at SciVerse ScienceDirect

Tourism Management 38 (2013) 131e141

Contents lists available

Tourism Management

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

Tourist areas: Examining the effects of location attributes on tour-operatorpackage holiday prices

Joaquín Alegre, Magdalena Cladera, Maria Sard*

Applied Economics Department, University of the Balearic Islands, Edificio Jovellanos-Campus UIB, Crta. Valldemossa Km. 7.5, 07122 Palma de Majorca, Illes Balears, Spain

h i g h l i g h t s

� There is a negative relationship between prices and the distance to the beach.� National differences exist between British and German tourists.� Having a room with sea views increases the price.� The distance from the area to the airport exerts a negative effect on prices.

a r t i c l e i n f o

Article history:Received 8 March 2012Accepted 19 February 2013

JEL Codes:C43D22D40L83R14

Keywords:Location attributesHedonic pricesTourist areasHoliday prices

* Corresponding author. Tel.: þ34 971 172826, þ34fax: þ34 971 172389.

E-mail addresses: joaquin.alegre@uib.es (J.(M. Cladera), maria.sard@uib.es (M. Sard).

0261-5177/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.tourman.2013.02.011

a b s t r a c t

This paper focuses on an analysis of the effect of locational characteristics on holiday prices, using thehedonic price model to estimate them. The paper’s main finding is that location attributes do have aneffect on prices. More specifically, when hotel-related locational characteristics were analysed, a negativerelationship was observed between prices and the distance to the beach for German and British packageholidays, a positive relationship between prices and the distance to the centre of the tourist resort forBritish tourists, and a negative one in this instance for German tourists. Having a room with a sea viewwas found to push up the price for both German and British packages and price differences among touristresorts were also observed. As for the area-related attributes that were considered, only the distancefrom the tourist resort to the airport turned out to be relevant, with a negative effect on prices beingidentified.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

For a tourist industry to develop, an existing underlyingresource is required, called a core product (Pearce, 1989; Smith,1994). This resource is the main incentive for tourism to the area.In the case of mass sun and sand tourism, beaches are a primemotivation (Aguiló, Alegre, & Sard, 2005; Alegre, Cladera, & Sard,2011), and they can thus be considered a core product for thiskind of destination. Tourist resorts are gradually developed aroundthese core products and, since they tend to differ in their locationalcharacteristics, this can make one resort more popular to touriststhan others. If tourists are willing to pay a premium for certain

971 171321, þ34 971 172389;

Alegre), mcladera@uib.es

All rights reserved.

locational characteristics, it might be useful to analyse what effect ahotel’s distance from a core product has on prices, together with theimpact of other resort-related location attributes, while also tryingto identify which locational characteristics allow some resorts to bemarketed at higher prices than their rivals.

Bull (1994) points out that when a hotel is well located, this in-creases its value, thus allowing hotel managers to charge a premiumin comparison with similar rival hotels set in less fortunate sur-roundings. Yang,Wong, andWang (2012) show that location is a keyfactor in the competitive strategy of hotels. Accessibility, agglomer-ation effect, proximity to public goods and services are factors thatcan improve profitability, given that all of them affect the tourist’sselection decision. At sun and sand holiday resorts, three mainlocation attributes can be considered to influence the value of hotels:

� Distance to the beach. Thrane (2005) incorporates the ‘distanceto the beach’ attribute in a linear manner as an explanatory

Fig. 1. Map of Majorca and the tourist resorts under consideration.

1 http://www.blueflag.org/.

J. Alegre et al. / Tourism Management 38 (2013) 131e141132

variable in Norwegian package holiday prices to the CanaryIslands, finding there to be a negative relationship. In theiranalysis of package holidays to the Costa Brava (Spain), Espinet,Saenz, Coenders, and Fluvia (2003) find evidence of a positiveeffect on prices if a hotel has a beachfront location, although thestudy does not explore the distance to the beach factor. Alsoconcentrating on the Costa Brava, Rigall-i-Torrent et al. (2010)find the same positive effect as Espinet et al. (2003). Unlikethe latter, however, they include the distance to the beach as anexplanatory variable and find a negative relationship in relationto package holiday prices.� Distance to the centre of the tourist resort. According to Sinclair,Clewer, and Pack (1990), British package holiday prices go upwhen hotels are located outside the centre of Malaga. Incontrast, Bull (1994) finds a negative relationship betweenmotel prices and the distance to the centre of Ballina (Australia).� Rooms with sea views. In a study by Aguiló, Alegre, and Sard(2003), this attribute is observed to have a positive effect onpackage holiday prices in the Balearic Islands. Fleischer (2012)demonstrates that a room with a sea view has a higher valuethan a room without, although no significant difference wasfound in the value of this attribute when different Mediterra-nean tourist regions were compared.

The tourist resort where a hotel is located might be anothersource of price differences, due to the resorts’ heterogeneity (Aguilóet al., 2003, 2005; Haroutunian, 2005; Juaneda, Raya, & Sastre,2011; Mangion, Durbarry, & Sinclair, 2005; Papatheodorou, 2002;Rigall-i-Torrent & Fluvià, 2007; 2011; Taylor, 1995; Thrane, 2005).These differences could be related to four possible factors:

� Distance from the airport. Lee and Jang (2010) analysed theproximity effects of airports and city-centre business districts

(CBDs) on room rates at airport hotels in the U.S.A. The resultsindicated that hotel rates were affected by the hotel’s distancefrom both places. Although the paper only analyses the airporthotel segment, it shows that airport hotel room rates drop as thedistance to the airport grows.� Beach-related characteristics (number of beaches in the area,length or width of the beach/beaches etc.). Rigall-i-Torrent et al.(2010) show that several beach-related characteristics influ-ence package holiday prices in the Costa Brava. The effect of thewidth of the beach and existence of blue flags,1 moorings,public toilets and hire of sunshades was assessed, finding thatthe number of blue flags has a positive effect on prices.

� Tourist congestion. Tourist congestion can have negative im-pacts on a resort. Too many businesses, over development,traffic and overcrowding all have negative effects on touristsatisfaction (Alegre & Garau, 2010) and so logically these re-sorts should have lower prices. However, these effects are noteasily empirically quantified and, to our knowledge, no previ-ous studies have analysed this issue. The main problem indoing so is possible conflicting effects on prices. For instance, aresort might become more built up because it is set in aparticularly desirable area. If the amount of congestion be-comes an inconvenience to tourists, prices there should bedropped in order to attract new visitors.

