stated preferences of tourists for eco-efficient destination planning options

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Tourism Management 28 (2007) 377–390

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Research article

Stated preferences of tourists for eco-efficientdestination planning options

Joe Kelly�, Wolfgang Haider, Peter W. Williams, Krista Englund

School of Resource and Environmental Management, Simon Fraser University, Burnaby, BC, Canada V5A 1S6

Received 17 December 2005; received in revised form 12 April 2006; accepted 16 April 2006

Abstract

Eco-efficiency is a concept that prescribes reducing the amount of energy and natural resources used, as well as wastes and pollutants

discharged in the production of goods and services. Numerous approaches to achieving greater levels of eco-efficiency have been

suggested for tourism operations and destinations. However, none of these options have been examined with respect to tourist responses

to them. This paper uses a discrete choice experiment to examine visitor preferences for a set of hypothetical tourism destination eco-

efficiency strategies. Visitors preferred ‘‘eco-efficient’’ planning options to business-as-usual scenarios. The degree of support for the

various planning options differed by market segments. Overall, tourist support existed for many options that could increase the overall

eco-efficiency of destinations. Visitors were also willing to tolerate additional fees for services that might help to offset the environmental

impacts of their behaviours. By having respondents evaluate and trade-off several resort eco-efficiency strategies simultaneously, the

discrete choice experiment provided a more comprehensive and realistic assessment of eco-efficiency options than would be possible using

traditional survey methods.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Destination planning; Eco-efficiency; Stated choice methods

1. Introduction

A significant portion of the dialogue concerningsustainable tourism development centres on creating great-er eco-efficiency in tourism operations. Eco-efficiency is aconcept that prescribes reducing the amount of energy andnatural resources used, as well as wastes and pollutantsdischarged in the production of goods and services (Ayres,1998; Cleveland & Ruth, 1999; DeSimone & Popoff, 1997;Reijnders, 1998). Numerous approaches to achievinggreater levels of eco-efficiency have been suggested (e.g.Bode, Hapke, & Zisler, 2003; Dorward, 1990; Gunn, 1994;Inskeep, 1987, 1991; Quilici, 1998). These include usingmore environmentally friendly land use and buildingdesigns; sustainable recreation options; innovative trans-

e front matter r 2006 Elsevier Ltd. All rights reserved.

urman.2006.04.015

ing author. PH–2570 Spruce Street, Vancouver, BC,

P7. Tel.: +1 604 737 1100.

esses: [email protected] (J. Kelly),

(W. Haider), [email protected] (P.W. Williams),

ca (K. Englund).

portation infrastructure and service options; low-impactenergy generators; and enhanced solid waste managementsystems. A few of these options have been assessed in termsof their overall technical effectiveness in a tourism context.However, none have been examined with respect to touristresponses to them.For tourism destination planners and managers, the

challenge is to select and implement eco-efficient strategiesthat appeal to the tastes and interests of tourists whilemeeting the needs of community stakeholders. Decisions ofthis type are difficult because tourists’ opinions on eachpotential strategy are not always apparent. Eliciting theseopinions can be particularly difficult because of the diverseperspectives of tourists and their broad distribution aroundthe globe. While researchers have investigated touristpreferences concerning destination development choices(e.g. Haider & Ewing, 1990; Hearne & Salinas, 2002;Lindberg, Andersson, & Dellaert, 2001; Mercado &Lassoie, 2002), no study to date has evaluated tourists’perspectives concerning planning alternatives that promoteeco-efficiency. Such research would help inform planners

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ARTICLE IN PRESSJ. Kelly et al. / Tourism Management 28 (2007) 377–390378

and private investors about tourism market responses tovarious eco-efficient options and the subsequent viability ofsuch practices.

It is within this context that this study develops asystematic framework and associated method for evaluat-ing tourist preferences for eco-efficient destination plan-ning strategies. More specifically, it uses a discrete choiceexperiment (DCE) method to examine visitor preferencesfor land-use, transportation, recreation, and other envir-onmental initiatives intended to promote eco-efficiency intourism destinations. It applies the method in a case studyof visitors to Whistler, British Columbia, Canada. Thisfour-season mountain resort community has made a strongcommitment to becoming a more sustainable destination,which is reflected by a range of eco-efficiency strategiesincorporated in its development plans (Resort Municipalityof Whistler (RMOW), 2004). Although the research isconducted in Whistler, its findings can inform destinationplanners and managers in general about potential marketresponses to such eco-efficiency strategies.

2. Literature review

2.1. Development planning options

The tourism literature contains a wide variety of landdevelopment policies and planning strategies for achievinggreater levels of eco-efficiency. These include implementinga range of innovative zoning practices, growth manage-ment programs, and environmentally friendly buildingdesign standards. They also encompass instituting a varietyof economic instruments such as development impact fees,property tax abatements, housing subsidies, and financialincentives for infill and redevelopment programs (Inskeep,1987; Sweeting, Bruner, & Rosenfeld, 1999). In combina-tion, these strategies are designed to encourage the creationof more compact and mixed development patterns thatminimize travel distances, facilitate walking and cycling,and reduce the demand for energy, water services andbuilding materials (Gunn, 1994; Inskeep, 1987, 1991;Quilici, 1998). For instance, by increasing the stock ofaffordable housing in typically high cost tourism destina-tions, significant decreases in the levels of traffic conges-tion, energy consumption and fuel emissions associatedwith resort employees commuting to and from work maybe possible (Gober, McHugh, & Leclerc, 1993; Kirkpatrick& Reeser, 1976). Such forms of development are poten-tially more feasible in tourism destinations than in otherurban settings because tourists and residents may be moreaware of and concerned with the quality of the environ-mental amenities they experience in such places (Bauer &Chan, 2001).

