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

Perceived Retail Crowding and Shopping Satisfaction: What Modifies This Relationship?

PERCEIVED RETAIL CROWDING AND MACHLEIT, SHOPPING EROGLU, SATISFACTION MANTEL

Karen A. Machleit Department of Marketing University of Cincinnati

Sevgin A. Eroglu Department of Marketing Georgia State University

Susan Powell Mantel Department of Marketing University of Toledo

Research has shown that an increase in perceived crowding in a retail store (created from either human 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 determine the extent to which it is a simple, direct relationship. Specifically, we consider the possibility that the crowding–satisfaction relationship is mediated by emotional reactions that are experienced while shopping. In addition, moderating variables such as prior expectations of crowding, tolerance for crowding, and store type are examined for their influence on the crowding–satisfaction relationship. The results of two field studies indicate that whereas emotions only partially mediate the relationship, the decrease in shopping satisfaction due to crowding is moderated by expectations of crowding and personal tolerance for crowding. A laboratory experiment replicated the field studies and shows, in addition, that although ceiling and floor effects may be present, the relationship between perceived crowding and shopping satisfaction appears to vary by store type.

The impact of physical environmental factors on store image and patronage is a topic that continues to attract research attention (Fantasia, 1996; Miller, 1993). Management decisions about the design, ambient, and social elements of the store environment can be greatly enhanced by an understanding of consumer–environment relationships (Bitner, 1992; Eroglu, Ellen, & Machleit, 1991; Rust & Oliver, 1994). Indeed, Iacobucci, Ostrom, and Grayson (1995) suggested that the physical environment plays a significant role in shaping customer satisfaction. One environmental factor that has received considerable research interest is in-store crowding (Eroglu & Machleit,

Requests for reprints should be sent to Karen A. Machleit, PO Box 210145, University of Cincinnati, Cincinnati, OH 45221–0145. E-mail: [email protected]

1990; Harrell, Hutt, & Anderson, 1980; Hui & Bateson, 1991; Machleit, Kellaris, & Eroglu, 1994). Perceived crowding is a psychological state that occurs when a person’s demand for space exceeds the supply (Stokols, 1972). Research to date has shown that the level of in-store crowding perceived by shoppers can affect their patronage decisions as well as satisfaction with the overall shopping activity (Eroglu & Machleit, 1990). Clearly, if perceived crowding does affect shopper behavior to some degree, those who are interested in shaping such behaviors will want to understand the specifics of this relationship. We extend previous work on retail crowding by examining the specific nature of its effects on shopper satisfaction. Recent work in the area has uncovered two dimensions of retail crowding—human and spatial—that are shown to have different relationships with store satisfaction (Machleit et al., 1994). Furthermore, these authors suggested that although perceived

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MACHLEIT, EROGLU, MANTEL

retail crowding can reduce shopping satisfaction, the relationship may not be a simple, direct one; there could be factors that moderate and mediate the relationship. Consistent with Anderson and Fornell’s (1994) call for further investigation into the antecedents of satisfaction, Machleit et al. specifically called for additional study to understand the particular way in which crowding acts as an antecedent to satisfaction. Consequently, this research focuses on several potential moderating and mediating influences on the relationship between retail crowding and customer satisfaction with the shopping experience. Specifically, we examine the role of emotions, crowding tolerance, and store category as potential influencers of the crowding–satisfaction relationship.

CROWDING Perceived crowding is a result of physical, social, and personal factors that sensitize the individual to actual or potential problems arising from scarce space (Stokols, 1972). When the number of people, objects, or both, in a limited space (referred to as density) restricts or interferes with individuals’ activities and goal achievement, the individual will perceive that the environment is crowded. Perceptions of crowding are individual in nature; two different shoppers in the same store may perceive different levels of crowding depending on individual characteristics and situational constraints. Perceived retail crowding appears to be a multidimensional construct consisting of two dimensions: spatial and social (Machleit et al., 1994). The number of nonhuman elements in an environment and their relationships to each other all help define the extent of spatial crowding perceived by individuals. Within the retailing context, for example, the amount of merchandise and fixtures as well as their configuration within the store could enhance or suppress perceived crowding associated with physical stimuli. The social (or human) dimension of crowding, on the other hand, concerns the number of individuals as well as the rate and extent of social interaction among people in a given environmental setting. High social density may lead to undesirable outcomes such as lack of privacy or personal territory resulting in heightened feelings of being crowded. The effects of crowding on shopping satisfaction may depend on certain moderators and mediators. One such variable could be customer emotions. The extent of human and spatial crowding perceived by a shopper may elicit negative emotions and stress associated with a lack of perceived control (Hui & Bateson, 1991; Nagar & Pandey, 1987). This undesirable outcome is particularly accentuated when high levels of crowding are not expected and the individual has a low tolerance for crowding. Given the demonstrated relationship between emotions and satisfaction (Oliver, 1993), it is likely that the nature and extent of emotions instigated by crowding could also play a role in shaping the relationship between cus-

tomers’ perceptions of crowding and their satisfaction with the shopping experience.

EMOTIONAL RESPONSES, RECALL, AND SATISFACTION Our behavioral reactions to emotions develop early and can affect perception, cognition, motivation, and behavior (Izard, 1993). There is a need to distinguish at this point between affect and emotion. Although both are related, affect is typically identified as simple positive, neutral, or negative feelings associated with a low involvement external stimuli, and emotion is a more deeply rooted, multidimensional construct (Holbrook & Batra, 1987) that can be influenced via specific situations and specific events (Gardner, 1985). Research indicates that both affect and emotion can influence behavior and thought processes by influencing storage, organization, and retrieval of cognitive information (Ger, 1989; Isen, 1989; Leventhal, 1981; Nasby & Yando, 1982; Teasdale, Taylor, & Fogarty, 1980). Consumer satisfaction is important to the retailer because it has been shown to be a recursive process in which satisfaction with a previous experience influences future shopping choices (Woodruff, Cadotte, & Jenkins, 1983). For retrospective satisfaction to influence the future shopping trip, the consumer must rely on some measure of recall from the previous experience. It has been shown that mood states tend to bias judgment in mood-congruent directions for product evaluations (Isen, Shalker, Clark, & Karp, 1978), enjoyableness (Carson & Adams, 1980), and respondent satisfaction with their lives (Schwarz & Clore, 1983). Furthermore, recall tends to be biased in the direction of the momentary emotion associated with the event being recalled (Bower, 1981; Bower, Gilligan, & Monteriro, 1981, Experiment 5). Therefore, the momentary emotion felt during a shopping trip is likely to influence judgments about the shopping trip, subsequent recall of the shopping trip, and future choices regarding similar shopping trips. Research has suggested that expectations are a determinant of consumer satisfaction (Punj & Stewart, 1983). Because consumers’ perception of an objective task is a function of the individuals’ reference point prior to the task (Tversky & Kahneman, 1981), postshopping consumer satisfaction should be related, at least in part, to the extent to which their expectations of the experience are exceeded or dispelled (Oliver, 1993). This “expectancy–disconfirmation” model of satisfaction has been empirically examined in a number of contexts (cf. Oliver & DeSarbo, 1988; Spreng & Mackoy, 1996; Tse & Wilton, 1988), and researchers have begun to consider the role of emotion in the model. For example, Westbrook (1987) and Oliver (1993) illustrated significant effects of both positive and negative affective responses on satisfaction in addition to a disconfirmation effect.

