112; 32%), and (2) long-haul travellersincluding international travellers and individuals from other areasof North America (n ¼ 237; 68%).

In this study, the vast majority of short-haul visitors relied onthe car as the means of transportation on their trip in 2005, whileonly 4.5% took the bus (Table 1). The pattern of actual mode choiceis very different for the long-haul visitor. Over 30% of them took thebus, a quarter relied on a private vehicle (typically rental car andlimo), and another third of respondents fall into the category‘other’. This group either traveled by some other means (e.g.airplane or helicopter), or did not indicate a conclusive mode.

The domination of the private mode of transport was expected,and led to our research question about the desirability of alterna-tive modes of transportation. Consequently the study’s surveyinstrument included the stated choice experiment which investi-gated which attributes of the transportation modes between Van-couver and Whistler would need to change in order to enticetravellers to select more sustainable modes of transportation. Theresults of the discrete choice experiment for the long-haul over-night skiers are summarized in Table 2. They are rather surprising.Even though the respective attribute levels varied widely, noindividual factor was significant in influencing the mode choices ofrespondents. Only the intercepts were significant, suggesting thatthe mode itself was more important to respondents than theattributes of any one of the modes. Since the intercepts are allpositive values, the results indicate that ‘‘would not go’’ is not reallyan option for respondents. If all else is equal, travelling by privatecar is preferred to not going. In other words, visitors are dedicatedto a particular mode of travel regardless of the characteristics ofalternative modes.

In an attempt to understand these puzzling results, we nextexamined the frequencies of mode choices in the discrete choiceexperiment (Table 3). Among the short-haul skiers, almost two

Fig. 3. Sample of a choice set (illustrates the pro-transit ‘‘common set’’).

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–7370

thirds (64%) chose the private mode consistently, only 7% chosepublic mode consistently, and less than one third (29%) actuallymade tradeoffs between private and public modes. Conversely,among long-haul skiers more than 60% traded off between privateand public modes within the various choice sets. Over one quarterof long-haul skiers chose public mode consistently and 12% choseprivate mode consistently.

Next we investigated the consistency between actual andhypothetical mode choice, separately for long-haul (Table 4) andshort-haul skiers (Table 5). The total number of respondents con-tained in this table is much lower, because only respondents whoconsistently chose the same mode of travel in the first three choicesets are included here. The interesting finding here is that long-haulrespondents were very consistent with choosing private mode ontheir 2005 trip and in their stated mode choice. This is not the casefor respondents who chose public consistently in the choiceexperiment, but still predominantly relied on the car in their actualtravel. As an aside to the analysis of long-haul skiers, Table 5 showsthe strong consistency of this group to private modes of travel.

Another way of examining the consistency of the choicebehaviour is by investigating the responses to the fourth choice set.

Table 1Actual mode choice of overnight visitors (as reported in the survey).

Mode choice Total sample Short haul Long haul Chi-square(p value)

Freq. % Freq. % Freq. %

Privateautomobile

114 32.7 97 86.6 17 7.2 219.554(0.000)

Rentalautomobile

47 13.5 6 5.4 41 17.3

Bus 78 22.3 5 4.5 73 30.8Limo 15 4.3 0 0.0 15 6.3Other 95 27.2 4 3.6 91 38.4Total 349 100 112 100 237 100

This common set was evaluated by each respondent. In it, thepublic transit option was set at particularly attractive levels. Justunder half of both short-haul and long-haul overnight skiers stillselected the private car option (Table 6). However, exactly half ofthe long-haul respondents chose the public mode option, whileonly a few of them chose not to travel to Whistler at all. Among theshort-haul skiers, 29% selected the public option, while an unex-pected 22% indicated that they would no longer go to Whistlerwhen these were the only available transport options.

5. Discussion

This paper focused on the travel component of the tourismsystem by looking at the case of the resort community of Whistler,British Columbia. Whistler’s location makes it interesting as itattracts two types of skiers with rather different travel needs andperceptions of travel. The first group is short-haul travellers whoprimarily arrive in Whistler without an air travel component totheir journey. The other is long-haul visitors who predominantly flyto Vancouver and must then travel on to Whistler. The road fromVancouver to Whistler is the only major access route to the desti-nation from major markets and airports. Given its length, the modechoice for travelling this route has significant implications on thedestination’s overall sustainability when judged from the overallsystems point of view.

