Tourism Management 24 (2003) 1–11

Crowding at an arts festival: extending crowding modelsto the frontcountry

Hoon Leea,*, Alan R. Graefeb

aDepartment of Tourism, Hanyang University, 17 Haengdang-2 Dong, Seongdong-Gu, Seoul 133-791, South KoreabSchool of Hotel, Restaurant and Recreation Management, Pennsylvania State University, University Park, Pennsylvania, USA

Received 13 June 2001; accepted 24 January 2002

Abstract

The purpose of this study was to compare existing crowding models and extend the concept of perceived crowding to the

frontcountry environment. Models based on three theories, expectancy theory, stimulus-overload theory and social interference

theory, were tested using path analysis. Specific hypotheses tests enabled comparison between traditional and new models which

added some theoretically relevant variables. Overall, theory-based variables were significant and showed more explanation of

variance than the traditional model based on density measures alone. The results of this study show that, as in backcountry settings,

perceptions of crowding among frontcountry visitors in a festival setting are more dependent on situational and environmental

factors than on physical use levels. Expectancy theory and stimulus-overload theory contributed the most relevant explanatory

variables for perceived crowding in this study.

r 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Perceived crowding; Density; Expectancy theory; Stimulus-overload theory; Social interference theory; Path analysis

1. Introduction

Researchers have studied social carrying capacity inan effort to manage the quality of visitors’ experiences.The notion of social carrying capacity has becomeclosely associated with the concept of crowding (Stankey& McCool, 1989). Most studies of perceived crowdinghave been conducted in backcountry recreationalsettings. Even though the participants of a festival inan urban area may have different characteristics thanthe visitors to natural areas, the factors and theories ofperceived crowding were thought to be useful in definingthe quality of a festival experience.

The purpose of this study is to examine specifictheories related to crowding related to a different type oftourism setting. In this study, the theories of expectancy,stimulus overload and social interference, which under-lie the concept of social carrying capacity have beenadopted to explain perceived crowding and festival

visitors’ experiences. This study will contribute to theliterature on crowding and tourism management byproviding an examination of the issues and the specifictheories related to crowding in a festival setting. Theresults of this study will also provide information forfestival planners and event managers to help establishbetter quality festivals.

2. Theories of perceived crowding

Crowding is conceptualized as a ‘‘psychological statecharacterized by stress and having motivational proper-ties’’ (Bell, Fisher, Baum, & Greene, 1990, p. 304). Inother words, crowding can be defined as a negativeassessment of a certain density level in a given area. Thisconcept refers closely to numbers of people and can be amore useful criterion for management than satisfactionbecause of its specificity (Shelby & Heberlein, 1986). Theterm ‘‘perceived crowding’’ is generally related to thesocial psychological, subjective or evaluative nature ofthe concept. According to Shelby and Heberlein (1986),social psychological factors have a more powerfulinfluence on crowding perception than use levels or

*Corresponding author. Tel.: +82-2-2290-0863; fax: +82-2-2281-

4554.

E-mail addresses: hoon2@hanyang.ac.kr (H. Lee), gyu@psu.edu

(A.R. Graefe).

0261-5177/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved.

PII: S 0 2 6 1 - 5 1 7 7 ( 0 2 ) 0 0 0 3 6 - 5

encounters. Stankey and McCool (1989) indicated theperception of ‘‘crowded’’ is generally based more onthe character and behavior of other visitors, and thevalue system of users and managers, than on the level ofdensity or the number of visitors encountered.

Kruse (1985) suggested the origins of crowding werederived from several influences: an experiential state ofperceived lack of space (Stokols, 1972a, b); the resultsof excessive stimulation (Desor, 1972; Saegert, 1978);experience of unwanted behavioral interference (Scho-pler & Stockdale, 1977); the need for more privacy(Altman, 1975); the attribution of arousal to theinvasion of personal space (Worchel & Teddlie,1976); or loss of control (Baron & Rodin, 1978; Rodin,1976; Rodin & Baum, 1978; Schmidt & Keating,1979).

‘‘Crowd’’ and ‘‘crowding’’ seem to be unrelated terms(Kruse, 1985; Shapere, 1974). In a crowd it is theemotional reaction which is facilitated by the expressivebehavior (facial expressions, gestures, shouts, hisses,murmurs) of others. Crowding is a complicated psycho-logical construct. For example, people can feel crowdedeven in low-density conditions because visitors’ personaland social standards interpret the place as one wherethey should see few other visitors (Shelby & Heberlein,1986). In a study of wilderness recreation carryingcapacity, Stankey (1973) identified broad visitor defini-tions of crowding including ‘‘references to litter,’’‘‘excessive levels of use’’ and ‘‘damage associated withlivestock grazing.’’

