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Integrated planning for sustainabletourism and mobility. A tourism trafficanalysis in Italy's South Tyrol regionAnna Scuttari a , Maria Della Lucia b & Umberto Martini ba Institute for Regional Development and Location Management,European Academy of Bolzano (EURAC Research) , Bolzano , Italyb Department of Economics and Management , University ofTrento , Trento , ItalyPublished online: 23 Apr 2013.

To cite this article: Anna Scuttari , Maria Della Lucia & Umberto Martini (2013): Integratedplanning for sustainable tourism and mobility. A tourism traffic analysis in Italy's South Tyrol region,Journal of Sustainable Tourism, 21:4, 614-637

To link to this article: http://dx.doi.org/10.1080/09669582.2013.786083

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Journal of Sustainable Tourism, 2013Vol. 21, No. 4, 614–637, http://dx.doi.org/10.1080/09669582.2013.786083

Integrated planning for sustainable tourism and mobility. A tourismtraffic analysis in Italy’s South Tyrol region

Anna Scuttaria, Maria Della Luciab∗ and Umberto Martinib

aInstitute for Regional Development and Location Management, European Academy of Bolzano(EURAC Research), Bolzano, Italy; bDepartment of Economics and Management, University ofTrento, Trento, Italy

(Received 1 October 2012; final version received 11 March 2013)

Emerging tourist market trends are compelling destinations to consider mobility as anessential strategic component of sustainable tourism planning. Tourism mobility analysisis a tool available to policy-makers when developing integrated and effective sustain-able transport and tourism policies. This paper introduces an innovative tourism-trafficanalysis based on survey techniques which allows the identification of tourism-relatedcomponents and an estimate of their environmental impact on a destination, informa-tion critical to the development of appropriate mobility management measures. Thismethodology was implemented in Italy’s South Tyrol region, an alpine province at theforefront of sustainable tourism and mobility innovation. The significant environmentalimpact of tourism traffic revealed in the destination justifies the innovative steps takentoward sustainable mobility in two pilot case studies covering eight communities. Anexploratory desk analysis shows that neither the push – encouraging sustainable behav-ior – nor the pull – discouraging unsustainable practices – mobility measures adoptedin these pilot areas decreased tourism flows; however, they did succeed in providingmore environmentally sustainable means of transport, with reduced emissions. And ina majority of cases, tourism flows increased above the regional average. A range ofproblems with the existing methodology are described, along with key issues for futureresearch.

Keywords: sustainable mobility; tourism planning; tourism traffic analysis;environmental impact; mobility management measures

Introduction

Emerging economic, political, environmental, technological, demographic and social mar-ket trends are prompting the tourist industry, like others, to consider increasing the sus-tainability of its development model (Dwyer, Edwards, Mistilis, Roman, & Scott, 2009;Gossling, 2009; Weaver, 2000, 2012). An appropriate balance between the economic ben-efits of tourism and its impacts on the environment and nonrenewable resources must befound if destinations are to retain their competitive advantage in terms of attracting visi-tor flows, differentiation from competitors, quality of tourist experience and local citizenwell-being (Inskeep, 1991; Swarbrooke, 1999). Mobility is a vital component in restruc-turing and re-qualifying a destination’s strategy, since without mobility infrastructure andservices, there cannot be any tourism and because mobility strongly impacts on the des-tination’s economic, environmental and social sustainability. Growing awareness of theseissues across society (Pine & Gilmore, 1999) means that more tourists (and residents) areconsidering ethical and eco-friendly solutions, in transport as elsewhere (Barra & Prillwitz,

∗Corresponding author. Email: maria.dellalucia@unitn.it

C© 2013 Taylor & Francis

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2012; Kelly, Haider, Williams, & Englund, 2007; Yeoman, 2005). The offer of sustain-able mobility (Black, 1996) may therefore be an opportunity to differentiate a destinationfrom its rivals (Schiefelsbusch, Jain, Schafer, & Muller, 2007) and attract emerging andincreasing segments of sustainable demand (Franch, Martini, Buffa, & Parisi, 2008).

The development of sustainable mobility infrastructure and services which add valueto the travel and tourism experience is becoming an ethical imperative from the sustain-ability perspective and is both an opportunity and a challenge for destination management(Dickinson & Robbins, 2007; Lumsdon, 2006). This can be a special challenge in des-tinations, including some community tourism destinations, with diverse interests, aims,competences and values across a range of public and private stakeholders, making co-ordination and decision-making difficult (Bieger, 1998, 2005; Flagestadt & Hope, 2001;Murphy, 1985).

Despite the strategic links between sustainable tourism planning and mobility man-agement, the two have long been treated as separate issues, both in the literature and inpractice (Haldrup, 2004; Page, 2005; Pechlaner, Pichler, & Herntrei, 2012). In recent years,the literature has explored their convergence, but few case studies exist, particularly at theregional level (Lumsdon, Downward, & Rhoden, 2006). This paper presents a case studyof the Italian Autonomous Province of Bolzano – South Tyrol, an Alpine region which is apioneer in sustainable tourism and mobility (Business Location Sudtirol, 2012). The paperproposes an innovative tourism traffic analysis based on survey-techniques and the assess-ment of the environmental impact of internal tourism mobility; it also evaluates the effectson tourist demand for mobility management measures designed to steer destinations towardsustainable visitor mobility.

The paper’s first section introduces sustainable tourism mobility and positions it betweenmobility management and destination management studies. The second and third sectionsdescribe South Tyrol and the methodology applied to tourism traffic analysis, environmentalimpact estimation and the assessment of mobility measures. The fourth section presentsresults from the analysis; the final section discusses the results, the study’s strengths andthe weaknesses and issues for future research.

Theoretical background

Management studies in the tourism and transport sectors have traditionally been separate.The role of transport in tourism management was almost ignored in developing mod-els and frameworks (Hall, 1999; Pechlaner, Pichler, & Herntrei, 2012), because mobilitywas considered a prerequisite for – rather than an integral part of – tourism development(Aronsson, 1997; Debbage, 1991; Haldrup, 2004). Equally, mobility solutions were seenin terms of physical infrastructure investments rather than issues of traveler management(Lumsdon et al., 2006). From this perspective, transport infrastructure provision is a prereq-uisite for allowing access to, and mobility around, a place and the efficiency of the transportsystem is a core issue for effective investment decision-making in the tourism sector (Chew,1987; Khadaroo & Seetanah, 2006). When the sustainability paradigm was introduced, boththe tourism and the transport sectors acknowledged it as an inspiring principle to aim to-ward, potentially achieving environmental protection, efficiency and fairness. Accordingly,significant changes occurred in approaches to mobility on both sides. The transport sectorshifted from the idea of “traffic system management” (Beckmann & Witte, 2003) to thatof “mobility (or travel demand) management”. This approach involved new partnershipsand tools to support and encourage changes of attitude and behavior in favor of both moresustainable modes of transport and alternatives to travel (Gronau & Kagermeier, 2004).

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In parallel, the tourism sector made mobility management an integral part of sustainabletourism and territorial planning, recognizing the imperative to satisfy current transport andmobility needs without compromising the ability of future generations to meet their needs(Black, 1996).

This change of perspective has drawn the tourism and transport disciplines closertogether; they agree that sustainable tourism mobility can minimize the negative impactsof tourism on the environment, economy and society, while still aiming to satisfy visitors’and residents’ needs. Such convergence allows the framing of sustainable tourism mobilityfrom a perspective which integrates the approaches, concepts and tools of both mobilityand destination management.