2.2. Recreation management options

Many recreational activities in destinations consumelarge amounts of natural resources and produce significant

quantities of waste. In particular, activities such as golf(irrigation, fertilization, pest control), as well as motorizedland, water and air based recreational activities (fuelconsumption and emissions) all place stress on the overallcapacities of destination resources (Balogh, Gibealt,Walker, Kenna, & Snow, 1992; Becken & Simmons,2002). Recreation management options available foraddressing these issues include: prohibiting certain formsof resource intensive use; establishing and enforcingappropriate fuel use and efficiency standards; encouragingparticipation in less energy and resource intensive pursuits(e.g. cultural and educational activities); and establishingaccessible low impact recreation options (e.g. biking andhiking trail networks) that conserve resources and makethe destination more desirable, competitive and resilient tochanging market demands.

2.3. Transportation options

Several transportation service options are available forencouraging reductions in energy consumption and fuelemissions. These initiatives focus on reducing the use ofprivate vehicles for internal transportation purposes. Theyinclude: developing pedestrian and non-motorized vehiclepaths conducive to tourist and resident use (Inskeep, 1987,1991; Lumsdon, 2000); establishing no-vehicle zones, slowspeed areas and limited parking capacities that reduce theincentives to use cars (Holding, 2001); and creating publictransit fee structures that encourage visitors to shift fromprivate vehicle use to public modes of travel (Sweetinget al., 1999; Thrasher, Hickey, & Hudome, 2000). Suchinterventions are especially applicable for tourism destina-tions that want visitors to experience their communities ina more engaging and tactile fashion. Although it is unlikelythat planning solutions can completely eliminate the use ofprivate automobiles within destination areas, minimizingvehicle use can enhance the experience of tourists bydecreasing noise and pollution. Such actions can contributeto a more relaxed atmosphere and increasing recreationalopportunities (Sweeting et al., 1999).

2.4. Solid waste management options

Investing in environmentally sensitive solid waste man-agement systems that emphasize reuse, reduction, recyclingand composting can minimize the amount of waste sent tolandfills (Bergh, 1994; Sheehan, 1994; Sweeting et al.,1999). Options include: implementing waste exchanges andreuse centres; enhancing collection systems and drop-offfacilities for recyclable materials; establishing centralizedregional composting facilities; promoting commercial andpublic composting programs; instituting waste collectionand tipping fee programs at landfills; and increasing wastereduction promotional campaigns for residents, visitorsand businesses. All these options help to divert solid wasteaway from landfills, and reduce direct emissions ofgreenhouse gases from these sites.

ARTICLE IN PRESSJ. Kelly et al. / Tourism Management 28 (2007) 377–390 379

2.5. Renewable energy options

Reductions in greenhouse gases and other air contaminantscan result from investments in renewable energy supplysystems. Options for such initiatives include using localenergy power sources, such as wind and micro hydro plants(Bode et al., 2003); on-site energy sources, such as photo-voltaic equipment or ground source heat pumps, to supple-ment or substitute for other power supply methods (Chan &Lam, 2003); and public transit and other resort vehicles thatare powered from renewable energy sources such as hydrogenfuel cells (Bode et al., 2003). The development of suchpractices within the borders of a destination region has thepotential to not only reduce negative environmental andhealth impacts, but also create financial savings, localemployment opportunities and greater self-sufficiency.

2.6. Greenspace protection options

Protecting greenspace and intact ecosystems withindestinations can provide a number of eco-efficiencybenefits. These include air filtering (gas regulation),microclimate regulation, rainwater drainage control (waterregulation), and sewage treatment advantages (wastetreatment) (Bolund & Hunhammar, 1999). In addition,such protected areas can reduce carbon dioxide levels bysequestering and storing carbon dioxide and by coolingambient air and allowing residents to minimize annualheating and cooling requirements (Rowntree & Nowak,1991). From a tourism perspective, such actions may alsocontribute to increased biodiversity and aesthetic values, aswell as improved recreational opportunities for tourists.

