Perceived retail crowding and shopping satisfaction: the role of shopping values

Perceived Retail Crowding and Shopping Satisfaction:What Modifies This Relationship? MACHLEIT, EROGLU, MANTELPERCEIVED RETAIL CROWDING AND SHOPPING SATISFACTION

Karen A. MachleitDepartment of MarketingUniversity of Cincinnati

Sevgin A. ErogluDepartment of MarketingGeorgia State University

Susan Powell MantelDepartment of Marketing

University of Toledo

Research has shown that an increase in perceived crowding in a retail store (created from eitherhuman or spatial density) can decrease the level of satisfaction that shoppers have with the store.The three studies reported here examine the retail crowding–satisfaction relationship to deter-mine the extent to which it is a simple, direct relationship. Specifically, we consider the possibil-ity that the crowding–satisfaction relationship is mediated by emotional reactions that are expe-rienced while shopping. In addition, moderating variables such as prior expectations ofcrowding, tolerance for crowding, and store type are examined for their influence on the crowd-ing–satisfaction relationship. The results of two field studies indicate that whereas emotionsonly partially mediate the relationship, the decrease in shopping satisfaction due to crowding ismoderated by expectations of crowding and personal tolerance for crowding. A laboratory ex-periment replicated the field studies and shows, in addition, that although ceiling and floor ef-fects may be present, the relationship between perceived crowding and shopping satisfactionappears to vary by store type.

The impact of physical environmental factors on store imageand patronage is a topic that continues to attract research at-tention (Fantasia, 1996; Miller, 1993). Management deci-sions about the design, ambient, and social elements of thestore environment can be greatly enhanced by an understand-ing of consumer–environment relationships (Bitner, 1992;Eroglu, Ellen, & Machleit, 1991; Rust & Oliver, 1994). In-deed, Iacobucci, Ostrom, and Grayson (1995) suggested thatthe physical environment plays a significant role in shapingcustomer satisfaction.

One environmental factor that has received considerableresearch interest is in-store crowding (Eroglu & Machleit,

1990; Harrell, Hutt, & Anderson, 1980; Hui & Bateson, 1991;Machleit, Kellaris, & Eroglu, 1994). Perceived crowding is apsychological state that occurs when a person’s demand forspace exceeds the supply (Stokols, 1972). Research to datehas shown that the level of in-store crowding perceived byshoppers can affect their patronage decisions as well as satis-faction with the overall shopping activity (Eroglu &Machleit, 1990). Clearly, if perceived crowding does affectshopper behavior to some degree, those who are interested inshaping such behaviors will want to understand the specificsof this relationship.

We extend previous work on retail crowding by examiningthe specific nature of its effects on shopper satisfaction. Re-cent work in the area has uncovered two dimensions of retailcrowding—humanandspatial—thatareshowntohavediffer-ent relationshipswithstoresatisfaction(Machleitetal.,1994).Furthermore, these authors suggested that although perceived

JOURNAL OF CONSUMER PSYCHOLOGY,9(1), 29–42Copyright © 2000, Lawrence Erlbaum Associates, Inc.

Requests for reprints should be sent to Karen A. Machleit, PO Box210145, University of Cincinnati, Cincinnati, OH 45221–0145. E-mail:[email protected]

retail crowding can reduce shopping satisfaction, the relation-shipmaynotbeasimple,directone; therecouldbe factors thatmoderate and mediate the relationship. Consistent with An-derson and Fornell’s (1994) call for further investigation intothe antecedents of satisfaction, Machleit et al. specificallycalled for additional study to understand the particular way inwhich crowding acts as an antecedent to satisfaction. Conse-quently, this research focuses on several potential moderatingand mediating influences on the relationship between retailcrowding and customer satisfaction with the shopping experi-ence.Specifically,weexamine the roleofemotions,crowdingtolerance, and store category as potential influencers of thecrowding–satisfaction relationship.

CROWDING

Perceived crowding is a result of physical, social, and per-sonal factors that sensitize the individual to actual or potentialproblems arising from scarce space (Stokols, 1972). Whenthe number of people, objects, or both, in a limited space (re-ferred to asdensity) restricts or interferes with individuals’activities and goal achievement, the individual will perceivethat the environment is crowded. Perceptions of crowding areindividual in nature; two different shoppers in the same storemay perceive different levels of crowding depending on indi-vidual characteristics and situational constraints.

Perceived retail crowding appears to be a multidimen-sional construct consisting of two dimensions: spatial and so-cial (Machleit et al., 1994). The number of nonhumanelements in an environment and their relationships to eachother all help define the extent ofspatialcrowding perceivedby individuals. Within the retailing context, for example, theamount of merchandise and fixtures as well as their configu-ration within the store could enhance or suppress perceivedcrowding associated with physical stimuli. Thesocial(orhu-man) dimension of crowding, on the other hand, concerns thenumber of individuals as well as the rate and extent of socialinteraction among people in a given environmental setting.High social density may lead to undesirable outcomes such aslack of privacy or personal territory resulting in heightenedfeelings of being crowded.

The effects of crowding on shopping satisfaction may de-pend on certain moderators and mediators. One such variablecould be customer emotions. The extent of human and spatialcrowding perceived by a shopper may elicit negative emo-tions and stress associated with a lack of perceived control(Hui & Bateson, 1991; Nagar & Pandey, 1987). This undesir-able outcome is particularly accentuated when high levels ofcrowding are not expected and the individual has a low toler-ance for crowding. Given the demonstrated relationship be-tween emotions and satisfaction (Oliver, 1993), it is likelythat the nature and extent of emotions instigated by crowdingcould also play a role in shaping the relationship between cus-

tomers’ perceptions of crowding and their satisfaction withthe shopping experience.

EMOTIONAL RESPONSES, RECALL,AND SATISFACTION

Our behavioral reactions to emotions develop early and canaffect perception, cognition, motivation, and behavior (Izard,1993). There is a need to distinguish at this point between af-fect and emotion. Although both are related, affect is typi-cally identified as simple positive, neutral, or negative feel-ings associated with a low involvement external stimuli, andemotion is a more deeply rooted, multidimensional construct(Holbrook & Batra, 1987) that can be influenced via specificsituations and specific events (Gardner, 1985). Research indi-cates that both affect and emotion can influence behavior andthought processes by influencing storage, organization, andretrieval of cognitive information (Ger, 1989; Isen, 1989;Leventhal, 1981; Nasby & Yando, 1982; Teasdale, Taylor, &Fogarty, 1980).

Consumer satisfaction is important to the retailer becauseit has been shown to be a recursive process in which satisfac-tion with a previous experience influences future shoppingchoices (Woodruff, Cadotte, & Jenkins, 1983). For retrospec-tive satisfaction to influence the future shopping trip, the con-sumer must rely on some measure of recall from the previousexperience. It has been shown that mood states tend to biasjudgment in mood-congruent directions for product evalua-tions (Isen, Shalker, Clark, & Karp, 1978), enjoyableness(Carson & Adams, 1980), and respondent satisfaction withtheir lives (Schwarz & Clore, 1983). Furthermore, recalltends to be biased in the direction of the momentary emotionassociated with the event being recalled (Bower, 1981;Bower, Gilligan, & Monteriro, 1981, Experiment 5). There-fore, the momentary emotion felt during a shopping trip islikely to influence judgments about the shopping trip, subse-quent recall of the shopping trip, and future choices regardingsimilar shopping trips.

Research has suggested that expectations are a determi-nant of consumer satisfaction (Punj & Stewart, 1983). Be-cause consumers’ perception of an objective task is a functionof the individuals’ reference point prior to the task (Tversky& Kahneman, 1981), postshopping consumer satisfactionshould be related, at least in part, to the extent to which theirexpectations of the experience are exceeded or dispelled (Oli-ver, 1993). This “expectancy–disconfirmation” model of sat-isfaction has been empirically examined in a number ofcontexts (cf. Oliver & DeSarbo, 1988; Spreng & Mackoy,1996; Tse & Wilton, 1988), and researchers have begun toconsider the role of emotion in the model. For example, West-brook (1987) and Oliver (1993) illustrated significant effectsof both positive and negative affective responses on satisfac-tion in addition to a disconfirmation effect.