� Characteristics of the tourist resort (tranquillity, safety, tourismpolicies etc.). Aguiló et al. (2005) suggest that package holidayprices of hotels in Calvia (Majorca) are higher than the rest ofthe Balearic Islands due to the sustainable development pol-icies in the field of tourism applied in this municipality. Sinclair

Table 1Variables included in the dataset and their description.

Variables Description

Locational characteristicsArea The area of Majorca in which the hotel is locatedDistance to centre The hotel’s distance in metres to the centre of

the resortDistance to beach The distance in metres to the nearest beachSea view Whether the room has sea viewsDistance from airport The distance from the airport to the resort in kmCongestion The ratio between the hotels at a specific resort

and the total no. of coastal hotelsBeach-related

variablesThe no. of beaches and total surface area, lengthand width of the beach(es)

Non-locational characteristicsRating The hotel’s star ratingType of room The beds per roomType of board The type of boardTour operator The tour operator marketing the holidayBabysitting Whether a babysitting service is offered by the

J. Alegre et al. / Tourism Management 38 (2013) 131e141 133

et al. (1990) point out that price differences in resorts in theMalaga area are associated with their setting and image.

In relevant literature, most papers focus on the characteristics ofhotels rather than on location attributes or they only take into ac-count some of the latter. This paper aimed to fill this gap by ana-lysing the effect of locational characteristics on prices. To be moreprecise, the analysis explored the relevance of a holiday resort’slocation attributes, taking into account two types: hotel-relatedlocational characteristics and resort-related ones. The first setwere made up of the distance to the beach, distance to the centre ofthe tourist resort, a room with or without sea views, and the spe-cific area where the hotel was located. In the second case, threevariables were analysed: the distance from the airport to the resort;the density of hotels there, in the form of a ratio between thenumber of hotels at the resort and the total number of coastalhotels in Majorca; and a number of beach-related characteristics,such as the number of beaches at the resort or the beach’s length.

The empirical study was based on the hedonic hypothesis thatgoods are valued according to the utility of their attributes. Hedonicprices are defined as the implicit price of these attributes, estimatedstatistically through a regression analysis. In the first stage of thestudy, the direct effects of hotel-related locational characteristicson prices were estimated. In this way, the price repercussions of thedistance to the beach, distance to the centre of the tourist resort,existence of a roomwith or without a sea view, and general effect ofthe tourist resort where the hotel was located could all be observed.The resort-related location attributes could not be included in thisregression due to a lack of more precise data and in order to avoidcollinearity. Thus in the second stage of the study, price differencesin resorts from the previous estimation were tested against certainattributes specific to these areas. Firstly, the distance from theairport was tested as a possible cause of price discrepancies in theresorts. Secondly, the density of hotels at the different resorts wasanalysed, followed finally by beach-related characteristics.

The paper is structured as follows. The next section outlines thedata that was used, followed, in section three, by an explanation ofthe empirical model. A summary is then given of the main results,and the paper finalizes with a discussion of the conclusions.

hotel or tour operatorPlayground Whether the hotel has a play areaAir conditioned Whether the hotel has air conditioningTV Whether the room has a TVSatellite TV Whether the room has satellite TVLift Whether the hotel has liftsGardens Whether the hotel has gardens or terracesEntertainment Whether the hotel offers entertainmentNo smoking Whether the hotel has no-smoking areasSwimming pool Whether the hotel has swimming poolsTennis Whether tennis is available at the hotel or in

the vicinityBicycles Whether bicycle hire is available at the hotel or in

the vicinitySports Whether sports are available at the hotel or in the

vicinityGym Whether the hotel has a gymSauna Whether the hotel has a saunaGolf Whether golf is available at the hotel or in the

vicinityMini-bar Whether the room has mini barInternet Whether the hotel has Internet facilitiesChain Whether the hotel belongs to a chainNo. of rooms Total no. of hotel roomsNo. of floors Total no. of hotel floorsExclusive Whether the hotel is only marketed by this tour

2. Data

The data used in the analysis was taken from a dataset ofpackage holiday prices, all for holidays to the Balearics sold by asample of British and German tour operators (the two main na-tionalities of tourists to the Balearic Islands). Information wasgathered about the prices and different characteristics of thepackage holidays described in the brochures. To complete thedataset, certain location attributes for each tourist resort were alsoused.2

Eleven German and nine British tour operator travel brochureswere taken for the summer of 2008. The German travel brochureswere published by Phoenix, ITS, JahnReisen, Tjaerborg, ThomasCook, Alltours, Neckermann, World of TUI, 1e2 Fly and FroschTouristik, SLR. The British ones were published by Thomson,Panorama, Porland, Skytours, First Choice, Cosmos, Thomas Cook,Ecplise and Airtours. This is a representative sample since, in termsof their market share, they encompassed almost all the tour oper-ators specializing in British and German package holidays toMajorca (FVW International, 2009). A total of 3636 prices were

2 This additional data was provided by the University of the Balearic Islands“Sistemes d’Informació Geogràfica i Teledetecció (SIGT)” and the “Institut Balear deTurisme (IBATUR)”.

analysed, 3101 relating to German tour operators and 535 to Britishones. The package holidays marketed by these companies covereddifferent parts of the island of Majorca (Spain). Fig. 1 shows a mapof Majorca and the different tourist resorts included in the study.From Fig. 1, it can be observed that some resorts were only targetedat one of the two nationalities. Indeed, very few of them featured inboth German and British travel brochures.

Tour operator package holiday prices for the same hotel varied,depending on the specific characteristics of the package (the bedsper room, type of board etc.) and on other factors (i.e. transportcosts, the length of stay and season of the year). For the purposes ofour analysis, as in Aguiló, Alegre, Riera (2001), we examined theinfluence of the characteristics of the package holidays on prices,rather than the influence of transport costs or the season of the yearwhen the holiday was taken. Thus, our analysis focused on holidaystays in Majorca (the Balearic Islands) at one to five-star hotels,taking prices for the first week (7 nights) of August 2008 (the highseason), with departures from Düsseldorf in the case of Germantourists and Gatwick in the case of British ones. The high seasonwas chosen (MayeOctober) because these are the months when

operatorQ Whether the hotel has been awarded a “Q” for

quality hallmark, guaranteeing quality, safety andprofessionalism. “Q” is a government-controlledquality guarantee: http://www.calidadturistica.es

Table 2Descriptive results of the variables used in the analysis.