2.7. Tourist preferences for eco-efficient destination

planning options

Successful implementation of the preceding options notonly requires innovative technical solutions, but also the

Table 1

Possible effects of eco-efficiency strategies on tourists

Potential positive effects

� More vibrant spaces and social interactions caused by compact

development

� Less aesthetically unappealing sprawl

� Convenient accessibility by foot and bike

� Less traffic congestion

� Less noise and light pollution from vehicles

� Enhanced transit services

� More access to certain recreational pursuits, such as educational and

cultural activities

� Less environmental pollution

� Fewer health problems

� Enhanced scenic quality of natural attractions and resources

� More intact natural areas and increased wildlife habitat

� Value in knowing the ‘‘right thing is being done’’

Sources: Bode et al. (2003); Gunn (1994); Holding (2001); Inskeep (1987, 199

(2000).

support of a wide range of stakeholders with varyinginterests (Gill & Williams, 1994; Haywood, 1988). Whiledecisions concerning destination planning options shouldbe driven by the values and priorities of local stakeholders,they should also be informed by the perspectives oftourists. This task is particularly difficult because touristsdo not typically reside in or near the destination (Gill &Williams, 1994).Eco-efficient planning strategies can impact travellers in

several different ways (Table 1). Visitors may perceivesome impacts as positive (e.g. less traffic congestion) andothers as negative (e.g. restricted automobile access).Clearly, some factors will be more important to touriststhan others. The net impact on their overall perception of adestination can be positive or negative depending on theparticular strategy deployed. Information concerning thesevisitor preference patterns can provide destination plannersand managers with useful insights about consumerresponses to potential eco-efficient policy and planningstrategies.A traveller’s perception of the preceding impacts usually

depends on their personal travel needs, motivations andvalues that they seek to satisfy (Seddighi & Theocharous,2002; Woodside & Dubelaar, 2002; Woodside & Lysonski,1989). Therefore, instead of responding with equalsatisfaction to a given planning alternative, various touristgroups may have very diverse reactions. Previous researchsuggests that visitor preferences vary systematically withrespect to several tourist characteristics (e.g. Apostolakis &Jaffry, 2005; Hearne & Salinas, 2002; Lindberg et al.,2001). These traits include: socio-demographic variables(e.g. gender, age, income and education), situationalvariables (e.g. place of residence), tourist destinationmotivations, and personal values and attitudes. Touristevaluations of destinations are also influenced by priordestination travel behaviour (Woodside & Dubelaar,2002). Particularly, visitor preferences can be affected by:travel party size, purpose of trip, length of stay, location

Potential negative effects

� Increased urbanization caused by compact development

� Reduced privacy and more crowding and noise

� Diminished viewscapes because of densification

� Restricted automobile access and parking

� Reduced safety because tourists must walk through car-free zones

� Diminished comfort caused by certain technologies (e.g. low-flow

showerheads)

� Less aesthetically pleasing landscaping methods (e.g. xeriscaping)

� Limited access to recreational activities, such as golfing and motorized

sports

� Redirected funds that might have been used for developing other

facilities or amenities

� Increased fees or taxes (e.g. parking fees)

1); Lumsdon (2000); Quilici (1998); Sweeting et al. (1999); Thrasher et al.


and type of accommodation and activities pursued duringthe visit. For instance, visitors who pursued motorizedsports during prior visits to a destination are likely todisapprove of proposed planning strategies that restrict orban those activities. Such preference heterogeneity presentschallenges to destination planners and managers, who mustdetermine whether the gains to some tourist segmentsoutweigh the losses to others.

3. Method

This study used a DCE to examine visitor preferences forland use, transportation, recreation and other environ-mental initiatives intended to promote eco-efficiency attourism destinations. DCEs collect and analyse individualpreference data to measure variations in choice behaviourunder varying scenarios or hypothetical situations (Lou-viere, Hensher, & Swait, 2000). Choice experiments areused widely in resource management problems andenvironmental valuation settings (Boxall, Adamowicz,Swait, Williams, & Louviere, 1996; Haider & Rasid,2002; Opaluch, Swallow, Weaver, Wessells, & Wichelns,1993), as well as in tourism and recreation contexts(Apostolakis & Jaffry, 2005; Crouch & Louviere, 2000;Louviere & Timmermans, 1990; Pettersson, 2002). Intourism, most studies involving DCEs have typicallyanalyzed: perceptions or images of recreational alterna-tives; preferences for tourism management alternativesinvolving hotels, restaurants and other amenities; ordestination choice behaviour (Crouch & Louviere, 2000;Louviere & Timmermans, 1990). Only a few studies haveused DCEs to analyse preferences or to evaluate the overallacceptability of different destination planning options (e.g.Hearne & Salinas, 2002; Lindberg, Dellaert, & Rassing,1999; Lindberg et al., 2001). Findings emanating fromthose studies illustrate the utility of the multi-attributeDCE technique in systematically examining stakeholderperspectives concerning the acceptability of and prefer-ences for multi-dimensional planning scenarios. However,no study to date has used a DCE to evaluate visitorpreferences concerning eco-efficient destination planningoptions. Such a multivariate investigation would not onlyprovide invaluable insights for key stakeholders involved inplanning processes, but also inform planners and privateinvestors about the viability of eco-efficient planningstrategies from a tourist perspective.

