Cross-cultural differences in crowd assessment

Journal of Business Research 60 (2007) 269 – 276

Cross-cultural differences in crowd assessment ☆ Frank Pons a,⁎, Michel Laroche b a

Université Laval, Faculté des Sciences de l'Administration, Québec, Canada G1K 7P4 b Concordia University, Montréal, Canada

Received 1 March 2006; received in revised form 1 September 2006; accepted 1 October 2006

Abstract This article clarifies how consumers deal with crowded service settings and, in particular, how density expectations impact this process. The article describes the key moderating role of culture in the density–dissatisfaction relationship by comparing consumers' reactions to crowd in two different countries (Canada and Mexico). Results suggest that expectations (through disconfirmation) play only a major role in the Canadian consumers' evaluation of crowded settings. The article provides potential explanations and managerial implications. © 2006 Published by Elsevier Inc. Keywords: Services marketing; Crowding; Culture; Expectations; Density; Dissatisfaction

1. Introduction Sociology and environmental psychology describe social and psychological reactions to crowds (e.g., Altman, 1975; Rapoport, 1976; Stokols, 1972; Stott and Drury, 2000). However, marketing provides a few studies on such individuals reactions to crowds (e.g., Eroglu and Harrell, 1986; Eroglu and Machleit, 1990; Harrell et al., 1980; Machleit et al., 2000 [include all authors in first call]) despite the fact that crowding represents an important environmental factor in consumers' evaluations of the retail experience. The literature documents well the stress induced by dense shopping situations and its negative influence on consumer's satisfaction (Eroglu and Machleit, 1990; Machleit et al., 1994) but the literature does not describe the process leading to this dissatisfaction. If marketers want to ease consumers' reactions to crowds, understanding whether consumers have an emotional/affective reaction to crowded retailers or if they process

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This article follows from the first author's doctoral dissertation under the supervision of the second author. The authors gratefully acknowledge the financial support of the John Molson School of Business (Concordia University) and the Fonds de recherche sur la société et la culture (Government of Quebec). ⁎ Corresponding author. Tel.: +1 619 260 4869; fax: +1 619 260 4891. E-mail address: [email protected] (F. Pons). 0148-2963/$ - see front matter © 2006 Published by Elsevier Inc. doi:10.1016/j.jbusres.2006.10.017

crowded situations in a more cognitive manner is important. This question embeds in the broader debate on the roles of cognition and emotion in forming satisfaction (Oliver, 1997). This article aims particularly at clarifying the role of density expectations (cognitive process) in forming dissatisfaction with a crowded retailer. Previous research introduces several variables as potential moderators of the density–satisfaction relationship. Unravelling the role of moderators of this complex relationship is presented as critical to the research on crowding (see Machleit et al., 2000). However, despite the fact culture is identified in environmental psychology (Westin, 1970; Evans et al., 2000; Sinha and Nayyar, 2000) as having strong influence on individuals' reactions to crowding, culture is ignored in the retail context. Moreover, growing cross-cultural interactions during service encounters and the globalization of services call for a better understanding of how culture impacts the way crowded settings are perceived and evaluated (Jamal, 2003). Therefore, the present study has two main objectives. First, it aims to clarify the way consumers process crowded settings and to examine how density expectations impact this process. Second, the key role of culture as a moderator of the density– dissatisfaction relationship is described by comparing consumers' reactions to crowd in two different countries (Canada and Mexico).