Variables German packages British packages

N Mean/Frec (%)

Min. Max. Standarddeviation

Variables N Mean/Frec (%)

Min. Max. Standarddeviation

Locational characteristics Locational characteristicsArea 3101 Area 535PLAYAS DE

ALCUDIA14,7 ALCUDIA 16,4

CALAS DECALA MILLOR

15,4 PUERTOANDRATX-CAMP DE MAR

1,5

CALA D’OR-PORTO PETRO

8,0 CA’N PICAFORT 4,3

CALAS DECAPDEPERA

12,3 CALABONA-CALAMILLOR

6,5

PUERTOPOLLENSA

1,2 CALAD’OR

14,2

CALA MAYOR-MAGALUF

3,0 CALADOMINGO-PORTOCOLOM

3,7

COLONIA DESANT JORDI

3,9 CALAMAYOR-PORTLAS

1,7

PLAYASPONENT

14,4 PUERTOPOLLENSA

14,4

PUERTO DESOLLER

3,5 MAGALUF-CALA VIÑAS

14,6

PLAYAS DEPALMA

23,6 SANTAPONSA-EL TORO

9,0

PALMANOVA

10,8

SA COMA-S’ILLOT

2,8

Distance tocentre (m)

3101 731,43 0 5000 1183,63 Distanceto centre (m)

535 962,29 0 5000 1453,07

Distance tobeach (m)

3101 193,99 0 1500 239,06 Distanceto beach (m)

535 171,24 0 1300 244,40

Sea view 3101 18,6 Sea view 535 23,0Area characteristics Area characteristicsDistance from

airport (Km)10 50,83 9,83 80 21,80 Distance

from airport(Km)

12 52,42 25 71 17,73

Congestion 10 Congestion 12Hotels in the

area/totalcoastal hotels

0,10 0,02 0,26 0,07 Hotels inthe area/totalcoastal hotels

,04 ,02 ,09 ,02

Hotel rooms/total roomsin coastalhotels

0,10 0,01 0,25 0,07 Hotel rooms/total roomsin coastal hotels

,05 ,02 ,10 ,02

Accommodation/totalcoastalaccommodation

0,10 0,02 0,16 0,05 Accommodation/totalcoastalaccommodation

,05 ,01 ,10 ,02

Beach-relatedvariables

10 Beach-related variables

12

Beaches inthe area

6,80 1 16 4,54 Beachesin the area

3,42 1 9 2,87

Surface areabeach (m2)

161233,92 17666,99 504971,80 132922,83 Surfacearea beach (m2)

80072,47 9555,28 299192,70 86355,17

Length ofbeaches (m)

3704,10 924 10202 2815,21 Length ofbeaches (m)

1806,17 195 7612 2067,11

Perimeter ofbeaches (m2)

9007,70 1905,85 23567,81 6131,58 Perimeterof beaches(m2)

4281,82 547,06 16862,44 4473,02

Non-locational characteristics Non-locational characteristicsRating 3101 Rating 5351 star ,9 1 star 02 star 3,1 2 star 3,93 star 51,6 3 star 67,34 star 39,8 4 star 28,05 star 4,7 5 star ,7

J. Alegre et al. / Tourism Management 38 (2013) 131e141134

Table 2 (continued )

Variables German packages British packages

N Mean/Frec (%)

Min. Max. Standarddeviation

Variables N Mean/Frec (%)

Min. Max. Standarddeviation

Type of room 3101 Type of room 535Single 33,9 Single 29,9Double 40,3 Double 41,5Three sharing 25,9 Three sharing 28,6Type of board 31,1 Type of board 535Half board 63,2 Half board 63,0Full board 6,2 Full board 12,0Breakfast 12,9 Breakfast 3,0All inclusive 17,7 All inclusive 22,1Tour operator 3101 Tour operator 535Alltours 9,0 Cosmos 12,3FTI 7,7 Thomas Cook 25,0Phoenix 2,6 Eclipse 2,41-2 Fly 12,2 First Choice 9,5SLR 18,3 Panorama 11,8Thomas Cook 4,9 Portland 6,4World of TUI 14,6 Skytours 7,7ITS 8,0 Thomson 12,5Jahn Reisen 7,8 Airtours 12,3Neckermann 11,3Tjaerborg 3,7Babysitting 3101 30,1 Babysitting 535 49,3Playground 3101 35,5 Playground 535 50,3Air-conditioned 3101 88,9 Air-conditioned 535 88,8TV 3101 92,4 TV 535 80,4SAT-TV 3101 91,6 SAT-TV 535 45,8Lift 3101 96,4 Lift 535 90,8Gardens 3101 99,5 Gardens 535 98,1Entertainment 3101 81,3 Entertainment 535 90,1No smoking 3101 36,4 No smoking 535 18,1Swimming pool 3101 98,5 Swimming pool 535 99,3Tennis 3101 57,9 Tennis 535 48,2Bicycles 3101 37,6 Bicycles 535 11,2Sports 3101 87,0 Sports 535 66,5Gym 3101 48,3 Gym 535 30,5Sauna 3101 50,0 Sauna 535 36,3Golf 3101 25,2 Golf 535 13,1Mini-bar 3101 40,8 Mini-bar 535 32,7Internet 3101 45,3 Internet 535 21,7Chain 3101 59,5 Chain 535 63,9No. of rooms 3101 190,6 13 1072 106,8 No. of rooms 535 334,69 21 757 184,24No. of floors 3101 5,2 1 14 2,3 No. of floors 535 6,33 1 13 3,05Exclusive 3101 ,7 Exclusive 535 16,4Q 3101 5,1 Q 535 13,8

J. Alegre et al. / Tourism Management 38 (2013) 131e141 135

most tourists visit the Balearic Islands. The first week of August waspicked at random. Our choice of Düsseldorf and Gatwick Airportswas based on the fact that they deal with 20.9% and 29.9% of allGerman and British tourists to the Balearics, respectively (Governde les Illes Balears, 2000).