The concept of a tourist transport system (Page, 2005) can be used to analyze the mul-tifaceted structure of tourist transport, combining the physical movement of visitors usingone or more forms of transport – the logistical component – and the travel experience – theexperiential component. Both components have a complex structure: the logistical includescommunication routes, means of transport and flows. Communication routes include arte-rial roads and internal distribution, specialized trails (e.g. bike and hiking trails), routes toperipheral areas and pedestrian paths (Berardi, 2007). The means of transport, commonlyreferred to as the means of destination access, may also be the location where an entireholiday is spent (Page, 2005). Flows generated on communication routes by different meansof transport determine different mobility forms: transit or access flows are defined as thedirect flows between origin and destination regions; internal (or intra-destination) mobilityis the tourist movement in the destination during a holiday; travel itineraries are a sortof imaginary travel chain, where different means of transport are linked to one another,(Schiefelsbusch et al., 2007). Junctions – the locations where tourists change from onemeans of transport to another – play a fundamental role in travel itineraries and allow thedevelopment of intermodal travel, i.e. the use of multiple means of transport.

The complexity of the experiential component of travel depends on users. First, transportreserved only for tourists – known as exclusive transport – differs from that shared withother users, such as the host community or tourism sector workers (Hall, 1999). In the caseof nonexclusive transport, the travel experience largely depends on the level of competitionamong users for means or routes. A second distinction is made between sedentary tourists(same-day visitors) – who use a means of transport in order to get from their region of originto their tourist destination – and itinerant tourists (also same-day visitors) for whom the heartof the tourist experience lies in the journey (Berardi, 2007). According to Schiefelsbuschet al. (2007), an itinerant holiday – named Reisekette in German, meaning travel chain inEnglish – with stops, changes of means of transport and visits to minor attractions increasesthe experiential value of traveling. Reiseketten transcend the merely instrumental conceptof travel itineraries and become a tourist product integrating tourism and transport in asingle package (Schiefelsbusch et al., 2007).

Both components of the tourist transport system have unavoidable environmental,economic and social impacts; these effects have been multiplied and increased by thetransport “democratization” caused by technological improvements in the transport sector,both in infrastructure and means of transport (Hernandez Luıs, 2008). Democratizationmeans the increased access to transport by different social groups, particularly the middleclasses. Despite the clear connections between different impact types, social and economicimpact analyses of tourist transport systems are still rare (Dickinson & Dickinson, 2006;Dickinson & Robbins, 2008; Dickinson, Robbins, & Fletcher, 2009; Saenz-de-Miera& Rossello, 2012; Schiefelsbusch et al., 2007). The numerous studies to date focusmainly on the environmental effects of tourism mobility in terms of energy consumption

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patterns (Becken, 2002; Becken & Simmons, 2002; Becken, Simmons, & Frampton, 2003a,2003b), global effects on climate change (Becken & Hay, 2007; Dubois, Peeters, Ceron,& Gossling, 2010; Peeters & Dubois, 2010; Peeters, Szimba, & Duijnisveld, 2007) andtourists’ and residents’ (transport-related) resource consumption at a local scale (Gossling,Borgstrom Hansson, Horstmeier, & Saggel, 2002; Martın-Cejas & Ramırez Sanchez, 2009).

The complexity of the transport system and its multidimensional impacts must beconsidered in the planning and development of sustainable tourism mobility, using thesame principles of strategic planning and stakeholder participation used widely for sustain-able tourism development (Godfrey & Clarke, 2000). Strategic planning frames mobilityin the wider process of territorial governance because mobility is cross-sectoral and spansdiverse policy domains; a coordination of policies in different sectors is needed to createsustainable tourism (Bramwell, 2011; Bramwell & Lane, 2011; Hall, 2008). The adoptionof a participatory approach to tourism mobility planning (Gronau & Kagermeier, 2007) canalso develop sustainability awareness and encourage sharing of responsibility for alternativetraffic management strategies.

Destinations can balance the impact of tourism mobility through pull or push strategiesoffering both carrots and sticks (Cullinane & Cullinane, 1999; Holding & Kreutner, 1998;Nocera & Cavallaro, 2011). Pull (carrot) measures are incentives to reduce private vehicleimpacts (public transport improvements, opportunities to hire low-impact mobility, zeroimpact holidays and mobility cards). Travelers – whether tourists or not – usually preferthese strategies (Stradling, Meadow, & Beatty, 2000), although the literature indicates thatby themselves, they achieve only limited success (Holding, 2001; Holding & Kreutner,1998). Push (stick) measures are mostly disincentives – limits/costs imposed on privatevehicle use (e.g. traffic restrictions, access tolls, fee parking), but they attract public andpolitical opposition and can be deemed unacceptable (Holding, 2001). Assuming the samedestination and governance model, the choice of a strategy and the effectiveness of itsimplementation depend directly on tourism mobility analyses designed to support trafficmanagement decision processes. The success of a strategy also depends on effective com-munication policies promoting the mobility alternatives available for potential users (VanExel & Rietveld, 2009).

Case study

The issue of tourism mobility within the framework of sustainable tourism planning andmanagement is analyzed through this case study from South Tyrol. South Tyrol is anautonomous province located in north-east Italy. It has a population of over 500,000 in-habitants, has an area of 7400 square kilometres and includes 116 municipalities (ASTAT[Provincial Institute of Statistics], 2009a). This alpine province is one of the most tourism-intensive and competitive destinations in Italy (Cracolici, Nijkamp, & Rietveld, 2006).About 5 million tourists (28 million overnight stays in 2008) visit South Tyrol annually(ASTAT, 2009c), making tourism a key part of the economy: it provides over 8% of provin-cial GDP and contributes to its high standard of living and well-being (ASTAT, 2009d).Germany (46.5%) and Italy (36.7%) are the main source markets (ASTAT, 2009c); nat-ural resources are the most important tourist attraction; hiking and sports, particularlywinter sports, are the main motivations for holidays in South Tyrol (ASTAT, 2009b). TheDestination Management Organization system is a pioneering Italian example of effec-tive public-private destination governance and has a three-tier structure: province (AltoAdige Sudtirol Marketing), inter-municipal (Tourist Consortia) and municipal (TourismAssociations) (Pechlaner, Volgger, & Herntrei, 2012).

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South Tyrol was chosen as a case study because of its special status in Italian law, whichallows it greater autonomy in formulating its tourism and mobility policies. Sustainabilitylies at the core of the provincial vision and mission: natural resources (and related traditions)are both vital inputs for local agriculture, still an important sector, and the province’smost important tourist attractions. It is crucial for the socio-economic vitality of thisalpine province that both tourism and mobility have low environmental impacts (Gios,Goio, Notaro, & Raffaelli, 2006) given the causal link between environment/landscapequality (including agricultural activities), the attraction of visitor flows and long-term localdevelopment and well-being. The recent inclusion of the Dolomites – partly in SouthTyrol – on the UNESCO World Natural Heritage List also supports the need for sustainabledevelopment by integrating and innovating in tourism and mobility.

The current South Tyrolean mobility system has integrated all regional transport modes,increased intermodal transport and consistently supported pioneering local initiatives. Pub-lic transport in South Tyrol is an integrated system, both in terms of ticketing and time-tabling. Several membership and mobility cards are available, covering not only publictransport use but also bike rental and access to recreational activities. A free phone in-formation service offers details of all available regional transport alternatives and timeta-bles, and a Customer Satisfaction Analysis of regional rail transport has been developed(Pechlaner, Bonelli, Scuttari, & Martini, 2012).

