being Shelby and Heberleins study. The research aim of this paper is to adapt the social car-

Enrique Navarro-Jurado (University of Malaga, Faculty of Tourism, Department ofGeography, Teatinos Campus. s/n, 29017. Malaga, Spain. Email ). Heobtained his Phd. in Geography from the University of Malaga in 2000. His research focuseson urban planning and environmental carrying capacity, sustainability indicators and thedevelopment of models in mature coastal destinations Mediterranean and Caribbean.

Annals of Tourism Research, Vol. 43, pp. 119, 20130160-7383/$ - see front matter 2013 Elsevier Ltd. All rights reserved.

Printed in Great Britain

http://dx.doi.org/10.1016/j.annals.2013.03.005www.elsevier.com/locate/atouresrying capacity model to a mature coastal destination, Costa del Sol. The empirical findingsprovide an indicator that allows us to establish the proportion of tourists who perceive over-crowding and are predisposed to leave. A cluster analysis was performed to better understandhow overcrowding is perceived by tourists, the socioeconomic characteristics of tourists andthe factors that may influence the capacity thresholds. The generating data will allow a scien-tific debate on the overcrowding problems and the growth limits. Keywords: carrying capac-ity, overcrowding, coastal destinations, perception, Costa del Sol. 2013 Elsevier Ltd. Allrights reserved.

INTRODUCTION

The Growth and Sustainability of Consolidated Destinations

Coastal destinations are characterized by a strong increase in de-mand and the occupation of a large amount of space, both of whichhave severe environmental and social impacts (Garay & Canoves,2011). In fact, a significant number of Mediterranean destinationsare characterized by maturity or, even decline according to the Butlermodel (2011). Since the 1990s, the future of consolidated sun andbeach destinations has been debated. Poon (1993) argued that thebreakdown of the Fordist model of mass tourism and the rise of thepost-Fordist model in the communication era would mean the endof mass tourism. Knowles and Curtis (1999) made the same determin-istic argument about the Mediterranean perimeter, claiming that theCARRYING CAPACITY MODELAPPLIED IN COASTAL

DESTINATIONS

Enrique Navarro JuradoIonela Mihaela Damian

AntonioFernandez-MoralesUniversidad de Malaga, Spain

Abstract: A large number of studies have been carried out on the social carrying capacity oftourists regions. Most of these studies have examined protected natural areas, the best known1

rejuvenation policies would achieve only a temporary delay in the trend

ical concept associated with limited growth, the idea of limits to growthmay be opposed because of the implications for economic develop-

2 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119ment. Saarinen (2006) related sustainability to the assignment of limitsto growth and to carrying capacity. In fact, sustainability and carryingcapacity have the same difficulties as the formulation of the ideas, prac-tices, utility and diversity of types of capacity.

Sustainability and Tourism Carrying Capacity

The concept of tourism carrying capacity arises from the perceptionthat tourism cannot grow continuously in a particular region withoutcausing irreversible damage to the local system (Coccossis & Mexa,2004). The concept of carrying capacity in tourism has its origins inthe 1960s, when it was developed to place limits on the numbers of vis-itors that a tourist attraction (such as a natural reserve) or destinationcould cope with (Coccossis & Mexa, 2004). Butler (2010) argues thatthe concept of carrying capacity in tourism was very much in voguein the 1970s, and has encountered a fall in interest since then. Manydefinitions of tourism carrying capacity have been proposed (Coccos-sis, Mexa, & Collovini, 2002; Saarinen, 2006) but the best known isthe World Tourism Organizations definition: the maximum numberof people that may visit a tourist destination at the same time withoutcausing destruction of the physical, economic or socio-cultural environ-ment and an unacceptable decrease in the quality of the tourist satis-faction (Coccossis et al., 2002, p. 38). This definition impliesvarious capacities: physical, economic, perceptual, social, ecological,and political (Getz, 1983).of declining visitor numbers at these destinations.Taking a more positive view, Ioannides and Debbage (1997) argued

that consolidated destinations are readjusting themselves to the mar-ket, by implementing new information and communication technolo-gies and by offering a tourism product that is target to particularmarket segments. Aguilo and Juaneda (2000), using supply and de-mand data on tourist spending, loyalty and satisfaction levels from1989 to 2000, concluded that the Balearic Islands, and, by extension,many mature Mediterranean destinations, will prosper and expandin the short and medium term. Without entering the debate aboutthe future of these destinations, it seems essential to achieve higher lev-els of sustainability at coastal destinations, because sustainability is animportant factor in development (Navarro, 2012) and competitiveness(Ritchie & Crouch, 2004).

Several authors have described the evolution of tourism develop-ment. Jafari (2001) analyzed it by applying four platforms as ways ofthinking about tourism: support, precaution, adaptation and knowl-edge. Macbeth (2005) included two more: the ethics (that is, therecognition of non-objective positions adopted by different fields thataffect tourism development), and sustainability. This latter is a polit-

number limit (Buckley, 1999; Lindberg, Mccool, & Stankey, 1997;Watson & Kopachevsky, 1996) because it is impossible to find a single

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 3number. This is because there are different ways to set limits (Saarinen,2006), there is no single carrying destination (Getz, 1983) and, the lim-its depends on human values and perceptions about resources, indica-tors, criteria and impacts (Saarinen, 2006).