Our survey of skiers indicated that the majority of them reliedon private modes of transportation for their Whistler trips.Furthermore, the majority could not be readily influenced to switchtheir modal choice. This was especially true for short-haul travel-lers who were able to drive their own vehicles because they livedclose enough to the destination to do so in a reasonably timelymanner. Among the long-haul visitors, about one third traveled bypublic modes, while 25% relied on private cars often rented fromrental agencies at the Vancouver airport. In the stated choice

Table 4Comparison of actual travel mode and dominant stated choices for long-haul skiers.

Actual travel mode Stated choice in survey Chi-Square(p value)

Private Public

Freq. % Freq. %

Private mode 16 57.1 35 56.5 2.537 (0.281)Public mode 0 0.0 5 8.1Other 12 42.9 22 35.5

Total 28 100 62 100

Table 2Parameter estimates for transportation stated choice model (long-haul visitorsonly).

Attributes and levels Coeff. St. err. Sig.

Road conditions Slushy and slippery sections �0.128 0.286 0.655Snowy sections withlimited visibility.

0.001 0.294 0.997

Auto – travel time 3 h from downtownVancouver

�0.001 0.115 0.994

4 h from downtownVancouver

0.017 0.115 0.883

Auto – one-wayuel cost

$15 0.077 0.114 0.500$30 0.060 0.114 0.599

Auto – rental cost $70/day þ insurance �0.131 0.145 0.366$90/day þ insurance 0.219 0.137 0.108

Auto – parking cost $5/day for day visitors;$15/night for overnightvisitors

0.024 0.115 0.833

$10/day for day visitors;$30/night for overnightvisitors

�0.008 0.115 0.948

Bus – travel time Same as automobile 0.145 0.101 0.15125% slower than automobile �0.075 0.101 0.461

Bus – one-waytravel cost

$50 �0.044 0.101 0.663$75 0.023 0.101 0.820

Bus – frequency Every 1 h �0.126 0.102 0.215Every 30 min �0.052 0.101 0.605

Bus – convenience Directly at accommodation �0.071 0.072 0.327

Train – travel time Same as automobile �0.019 0.105 0.85325% slower than automobile 0.038 0.105 0.715

Train – one-waytravel cost

$50 �0.110 0.106 0.301$75 �0.063 0.106 0.549

Train – frequency Twice/day 0.005 0.105 0.965Every 2 h �0.068 0.106 0.521

Train – convenience North Vancouver with freeshuttle from airport ordowntown

0.124 0.075 0.098

Intercept Private automobile 1.268 0.232 0.000Rental automobile 1.587 0.225 0.000Express bus 2.621 0.213 0.000Train 2.461 0.214 0.000

Log-likelihood �1115.682

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–73 71

experiment, skiers exhibited one main and somewhat surprisingaspect to their travel behaviour. The majority of them could not beinfluenced to switch away from the use of private vehicles, despitethe inclusion of several attribute configurations in the hypotheticalscenarios designed to encourage a shift to more fuel efficientalternatives. This resistance to switching even occurred when theattributes of the more conventional modes of travel (own car orrental car) became less attractive. None of the transportation

Table 3Mode choices in stated choice experiment.

Mode choice Total sample Short

Freq. % Freq.

Made tradeoffs betweenprivate and public modes

177 50.7 32

Chose only private modes 100 28.7 72Chose only public modes 70 20.1 8Chose only ‘‘would not go’’ 2 0.6 0

Total 349 100 112

attributes, including travel time, fuel costs or parking fees signifi-cantly influenced mode choices. Many respondents who hada dominant mode choice predisposition could not even bepersuaded to switch in the common set, which contained anextremely attractive public transit mode.

These results of skiers were especially surprising becausea related study of summer visitors to Whistler (conducted 9 monthsearlier) showed a rather different stated choice behaviour. Thesummer study’s findings clearly pointed to the promising capacityof several similar demand strategies to shift travellers to more eco-efficient travel modes (Kelly et al., 2007). If anything, the winter setof private vehicle transport attributes were less attractive thanthose for summer car travel. The winter survey version includedprivate vehicle transport attributes such as poor road conditions,increasing travel times, and fuel costs of $30 for a one-way trip(120 km) which was unheard of at the time of study in 2005. Yetthese changes still did not trigger respondents to significantly shiftfrom private vehicle to public transit modes.