This study used an on-line survey instrument toadminister the DCE. The use of the Internet allowed arelatively complex and lengthy survey to be presented in avisually attractive and entertaining way. These featureshelped keep respondents engaged throughout the entiresurvey. Only 8.6% of respondents quit the survey beforecompleting all sections. The Web also enabled the surveydesign to be dynamic and adaptable. For instance, severalsurvey questions were tailored to individual respondentsbased on specific characteristics (e.g. whether or not they

were an overnight or day visitor). The Web also allowedfor a very efficient and reliable data entry.The survey was developed based on information gleaned

from existing literature, as well as input gained fromdestination planners and managers in Whistler. The finalsurvey instrument contained questions involving the DCE,as well as several other questions relating to previous tripcharacteristics, tourist destination motivations, and socio-demographic characteristics of the respondents. The surveyalso contained several ‘‘learning questions’’ that precededthe DCE. These basic opinion questions asked respondentsto indicate their preferred level of each attribute included inthe DCE. While the responses to these questions providedvaluable information about visitor preferences by them-selves, their main purpose was to familiarize the respon-dents with the attributes and levels that were included inthe DCE.In the DCE section of the survey, respondents were

shown three choice sets, each containing a pair ofhypothetical mountain resorts. For each pair, respondentswere asked to choose their preferred resort on a scaleprovided at the bottom (Fig. 1). Since the scale did notcontain a mid-point (or indifference point), each respon-dent had to choose one alternative over the other. The scalesimply provided an opportunity for respondents to indicatethe strength of their preference. This response task issimilar to ones used by Johnson and Desvousges (1997)and Johnston and Swallow (1999). Respondents were toldto imagine a mountain resort with a maximum capacity of50,000 people (including visitors, residents and secondhome owners). This was about the same size as Whistler—the destination they had all visited prior to the DCEsurvey.The hypothetical resorts were described in terms of

several attributes related to developed land, recreationalopportunities, local transportation, and environmentalinitiatives (Table 2). These attributes were defined a priorias being (1) important determinants of eco-efficiency, (2)relevant for a tourist, and (3) within the influence ofplanners or other stakeholders at the destination. Thelevels for each attribute provided sufficient variation tomatter for tourists and to allow for the simulation ofcurrent and potential conditions. The final set of attributesand levels was determined through a process involving areview of academic literature and stakeholder feedback. Tomake the scenarios realistic, an attribute was included todescribe a potential environmental fee that would becharged to help cover the cost of implementing environ-mental initiatives at the resort. The inclusion of such a‘‘payment vehicle’’ is common practice in DCEs (Louviereet al., 2000).

3.1. Experimental design

Experimental design techniques were used to generatethe combination of attribute levels explored in each choiceset (Louviere et al., 2000). A full factorial design involving

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Fig. 1. Format of choice task for an overnight visitor.

J. Kelly et al. / Tourism Management 28 (2007) 377–390 381

all possible combinations of attributes and levels wouldhave allowed all main and interaction effects to beestimated. However, the impracticality of such an ap-proach meant that the profiles in the choice sets weregenerated by using an orthogonal fractional factorialdesign that contained only a small subset of all possiblecombinations of attributes and levels. A Resolution IIImain effects design plan required 54 unique choice sets(Montgomery, 2001), which were split into 18 versions ofthree choice sets each. Each respondent evaluated one ofthese versions. These designs allowed efficient estimation ofmain effects only.

3.2. Data collection

Respondents for the survey consisted of summer visitorswho were personally recruited during their trip to Whistlerin August or September 2004. These individuals wereintercepted on a daily basis at strategic locations inWhistler. Proportionally more visitors were interceptedon Saturday and Sunday than on other days, whichreplicated the actual visitation patterns in the destination.Specific selection procedures were applied to ensurerandomness.

A total of 2016 visitors over 19 years of age wererecruited using this method. These individuals completed aone-page questionnaire that screened out resort employeesor residents, and ensured the sample was representative ofthe overall population of summer visitors. Additionally,individuals were asked for an email address where theycould be contacted to complete a more comprehensiveonline survey after their visit was finished. All recruited

individuals received a token gift in appreciation of theirparticipation. This gift was also intended to providerespondents with an incentive to participate in the lateronline survey.The online survey was pretested twice with a few

individuals from the recruited sample. Both tests led tosubsequent refinements to the online survey instrument. Alink to the final web survey was sent to all recruitedindividuals in an email. Overall, 1825 emails (91%) weredelivered to respondents. To encourage completion of thesurvey, respondents were given the option to enter a drawfor various prizes.Of the 1825 surveys initially delivered 876 were

completed for a 48% return rate. This compared favour-ably with response rates reported in other web-basedsurvey research (Cho & LaRose, 1999). Consistent withother web surveys, the response time for this survey wasquick (McCabe, Boyd, Couper, Crawford, & d’Arcy, 2002;Schaefer & Dillman, 1998). Over half (56%) of allresponses were received within the first three days of theinitial mailing of the link.