Shelby, Vaske, and Heberlein (1989) reviewed crowd-ing studies from 15 years of research. The results of theiranalysis showed that four factors influenced perceivedcrowding: time, resource availability, accessibilityor convenience, and management. Three other variables,however, had no influence on the level of perceivedcrowding: regional differences, consumptive or non-consumptive recreation activity, and methodologicalfactors.

Some researchers have tried to study normativeapproaches to crowding (Manning & Ciali, 1980;Manning, Lime, Freimund, & Pitt, 1996; Roggenbuck,Williams, Bange, & Dean, 1991; Shelby, 1981; Vaske,Donnelly, & Petruzzi, 1996; Vaske, Shelby, Graefe, &Heberlein, 1986; Whittaker & Shelby, 1988). Norms aredefined as standards which individuals use to evaluatebehavior and situational or environmental conditions ina setting (Vaske et al., 1986; Whittaker & Shelby, 1988).This study did not include encounter norms becausethese norms may be less useful in high density settingsthan under low density conditions (Shelby & Vaske,1991). Heywood (1993) mentioned that users in higherdensity wildland situations have a tendency to be lessclearly expressive about a norm and experience lessconsensus than visitors in lower density wildlandsituations.

Recently, some researchers have become interestedin crowding issues within frontcountry settings (c.f.,Manning et al., 1996; Tarrant & English, 1996; Vaskeet al., 1996). Vaske et al. (1996) summarized thesimilarities and differences between frontcountry andbackcountry settings based on previous studies. Simila-rities include the fact that encounter norms varyaccording to the type of visitor contacted and thelocation of the encounter. Differences suggest that thereported tolerance limits in frontcountry are signifi-cantly higher than those in the backcountry. Westoverand Collins (1987) argued that the extension ofrecreation crowding studies to urban settings has boththeoretical and pragmatic significance.

Even though density is needed to understand theperception of crowding, crowding is also influenced byother social, personal, and environmental variables(Altman, 1975; Andereck, 1989). Graefe, Vaske, andKuss (1984) concluded that, while perceived crowdingis influenced by density levels, this influence is alsomediated by many other variables: situational andsubjective variables, geographic variables, or the in-dividual’s perception of the experience.

2.1. Expectancy theory

Expectancy can be defined as a temporary belief that acertain act will be followed by a certain result (Lawler,1973; Schreyer & Roggenbuck, 1978). People usuallytake part in recreational activities with the expectationof particular rewards such as excitement, solitude,friendship, status, etc. (Driver & Tocher, 1970; Graefeet al., 1984; Knopf & Driver, 1973; Vroom, 1964).Peoples’ expectations depend on individual and circum-stantial factors: the value and forms of earlier experi-ence, the degree of conversation with others, situationalvariables, and personality (Graefe et al., 1984; Lawler,1973; Schreyer & Roggenbuck, 1978).

Schreyer and Roggenbuck (1978) concluded thatpeople have multiple expectations in recreationalactivities. They also argued that people participating inthe same recreation activities may expect differentrewards or people engaged in various activities usingthe same environment may expect different rewards.Further, socio-economic and environmental variableswere found useful in explaining people’s expectations.

Certain expectations may generate from the visitor’senvironment, the visitor’s own previous experience, orfrom information collected via communication withothers or the mass media (Vaske, Donnelly, Doctor, &Petruzzi, 1994). Several studies have shown that addingthe factors of expectations and preferences can helpexplain the typical weak relationship between actualencounters and perceived crowding to make a strongercrowding model (Roggenbuck, 1992). For example,Andereck and Becker (1993) studied perceived crowding

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–112

at Fort Sumter National Monument in Charleston, SC.Their results showed expectations for density contrib-uted significantly and directly to perceived crowding.

Shelby, Heberlein, Vaske, and Alfano (1983) alsoresearched the effects of expectations on perceivedcrowding in six different recreation areas. Expectancytheory was supported by the results strongly andconsistently. Seeing more people than expected causedpeople to feel more crowded in each of the studies.When visitors saw fewer or the same number of othervisitors as they expected, perceived crowding levels wereremarkably low (3% and 4%, respectively). However,when more people than expected were encountered, theperceived crowding level increased to 42%. Otherresearch also supports the notion that crowding is moreclosely connected to the user’s expectations than toactual encounter levels (Ditton, Fedler, & Graefe, 1983).Vaske et al. (1994) suggested that building realisticexpectations among the users may be a promising wayto reduce difficulties related to crowding.