In the community based tradition, the limit is viewed as a manage-ment concept (Lindberg et al., 1997). Managers have to know touriststhresholds because when this limit is exceeded, tourists flee to other,less-crowded, destinations, initiating the destinations decline and itsloss of competitiveness. The management of tourism crowding is animportant part of sustainable development (Jin & Pearce, 2011).

The Social Carrying Capacity of the Demand

To study tourists thresholds, it is necessary to know the demandcharacteristics. Tourist behavior and decision-making have always beena central issue in the tourism management literature (Papatheodorou,2001). In practice, managers usually ask why tourists hesitate or delay,or even change their destination and itinerary-related decisions?(Wong & Yeh, 2009). Numerous studies have identified various factorsthat prompt people to visit a destination (Nadeau, Heslop, OReilly, &Luk, 2008; Um & Crompton, 1990), and these factors are categorizedas pull (the external forces of the destination) and push factors (inter-nal, psychological forces) (Beerli, Meneses, & Gil, 2007; Yoon & Uysal,2005). These include factors such as tourist characteristics (Papatheod-orou, 2001), destination preferences and awareness (Goodrich, 1978),nationality (Pizam & Sussmann, 1995), attitudes (Um & Crompton,1990), health-related issues, safety, time, expenditure and trip distance(Bansal & Eiselt, 2004). A places image is derived from attitudes to-ward the destinations perceived tourism attributes (Um & Crompton,Saarinen (2006) applied this definition to sustainability limits, pro-posing three approaches that have guided studies according to differ-ent ontological ideas and different epistemological perspectives. First,the resource-based tradition based on a positivist ecological perspective(McKercher, 1993) and aims to protect resource by introducing limitsand measurable goals. Second, the activity based tradition in which lim-its are dynamic and the changes depend on how the destination adaptsto new situations and grounds the best known tourism model in the lit-erature, the product life cycle of Butler (2011); carrying capacity can beincreased by marketing, improving the infrastructure or renewing theproducts. This approach has a developmental perspective, and it isthe approach taken by various international organizations such asthe World Tourism Organization. Finally, the community based tradi-tion is based on communities and is related to information, knowledgeand relationships with empowerment; the limits are chosen throughparticipation of stakeholders by means of a process of social negotia-tion (Hughes, 1995).

Therefore, we must close the 1990s discussion about the magic

4 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 1191990) and recent research provides evidence that places image influ-ences tourists decisions (Pike & Ryan, 2004; Tapachai & Waryszak,2000). Therefore it is important to study tourists perceptions of thesaturation of a destination.

There are numerous case studies measuring tourists thresholds(Burton, 1975, Navarro, 2005; PAC/RAC, 2003). According to Shelbyand Heberlein (1986), we should determine carrying capacity by study-ing tourists expectations along with destination managers pre-deter-mined rules. In their study, the two sociologists develop conceptualfoundations, allowing the creation of social carrying capacity modelthat is still valid and has been applied to natural areas by distinguishingthe types of activities tourists engage in there. Vaske and Shelbys paper(2008, p. 123) reviews studies of perceived crowding from 1975 to 2005(all in recreational settings) and reports that the standards proposedby Shelby and Heberlein (1986) remain a viable method for assessingcarrying capacity judgments based on levels of perceived crowding.When people evaluate an area as crowded, they have at least implicitlycompared the conditions they experienced (impacts) with their per-ception of what is acceptable (standards) (Vaske & Donnelly, 2002).

Several studies show the factors that may influence carrying capacitythresholds, such as the tourists gender (Freedman, Levy, Buchanan, &Price, 1972), education (Fleishman, Feitelson, & Salomon, 2004) andsocio-economic status (Hayduk, 1983). Other factors include the fol-lowing: spatial organization of the destination (Stokols, 1972), socialenvironment of the destination (Rustemli, 1992), reasons for the expe-rience (Bellenger & Korgaonkar, 1980) different types of areas, re-sources and activities carried out (Mieczkowski, 1995), touristspsychological adaptation to different levels of use (Stankey, 1982),the tourists sociological characteristics and the type of trip that theyengage in (Santana & Hernandez, 2011), local peoples behavior to-ward tourists (Mieczkowski, 1995), familiarity with the destination(Getz 1983), noise and rude behavior (Ruddell & Gramann, 1994).