3.3. Data analysis

This study used the traditional Multinomial Logit(MNL) model to analyse the data collected from theDCE. Analytical procedures for estimating the choiceprobabilities as suggested by Ben-Akiva and Lerman(1985) and Louviere et al. (2000) were used.A limitation of the MNL modelling approach is that it

does not account for systematic variation in preferencesamong individuals. Such preference heterogeneity means

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Table 2

Resort attributes and levels

Attributes Levels

Development

Form of development 1. Compact (1200 acre developed, high density)

2. Nodal (1700 acre developed, moderate density)

3. Dispersed (2500 acre developed, low density)

Percent of workforce living in host community 1. 25%

2. 75%

3. 100%

Recreational opportunities

Availability of cultural and educational activities 1. Limited (only a few cultural and educational activities available)

2. Extensive (many cultural and educational activities available)

Extent of trail system in natural areas 1. Moderate (few trails of different degrees of difficulty, encounters with others common)

2. Extensive (many trails of different degrees of difficulty, encounters with others uncommon)

Availability of motorized sports 1. Not available

2. Available at base of hill

Availability of golf courses 1. One

2. Two

3. Three or more

Private automobile

Automobile accessibility 1. Private vehicles allowed everywhere

2. Private vehicles not allowed in village core area

3. Private vehicles not allowed anywhere within the resort boundaries (parking at resort entrance with

connecting shuttles)

Parking fees 1. Free

2. $5/day for day visitors and $15/night for overnight visitors

3. $10/day for day visitors $30/night for overnight visitors

Local transit bus service

Availability of bus 1. Not available

2. Limited accessibility (a few key routes serviced with moderate frequency)

3. Extensive accessibility (many routes with frequent service)

Bus fare 1. Free

2. $1.50

3. $3.00

Environmental initiatives

Amount of protected area 1. 5%

2. 20%

3. 35%

Percent of energy requirements met with renewable sources 1. 25%

2. 50%

3. 75%

Percent of waste recycled and composted 1. None

2. 25% of waste recycled

3. 50% of waste recycled

Environmental fee 1. None

2. 2% environmental fee

3. 4% environmental fee

J. Kelly et al. / Tourism Management 28 (2007) 377–390382

that choice probabilities will differ systematically amongstindividuals even though the choice alternatives areidentical. Therefore, the choice model was expanded to

include relevant attributes relating to the individual. Thisapproach extended the traditional MNL model to asystematic heterogeneous specification, which is not


uncommon in tourism contexts (e.g. Apostolakis & Jaffry,2005; Breffle & Morey, 2000; Huybers & Bennett, 2000;Lindberg et al., 1999). In this study, several individualcharacteristics were tested but were rejected for the finalchoice model. These included socio-demographic variables(e.g. gender, age, income, education), situational variables(e.g. place of residence), prior trip characteristics (e.g.travel party size, purpose of trip) and tourist destinationmotivations. The only significant interaction at the90% confidence level was observed between the availabilityof motorized sports and previous engagement in thatactivity.

Using the LIMDEP 8.0 software package (Greene,2002), maximum likelihood procedures were used toestimate the parameters of the choice model, in whichrespondents choose between resorts A and B. We alsotested a MNL model in which the responses were weightedby strength of preference, but the simple choice model hada better fit and more plausible parameter estimates; hence itwas retained for the discussion in this paper. All categoricalattributes (e.g. form of development) were effects codedand numerical attributes were linear and quadratic coded(Louviere et al., 2000). In the final model the quadraticterms were dropped if they were not significant at the 90%confidence level.

The estimated model was used to predict choicebehaviour in response to changes in attribute levels. Byadjusting the attribute levels in the choice model, it waspossible to evaluate tourist preferences for various eco-efficient planning strategies. These options included im-plementing compact and mixed development patterns;affordable employee housing programs to increase thenumber of employees residing within resort boundaries;low impact cultural and educational activities; an extensivenature trail system to help offset the demand for resource-intensive activities; limits to the number of golf courses;regulations for motorized sports; private automobilerestrictions and parking fees; local public transit services;greenspace protection; increased renewable energy sources;waste recycling and composting initiatives; and environ-mental fees to help fund local environmental initiatives. Inthis context, the estimated effects of implementing theseeco-efficient strategies were compared with the impacts ofemploying more resource intensive strategies or alterna-tively continuing with a current business-as-usual path(Table 3). This list of planning scenarios was not meant tobe exhaustive. It rather served to illustrate the range ofconditions possible at a resort destination like Whistler.

4. Findings

Table 4 presents the results of the DCE for overnightand day visitors separately. They describe visitor prefer-ences for land use, transportation, recreation and otherenvironmental initiatives intended to promote eco-effi-ciency.

4.1. Development

The form of development in the resort (compact, multi-centred or dispersed) significantly affected the preferencesof overnight visitors (Fig. 2). In particular, they were morelikely to prefer a nodal development form to compact ordispersed forms. Day visitors were indifferent to the formof development.Overnight tourists tended to prefer resorts with lower

percentages of the workforce living in the community(Fig. 2). They preferred separation from at least someresort employees even if it resulted in more employeecommuting, air pollution and congestion on the roads. Dayvisitors did not express a need for this form of separation.