PERCEIVED RETAIL CROWDING AND SHOPPING SATISFACTION

Although the expectancy–disconfirmation paradigm has dominated satisfaction research, Anderson and Fornell (1994) emphasized the need to identify additional antecedents of satisfaction beyond expectations, including their relationships, possible moderators, and importance for shaping a satisfaction response. For the retailer, perceived retail crowding is an important antecedent of customer satisfaction (Eroglu & Machleit, 1990; Machleit et al., 1994). Given this premise, we work to delineate more precisely the role of several mediating and moderating factors on the relationship between shopper satisfaction and one of its antecedents, perceived retail crowding.

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thus, joy should decrease due to crowding. Furthermore, when a shopper experiences a store that is not crowded, feelings of joy may result due to the relief brought about by the added space. The other positive emotion, interest, should also decrease when crowding increases due to the shopper’s reduced ability to adequately pursue desired goals in the environment. Because interest is often related to the pursuit of goals (Izard, 1977), when shoppers’ ability to accomplish their goals is blocked by the crowded in-store environment, interest should decline. Izard (1977) named the negative emotions of anger, disgust, and contempt to be a “hostility triad” that is frequently experienced by individuals. Anger is the least subtle of the three and can be triggered by

HYPOTHESES Considering research in the areas of emotion, satisfaction, and crowding, several hypotheses are suggested. Hui and Bateson (1991) showed that perceived crowding (measured as a unidimensional construct) decreases feelings of pleasure in a service environment. We expect to replicate this finding with both dimensions of crowding in the retail environment. Furthermore, we hypothesize crowding to influence a multitude of affective responses beyond a pleasure response. This contention is based, in part, on work that posits that two dimensions of emotional response—pleasure and arousal—encompass a range of emotional reactions that can take place in an environment (Mehrabian & Russell, 1974; Russell, 1980). Literature suggests that perceived crowding can affect arousal in addition to a pleasure response; for example, dense settings are shown to increase tension and arousal (Stokols, 1972). Although an advantage of the Mehrabian and Russell two-dimensional emotion typology is its parsimony, there are other emotion typologies that may help us understand more specific emotional responses to crowding. Izard (1977), for example, in his Differential Emotions Theory, has identified 10 emotion types. These include 7 negative dimensions of emotion (sadness, anger, disgust, contempt, fear, shyness, and guilt), 2 positive emotional dimensions (joy and interest), and 1 neutral dimension (surprise). Given that we expect retail crowding to produce negative reactions from shoppers, this typology, with its extensive negative dimensions, is particularly appealing. Furthermore, this classification has been successfully used in research that investigated the relationship between emotion and satisfaction (Oliver, 1993; Westbrook, 1987). Overall, we anticipate that because crowding creates feelings of stress and weakens coping abilities, shoppers in crowded retail environments will experience decreased levels of positive emotion and increased negative emotion. Furthermore, we hypothesize specific emotional states (Izard’s 10 dimensions) to be elicited by both human and spatial crowding. Izard (1977) noted that joy will be reduced by “matters that create stress and call for discontent” (p. 240);

being either physically or psychologically restrained from doing what one intensely desires to do. Other causes of anger include personal insult, everyday frustrations (blocking or interfering with goal-oriented behavior), interruption of interest or joy, being taken advantage of, and being compelled to do something against one’s wishes. (p. 330)

As both human and spatial density can lead to restraint, frustrations, and having to move or otherwise adapt to the density (essentially against one’s desires), we anticipate that feelings of anger will result. It is also noted, however, that there are a very few stimuli or situations that evoke anger and only anger; feelings of disgust (wanting to remove or get away from the object) and feelings of contempt (which involves feelings of 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 human density and undesired interactions as well as to the discomfort arising from high spatial density of the store (Oliver, 1993). Although we anticipate the strongest effects of perceived retail crowding on the emotion types of anger, disgust, and contempt, we hypothesize that crowding may also result in other negative feelings, although to a lesser extent. Feelings of shyness (or shame) arise when attention to the self is increased, a partial reduction of interest or enjoyment occurs, and when barriers to positive emotion-evoking exploration occur (Izard, 1977). Given that high density settings are known to obstruct exploration and enjoyment (Brehm, 1966), we posit that retail crowding will be positively correlated with feelings of shyness and shame. Furthermore, contempt from the self or others can activate shyness and shame (Izard, 1977), and we anticipate that such contempt, which results from crowding, will, albeit weakly, contribute to feelings of shyness. Similarly, guilt feelings, which are closely related to shyness and shame, result from sanctions (either external or internal) due to some sort of personal misconduct or violation of social conventions (Izard, 1977; Tangney, Miller, Flicker, & Barlow, 1996). In this context, when a store is crowded, it is likely that a shopper might violate standards of conduct—for example, by cutting someone off, reaching in front of some-