2.2. Stimulus overload

The theory of stimulus overload is derived from socialpsychological analyses of the stresses of urban, highdensity living (Gramann, 1982; Milgram, 1970; Wirth,1938). High density can be unpleasant because it canoverwhelm the senses. According to this theory, negativeoutcomes occur when the amount and rate of stimulationcaused by density exceed our ability to deal with it (Bellet al., 1990). Schmidt and Keating (1979) explained thestimulus overload concept as people feeling crowdedwhen they are overwhelmed by the attendance of othervisitors or by the condition of the physical environment ata given area. This definition emphasizes a conceptual orcognitive interference rather than behavioral constraints.

A control approach can offer a good explanation ofstimulus-overload theory. Overload happens when thereare too many unwanted and uncontrolled interactionsand unfamiliar or inappropriate social contacts (Ander-eck, 1989). The overload model is based on conditionsof high density in which people meet more stimuli thanthey can handle, which is related to the loss of control(Bell et al., 1990). Uncertainty and uncontrollability areimportant factors in the experience of overload. Baumand Paulus (1991) suggested ‘‘overload is experiencedand various adaptive mechanisms ensure to reduce theoverload when the demands of functioning in highlydense environments exceed the individual’s capacity tohandle them’’ (p. 553).

The fundamental assumption of the stimulus-over-load model is that the size, density, and heterogeneity ofother people cause recreation users to be exposed toexcessive levels of psychic stress (Gramann, 1982;Schmidt & Keating, 1979). Density level and interac-tions with others are more important factors than

limited space (Baum & Paulus, 1991). People try tohandle this overly stimulating state with variousstrategies. If these adaptations are successful, they canlessen or get rid of the negative effects of stress.However, if these strategies do not work or are notappropriate in reducing density-induced stress, thencrowding is experienced (Gramann, 1982; Schmidt &Keating, 1979).

The individual visitor situationally determines opti-mal levels of stimulation. Therefore, crowding percep-tions may be highest if the level of stimulation is beyondthe level preferred and cannot be eliminated or lessened(Andereck & Becker, 1993; Gramann, 1982; Schmidt &Keating, 1979). Stimulus-overload theory denotes that,because each individual in a setting represents a latentsocial contact, high density is a possible root of extremestimulation resulting in a state of social overload(Andereck & Becker, 1993; Baum & Paulus, 1991).

2.3. Social interference

Social interference theory suggests crowding occurswhen the levels of density interfere with a visitor’sactivities and goals in a particular setting (Schmidt &Keating, 1979). This theory emphasizes density-relatedinterference or density compatibility with numerouspsychological goals motivating a behavior (Brehm,1966; Graefe et al., 1984; Gramann, 1982; Proshansky,Ittelson, & Rivlin, 1970). Crowding reflects unsuitablesituations among physical density, incompatible beha-vior and psychological goals or expectations. In addi-tion, the social interference perspectives of crowding canbe considered in view of the lack or the loss of controlover the situation. Density interferes with an indivi-dual’s ability to maintain control of the situation inorder to achieve his or her goal. This loss of situationalcontrol results in perceptions of crowding (Andereck &Becker, 1993).

The assumption in this theory is that much of thevisitor’s behavior in recreational settings is consciouslyor subconsciously motivated by the desire to accomplisha variety of psychological states like solitude, stressrelease, or social interaction. Crowding perceptionsmay be the result of density-related blockages of thesegoals (Altman, 1975; Gramann, 1982; Stokols, 1976).Gramann (1982) suggested that human behavior is oftengoal directed, and ‘‘crowding attributions occur whenthe number, behavior, or proximity of other persons in asetting are incompatible with an important goal andthus interferes with its attainment’’ (p. 112). Severalresearchers support this idea that behavioral interfer-ence is a crucial variable when the environment of arecreation area is evaluated as crowded (c.f., Andereck& Becker, 1993; Schopler & Stockdale, 1977; Sherrod,1974; Sundstrom, 1975; Wicker, Kirmeyer, Hanson, &Alexander, 1976).

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–11 3

Three hypothesis are suggested to examine (a) therelationship of estimated density and perceived crowd-ing as a traditional model, (b) the relationships ofestimated density and expectation of crowding, andperceived crowding, and (c) the relationships of esti-mated density, expectation of crowding, stimulus-related evaluation, and goal-related evaluation, andperceived crowding as a theoretical model. The specifichypotheses tested are listed below:

H1: Crowding Model I: Estimated density will bedirectly and positively related with perceived crowdingof festival visitors.