Once the aforementioned variables (the transport cost, length ofstay, and season of the year) had been homogenized, the maincharacteristics of the package holidays featured in the brochurescould be defined. The brochures described the features of eachpackage holiday in detail (i.e. the category of hotel, its proximity tobeaches, the existence of a swimming pool etc.) and they gave anoverall price rather than a price for each component of the holiday.Many of the characteristics described in the brochures can beassociatedwith the hotels’ star ratings,3 which are regulated by law.However, it should be stressed that a full picture of a hotel orholiday cannot be gained from a star rating, and other

3 Sinclair et al. (1990) point out that the hotel rating is a good indicator of theservices and facilities that it offers.

characteristics may influence package holiday prices. This set ofcharacteristics was thought to fit into one of two groups, location ornon-location attributes. Table 1 describes the variables included inthe dataset and Table 2 shows the number of observations, themean or frequency (in %), minimum value, maximum value andstandard deviation of these variables.

3. The empirical model

The empirical analysis was based on the hedonic price method.This method is founded on what is known as the hedonic hy-pothesis, according to which people assess a product by the use-fulness of its characteristics and not by the product in itself (Rosen,1974). Hedonic prices are defined as the implicit prices of thesecharacteristics. Lancaster (1966) introduced the idea that con-sumers do not obtain utility directly from a good but from itscharacteristics. The hedonic price method is based on this con-sumer choice theory, but it was Rosen (1974) who first formalizedthe theoretical basis of this method. The hedonic price method canbe adapted to services and, more specifically, to package holidays.

J. Alegre et al. / Tourism Management 38 (2013) 131e141136

According to the hedonic hypothesis, the price of a package holidaycan be expressed in terms of its location-related and non-locationalpackage holiday characteristics. In other words, we can establishwhat is known as the hedonic price function:

Table 3Estimated effects of location and non-location attributes for German and British tour op

Dependent variable: lnprice

Estimated German hedonic model

B Sig.Intercept 6.988 .000Location-relatedAreaPLAYAS DE MURO �.040 .000CALAS DE CALA MILLOR �.036 .000CALA D’OR-PORTO PETRO .004 .672CALAS DE CAPDEPERA �.052 .000PUERTO POLLENSA �.020 .360CALA MAYOR-MAGALUF .024 .111COLONIA DE SANT JORDI .015 .253PLAYAS PONENT .009 .261PUERTO DE SOLLER �.032 .023PLAYAS DE PALMA 0 .

Distance to centre �0.0000314335 .000Distance to centre squared 0.0000000089 .000Inverse distance to beach 0.0514653382 .000Sea view .085 .000

Non-location-relatedRating1 star �.713 .0002 star �.645 .0003 star �.560 .0004 star �.409 .0005 star 0Type of roomSingle room .171 .000Double room .050 .000Three sharing 0Type of boardHalf board �.141 .000Full board �.049 .000Bed & breakfast �.171 .000All inclusive 0Tour operatorAlltours �.143 .000FTI .062 .000Phoenix .087 .0001e2 Fly �.107 .000SLR .075 .000Thomas Cook .084 .000World of TUI .109 .000ITS .000 .975Jahn Reisen .080 .000Neckermann �.041 .003Tjaerborg 0 .Babysitting .045 .000Playground �.013 .026Air-conditioned .059 .000TV .023 .019Entertainment �.023 .000Swimming pool .087 .000Tennis .020 .000Bicycles .010 .051Golf .014 .025Mini-bar .033 .000Internet .021 .000Chain .027 .000Number of rooms 0.0001610778 .000number of floors �0.0152112873 .000

Adjusted R2 ¼ 0.79

*Joined due to the lack of representativeness of 5-star hotels.

P ¼ f (distance to the beach, distance to the tourist centre, seaview, area, non-locational characteristics).

Where the price of a package holiday, P, is a function of all itslocation and non-locational characteristics.

erators.

Estimated British hedonic model

B Sig.Intercept 6.701 .000Location-relatedAreaALCUDIA .041 .140PUERTO ANDRATX-CAMP DE MAR �.109 .008CA’N PICAFORT �.035 .249CALA BONA-CALA MILLOR �.125 .000CALA D’OR �.018 .553CALA DOMINGO-PORTO COLOM �.054 .111CALA MAYOR-PORTLAS �.005 .897PUERTO POLLENSA .034 .252MAGALUF-CALA VIÑAS .061 .033SANTA PONSA-EL TORO .097 .001PALMA NOVA .048 .084SA COMA-S’ILLOT 0Distance to centre 0.0000761454 .000Distance to centre squared �0.0000000091 .005Inverse distance to beach 0.0705476237 .016Sea view .066 .000Non-location-relatedRating2 star �.117 .0003 star �.111 .0004 and 5 star* 0

Type of roomSingle room .188 .000Double room .071 .000Three sharing 0Type of boardHalf board �.140 .000Full board �.068 .000Bed & breakfast �.165 .000All inclusive 0Tour operatorCosmos �.018 .296Thomas cook .055 .000Eclipse �.047 .067First choice .041 .009Panorama .210 .000Portland .091 .000Skytours .058 .001Thomson .158 .000Airtours 0

Q .093 .000Babysitting .063 .000Playground �.038 .000Gym .080 .000Golf .031 .017Mini-bar .018 .097Internet .034 .002No smoking .026 .050Number of rooms �0.0001441319 .000

Adjusted R2 ¼ 0.84

Fig. 2. The ‘distance to the beach’ effect for German and British tourists.

J. Alegre et al. / Tourism Management 38 (2013) 131e141 137

The implicit prices are econometrically estimated by means of aregression analysis, and the non-location attributes are included inthe regression as dummy variables (the hotel rating, type ofroom, type of board, tour operator, babysitting, playground,air-conditioning, TV, entertainment, swimming pool, tennis, bi-cycles, golf, mini-bar, Internet, hotel chain, Q symbol, gym and non-smoking facilities) or discrete variables (the number of rooms andnumber of floors).