As other studies have found (Dickinson & Dickinson, 2006), it ischallenging to entice travellers to willingly abandon their privatevehicle as long as long as it is available as an option. This is the casefor the majority of Whistler’s skiers. A number of issues conspire tomake public transport to Whistler inconvenient for short-haulvisitors. First, skiers must transport a considerable amount ofequipment (e.g., skis, boots, poles, helmet, outdoor clothing). Next,the skier must take either a private car or navigate the intra-urbanor local public transit with all their equipment to reach a pointwhere they can access public transit to Whistler (currently down-town Vancouver). If several skiers travel in one group, the publicoption becomes even less appealing as compared to travel byprivate vehicle. Their long-haul counterparts do not face the sameissues. These skiers basically have a choice between rental car andbus from the Vancouver International Airport. Their trade offbehaviour is more varied, but still very much dominated by pref-erence for a particular mode rather than preference for particularattributes.

The differences between actual mode used on respondents’ tripsand their stated preference in the discrete choice survey areinsightful (Tables 4 and 5). Short-haul visitors overwhelminglychose private modes for both their actual trip and their choices in

haul Long haul Chi-square(p value)

% Freq. %

28.6 145 61.2 103.859(0.000)

64.3 28 11.87.1 62 26.20.0 2 0.8

100 237 100

Table 5Comparison of actual travel mode and dominant stated choices for short-haul skiers.

Actual travel mode Stated choice in survey Chi-Square(p value)

Private Public

Freq. % Freq. %

Private mode 69 95.8 8 100.0 0.346 (0.556)Public mode 0 0.0 0 0.0Other 3 4.2 0 0.0

Total 72 100 8 100

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–7372

the discrete choice survey. However, the fact that 10% (n ¼ 8) of theshort-haul skiers who arrived by private vehicle consistently chosethe public transit option indicates that at least a small minority ofthese skiers is interested in switching. More importantly, thepotential for switching behaviour seems to be much larger for long-haul visitors. Of long-haul skiers, 57% (n ¼ 16) consistently choseprivate modes in the stated choice survey also traveled by privatemodes on their trip in 2005 (Table 4). However, 57% (n ¼ 35) oflong-haul skiers consistently chose public modes in the choicesurvey after having traveled to Whistler via private modes. Whenconsidering these findings with the fact that 61% of long-haultravellers actually considered trade-offs in the three choice sets(Table 3), it becomes clear that the best client group to be attractedto public transit are long-haul travellers flying into VancouverInternational Airport. This is an important finding for a worldrenowned destination like Whistler that has the proven capacity toattract travellers from international markets with a strongpropensity for making environmentally friendly behaviours (Wil-liams, Haider, & Reilly, 2006).

Table 6 also confirms the importance of focusing on the long-haul skiers. In the pro-transit common set, about 50% of long-haulskiers chose the public transit option, while very few decided notgo. Conversely, a decision that would limit the attraction of privatemodes of transportation seems to quickly affect the trip decision ofshort-haul travellers. A full 22% of them would no longer travel toWhistler in this context. If a private mode became as unattractive asit was in the common set, these respondents would most likelyconsider other ski resort alternatives.

From a conceptual perspective, it is clear that the most effectiveplace for destination managers to influence travel mode choices is atinter-modal transport hubs identified in Hill and Lundgren’s model(Hills & Lundgren, 1977). It is here where the largest (albeit limited)segment of travellers willing to shift transport modes exists.Destinations can help entice travellers to select more eco-efficientoptions in two primary ways. First, they can create travel packagesthat automatically incorporate public transit into the bundle ofproducts and services that comprise the travel experience. In thiscontext, transport mode choices are positioned as but one elementin a set of predetermined package attributes which collectivelypredispose customers to visit the destination. In some markets,focussing and promoting eco-efficient transportation options aspart of the destinations package will be perceived as creating

Table 6Mode choices in pro-transit common set.

Mode choice Totalsample

Short haul Long haul Chi-square(p value)

Freq. % Freq. % Freq. %

Private mode 165 47.3 55 49.1 110 46.4 48.885 (0.000)Public mode 151 43.3 32 28.6 119 50.2Would not go 33 9.5 25 22.3 8 3.4

Total 349 100 112 100 237 100

additional value for consumers. In other cases, it might be better tosimply highlight other ‘hassle free’ and value generating attributesof a package that includes a public mode of travel. In this instance,destinations might design and promote the hassle free, seamlessand cost effective advantages of available public transport options(Cullinane & Cullinane, 1999; Hine & Scott, 2000; Lumsdon, 2006)via brochures, websites or other promotional materials. This infor-mation may entice visitors to take public transit, as well as orientthem to the overriding environmentally friendly disposition of thedestination they are about to visit. In either the case the intent is toyield positive contributions to the destination’s tourism value chainfrom both eco-efficiency and consumer satisfaction perspectives.