Another interesting line of research relates tourists satisfaction withcarrying capacity thresholds and states, the satisfaction model comesfrom economics, and the implicit evaluative criterion is the point ofmaximum aggregate benefits (Shelby & Heberlein, 1986, p. 55). Thismodel states that increasing the number of people at a destination willdecrease the satisfaction and it is called the economic approach (All-dredge, 1973). Moreover, other studies (Lucas, 1964) have defined car-rying capacity as the ability to provide satisfaction. However, studiessince the 1980s have suggest that increasing the number of touristsdoes not diminish satisfaction on the basis of four hypotheses thatare well documented in the literature (Shelby & Heberlein, 1986;Vaske, Donnelly, & Heberlein, 1980): self-selection, product shiftsand displacement, multiple sources of satisfaction and rational-izing. In conclusion, satisfaction may influence the overall satisfactionof the tourist experience but may not be the only variable with which tomeasure the carrying capacity.

Because of the difficulties associated with the concept of satisfaction,Shelby and Heberlein (1986) proposed using other variables. They

emphasized the need to verify the level of contact with tourists (how

completely transformed the territory, and its society and economy.The Costa del Sol is divided into two zones: the western part, which

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 5is the larger and more developed of the two zones; and the easternpart, where tourism competes with intensive, highly profitable agricul-ture (under plastic or in greenhouses).

The study area is in eastern Costa del Sol (Figure 1), and includes anarea of 331 km2 with, a population of 147,637 people in 2007 and55 km of coastline.

The area has strongly compartmentalized geographical characteris-tics, alternating between small floodplains, where the widest beachesare located, and mountains in a range that extends to the sea, formingsmall coves. These features, coupled with a subtropical climate (owingto mild temperatures and scarce rainfall), have great tourist potential.

In 2007, tourist accommodation could house 209,376 people in med-iumquality accommodation, mostly in holiday home (non-regulatedoffer). Only 16,392 places were formal offers, which is less than 7.8% ofthe accommodation available. The coastal area is complemented by theinternal area (Axarquia) offering considerable interest to tourist be-cause of its mix of: sun and beach, rural areas, cultural activities, adven-ture trips, marine activities, golfing etc.many times the different groups of tourists were engaged in each of thestudied recreational activities) and preferences regarding the con-tact (the number of people the tourist wanted to meet) in a particularactivity or destination. However, Tarrant and English (1996) arguedthat verification of the level of contact between tourists can existonly under certain background conditions in destination of low den-sity, making the concept potentially less useful in destination of highdensity than those carried out in the open (non-island coastal destina-tions). Navarro (2005) determined a saturation indicator for openspaces and, high- density destinations, adapting Shelby and Heber-leins method to coastal destinations.

The research reviewed here has three goals: first, to establish the per-centage of tourists who perceive overcrowding and are considering toleave; second, to deepen our understanding of how tourists perceiveovercrowding and of the socioeconomic characteristics and other factorsthat influence capacity thresholds; and third, reposition the problems ofovercrowding and the limits of growth in the scientific debate, particu-larly for the most popular destinations and those that need it most.

METHODOLOGY

Study Area

The Costa del Sol (Malaga, Spain) is one of the most important tour-ist destinations in the Spanish Mediterranean, with a well establishedreputation that attracts more than nine million tourists a year. Sinceit first became a tourist destination at the end of the 1950s, tourismhas been the most important productive sector in the area and has

6 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119The number of tourists visiting this region has been constantly grow-ing since the 1990s, from 1.5 million in 1996 to 1.9 million in 2007,

Figure 1. Location of the Study Area. Southeastern Coast of Costa del Sol(Spain)which has put great pressure on the territory. However, during the con-struction boom (19982007), the demand increased. For instance, theformal offer grew by 92% and the tourist housing by 40%. These datareflect how the development of tourism has been linked to urbangrowth, as is common in other Spanish Mediterranean destinations.The direct consequence of this excessive growth in offers is a majordrop in the hotel occupancy rate (from 73% in 1999 to 55% in2007) and, a decline in tourist daily expenditure (US$44.6 in 2000 goesto $38.7 in 2005), which created a direct effect in reducing the directeconomic impact of tourism, amounting to $729 million (556 mil-lion) (Junta de Andaluca, 2007) and great dissatisfaction with certainfactors (such as traffic, overcrowding, and noise) (Sociedad de Plan-ificacion y Desarrollo, 19992007).

Urban planning has influenced this growth, not tourism strategies,although economic and political situation has affected growth intourism, a sector with a very good image. The result has been a majortransformation of the coastal landscape, including irreversible environ-mental impacts (such as loss of beach sand, artificiality of watercourses,and groundwater contamination), a high economic dependence onreal estate, and economic benefits that have detracted from the qualityof life for resident.

In conclusion, the choice of the study area is justified for three rea-sons: it is a clear example to Spanish coastal destination that has expe-riences growth; it is a consolidated destination; and it is a popular

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 7The data have been analyzed in four phases. In the first phase, wedetermine the profile of the tourism demand through descriptiveFor our analysis, we draw on a survey of tourists in the Eastern Costadel Sol that was conducted from June to August 2007. Our sample in-cludes 739 interviews with a sampling error of 3.3% and a 95% confi-dence level. Data were collected directly from the tourists in placessuch as beaches and beach promenades, throughout the whole areaof the study. The number of interviews was distributed proportionallyto the tourist accommodation capacity of each of the five municipali-ties in which the beaches are located. In order to avoid biases derivedfrom an incorrect composition by nationalities of the sample, quotacontrols were taken for this variable, according to demand studies fromthe Tourist Observatory of Costa del Sol (Sociedad de Planificacion yDesarrollo, 19992008)and based in the tourist accommodationcapacity of each municipality.