H2: Crowding Model II: Estimated density andexpectation of crowding will be directly related withperceived crowding of festival visitors.

H3: Crowding Model III: Estimated density, expecta-tion of crowding, stimulus-related evaluation, and goal-related evaluation will be directly related with perceivedcrowding of festival visitors.

3. Methods

3.1. Data collection

Ralston and Stewart (1990) studied methodologicalapproaches for festival research studies. They suggestedusing a triangulation approach because ‘‘using two ormore methods increases the confidence in the resultscompared to evidence emerging from a mono-methodstudy’’ (pp. 289). This study used two techniques, on-siteand mail follow-up questionnaires.

For this study, a random sample of individualsattending the 1995 Central Pennsylvania Festival ofthe Arts (CPFA) was selected over a 4-day period. TheCPFA was created in 1967 with the primary objective ofstimulating the local summer economy in the downtownarea of State College, Pennsylvania. The festival runsover 5 days and includes indoor exhibitions, performingarts, and a sidewalk sale of arts and crafts. Uponcompletion of a one-page on-site interview, respondentswere asked to complete a more extensive follow-upquestionnaire. If they agreed, they were asked to writetheir mailing address on a form and were given a follow-up survey. The follow-up questionnaire consisted of foursections: expenditure data, festival behavior, informa-tion use, and visitor information. For the purposes ofthis study, the only information referenced was thatwhich was provided in Section 2—festival behavior, andSection 4, visitor information.

A total of 969 individuals completed the on-sitequestionnaire. Five days after the last day of the festival,a reminder post-card was mailed to individuals whohad agreed to complete the follow-up survey. The post-card reinforced the value of the study and encouragedrecipients to send in their questionnaire if they had not

already done so. A second follow-up questionnaire wasmailed 2 weeks later to individuals who had notresponded. Five hundred ninety-one individuals com-pleted both the on-site and follow-up questionnaires,resulting in a response rate of 61%.

3.2. Measurement and treatment of variables

Perceived crowding was measured using a five-pointLikert-type scale. The question was, ‘‘Did you feelcrowded by the number of visitors at the CentralPennsylvania Festival of the Arts?’’ (1 ‘‘Not at allcrowded’’ to 5 ‘‘extremely crowded’’ were the responsecategories).

During the festival, density was estimated daily by thefollowing method. Individuals were asked on-site whetheror not they had parked at the shuttle parking lot. Theestimated percentage of those attending the festival andriding the shuttle bus each day was used with busridership records to arrive at an estimated daily numberof festival attendees (Kerstetter, Farrell, & Lee, 1996).

Expectation of perceived crowding was measuredusing a four-point scale. festival visitors were asked,‘‘How did the number of people you actually saw at thefestival compare to the number of people you expectedto see?’’ Responses ranged from ‘‘fewer than I expected’’(1) to ‘‘more than I expected’’ (3), with a separatecategory, ‘‘I did not know what to expect’’ (4). Theresponse, ‘‘I did not know what to expect,’’ was treatedas a missing value in the regression analysis. Thus, thisdata analysis may be slightly biased towards repeatvisitors because they were more likely to select aresponse other than ‘‘I did not know what to expect.’’

For a stimulus-related variable based on stimulus-overload theory, which focused on cognitive evaluationsof density-induced environments or conditions, fouritems were selected and tested for reliability. Theyincluded: ‘‘The cleanliness of the festival grounds,’’‘‘Parking opportunity,’’ ‘‘Shuttle bus service,’’ and ‘‘Thebehavior of festival guests.’’ The measurement useda five-point Likert-type scale ranging from 1 ‘‘verypoor’’ to 5 ‘‘excellent,’’ with a ‘‘not applicable’’ optionincluded. Many responses to the item, ‘‘shuttle busservice,’’ were answered with ‘‘not applicable,’’ becausethese respondents did not take the shuttle bus whileattending the festival. An item analysis includingcalculation of item-total correlations and Cronbach awas conducted on the four stimulus-related evaluationvariables to identify the best combination of scale items(Table 1). The complete four-item index was confirmedwith an a level of 0.78 (standardized item a=0.79).

For a goal-related evaluation variable based on socialinterference theory, the hypotheses were based on goalblocking relative to the fine arts and crafts at thesidewalk sale, the opportunity to learn more about arts,and the opportunity to have fun in a festival setting.