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2. Literature review 2.1. Crowd issues: definitions Most of the studies dealing with crowds in a retail (service) environment insist on the importance to understand the difference between density and crowding (Harrell et al., 1980; Eroglu and Harrell, 1986, Eroglu and Machleit, 1990): Density alone does not produce adaptation behaviours. Only when it produces perceived crowding do shoppers act. Perhaps, then, environmental designs can be created which provide for increased density but lessen the feeling of being crowded (Harrell et al., 1980). Using a psychological approach, Rapoport (1976) also emphasizes the importance of density and how it differs from perceived crowding. He considers that there is a missing link between “the physicalist features of density and psychologically negative states of crowding”. In addition, his definition of density goes beyond this simplistic number of people per unit (Stokols, 1972) with the inclusion of psychological and social factors. He argues that perceived density is the key concept in the study of dense environments and their consequences for individuals as crowding represents the negative affective evaluation of a given perceived density level: The difference is the following. Density is the perception and estimate of the number of people present in a given area, the space available, and its organization, whereas crowding or isolation (which we could call affective density) is the evaluation or judgment of that perceived density (Rapoport, 1976). Several other researchers (Eroglu and Harrell, 1986; Rustemli, 1993) support this conceptual definition of crowding as a negative affective evaluation of a dense situation. 2.2. Density and shopping satisfaction: what relationship? The focus in the majority of the retail crowding research lies in the density–satisfaction relationship (Harrell et al., 1980; Eroglu and Harrell, 1986; Eroglu and Machleit, 1990). In particular, the main debate deals with the way density bridges to crowding and how cognition, perception and affective issues are involved (Baum and Epstein, 1978; Downs and Stea, 1973). Previous studies consensually define perceived density as an antecedent to the affective reaction that consumers have in dense environment (Eroglu and Harrell, 1986). Therefore, this affective evaluation plays a mediating role in the density– satisfaction (route 1 in Fig. 1). Along with Eroglu and Harrell's (1986) conceptualization, an additional density–satisfaction relationship is often mentioned in environmental psychology studies (Choi et al., 1976) but neglected in marketing studies on crowding. In this alternative conceptualization, the perceived density is used as a signal to directly trigger dissatisfaction (route 2 in Fig. 1). This relationship presents some similarities with findings in the servicescapes' literature, in which environmental cues, such as

Fig. 1. Density–satisfaction relationship.

design or atmosphere, are used as heuristics by consumers to assess their satisfaction/dissatisfaction with the service experience (Bitner, 1992; Wakefield and Blodgett, 1994; Chang, 2000). This study proposes to evaluate both the direct and indirect influence of perceived density on satisfaction as underlined in Fig. 1. 2.3. The key role of expectations Expectations represent a key concept in the research on satisfaction (Oliver, 1997; Zeithaml et al., 1993) but they have been neglected in the retail crowding literature (Machleit et al., 2000). Expectations are anticipations of future consequences (Taylor, 1994) or comparison standards (Oliver, 1997) that are confirmed/disconfirmed by the product/service delivery. The use of these comparative standards in the assessment of satisfaction is widely spread in marketing literature and the pertinence of the expectancy–disconfirmation approach is supported by several studies (Yi, 1990; Tse et al., 1990; Erevelles and Leavitt, 1992). In the expectancy model, the confirmation/disconfirmation variable is usually the driver for satisfaction but there are several variations of the expectancy– disconfirmation model. In most of the cases, the debate revolves around potential effects of confirmation/disconfirmation or performance on satisfaction (Oliver, 1997). In their extended model of retail crowding, Eroglu and Harrell (1986) give a limited role to the density expected by consumers prior to their encounter with the dense situation. The authors only consider the anticipation of future high-density conditions as one of several cues or information that may affect consumers' interactions with the situation. On the contrary, Rapoport (1976) and Altman (1975) insist on the central role that expectations, or standards of comparison, have in the evaluation or the assessment of dense conditions. Indeed, they present a very social–cognitive approach to the notion of density and its influence. Their work never estimates perceived density in an absolute manner but rather assesses perceived density by a comparison with a desired or expected level of density, requiring a consequent cognitive effort from the individual. The resulting discrepancy (gap) between the perceived and the expected density is then affectively evaluated by the individual (in a positive manner for crowd enjoyment or in a negative manner for crowding) (Heimstra and McFarling, 1978). Since then, the

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2.4. The moderating role of culture

Fig. 2. The revisited density–satisfaction relationship.