30 MACHLEIT, EROGLU, MANTEL

Although the expectancy–disconfirmation paradigm hasdominated satisfaction research, Anderson and Fornell(1994) emphasized the need to identify additional anteced-ents of satisfaction beyond expectations, including their rela-tionships, possible moderators, and importance for shaping asatisfaction response. For the retailer, perceived retail crowd-ing is an important antecedent of customer satisfaction(Eroglu & Machleit, 1990; Machleit et al., 1994). Given thispremise, we work to delineate more precisely the role of sev-eral mediating and moderating factors on the relationship be-tween shopper satisfaction and one of its antecedents,perceived retail crowding.

HYPOTHESES

Considering research in the areas of emotion, satisfaction,and crowding, several hypotheses are suggested. Hui andBateson (1991) showed that perceived crowding (measuredas a unidimensional construct) decreases feelings of plea-sure in a service environment. We expect to replicate thisfinding with bothdimensions of crowding in the retail envi-ronment. Furthermore, we hypothesize crowding to influ-ence a multitude of affective responses beyond a pleasureresponse. This contention is based, in part, on work thatposits that two dimensions of emotional response—pleasureand arousal—encompass a range of emotional reactions thatcan take place in an environment (Mehrabian & Russell,1974; Russell, 1980). Literature suggests that perceivedcrowding can affect arousal in addition to a pleasure re-sponse; for example, dense settings are shown to increasetension and arousal (Stokols, 1972).

Although an advantage of the Mehrabian and Russelltwo-dimensional emotion typology is its parsimony, there areother emotion typologies that may help us understand morespecific emotional responses to crowding. Izard (1977), forexample, in his Differential Emotions Theory, has identified10 emotion types. These include 7 negative dimensions ofemotion (sadness, anger, disgust, contempt, fear, shyness,and guilt), 2 positive emotional dimensions (joy and interest),and 1 neutral dimension (surprise). Given that we expect re-tail crowding to produce negative reactions from shoppers,this typology, with its extensive negative dimensions, is par-ticularly appealing. Furthermore, this classification has beensuccessfully used in research that investigated the relation-ship between emotion and satisfaction (Oliver, 1993; West-brook, 1987).

Overall, we anticipate that because crowding creates feel-ings of stress and weakens coping abilities, shoppers incrowded retail environments will experience decreased lev-els of positive emotion and increased negative emotion. Fur-thermore, we hypothesize specific emotional states (Izard’s10 dimensions) to be elicited by both human and spatialcrowding. Izard (1977) noted that joy will be reduced by“matters that create stress and call for discontent” (p. 240);

thus, joy should decrease due to crowding. Furthermore,when a shopper experiences a store that isnotcrowded, feel-ings of joy may result due to the relief brought about by theadded space. The other positive emotion, interest, should alsodecrease when crowding increases due to the shopper’s re-duced ability to adequately pursue desired goals in the envi-ronment. Because interest is often related to the pursuit ofgoals (Izard, 1977), when shoppers’ ability to accomplishtheir goals is blocked by the crowded in-store environment,interest should decline.

Izard (1977) named the negative emotions of anger, dis-gust, and contempt to be a “hostility triad” that is frequentlyexperienced by individuals. Anger is the least subtle of thethree and can be triggered by

being either physically or psychologically restrained fromdoing what one intensely desires to do. Other causes of angerinclude personal insult, everyday frustrations (blocking or in-terfering with goal-oriented behavior), interruption of inter-est or joy, being taken advantage of, and being compelled todo something against one’s wishes. (p. 330)

As both human and spatial density can lead to restraint, frus-trations, and having to move or otherwise adapt to the density(essentially against one’s desires), we anticipate that feelingsof anger will result. It is also noted, however, that there are avery few stimuli or situations that evoke anger and only an-ger; feelings of disgust (wanting to remove or get away fromthe object) and feelings of contempt (which involves feelingsof hostility and prejudice) are closely intertwined with anger.All of these three emotions are “other-oriented” in nature(Smith & Ellsworth, 1985) and could be attributed to humandensity and undesired interactions as well as to the discomfortarising from high spatial density of the store (Oliver, 1993).

Although we anticipate the strongest effects of perceivedretail crowding on the emotion types of anger, disgust, andcontempt, we hypothesize that crowding may also result inother negative feelings, although to a lesser extent. Feelingsof shyness (or shame) arise when attention to the self is in-creased, a partial reduction of interest or enjoyment occurs,and when barriers to positive emotion-evoking explorationoccur (Izard, 1977). Given that high density settings areknown to obstruct exploration and enjoyment (Brehm, 1966),we posit that retail crowding will be positively correlatedwith feelings of shyness and shame. Furthermore, contemptfrom the self or others can activate shyness and shame (Izard,1977), and we anticipate that such contempt, which resultsfrom crowding, will, albeit weakly, contribute to feelings ofshyness. Similarly, guilt feelings, which are closely related toshyness and shame, result from sanctions (either external orinternal) due to some sort of personal misconduct or violationof social conventions (Izard, 1977; Tangney, Miller, Flicker,& Barlow, 1996). In this context, when a store is crowded, it islikely that a shopper might violate standards of conduct—forexample, by cutting someone off, reaching in front of some-

PERCEIVED RETAIL CROWDING AND SHOPPING SATISFACTION 31

one, or moving past someone without a typical level of polite-ness. In addition, guilt and anger often interact in frustratingsituations (Izard, 1977). We anticipate that the individualmay feel, at minimum, a low level of guilt if the anger is ex-pressed in a socially unacceptable manner.

Sadness is an emotion that can result from failure (Izard,1977). Unmet shopping objectives within a given period oftime, for instance, can instigate feelings of failure and sad-ness. On a similar note, Tomkins’s (1963) research illustratedthat sadness (or distress) can result from a continued exces-sive level of stimulation. The excess stimulation and blockingof goals, which are shown to be outcomes of crowding(Brehm, 1966), are, therefore, hypothesized to significantlyincrease feelings of sadness while shopping.

The experience of fear can vary by context and by indi-vidual differences; however, fear is generally felt by an in-dividual in the presence of something threatening (Izard,1977). Because crowding can create feelings of insecurity(perhaps due to personal harm or an increased likelihood ofhaving one’s possessions stolen), we hypothesize an in-crease in the level of fear experienced by shoppers when thestore is crowded.

Surprise, a neutrally valenced emotion, is a response thatcan arise when something unexpected is encountered (Izard,1977). Given that the spatial layout of a store does not changeoften, as long as the shopper is familiar with the store, spatialcrowding should not result in a surprise reaction. However,human crowding, when unexpected, could lead to feelings ofsurprise. In light of this discussion, it is hypothesized that

H1: Perceived retail crowding should be positivelycorrelated with negative and neutral emotionsand negatively correlated with positive emotions.Specifically:

a. Anger, disgust, contempt, fear, shyness, guilt, sad-ness, and arousal are positively correlated withperceived retail crowding.

b. Pleasure and joy are negatively correlated withperceived retail crowding.

c. The highest correlations will be observed for the hos-tility triad of emotions (anger, disgust, contempt).

d. Surpriseshouldcorrelatewithhumancrowdingonly.

Although retail crowding has been shown to reduce shop-ping satisfaction (Eroglu & Machleit, 1990; Machleit et al.,1994), we find it useful to retest this relationship because itconstitutes the basis for the following hypotheses. However,because high levels of crowding are expected to generate neg-ative emotions, and emotions have been shown to influencesatisfaction (Oliver, 1993), it seems reasonable to suspect thatemotions may mediate the relationship between crowdingand shopping satisfaction. That is, the negative feelings (anddecreased positive feelings) that result from crowding may bethe reason that satisfaction is reduced when the retail environ-ment is crowded. Thus, the following are posited:

H2a: Higher levels of perceived retail crowding willresult in lower levels of shopper satisfaction.

H2b: Therelationship between perceived retail crowdingand shopper satisfaction will be mediated by theemotionsassociatedwith theshoppingexperience.

The expectancy–disconfirmation model illustrates thatexpectations about product and service performance that arenot confirmed will influence satisfaction with the experience(Oliver, 1993; Westbrook, 1987). We extend this to the retailenvironment and hypothesize that shoppers who experience alevel of crowding consistent with what was expected willhave a high level of shopping satisfaction. Furthermore, whentheir expectations have been exceeded (e.g., the store is lesscrowded than anticipated), satisfaction will also be high. Butwhen expectations are negatively disconfirmed (e.g., thestore is more crowded than expected), satisfaction should below (Bitner, 1992).