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–114

The response format was again 1 ‘‘very poor’’ to 5‘‘excellent’’ and ‘‘not applicable.’’ In the reliability test,the goal-related evaluation index was confirmed with ana of 0.73 (standardized item a=0.73, Table 1).

3.3. Path analysis

Path analysis is a method of analyzing quantitativedata which estimates the effects of variables in anhypothesized causal system (Bohrnstedt & Knoke, 1988)and decomposes structural relationships between vari-ables in a structural equation model. This method candistinguish the part of the relationship that the researcherbelieves to be the causal effect from the part which isspurious or irrelevant (Keane, 1994). Path analysis can bethe most suitable method to examine the numerousinfluences involved in a causal model (Anderson & Evans,1974; Cook & Campbell, 1979; Duncan, 1975). Asher(1984) also defined path analysis as a method for testingthe validity of a theory about causal relationshipsbetween several variables. Specifically, path analysis cantest a designed model or theories about hypothesizedcausal links between variables by comparing observedconnections among the variables. Pedhazur (1982)suggested the assumptions of path analysis are as follows:

(1) the relations among the variables in the model arelinear, additive, and causal; (2) each residual is notcorrelated with the variables that precede it in themodel; (3) there is a one-way causal flow in thesystem; that is, reciprocal causation between vari-ables is ruled out; (4) the variables are measured onan interval scale; and (5) the variables are measuredwithout error (p. 582).

With regard to assumptions (1) and (3), the variablesin this study were shown to meet the linearity assump-

tion by using residual plots. The assumption of causalitywas also fulfilled in this study by checking the conditionsof covariation, time order, and nonspuriousness. Covar-iation means that systematic changes in one variablehave to occur with corresponding changes in the othervariable. The relations of time order between exogenousand endogenous variables require that the change in theexogenous variable must precede in time the change inthe endogenous measure. Nonspuriousness means thatthe pattern of association between the variables does notoccur from other, common causal factors (Bishop,1995). One-way causal flow in the system is alsohypothesized to be met as a relation of variables inthis study.

These assumptions, especially (2) and (5), are rarelymet in applied social science research (Pedhazur, 1982).It is best to do research based on research designs usedin existing literature and variables that are psychome-trically sound (Bishop, 1995). In this study, the modelsand instruments, based on the three social carryingcapacity theories and previous models, aid in fulfillingthese assumptions.

Assumption (5) was met as variables of this studywere measured on an interval scale. In addition, theusual assumptions for regression analysis were met:normality of variables and homoscedasticity of residualsby an examination of the variable distributions andresidual plots; multicollinearity of variables by determi-nation of variance inflation factors (VIFs) (e.g., below10) and correlation matrix (e.g., below 0.7).

4. Results

About 14,000 people, on average, attended the festivalper day (mean=14,199 visitors). Overall evaluations offestival attributes were mostly positive (Table 2). When

Table 1

Reliability statistics for goal-related evaluation and stimulus-related evaluation scales

Attachment statement Ma SD Corrected item—total

correlation

a if item deleted

Goal-related evaluation variables

The fine arts and crafts at the Sidewalk Sale 4.34 0.70 0.49 0.72

The opportunity to learn more about the arts 3.94 0.78 0.58 0.62

The opportunity to have fun 4.39 0.70 0.61 0.58

a (standardized item a)b 0.73 (0.73)

Stimulus-related evaluation variables

The cleanliness of the festival grounds 4.34 0.69 0.53 0.76

Parking opportunity 3.74 1.10 0.63 0.73

Shuttle bus service 4.36 0.85 0.73 0.65

The behavior of festival guests 4.3 0.65 0.53 0.76

a (standardized item a)c 0.78 (0.79)

a Items were coded on a 5-point scale ranging from very poor (1) to excellent (5), with not applicable (6) being treated as a missing variable.bn ¼ 484:cn ¼ 130:

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–11 5

testing the expectation of crowding, the mean score was1.73, reflecting that most respondents encounteredabout as many as they had expected or fewer thanexpected. The overall stimulus-related evaluations(mean=4.23) and the evaluations of goal-related vari-ables were very high (mean=4.18). The festival partici-pants’ perception of crowding was below ‘‘moderatelycrowded’’ (mean score=2.17).

4.1. Hypothesis testing

The aim of path analysis is to decompose the zeroorder correlation between two variables into compo-nents due to various effects. The correlation matrix forthe variables is presented in Table 3. This matrixprovides insight into the nature of relationships betweenthe variables. Perceived crowding was significantlyrelated with all explanatory variables: estimated density(r ¼ 0:093); expectation of crowding (r ¼ 0:288); stimu-lus-related evaluation (r ¼ �0:236); and goal-relatedevaluation (r ¼ �0:140).