4.2. Recreational opportunities

Overnight visitors generally preferred extensive culturaland educational opportunities to limited ones. Suchactivities include: museums, historic sites, interpretive sitesand demonstration projects. Day visitors did not have astrong preference concerning the availability of culturaland educational opportunities in the destination (Fig. 3).Overnight tourists were more inclined to prefer an

extensive nature trail system to a moderate one (Fig. 3).This system includes gravel or dirt trails for hiking andmountain biking through forested areas, grasslands andother undeveloped areas in the resort. Conversely, dayvisitors were indifferent to the extensiveness of the trailsystem. Although day tourists were impartial to the level oftrail extensiveness, it is possible that the two attribute levelstested (extensive/moderate) were not distinct enough toelicit a substantial difference in preference. A level less than‘‘moderate’’ was not tested in this study.Both overnight and day visitors were indifferent to the

availability of motorized sports (e.g. ATV or Hummertours). However, some tourist groups preferred thatmotorized sports be available, while others did not wantthese activities to be permitted within resort boundaries.These individual differences are explored later in the paper.Similarly, there was little difference in visitor preference

for the number of golf courses at the resort. Overnighttourists were impartial to the number of golf courses,whereas day visitors tended to favour fewer courses.

4.3. Transportation

Tourists preferred some restrictions on automobile use,although they did not want complete vehicle restrictions inthe resort community (Fig. 4). In particular, visitors tendedto prefer resorts where private automobiles were notallowed in the main village area, but were permitted inall other areas of the resort. Overnight tourists were far lessinclined to prefer resorts where private vehicles were notallowed anywhere within resort boundaries. In this case,visitors would be obliged to take free shuttles from asatellite parking lot located approximately 10 km from the

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Table 3

Comparison of planning scenarios examined

Attributes BAU scenario Eco-efficient scenario Resource intensive scenario

Development

Form of development Nodal Compact Dispersed

Percent of workforce living in host community 75% 100% 25%

Recreational opportunities

Availability of cultural and educational

activities

Limited Extensive Limited

Extent of trail system in natural areas Extensive Extensive Moderate

Availability of motorized sports Available at base of hill Not available Available at base of hill

Availability of golf courses 3 or more 1 3 or more

Private Automobile

Automobile accessibility Private vehicles not allowed in

village core area

Private vehicles not allowed

anywhere within the resort

boundaries

Private vehicles allowed

everywhere

Parking fees Free for day visitors and $15/

night for overnight visitors

$10/day for day visitors and

$30/night for overnight visitors

Free

Local transit bus service

Availability of bus Extensive accessibility Extensive accessibility Not available

Bus fare $1.50 Free —

Environmental initiatives

Amount of protected area 5% 35% 5%

Percent of energy requirements met with

renewable sources

50% 75% 25%

Percent of waste recycled and composted 25% 50% 0%

Environmental fee None 4% None


main village area. While this scenario is clearly the mostaggressive from an eco-efficiency perspective, it was theleast desirable amongst overnight tourists.

Tourists tended to prefer resorts with no or low parkingfees to those with high charges (Fig. 4). Their preference forspecific resorts significantly decreased as parking feesexceeded $5/day for day visitors and $15/night for over-night visitors. However, respondents were essentiallyindifferent between free parking and fees of $5/day forday visitors and $15/night for overnight tourists. Thesefindings suggest that visitors may actually tolerate lowparking fees used to improve transportation infrastructureand provide alternative modes of transportation in theresort (e.g. local transit). However, visitor acceptance levelsdeclined rapidly as the fees escalated beyond those levels.

The availability of local bus service was one of themore important determinants of visitor preferences forresort destinations. Both overnight and day visitorssignificantly preferred limited or extensive service to noneat all (Fig. 4). These results suggest there is a high level ofsupport for local bus service in resort destinations. Withrespect to fare levels, overnight visitors were more likely toprefer a bus fare of $1.50 to either $3.00 or no fare(Fig. 4). Conversely, day visitors were completely indiffer-ent to bus fare levels. These results suggest that visitors arewilling to pay a reasonable fare to ensure that bus service isavailable.

4.4. Environmental initiatives

Both overnight and day visitors tended to prefer resortswith higher percentages of protected landscape (Fig. 5).This land would be set aside to preserve wildlife habitatand ecologically valuable areas, such as wetlands andhabitat for rare species. No future development and norecreation access would be permitted in protected areas.Day visitors also preferred that a large percentage of a

resort’s energy requirements be met with renewablesources, such as wind, hydroelectric and geothermal.Evidently, day tourists benefit from knowing that a resortuses renewable sources to meet its energy needs. Theseenergy sources emit less pollution than non-renewablesources such as fossil fuels. Overnight visitors did not havea strong preference concerning the percent of energyrequirements met with renewable sources.The level of waste recycling/composting was one of the

more important determinants of overall resort preference.Both overnight and day tourists preferred resorts thatrecycled and composted higher percentages of waste. Thesefindings suggest fairly strong visitor support for actions toimprove recycling and composting programs in resortdestinations.Respondents were willing to tolerate an environmental

fee added to their accommodation, restaurant and activitybills. The revenues generated from this tax would not be