An outline will now be made of the location attributes, the mainfocus of this paper. The ‘distance to the beach’ and ‘distance to thecentre of the resort’ attributes refer to the distance from the hotel tothese places in metres. Following Bull (1998), the distance to thebeach was included in the regression equation in a non-linearmanner, as the inverse of this distance. This was because the ef-fect of a shift from a seafront hotel to a non-seafront one close to thebeach was greater than a shift from a hotel far from the beach toanother even further away. When a certain threshold point fromthe beach is reached, a few more kilometres might not make anydifference to tourists. The distance to the centre was included inquadratic form, since the effect on prices was not expected toremain constant as the distance grew and, from a certain point, theeffect might actually be just the reverse. ‘Sea view’ was a dummyvariable indicating whether a room had a sea view or not, and ‘area’was another dummy variable showing the resort where the hotelwas located. This attribute’s estimated implicit prices capturedarea-specific effects on price, interpreted as differences in touristresorts that cannot be accounted for by differences in the charac-teristics advertised in the brochures. To explore the source of thesearea-specific price differences, a hedonic price index was con-structed. First of all, the percentage change in relation to thereference area was calculated: ðe~l � 1Þ*100 To construct the index,the reference area was assigned a value of 100. The value for theremaining areas is the reference value (100) plus/minus thecalculated percentage change in relation to the reference area.

Although dummy variables for the resorts were included in theaforementioned regression model, the inclusion of any otherresort-related characteristic would have led to a problem of exact

Fig. 3. The ‘distance to the centre’ effe

multicollinearity and so a complementary analysis was needed inorder to analyse the effect of certain general features of the resortson prices. Consequently, once the area effect had been estimated inthe hedonic regression, it was related to relevant characteristics ofthe resorts. In this paper, three possible sources of price differencesin the resorts were examined: the distance from the airport to thetourist resort, the area congestion (the density of hotels at a specificresort in relation to the total number of coastal hotels), and anumber of beach-related characteristics, such as the number ofbeaches and total surface area, length and width of the beach(es).

4. Results

4.1. Hedonic regression

The presented results are taken from separate estimations of themodel for the two nationalities. British and German package holi-days tend to be concentrated in different parts of the island, withsome areas mainly receiving either British or German tourists. Inaddition, by estimating the model separately for each nationality, itwas possible to work under the assumption that the effects of theexplanatory variables on prices might be different for each na-tionality. The final estimations supported this hypothesis because adifferent value or even sign was obtained for some estimated co-efficients. Nonetheless, prior to this, the hypothesis of equal co-efficients was tested using a sub-sample drawn up by using Britishand German package holidays to the same area. The results of thissub-sample show that although there were no statistically signifi-cant differences between both nationalities for some of the mainexplanatory variables (like the category of hotel), big differencescould be observed for others, as was the case of some of thelocation-related variables (the distance from the hotel to the centreof the resort and the dummies indicating the area where the hotelwas located). Having said that, statistically different coefficientswere also obtained for other characteristics of the package holiday(a mini-bar in the room, the availability of bicycles, non-smokingareas, the number of floors in the hotel, and whether the hotel

ct for German and British tourists.

Table 4German and British area-based hedonic indexes.

German areas Index British areas Index

CALA MAYOR-MAGALUF 102.41 SANTA PONSA-EL TORO 110.22COLONIA DE SANT JORDI 101.49 MAGALUF-CALA VIÑAS 106.31PLAYAS PONENT 100.91 PALMA NOVA 104.90CALA D’OR-PORTO PETRO 100.44 ALCUDIA 104.23PLAYAS DE PALMA 100.00 PUERTO POLLENSA 103.44PUERTO POLLENSA 97.99 SA COMA-S’ILLOT 100.00PUERTO DE SOLLER 96.81 CALA MAYOR-PORTLAS 99.53CALAS DE CALA MILLOR 96.43 CALA D’OR 98.18PLAYAS DE ALCUDIA 96.11 CA’N PICAFORT 96.54CALAS DE CAPDEPERA 94.93 CALA DOMINGO-PORTO

COLOM94.75

PUERTO ANDRATX-CAMPDE MAR

89.68

CALA BONA-CALA MILLOR 88.22

Fig. 4. The relationship between the German area-based hedonic index and the dis-tance from the airport.

J. Alegre et al. / Tourism Management 38 (2013) 131e141138

belonged to a chain). The results of the separate estimations foreach nationality are shown below.

To determine the functional form, a BoxeCox test of the linearand log-linear functional forms was performed. The test showedthat, with our data, it was better to use a log-linear functional form.The estimated models had a goodness-of-fit coefficient (adjustedR2) of 0.79 for the German estimation and 0.84 for the British one.Table 3 shows the estimated effects of location and non-locationattributes for German and British tour operators, respectively.

Generally speaking, the signs of the non-location attributeswere as expected and they coincided with those obtained in pre-vious papers on package holidays.

All the location attributes were statistically significant for bothnationalities (F-statistic, p-value 0.000). Having a room with a seaview pushed up the price by 8.84% for German package holidaysand by just 6.85% for British ones. The estimated ‘distance to thebeach’ parameter was positive and statistically significant for bothnationalities (p-value 0.000). Fig. 2 plots the effect of the distance tothe beach on prices for German and British package holidays. The x-axis plots the distance to the beach in metres, while the y-axisshows the effect on prices, in percentage terms, of staying at a hotellocated at a distance of i from the beach, calculated aseb1 ðð1=BeachiÞ � ð1=BeachoÞÞ*100. b1 represents the estimatedparameter of the ‘distance to the beach’ attribute, included as theinverse of this distance. A value of 100 was given to a hotel with abeachfront location. When the price of a beachfront hotel and hotelwith a near-beachfront location (10 m away) is compared, the plotshows a huge drop in price of 22.28% for German tourists and29.23% for British ones. From then on, the effect lessens as thedistance grows, until a certain point is reached (175m) where a fewmetres more or less might make no difference to tourists.

As for the effect of the distance to the centre of the resort onprices, it was statistically significant for both nationalities (p-value0.000), although the effect differed from one nationality to the other.Fig. 3 shows the non-linear relationship between the distance to thecentre of the tourist resort and the prices of German and Britishpackage holidays. The x-axis plots the distance to the centre of theresort in metres, while the y-axis shows the effect, in percentageterms, of staying at a hotel located at a distance of i from the centreof the resort on prices, calculated as eðb2centeri�b2center2i Þ*100:. b2 andb3 are the estimated parameters of the ‘distance to the centre of theresort’ attribute, which was included in quadratic form. A value of100 was assigned to hotels located in the centre of the tourist resort.For German tour operators, the further a hotel is from the centre of aresort, the more prices drop until a minimum price is reached at adistance of 1775 m. From this point onwards, prices begin to rise.The price of a package holiday at a hotel in the centre of a resort is2.73% more expensive than the price of one located on the 1775-mthreshold.