central role of expectations in crowd assessment has been well documented in several sociological and psychological studies (Webb and Worchel, 1993; Ford, 2001; Martin, 1996). These studies demonstrate that one's expectations about crowded or highly dense environments may influence outcomes for the individual in subsequent high-density situations. For instance, it is demonstrated that, in their primary setting (home), older people do not experience high density as negatively as other members of the family, because such a level of interactions is expected (Sinha and Nayyar, 2000). This position tends to support the importance of expectations in the consumers' evaluations of dense settings. This calls for the application of an expectancy–disconfirmation approach to conceptualize the density–satisfaction relationship (Webb and Worchel, 1993; Ford, 2001; Martin, 1996). Therefore, we can posit the following hypotheses (Fig. 2), with two potential routes leading to satisfaction, one more cognitive, in which expectations play a key role, and one more affective, where perceptions only influence the reactions of the consumer. Hypothesis 1a. In a service setting, the perceived density encountered during the experience has a significant and direct influence on the level of satisfaction of the customer with the service experience. Hypothesis 1b. In a service setting, the disconfirmation (gap) between perceived and expected density has a significant and direct influence on the level of satisfaction of the customer with the service experience. Hypothesis 2a. In a service setting, the perceived density encountered during the experience has a significant and direct influence on the affective evaluation of the level of density encountered during the experience. Hypothesis 2b. In a service setting, the disconfirmation (gap) between perceived and expected density has a significant and direct influence on the affective evaluation of the level of density encountered during the experience. Hypothesis 3. In a service setting, the affective evaluation of the level of density encountered during the experience has a positive influence on the satisfaction with the experience.

Extensive research reports on the impact of culture on privacy issues (Mexican context with Lewis, 1961; English homes with Kuper, 1953; Samoan lifestyle with Westin, 1970; Elderly in India with Sinha and Nayyar, 2000) and personal space (Arabic, Latin American and Middle Eastern with Hall, 1966 and Baxter, 1970). In all cases, cultural differences in spatial distancing influences the use of space and the socialinteraction style (Hall, 1966; Heimstra and McFarling, 1978). For instance, Arabic, Mediterranean and Latin American cultures tend to exhibit smaller distancing and higher levels of contact than their Northern European and Caucasian North American counterparts (Altman and Vinsel, 1977; Baxter, 1970). These findings can be explained by two theoretical accounts. These accounts are based on differences between high and low context cultures and differences between collectivistic and individualistic cultures. According to the proxemic account, high context cultures prefer closer interpersonal distances and more interactions than low context cultures. Alternatively, the collectivism–individualism perspective views individuals from a collectivistic culture as more eager to create connections with their peers. They are more likely to seize opportunities that allow for proximate social interactions than individuals from individualistic cultures (Evans et al., 2000). The North American culture is often depicted as the archetypal individualistic and low context culture (Altman, 1975; Evans et al., 2000; Markus and Kitayama, 1991; Park, 1998). In contrast, the Latin culture is often described as a high context culture that promotes collectivistic strivings (Lewis, 1961; Hall, 1966). Therefore, expecting differences in reactions to density between Canada and Mexico is reasonable. Through socialization and enculturation, cultural groups may define their own norms and ranges of acceptance for density. Evans et al. (2000), for instance, found that measures of perceived density in crowded situations were often lower in high context cultures (e.g. Latin American culture) than in low context cultures (e.g. North American culture). Similarly, we expect consumers from Mexico (high context) to perceive the same setting as being denser than would consumers from Canada (low context). Moreover, recent studies highlight additional cultural differences pertaining to satisfaction and service quality measurement (Ueltschy et al., 2004; Laroche et al., 2004) as well as information processing (Laroche et al., 2002). In particular, Laroche et al. (2002) support the idea of different information processing routes depending on the culture considered. These results are context dependent but generally, it appears that Latin cultures usually prefer a more affective route, whereas North Americans adopt a more cognitive route to process information. In sum, culture is expected to influence the perception of density in addition to moderating the relationship between perceived density and consumers' evaluations of the service setting. Hypothesis 4. Mexican respondents' perceive lower levels of density than their Canadian counterparts in a highly dense situation.