4.1.1. H1: Crowding model I

As a traditional model, the relationship betweenestimated density and perceived crowding at the festival

setting was examined (see Eqs. (1) and (2)). Estimateddensity was found to directly and positively influencethe perceived crowding of festival visitors (p51 ¼ 0:104).About 1% of the variance in perceived crowding(R2 ¼ 0:011) was explained by estimated density.Although this explanation of variance is low andmight be insignificant in a smaller sample size, thevariable and overall model were statistically significant(t ¼ 2:517; po0:05; F ¼ 6:337; po0:05). In addition,according to the Simon–Blalock Technique, if the actualpartial r > 0:100; the arrow in the model should be kept(Hopkins, 1974). Therefore, in this model a direct,though weak, effect of density on perceived crowdingwas found (Fig. 1). This finding supports the results ofresearch in outdoor recreation settings which shows asignificant and positive relationship between actualdensity and perceived crowding. As expected, therelationship was weaker in a festival setting where theexperience is more social than in typical backcountrysettings where solitude may be highly valued (c.f.,Absher, 1980; Absher & Lee, 1981; Ditton et al., 1982,1983; Graefe et al., 1984; Hammitt, McDonald, & Noe,1982; Heberlein & Baumgartner, 1978; Heberlein,Trent, & Baugartner, 1982; Heberlein & Vaske, 1977;Lee, 1975; Randall, 1977; Shelby, 1976, 1980; Shelby &Colvin, 1979):

H1: Initial model

X5 ¼ p51X1: ð1Þ

Table 2

Descriptive analysis results for variables included in the path models

Variable name M SD

Estimated density (X1)a 14,199 5191

Expectation of crowding (X2)b 1.73 0.62

Stimulus-related evaluation (X3)c 4.23 0.59

Goal-related evaluation (X4)d 4.18 0.65

Perceived crowding (X5)e 2.17 0.93

aTotal daily estimated attendance.bMeasured on a 3-point Likert scale where 1=fewer than I expected

to 3=more than I expected.cMeasured on a 5-point Likert scale where 1=very poor to

5=excellent.dMeasured on a 5-point Likert scale where 1=very poor to

5=excellent.eMeasured on a 5-point Likert scale where 1=not at all crowded to

5=extremely crowded.

Table 3

Correlation matrix for variables

DENSITY EXPECT STMLS GOAL CROWD

DENSITY 1.000

EXPECT �0.087n 1.000

STIMLS �0.168 0.257nn 1.000

GOAL 0.033 0.067 0.567nn 1.000

CROWD 0.093n 0.288nn �0.236nn �0.140nn 1.000

nStatistically significant at po0:05:nnStatistically significant at po0:01:

Note: DENSITY=estimated density; EXPECT=expectation of crowding; STMLS=stimulus-related evaluation; GOAL=goal-related evaluation;

and CROWD=crowding.

X5 :Crowding

R2 =.011

e1

.994

.104X1:Density

Where: X1: Estimated density X5: Perceived crowding

Fig. 1. H1: Path diagram of the relationship between estimated density

and perceived crowding.

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–116

H1: Final model

X5 ¼ 0:104X1; R2 ¼ 0:011;

t ¼ 2:517; F ¼ 6:337;

po0:05; po0:05: ð2Þ

4.1.2. H2: Crowding model II

Expectancy theory was examined in the secondcrowding model at the festival setting (see Eqs. (3) and(4)). Estimated density (p51 ¼ 0:129) and expectation ofcrowding (p52 ¼ 0:309) were found to directly andpositively influence the perceived crowding of festivalvisitors. Participants felt more crowded at the festivalwhen density was higher and the expectation ofcrowding was held constant. Similarly, participants feltmore crowded at the festival when there were moreparticipants than they expected and density was heldconstant. Expectation of crowding showed more influ-ence on perceived crowding than did estimated density.The percent of the variance explained in perceivedcrowding increased to over 10% (R2 ¼ 0:106) by addingthe expectation of crowding variable. The overall modelwas also highly significant (F ¼ 31:755; po0:001). Thedecomposition of the model (Fig. 2) indicates that bothexogenous variables had direct effects on perceivedcrowding. The results of the analysis suggest that theexpectation of crowding (X2), based on expectancytheory, is an important exogenous variable for perceivedcrowding at the festival. This finding supports the resultsof research in outdoor recreation settings showing asignificant relationship between expectations and per-ceived crowding (c.f., Andereck, 1989; Bultena, Field,Womble, & Albrecht, 1981; Schreyer & Roggenbuck,1978; Shelby et al., 1983).