H3: Shopper satisfaction will be higher when perceivedcrowding falls short of or meets crowding expecta-tions, and lower when perceived crowding exceedsexpectations.

Although research on the relationship between personalitytraits and crowding perceptions is scant, there is evidence thatan individual’s tolerance for crowding might be a potentialmoderator of the crowding–satisfaction relationship (Cozby,1973; Dooley, 1974). We propose that some people may actu-ally enjoy shopping (and even seek) crowded retail environ-ments, whereas others might have a very low tolerance forcrowds. Krohne, Hock, and Kohlmann (1992) presented apersonality model of coping and noted that individuals varyhabitually in their ability to tolerate both uncertainty andemotional arousal. Their suggestion of a personality charac-teristic of “Intolerance of Emotional Arousal” parallels ourproposition that there exists a personality characteristic of In-tolerance for Crowding. Thus, it seems reasonable that toler-ance for crowding should moderate the influence of crowdingon satisfaction.

H4a: Individuals vary in their ability to tolerate humandensity levels.

H4b: For individuals with a high tolerance for crowd-ing, there should be little or no relationship betweencrowding and satisfaction; conversely, for individu-als with a low tolerance for crowding, crowding willnegatively affect satisfaction.

Finally, the type of store may moderate the effect ofcrowding on satisfaction (Machleit et al., 1994). Shoppersmay gauge the “value” of a discount, outlet, or wholesaleclub by the number of people who are shopping there. Theshopper may make the attribution that if the store is notcrowded, the value must not be that good. The basis for


this hypothesis also comes from Manning Theory (Barker,1963) in ecological psychology. Barker examined the be-havioral and cognitive consequences of “undermanning,”a condition where participants are fewer than the numbertypically required to maintain a setting at an expected, op-timal level. In the case of discount stores, where the num-ber of shoppers could be considered as an integral part ofthe store environment and its low cost and high value posi-tioning, too few patrons could result in the condition ofperceived undermanning and potentially affect shoppers’store evaluation and satisfaction.

H5: For discount-type stores, high levels of humancrowding should not affect shopping satisfaction,whereas spatial crowding will be negatively re-lated to satisfaction. For other store types, therewill be a negative correlation between both di-mensions of crowding and satisfaction.

METHOD

Three studies were conducted. The first was a large fieldstudy, next was a similar field study with a smaller adult sam-ple, and the third was a laboratory experiment. The studies arediscussed sequentially next.

STUDY 1

Respondents

Students enrolled in undergraduate and graduate marketingclasses at three different (two large midwestern and one largesouthern) universities were asked to fill out a retrospectivesurvey. A description of the sample and the store type is foundin Table 1.

Survey Instrument

The cover page of the questionnaire briefly described for therespondents the purpose of the study: The researchers “… areinterested in the feelings and opinions that people have whilethey are shopping.” Students were asked to take the surveyhome and fill it out after their next shopping trip (and weretold that the shopping trip need not have resulted in a pur-chase). They were informed that there were no right or wronganswers and their responses would be anonymous. The sur-vey asked respondents to take a few minutes to think about theshopping trip and then answer the questions. After naming thestore, shopping center, or mall where they shopped, respon-dents were asked to answer various questions regarding thatshopping trip, ordered in such a way as to realistically recon-


TABLE 1Sample Characteristics

Study 1 Study 2 Study 3

Sample size 722 153 231Age

M 23.3 36.8 21.0Range 19–50 16–78 18–55

SexMale 54% 25% 54%Female 46% 75% 46%

Store typeCampus bookstore 2.9% 0.0%Mall 32.2% 13.8%Grocery store 17.3% 25.7%Hypermart 4.4% 14.5%Discount 6.5% 9.9%Department 11.4% 13.8%Off-price or outlet 2.9% 0.7%Wholesale club 0.1% 2.0%Drug store 3.3% 2.0%Specialty clothing 5.7% 3.9%Specialty shoes 0.7% 0.7%Specialty music 1.0% 0.0%Specialty books 1.2% 1.3%Sporting goods 1.5% 1.3%Stereo/Appliance/Electronic 2.9% 2.0%Hardware 0.5% 0.7%Other 5.6% 7.9%

struct the shopping experience in the respondent’s mind. Re-spondents were asked about their purchase behavior, purposefor the shopping trip, and past experience with the store ormall, and then asked about their perceptions of crowding, sat-isfaction, and outcome of the shopping trip. Next, the respon-dent was presented with traditional emotion measurementquestions. Finally, crowding tolerance questions and demo-graphic questions were asked.

This procedure of asking respondents to recall and rate arecent shopping trip has been used in other research to evalu-ate recent shopping experiences (Goff, Bellenger, & Stojack,1994; Mulhern & Padgett, 1995). Respondents have beenshown to be fairly accurate in their retrospective ratings ofemotions (Barrett, 1997), and they should be reasonably ac-curate in their recall of the details of the shopping episode, es-pecially given that they were asked to fill out thequestionnaire immediately following their next shoppingtrip. Furthermore, the critical incident method used in ser-vices marketing provides evidence that respondents are ableto recall the details of a prior event (Bitner, Booms, &Tetreault, 1990). Therefore, we conclude that this sur-vey-based approach, although perhaps not ideal, is an accept-able data collection method.

Measures

Perceived crowding was measured via the eight-item,two-dimensional Likert-type scale validated by Machleit etal. (1994). The four items in the human crowding dimensionwere “The store seemed very crowded to me,” “The store wasa little too busy,” “There wasn’t much traffic in the store dur-ing my shopping trip” (reverse coded), “There were a lot ofshoppers in the store.” The four items included in the spatialcrowding dimension were “The store seemed very spacious”(reverse coded); “I felt cramped shopping in the store”; “Thestore had an open, airy feeling to it” (reverse coded); “Thestore felt confining to shoppers.” All items loaded on the ex-pected dimensions, and the coefficient alpha reliability val-ues for each dimension were .90 and .84 for human and spatialcrowding, respectively.

Satisfaction was measured with the items used by Erogluand Machleit (1990) and Machleit et al. (1994). The 7-pointagreement items were “I enjoyed shopping at the store”; “I wassatisfied with my shopping experience at the store”; “Given achoice, I would probablynot go back to the store” (reversecoded); “I would recommend the store to other people.” Coef-ficient alpha reliability for the four item summed scale was .82.

Emotions were measured in two different ways: via the 10emotion types from Izard’s (1977) differential emotions the-ory and via Mehrabian and Russell’s (1974) pleasure andarousal dimensions. Izard’s 10 emotion types were measuredwith responses to the following adjectives: happy, delighted,cheerful for the joy emotion; sad, gloomy, depressed for thesadness emotion; alert, attentive for the interest emotion;mad, angry, irritated for the anger emotion; guilty, repentant,

blameworthy for the guilt emotion; ashamed, bashful, shy forthe shyness emotion; disgusted, feeling of distaste for the dis-gust emotion; disregard, contemptuous, scornful, defiant forthe contempt emotion; astonished, surprised for the surpriseemotion; and fearful, nervous for the fear emotion. Respon-dents were asked to indicate the extent to which they felt asdescribed by each of the adjectives during the shopping trip.These feelings were recorded on a 5-point scale ranging from1 (not at all) to 5 (very much so). Coefficient alpha reliabilityranged from .71 to .90 for all dimensions.

Pleasure and arousal were measured via Mehrabian andRussell’s (1974) semantic-differential scale that contains setsof bipolar adjectives designed to tap the two dimensions. Thesatisfied–unsatisfied item was removed from the pleasure di-mension so that it would not inflate the relationship betweenpleasure and satisfaction. After deleting other inappropriateitems (per a confirmatory factor analysis), the pleasure di-mension included three items (happy–unhappy, pleased–an-noyed, contented–melancholic) and the arousal dimensionincluded three items (stimulated–relaxed, excited–calm,aroused–unaroused). The alpha reliabilities were .87 and .76for the pleasure and arousal dimensions, respectively.

Prior expectations of crowding were measured by askingrespondents to rate expectations of human crowding on a7-point scale anchored ranging from 7 (more shoppers thanwere expected) to 4 (about as many shoppers as expected) to 1(fewer shoppers than were expected).