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Hypothesis 5. Culture moderates the relationship between perceived density and satisfaction. 3. Method 3.1. Research design and sample One of the research objectives is to investigate the influence of culture on consumers' reactions to a crowded retail environment. Building on previous work (Hall, 1966; Sanders et al., 1985), the level of analysis adopted in this manuscript is cross-cultural. However, as in previous studies (e.g., Kim et al., 1990), we use “countries” (Mexico and Canada) as a proxy for culture. We recognize that intra-country differences exist, but we remain confident that inter-country differences will account for the greater part of variation in reactions to crowd (Buda and Elsayed-Elkhouly, 1998; Harcar and Karakaya, 2005; Reynolds et al., 2003; Samiee and Jeong, 1994). Additionally, we have attempted to minimize demographic differences between the two samples in order to enhance the validity of the crosscultural findings. The groups interviewed in each culture are similar in regards to basic demographic variables (age, living in an urban setting). In addition to the cultural variable, the perceived and expected density levels are also manipulated independently to ensure enough variance in the independent variables. In short, a 2 (Mexican versus Canadian) × 2 (high perceived density versus low perceived density) × 2 (high expected density versus low expected density) factorial design is used in this experiment. Therefore, the groups in each culture are necessary to implement the experimental design planned. Introductory business courses, with at least forty-five students registered, were randomly selected to be part of the study. The final sample includes 861 Canadian undergraduates and 862 Mexican undergraduates. The Canadian sample is drawn from an English-speaking university in Montreal. All the participants are Canadian citizens and under 30 years old. 46.9% are men and 53.1% are women. The Mexican sample includes only Mexican citizens and is drawn from a university in Puebla. All the participants are under 30 years old and 52% are men (48% of women). Written scenarios and video stimuli are used to respectively operationalize the expected density levels and the density perceptions. The scenarios were written by one of the researchers, reviewed by a panel of experts (marketing faculty and PhD students) and pretested in undergraduate classes in a Canadian (thirty respondents) and a Mexican university (thirtytwo respondents). The questionnaires and the scenarios were also given for translation to a Mexican-born translator living in Montreal. They were then sent to Mexico and back translated into English by one of the Mexican researchers. The video stimuli were shot in a university bookstore and edited by a professional. 3.2. Procedure and data collection The questionnaire starts with a written scenario describing a service situation. The researcher reads it aloud while students

can also read along. It is emphasized that they picture themselves in the situation. In this scenario, density expectations (high or low) are manipulated through statements about the crowd to be expected in the bookstore; then, subjects turn the page and answer questions about their density expectations for the situation just described. The students are then told that they are about to enter the bookstore previously described. Then, a short video (1 min) depicting the situation is shown twice. Subjects are told to carefully watch the video and to imagine that they are entering the bookstore. Consumers' density in the store is manipulated with the video showing either many or only few consumers. All other conditions are kept identical (music, design, lights). After viewing the video, respondents are then asked to complete the remaining section of the questionnaire. Pretests indicated adequate manipulations. Significant differences were found for the score of expectations on a 7-point Likert scale (Mhighexp = 6.0 vs Mlowexp = 3.0; F(1,62) = 169.2, p b 0.001) and for the estimation of the number of people (1 question) (Mmany = 122.9 vs Mfew = 10.5; F(1,62) = 153.8, p b 0.001). 4. Measures A self-administered questionnaire is used to gather the data, and all the items are measured on a 7-point Likert scale. In the questionnaire, these items were mixed with other questions regarding the servicescapes and the general consumers' experience to avoid respondents to focus only on crowd issues. Density perceptions are measured with three items borrowed and adapted from existing scales and studies on crowding (Machleit et al., 1994; Webb and Worchel, 1993; Hui and Bateson, 1991). Two additional items (it is easy to make my way through this store, this store is jammed) are developed for this study to reflect environmental psychology findings on density (Rapoport, 1976, Altman, 1975). Coefficient alpha reliability for the five item scale is 0.91. Density expectations are measured with similar items but phrased to capture the pre-encounter nature of expectations (for example, I expect this tore to be jammed). Coefficient alpha reliability for the five item scale is 0.86. Based on satisfaction studies using the disconfirmation paradigm (Oliver, 1997), the disconfirmation variable was operationnalized through the actual standardized difference between perceived and expected levels of density. The affective evaluation is assessed by asking respondents their degree of appreciation (liking) of the situation they just encountered in the video. Two items are borrowed from Machleit et al. (1994) and Hui and Bateson (1991). Additional items are adapted from the affective response scale to fit the bookstore situation (being in this store makes me happy, being in this store gives me pleasure). Coefficient alpha reliability for the five item scale is 0.83. Satisfaction is measured for the overall service experience as suggested by Oliver (1997). All items are borrowed from Eroglu and Machleit (1990) and Machleit et al. (1994). Coefficient alpha reliability for the item scale is 0.94.