Among many initiatives involving South Tyrol, two projects stand out as good examplesof the application of pull and push measures in tourism mobility management. The “AlpinePearls” project (http://www.alpine-pearls.com) is a network of 28 alpine locations in sixEuropean countries, including seven South Tyrolean municipalities (Moso in Passiria,Nova Levante, Nova Ponente, Tires, Racines, Cornedo and Funes). It promotes eco-friendlyholidays through the development of pull traffic management measures and other initiatives,provides tourist packages on a single web-based platform and encourages environmentallysustainable same-day trips from one location to another in the network (Federal Ministry ofAgriculture, Forestry, Environment and Water Management, Federal Ministry for Transport,Innovation and Technology, & Federal Ministry of Economics and Labour, 2006). Each“Pearl” destination has developed ways in which locations within it can be accessed bypublic transport or alternative transport services – shuttle buses, taxis, free ski buses,electric vehicles, e-bikes and electric hire cars, some of which are even available on call.Areas where traffic is limited have been given over to nature-based leisure and sportingactivities, thus making restricted traffic a particular tourist experience. In contrast to the“Alpine Pearls”, the Alpe di Siusi initiative (http://www.alpedisiusi.net) involves a singlearea in the Castelrotto municipality which includes the hamlets of Compatsch-Compaccio,Saltria and Piz and is situated on the Sciliar, one of the largest European plateaus. Localmobility is mainly managed through push measures. Since 2003, the plateau has been closedto traffic in the peak season – from May to October and from December to April – andalternative transport is provided – buses, shuttle buses and cableways. Integrated transportservice tickets are valid on these services, as are ad-hoc mobility cards. The Alpe di Siusitourist board explicitly follows the principles of sustainable tourism development and hasplaced alternative mobility management within the wider framework of tourism planning.

Research methodology

This analysis of tourism mobility in South Tyrol includes three steps. The first analyzesinbound traffic and breaks it down into its components, both tourism-related and not,using survey techniques. The second step assesses the environmental impact of tourism

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First Step. Inbound traffic (IT) analysis

Data • Census data on traffic flows (vehicles) • Census data and sample survey data on visitor flows (people)

Conversion parameters(People → Vehicles)

• Tourist nucleus (average number of people using one vehicle) • Percentage of visitor arrivals by own transportation

Breakdown of IT using alinear, deterministic model with constant coefficients

IT = (TTI + TTSI) +(TTO +TTSO) + (TEI + TEO + TET) +TNT + R8 • 8 tourism and nontourism-related components; 1 residual component

Output. Estimation of tourism-related traffic components

Second Step. Environmental impact of tourism traffic components

Conversion parameters(Vehicles → People)

• Tourist nucleus (average number of people using one vehicle) • Percentage of visitor arrivals by own transportation

Environmental coefficients (People/Distance → Emission)

• Emissions per kilometer (Peeters et al., 2007) • Energy consumption per kilometer (UITP, 2003)

Output. Estimation of internal environmental impact

Third Step. Effects of mobility management measures on tourist flows in pilot cases

Pilot cases • Alpe di Siusi (pull measures) • South Tyrolean Alpine Pearls (push measures)

Assumption and proxy to assess the effects

• Assumption: Each pilot location adopts only one type of measure • Proxy: Average annual % Δ of arrivals before and after the

introduction of traffic measures (compared with provincial figures)

Output. Assessment of effects of mobility management measures

Data (TTI + TTSI) • Tourism traffic components estimated in the first step

Figure 1. Steps of the research methodology.

traffic components within the destination (intra-destination mobility): internal mobilitymanagement is crucial to sustainable tourism and tourism and mobility authorities cancooperate on it effectively. The third step explores the effects of mobility managementmeasures on tourist flows in pilot cases. Figure 1 depicts the main phases and core outputsof the three research steps and there is a detailed discussion of each step in the followingsub-sections.

First step: Inbound traffic analysis

The main issues related to inbound traffic analysis concern the types of data and sourcesused, the methodology applied, the assumptions made and parameters used to break inboundtraffic down into its components.

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The data used in the analysis are secondary census or sample surveys data recordingincoming vehicles (both tourism-related and not) and tourism-related flows (inbound andoutbound tourists and same-day visitors) for the tourist year 2007/2008 (November 2007to October 2008). These data come from national or provincial official institutions (bothstatistical and not) (the National Institute of Statistics – ISTAT, Provincial Institute ofStatistics – ASTAT, Bank of Italy) or from reliable sources used by these institutions(Brenner Motorway S.p.A). The quality of data, especially sample survey data, is assuredboth by the reliability of the institutions providing them (in some cases on demand) and bythe use of these data in developing sector-specific analyses at the provincial level (e.g. SouthTyrolean Tourism Satellite Account). Same-day visit data are only from sample surveys, butall official sources available in Italy have been accessed and integrated into the database:see Table 1.

Data recording incoming vehicles, which have been integrated in a single database,define the time series to be analyzed, i.e. light daily inbound traffic (IT) (henceforth inboundtraffic). Inbound traffic is the daily inbound movement of light vehicles (motorbikes, cars

Table 1. Data types and sources.

Type of data Type of source Data description used in the analysis

Census dataVisitor movementto accommodationfacilities

ISTAT – National Institute ofStatistics (http://www.istat.it/it/archivio/turismo)

Daily arrivals and overnight stays ofinbound tourists in South Tyrol andmonthly arrivals of outbound touriststo other Italian regions

Traffic flows onBrenner Motorway

Brenner Motorway S.p.A (dataavailable on demand)

Daily movement of light traffic(motorcycles, cars and small vans) atsix South Tyrolean tollgates enteringthe motorway from outside theprovincial border

Traffic flows onstate and provincialroads

ASTAT – Provincial Institute ofStatistics (http://www.provinz.bz.it/astat/it/mobilita-turismo/traffico-trasporti.asp)

Daily inbound movement of lightvehicles (motorcycles, cars and smallvans) at 18 monitoring stations locatednext to the South Tyrolean border onstate and provincial roads

Sample survey dataTouristexpenditure

ASTAT – Provincial Institute ofStatistics (data available ondemand)

Percentage of tourists traveling to SouthTyrol by own means of transportation(motorcycles, cars and small vans);average number of tourists per meansof transportation (tourist nucleus);distance traveled during the holiday inSouth Tyrol

Journeys andHolidays of theItalians

ISTAT – National Institute ofStatistics (http://www.istat.it/it/archivio/turismo)

Estimated arrivals of Italian tourists infree South Tyrolean accommodationfacilities (e.g. friends and relatives) peryear; estimated inbound and outboundsame-day visitors per year from/to Italy

InternationalTourism

Bank of Italy (http://www.bancaditalia.it/statistiche/rapp_estero/turismo-int)

Estimated arrivals of foreign tourists infree South Tyrolean accommodationfacilities (e.g. friends and relatives) peryear; estimated inbound and outboundsame-day visitors per year from/toforeign countries

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and vans) crossing the border into South Tyrol, detected at monitoring stations on stateand provincial roads and at motorways gates. It is important to underline that inboundtraffic does not correspond to inbound tourism because (1) vehicles may cross provincialborders daily for different purposes (not only for tourism) and (2) tourist vehicles mayeither be related to inbound tourism entering the destination or to outbound tourism, whenSouth Tyrolean tourists travel back to the province. Data referring to tourism are used tobreak down inbound traffic and estimating tourism-related and nontourism-related trafficcomponents.