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one, or moving past someone without a typical level of politeness. In addition, guilt and anger often interact in frustrating situations (Izard, 1977). We anticipate that the individual may feel, at minimum, a low level of guilt if the anger is expressed in a socially unacceptable manner. Sadness is an emotion that can result from failure (Izard, 1977). Unmet shopping objectives within a given period of time, for instance, can instigate feelings of failure and sadness. On a similar note, Tomkins’s (1963) research illustrated that sadness (or distress) can result from a continued excessive level of stimulation. The excess stimulation and blocking of goals, which are shown to be outcomes of crowding (Brehm, 1966), are, therefore, hypothesized to significantly increase feelings of sadness while shopping. The experience of fear can vary by context and by individual differences; however, fear is generally felt by an individual in the presence of something threatening (Izard, 1977). Because crowding can create feelings of insecurity (perhaps due to personal harm or an increased likelihood of having one’s possessions stolen), we hypothesize an increase in the level of fear experienced by shoppers when the store is crowded. Surprise, a neutrally valenced emotion, is a response that can arise when something unexpected is encountered (Izard, 1977). Given that the spatial layout of a store does not change often, as long as the shopper is familiar with the store, spatial crowding should not result in a surprise reaction. However, human crowding, when unexpected, could lead to feelings of surprise. In light of this discussion, it is hypothesized that H1: Perceived retail crowding should be positively correlated with negative and neutral emotions and negatively correlated with positive emotions. Specifically: a. Anger, disgust, contempt, fear, shyness, guilt, sadness, and arousal are positively correlated with perceived retail crowding. b. Pleasure and joy are negatively correlated with perceived retail crowding. c. The highest correlations will be observed for the hostility triad of emotions (anger, disgust, contempt). d. Surprise should correlate with human crowding only. Although retail crowding has been shown to reduce shopping satisfaction (Eroglu & Machleit, 1990; Machleit et al., 1994), we find it useful to retest this relationship because it constitutes the basis for the following hypotheses. However, because high levels of crowding are expected to generate negative emotions, and emotions have been shown to influence satisfaction (Oliver, 1993), it seems reasonable to suspect that emotions may mediate the relationship between crowding and shopping satisfaction. That is, the negative feelings (and decreased positive feelings) that result from crowding may be the reason that satisfaction is reduced when the retail environment is crowded. Thus, the following are posited:

H2a: Higher levels of perceived retail crowding will result in lower levels of shopper satisfaction. H2b: The relationship between perceived retail crowding and shopper satisfaction will be mediated by the emotions associated with the shopping experience. The expectancy–disconfirmation model illustrates that expectations about product and service performance that are not confirmed will influence satisfaction with the experience (Oliver, 1993; Westbrook, 1987). We extend this to the retail environment and hypothesize that shoppers who experience a level of crowding consistent with what was expected will have a high level of shopping satisfaction. Furthermore, when their expectations have been exceeded (e.g., the store is less crowded than anticipated), satisfaction will also be high. But when expectations are negatively disconfirmed (e.g., the store is more crowded than expected), satisfaction should be low (Bitner, 1992). H3: Shopper satisfaction will be higher when perceived crowding falls short of or meets crowding expectations, and lower when perceived crowding exceeds expectations. Although research on the relationship between personality traits and crowding perceptions is scant, there is evidence that an individual’s tolerance for crowding might be a potential moderator of the crowding–satisfaction relationship (Cozby, 1973; Dooley, 1974). We propose that some people may actually enjoy shopping (and even seek) crowded retail environments, whereas others might have a very low tolerance for crowds. Krohne, Hock, and Kohlmann (1992) presented a personality model of coping and noted that individuals vary habitually in their ability to tolerate both uncertainty and emotional arousal. Their suggestion of a personality characteristic of “Intolerance of Emotional Arousal” parallels our proposition that there exists a personality characteristic of Intolerance for Crowding. Thus, it seems reasonable that tolerance for crowding should moderate the influence of crowding on satisfaction. H4a: Individuals vary in their ability to tolerate human density levels. H4b: For individuals with a high tolerance for crowding, there should be little or no relationship between crowding and satisfaction; conversely, for individuals with a low tolerance for crowding, crowding will negatively affect satisfaction. Finally, the type of store may moderate the effect of crowding on satisfaction (Machleit et al., 1994). Shoppers may gauge the “value” of a discount, outlet, or wholesale club by the number of people who are shopping there. The shopper may make the attribution that if the store is not crowded, 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 behavioral and cognitive consequences of “undermanning,” a condition where participants are fewer than the number typically required to maintain a setting at an expected, optimal level. In the case of discount stores, where the number of shoppers could be considered as an integral part of the store environment and its low cost and high value positioning, too few patrons could result in the condition of perceived undermanning and potentially affect shoppers’ store evaluation and satisfaction.

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STUDY 1 Respondents Students enrolled in undergraduate and graduate marketing classes at three different (two large midwestern and one large southern) universities were asked to fill out a retrospective survey. A description of the sample and the store type is found in Table 1.

Survey Instrument H5: For discount-type stores, high levels of human crowding should not affect shopping satisfaction, whereas spatial crowding will be negatively related to satisfaction. For other store types, there will be a negative correlation between both dimensions of crowding and satisfaction.

METHOD Three studies were conducted. The first was a large field study, next was a similar field study with a smaller adult sample, and the third was a laboratory experiment. The studies are discussed sequentially next.

The cover page of the questionnaire briefly described for the respondents the purpose of the study: The researchers “… are interested in the feelings and opinions that people have while they are shopping.” Students were asked to take the survey home and fill it out after their next shopping trip (and were told that the shopping trip need not have resulted in a purchase). They were informed that there were no right or wrong answers and their responses would be anonymous. The survey asked respondents to take a few minutes to think about the shopping trip and then answer the questions. After naming the store, shopping center, or mall where they shopped, respondents were asked to answer various questions regarding that shopping trip, ordered in such a way as to realistically recon-

TABLE 1 Sample Characteristics

Sample size Age M Range Sex Male Female Store type Campus bookstore Mall Grocery store Hypermart Discount Department Off-price or outlet Wholesale club Drug store Specialty clothing Specialty shoes Specialty music Specialty books Sporting goods Stereo/Appliance/Electronic Hardware Other

Study 1

Study 2

Study 3

722

153

231

23.3 19–50

36.8 16–78

21.0 18–55

54% 46%

25% 75%

54% 46%

2.9% 32.2% 17.3% 4.4% 6.5% 11.4% 2.9% 0.1% 3.3% 5.7% 0.7% 1.0% 1.2% 1.5% 2.9% 0.5% 5.6%

0.0% 13.8% 25.7% 14.5% 9.9% 13.8% 0.7% 2.0% 2.0% 3.9% 0.7% 0.0% 1.3% 1.3% 2.0% 0.7% 7.9%