H2: Initial model

X5 ¼ p51X1 þ p52X2 þ e5: ð3Þ

H2: Final model

X5 ¼ 0:129X1 þ 0:31X2; R2 ¼ 0:106;

t ¼ 3:149; t ¼ 7:553; F ¼ 31:755;

po0:01; po0:001; po0:001: ð4Þ

4.1.3. H3: Crowding model III

This hypothesis extends the traditional model (H1)further by adding three explanatory variables based onthe theories for perceived crowding (see Eqs. (5) and(6)). Although density and goal-related evaluationwere correlated with crowding (see correlation matrix,Table 3), they were eliminated from the path modelbecause the other two variables showed relativelymore significant and stronger relationships with per-ceived crowding. Expectation of crowding (p52 ¼ 0:374)positively influenced the perceived crowding offestival visitors, while stimulus-related evaluation(p53 ¼ �0:332) showed a negative influence. For exam-ple, participants felt more crowded when there weremore people than they expected and when the stimulus-related evaluation was held constant. Similarly, partici-pants felt more crowded when stimulus-related evalua-tion was given low scores and expectation of crowdingwas held constant. Expectation of crowding was morehighly correlated with perceived crowding than stimu-lus-related evaluation. The percent of the variance inperceived crowding was increased to over 18%(R2 ¼ 0:186) by both exogenous variables. The overallmodel was also highly significant (F ¼ 13:499;po0:001). The decomposition of the model (Fig. 3)indicates that both exogenous variables had directeffects on perceived crowding. This finding supportsthe notion that expectation (X2) based on expectancytheory and stimulus-related evaluation (X3) based onstimulus-overload theory are more important variablesthan estimated density (X1) and goal-related evaluation

X5 :

Crowding

R2=.106

e1

.946

X2 :

Expectation

.309

X1 :

Density.129

Where: X1: Estimated density X2: Expectation of crowding X5: Perceived crowding

Fig. 2. H2: Path diagram of the relationships of estimated density, expectation of crowding, and perceived crowding.

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–11 7

(X4) in explaining perceived crowding (X5) in the festivalsetting:

H3: Initial model

X5 ¼ p51X1 þ p52X2 þ p53X3 þ p54X4 þ e5: ð5Þ

H3: Final model

X5 ¼ 0:374X2 þ ð�0:332X3Þ; R2 ¼ 0:186;

t ¼ 4:350; t ¼ �3:864; F ¼ 13:499;

po0:001; po0:001; po0:001: ð6Þ

5. Conclusions

The endeavor to generalize the notion of perceivedcrowding obtained meaningful outcomes. As the find-ings demonstrated, there were both differences andsimilarities in the relative importance of models andfactors between the festival setting and backcountryoutdoor recreation settings. Notably, two theoriesrelated to crowding were confirmed; thus they maypossibly be applied to other settings for similar festivals.

The traditional model (H1) of the influence ofestimated density on perceived crowding at the festivalsetting was confirmed, as studies in outdoor recreationsettings would have predicted. However, the relation-ships of an exogenous variable (estimated density) andan endogenous variable (perceived crowding) weresomewhat weaker in this study than those typicallyfound in outdoor recreation sites (see Eq. (2) andFig. 1). This finding demonstrates that estimated densityis still a significant exogenous variable affecting per-ceived crowding at the festival, but the relationships arerelatively weak. The reason may be that the festivalsetting involves a special type of community or differentattributes from outdoor recreation settings and moreremote destinations. At this festival, the use level of thefestival visitors might not exceed the ‘‘optimal level’’ yet.

Vaske et al. (1996) reported that tolerance limits infrontcountry (e.g., festival settings) are higher thanthose in backcountry.

When the theory-based variables were added, expec-tation of crowding based on expectancy theory (H2 andH3) and stimulus-related evaluation based on stimulus-overload theory (H3) relatively strongly and significantlyexplained perceived crowding at the festival. However,goal-related evaluation based on social interferencetheory (H3) and estimated density did not significantlyrelate to perceived crowding. Thus, the social inter-ference theory was not supported by the results of thisstudy. Based on the theory, crowding was assumed toresult from density-induced blockages of goals. How-ever, the evaluated goals of the participants were notseriously interrupted by the number of people or uselevel at the festival setting, unlike blocked goals such assolitude or stress release in backcountry settings.