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Table 4

Summary of choice model findings

Model 1: Overnight visitors Model 2: Day visitors

Attribute Term Coefficient Standard error Coefficient Standard error

Form of development Compact �0.077 �0.161

Nodal 0.102�� 0.051 0.062 0.104

Dispersed �0.025 0.051 0.098 0.109

Percent of workforce living in resort Linear �0.028�� 0.012 0.000 0.025

Availability of cultural and educational opportunities Limited �0.146 �0.076

Extensive 0.146�� 0.038 0.076 0.074

Extent of trail system Moderate �0.077 0.060

Extensive 0.077�� 0.036 �0.060 0.074

Availability of motorized sports Not available �0.037 0.048

Available at base of hill 0.037 0.040 �0.048 0.080

Availability of golf courses Linear 0.017 0.043 �0.159* 0.097

Automobile accessibility Allowed everywhere �0.040 �0.194

Not allowed in village 0.247�� 0.052 0.289�� 0.118

Not allowed anywhere �0.206�� 0.052 �0.095 0.114

Parking fee Linear �0.279�� 0.044 �0.218�� 0.096

Quadratic �0.066�� 0.026 �0.133�� 0.054

Bus availability Not available �0.475 �0.341

Limited accessibility 0.230�� 0.051 0.149 0.112

Extensive accessibility 0.245�� 0.052 0.193� 0.111

Bus fare Linear �0.078� 0.045 0.009 0.098

Quadratic �0.071�� 0.025 N.I.

Amount of protected area Linear 0.181�� 0.045 0.298�� 0.090

Quadratic �0.087�� 0.025 N.I.

Percent renewable energy Linear 0.052 0.044 0.252�� 0.089

Percent waste recycled Linear 0.327�� 0.037 0.542�� 0.079

Quadratic �0.081�� 0.020 �0.124�� 0.042

Environmental fee Linear 0.021 0.036 �0.039 0.076

Availability of motorized sports�Previous use Available � Previous use 0.248� 0.139 0.913� 0.472

Observations 1868 491

Log Likelihood �1134.9 �284.0

Rho-Square 0.123 0.165

N.I. ¼ Not included.�P-valueo0.10.��P-valueo0.05.��P-valueo0.01.


used for any purpose other than local environmentalinitiatives. Both overnight and day visitors were willing toaccept an environmental tax of 2%, and even 4%, chargedto their accommodation, restaurant and activity bills(Fig. 5).

4.5. Individual characteristics

To account for varying preferences among touristsegments, the choice models examined how the individualcharacteristics of respondents influenced visitor preferencesfor destination planning attributes. The findings indicatedthat visitors’ previous trip behaviour significantly affectedtheir preferences for certain destination characteristics.

This result is consistent with previous research (Woodside& Dubelaar, 2002).It is not surprising that visitors who participated in

motorized sports during their last trip to Whistler stronglypreferred that motorized sports be available in thedestination (Fig. 6). For this tourist segment, the avail-ability of motorized sports was one of the most importantfactors influencing their preference for a specific resort.Conversely, visitors who did not pursue this activity werecompletely indifferent to the availability of motorizedsports. While several other individual characteristics weretested for their impact on visitor preferences, they are notreported because they were not significant at the 90%confidence level.

ARTICLE IN PRESS

Form of Development

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

Compact Nodal Dispersed

Par

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orth

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ity

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ity

Overnight Visitors Day Only Visitors

Percent of Workforce Living in Resort

25% 50% 75% 100%


Fig. 2. DCE results: relative preferences for development related attributes.

Availability of Cultural and Educational

Opportunities

-0.8

-0.2-0.4-0.6

0.00.20.40.60.8

Limited Extensive

Par

t-W

orth

Util

ity

-0.8

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-0.6

0.0

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ity


Extent of Trail System

Moderate Extensive


Fig. 3. DCE results: relative preferences for recreational attributes.


4.6. Modelling visitor preferences for eco-efficient planning

alternatives

A key benefit of conducting a DCE is that entireplanning scenarios can be evaluated from a visitorperspective. By selecting specific combinations of attributelevels, it is possible to evaluate various planning scenariosin terms of their acceptance by tourists. The studycompared preferences for a ‘‘business-as-usual’’ (BAU)scenario based on Whistler’s current conditions to an ‘‘eco-efficient’’ option in which all attributes were set to theirmost efficient levels. Overall, a sizeable share of touristspreferred the eco-efficient planning scenario to the BAUscenario (Table 5). The BAU scenario was also comparedto a ‘‘resource intensive’’ scenario, in which all attributeswere set to their least efficient levels. Overall, the resourceintensive scenario was far less favoured than the BAUscenario (Table 6).

Some significant differences in preferences emergedbetween overnight and day visitors. Whereas day touristswere much more likely to prefer the eco-efficient scenarioto the BAU scenario, overnight visitors were more inclinedto prefer the BAU option. Day visitors, whose trips haveshorter durations, may not be as inconvenienced bypotential adverse impacts associated with the eco-efficientscenario (e.g. increased parking fees, more restrictedautomobile access, fewer golf courses, lower cumulative

environmental fees, etc.) Also, day visitors may favourenvironmentally sensitive planning strategies because theyare often repeat visitors from British Columbia, who have avested interest in protecting the natural environment ofWhistler.