The methodology applied to break down inbound traffic (IT) is a linear, deterministicmodel with constant coefficients, where inbound traffic (IT) is the dependent variable, whiletourism-related phenomena are independent variables. The estimation of variable coeffi-cients is based on survey techniques, i.e. parameters derived from local-specific samplesurveys by the ASTAT on tourism and traffic (sector-specific) are applied to independentvariables to estimate tourism-related traffic components (see Table 1). The selection oftraffic components to be introduced in the model is made after a progressive analysis of theresidual: the methodology is also known as the “residual method” (Vaccaro, 2007).

Inbound traffic breakdown using survey techniques is based on reasonable assump-tions. The first assumption concerns the conversion of tourism flows into traffic flows usingthe parameters tourists per vehicle and percentage of own transportation inbound arrivals.There are no studies from which these parameters can be borrowed in the tourism literature.However, evidence that the seat occupation rate of tourist vehicles (i.e. tourists per vehicle)differs significantly from that of commuters suggests that survey investigation might beappropriate (Peeters et al., 2007). The conversion factors used in this case study are there-fore reliable, place-specific and sector-specific parameters related to (1) the compositionof the tourist nucleus (the average number of people using one vehicle) and (2) the per-centage of own transportation inbound arrivals (the ratio of own transportation arrivals tototal arrivals). Both are derived from the official sample survey of the ASTAT on Touristexpenditure (see Table 1). In the province of Bolzano, the tourist nucleus is 2.94 people andthe percentage of own transportation inbound arrivals is 88.5% of total arrivals (ASTAT,2009b).

The second assumption is that nontourism traffic is a constant and is twice as intense onworking days as during holidays because of the high number of commuters. This assumptionis based on an analysis of the low-intensity tourism periods of the inbound traffic dataset: inNovember 2007, the average number of vehicles entering the province on working days was22,431 (rounded to 22,000), while the average number of vehicles entering the provinceduring holidays was almost half (48.7%) of this (rounded to 11,000).

Starting from these two assumptions and related parameters, the breakdown of inboundtraffic (IT) using survey techniques is carried out as follows:

• the identification and quantification of daily IT components and the conversion ofannual data into daily data through appropriate distribution when daily data are notavailable;

• the progressive removal from the IT of the components thus obtained; and• the analysis of the residual component.

The result of the breakdown is synthesized by the following equation, according towhich inbound traffic (IT) is the algebraic sum of different components.

IT = (TTI + TTSI) + (TTO + TTSO) + (TEI + TEO + TET) + TNT + R8 (1)

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A total of eight TI components were defined: two related to inbound tourist flows intothe province (TTI and TTSI), two related to outbound tourist flows recorded on their returnto the province (TTO and TTSO), three to same-day visits (TEI, TEO and TET) and one tonontourism traffic (TNT). The residual (R8) is what remains after the progressive removalof these components. The third assumption made is that the residual (R8) is entirely madeup of potential errors related to same-day visits because this is the category most likely toinvolve the underestimation of known components, as it is the only one estimated entirelyon the basis of annual sample surveys (see Table 1). The residual is therefore added to theknown inbound and outbound same-day visit components (TEI) and (TEO) in a measureproportional to the incidence of each of these components on the annual same-day visitsestimation through sample surveys. R8∗ and R8∗∗ are therefore the residual amounts R8,added to TEI and TEO, respectively. Table 2 provides details of each component (definition,sources and estimation process).

Second step: Environmental impact of tourism traffic on the destination

The second stage of the research estimates the environmental impact of the tourism trafficcomponents, identified and estimated in the first stage, on the destination during holidays –i.e. inbound tourism (TTI and TTSI). Inbound same-day visits (TET + TEI + R8∗) areexcluded from the environmental impact analysis of internal mobility, as distances coveredinside the destination during same-day visits are unknown and estimates cannot be derivedfrom sample surveys on tourism.

The estimate of the environmental impact of tourism traffic in the destination starts fromthe (first) assumption linking tourist flows to vehicle flows and goes backwards, applying thepreviously used parameters (tourist nucleus and percentage of own transportation inboundarrivals) to turn tourism-related vehicles into people.

The environmental impact on the destination of the people using these vehicles isestimated by applying both nontourism-specific energy consumption coefficients (UITP[Union Internacional de Transportes Publicos], 2003) and tourism-specific emission coeffi-cients (Peeters et al., 2007) and by considering the average distances people covered withinthe destination in the summer and winter seasons (ASTAT, 2009b). Since neither the fleetcomposition nor vehicle-specific fuel consumption patterns were available, average fleetand vehicle characteristics were assumed.

Third step: Effects of mobility management measures on tourist flows in pilotcases

This exploratory stage goes beyond tourism traffic analysis and assesses the effect ontourist demand of tourism traffic management measures introduced by areas in South Tyrolinvolved in pioneering mobility initiatives. The pilot cases are the Alpe di Siusi initiative inthe municipality of Castelrotto and the seven South Tyrolean municipalities of the “AlpinePearls” network (see above); the latter choosing predominantly pull measures, the formerpredominantly push ones.

Knowing that multiple short, medium and long term factors can affect demand and thatthese effects are both quantitative (consistency) and qualitative (behaviors and habits), thisexploratory analysis has focused on quantitative effects and introduces two assumptions.First, the proxy used to estimate the effects of mobility measures is the official arrivaltime series in these locations provided by ASTAT, which covers the periods before andafter the introduction of the measures. In addition, a cross-check of arrival series with

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onst

ate

and

prov

ince

road

sby

AS

TAT

;Vis

itor

mov

emen

tto

acco

mm

odat

ion

faci

liti

esby

ISTA

T

•App

roxi

mat

ion

toro

unde

dva

lues

ofda

ilyli

ghtt

raffi

cpa

ssag

esin

wee

kday

s(2

2,00

0)an

dho

lida

ys(1

1,00

0)du

ring

the

peri

odof

low

esti

nten

sity

tour

ism

inth

eto

uris

tye

ar20

07/2

008

(Nov

embe

r20

07)

Inbo

und

tour

ism

TT

I(T

raffi

cfo

rin

boun

dto

uris

m)

Tra

ffic

gene

rate

dby

inbo

und

tour

ista

rriv

als

inho

tels

,com

plem

enta

ryan

dfr

eeac

com

mod

atio

nfa

cili

ties

Cen

sus:

Vis

itor

mov

emen

tto

acco

mm

odat

ion

faci

liti

esby

ISTA

TS

ampl

esu

rvey

s:Jo

urne

ysan

dH

olid

ays

ofth

eIt

alia

nsby

ISTA

T,In

tern

atio

nal

Tour

ism

byB

ank

ofIt

aly,

Tour

ist

expe

ndit

ure

byA

STA

T

•Sum

ofda

ilyar

riva

lsin

hote

lsan

dot

her

coll

ectiv

eac

com

mod

atio

nes

tabl

ishm

ents

(dai

lyda

ta)

wit

hda

ilyes

tim

ated

arri

vals

infr

eeac

com

mod

atio

nfa

cili

ties

(ann

ual

data

),as

sum

ing

that

daily

dist

ribu

tion

ofar

riva

lsin

free

acco

mm

odat

ion

faci

liti

esis

equa

lto

that

ofar

riva

lsin

hote

lsan

dco

mpl

emen

tary

faci

liti

es•C

onve

rsio

nof

tota

ldai

lyes

tim

ated

arri

vals

into

traf

fic

flow

sth

roug

hpa

ram

eter

s(t

ouri

stnu

cleu

san

dpe

rcen

tage

ofow

ntr

ansp

orta

tion

inbo

und

arri

vals

)T

TS

I(T

raffi

cfo

rin

boun

dhi

dden

tour

ism

)T

raffi

cge

nera

ted

byin

boun

dto

uris

tflow

sno

tof

fici

ally

regi

ster

edby

acco

mm

odat

ion

faci

liti

es(h

idde

n)

Sam

eso

urce

sas

for

TT

Ico

mpo

nent

•App

roxi

mat

ion

toa

roun

ded

prop

orti

onof

daily

TT

I(2

0%)

defi

ned

thro

ugh

asi

mul

tane

ous

max

imiz

atio

nof

the

TT

SI

and

TT

SO

com

pone

nts

onth

eun

ders

tand

ing

that

the

equa

tion

ofth

em

odel

com

pari

ngin

boun

dtr

affi

can

dth

esu

mof

its

nine

esti

mat

edco

mpo

nent

sm

ustb

eve

rifi

edda

ily(C

onti

nued

onne

xtpa

ge)

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624 A. Scuttari et al.