British tourists differ fromGermans, given that they paymore tostay far from the centre. Prices peak a long way from the centre(4200 m), showing an increase in price of 17.34%. From this pointon, as the distance grows, the effect on prices declines.

The tourist areawhere the hotel was locatedwas found to have astatistically significant effect on prices (F-statistic, p-value 0.000)and statistically significant price differences were observed be-tween certain resorts and the reference one (Playa de Palma forGerman estimations and Sa Coma for British ones).

4.2. The area-based hedonic price index

Using the estimated parameters for the tourist areas, hedonicindexes were created, as explained in the above section. Table 4shows the area-based hedonic indexes for German and Britishpackage holidays, respectively. The different set of resorts for each

nationality is due to the different distribution of both nationalitiesin Majorca, as shown in Fig. 1. With these indexes, a price-rankedlist of tourist resorts could be drawn up, allowing us to observewhich areas were sold at a premium. For German tourists, a pack-age holiday at a hotel in Cala Mayor-Magaluf (the most expensivearea) was 7.87% dearer than a holiday at a hotel of the same char-acteristics located in Calas de Capdepera (the cheapest area). Theseprice differences were even bigger for British packages. The price ofan identical package holiday was 24.93% more expensive if thehotel was located in Santa Ponsa-El Toro as compared with CalaBona-Cala Millor. From the estimated hedonic price indexes, itcould be seen that price differences in German package holidays atdifferent resorts were lower than price differences in British ones.This might indicate that German tourists are less sensitive to thehotel’s location in Majorca than British tourists.

4.3. Correlation analysis

As mentioned in the section on the empirical model, a secondanalysis was required to estimate the effect of the different areas’locational characteristics on prices. Thus, after area-based hedonicprice indexes had been created to show price differences in touristareas, correlations were estimated to assess whether these dis-parities could be associated with specific location-related factors ineach tourist area. Three possible factors were considered: the dis-tance from the airport to the tourist resort, the density of hotels in

Fig. 5. The relationship between the British area-based hedonic index and the distancefrom the airport.

J. Alegre et al. / Tourism Management 38 (2013) 131e141 139

the tourist area in relation to the total number of coastal hotels (ameasure of congestion), and some beach-related variables, such asthe number of beaches in the area and the total surface area, lengthand width of the beach(es) there.

Congestion occurs in an area, first as a result of business locationcriteria, guided by the expected positive effects of agglomeration aswell as finding places with an abundant supply of infrastructureand public goods (Yang et al., 2012). These pull factors, however,can have negative effects on profitability from some threshold,where the enjoyment of public goods (environmental quality,public infrastructure availability etc.) is less satisfactory for tourists.Perhaps the feeling of congestion in an area has an importantcomponent of subjective or personal perception. However, thisdoes not eliminate the possibility of using objective measures ofcongestion. In this paper, the ratio between the number of hotels ata specific tourist area and the total number of coastal hotels inMallorca has been used as a measure of congestion in the area,although other alternatives definitions have been tested (as thenumber of hotel rooms), with the same result: no relationship wasfound between the area-based hedonic index and the level ofcongestion at the resort or its beach-related characteristics.

Figs. 4 and 5 show the relationship between the area-based he-donic index and thedistance fromthe airport forGermanandBritishpackage holidays, respectively. In the case of German package hol-idays, the correlation was negative and statistically significant(�0.642). For British package holidays, the correlationwas negativeand high (�0.417), although it was not statistically significant due tothe reduced number of observations. Hence the results suggest thatthe distance from the airport to the resort where the hotel is locatedis the main explanatory factor for prices, with package holidaysdropping in price, the further the hotel is from the airport.

5. Conclusions

This paper has analysed the effect of a hotel’s location on pricesin relation to the core product (beaches) and other locational char-acteristics of tourist resorts. It has also attempted to identify whichof these locational characteristics results in certain areas beingmarketed at higher prices than others. Tourism literature on thesubject has tended to focus on the characteristics of hotels ratherthan aspects associatedwith their location and, if the latter has beentaken into account, only some such characteristics have beenconsidered. This paper has tried to fill this gap by analysing and

quantifying the effect of location attributes on prices at a sun andsand destinations, taking two different types into consideration:hotel-related location attributes and other more general onesassociated with the location of the resort. In the first case, the dis-tance to the beach, distance to the centre of the tourist resort, aroom with or without a sea view, and the area where the hotel waslocated were all taken into consideration. In the second instance,three characteristics were analysed: the distance from the airport tothe tourist resort, the density of hotels there, and certain charac-teristics associated with the resort’s beaches, such as the number ofavailable beaches or their total length.

By using the hedonic method for the empirical analysis, theimplicit price of each hotel-related location attribute (the distanceto the beach, distance to the centre of the tourist resort, a roomwithor without a sea view, and the corresponding area) could be esti-mated. The ‘distance to the beach’ variable had an explanatorycapacity on package holiday prices for both nationalities, demon-strating that a higher package holiday price was charged for abeachfront location, although the effect on prices was negligiblewhen hotels a few metres from the beach were compared withones just beyond them. Consequently, for non-seafront hotels, theeffect of the distance from the beach on prices was only very slight.Aguiló et al. (2003), Espinet et al. (2003) and Rigall-i-Torrent &Fluvià (2007; 2011) also found that a beachfront location wasmarketed at higher prices. Linking in with this is the importance ofthe ‘sea view’ attribute. Having a roomwith a sea viewwas found toincrease the price by 8.84% for German packages and 6.85% forBritish ones.

The distance to the centre of the resort was also found to affectprices, although the effect differs for each nationality. This could bedue to the two nationalities’ different preferences in this respect.German package holiday prices are higher if the hotel is located inthe centre of a tourist resort, while British prices increase as thedistance to the centre grows. German tourists therefore seem to bemore willing to pay for hotels in the centre of a tourist resort thanfor hotels at a distance from it. However, when a certain thresholdpoint is reached, a further increase in this distance drives the priceup and so German packages are sold at a higher price if the hotel islocated in the centre of a tourist resort and when it reaches acertain distance from it (more than 1775 m from the centre) if it isset in tranquil surroundings. In contrast, British tourists seem toprefer hotels that are not located in the centre of a resort, given thatprices increase as the distance to the centre grows. Having said this,they do like to be close to the centre, because from a certainthreshold point, a further increase in the distance implies adecrease in prices.