Finally, an Intolerance for Crowding measure was devel-oped. Four scale items were created, which reflected the do-main of the construct: “I avoid crowded stores wheneverpossible”; “A crowded store doesn’t really bother me” (re-verse coded); “If I see a store that is crowded, I won’t even goinside”; “It’s worth having to deal with a crowded store if Ican save money on the things I buy” (reverse coded). Confir-matory factor analysis indicated that all four items loaded ap-propriately on the one-dimensional measure, and coefficientalpha was .79.

Results

To investigate the relationship between emotion and per-ceived crowding, the two crowding dimensions were corre-lated with each dimension included in the Izard andMehrabian and Russell emotion typologies (Table 2). Consis-tent with H1, increased perceptions of crowding results in de-creased positive feelings, increased negative feelings, orboth. Note that both human and spatial crowding signifi-cantly affect pleasure, although the effect is stronger (z* =2.55,p = .006)1 for spatial crowding (r = –.24) than it is forhuman crowding (r = –.11). Contrary to our prediction, how-


1We use the Fisherz transformation for two Pearsonrs (Neter,

Wasserman, & Kutner, 1989) to test for significant directional differencesbetween correlations.

ever, perceived human crowding does not significantly affectfeelings of arousal. Furthermore, the effect of spatial crowd-ing on arousal is negative. If we consider the scale items usedto measure arousal (stimulated, excited, aroused), it could bethat the items were actually tapping a state of excitement forthe shopping trip rather than a state of tension (as hypothe-sized). Hence, if the shopper found the store to be spatiallycrowded, then the excitement of shopping was lessened.

Correlations with the emotional responses from Izard’stypology are also presented in Table 2. Notice that only spa-tial crowding significantly affects the positive emotion feel-ings of interest and joy. As hypothesized, feelings of surprisesignificantly increase when the shopper experiences humancrowding. Given that the respondents were highly familiarwith the stores they reported about (only 3.5% had never beento the store before; 75% had been to the store 10 or moretimes), it is logical that spatial crowding did not result in feel-ings of surprise.

Although crowding significantly increases all of the nega-tive feeling states, the hostility triad of anger, disgust, and con-tempt (other-orientedemotions)have thestrongestcorrelationswith both human and spatial crowding. The correlations withthe remaining emotions (the individual-oriented emotions), onthe other hand, are not as strong. This is as expected, given thatbothhumanandspatialcrowdingessentially force increased in-teractions with others while shopping, thus producing strongerresponses to the other-oriented emotions.

Consistent with findings from previous research, higherlevelsofcrowdingareassociatedwith lower levelsofsatisfac-tion (supporting H2a). Both human crowding and spatial

crowdingaresignificantlynegativelycorrelatedwithsatisfac-tion(r =–.16,p<.01;r =–.36,p<.01, respectively;n=725).

Next, with respect to the mediational effect of emotions onthe crowding–satisfaction link (H2b), we find that emotionsonly partially mediate the relationship (Baron & Kenny,1986). When the pleasure and arousal dimensions of emotionare included as mediators, the human crowding–satisfactionrelationship drops in magnitude (from –.16 to –.08), but stillremains significant (p = .015). For spatial crowding, the rela-tionship also significantly decreases in strength (from –.36 to–.23), but is still highly significant (p= .000). When the Izardemotions are used, the results are nearly the same: humancrowding–satisfaction relationship significantly drops inmagnitude (to –.07), but remains significant (p= .03); for spa-tial crowding, the relationship again decreases (to –.23) and isstill highly significant (p< .001). We conclude, therefore, thatemotions only partially mediate the effect of crowding on sat-isfaction and that there exists some direct effect of crowding,beyond the emotional reactions it evokes, that leads tochanges in satisfaction levels.

To test the extent to which crowding expectations relate tosatisfaction (H3), respondents were coded into three expecta-tion groups (“There were about as many shoppers as I ex-pected,” “There were fewer shoppers than I expected,” “Therewere more shoppers than I expected”). The data indicate thatnot only are shoppers most satisfied (M = 5.55, where 7 is high-est;n = 548) when their expectations are met, but they areequally satisfied (M = 5.47,n = 128) when the store is lesscrowded than they had expected. Conversely, shoppers’ satis-faction levels (M = 5.01,n = 62) are significantly lower,F(2,


TABLE 2Correlations Between Perceived Crowding and Emotion

Study 1a Study 2b Study 3c

HumanCrowding

SpatialCrowding

HumanCrowding

SpatialCrowding

HumanCrowding

SpatialCrowding

Mehrabian and RussellPleasure –.11** –.24** –.24** –.46**Arousal –.07 –.08* .23** .20**

IzardPositive dimensions

Joy –.07 –.16** –.11 –.27** .05 –.25**Interest .02 –.17** .09 –.09 –.03 –.01

Neutral dimensionSurprise .08* –.01 .04 –.12 .06 .04

Negative dimensionsAnger .25** .25** .17* .13 .25** .36**Disgust .17** .26** .12 .16* .15* .38**Contempt .20** .21** .12 .28** .21** .28**Shyness .10* .11** .10 .06 .08 .03Guilt .10* .09* .01 .11 .04 .11Sadness .09* .17** .05 .11 .25** .34**Fear .12** .12** .15* .03 .02 .05

an = 722.bn = 153.cn = 231.*p < .05. **p < .01.

735) = 6.54,p= .002, when there were more shoppers than theyhad anticipated. Thus, H3 is supported.

As proposed in H4a, we find that respondents do indeedvary in their tolerance for crowding. Scores on the four-item,7-point measure covered the entire possible range (from 4 to28) with a mean of 15.96, median and mode of 16, and a stan-dard deviation of 5.46. On an exploratory basis, we also in-vestigated the potential impact of sex on tolerance forcrowding. Previous studies on the impact of sex on crowdinghave been insignificant or inconclusive at best. Although fe-male respondents are found to report higher mean tolerancelevels than male respondents, the difference here was not sig-nificant. As proposed in H4b, the perceived crowding–satis-faction relationship appears to be moderated by tolerance forcrowding. Among those who report a low level of tolerancefor crowding (n = 158), both human and spatial crowding arenegatively correlated with satisfaction (r = –.16, p < .05;r =–.37,p< .01, respectively). Conversely, among those who re-port a high tolerance for crowding (n = 180), only spatialcrowding is negatively correlated with satisfaction (humancrowding–satisfactionr = .02,ns; spatial crowding–satisfac-tion r = –.30,p < .01). Thez transformation shows a signifi-cant moderating effect for human crowding (z* = 1.648,p =.05); thus, H4 is supported.

H5 suggests that the type of store should moderate thecrowding perceptions–satisfaction relationship for the hu-man crowding dimension only. Specifically, for the storeswhere shoppers may gauge value by the number of peopleshopping in the store (i.e., discount stores, outlet stores, etc.),human crowding is not significantly related to satisfaction (r= –.16,ns, n= 99), but spatial crowding remains significantlynegatively correlated with satisfaction (r = –.40,p < .01,n =99). For all other stores, satisfaction is significantly related toboth human and spatial crowding (r = –.15,p< .01,n= 630;r= –.33,p < .01,n = 630, respectively). We should note, how-ever, that whereas the correlation between human crowdingand satisfaction is nonsignificant in the discount store cate-gory (as hypothesized), the correlation is nearly the same inmagnitude for both store type categories and is not signifi-cantly different using thez transformation (z* = .09, ns).Thus, we cannot fully endorse H5.

Finally, we explored several other potential moderatorsof the crowding–satisfaction relationship, such as sex, storefamiliarity, time pressure, and whether a purchase wasmade during the shopping trip (Eroglu & Harrell, 1986).Findings indicate that of these suggested moderators, noneof them appeared to moderate the effects of perceivedcrowding on satisfaction.

STUDY 2

Because we were concerned that student respondents maydiffer in their responses to shopping relative to a more diverseadult audience, Study 2 was conducted as a replication of

Study 1 using nonstudent respondents. Respondents were re-cruited from a suburban parenting and social group, from twodifferent day care facilities, and from a private elementaryschool, and they were asked to participate in the study as partof a fund-raising activity. The organizations received $2 foreach completed questionnaire; staff and parents completedquestionnaires and recruited people they knew to participateas well. All respondents were instructed to take the task seri-ously. Because respondent fatigue was a concern with thisnonstudent sample, the Mehrabian and Russell measure wasnot included on the questionnaire. A description of the sampleis included in Table 1. Coefficient alpha levels were accept-able for all measures.