Com

pone

nts

Defi

niti

onS

ourc

esE

stim

atio

npr

oces

s

TE

I+

R8∗

(Tra

ffic

for

inbo

und

and

resi

dual

sam

e-da

yvi

sits

)

Tra

ffic

gene

rate

dby

inbo

und

sam

e-da

yvi

sito

rfl

ows

Sam

ple

surv

eys:

Jour

neys

and

Hol

iday

sof

the

Ital

ians

byIS

TAT,

Inte

rnat

iona

lTo

uris

mby

Ban

kof

Ital

y,To

uris

tex

pend

itur

eby

AS

TAT

•Con

vers

ion

ofan

nual

inbo

und

sam

e-da

yvi

sito

res

tim

ates

into

traf

fic

flow

sth

roug

hpa

ram

eter

s(t

ouri

stnu

cleu

san

dpe

rcen

tage

ofow

ntr

ansp

orta

tion

inbo

und

arri

vals

),as

sum

ing

that

the

trav

elha

bits

ofto

uris

tsan

dsa

me-

day

visi

tors

inac

cess

ing

the

dest

inat

ion

are

the

sam

e•D

aily

dist

ribu

tion

acco

rdin

gto

the

dist

ribu

tion

ofre

sidu

altr

affi

c•A

ddit

ion

ofre

sidu

alR

8∗pr

opor

tion

alto

the

inci

denc

eof

TE

Oan

dT

EI

onth

eto

tals

ame-

day

visi

ttra

ffic

Out

boun

dto

uris

mT

TO

(Tra

ffic

for

outb

ound

tour

ism

)T

raffi

cge

nera

ted

byou

tbou

ndto

uris

tflow

s,re

gist

ered

upon

retu

rnto

the

prov

ince

Cen

sus:

Vis

itor

mov

emen

tto

acco

mm

odat

ion

faci

liti

esby

ISTA

TS

ampl

esu

rvey

s:Jo

urne

ysan

dH

olid

ays

ofth

eIt

alia

nsby

ISTA

T,In

tern

atio

nal

Tour

ism

byB

ank

ofIt

aly,

Tour

ist

expe

ndit

ure

byA

STA

T

•Sum

ofda

ilyes

tim

ated

outb

ound

arri

vals

inho

tels

and

othe

rco

llec

tive

acco

mm

odat

ion

esta

blis

hmen

tsin

Ital

ian

regi

ons

(mon

thly

data

),w

ith

daily

esti

mat

edar

riva

lsin

free

acco

mm

odat

ion

faci

liti

esin

Ital

ian

regi

ons

(ann

uald

ata)

and

wit

hda

ilyes

tim

ated

arri

vals

inho

tels

,com

plem

enta

ryan

dfr

eeac

com

mod

atio

nfa

cili

ties

info

reig

nco

untr

ies

(ann

uald

ata)

;ass

umin

gth

at(a

)ou

tbou

ndar

riva

lsar

ere

gist

ered

upon

retu

rnto

the

prov

ince

and

(b)

the

daily

dist

ribu

tion

ofm

onth

lyda

ta(a

rriv

als)

iseq

ualt

oth

eda

ilydi

stri

buti

onof

inbo

und

tour

ists

’m

onth

lyda

ta(d

epar

ture

s);

daily

esti

mat

esof

year

lyda

taar

epr

opor

tion

alto

the

dist

ribu

tion

obta

ined

from

mon

thly

data

•Con

vers

ion

ofto

tald

aily

esti

mat

edar

riva

lsin

totr

affi

cfl

ows

thro

ugh

para

met

ers,

assu

min

gth

atth

etr

avel

habi

tsof

outb

ound

tour

ists

and

inbo

und

tour

ists

are

the

sam

e(t

heco

nver

sion

para

met

ers

tour

istn

ucle

usan

dpe

rcen

tage

ofow

ntr

ansp

orta

tion

inbo

und

arri

vals

have

been

used

agai

n)(C

onti

nued

onne

xtpa

ge)

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Journal of Sustainable Tourism 625

Tabl

e2.

Inbo

und

traf

fic

com

pone

nts.

(Con

tinu

ed)

Com

pone

nts

Defi

niti

onS

ourc

esE

stim

atio

npr

oces

s

TT

SO

(Tra

ffic

for

outb

ound

hidd

ento

uris

m)

Tra

ffic

gene

rate

dby

outb

ound

tour

istfl

ows,

noto

ffici

ally

regi

ster

edby

acco

mm

odat

ion

faci

liti

es(h

idde

n),

regi

ster

edup

onre

turn

toth

epr

ovin

ce

Sam

eso

urce

sof

TTO

com

pone

nt•A

ppro

xim

atio

nto

aro

unde

dpr

opor

tion

ofda

ilyT

TO

(20%

),de

fine

dth

roug

ha

sim

ulta

neou

sm

axim

izat

ion

ofth

eT

TS

Oan

dT

TS

Ion

the

unde

rsta

ndin

gth

atth

eeq

uati

onof

the

mod

elco

mpa

ring

inbo

und

traf

fic

and

the

sum

ofit

sni

nees

tim

ated

com

pone

nts

mus

tbe

veri

fied

daily

TE

O+

R8∗∗

(Tra

ffic

for

outb

ound

and

resi

dual

sam

e-da

yvi

sits

)

Tra

ffic

gene

rate

dby

outb

ound

sam

e-da

yvi

sito

rfl

ows

regi

ster

edup

onre

turn

toth

epr

ovin

ce

Sam

ple

surv

eys:

Jour

neys

and

Hol

iday

sof

the

Ital

ians

byIS

TAT,

Inte

rnat

iona

lTo

uris

mby

Ban

kof

Ital

y,To

uris

tex

pend

itur

eby

AS

TAT

•Con

vers

ion

ofan

nual

outb

ound

sam

e-da

yvi

sito

res

tim

ates

into

traf

fic

flow

sth

roug

hpa

ram

eter

s(t

ouri

stnu

cleu

san

dpe

rcen

tage

ofow

ntr

ansp

orta

tion

inbo

und

arri

vals

),as

sum

ing

that

tour

ists

acce

ssin

gth

ede

stin

atio

nan

dsa

me-

day

visi

tors

leav

ing

itha

veth

esa

me

trav

elha

bits

•Dai

lydi

stri

buti

onac

cord

ing

toth

edi

stri

buti

onof

resi

dual

traf

fic

•Add

itio

nof

resi

dual

R8∗∗

prop

orti

onal

toth

ein

cide

nce

ofT

EO

and

TE

Ion

tota

lsam

e-da

yvi

sitt

raffi

cT

ET

(Tra

ffic

for

sam

e-da

yto

uris

tvi

sits

)