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struct the shopping experience in the respondent’s mind. Respondents were asked about their purchase behavior, purpose for the shopping trip, and past experience with the store or mall, and then asked about their perceptions of crowding, satisfaction, and outcome of the shopping trip. Next, the respondent was presented with traditional emotion measurement questions. Finally, crowding tolerance questions and demographic questions were asked. This procedure of asking respondents to recall and rate a recent shopping trip has been used in other research to evaluate recent shopping experiences (Goff, Bellenger, & Stojack, 1994; Mulhern & Padgett, 1995). Respondents have been shown to be fairly accurate in their retrospective ratings of emotions (Barrett, 1997), and they should be reasonably accurate in their recall of the details of the shopping episode, especially given that they were asked to fill out the questionnaire immediately following their next shopping trip. Furthermore, the critical incident method used in services marketing provides evidence that respondents are able to recall the details of a prior event (Bitner, Booms, & Tetreault, 1990). Therefore, we conclude that this survey-based approach, although perhaps not ideal, is an acceptable data collection method. Measures Perceived crowding was measured via the eight-item, two-dimensional Likert-type scale validated by Machleit et al. (1994). The four items in the human crowding dimension were “The store seemed very crowded to me,” “The store was a little too busy,” “There wasn’t much traffic in the store during my shopping trip” (reverse coded), “There were a lot of shoppers in the store.” The four items included in the spatial crowding dimension were “The store seemed very spacious” (reverse coded); “I felt cramped shopping in the store”; “The store had an open, airy feeling to it” (reverse coded); “The store felt confining to shoppers.” All items loaded on the expected dimensions, and the coefficient alpha reliability values for each dimension were .90 and .84 for human and spatial crowding, respectively. Satisfaction was measured with the items used by Eroglu and Machleit (1990) and Machleit et al. (1994). The 7-point agreement items were “I enjoyed shopping at the store”; “I was satisfied with my shopping experience at the store”; “Given a choice, I would probably not go back to the store” (reverse coded); “I would recommend the store to other people.” Coefficient alpha reliability for the four item summed scale was .82. Emotions were measured in two different ways: via the 10 emotion types from Izard’s (1977) differential emotions theory and via Mehrabian and Russell’s (1974) pleasure and arousal dimensions. Izard’s 10 emotion types were measured with responses to the following adjectives: happy, delighted, cheerful for the joy emotion; sad, gloomy, depressed for the sadness emotion; alert, attentive for the interest emotion; mad, angry, irritated for the anger emotion; guilty, repentant,

blameworthy for the guilt emotion; ashamed, bashful, shy for the shyness emotion; disgusted, feeling of distaste for the disgust emotion; disregard, contemptuous, scornful, defiant for the contempt emotion; astonished, surprised for the surprise emotion; and fearful, nervous for the fear emotion. Respondents were asked to indicate the extent to which they felt as described by each of the adjectives during the shopping trip. These feelings were recorded on a 5-point scale ranging from 1 (not at all) to 5 (very much so). Coefficient alpha reliability ranged from .71 to .90 for all dimensions. Pleasure and arousal were measured via Mehrabian and Russell’s (1974) semantic-differential scale that contains sets of bipolar adjectives designed to tap the two dimensions. The satisfied–unsatisfied item was removed from the pleasure dimension so that it would not inflate the relationship between pleasure and satisfaction. After deleting other inappropriate items (per a confirmatory factor analysis), the pleasure dimension included three items (happy–unhappy, pleased–annoyed, contented–melancholic) and the arousal dimension included three items (stimulated–relaxed, excited–calm, aroused–unaroused). The alpha reliabilities were .87 and .76 for the pleasure and arousal dimensions, respectively. Prior expectations of crowding were measured by asking respondents to rate expectations of human crowding on a 7-point scale anchored ranging from 7 (more shoppers than were expected) to 4 (about as many shoppers as expected) to 1 (fewer shoppers than were expected). Finally, an Intolerance for Crowding measure was developed. Four scale items were created, which reflected the domain of the construct: “I avoid crowded stores whenever possible”; “A crowded store doesn’t really bother me” (reverse coded); “If I see a store that is crowded, I won’t even go inside”; “It’s worth having to deal with a crowded store if I can save money on the things I buy” (reverse coded). Confirmatory factor analysis indicated that all four items loaded appropriately on the one-dimensional measure, and coefficient alpha was .79. Results To investigate the relationship between emotion and perceived crowding, the two crowding dimensions were correlated with each dimension included in the Izard and Mehrabian and Russell emotion typologies (Table 2). Consistent with H1, increased perceptions of crowding results in decreased positive feelings, increased negative feelings, or both. Note that both human and spatial crowding significantly affect pleasure, although the effect is stronger (z* = 2.55, p = .006)1 for spatial crowding (r = –.24) than it is for human crowding (r = –.11). Contrary to our prediction, how-

1

We use the Fisher z transformation for two Pearson rs (Neter, Wasserman, & Kutner, 1989) to test for significant directional differences between correlations.


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TABLE 2 Correlations Between Perceived Crowding and Emotion Study 1

a

Study 2b

Human Crowding

Spatial Crowding

–.11** –.07

–.24** –.08*

–.07 .02

–.16** –.17**

Mehrabian and Russell Pleasure Arousal Izard Positive dimensions Joy Interest Neutral dimension Surprise Negative dimensions Anger Disgust Contempt Shyness Guilt Sadness Fear

.08* .25** .17** .20** .10* .10* .09* .12**

–.01 .25** .26** .21** .11** .09* .17** .12**

Human Crowding

–.11 .09 .04 .17* .12 .12 .10 .01 .05 .15*

Study 3c

Spatial Crowding

–.27** –.09 –.12 .13 .16* .28** .06 .11 .11 .03

Human Crowding

Spatial Crowding

–.24** .23**

–.46** .20**

.05 –.03

–.25** –.01

.06

.04

.25** .15* .21** .08 .04 .25** .02

.36** .38** .28** .03 .11 .34** .05

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

ever, perceived human crowding does not significantly affect feelings of arousal. Furthermore, the effect of spatial crowding on arousal is negative. If we consider the scale items used to measure arousal (stimulated, excited, aroused), it could be that the items were actually tapping a state of excitement for the shopping trip rather than a state of tension (as hypothesized). Hence, if the shopper found the store to be spatially crowded, then the excitement of shopping was lessened. Correlations with the emotional responses from Izard’s typology are also presented in Table 2. Notice that only spatial crowding significantly affects the positive emotion feelings of interest and joy. As hypothesized, feelings of surprise significantly increase when the shopper experiences human crowding. Given that the respondents were highly familiar with the stores they reported about (only 3.5% had never been to the store before; 75% had been to the store 10 or more times), it is logical that spatial crowding did not result in feelings of surprise. Although crowding significantly increases all of the negative feeling states, the hostility triad of anger, disgust, and contempt (other-oriented emotions) have the strongest correlations with both human and spatial crowding. The correlations with the remaining emotions (the individual-oriented emotions), on the other hand, are not as strong. This is as expected, given that both human and spatial crowding essentially force increased interactions with others while shopping, thus producing stronger responses to the other-oriented emotions. Consistent with findings from previous research, higher levels of crowding are associated with lower levels of satisfaction (supporting H2a). Both human crowding and spatial