The questionnaire was divided into four sections. The first section en-quires about tourists characteristics, such as: age, educational level,employment status and place of residence. The second section includesquestions related to the trip, such as: daily expenditure, length of stay,type of accommodation, whether the tourist would recommend the des-tination and trip satisfaction. The third section assesses various aspectsof the destination such as noise, authenticity, the number of people,and the spatial organization: the respondents were asked to choose from5 item scale, from a very negative to a very positive opinion. In thefourth and final part, overcrowding elements are included.

More specifically, to assess overcrowding in the place of residence,the tourist were asked to indicate, using a five-point scale, their levelof agreement with the statement that there are too many touristsin their usual place of residence, and how overcrowding influencedtheir satisfaction with their trip. This section of the questionnaire alsoused a five-point scale and asked tourists opinion on the current loadand whether they thought that too many people were in the visited pla-ces,(this is called perception of crowding) and their attitude to-ward overcrowding. Giving the impossibility of measuring theacceptable level of encounters, (Shelby and Heberleins value),the solution was to measure the tourists attitude toward possibleovercrowding, the predisposition of people ready to leave the destina-tion (also on five point scale). Reported encounters describe a count ofthe number of other people that an individual remembers observingin an area (Vaske & Donnelly, 2002). Perceived crowding is a subjective,negative evaluation that the number of encounters or people observedin an area is too many (Shelby & Heberlein, 1986).

Analysisdestination with a well-established image and is positioned in theMediterranean, the most important tourist region in the world.

Questionnaire Design and Sampling

analysis. The second phase aims at establishing the social carryingcapacity perceived by tourists obtained by linking the two questions:perception of crowding and tourists attitude toward possibleovercrowding. This indicator has been named the current risk

Table 1. Characteristics of Demand (N = 739)

Frequency(%)

Frequency(%)

Country of residence IncomeSpain 64.0 Less than 1,300 $ 6.8Great Britain and Northern

Ireland10.7 Between 1,301 $ and 1,900 $ 18.7

Germany 9.6 Between 1,901$ and 3,150$ 26.1France 3.4 Between 3,151$ and 4,300$ 25.6Italy 0.1 More than 4,301$ 22.8Benelux 1.6Ireland 1.4 Type housingThe rest of Europe 7.6 Hotel 18.3USA 0.4 Pension 1.6Others 1.2 Apartment hotel 5.3

Private house 39.1Age Housing rented to an individual 17.01829 years 23.4 Housing rented to an agency 7.23039 years 21.6 House of friends or relatives 9.14049 years 24.4 Camping 1.45064 years 24.0 Multiple property 0.1More than 65 years 6.6 Others 0.9

Study level Days of stayNo schooling 4.2 From 0 to 1 day 0.3Primary studies complete 13.9 Two days 13.8Secondary studies 34.1 From 3 to 6 days 23.7University studies at Bachelor

level21.7 From 7 to 10 days 24.7

University studies at a highergrade

21.1 From 11 to 15 days 15.4

Other 5.0 From 16 to 30 days 10.9More than 1 month 11.2

Professional categoryLiberal profession 6.4 Previous visitsEntrepreneur 7.1 Yes 74.1Executive 4.2 No 25.9Mid-level manager 4.1Qualified worker 27.6Unskilled worker 6.8High-level official 9.3Other officials 1.5

8 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119Student 11.1Housewife 7.2Retired 7.0Other 7.7

squared Euclidean distance was chosen as the dissimilarity measure.Discriminant analysis is used to validate the cluster solution.

among the clusters in the variables perception of crowding andattitude toward possible overcrowding in order to verify which have

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 9the highest current risk population, and thus to identify the profile ofthe tourist groups by means of segment analysis.

RESULTS

Sample Profile

The characteristics of tourist demand in the Eastern Costa del Solare shown in Table 1. A descriptive analysis of the sample indicates thatSpanish tourists (64%) are the largest group of tourists in the EasternCosta del Sol. The segment comprised of British and Irish tourists(11%) and German tourists (10%) is the most common foreign touristgroup. The analysis also reveals a medium-high cultural level of thetourists, with qualified workers (28%) with average purchasing power(nearly half earn more than $3,150 per month) being the dominantgroup. Private housing (39%) is the most popular accommodation, fol-lowed by hotels (18%), and most tourist (25%) stay seven to ten days. Itis also worth noting that tourist generally have a high level of familiaritywith the destination (74% of them have visited the region previously).