Finally, given the challenges of shifting individuals out of theirown vehicles, formal regulation (e.g., more fuel efficient vehiclerequirements) is a policy option that should also be carefullyconsidered. While implementing this option is largely beyond thecontrol of destination managers, they can encourage and promotethe implementation of specific eco-efficient transport commandand control regimes by higher levels of government. Understandinghow such regimes should be best played out in specific contextsshould be an integral and growing part of the destination manag-er’s value chain management responsibility.

6. Conclusion

This research contributes to the growing literature associatedwith managing transportation-related energy consumption in thetourism system. Focussing on the travel behaviours of Whistler,BC’s skiing markets, it investigated the actual and hypotheticaltransport mode choices of skiers visiting the destination. Its find-ings suggest that for the most part, skiers as a travel market arerelatively firm in their preference for the use of private automobileswhen travelling to that destination. Few conventional eco-effi-ciency travel management options appear to alter this behaviour.This situation is especially apparent for short-haul skiers. Moreopportunities exist to shape the transport choices of long-haulskiers, specifically those who require an inter-modal transfer fromairplane into a regional travel system.

Understanding visitor preferences and behavioural intentions isan important initial step in developing the strategic programsneeded to effectively shift tourists to more eco-efficient transportmodes. Typically, destination managers do not play a significantrole in shaping the inter-urban transportation portions of tourismtravel. However, the structure of long-haul transportation to andfrom a destination has the potential to be directly impacted bydestination policy and planning decisions. As such, destinationmanagers have an unusual opportunity to influence the eco-effi-ciency of tourist travel for specific travel markets. Destinationmanagers need to reach long-haul tourists in the planning phase oftheir trip and to a lesser extent at key inter-modal transit hubs, inorder to effectively mould the flow of tourists in the tourismtransport system.

Given the case study format of this research, we are uncertain ofthe extent to which these findings are indicative of the behavioursof skiers in other winter resorts, other tourists to Whistler who arenot participating in skiing, and other types of travellers visitingother types of destinations. The situation may apply to similardestination resorts, for example ski resorts in Colorado vis-a-vistheir hub of Denver. Similar research exploring such relationshipsin other market and destination contexts would help to confirmand/or refine the theoretical and applied utility of the results.

Opportunities to more fully explore the transportation shiftingbehaviour of skiers also exist. In this study, respondents were askedto choose between attributes with levels that were at the outerextent of realistic levels (especially in the case of fuel costs).

J. Reilly et al. / Research in Transportation Economics 26 (2010) 66–73 73

However, because the research was conducted in the context ofa ‘live’ case study situation, options for exploring more extremeeco-efficiency options were confined by local political and fiscalrealities. As a consequence, the research findings failed to identifythe full range of incentives and impediments that might havealtered skier responses. Future research should explore moreextreme levels of the transportation attributes identified (time,speed, road conditions, etc.), as well as more futuristic and radicaltransport options (e.g., high speed trains, more convenient trans-port transfer points, etc.). Such extensions of the attributes assessedwould provide for a more robust analysis of the data collected.Researchers could apply these recommendations in a range ofwinter and other destination contexts to test the transferability ofthe findings presented here.

Finally, the interpretations of the findings presented in thispaper would have benefited from more qualitative explanation ofchoices provided by the skiers. By combining the quantitativeempirical evidence unearthed with more qualitative perspectives,a fuller appreciation of what is required to shift travellers to moreeco-efficient transport options might have emerged. Researchersconducting further research of this type are encouraged to incor-porate such qualitative explorations into their investigations.

Acknowledgements

Technical assistance from Simon Fraser University School ofResource and Environmental Management doctoral candidates JoeKelly and Ben Beardmore are gratefully acknowledged.

This research was funded by resources obtained from a standardCanadian Social Sciences and Humanities Research Grant. Thefunds were used to employ students in the survey design, datacollection, data analysis and writing stages of this broad researchprogram. This paper was one part of a larger set of discrete andcomplementary findings emanating from that work.

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