H1 issupportedwith thisdataset.Table2showsthatasper-ceived crowding increases, feelings of positive emotionalfeelings decreases and negative feelings increases (particu-larly the hostility triad). Interestingly, human crowding corre-lateswith feelingsofangerand fear,whereasperceivedspatialcrowding correlates with disgust and contempt. It is also inter-esting to note, however, that overall the correlations are not asstrong as those we observed in Study 1. We speculate that thisoutcome could be due to one of several factors. First, becauseof the smaller sample in Study 2, sampling error may be ob-scuring the true correlations. Another viable explanation isthat more of the Study 2 respondents reported their experi-encesshoppingatagrocerystorecomparedtomoremallshop-pers in Study 1. We would expect that mall shoppers, due tomore and varied environmental and merchandise stimulation,would experience a more diverse set of feelings than grocerystoreshoppers.A thirdexplanation is thatwhencomparing thelevels of perceived crowding experienced across the two sam-ples, Study 1 shoppers experienced higher levels of perceivedhumanandspatialcrowdingcompared to theStudy2shoppers(for Study 1, mean levels of human and spatial crowding were3.60 and 3.32, respectively; for Study 2, they were only 2.47and 2.26). Because perceived crowding was not as high for theStudy2shoppers, theymaynothaveexperienced thesameva-riety of emotions due to the higher crowding levels experi-enced by Study 1 shoppers.

H2a is supported with the Study 2 data. Again, both humanand spatial crowding significantly decrease shopping satis-faction (r = –.223,p< .01;r = –.32,p< .01). Furthermore, theemotion measures completely mediate the effect of humancrowding on satisfaction (H2b); the coefficient drops to –.09and is nonsignificant (p = .24). For spatial crowding, partialmediation is suggested by the decrease in the coefficient to–.20, and it remains significant (p = .01).

Contrary to the results from Study 1, H3 is not supportedwith the Study 2 data. Although the mean satisfaction valuesare as anticipated, there are no significant differences,F(2,107) = .847,p = .43, in shopping satisfaction for the three ex-pectation groups. When expectations were confirmed(“There were about as many shoppers as I expected”), themean satisfaction value (5 is highest) was 4.12 (n= 81). Whenthe store is less crowded than the shopper expected, satisfac-


tion is 3.99 (n= 19); when there are more shoppers than antic-ipated, the satisfaction level is lowest (3.83,n = 10). Note,however, that the group sizes (n = 19 andn = 10) for thedisconfirmed expectation groups are small, and statisticalpower may be an issue.2 Low group sizes not withstanding,the effect could be the result of other factors. Recall that forthe Study 2 sample, perceived crowding levels were low. Al-though some shoppers experienced an environment that con-tained greater human density than expected, perceptions ofcrowding were not at a high level overall. This restrictedrange may also be the reason for the lack of support for H3.

H4a is supported; respondents vary on their ability to toler-ate crowding as they report tolerance for crowding levelsacross all points on the scale. Again, consistent with the Study1 data, there is no significant difference in tolerance levels formen versus women. H4b, that the perceived crowding–satis-faction relationship is moderated by tolerance for crowding,is again supported. For those who report a low tolerance forcrowding, crowding correlates with shopping satisfaction (r= –.40,p< .01;r = –.45,p< .01,n= 47, for human and spatialcrowding, respectively). Only spatial crowding correlateswith satisfaction for the high tolerance individuals (r = .01,ns; r = –.31,p < .01,n = 48, for human and spatial crowding,respectively). The difference between high and low toleranceindividuals is significant for perceived human crowding (z* =2.03,p = .02), but not for spatial crowding (z* = .71,ns).

Recall that H5 posits that store type should moderate thecrowding–satisfaction relationship such that human crowd-ing should not affect shopping satisfaction for discount storetypes. We interpreted the Study 1 results cautiously becausethe magnitude of the human crowding correlation, eventhough nonsignificant for the discount store types, was nearlythe same for the two store-type groups. We find the same pat-tern with the Study 2 data. For discount-type stores, humancrowding is not significantly related to satisfaction (r = –.24,ns, n= 38), but spatial crowding is significantly correlatedwith satisfaction (r = –.42,p < .01, n = 38). For all otherstores, both human and spatial crowding significantly affectshopping satisfaction (r = –.23,p < .05,n = 107;r = –.29,p <.01,n = 107, for human and spatial crowding, respectively).Note that like the Study 1 data, the human crowding–satisfac-tion relationship is nearly the same in magnitude for the twogroups, even though, as hypothesized, it is nonsignificant inthe discount store group. But again, theztransformation indi-cates that there are no significant differences between the cor-relations in the discount versus other stores for human (z* =.05,ns) and spatial crowding perceptions (z* = .76,ns).

Finally, as in Study 1, we explored other potential modera-tors of the crowding–satisfaction relationship. Sex, time pres-sure, and whether a purchase was made were examined asmoderators in Study 2. Recall that when considering thesevariables in Study 1, none of them emerged as significantmoderators. For Study 2, however, we found that time pres-sure significantly moderates the crowding–satisfaction rela-tionship. There was a significant moderating effect of timepressure (z* = 2.16,p = .02) for human crowding; humancrowding significantly affects shopping satisfaction for thoseunder high time pressure (r = –.53,p< .001), but not for thoseunder low time pressure (r = .07,p = .63). Given that timepressure is shown to exacerbate perceptions of crowding(Eroglu & Machleit, 1990), it is not surprising that there issuch a strong correlation between crowding and satisfactionfor those under higher time pressure. Furthermore, looking atcorrelations between crowding and satisfaction by sex showsa pattern of moderating effects, although the differences werenot significant using a two-tailedz transformation test.3 Formale respondents (n = 37), human crowding does not signifi-cantly affect shopping satisfaction (r = –.01, p = .95),whereas spatial crowding does (r = –.35,p = 03). For femalerespondents (n = 107), both dimensions of crowding affectshopping satisfaction (r = –.28,p = .00 for human crowdingandr = –.32,p < .001 for spatial crowding). This moderatingeffect, however, is not borne out by thez transformation: hu-man crowding dimension (z* = 1.48 ,p = .14); spatial crowd-ing dimension (z* = .40,p = .69).

STUDY 3

As Studies 1 and 2 are field studies, they have the advantageof external and ecological validity. Respondents reportedtheir shopping experience as it naturally occurred across awide range of retail contexts. However, there are also someinherent limitations. First, the data are correlational in naturebased on a retrospective report by the respondents. As such,many elements that have been suggested to affect crowdingperceptions (Eroglu & Harrell, 1986) are not controlled, andthe causal nature of the relationship is unclear. Second, be-cause respondents reported a self-selected shopping experi-ence, self-selection bias could color the results. To overcomethese limitations, a laboratory experiment was designed toreplicate and extend the field work. Using videotapes of a re-tail setting, we can control the absolute number of shoppers inthe store, the amount of merchandise visible, and the place-ment of the merchandise. The store type and shopping crite-rion are controlled using a realistic scenario coupled with oneof four videotaped “stores.” In this way, the temporal order of


2The power for this analysis is only .20 (α = .05) and .31 (α = .10). This

low level of power (Stevens, 1990) suggests a high probability of Type II er-ror. This low power is driven by a combination of low effect sizef = .124 (Co-hen, 1977) and extremely low base sizes in two of the cells (n = 19 andn =10). Even if we were expecting a medium effect size similar to the effectfound in Study 1 (f = .25), we would need between 32 and 44 participants percell to have an acceptable level of power.

3As prior research shows mixed effects regarding sex and crowding

(Stockdale, 1978), we could not pose a directional prediction.

events can be controlled, and self-selection of shopping situa-tion can be eliminated.

The four videotapes manipulated both human and spa-tial density (higher vs. lower human density and highervs. lower spatial density). A professional videographerfilmed a scene from a campus bookstore (approximatesize of 45 × 60 ft). The scene included an aisle in the cen-ter that led to a circular checkout desk with three cash reg-isters (only one cash register was open at this time). Onboth sides of the aisle and behind the checkout area(where there was about 20–25 ft of retail space) werebookracks and shelves. There was nothing in the scene toindicate that this was a campus bookstore.