5. Conclusion

The purpose of this study was to evaluate visitorperspectives of eco-efficient destination planning options.A DCE explored the preferences of tourists for land-use,transportation, recreation and other environmental initia-tives intended to promote eco-efficiency at destinationresorts. By allowing respondents to evaluate and trade-offseveral attributes simultaneously, the discrete choice surveyprovided a more comprehensive assessment of visitorpreferences than traditional opinion surveys that askrespondents about attributes one at a time.The choice experiment results were used to test the

preferences for various destination planning and manage-ment scenarios. Overall, significant tourist support existedfor options that could increase the overall eco-efficiency ofdestinations. While a destination’s existing revenue streams(e.g. property taxes, development fees, accommodationtaxes) may cover some of the costs associated withimplementing proposed eco-efficient planning strategies,additional new and innovative sources of revenue may also

ARTICLE IN PRESS

Automobile Accessibility

-0.8-0.6-0.4-0.20.00.20.40.60.8

Allowedeverywhere

Not allowed invillage

Not allowedanywhere

Par

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Util

ity

-0.8-0.6-0.4-0.20.00.20.40.60.8

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ity

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Overnight Visitors Day Only Visitors Overnight Visitors Day Only Visitors


Parking Fee

$0 $5 $10 $15 $20 $25 $30

Bus Fare

$0.00 $1.50 $3.00

Bus Availability

Not available Limitedaccessibility

Extensiveaccessibility

Fig. 4. DCE results: relative preferences for transportation related attributes.

Amount of Protected Area

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0.0

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5% 20% 35%

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ity

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ity

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ity

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Percent of Energy Requirements metwith Renewable Sources

25% 50% 75%

Percent of Waste Recycled orComposted

0% 25% 50%

Environmental Fee

0% 2% 4%

Fig. 5. DCE results: relative preferences for environmental initiative attributes.


ARTICLE IN PRESS

Availability of Motorized Sports

(Overnight Visitors)

-1.0-0.8-0.6-0.4-0.20.00.20.40.60.81.0

Not available Available at base of hill Not available Available at base of hill

Par

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orth

Util

ity

-1.0-0.8-0.6-0.4-0.20.00.20.40.60.81.0

Par

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orth

Util

ity

Participated in Motorized Sports Did Not Participate Participated in Motorized Sports Did Not Participate

Availability of Motorized Sports

(Day Visitors)

Fig. 6. DCE results: effects of previous use on relative preferences.

Table 5

Visitor preferences for eco-efficient scenario

Overnight

visitors (%)

Day visitors

(%)

Total

(%)

Prefer eco-efficient scenario 34.7 59.8 42.3

Prefer BAU scenario 65.3 40.2 57.7

Total 100.0 100.0 100.0

Table 6

Visitor preferences for resource intensive scenario

Overnight

visitors (%)

Day visitors

(%)

Total

(%)

Prefer resource intensive

scenario

13.9 11.6 13.2

Prefer BAU 86.1 88.4 86.8

Total 100.0 100.0 100.0


be required. Several visitor revenue options were includedin the survey: (1) an environmental tax charged to touristsas part of their accommodation, restaurant and activitybills, (2) parking fees at the destination and (3) increasedtransit fares. Overall, visitors tolerated the introduction ofsome fees. However, their acceptance levels declinedrapidly as the fees became excessive. These results areconsistent with previous research that showed tourists arewilling to pay a reasonable amount of money for certainenvironmental measures (e.g. Mercado & Lassoie, 2002).While this study’s findings indicate that visitors maysupport the introduction of some limited fees, it does notnecessarily mean that they will change their own resourceconsumption behaviour (e.g. stop using private vehicles toget around the destination). However, even if these feeshave little influence on visitor behaviour, they mightprovide additional revenues to help offset the environ-mental impacts of tourist behaviours.

Since this study’s findings are based on the responses ofvisitors to a specific tourism destination, it is misleading to

draw broad conclusions from the results. While theresearch partially addressed this issue by presenting choicesituations involving hypothetical resorts, the extent that thefindings can be generalized is limited because (1) visitorswere told that these resorts were mountain destinations andabout the same size as Whistler, and (2) only Whistlertourists completed these choice tasks. As such, the choiceexperiment results may not apply to different types ofresort destinations (e.g. island or coastal destinations) orvisitors (e.g. cultural tourists). Applications of the methodin other mountain destinations would serve to confirm ormodify the accuracy of the findings generated by this work.The methodology developed in this research offers

destination planners and managers a valuable tool forevaluating tourist preferences for complex and multi-faceted planning issues. It is particularly relevant intourism situations where proposed policy and planningoptions can be evaluated before alternatives are imple-mented. The method provides a useful means of elicitingthe perspectives of tourists for decision-making purposes.Examining the usefulness of this approach from theperspective of local stakeholders and decision makerswould help to define what attributes and levels should beideally included in such analyses.Visitor preferences for eco-efficient planning options

should be examined in different types of tourism destina-tions in different seasons. Comparative studies woulddetermine if tourist preferences were stable between certainuser segments, as well as between various destinationcharacteristics (e.g. geographic location, managementstructure, destination lifecycle phase).Future studies should include a broader assessment of

external factors (e.g. weather conditions, macro economicand technological circumstances) that may influence visitorpreferences. Even though these factors are largely outsidethe control of local decision-makers, it is important tounderstand how they either facilitate or constrain potentialeco-efficient planning strategies.Finally, new research should examine the propensity of

private-sector agents to pay additional taxes or fees tofund eco-efficient planning strategies. Complementarystudies might evaluate the financial incentives needed for


individuals and firms to change their resource consumptionbehaviour.

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