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These measures borrow from different studies and were developed in different contexts. Therefore, a series of analyses were performed on each of the latent variables used in the model to determine their psychometric properties and particularly assess their reliability and validity. Results from exploratory factor analyses, using the principal component extraction method, suggested adequate dimensionalities and satisfying reliability indicators for each factor present in the model (all Cronbach alphas above 0.83). A confirmatory factor analysis (CFA) was performed on the measurement model derived from Fig. 2. Results of the CFA analysis suggest a good fit of the model to the data. The Comparative Fit Index (0.975) and the Root Mean Square Error Approximation (0.047) are both in line with the established criteria (CFI above 0.90, and RMSEA below 0.07) (Bollen, 1989). The adjusted χ 2 (χ 2 /df = 232.5/ 150 = 1.55) is below the prescribed limit of 2.5 to 4 (Carmines and Mc Iver, 1981). As the study is conducted in two different cultures, assessing the cross-cultural invariance of the latent measures is a valuable step (Ueltschy et al., 2004). The minimum requirement for cross-cultural measurement invariance is to show that the hypothesized structure provides a good fit in the two cultural groups (Durvasula et al., 2001). In this case, the hypothesized model is tested in each sample separately. Results show an adjusted χ2 of 1.60 (χ2/df = 240/150 = 1.60), a CFI of 0.968 and a RMSEA of 0.056 in the Canadian sample, and an adjusted χ2 of 1.74 (χ2/df = 226.5/150 = 1.51), a CFI of 0.972 and a RMSEA of 0.053 in the Mexican sample. Furthermore, all the item loadings are significant ( p b 0.05) on their respective dimension for the two populations. These results indicate a similar factor structure for the latent measures across the 2 samples (configural invariance). To indicate whether responses to the scale items can be compared meaningfully across the two groups, a metric invariance test is conducted (Durvasula et al., 2001; Steenkamp and Baumgartner, 1998). The results show an adequate fit to the data (adjusted χ2 of 2.08, a CFI of 0.95 and a RMSEA of 0.50) and therefore support for metric invariance. The configural and metric invariances suggest that the latent concepts used in the study have the same basic structure across these two cultural groups, thus offering evidence of crosscultural validity of the measures. 5. Results and analysis 5.1. Manipulation checks The expected/perceived density manipulations are checked. A paired sample t-test is used in order to ensure that the 4 confirmation/disconfirmation groups adequately reflect the perceived/expected density manipulation. These results support the success of the manipulations and the conformity with the experimental design. In addition, no difference is reported in the perceived similarity between the respondents and the people in the video (bookstore) (F(15,558) = .957, p = .413).