Human density was varied by controlling the number ofshoppers in the scene. Spatial density was varied by movingsome of the 3-ft-high bookracks into the aisle area rather thanhaving them on the side; shoppers then had to weave in andout of the bookracks to reach the checkout area. All tapes hadthe same bookracks in the scene; they were simply positioneddifferently in the space to represent differences in spatial den-sity. A pretest indicated that the higher versus lower humanand spatial density levels were successfully manipulated.Overall multivariate analysis of variance and univariate anal-ysis of variance tests show that the spatial density effects onvariables related to the amount of space and arrangement ofmerchandise in the store were significant; similarly, the hu-man density effect on statements about the number of peoplein the store were also significant (p < .01).

The scenarios used to set up the “shopping experience”were designed to enable us to replicate the findings fromthe field studies. Because respondents in the first two stud-ies were able to choose the store type, self-selection biaswas clearly at issue in testing H5; therefore, the experimentwas set up to further investigate the store-type moderationhypothesis. Thus, store type (discount vs. upscale book-store) was manipulated via the scenario. Participants weretold the following:

Now I will read to you the description of a shopping sit-uation that also appears below. Please read it silentlywhile I read aloud and try to imagine yourself in the de-scribed situation. It is very important that you put your-self in the context that is being described:

You are now in adiscount [upscale] bookstore(suchas Half-Priced Books [Barnes and Noble]). You aretrying to find a book that you previously have hadtrouble locating. This book is critical because it wassuggested to you that it would be helpful in your jobsearch strategy. Next week is the only stretch of timethat you can devote to reading the book, so you wouldlike to find it soon.

Now please watch the video and imagine yourself shop-ping for the book in thisdiscount [upscale] bookstore.

There were 231 student participants processed in large groups.Theyweregiven thescenario to readand then theywatched the55second videotape on a large screen. Manipulation checks indi-cated that the store-type manipulation was successful; respon-dents indicated that they expected the store to have inexpensive(expensive) books and books priced lower (higher) than the com-petition for the discount (upscale) store type (p < .000).

Note thatdensity,not perceived crowding,was manipu-lated with the videotapes. Density is an objective measureof the number of people and the amount and placement ofthe merchandise, whereas perceptions of crowding are indi-vidual in nature. Because density is a precursor to crowdingperceptions, we examined the effects of the manipulations(i.e., human density, spatial density, and store type) on per-ceived retail crowding (both human and spatial). As ex-pected, there were no main or interactive effects of storetype on either human or spatial crowding perceptions. Theeffects of the two density manipulations on perceived hu-man and spatial crowding are also in the expected directionand shown in Figure 1.

For human crowding, there is a significant main effect ofhuman density (p < .001), a nonsignificant main effect ofspatial density (p = .165), and a significant Human Density× Spatial Density interactive effect (p < .006). Interestingly,it appears that when the store is spatially dense (i.e., less


FIGURE 1 Mean perceived crowding levels by density manipulations.

space to move about), this adds to the perceptions of humancrowding (i.e., shoppers experience greater feelings of hu-man crowding).

For spatial crowding perceptions, there are significantmain effects for spatial density (p < .001) and human density(p = .030), but no significant interactive effect (p = .278).Across both spatial density conditions, feelings of spatialcrowding were lower when human density was lower. Fur-thermore, both types of density seem to affect both types ofcrowding perceptions (either via a main or an interactive ef-fect). This is an interesting finding because, to our knowl-edge, prior work has not been able to isolate the relationshipbetween the crowding dimensions and density to this extent.

We now test the hypothesized relationships with this newexperimental data. Recall that H1 posits that higher levels ofcrowding will result in decreased positive feelings and in-creased negative feelings. The correlations between humanand spatial crowding and the emotion measures are includedin Table 2. Overall, these correlations are quite similar towhat was found in the field studies, especially given that asimulated shopping episode would be expected to produceweaker feelings than what would be experienced in a realshopping trip. Of particular note is that some of the highestcorrelations are found for Izard’s hostility triad of anger, dis-gust, and contempt. Perceptions of both human and spatialcrowding seem to evoke these negative feelings in shoppers.Furthermore, both human and spatial crowding decrease feel-ings of pleasure while shopping, with spatial crowding hav-ing the strongest effect (–.46).

Given that the rest of the hypotheses are related to moder-ating and mediating factors of therelationshipbetween per-ceived crowding and shopping satisfaction, correlations ofperceived human and spatial crowding with shopping satis-faction are examined (paralleling Study 1). Consistent withStudies 1 and 2, both human and spatial crowding result inlower levels of shopping satisfaction (r = –.18,p < .01; r =–.56,p < .01, respectively;n = 231) to support H2a.

Consistent with the field studies, emotions are shown to par-tiallymediate theeffectofbothhumanandspatial crowdingper-ceptions on satisfaction (H2b). When the pleasure and arousaldimensions of emotion are used, the results resemble Study 2:The human crowding–satisfaction relationship drops in magni-tude (from –.18 to –.02) and becomes nonsignificant. For spatialcrowding the relationship also drops (from –.56 to –.32), but isstill highly significant (p < .001). When the Izard emotions areused, the results are consistent with Study 1: Human crowd-ing–satisfaction relationship drops (to –.12), but remains signifi-cant (p= .034), and spatial crowding–satisfaction drops to –.41,but also remains significant (p < .001). Thus, given the resultsfrom these three data sets, we can feel confident in our conclu-sion that emotions only partially mediate the effect of crowdingon shopping satisfaction. Therefore, there exists either a directeffect of crowding or some other mediating effect beyond theemotional responses evoked by crowding that leads to changesin shopper satisfaction.

The lab study was not designed to test H3. H3 involvedshoppers’ expectations of crowding before coming to thestore; given that the shopping episode in Study 2 was a simu-lated one, the participants could not have had expectationsabout the shopping event prior to the study.

H4 posits that the perceived crowding–satisfaction rela-tionship will be moderated by personal tolerance levels forcrowding. Again, consistent with Studies 1 and 2, for thosewho report a low level of tolerance for crowding (n = 126),both human and spatial crowding are negatively correlatedwith satisfaction (r = –.29,p < .01;r = –.59,p < .01, respec-tively), whereas for those who report a high tolerance level (n= 105), only spatial crowding is negatively correlated withsatisfaction (human crowding–satisfactionr = –.04,ns; spa-tial crowding–satisfactionr = –.52, p < .01). The humancrowding correlations are significantly different for the twogroups (z* = 1.93,p = .026), therefore, H4 is supported withall three data sets. Also, consistent with Studies 1 and 2,women reported higher mean tolerance for crowding levelsthan men, but the difference again was not significant.

H5 examines the moderating effect of store type on thecrowding–satisfaction relationship. Specifically, it was hy-pothesized that for discount-type stores, human crowdingshould not be significantly related to shopping satisfaction.Recall that H5 was supported in Studies 1 and 2, but becausethe correlations between human crowding–satisfaction inboth store types were nearly the same in magnitude (althoughnonsignificant, as hypothesized, for the discount store), weinterpreted the findings cautiously.

In Study 3, however, we find almost the opposite of whatwe hypothesize. In the discount store condition, contrary topredictions, human crowding is significantly correlated withsatisfaction (r = –.21,p = .022) as is spatial crowding (r =–.48,p< .01). For the upscale store condition, we find that hu-man crowding is not significantly correlated with shoppingsatisfaction (r = –.15,p= .101) and spatial crowding is signif-icantly correlated (r = –.62,p < .001). Neither the humancrowding (z* = .47,ns) nor the spatial crowding correlations(z* = 1.52,p = .06) were significantly different by store type.To try and further understand these results, we examined thecrowding–satisfaction correlations by store type and alsoacross the density conditions; Table 3 shows the correlationsfor each cell. Notice that, as hypothesized, spatial crowdingaffects shopping satisfaction across all cells for both storetypes. Also, the human crowding–satisfaction relationship isnonsignificant for the discount store (as hypothesized) in allbut one cell: the high spatial, high human density cell. Recallthat there was an interaction effect of human and spatial den-sity on human crowding perceptions, with the highest humancrowding level for this particular cell. It could be that we areobserving a ceiling effect where, even if it is a discount storeand the level of human density is such that it suggests value,there is a point where the environment gets too crowded andsatisfaction levels are affected. Similarly, there may also be afloor effect. For example, in the low human density condi-


tions for the upscale store, we see that perceptions of humancrowding do not significantly affect shopping satisfaction.For these low density situations, some other factors appear tobe driving satisfaction.