Estimation of the Social Carrying Capacity Perceived by the Tourists

We adapt Shelby and Heberleins social carrying capacity model(1986) to a mature coastal destination, as opposed to an insular desti-nation, in this research. The descriptive analysis of the sample indicatesCluster analysis is dependent on the selection of variables. Thus, vari-ables for inclusion in the cluster analysis should be chosen within thecontext of a theory (or theories), that is needed to support the classi-fication. In this sense, the considered variables are age and educationlevel (Fleishman et al., 2004), income (Hayduk, 1983), daily expendi-ture, perception of the amount of people and closed or open space(Stokols, 1972), including noise perception (Ruddell & Gramann,1994), authenticity of the study area (Navarro, 2005), and familiarity(previous visits) of an individual with the destination (ORiordan,1969). Similarly, we also include tourists perception of residents(Mieczkowski, 1995), tourists satisfaction with their experience (Lucas,1964), the dissatisfaction with overcrowding at the destination (Ryan &Cessford, 2003), overcrowding in the place of residence (Getz, 1983),perception of crowding and, the attitude toward possible overcrowd-ing. Finally, we investigate whether there are significant differencespopulation: tourists who perceive the overcrowding and are predis-posed to leave the destination they are visiting (Navarro, 2005). Thethird phase, examines a segmentation of tourists using cluster analysis,performed using the SPSS 19 program. The number of clusters wasdecided after hierarchical clustering with the Ward method and the

Andaluca or in SpainTotal 100 100

10 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119that 27% of tourists perceive crowding, whereas 49% do not and 24%are undecided (Table 2). According to Shelby and Heberlein (1986, p.62) if more than two-thirds of the visitors say that they are crowded, itappears likely that the capacity has been exceeded. If less than onethird senses the overcrowding, the area is probably below the loadcapacity. When the perception of the mass is between these thresholds,no determination can be made with this rule. Following this criterion,we conclude that the Eastern Costa de Sol did not exceed its capacity in2007. Faced with possible overcrowding of the destination, only 27% ofthe tourists would not be affected at all by the overcrowding, whereasthe rest would be affected (Table 2).

The cross classification of the two variables analyzed above shows thatonly 20% of tourists, represent the current risk population (touristsTable 2. Perception of Crowding at the Destination and Attitude TowardOvercrowding

Frequency (%) Frequency (%)

Perception of crowding Attitude toward possible overcrowdingStrongly disagree 10.30 It doesnt influence me in any

way26.60

Disagree 39.02 I would avoid areas withnumerous tourists

27.56

Neither agreeor disagree

24.39 I would visit in another season 19.92

Agree 18.97 I would go to another site in theCosta del Sol

9.55

Strongly agree 7.32 I would go to another site in 16.37who perceived overcrowding and are affected by it), i.e., only 20% oftourist have reached their carrying capacity thresholds for the destina-tion and are therefore predisposed to leave the destination.

Segmentation Analysis

We segmented tourist in the sample using cluster analysis, asdescribed in 2.3. Following the recommendation of Hair, Anderson,Tatham, and Black (1998), we considered the samples representative-ness and tested for the absence of multicollinearity. With regards to theformer, the sampling method, sample design and size (describedabove), mean that the sample representative of the population of inter-est. With regards to the latter, the elements of the matrix of correlationcoefficients between the variables included in the cluster analysisranges from .17 to +.38 indicating low collinearity among variables.

After performing hierarchical cluster analysis and examining thedendrogram, the group membership and group sizes and the aims ofthe study suggested a two-cluster solution.

We used discriminant analysis with appropriate tests to assess theclassification and consistency of the two groups obtained. One canon-ical discriminant function was estimated by using classical discriminantanalysis of all factors. The function is statistically significant as mea-sured by Wilks lambda (K = 0.434; with associated v2 = 537.53,d.f. = 15, p < 0.0001 and statistic F15,638 = 59.43, p < 0.0001), indicatingthat the function discriminates significantly between the two groups.However the data matrix of factors does not support the hypothesisof multivariate normality (Doornik-Hansens v2 = 730.52 and 1088.71for groups 1 and 2, both with d.f. = 30, p < 0.0001) and Boxs M statisticshows significant differences in error variances across them (BoxsM = 298.45, p < 0.0001). Thus, we also conducted a robust discriminantanalysis, by replacing the classical group means and within groupcovariance matrix by robust equivalents based on the minimum covari-ance determinant estimator (Todorov & Filzmoser, 2009). Robust testsof the homogeneity of variances, Levene and Browne and Forsythetests indicate that only three of the independent variables exhibit sig-nificant differences in their variances across groups. The robustly esti-mated discriminant function is also significant (K = 0.445; withassociated v2 = 521.41, d.f. = 15, p < 0.0001 and statistic F15,638 = 56.83,p < 0.0001). The classification matrices of the classical and robust dis-criminant functions showed that 88.36% and 86.22% of the cases, werecorrectly classified, respectively, indicating a relatively high accuracyand reliability of the cluster solution.

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 11An additional way in which to assess the stability of the estimatedcluster solution is to split the sample and cross-replicate the analysis.