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Table 1 Standardized estimates for the density–satisfaction model Path tested

Standardized estimate (t-value)

Perceptions → affective evaluation ( H2a) Perceptions → satisfaction ( H1a) Disconfirmation → affective evaluation ( H2b) Disconfirmation → satisfaction ( H1b) Affective evaluation → satisfaction ( H3)

− .287 (− 3.90) − .205 (− 2.88) − .696 (− 10.22) NS .837 (24.72)

5.2. Structural relationships: evaluation of density–satisfaction relationships 5.2.1. General model evaluation In this first analysis, the model is applied to the entire sample (1723 respondents) to check for overall patterns of relationships (Harrell et al., 1980; Eroglu and Machleit, 1990; Machleit et al., 2000). The hypothesized model produces a Chisquare value of 520.5 with 145 degrees of freedom (χ2/ df = 3.59). The CFI is 0.928 and the RMSEA are 0.069. All the standardized loadings on the respective latent factor are above 0.60 and are significant at p b 0.001 (t−value N 1.96). The fit indicators suggest an adequate performance of the specified model. The standardized estimates of the parameters and their respective t-values are presented in Table 1. As shown, all of the structural relationships, except for the one regarding the direct influence of perceived density on satisfaction, are significant at p b 0.001 (t-value N 1.96; Anderson and Gerbing, 1988) and provide key insights on the relationship between density and satisfaction in a retail setting. First, in line with the crowding literature (Harrell et al., 1980; Eroglu and Harrell, 1986) and recent empirical studies (Machleit et al., 2000), the results show that affective reactions mediate the relationship between perceived density and satisfaction in retail crowding. The findings support Hypotheses H2a H2b and H3. Second, hypothesis H2b supports and underlines the predominant role of expectations (through disconfirmation) in the process through which an individual reacts to density in a retail environment. Indeed, this result suggests that the comparison between perceived and expected density (disconfirmation) drives the level of consumers' satisfaction. The use of comparisons (perceptions during the encounter versus expectations formed prior to the encounter) requires a cognitive effort from the consumer (memory and comparison). This mental calculation, embedded in the consumer's evaluation of a crowded setting, represents the first empirical support of a cognitive evaluation of the density to form satisfaction in crowded situations. Additionally, in this study, the more the density level is disconfirmed (more people encountered than expected), the less the consumers are satisfied. The valence of this relationship (negative) is typical of studies on crowding and contributes to enhance the external validity of the research. Finally, the perceived density also has a significant and direct impact on satisfaction (H1a). This result suggests the sole perceived density may lead to the satisfaction/dissatisfaction regarding the service situation. The cognitive effort in this context is greatly reduced as the process does not require any

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Table 2 Density–satisfaction model in the two cultures Path tested

Perceptions → affective evaluation Perceptions → satisfaction Disconfirmation → affective evaluation Disconfirmation → satisfaction Affective evaluation → satisfaction

Canadian

Mexican

Standardized estimate (t-value)

Standardized estimate (t-value)

− .398 (− 14.1) NS − .820 (− 38.2) NS .831 (41.7)

− .143 (− 2.0) − .267 (− 3.7) NS NS .816 (38.7)

comparisons or use of standards stored in memory. Therefore, there may be two routes to satisfaction when consumers deal with crowded settings. These results are in line with studies on satisfaction (Oliver, 1997; Oliver and De Sarbo, 1986) who suggest multiple routes to satisfaction. In addition, these studies suggest the development of additional analyses to include moderators of the relationships that lead to satisfaction. 5.3. Testing the potential moderating effect of culture Multi-group analyses are used to compare the general model across the Canadian and the Mexican samples. Hypothesis 5 is tested by fitting a structural model in which all the parameters of the causal structure are constrained to be equal across the two samples. The results suggest the release of three of the five constraints, which supports the relatively poor similarity of structural coefficients between the two groups. After the release of these three constraints, the model is re-evaluated. The final indicators are a χ2 of 634.3 with 287 degrees of freedom, χ2/ df = 2.21, CFI = .952 and RMSEA = 0.07. These results suggest a fairly good fit to the data. Table 2 presents parameter estimates. A close examination of the results presented in Table 2 suggests that culture strongly moderates the density–satisfaction relationship; therefore, H5 is supported. Even though, density negatively affects the service's evaluation for the entire sample, culture definitely impacts the way individuals react to the crowded bookstore. Indeed, there are multiple effects of culture on the way individuals process crowded settings. These influences are detailed next. First, as studies in psychology (Hall, 1966; Sinha and Nayyar, 2000) suggest, a dense shopping situation triggers higher perceived density for Canadian consumers than Mexican patrons. An analysis of variance (ANOVA) supports this result (H4 (F(1,1721) = 70.35, p b 0.001). In dense conditions, Mexicans always perceive the situation not as dense as Canadians do (MMexican = 5.77 vs MCanadian = 6.57). In addition to the effect on perceived density, the results show that culture also influences the way consumers process crowded settings. Indeed, in a bookstore, high density affects Mexicans less negatively than their Canadian counterparts. The negative coefficients leading to dissatisfaction are significantly dissimilar and weaker in the case of the Mexican sample (left versus right column of Table 2). Even though crowd has a negative influence on the shopping experience, it is not as bad for the Mexicans than the Canadians. This finding supports the views of the influence of culture on crowding and further