Studies 1 and 2 examined other moderating variables on anexploratory basis; because Study 3 is an experiment and theshopping intentions and context are controlled, the only addi-tional variable to explore is sex. Recall that Study 1 showedno moderating effects of sex, whereas Study 2 showed a pat-tern of moderating effects that were not significant. Consis-tent with Study 2, the Study 3 data show that both dimensionsof crowding affect shopping satisfaction for female respon-dents (r = –.32,p = .00, human crowding;r = –.65,p = .00,spatial crowding), but for male respondents, only spatialcrowding affects satisfaction (r = –.09,p= .32, human crowd-ing; r = –.48,p = .00, spatial crowding). At a .10 level, maleand female shoppers are significantly different for both hu-man (z* = 1.80,p= .08, two-tailed test) and spatial (z* = 1.89,p = .06, two-tailed test) crowding correlations with satisfac-tion. Thus, our findings are in keeping with previous studieson the relationship between crowding and sex differences,which have shown inconsistent and mixed results (see Stock-dale, 1978, for a review).

DISCUSSION

Overall, the results from three studies indicate that the effectof retail crowding on shopping satisfaction is not a simple, di-rect one. A crowded store may or may not result in decreasedsatisfaction; this effect depends on a number of different indi-vidual and situational factors. The results of two field studiesindicate that although emotions partially mediate the crowd-ing–satisfaction relationship, the decrease in shopping satis-faction due to crowding is mediated by expectations of andtolerance for crowding. A laboratory experiment that repli-cated the field studies showed that the relationship betweenperceived crowding and store satisfaction also appears tovary by store type, albeit with the existence of a “floor andceiling” effect.

To place our findings and conclusions in proper per-spective, however, it is important to note the limitations of

the study. Although some of these were addressed byundertaking multiple studies, the others can suggest direc-tions for future research. For example, given the potentialdifferences in reactions to crowding between younger andolder shoppers, Study 2 was conducted as a replication ofthe first study. Similarly, Study 3 was conducted to ad-dress the limitations of the two field studies that producedcorrelational data and are based on a retrospective reportof a self-selected shopping experience. Another limitationconcerns the ecological validity of the videotaped densitymanipulations used to create various levels of store crowd-ing. The extent to which respondents can successfullyimagine themselves in the described store environment islikely to affect their responses.

A number of future research avenues emerge from thesefindings. First, the stronger negative effects of spatial crowd-ing relative to human crowding in all three studies deservesspecial attention given the potential theoretical and practicalimplications of this finding. In Study 1 particularly, spatialcrowding was found to heighten all of the negative emotionswhile reducing all of the positive emotions and shopper satis-faction. These effects were stronger than those created by hu-man crowding for almost every emotion dimension. Theseresults are consistent with Saegert’s (1973) work, whichshowed that individuals react differently to changes in groupsize (i.e., human density) than to changes in spatial features.Although a higher number of people may heighten complex-ity and total stimulation, it may also imply a potential forchange in crowding perceptions because people are likely tomove in time, thereby altering density perceptions within thegiven space. Conversely, a reduction in available space due tononhuman elements can be seen as being less flexible andmore permanent, at least in the limited time period allotted toshopping. In the context of a store that is not spatiallycrowded but densely populated with shoppers, the potentialfor movement and alteration of the crowding levels might, toa certain extent, help diffuse some of the negative retailcrowding outcomes. On the contrary, if the store werecrowded on the space dimension (say, due to excessive mer-chandise, narrow aisles, overflowing racks), shoppers mighthave felt that they had less opportunity to change the environ-ment. Interestingly, our data show that even among those who


TABLE 3Study 3 Correlations Between Crowding and Satisfaction by Experimental Cells

Discount Store Upscale Store

Density Condition Human Cr. Spatial Cr. Human Cr. Spatial Cr.

Low spatial, high human density –.354 –.554** –.526** –.693**High spatial, high human density –.535** –.462* –.437* –.501*High spatial, low human density .204 –.586** –.092 –.771**Low spatial, low human density –.152 –.334* –.263 –.551**

Note. Cr. = crowding.*p < .05. **p < .01.

have a high tolerance for crowding, spatial crowding still cor-relates negatively with shopper satisfaction. The relationshipbetween these two crowding dimensions as well as their indi-vidual and combined effects on various shopping strategiesand outcomes are topics that require further attention giventheir significant theoretical and managerial implications.

The role of attributions in determining the crowding–satis-faction relationship is another potential future research areaemerging from this study. For example, it may be that when astore has a large number of people, shoppers may not hold thisagainst the retailer in making a satisfaction judgment. On onehand, shoppers might reason that it is not the retailer’s faultthat a lot of people decided to shop today. On the other hand,they might think that the retailer should have anticipated thecrowds and done something about it. Conversely, if the shop-per thinks that the retailer really has made an effort to accountfor the increased number of shoppers (e.g., by adding morecheckout lines at a grocery store), then human crowdingshould not significantly affect satisfaction. If this is the case,then it would be important to examine the attributions thatshoppers make about reasons for and management’s dealingwith the crowding issue and how these attributions moderatethe crowding–satisfaction relationship.

Another area of further investigation concerns the role ofstore type as a moderator of the impact of crowding on satisfac-tion. Specifically, for discount-type stores, where shoppersmay gauge value by the number of patrons in the store, humancrowding was not significantly related to shopping satisfac-tion. Yet, this was not true for nondiscount stores. One possibleexplanation can be found in Barker’s (1963) Manning Theoryand its implications on store staffing and customer–staff inter-action policies. In addition, the possibility of observing differ-ent ceiling and floor effects across different store types shouldbe examined more carefully, as these findings might yield im-portant store atmosphere and customer routing suggestions forretail managers.

Inconclusion,wehavemadeprogress inunderstanding theboundary conditions for the perceived crowding–satisfactionrelationship. Given our existing knowledge about the impactof retailcrowdingonvariousaspectsofshoppingbehaviorandoutcomes, it would seem appropriate to also start focusing at-tention on how shoppers respond to retailer strategies de-signed to alleviate the negative consequences of crowding.

ACKNOWLEDGMENTS

This study was supported, in part, by a University ofCincinnati College of Business Administration Summer Fac-ulty Research Fellowship and a University of Toledo Infor-mation Systems and Operations Management DepartmentAcademic Challenge Grant.

We thank Paul Herr and three anonymous reviewers fortheir helpful suggestions.

REFERENCES

Anderson, E. W., & Fornell, C. (1994). A customer satisfaction research pro-spectus. In R. T. Rust & R. L. Oliver (Eds.),Service quality: New direc-tions in theory and practice(pp. 241–268). Thousand Oaks, CA: Sage.

Barker, R. (1963). Ecology and motivation.Nebraska Symposium on Moti-vation, 8,1–50.

Baron, R. M., & Kenny, D. (1986). The moderator–mediator distinction insocial psychology research: Conceptual, strategic, and statistical con-siderations. Journal of Personality and Social Psychology, 51,1173–1182.

Barrett, L. F. (1997). The relationships among momentary emotion experi-ences, personality descriptions, and retrospective ratings of emotion.Personality and Social Psychology Bulletin, 23,1100–1110.

Bitner, M. J. (1992). Servicescapes: The impact of physical surroundings oncustomers and employees.Journal of Marketing, 56,57–71.

Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encoun-ter: Diagnosing favorable and unfavorable incidents.Journal of Mar-keting, 54,71–84.

Bower, G. (1981). Mood and memory.American Psychologist, 36,129–148.Bower, G., Gilligan, S., & Monteriro, K. (1981). Selectivity of learning

caused by affective states.Journal of Experimental Psychology: Gen-eral, 110,451–473.