crowding are significantly negatively correlated with satisfaction (r = –.16, p < .01; r = –.36, p < .01, respectively; n = 725). Next, with respect to the mediational effect of emotions on the crowding–satisfaction link (H2b), we find that emotions only partially mediate the relationship (Baron & Kenny, 1986). When the pleasure and arousal dimensions of emotion are included as mediators, the human crowding–satisfaction relationship drops in magnitude (from –.16 to –.08), but still remains significant (p = .015). For spatial crowding, the relationship also significantly decreases in strength (from –.36 to –.23), but is still highly significant (p = .000). When the Izard emotions are used, the results are nearly the same: human crowding–satisfaction relationship significantly drops in magnitude (to –.07), but remains significant (p = .03); for spatial crowding, the relationship again decreases (to –.23) and is still highly significant (p < .001). We conclude, therefore, that emotions only partially mediate the effect of crowding on satisfaction and that there exists some direct effect of crowding, beyond the emotional reactions it evokes, that leads to changes in satisfaction levels. To test the extent to which crowding expectations relate to satisfaction (H3), respondents were coded into three expectation groups (“There were about as many shoppers as I expected,” “There were fewer shoppers than I expected,” “There were more shoppers than I expected”). The data indicate that not only are shoppers most satisfied (M = 5.55, where 7 is highest; n = 548) when their expectations are met, but they are equally satisfied (M = 5.47, n = 128) when the store is less crowded than they had expected. Conversely, shoppers’ satisfaction levels (M = 5.01, n = 62) are significantly lower, F(2,

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735) = 6.54, p = .002, when there were more shoppers than they had anticipated. Thus, H3 is supported. As proposed in H4a, we find that respondents do indeed vary in their tolerance for crowding. Scores on the four-item, 7-point measure covered the entire possible range (from 4 to 28) with a mean of 15.96, median and mode of 16, and a standard deviation of 5.46. On an exploratory basis, we also investigated the potential impact of sex on tolerance for crowding. Previous studies on the impact of sex on crowding have been insignificant or inconclusive at best. Although female respondents are found to report higher mean tolerance levels than male respondents, the difference here was not significant. As proposed in H4b, the perceived crowding–satisfaction relationship appears to be moderated by tolerance for crowding. Among those who report a low level of tolerance for crowding (n = 158), both human and spatial crowding are negatively correlated with satisfaction (r = –.16, p < .05; r = –.37, p < .01, respectively). Conversely, among those who report a high tolerance for crowding (n = 180), only spatial crowding is negatively correlated with satisfaction (human crowding–satisfaction r = .02, ns; spatial crowding–satisfaction r = –.30, p < .01). The z transformation shows a significant moderating effect for human crowding (z* = 1.648, p = .05); thus, H4 is supported. H5 suggests that the type of store should moderate the crowding perceptions–satisfaction relationship for the human crowding dimension only. Specifically, for the stores where shoppers may gauge value by the number of people shopping 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 significantly negatively correlated with satisfaction (r = –.40, p < .01, n = 99). For all other stores, satisfaction is significantly related to both human and spatial crowding (r = –.15, p < .01, n = 630; r = –.33, p < .01, n = 630, respectively). We should note, however, that whereas the correlation between human crowding and satisfaction is nonsignificant in the discount store category (as hypothesized), the correlation is nearly the same in magnitude for both store type categories and is not significantly different using the z transformation (z* = .09, ns). Thus, we cannot fully endorse H5. Finally, we explored several other potential moderators of the crowding–satisfaction relationship, such as sex, store familiarity, time pressure, and whether a purchase was made during the shopping trip (Eroglu & Harrell, 1986). Findings indicate that of these suggested moderators, none of them appeared to moderate the effects of perceived crowding on satisfaction.

STUDY 2 Because we were concerned that student respondents may differ in their responses to shopping relative to a more diverse adult audience, Study 2 was conducted as a replication of

Study 1 using nonstudent respondents. Respondents were recruited from a suburban parenting and social group, from two different day care facilities, and from a private elementary school, and they were asked to participate in the study as part of a fund-raising activity. The organizations received $2 for each completed questionnaire; staff and parents completed questionnaires and recruited people they knew to participate as well. All respondents were instructed to take the task seriously. Because respondent fatigue was a concern with this nonstudent sample, the Mehrabian and Russell measure was not included on the questionnaire. A description of the sample is included in Table 1. Coefficient alpha levels were acceptable for all measures. H1 is supported with this data set. Table 2 shows that as perceived crowding increases, feelings of positive emotional feelings decreases and negative feelings increases (particularly the hostility triad). Interestingly, human crowding correlates with feelings of anger and fear, whereas perceived spatial crowding correlates with disgust and contempt. It is also interesting to note, however, that overall the correlations are not as strong as those we observed in Study 1. We speculate that this outcome could be due to one of several factors. First, because of the smaller sample in Study 2, sampling error may be obscuring the true correlations. Another viable explanation is that more of the Study 2 respondents reported their experiences shopping at a grocery store compared to more mall shoppers in Study 1. We would expect that mall shoppers, due to more and varied environmental and merchandise stimulation, would experience a more diverse set of feelings than grocery store shoppers. A third explanation is that when comparing the levels of perceived crowding experienced across the two samples, Study 1 shoppers experienced higher levels of perceived human and spatial crowding compared to the Study 2 shoppers (for Study 1, mean levels of human and spatial crowding were 3.60 and 3.32, respectively; for Study 2, they were only 2.47 and 2.26). Because perceived crowding was not as high for the Study 2 shoppers, they may not have experienced the same variety of emotions due to the higher crowding levels experienced by Study 1 shoppers. H2a is supported with the Study 2 data. Again, both human and spatial crowding significantly decrease shopping satisfaction (r = –.223, p < .01; r = –.32, p < .01). Furthermore, the emotion measures completely mediate the effect of human crowding on satisfaction (H2b); the coefficient drops to –.09 and is nonsignificant (p = .24). For spatial crowding, partial mediation 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 supported with the Study 2 data. Although the mean satisfaction values are as anticipated, there are no significant differences, F(2, 107) = .847, p = .43, in shopping satisfaction for the three expectation groups. When expectations were confirmed (“There were about as many shoppers as I expected”), the mean satisfaction value (5 is highest) was 4.12 (n = 81). When the store is less crowded than the shopper expected, satisfac-