Table 3. Identification of Clusters Based on the Perception of Crowding andthe Attitude Toward Overcrowding

TSC (n = 315/48.2%)

TNSC (n = 338/51.8%)

v2 gl p

Perception of crowding 11.353 4 0.023Strongly disagree 7.9 13.6Disagree 37.2 41.1Neither agree or disagree 23.5 23.4Agree 22.2 16.3Strongly agree 9.2 5.6Total 100 100

Attitude toward possible overcrowding 102.795 4 0.000It doesnt influence me in any way 12.1 41.4I would avoid areas with numerous

tourists27.3 28.7

I would visit in another season 21.6 16.9I would go to another site in the

Costa del Sol12.0 7.1

I would go to another site inAndaluca or in Spain

27.0 5.9

Total 100 100

We randomly split the sample into two equal sized subsamples and rep-licated the cluster analysis with the same variables. The resultant classi-fication agrees with the original solution in 84.5% of the cases.

Across the two groups, we performed a chi-squared test of associationwith the two questions perception of crowding and attitude towardpossible overcrowding, confirming that the clusters can be well differ-entiated, on the basis of these two variables (Table 3).

Cluster Profile

The two resultant clusters are: cluster I (48% of the sample), inwhich the tourists predisposed to leave the destination site as a resultof crowding, i.e., predominating tourists sensitive to crowding(TSC), predominate, and cluster II (52% of the sample), representingtourists not influenced by crowding, i.e., tourists non sensitive tocrowding (TNSC). We also use segmentation analysis to determinehow strongly each variable used in the cluster analysis affects the tour-ists social carrying capacity. The analysis of tourist profile by clustersvaries notably in our case study. In socio-demographic terms, theTSC is a segment of older people (60% of the cluster is over 40 yearsof age), whereas the TNSC is younger (56% of this cluster is between18 and 39 years of age). We also find that tourist in the TSC segmenthave a higher level of education (49% have a university education,

Secondary studies 28.6% 39.6% Between 40$ and 78$ 34.3% 35.2%

12 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119University studies atBachelor level

23.2% 20.1% Between 79$ and 130$ 28.8% 24.0%

University studies at ahigher grade

26.0% 17.2% More than 131$ 13.7% 10.9%

Other 3.5% 5.3%

av2 = 47.92, d.f.4, p < 0.001; bv2 = 14.07, d.f. 4, p = 0.015; cv2 = 33.21, d.f. 4, p < 0.001;dv2 = 9.27, d.f. 4, p < 0.055.compared to 37% of those in the TNSC segment) and a higher income(58% of the TSC segment have a monthly income above $3,151(2,400) and 30% have an income of monthly more than $4,301

Table 4. Socio-Demographic Profile of the Two Clusters (N = 653)

Tourists profile TSC TNSC Tourists profile TSC TNSC

Agea Incomec

1829 years 13.0% 32.8% Less than 1,300 $ 6.7% 7.4%3039 years 21.0% 23.4% Between 1,301 $ and 1,900 $ 13.6% 23.4%4049 years 27.9% 22.5% Between 1,901$ and 3,150$ 21.6% 29.9%5064 years 27.9% 17.7% Between 3,151$ and 4,300$ 27.3% 25.1%More than 65 years 10.2% 3.6% More than 4,301$ 30.8% 14.2%

Study level b Daily expenditured

No schooling 5.1% 4.1% Less than 23$ 3.2% 7.1%Primary studies complete 13.6% 13.7% Between 24$ and 39$ 20.0% 22.8%

(3,300)). It seems that tourists who have sensitive to crowding arethose who spend more money at the destination (43% of TSC touristsspent more than $79 per day) (Table 4). In addition, we see in Table 5that 39% of tourists in the TSC segment believe that their usual resi-dence is overcrowded, compared to 33% in the TNSC segment.

The segmentation of tourists based on their perceptions of the des-tination and trip characteristics allows us to determine the key factors

Table 5. The Profile of the Tourists Perception of the Destination and TripCharacteristics

TSC TNSC TSC TNSC

Overcrowding in the resident placea Days of stayf

Strongly disagree 12.8% 14.8% From 0 to 1 day 0.0% 0.3%Disagree 34.6% 35.6% Two days 12.4% 14.2%Neither agree or disagree 13.2% 16.0% From 3 to 6 days 17.4% 30.8%Agree 23.7% 20.2% From 7 to 10 days 26.7% 23.0%Strongly agree 15.7% 13.4% From 11 to 15 days 15.9% 16.0%

From 16 to 30 days 13.0% 8.6%More than 1 month 14.6% 7.1%

Noiseb Satisfaction with trip experiencesg

Very negative 14.9% 5.3% Not at all satisfied 1.6% 0.9%Negative 19.4% 13.9% Dissatisfied 1.3% 0.3%Normal 28.9% 27.8% Moderately satisfied 19.0% 10.0%Positive 30.1% 37.0% Mostly satisfied 50.5% 45.3%Very positive 6.7% 16.0% Very satisfied 27.6% 43.5%Authenticityc