Tra

ffic

gene

rate

dby

inbo

und

tour

ists

onsa

me-

day

trip

sou

tsid

eth

epr

ovin

ce,r

egis

tere

dup

onre

turn

toth

e

Cen

sus:

Vis

itor

mov

emen

tto

acco

mm

odat

ion

faci

liti

esby

ISTA

TS

ampl

esu

rvey

s:To

uris

texp

endi

ture

byA

STA

T

•Inb

ound

tour

ists

trav

elin

gm

ore

than

40km

away

from

thei

rde

stin

atio

nfo

rsa

me-

day

trip

s,es

tim

ated

per

seas

onas

apr

opor

tion

ofin

boun

dar

riva

ls(1

7.60

%in

win

ter

and

36.1

1%in

sum

mer

seas

on)

and

per

day

assu

min

gth

atsa

me-

day

trip

soc

cur

ever

yda

yex

cept

the

arri

vald

aypr

ovin

ce•C

onve

rsio

nof

arri

vals

into

traf

fic

flow

sth

roug

hpa

ram

eter

s(t

ouri

stnu

cleu

san

dpe

rcen

tage

ofow

ntr

ansp

orta

tion

inbo

und

arri

vals

),as

sum

ing

that

tour

ists

’tr

avel

habi

tsar

eth

esa

me,

whe

ther

they

are

acce

ssin

gth

ede

stin

atio

nor

onsa

me-

day

trip

sdu

ring

thei

rho

lida

y

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626 A. Scuttari et al.

accommodation facility series (beds) for the same periods helps compare policy effects(mobility management measures) and marketing effects (bed capacity) on demand. Second,it has been assumed that each pilot location has only adopted one type of measure. Howevereach location is using a mix of measures which have simultaneous effects that cannot bemeasured separately. According to the assumptions introduced, the results of the analysisare preliminary, providing initial synthetic indications/insights.

Main results

This analysis of South Tyrolean tourism mobility has produced three types of results. First,an estimate of tourist and same-day visitor vehicles and their annual, seasonal, monthly anddaily distribution. Second, an evaluation of the environmental impact of inbound tourismvehicles on the destination. Third, an exploratory assessment of the effects in pilot cases ofmobility management measures aimed at sustainable tourism.

Vehicles for tourism-related purposes

Over half (51.2%) of the almost 14 million light vehicles entering South Tyrol in the2007/2008 tourist year were tourism-related traffic. The different components of this trafficare depicted in Figure 2. Inbound tourism (TTI + TTSI) and same-day visits (TEI +R8∗) account for almost one third (30.7%) of the overall inbound traffic, i.e. the largestamount after nontourism traffic (TNT). Interestingly, the number of vehicles in each ofthese components is almost the same. On the other hand, overall outbound traffic only justexceeds (by 17%) inbound traffic and there is far more outbound same-day visit trafficthan tourist traffic. In fact, tourism outside the province (TTO + TTSO) accounts for onlyone sixth of the outbound same-day visits (TEO + R8∗∗) and is even less than the trafficgenerated by inbound tourists’ same-day visits (TET) outside the province.

The monthly percentage distribution of yearly traffic shows very high scores during thesummer for all its components (see Figure 3). About two thirds of outbound tourism (67%)and over 60% of inbound tourism occur between May and October and inbound same-dayvisits in the summer are about 65% of the overall same-day visit flows.

Figure 2. Inbound traffic components.

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Journal of Sustainable Tourism 627

0%

5%

10%

15%

20%

25%Jan

Febr

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Inbound Tourism Traffic (TTI + TTSI)

Inbound Same-day Visit Traffic (TEI + R8*)

Outbound Tourism Traffic (TTO + TTSO)

Figure 3. Percentage composition of monthly traffic flows.

Same-day visits by inbound tourists traveling daily outside the province (TET) take placealmost exclusively in the summer (78.4%). Seventeen percent of the traffic flows generatedby the return of outbound tourists are concentrated in June, while inbound tourism andsame-day visits reach their peak in August. The number of same-day visitors (over 20%) inthis month is higher than that of tourists (about 16%), whereas in the other summer monthsthe concentration of tourists and same-day visitors in South Tyrol is more or less the same.During the winter months of January, February and March – the ski season – there are moretourists than same-day visitors.

Finally, the daily analysis shows the typical trend of traffic components during the week.Same-day visits are concentrated at weekends and peak tourist flows are usually recordedon Saturdays, while returning outbound flows are most intense on Sundays. These trendsdetermine the differences between holidays and workdays in the intensity of tourist traffic.Inbound same-day visits are also concentrated during holidays, when there are on averagetwice as many trips (about 10,000) as on workdays (about 5000). The differences are lessmarked for inbound tourism: there are roughly 30% more trips on holidays than on workdays(c. 7000 vs. c. 5500). The daily analysis of tourist and same-day visit traffic around particularfestivals shows a decrease in the flow at Easter and Christmas, which are traditionallycelebrated within the family (see Figure 4). In contrast, on holidays traditionally dedicatedto same-day trips – May Day, or Pentecost – flows record sudden increases, particularly for

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628 A. Scuttari et al.

Figure 4. Daily traffic flows in December 2007.

same-day visits. The festival calendar in German-speaking countries also explains trafficpeaks on the public holiday celebrating the unification of Germany or at Corpus Christi.

Environmental impact of tourism traffic on the destination

Over 4 million (4,264,736) tourist and same-day visitor vehicles arrived in South Tyrol inthe tourist year 2007/2008 (see Figure 2). This means a daily circulation in the provinceof holidaymakers in over 35,000 vehicles (36,430), which are added to the local vehiclefleet – c. 300,000 units per year (294.608) (ASTAT, 2009a). The environmental impactof this additional traffic inside the destination estimated by applying energy consumption(UITP, 2003) and emission coefficients (Peeters et al., 2007) to people using these vehicles(about 12 million people for 4 million vehicles) and considering the distances they coveredwithin the destination is quite considerable. It is estimated that internal tourists’ mobilityconsumed 694.3 million Mj of energy, produced 29,313 tons of CO2 and 30,790 tons ofCO2 equivalent gas and introduced 4959 kg of particulates and 110,200 kg of nitrogenoxides into the atmosphere.

In addition to the environmental impact estimate, this research step also provides asignificant half-way result when tourism-related vehicles are transformed into people. Theestimate of daily same-day visits is valuable information: this subject is widely neglected,both in the literature and in practice.

Effects of traffic management measures on tourist flows in pilot cases

The arrival time series analysis in Alpe di Siusi (push measures) and the South Tyrolmunicipalities involved in the “Alpine Pearls” network (pull measures), intended to assessthe impact of their mobility management measures on tourist flows, produced encouraging,

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Journal of Sustainable Tourism 629

Figure 5. Mean yearly percentage variations of arrivals in pilot areas.

although still exploratory, results. Figure 5 shows the variations in arrivals in the periodsbefore and after the introduction of traffic management measures by comparing them tocorresponding variations in the province. In order to harmonize projects in which trafficmanagement measures were initiated at different times (2003 in Alpe di Siusi and 2006in the “South Tyrolean Pearls”), variations are expressed as average yearly percentages.However, the size of the variations cannot be directly compared between pilot cases, as themeasures were introduced at different times and the intervals used to calculate the meanvariations in the two pilot cases do not coincide. Moso in Passiria was excluded as it hasonly been involved in the project since 2010.