tion is 3.99 (n = 19); when there are more shoppers than anticipated, the satisfaction level is lowest (3.83, n = 10). Note, however, that the group sizes (n = 19 and n = 10) for the disconfirmed expectation groups are small, and statistical power may be an issue.2 Low group sizes not withstanding, the effect could be the result of other factors. Recall that for the Study 2 sample, perceived crowding levels were low. Although some shoppers experienced an environment that contained greater human density than expected, perceptions of crowding were not at a high level overall. This restricted range may also be the reason for the lack of support for H3. H4a is supported; respondents vary on their ability to tolerate crowding as they report tolerance for crowding levels across all points on the scale. Again, consistent with the Study 1 data, there is no significant difference in tolerance levels for men versus women. H4b, that the perceived crowding–satisfaction relationship is moderated by tolerance for crowding, is again supported. For those who report a low tolerance for crowding, crowding correlates with shopping satisfaction (r = –.40, p < .01; r = –.45, p < .01, n = 47, for human and spatial crowding, respectively). Only spatial crowding correlates with 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 tolerance individuals 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 the crowding–satisfaction relationship such that human crowding should not affect shopping satisfaction for discount store types. We interpreted the Study 1 results cautiously because the magnitude of the human crowding correlation, even though nonsignificant for the discount store types, was nearly the same for the two store-type groups. We find the same pattern with the Study 2 data. For discount-type stores, human crowding is not significantly related to satisfaction (r = –.24, ns, n = 38), but spatial crowding is significantly correlated with satisfaction (r = –.42, p < .01, n = 38). For all other stores, both human and spatial crowding significantly affect shopping 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–satisfaction relationship is nearly the same in magnitude for the two groups, even though, as hypothesized, it is nonsignificant in the discount store group. But again, the z transformation indicates that there are no significant differences between the correlations in the discount versus other stores for human (z* = .05, ns) and spatial crowding perceptions (z* = .76, ns).

2

The 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 error. This low power is driven by a combination of low effect size f = .124 (Cohen, 1977) and extremely low base sizes in two of the cells (n = 19 and n = 10). Even if we were expecting a medium effect size similar to the effect found in Study 1 (f = .25), we would need between 32 and 44 participants per cell to have an acceptable level of power.

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Finally, as in Study 1, we explored other potential moderators of the crowding–satisfaction relationship. Sex, time pressure, and whether a purchase was made were examined as moderators in Study 2. Recall that when considering these variables in Study 1, none of them emerged as significant moderators. For Study 2, however, we found that time pressure significantly moderates the crowding–satisfaction relationship. There was a significant moderating effect of time pressure (z* = 2.16, p = .02) for human crowding; human crowding significantly affects shopping satisfaction for those under high time pressure (r = –.53, p < .001), but not for those under low time pressure (r = .07, p = .63). Given that time pressure is shown to exacerbate perceptions of crowding (Eroglu & Machleit, 1990), it is not surprising that there is such a strong correlation between crowding and satisfaction for those under higher time pressure. Furthermore, looking at correlations between crowding and satisfaction by sex shows a pattern of moderating effects, although the differences were not significant using a two-tailed z transformation test.3 For male respondents (n = 37), human crowding does not significantly affect shopping satisfaction (r = –.01, p = .95), whereas spatial crowding does (r = –.35, p = 03). For female respondents (n = 107), both dimensions of crowding affect shopping satisfaction (r = –.28, p = .00 for human crowding and r = –.32, p < .001 for spatial crowding). This moderating effect, however, is not borne out by the z transformation: human crowding dimension (z* = 1.48 , p = .14); spatial crowding dimension (z* = .40, p = .69).

STUDY 3 As Studies 1 and 2 are field studies, they have the advantage of external and ecological validity. Respondents reported their shopping experience as it naturally occurred across a wide range of retail contexts. However, there are also some inherent limitations. First, the data are correlational in nature based on a retrospective report by the respondents. As such, many elements that have been suggested to affect crowding perceptions (Eroglu & Harrell, 1986) are not controlled, and the causal nature of the relationship is unclear. Second, because respondents reported a self-selected shopping experience, self-selection bias could color the results. To overcome these limitations, a laboratory experiment was designed to replicate and extend the field work. Using videotapes of a retail setting, we can control the absolute number of shoppers in the store, the amount of merchandise visible, and the placement of the merchandise. The store type and shopping criterion are controlled using a realistic scenario coupled with one of four videotaped “stores.” In this way, the temporal order of

3

As prior research shows mixed effects regarding sex and crowding (Stockdale, 1978), we could not pose a directional prediction.

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events can be controlled, and self-selection of shopping situation can be eliminated. The four videotapes manipulated both human and spatial density (higher vs. lower human density and higher vs. lower spatial density). A professional videographer filmed a scene from a campus bookstore (approximate size of 45 × 60 ft). The scene included an aisle in the center that led to a circular checkout desk with three cash registers (only one cash register was open at this time). On both sides of the aisle and behind the checkout area (where there was about 20–25 ft of retail space) were bookracks and shelves. There was nothing in the scene to indicate that this was a campus bookstore. Human density was varied by controlling the number of shoppers in the scene. Spatial density was varied by moving some of the 3-ft-high bookracks into the aisle area rather than having them on the side; shoppers then had to weave in and out of the bookracks to reach the checkout area. All tapes had the same bookracks in the scene; they were simply positioned differently in the space to represent differences in spatial density. A pretest indicated that the higher versus lower human and spatial density levels were successfully manipulated. Overall multivariate analysis of variance and univariate analysis of variance tests show that the spatial density effects on variables related to the amount of space and arrangement of merchandise in the store were significant; similarly, the human density effect on statements about the number of people in 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 from the field studies. Because respondents in the first two studies were able to choose the store type, self-selection bias was clearly at issue in testing H5; therefore, the experiment was set up to further investigate the store-type moderation hypothesis. Thus, store type (discount vs. upscale bookstore) was manipulated via the scenario. Participants were told the following:

There were 231 student participants processed in large groups. They were given the scenario to read and then they watched the 55 second videotape on a large screen. Manipulation checks indicated that the store-type manipulation was successful; respondents indicated that they expected the store to have inexpensive (expensive) books and books priced lower (higher) than the competition for the discount (upscale) store type (p < .000). Note that density, not perceived crowding, was manipulated with the videotapes. Density is an objective measure of the number of people and the amount and placement of the merchandise, whereas perceptions of crowding are individual in nature. Because density is a precursor to crowding perceptions, we examined the effects of the manipulations (i.e., human density, spatial density, and store type) on perceived retail crowding (both human and spatial). As expected, there were no main or interactive effects of store type on either human or spatial crowding perceptions. The effects of the two density manipulations on perceived human and spatial crowding are also in the expected direction and shown in Figure 1. For human crowding, there is a significant main effect of human density (p < .001), a nonsignificant main effect of spatial 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

Now I will read to you the description of a shopping situation that also appears below. Please read it silently while I read aloud and try to imagine yourself in the described situation. It is very important that you put yourself in the context that is being described: You are now in a discount [upscale] bookstore (such as Half-Priced Books [Barnes and Noble]). You are trying to find a book that you previously have had trouble locating. This book is critical because it was suggested to you that it would be helpful in your job search strategy. Next week is the only stretch of time that you can devote to reading the book, so you would like to find it soon. Now please watch the video and imagine yourself shopping for the book in this discount [upscale] bookstore.

FIGURE 1 Mean perceived crowding levels by density manipulations.


space to move about), this adds to the perceptions of human crowding (i.e., shoppers experience greater feelings of human crowding). For spatial crowding perceptions, there are significant main 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 spatial crowding were lower when human density was lower. Furthermore, both types of density seem to affect both types of crowding perceptions (either via a main or an interactive effect). This is an interesting finding because, to our knowledge, prior work has not been able to isolate the relationship between the crowding dimensions and density to this extent. We now test the hypothesized relationships with this new experimental data. Recall that H1 posits that higher levels of crowding will result in decreased positive feelings and increased negative feelings. The correlations between human and spatial crowding and the emotion measures are included in Table 2. Overall, these correlations are quite similar to what was found in the field studies, especially given that a simulated shopping episode would be expected to produce weaker feelings than what would be experienced in a real shopping trip. Of particular note is that some of the highest correlations are found for Izard’s hostility triad of anger, disgust, and contempt. Perceptions of both human and spatial crowding seem to evoke these negative feelings in shoppers. Furthermore, both human and spatial crowding decrease feelings of pleasure while shopping, with spatial crowding having the strongest effect (–.46). Given that the rest of the hypotheses are related to moderating and mediating factors of the relationship between perceived crowding and shopping satisfaction, correlations of perceived human and spatial crowding with shopping satisfaction are examined (paralleling Study 1). Consistent with Studies 1 and 2, both human and spatial crowding result in lower 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 partially mediate the effect of both human and spatial crowding perceptions on satisfaction (H2b). When the pleasure and arousal dimensions of emotion are used, the results resemble Study 2: The human crowding–satisfaction relationship drops in magnitude (from –.18 to –.02) and becomes nonsignificant. For spatial crowding the relationship also drops (from –.56 to –.32), but is still highly significant (p < .001). When the Izard emotions are used, the results are consistent with Study 1: Human crowding–satisfaction relationship drops (to –.12), but remains significant (p = .034), and spatial crowding–satisfaction drops to –.41, but also remains significant (p < .001). Thus, given the results from these three data sets, we can feel confident in our conclusion that emotions only partially mediate the effect of crowding on shopping satisfaction. Therefore, there exists either a direct effect of crowding or some other mediating effect beyond the emotional responses evoked by crowding that leads to changes in shopper satisfaction.

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The lab study was not designed to test H3. H3 involved shoppers’ expectations of crowding before coming to the store; given that the shopping episode in Study 2 was a simulated one, the participants could not have had expectations about the shopping event prior to the study. H4 posits that the perceived crowding–satisfaction relationship will be moderated by personal tolerance levels for crowding. Again, consistent with Studies 1 and 2, for those who report a low level of tolerance for crowding (n = 126), both human and spatial crowding are negatively correlated with satisfaction (r = –.29, p < .01; r = –.59, p < .01, respectively), whereas for those who report a high tolerance level (n = 105), only spatial crowding is negatively correlated with satisfaction (human crowding–satisfaction r = –.04, ns; spatial crowding–satisfaction r = –.52, p < .01). The human crowding correlations are significantly different for the two groups (z* = 1.93, p = .026), therefore, H4 is supported with all three data sets. Also, consistent with Studies 1 and 2, women reported higher mean tolerance for crowding levels than men, but the difference again was not significant. H5 examines the moderating effect of store type on the crowding–satisfaction relationship. Specifically, it was hypothesized that for discount-type stores, human crowding should not be significantly related to shopping satisfaction. Recall that H5 was supported in Studies 1 and 2, but because the correlations between human crowding–satisfaction in both store types were nearly the same in magnitude (although nonsignificant, as hypothesized, for the discount store), we interpreted the findings cautiously. In Study 3, however, we find almost the opposite of what we hypothesize. In the discount store condition, contrary to predictions, human crowding is significantly correlated with satisfaction (r = –.21, p = .022) as is spatial crowding (r = –.48, p < .01). For the upscale store condition, we find that human crowding is not significantly correlated with shopping satisfaction (r = –.15, p = .101) and spatial crowding is significantly correlated (r = –.62, p < .001). Neither the human crowding (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 the crowding–satisfaction correlations by store type and also across the density conditions; Table 3 shows the correlations for each cell. Notice that, as hypothesized, spatial crowding affects shopping satisfaction across all cells for both store types. Also, the human crowding–satisfaction relationship is nonsignificant for the discount store (as hypothesized) in all but one cell: the high spatial, high human density cell. Recall that there was an interaction effect of human and spatial density on human crowding perceptions, with the highest human crowding level for this particular cell. It could be that we are observing a ceiling effect where, even if it is a discount store and the level of human density is such that it suggests value, there is a point where the environment gets too crowded and satisfaction levels are affected. Similarly, there may also be a floor effect. For example, in the low human density condi-

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MACHLEIT, EROGLU, MANTEL TABLE 3 Study 3 Correlations Between Crowding and Satisfaction by Experimental Cells Discount Store Density Condition Low spatial, high human density High spatial, high human density High spatial, low human density Low spatial, low human density

Upscale Store

Human Cr.