Brehm, J. (1966).A theory of psychological reactance.New York: Academic.Carson, T., & Adams, H. (1980). Activity valence as a function of mood

change.Journal of Abnormal Psychology, 89,368–377.Cohen, J. (1977).Statistical power analysis for the behavioral sciences. New

York: Academic.Cozby, P. C. (1973). Effects of density, activity, and personality on environ-

mental preferences.Journal of Research in Personality, 7,45–60.Dooley, B. B. (1974).Crowding stress: The effects of social density on men

with “close” or “far” personal space.Unpublished doctoral disserta-tion, University of California, Los Angeles.

Eroglu, S. A., Ellen, P. S., & Machleit, K. A. (1991). Environmental cues inretailing: Suggestions for a research agenda. In W. R. Darden, R. F.Lusch, & J. B. Mason (Eds.),Proceedings of the 1991 symposium on pa-tronage behavior and retail strategy: The cutting edge II(pp. 51–60).Baton Rouge: Louisiana State University.

Eroglu, S. A., & Harrell, G. D. (1986). Retail crowding: Theoretical and stra-tegic implications.Journal of Retailing, 62,347–363.

Eroglu, S. A., & Machleit, K. A. (1990). An empirical study of retail crowd-ing: Antecedents and consequences.Journal of Retailing, 66,201–221.

Fantasia, R. (1996, March 10). Market strategies: Grocery stores are findingways to make shopping more convenient for their busy customers.TheVirginian-Pilot, p. F1.

Gardner, M. P. (1985). Mood states and consumer behavior: A critical re-view. Journal of Consumer Research, 12,281–300.

Ger, G. (1989). Nature of effects of affect on judgment: Theoretical andmethodological issues. In P. Cafferata & A. M. Tybout (Eds.),Cogni-tive and affective responses to advertising(pp. 263–275). Lexington,MA: D. C. Heath.

Goff, B. G., Bellenger, D. N., & Stojack, C. (1994). Cues to consumer sus-ceptibility to salesperson influence: Implications for adaptive retailselling. Journal of Personal Selling & Sales Management, 14(2),25–39.

Harrell, G. D., Hutt, M. D., & Anderson, J. C. (1980). Path analysis of buyerbehavior under conditions of crowding.Journal of Marketing Re-search, 17,45–51.

Holbrook, M. B., & Batra, R. (1987). Assessing the role of emotions as medi-ators of consumer responses to advertising.Journal of Consumer Re-search, 14,404–420.

Hui, M. K., & Bateson, J. E. G. (1991). Perceived control and the effects ofcrowding and consumer choice on the service experience.Journal ofConsumer Research, 18,174–184.


Iacobucci, D., Ostrom, A., & Grayson, K. (1995). Distinguishing servicequality and customer satisfaction: The voice of the consumer.Journalof Consumer Psychology, 4,277–303.

Isen, A. M. (1989). Some ways in which affect influences cognitive pro-cesses: Implications for advertising and consumer behavior. In P.Cafferata & A. M. Tybout (Eds.),Cognitive and affective responses toadvertising(pp. 91–117). Lexington, MA: D. C. Heath.

Isen, A., Shalker, T., Clark, M., & Karp, L. (1978). Affect, accessibility ofmaterial in memory, and behavior: A cognitive loop?Journal of Per-sonality and Social Psychology, 36,1–12.

Izard, C. E. (1977).Human emotions. New York: Plenum.Izard, C. E. (1993). Organizational and motivational functions of discrete

emotions. In M. Lewis & J. M. Haviland (Eds.),Handbook of emotions(pp. 631–641). New York: Guilford.

Krohne, H. W., Hock, M., & Kohlmann, C-W. (1992). Coping dispositions,uncertainty and emotional arousal. In K. T. Strongman (Ed.),Interna-tional review of studies on emotion, 2(pp. 73–96). Winchester, Eng-land: Wiley.

Leventhal, H. (1981). The integration of emotion and cognition: A viewfrom the perceptual-motor theory of emotion. In M. Clark & S. Fiske(Eds.),Affect and cognition: The Seventeenth Annual Carnegie Sym-posium on Cognition(pp. 121–156). Hillsdale, NJ: Lawrence ErlbaumAssociates, Inc.

Machleit, K. A., Kellaris, J. J., & Eroglu, S. A. (1994). Human vs. spatial di-mensions of crowding perceptions in retail environments: A note ontheir measurement and effect on shopper satisfaction.Marketing Let-ters, 5,183–194.

Mehrabian, A., & Russell, J. A. (1974).An approach to environmental psy-chology.Cambridge, MA: MIT Press.

Miller, C. (1993, August 30). Glitzy interiors transform stores into “destina-tions,” boost sales.Marketing News,pp. 1, 6.

Mulhern, F. J., & Padgett, D. T. (1995). The relationship between retail pricepromotions and regular price purchases.Journal of Marketing, 59(4),83–90.

Nagar, D., & Pandey, J. (1987). Affect and performance on cognitive task asa function of crowding and noise.Journal of Applied Social Psychol-ogy, 17,147–157.

Nasby, W., & Yando, R. (1982). Selective encoding and retrieval ofaffectively valence information.Journal of Personality and Social Psy-chology, 43,1244–1255.

Neter, J., Wasserman, W., & Kutner, M. (1989).Applied linear regressionmodels(2nd ed.). Boston: Irwin.

Oliver, R. L. (1993). Cognitive, affective and attribute bases of the satisfac-tion response.Journal of Consumer Research, 20,418–430.

Oliver, R. L., & DeSarbo, W. S. (1988). Response determinants in satisfac-tion judgments.Journal of Consumer Research, 14,495–507.

Punj, G. N., & Stewart, D. W. (1983). An interaction framework of consumerdecision-making.Journal of Consumer Research, 10,181–196.

Russell, J. A. (1980). A circumplex model of affect.Journal of Personalityand Social Psychology, 39,1161–1178.

Rust, R. T., & Oliver, R. L. (1994). Service quality: Insights and managerialimplications from the frontier. In R. T. Rust & R. L. Oliver (Eds.),Ser-vice quality: New directions in theory and practice(pp. 1–20). Thou-sand Oaks, CA: Sage.

Saegert, S. C. (1973). Crowding, cognitive overload and behavioral con-straint. In N. Prieser (Ed.),Environmental design and research. PA:Dresden, Hutchinson and Ross.

Schwarz, N., & Clore, G. (1983). Mood, misattribution, and judgments ofwell being: Informative and directive functions of affective states.Jour-nal of Personality and Social Psychology, 45,513–523.

Smith, C. A., & Ellsworth, P. C. (1985). Patterns of appraisal and emotion re-lated to taking an exam.Journal of Personality and Social Psychology,52,475–488.

Spreng, R. A., & Mackoy, R. D. (1996). An empirical examination of a model ofperceivedservicequalityandsatisfaction.JournalofRetailing,72,201–214.

Stevens, J. (1990).Intermediate statistics: A modern approach. Hillsdale,NJ: Lawrence Erlbaum Associates, Inc.

Stockdale, J. E. (1978). Crowding: Determinants and effects.Advances inExperimental and Social Psychology, 11,197–245.

Stokols, D. (1972). On the distinction between density and crowding.Psy-chological Review, 79,275–277.

Tangney, J. P., Miller, R. S., Flicker, L., & Barlow, D. H. (1996). Are shame,guilt, and embarrassment distinct emotions?Journal of Personality andSocial Psychology, 70,1256–1269.

Teasdale, J. D., Taylor, R., & Fogarty, S. J. (1980). Effects of induced ela-tion–depression on memories of happy and unhappy experiences.Be-havior Research and Therapy, 18,339–346.

Tomkins, S. S. (1963).Affect, imagery, consciousness. Vol. II. The negativeaffects. New York: Springer.

Tse, D. K., & Wilton, P. C. (1988). Models of consumer satisfaction forma-tion: An extension.Journal of Marketing Research, 25,204–212.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psy-chology of choice.Science, 211,453–458.

Westbrook, R. A. (1987). Product/consumption-based affective responsesand postpurchase processes.Journal of Marketing Research, 24,258–270.

Woodruff, R. B., Cadotte, E. R., & Jenkins, R. L. (1983). Modeling consumersatisfaction process using experience-based norms.Journal of Mar-keting Research, 20,296–304.

Accepted by Paul Herr.


Perceived retail crowding and shopping satisfaction: the role of shopping values

Documents

Transcript of Perceived retail crowding and shopping satisfaction: the role of shopping values