Previous studies (Close, 2012; Kozak, 2002; Mykletun, Crotts,Mykletun, 2001; Prayag and Ryan, 2011) have shown that nation-ality affects some tourist motivations and preferences and that it isa useful proxy in measuring cultural differences in tourists. Nicolauand Más (2006) show that different motivations influence theprices tourists are willing to pay for a package holiday. From ouranalysis of the aforementioned location attributes, it can only beconfirmed that tour operators set prices differently for each of thetwo nationalities. This could be accounted for by differences intourist motivations or preferences, thereby encouraging tour op-erators to set higher prices when there is a greater willingness topay more for a hotel in a particular location.

It was also found that the area itself explains package holidayprices. Furthermore, there are price differences in areas that cannotbe accounted for by our set of location or non-location attributes.From the area-based hedonic price indexes, it was possible toobserve which areas are sold at a premium. For German packages,Cala Mayor-Magaluf (the most expensive area) is marketed at a7.87% higher price than Calas de Capdepera (the cheapest area).

J. Alegre et al. / Tourism Management 38 (2013) 131e141140

These price differences are even bigger for British packages. Theprice of a package holiday of the same characteristics is 24.93%more expensive if the hotel is located in Santa Ponsa-El Toro ascompared with Cala Bona-Cala Millor. In addition, these resultsshow that both nationalities have different preferences. While theGermans seem to regard Majorca as a general destination, with noparticular preference (seen in price differences) for any special area,the British seem to prefer some specific parts of the island and to bewilling to pay more for this. Previous studies (Aguiló et al., 2005)have demonstrated the important role that location plays in theprice of package holidays to Majorca. In Aguiló et al. (2005), it issuggested that tourists are increasingly demanding when it comesto price/quality ratios and, indeed, to the tourist area in general.Price differences in areas would be explained by tourists’ percep-tions of them, particularly in the cases of destinations with a highrepeat visitor rate (where visitors would be more familiar withdifferent resorts).

To analyse the possible causes of these prices differences intourist areas, a correlation analysis was conducted. Due to a prob-lem of perfect collinearity, we were unable to incorporate theseattributes into the hedonic regression. In this paper, three possibleexplanations for these price differences were tested: the distancefrom the airport, the density of hotels in the area, and beach-relatedcharacteristics. Evidence was only found in the first case, with anegative relationship being observed between price differences inareas and the distance from the airport, since the price of packageholidays of identical characteristics decreases as the distance fromthe airport to the resort grows.

The results of this research study could be of interest to hotelmanagers and policy makers. Hotel managers would have anothermeans at their disposal of identifying and promoting attributes thathave a positive effect on prices, while toning down or modifyingones with a negative effect. For instance, although a hotel might nothave a beachfront location, it might boast an elevated positionwithsea views, in which case this advantage can be emphasized on itswebsite and used in search engine keywords and a premium can becharged on its room rates. Likewise, a shuttle service to the beachcan be organized to reduce the negative impact of the distance tothe beach on prices. In addition, when hotels are renovated, at-tempts can be made to create as many sea-facing rooms as possible,thus ensuring a big rise in room rates.

The results of this study could also be useful when prices arenegotiated at a particular resort. A hotel’s location is a fix factor andby identifying which attributes affect prices and how much theyaffect them, prices can be adjusted (increased or decreased) toensure higher occupancy rates. Hoteliers must take advantage ofbargaining leeway with tour operators, trying to negotiate higherprices by highlighting their hotels’ strong points. In these negoti-ations, theymust be aware that certain location attributes can pushup room prices. If, on the other hand, they cannot charge highprices because their hotels are not close to the beach or do not havesea views, they can highlight other attributes that do have a positiveeffect on prices.

At the same time, tourism policies that are applied at severalmature mass sun and sand destinations could be improved on bypolicy makers. To give a few examples of recommendations derivedfrom this analysis:

1. When rejuvenation policies are being drafted for tourist re-sorts, emphasis should be given to refurbishing beachfronthotels and to freeing space by demolishing hotels whose lo-cations are regarded as more inferior by tourists.

2. At big resorts or ones that have grown up along the coastline,more than one tourist centre should be created, ensuring goodaccess and links to all of them.

3. In countries or regions where tourism accounts for a significantpart of the GDP, this type of study could be used in conjunctionwith others when decisions where to locate new airports aretaken.

4. Hotels and tour operators must design policies that takeadvantage of the positive effects of certain package holidaycharacteristics on prices. In particular, tourist preferences forcertain areas should be explored and taken into account whenprices are set.

In short, further analysis is needed to try and ascertain whatmakes one area preferable to another so that improvements can bemade to resorts (in terms of local policies) and market segmentsdefined as accurately as possible. In terms of supply-side policies,one of the most salient results of this study is the importance thatcertain areas and location attributes might have on prices. Morespecifically, resort-based price differences in hotels can beaccounted for by tourist preferences for certain areas.

Themain constraints of this studyweredifficulties indeterminingthe factors that explain these preferences for certain areas. Noconclusive results were obtained from the correlation analyses be-tween the hedonic prices of areas and certain resort-related char-acteristics, given the limited number of observations that wereavailable.Nonetheless, the results do showthe importance that someof these characteristics might have on hotel prices. Another issue tobear in mind is the fact that the analysis was conducted using meanprices. Future research must try and assess the effect of packageholiday characteristics onother points of theprice distribution, usingquantile regressions (Garcia & Raya, in press; McMillen, 2008).

Acknowledgments

This work was supported by the SpanishMinistry of Science andInnovation (ECO2010-20600).

References

Aguiló, P. M., Alegre, J., & Riera, A. (March 2001). Determinants of the price of Germantourist packages on the island of Mallorca”. Tourism Economics, 7(1), 59e74.

Aguiló, E., Alegre, J., & Sard, M. (2003). Examining the market structure of Germanand UK tour operating industries through an analysis of package holiday prices.Tourism Economics, 9(3), 255e278.

Aguiló, E., Alegre, J., & Sard, M. (2005). The persistence of the sun and sand tourismmodel. Tourism Management, 26, 219e231.

Alegre, J., Cladera, M., & Sard, M. (2011). Analysing the influence of tourist moti-vations on tourist expenditure at a sun and sand destination. Tourism Eco-nomics, 17(4), 813e832.