Very negative 3.5% 1.5% Relationship between overcrowding andsatisfactionh

Negative 20.6% 6.5% Nothing at all 13.0% 65.7%Normal 31.7% 29.0% A little 5.4% 13.0%Positive 35.9% 45.0% Moderate 23.5% 13.0%Very positive 8.3% 18.0% A lot 37.5% 7.7%Number of peopled Very much 20.6% 0.6%Very negative 3.5% 0.0%Negative 13.6% 5.3% Contact with residentsi

Normal 31.1% 23.1% Very negative 0.3% 0.3%Positive 45.1% 54.7% Negative 1.3% 0.9%Very positive 6.7% 16.9% Normal 16.8% 14.5%Destination perceived as closed spacee Positive 57.8% 52.6%Very negative 3.8% 0.3% Very positive 23.8% 31.7%Negative 7.3% 4.4%Normal 27.6% 12.8% Previous visitsj

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 13Positive 48.0% 46.7% Yes 78.0% 70.7%Very positive 13.3% 35.8% No 22.0% 29.3%

av2 = 2.94, d.f.4, p < 0.560; bv2 = 32.64, d.f. 4, p < 0.001; cv2 = 42.59, d.f. 4, p < 0.001;dv2 = 45.03, d.f. 4, p < 0.001; ev2 = 63.60, d.f. 4, p < 0.001; fv2 = 25.60, d.f. 6, p < 0.001;gv2 = 24.21, d.f. 4, p < 0.001; hv2 = 261.68, d.f. 4, p < 0.001; iv2 = 5.17, d.f. 4, p < 0.271;jv2 = 4.55, d.f. 1 p < 0.033.

(11%). Therefore, it is not enough to determine only the satisfactionlevel of the trip experienceit is also important to specifically enquire

14 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119about the impacts of overcrowding on satisfaction. This study sought toinvestigate these relationships and the results are clear: a high percent-age of the TNSC segment believe that overcrowding does not influencetheir satisfaction (66% respond Nothing), whereas 58% of touristsin the TSC segment responded that overcrowding affected their levelof satisfaction a lot or very much (Table 5).

DISCUSSION

The results obtained show that only 20% of tourists in the study areaperceived overcrowding and were predisposed to leave the destination.Another study using the same methodology in 1999 in the Costa delSol stated that only 10% of tourists had exceeded perceived overcrowd-ing. In that study, the tourist mainly had high levels of education andpocket spending (Navarro, 2005). It is not possible to find whetherthose 10% of tourists left the destination, but a study from 2005 (Juntade Andaluca, 2007) showed that a decline in pocket spending between2000 and 2005, during a boom in demand and supply, had a direct ef-fect on reducing the economic impact of expansion. The impact of thisdecline in spending was estimated at $729 million. Did the destina-tions saturation have an economic cost?

The first conclusion of our study is that mature tourists who are bet-ter educated have a high socioeconomic status because of their highincome and are more beneficial to the destination, but these touristsmake up the segment that is most sensitive to crowding. These resultsconfirm Hayduks finding that higher status individuals are less toler-ant of crowding (1983). It is generally accepted that old and youngthat allow tourists to recognize their threshold value and decidewhether to leave the destination (Table 5). Approximately, 25% oftourists who are sensitive to crowding consider lack of authenticity asnegative or very negative. They are also more likely to regard noiseas a negative aspect (34% for TSC versus 19% for TNSC). A particularlyimportant geographical aspect of the destination is the perception ofspace as closed. Eleven percent of the TSC segment perceived thestudy area as closed compared with only 5% of the TNSC. Thosewho perceive the space as closed are likely to perceive a greater num-ber of people. Therefore, individuals in the TSC cluster tend to expe-rience the presence of more people (17% versus 5% of the othercluster). Additionally, the TSC is characterized by medium and longholidays (28% stay more than 16 days) and familiarity with the des-tination (78%). Finally, our results indicate that tourists in the TSC seg-ment perceive the contact with residents slightly more negatively (1.6%versus 1.2% of TNSC) and slightly less positively (82% versus 84% ofTNSC), although this particular result is merely descriptive: the chi-squared test of association is not significant.

Regarding the satisfaction levels, the TSC segment is generally lesssatisfied with the trip experience (22%) than the other cluster

people do not have the same thresholds as each other. However, Fleish-man et al.s investigation, (2004), held in nature reserves, found the

E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119 15opposite: it showed that young people are less tolerant of crowdingthan older people. This result points to one of the most importantquestions in this study: what is the difference between the experienceof tourists visiting a natural destination and the experience of those vis-iting a coastline destination. It is also important to note that 70% oftourists who frequently visit the Costa del Sol are over 40 years of age(Sociedad de Planificacion y Desarrollo, 2007).