Spatial Cr.

Human Cr.

–.354 –.535** .204 –.152

–.554** –.462* –.586** –.334*

–.526** –.437* –.092 –.263

Spatial Cr. –.693** –.501* –.771** –.551**

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

tions for the upscale store, we see that perceptions of human crowding do not significantly affect shopping satisfaction. For these low density situations, some other factors appear to be driving satisfaction. Studies 1 and 2 examined other moderating variables on an exploratory basis; because Study 3 is an experiment and the shopping intentions and context are controlled, the only additional variable to explore is sex. Recall that Study 1 showed no moderating effects of sex, whereas Study 2 showed a pattern of moderating effects that were not significant. Consistent with Study 2, the Study 3 data show that both dimensions of crowding affect shopping satisfaction for female respondents (r = –.32, p = .00, human crowding; r = –.65, p = .00, spatial crowding), but for male respondents, only spatial crowding affects satisfaction (r = –.09, p = .32, human crowding; r = –.48, p = .00, spatial crowding). At a .10 level, male and female shoppers are significantly different for both human (z* = 1.80, p = .08, two-tailed test) and spatial (z* = 1.89, p = .06, two-tailed test) crowding correlations with satisfaction. Thus, our findings are in keeping with previous studies on the relationship between crowding and sex differences, which have shown inconsistent and mixed results (see Stockdale, 1978, for a review).

DISCUSSION Overall, the results from three studies indicate that the effect of retail crowding on shopping satisfaction is not a simple, direct one. A crowded store may or may not result in decreased satisfaction; this effect depends on a number of different individual and situational factors. The results of two field studies indicate that although emotions partially mediate the crowding–satisfaction relationship, the decrease in shopping satisfaction due to crowding is mediated by expectations of and tolerance for crowding. A laboratory experiment that replicated the field studies showed that the relationship between perceived crowding and store satisfaction also appears to vary by store type, albeit with the existence of a “floor and ceiling” effect. To place our findings and conclusions in proper perspective, however, it is important to note the limitations of

the study. Although some of these were addressed by undertaking multiple studies, the others can suggest directions for future research. For example, given the potential differences in reactions to crowding between younger and older shoppers, Study 2 was conducted as a replication of the first study. Similarly, Study 3 was conducted to address the limitations of the two field studies that produced correlational data and are based on a retrospective report of a self-selected shopping experience. Another limitation concerns the ecological validity of the videotaped density manipulations used to create various levels of store crowding. The extent to which respondents can successfully imagine themselves in the described store environment is likely to affect their responses. A number of future research avenues emerge from these findings. First, the stronger negative effects of spatial crowding relative to human crowding in all three studies deserves special attention given the potential theoretical and practical implications of this finding. In Study 1 particularly, spatial crowding was found to heighten all of the negative emotions while reducing all of the positive emotions and shopper satisfaction. These effects were stronger than those created by human crowding for almost every emotion dimension. These results are consistent with Saegert’s (1973) work, which showed that individuals react differently to changes in group size (i.e., human density) than to changes in spatial features. Although a higher number of people may heighten complexity and total stimulation, it may also imply a potential for change in crowding perceptions because people are likely to move in time, thereby altering density perceptions within the given space. Conversely, a reduction in available space due to nonhuman elements can be seen as being less flexible and more permanent, at least in the limited time period allotted to shopping. In the context of a store that is not spatially crowded but densely populated with shoppers, the potential for movement and alteration of the crowding levels might, to a certain extent, help diffuse some of the negative retail crowding outcomes. On the contrary, if the store were crowded on the space dimension (say, due to excessive merchandise, narrow aisles, overflowing racks), shoppers might have felt that they had less opportunity to change the environment. Interestingly, our data show that even among those who


have a high tolerance for crowding, spatial crowding still correlates negatively with shopper satisfaction. The relationship between these two crowding dimensions as well as their individual and combined effects on various shopping strategies and outcomes are topics that require further attention given their significant theoretical and managerial implications. The role of attributions in determining the crowding–satisfaction relationship is another potential future research area emerging from this study. For example, it may be that when a store has a large number of people, shoppers may not hold this against the retailer in making a satisfaction judgment. On one hand, shoppers might reason that it is not the retailer’s fault that a lot of people decided to shop today. On the other hand, they might think that the retailer should have anticipated the crowds and done something about it. Conversely, if the shopper thinks that the retailer really has made an effort to account for the increased number of shoppers (e.g., by adding more checkout lines at a grocery store), then human crowding should not significantly affect satisfaction. If this is the case, then it would be important to examine the attributions that shoppers make about reasons for and management’s dealing with the crowding issue and how these attributions moderate the crowding–satisfaction relationship. Another area of further investigation concerns the role of store type as a moderator of the impact of crowding on satisfaction. Specifically, for discount-type stores, where shoppers may gauge value by the number of patrons in the store, human crowding was not significantly related to shopping satisfaction. Yet, this was not true for nondiscount stores. One possible explanation can be found in Barker’s (1963) Manning Theory and its implications on store staffing and customer–staff interaction policies. In addition, the possibility of observing different ceiling and floor effects across different store types should be examined more carefully, as these findings might yield important store atmosphere and customer routing suggestions for retail managers. In conclusion, we have made progress in understanding the boundary conditions for the perceived crowding–satisfaction relationship. Given our existing knowledge about the impact of retail crowding on various aspects of shopping behavior and outcomes, it would seem appropriate to also start focusing attention on how shoppers respond to retailer strategies designed to alleviate the negative consequences of crowding.

ACKNOWLEDGMENTS This study was supported, in part, by a University of Cincinnati College of Business Administration Summer Faculty Research Fellowship and a University of Toledo Information Systems and Operations Management Department Academic Challenge Grant. We thank Paul Herr and three anonymous reviewers for their helpful suggestions.

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Accepted by Paul Herr.