Alegre, J., & Garau, J. (2010). Tourist satisfaction and dissatisfaction. Annals ofTourism Research, 37(1), 52e73.

Bull, A. O. (1994). Pricing a motel’s location. International Journal of ContemporaryHospitality Management, 6(6), 10e15.

Bull, A. (1998). The effects of location and other attributes on the price ofproducts which are place-sensitive in demandAvailable from http://www4.gu.edu.au:8080/adt-root/uploads/approved/adt-QGU20030102.085840/public/02Whole.pdf.

Close, A. (2012). Tourist motivations: Differences between Anglophone and Franco-phone tourists. http://libdspace.uwaterloo.ca/handle/10012/6850.

Espinet, J. M., Saenz, M., Coenders, G., & Fluvia, M. (2003). Effect on prices of theattributes of holiday hotels: a hedonic prices approach. Tourism Economics, 9(2),165e177.

Fleischer, A. (2012). A room with a view-a valuation of the Mediterranean sea view.Tourism Management, 33, 598e602.

FVW International dokumentation. (2009). Europäische Veranstalter, 2009.Garcia J. and Raya J. “Analysis of inequality in housing prices: a quantile approach”,

Journal of Housing Economics, in press.Govern de les Illes Balears (2000), “El Turisme a les Illes Balears, dades informatives,

any 1999”. Palma de Majorca. (Government of the Balearic Islands (2000),Tourism to the Balearic Islands. Informative data for the year 1999, Palma deMajorca.)

Haroutunian, S., Mitsis, P., & Pashardes, P. (2005). Using brochure information forthe hedonic analysis of holiday packages. Tourism Economics, 11(1), 69e84.

Juaneda, C., Raya, J. M., & Sastre, F. (2011). Pricing the time and location of a stay at ahotel or apartment. Tourism Economics, 17(2), 321e338.

J. Alegre et al. / Tourism Management 38 (2013) 131e141 141

Kozak, M. (2002). Comparative analysis of tourist motivations by nationality anddestinations. Tourism Management, 23(3), 221e232.

Lancaster, K. J. (1966). A new approach to consumer theory. Journal of PoliticalEconomy, 74, 132e157.

Lee, S. K., & Jang, S. (2010). Room rates of U.S. airport hotels: examining the dualeffects of proximities. Journal of Travel Research, 20(10), 1e12.

McMillen, D. (2008). Changes in the distribution of house prices over time: struc-tural characteristics, neighborhood, or coefficients? Journal of Urban Economics,64, 573e589.

Mangion, M.-L., Durbarry, R., & Sinclair, M. T. (2005). Tourism competitiveness:price and quality. Tourism Economics, 11(1), 45e68.

Mykletun, R. J., Crotts, J. C., & Mykletun, A. (2001). Positioning an island destinationin the peripheral area of the Baltics: a flexible approach to market segmenta-tion. Tourism Management, 2(5), 493e500.

Nicolau, J. L., & Mas, F. J. (2006). The influence of distance and prices on the choice oftourist destinations: the moderating role of motivations. Tourism Management,27, 982e996.

Papatheodorou, A. (2002). Exploring competitiveness in Mediterranean resorts.Tourism Economics, 8(2), 133e150.

Pearce, D. (1989). Tourism development. Harlow, UK: Longman.Prayag, G., & Ryan, C. (2011). The relationship between the “push” and “pull” factors

of a tourist destination: the role of nationality ean analytical qualitativeresearch approach. Current Issues in Tourism, 14(2), 121e143.

Rigall-i-Torrent, R., & Fluvià, M. (2007). Public goods in tourism municipalities:formal analysis, empirical evidence and implications for sustainable develop-ment. Tourism Economics, 13(3), 361e378.

Rigall-i-Torrent, R., & Fluvià, M. (2011). Managing tourism products and destina-tions embedding public good components: a hedonic approach. Tourism Man-agement, 32(2), 244e255.

Rigall-i-Torrent, R., Fluvià, M., Ballester, R., Saló, A., Ariza, E., & Espinet, J. M. (2010).The effect of beach characteristics and location with respect to hotel prices.Tourism Management, 30(1), 1e9.

Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation inpure competition. Journal of Political Economy, 82(1), 34e55.

Sinclair, M. T., Clewer, A., & Pack, A. (1990). Hedonic prices and the marketing ofpackage holidays: the case of tourism resorts in Malaga. In G. Ashworth, &B. Goodall (Eds.), Marketing of tourism places (pp. 85e103). London: Routledge.

Smith, S. L. J. (1994). The tourism product. Annals of Tourism Research, 21(3), 582e595.

Taylor, P. (1995). Measuring changes in the relative competitiveness of package tourdestinations. Tourism Economics, 1(2), 169e182.

Thrane, C. (2005). Hedonic price models and sun-and-beach package tours: theNorwegian case. Journal of Travel Research, 43(3), 302e308.

Yang, Y., Wong, K. K. F., & Wang, T. (2012). How do hotels choose their location?Evidence from hotels in Beijing. International Journal of Hospitality Management,31(3), 675e685.

Joaquín Alegre is Ph.D. in Economics at the University ofBarcelona. Nowadays his position is Associate Professor atthe University of the Balearic Islands. He teaches StatisticsTechniques and Econometrics. His research topic of inter-est is Tourism Economics. He has co-authored severalbooks on statistics and econometrics. As regard their sci-entist articles, he has published articles focusing on thetour-operator industry, tourism expenditure (both at visi-tors’ destination and from household budget surveys)and tourism participation, tourists’ length of stay, tourists’loyalty and satisfaction.

Magdalena Cladera is Ph.D. in Economics at the Universityof Balearic Islands. Nowadays her position is AssociateProfessor at the University of the Balearic Islands. Sheteaches Statistics Techniques and Econometrics. Herresearch topic of interest is Tourism Economics. She hasco-authored several books on statistics and econometrics.As regard her scientist articles, he has published articlesfocusing on tourism expenditure, tourists’ loyalty andsatisfaction.

Maria Sard is Ph.D. in Economics at the University of theBalearic Islands and she is a professor of applied eco-nomics at this University. She teaches Macroeconomicsand Industrial Economics. Her research focuses on TourismEconomics. She has published several papers related onthe tour-operator industry and hedonic pricing.