Our finding confirm that a low level of authenticity of a destination(Navarro, 2005) and a high level of noise (Ruddell & Gramann 1994)are two of the most important factors influencing the social carryingcapacity. Many tourists were dissatisfied with noise levels in Costa delSol. In particular, although only 3% of tourists were dissatisfied withnoise level in 2000 by 2008, 14% were (Sociedad de Planificacion yDesarrollo, 2008).

This research also finds that tourists tend to perceive the concentra-tion of people more accurately if the destination is perceived as aclosed space, (Stokols, 1972), and in this case, they recognize thecarrying capacity threshold earlier. From a social point of view, it isimportant to understand the relationship between tourists and resi-dents. Mieczkowski (1995) argues that if tourists perceive the local pop-ulation as friendly, they may more easily handle the saturation level.Although this study does not provide clear findings on this point, thereis evidence that the TSC group perceive contact with residents slightlymore negatively.

According to ORiordan (1969), the perception of overcrowding isrelated to an individuals familiarity with the destination. Therefore,those tourists who are more familiar with a destination are less tolerantof concentration levels. Our study seems to confirm that deeper knowl-edge of the area, either from familiarity with the area or longer stays,influences the perception of saturation and the destination capacitythreshold.

Our results show that tourists in the TSC group are less satisfied withtheir trip experience. Numerous studies reveal that this displeasurestems from overcrowding at a destination (Needham & Rollins, 2005;Ryan & Cessford, 2003; Saveriades, 2000). Managers and employersin the Costa del Sol are aware of this. Tourist Observatory in the Costadel Sol (Sociedad de Planificacion y Desarrollo, 20002008) shows thatovercrowding is an issue that tourists find unsatisfactory: the percent-age of tourist who expressed this dissatisfaction rose from 7% in2000 to 9% in 2008. Clearly, when crowding is perceived in a negativeway, the overall satisfaction decreases.

Overall, use of the above methods enabled us to meet the first twogoals of the research, i.e., to identify he percentage of tourists whohad exceeded the social carrying capacity threshold, and to determinethe profile of those tourist who perceive overcrowding and the key fac-tors that most affect these tourists.

16 E. Navarro Jurado, I.M. Damian / Annals of Tourism Research 43 (2013) 119CONCLUSION

Carrying capacity is an operational tool to achieve sustainability. Asargued by Saarinen (2006), there is no sustainability without limits. Itis impossible to establish an equation for a destination, and it is a fal-lacy of political marketing to think otherwise. In mature destinationsand those that are beginning to consolidate, tourism management can-not ignore this tool, because if tourism managers want to control a des-tinations impact, they must know how to anticipate impact. This paperexamines tourists perceptions and attitudes toward overcrowding inorder to contribute to developing a more holistic approach to open-area evaluation procedures.

We separately examined two groups using a cluster analysis in orderto determine which factors influence tourists perceptions of over-crowding and their desire to leave a destination. Our results show thatthere are statistically significant differences in perception between thetwo clusters. Tourists who are sensitive to crowding in the EasternCosta del Sol are older, better education, have a higher income and,consequently, have a greater expenditure at the destination. Theyare known as quality tourists. The factors influencing this segment oftourists are noise at the destination, the areas authenticity, perceptionof space as closed and knowledge of the destination. All of this factorslead too somewhat lower level of satisfaction with their trip experience.This study has shown that tourists perceptions vary according to theirprofile and these profiles could be used to formulate better plans forarea management.

From a practical point of view, this study shows that measuring thesocial carrying capacity of tourists in mass coastal destinations is possi-ble. Each year, the tourism managers from the Costa del Sol conduct asurvey of tourists with a sample size of over 2000. This survey shouldadd only these two new key questions: the other variables are alreadycovered in this survey. The difficulty in analyzing tourists thresholdsis not budgetary but political; managers do not wants to publish nega-tive impacts on society because they would have to propose relief mea-sures which would limit economic growth and political projections.The tourism sector is a friendly activity and it has great politicaladvantage because it is always seen as a positive activity: more tourists,more growth, more businesses, and so on. Only scientists and academ-ics want to determine the limits of economic growth.

Neither the subject of this investigation nor the methodology it usesis new. It is simply a case study that provides an additional example tothe scientific community. This papers value is that a model that waspreviously applied to natural areas has been applied to mature coastaldestinations, with problems of overcrowding. These are the most pop-ular destinations in Spain, and need the most help to avoid or amelio-rate the impacts that arise from their success: however, they are theleast studied in the carrying capacity literature. Another importantcontribution of this paper is the application of advanced statistics toprecisely determine the profile of tourists who are sensitive to crowdingand the factors that influence these tourists. By extending social

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CARRYING CAPACITY MODEL APPLIED IN COASTAL DESTINATIONSINTRODUCTIONThe Growth and Sustainability of Consolidated DestinationsSustainability and Tourism Carrying CapacityThe Social Carrying Capacity of the Demand

MethodologyStudy AreaQuestionnaire Design and SamplingAnalysis

ResultsSample ProfileEstimation of the Social Carrying Capacity Perceived by the TouristsSegmentation AnalysisCluster Profile

DiscussionConclusionAcknowledgementReferences