In the Castelrotto municipality, where the hamlets of the Alpe di Siusi initiative havebeen closed to traffic since 2003 and can only be reached by cable car, increases in arrivals

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630 A. Scuttari et al.

were recorded both before and after the introduction of traffic management measures (seeFigure 5a). In line with figures recorded in the province, the most meaningful increasestook place after 2003, demonstrating that traffic management has not had a negative impacton tourist flows in these locations. The average annual increase after access was denied totraffic actually exceeds the provincial average (+4.8% vs. +3.1%).

In the seven South Tyrol municipalities belonging to the “Alpine Pearls” network, thedata analysis before and after the introduction of traffic management measures performed in2006 does not provide uniform results. Two locations (Funes and Tires) show a significantaverage increase in the period after the introduction of the measures. However, the opposite istrue in three other locations (Nova Levante, Nova Ponente and Racines), where tourist flowsdecreased (see Figure 5b). The Cornedo municipality recorded a decrease in arrivals in eachperiod, most noticeably after 2006. The size of the arrival variations is not uniform either.Funes and Tires, which do not seem to have been affected negatively by the introductionof the measures, show increases in arrivals after 2006 that exceed the provincial average(+4.1% and +4.4% respectively, against +3.1%). Even in Racines, which seems to havebeen negatively affected by traffic management, the mean variation in arrivals after 2006exceeds that of the province (+4.2%). In contrast, Nova Levante and Nova Ponente are wellbelow the provincial average (+0.8% and +1.6%). Cornedo recorded a 1.1% decrease inarrivals.

There are probably four different reasons for the contrasting results obtained throughthe arrival analysis in the two pilot projects. First, the Alpe di Siusi initiative and some ofthe Alpine Pearls communities are villages within a municipality; therefore, the recordedarrivals in their municipalities are not sufficiently precise proxies for assessing the impacton tourist flows of measures taken by certain areas within these municipalities. Second, the“Alpine Pearls” project has only operated since 2006 and, even though six out of the sevenSouth Tyrol villages joined the network at the very beginning, the observation span is stilltoo short for a spill over analysis of the project. Third, the mobility management measuresadopted by the “Alpine Pearls” have been promoted on the network’s official website,but they are not very visible on the websites of the South Tyrol partners and are weaklyintegrated into the local tourist offer. Therefore many tourists are not aware of the alternativetraffic management options before setting off on holiday. Finally, but most importantly, thepush or pull traffic management measures may be among the drivers that have influencedthe complex phenomenon of the arrival time series. A cross-check of arrival series withaccommodation facility series (beds) for the same periods excludes the possibility thatpositive trends in arrivals are due to marketing effects (bed capacity) on the demand ratherthan to policy effects (mobility management measures). After the introduction of thesepolicies, beds show average annual decreases in all areas of the two pilot cases, except forthe Alpine Pearls of Nova Ponente and Racines. Before their introduction, the bed timeseries also shows a generally negative trend. In contrast, South Tyrol demonstrates a positivetrend in bed places, over both periods.

To sum up, this preliminary and exploratory analysis of the effects of mobility manage-ment on arrivals seems to show non-negative results, regardless of the measures adopted.This result is confirmed by a further study on the pilot case of Werfenweng in Austria,the most popular and active “Alpine Pearl”, whose overnight trends have been monitoredregularly for about eight years and have increased significantly (Federal Ministry of Agri-culture, Forestry, Environment and Water Management, Federal Ministry for Transport,Innovation and Technology, & Federal Ministry of Economics and Labour, 2006). A moreprecise evaluation of the impact and effectiveness of single mobility measures in the SouthTyrolean pilot cases still requires further research.

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Journal of Sustainable Tourism 631

Conclusions

This paper covers an important and emerging sustainable tourism field on the integration ofmobility into destination planning and management. It provides valuable methodologicaland managerial insights upon which to base integrated policy-making on traffic and tourismanalyses. It proposes a methodology for the estimation of own-transport tourism-relatedtraffic and its internal environmental impact and an evaluation of the effects on touristdemand of mobility policies aimed at more sustainable destination development.

The methodology is a deterministic model with constant coefficients estimated onthe base of survey techniques applied to break down inbound traffic according to trippurpose and to estimate the tourism-related components and their environmental impactson the destination. The originality of the methodology lies not in the survey techniqueper se, but in its novel application to an analysis which integrates tourism and mobilitydomains. This results both in the integration and cross-fertilization of related data, sourcesand methodologies and the generation of new knowledge about traffic and tourism-relatedphenomena which can support synergistic policy decision-making and actions in thesedomains, helping bridge gaps between them. The validity of a methodology based on surveytechniques lies in the availability and accessibility of a wide range of data on traffic andtourism; the quality and reliability of both data surveys and sources; and the quality of theparameters used to break down and estimate inbound traffic components (these must derivefrom reliable, place-specific and sector-specific surveys) as evidence suggests (Peeters et al.,2007). Consequently the validity of the methodology and the accuracy and effectivenessof inbound traffic component estimates depend on the presence of these conditions, whichare place-specific (e.g. availability of local data sources) and sector-specific (availability,accessibility and quality of data on traffic and tourism at a local level). These conditionsallow the methodology for the daily verification of the equation between inbound trafficand the sum of its eight estimated traffic components.

This methodology was implemented and tested in South Tyrol because it meets theseconditions. The province has pioneered sustainable tourism and mobility policies andinitiatives integrating both fields and has a network of official institutions and researchcenters which carry out and update surveys in these fields. The application of surveytechniques to the breakdown of inbound traffic and the estimation of its components in thiscase study used parameters drawn from secondary census or sample survey data on trafficand tourism from official national or provincial statistics institutes or from reliable sourcesused by these institutions.

Interesting results have been obtained through the application of this methodology inSouth Tyrol. First, neglected but crucial phenomena such as same-day visits, hidden tourismand same-day visitor behavior linked to mobility have been estimated through officialsecondary data on tourism and traffic along with tourism-related traffic components. InSouth Tyrol, the same-day visit traffic numbers are the same as those for tourist traffic andare more concentrated in the summer – mainly in August – and in holiday periods thanis tourist traffic. A second result concerns the environmental impact on the destination ofpeople using vehicles for tourism-related purposes, drawn from the combination of thesame conversion parameters (used backwards to convert traffic flows into visitors) withenergy consumption and emission coefficients.

The significance of tourism-related traffic and the environmental impact of internaltourism mobility justifies the pioneering steps taken toward sustainable mobility manage-ment in the two pilot cases in South Tyrol. Although at the moment, the introduction ofthese measures is not connected to these findings, the methodology used in this study

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could help to establish a causal link between tourist traffic analyses (environmental impactincluded) and mobility polices. Our assessment of the effects of these measures on touristflows in pilot cases, the third finding presented, both goes beyond inbound traffic analysisand complements it. This exploratory analysis shows that both policies adopted in the Alpedi Siusi initiative to discourage tourist traffic (push measures) and in the South TyroleanAlpine Pearls to encourage the use of means other than private vehicles (pull measures) hada non-negative impact on tourist demand while providing more environmentally sustainablemeans of transport. Tourist arrivals in these locations increased in most cases, even afterthe introduction of mobility measures, and did so to a greater extent than the provincialaverage in the same periods. Studies confirmed both the methodology used in this ex-ploratory analysis and these preliminary findings, and a cross-analysis of arrival series withbed capacity ruled out any dependence of tourist demand on the accommodation capacitytrend.