In the data treatment for expectation of crowding, theresults were mostly based on repeat festival visitorsbecause first time attendees were more likely to state, ‘‘Idid not know what to expect,’’ and thus were deletedfrom the analysis. Even though most festival partici-pants answered ‘‘as many as I expected’’ or ‘‘fewer thanI expected’’ to this question, the expectation theorywhich is rooted in comparing a preferred situation to anactual one, was supported significantly and strongly bythe results of this study. Seeing more participants thanone expected caused people to feel more crowded at thefestival as it has in other outdoor recreation settings(Andereck & Becker, 1993; Shelby et al., 1983).

The stimulus-overload theory was supported by theresults of this study. Crowding is assumed to result whenan individual is overwhelmed by the density-inducedcondition of the physical environment or interactionswith other visitors at a given area. The results of thisstudy supported the notion that participants feelperceived crowding at the festival situational andenvironmentally. Results agree with Stankey and

X5 :

Crowding

R2 =.186

e1.902X2:

Expectation.374

X3:

Stimulus

-.332

Where: X2: Expectation of crowding X3: Stimulus-related evaluation X5: Perceived crowding

Fig. 3. H3: Path diagram of the relationships of expectation of crowding, stimulus-related evaluation, and perceived crowding.

H. Lee, A.R. Graefe / Tourism Management 24 (2003) 1–118

McCool’s (1989) statement that ‘‘the question ofwhether an area is ‘‘crowded’’ or not is often rootedmore in the nature of the character and behavior of otherusers, and the value systems of users and managers, thanin the number of visitors’’ (p. 503).

6. Implications for planning and management

The results of this study showed significant relation-ships among the explanatory variables and perceivedcrowding at an alternative tourism destination. Thefindings also suggest some useful implications forfestival management and planning. It is important tonote that for crowding management and planning, thefestival participants felt more perceived crowdingindirectly, and environmentally rather than basedsimply on physical use level. Expectation of crowdingand stimulus-related evaluation were shown as thesignificant explanatory variables in this study. There-fore, as Heberlein (1992), and Werner and Kaminoff(1983) suggested, appropriate information about thefestival situation could reduce perceived crowding infestival settings. In addition, keeping sound or positiveconditions within the festival environment instead oflimiting use levels also could reduce negative stimula-tion, thus making participants perceive less crowding.

A local newspaper reporting on the festival’s level ofcrowding (Young, 1995) suggested that uncomfortablycrowded conditions may have negatively influenced thequality of festival participants’ experience and theiractivities. From the results of this study’s descriptiveanalysis, however, most festival participants did notexperience feeling crowded. The reasons may be that theparticipants like to see a number of people at the festivalor one of their motivations for attending the festival is tosocialize with friends, families or other people. Thereasons may also be tied to expectations, since mostparticipants encountered about the number of peoplethey expected to see at the festival. Based on the resultsof this study, managers should not worry if photographsused in different promotional channels (e.g., newspaperstories, brochures, festival guide) depict crowds becausevisitors did not perceive much crowding in this festivalsetting.

This does not suggest that the study of perceivedcrowding at an alternative tourism destination such as afestival setting is trivial. Managers should continue tomonitor visitors’ responses to crowding, even if they findlow levels of perceived crowding among large numbersof participants. Urban park managers (and festivalmanagers) have promoted increased park attendancerather than seeking to limit use, because high use levelequates with high profits. This approach may bedangerous according to Westover and Collins (1987)who suggest that ‘‘y it is important to establish

appropriate social density norms for different types ofdeveloped recreation sites so that the opportunitystabilization approaches can be implemented andunanticipated, unplanned ‘product shifts’ avoided’’(p. 97).

Further research is needed to address several keyissues. First, more effective and more appropriatemeasurements of density are needed. Weak relationshipsbetween density and perceived crowding in this studymay partially reflect limitations in the method of esti-mating density in the current study. Some researchershave suggested remote sensing technologies (Marnell,1977) and visual approaches to measuring density(Manning et al., 1996). Secondly, more theoreticalapproaches to explain social carrying capacity withinthe festival/event settings are needed. The expectancytheory, social interference theory, and stimulus-overloadtheory need to be tested further and made use of moreeffectively in other studies. Finally, better measurementsof perceived crowding are needed. As in much of theresearch on outdoor recreation, this study used a singleitem to measure perceived crowding. A multiple-iteminstrument to measure visitors’ complex experience maycontribute to finding stronger relationships betweenvariables.

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