Despite the significance of these results, both the method used to break down inboundtraffic and the assessment of the mobility policies’ impact on demand have limitations,suggesting the need for improvements if these analyses are to be used further.

The main problem with inbound traffic analyses based on survey techniques is that awide, complete, up-to-date and place-specific range of data on traffic, tourism and visitortravel habits derived from reliable surveys/sources are needed to make these analysesaccurate and effective. There are still limitations in the South Tyrol analysis, although thisdestination is at the forefront of sustainable tourism and mobility innovation:

• First, sample surveys are not collected yearly and an integrated approach to tourismand traffic sample surveys is still in its early stages. The inbound traffic analysisused here refers to 2007/2008, the most recent years when all available surveys wereup-to-date.

• Second, data/surveys on same-day visit, hidden tourism (inbound and outbound)and nontourism traffic are rare or nonexistent, i.e. specific parameters to estimatethe related traffic components are unknown. The estimation of same-day visitor andhidden tourist (inbound and outbound) components is based on the same conversionparameters related to inbound tourism and assumes that their travel behavior/habitsare the same (see Table 2). The estimation of nontourism traffic is based on theanalysis of the inbound traffic dataset during the low tourism periods of the yearand assumes a constant daily value that is twice as intense on working days as onholidays, because of the high number of commuters (see Table 2). These assumptionsare subject to possible errors of estimation. The development of ad-hoc surveysand/or the reintroduction of commuter flow analysis by the ISTAT could improve theaccuracy of these components. Alternatively, unknown parameters could be estimatedusing statistical methods (econometric techniques, ratio methods).

• Third, census and sample survey data on tourism and traffic are considered equallyreliable, i.e. daily distribution of annual sample survey data is considered as re-liable as daily census data. The use of semi-automatic iterative balance systemscan help to overcome these limitations by weighting the different components ac-cording to data reliability and attributing more reliability to census than to samplesurveys.

• Fourth, the environmental impact of tourism traffic components in the destination iscalculated assuming standard fleet and vehicle characteristics and using nontourism-related coefficients (for energy consumption estimation), i.e. average fleet/vehiclecharacteristics and energy consumption are assumed. Ad-hoc surveys of these factors

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(e.g. tourist fleet composition and vehicle-specific fuel consumption patterns) couldhelp to increase the accuracy of estimates.

• Fifth, the environmental impact analysis only focuses on tourist traffic because aninternal mobility perspective is adopted, i.e. although intra-destination environmentalimpact is considerable, it is underestimated. A more comprehensive estimate of theimpact of tourism mobility would include same-day visit traffic in internal mobilityanalyses and also integrate the impact of tourism-related traffic accessing the des-tination by deriving origin/destination data on both tourists and same-day visitorsfrom ad-hoc surveys.

The main problem with the assessment of the impact of mobility policies on touristdemand is that the causal link between mobility measures and arrivals is complex becausemultiple short, medium and long term factors may influence the final effects on demand(e.g. seasonality, accommodation capacity, quality of accommodation, environmental certi-fications, thematic packages, image of the destination, etc). Destination marketing policiesare particularly crucial to the attraction of visitor flows, through communication strategies,innovative tourist offers and improved accommodation facilities. An assessment of theeffectiveness of these measures in terms of sustainability should consider both the quanti-tative and qualitative effects on demand, i.e. the impact of measures on the consistency oftourist flows and on tourist behaviors, particularly travel habits (environmental and socialsustainability) and consuming and spending behaviors (economic sustainability). Not least,quantitative and qualitative effects might not follow the same trend: mobility measurescould decrease visitor demand in the mass tourist segment but improve visitors’ travelbehavior and demand in other market segments. In conclusion, a comprehensive analysisof the effects of mobility measures on tourist demand requires the combination of quanti-tative and qualitative analyses focusing on both tourists and same-day visitors. The mainlimitations of the exploratory analysis for the South Tyrolean pilot cases are the following:

• The use of a single factor to assess the effects of mobility policies, i.e. arrival timeseries’ trends before and after the introduction of the measures.

• The assumption that each pilot location only adopts one type of measure: simulta-neous effects of the mix of measures used in each place cannot be separated andassessed.

• The short period over which arrival time series were observed, i.e. the introductionof mobility measures is too recent to assess these policies effectively. Analysis forlonger time spans is needed.

• The focus on the quantitative effects of mobility policies, i.e. critical aspects oftravel habits (e.g. frequency and distance of visitor movements, ways of accessingthe destination) are excluded from these analyses.

Although the contribution of this paper is mainly methodological, it also providesmanagerial insights. This case study describes an important example of the causal linkbetween traffic, tourism and policy-making and provides a methodology for tourism trafficanalyses which could support policy-makers wishing to develop integrated and effectivetourism and mobility policies. The case study also shows that this causal link is notpresumed in practice, even in destinations leading in sustainable tourism and mobilitypolicies: integrated datasets do not exist, surveys are not coordinated and mobility policymaking is not the result of integrated analyses and tools. It reflects a political culture ofdestination sustainability.

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Taking effective steps toward integrating mobility and sustainable tourism requires rais-ing awareness of sustainable development as a systemic process which depends on multi-sectorial interdependencies and related institutional and social interdependencies. Mobilityand tourism are core sectors from this sustainability perspective as they both depend andimpact on multiple activities. As their interdependencies involve cross-managerial issues,the development of effective and integrated policies in these sectors should occur withinthe wider process of territorial planning and governance aimed at pursuing the best possibleuse of a place and its inherited resources, human capital, facilities and services, throughcoordinated decision-making. Consequently, critical governance-related issues need to befaced. If, and how effectively, is integration between policies in these sectors to be pro-moted? If, and how, does coordination of these policies occur on the local-regional axis?Which policies and measures need to be in place to move toward sustainable mobility andtourism? Which approaches and tools are used to support integrated and effective decision-making and to evaluate/control the results of these decisions? Which stakeholders shouldbe involved? What impacts do these policies have on the competitiveness and brand of theplace? All these issues could profitably be investigated through comparative studies in thefuture.

AcknowledgementsThe authors would like to acknowledge methodological support received from Dr Ludwig Castlunger(Provincial Statistics Institute of Bolzano), Professor Pier Luigi Novi Inverardi (University of Trento)and Dr Marco Giuliani (University of Bologna/EURAC research). Helpful comments and assistancefrom the journal co-editor and four anonymous reviewers in improving this paper are also gratefullyacknowledged.

Notes on contributorsAnna Scuttari is a scientific researcher at the Institute for Regional Development and LocationManagement at the European Academy of Bozen-Bolzano (EURAC research), Italy. Her researchfields include tourism and sustainable mobility, destination management and governance, regionaldevelopment and customer satisfaction.

Maria Della Lucia is an assistant professor of economics and management at the University of Trentoin Italy and a member of the eTourism research group (http://etourism.economia.unitn.it). She teachesmarketing, strategy, destination management and models of local development. Her research interestsinclude local/regional development, destination management and governance, sustainable tourism andwell-being, sustainable mobility, event management and marketing, and economic impact analysis asan investment decision-making tool. She focuses on community-based alpine and rural destinations.

Umberto Martini is a full professor of economics and management at the University of Trentoin Italy and a senior member of the eTourism research group (http://etourism.economia.unitn.it).He teaches marketing and tourism marketing. He is the scientific coordinator of the School ofTourism Management at the Trentino School of Management. His research interests include tourismmanagement and marketing, tourist behavior and decision-making, and service quality, with a focuson community destinations, particularly alpine destinations.

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