suggests a cultural bias in the way people are affected by crowded settings. Second, the role of expectations really differs depending on the culture at hand. For instance, it appears that expectations (through disconfirmation) play a more significantly important role in the case of the Canadians than for the Mexicans. Canadians utilize their expectations to form evaluations of crowded situations before deciding whether the situations are likeable. In the case of the Mexican culture, its satisfaction or affective evaluation does not rely at all on expectations. However, it is mainly driven by its perception of the situation. Finally, another important finding lies in the support of the dual route to satisfaction in crowded service settings across cultures. Both Mexicans and Canadians use either a direct route to satisfaction through their perceptions of the situation, or an indirect route through affective evaluation. The only difference between the two cultural groups is whether or not they use expectations to evaluate the service situation. It appears that Mexicans rely more on perceptions and limit their cognitive work (expectations), whereas Canadians heavily rely heavily upon cognitive processes. These processes mainly involve comparisons against and use of density expectations stored in memory. 6. Discussion and conclusion The results have implications at both the managerial and research levels. The results highlight the fact that consumers may analyze and react to crowded situations differently, depending on their cultural origins. The extended retail crowding model presented in this study suggests that expectations (through disconfirmation) play a major role in the way consumers evaluate crowded settings. Furthermore, it appears that consumers engage in a demanding cognitive task (to form expectations) when assessing their satisfaction with a crowded service situation. This result has immediate managerial implications suggesting that overseeing expectations (before coming to the store for example) can be a solution to reduce dissatisfaction of consumers shopping in crowded situations. The results also suggest that perception only may directly affect consumers' satisfaction with the service setting. Therefore, not only should store owners manage expectations of density/crowding, but they should also try to reduce the on-site density because some customers rely solely on this variable to evaluate the situation. This dual route to satisfaction in crowded settings also calls for more research to determine what trigger a preferred path in a given segments of consumers. This study also provides great insights on the ways culture may moderate the extended retail crowding model. The results show that in the Mexican sample, expectations (through disconfirmation) do not play any role in shaping consumers' reactions to crowded settings. In fact, all the relationships dealing with disconfirmation are insignificant in the Mexican sample whereas they have a strong impact in the Canadian sample. The social–cognitive approach to crowd assessment (Rapoport, 1976), the importance of standards of comparison

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(Heimstra and McFarling, 1978) and the central role of expectations in crowd assessment (Webb and Worchel, 1993) only applies to the Canadian sample. In addition, culture influences the overall level of density perceived by the respondents. It appears that Mexican respondents exposed to dense stimuli always perceive lower levels of density than their Canadian counterparts. This result reinforces the importance of socialization and enculturation issues in the assessment of a crowd. In fact, culture seems to be pervasive to individuals' lives and alters their perceptions of everyday situations involving crowds. Potential explanations of differences found in the two cultural groups considered are now presented. The Canadian and Mexican cultures present specificities that may explain the moderation effect found in this paper. First, as part of larger cultural entities, these nations are considered as opposites on the individualism/collectivism (Hofstede, 1980) continuum. Second, historical and geographical perspectives on shopping habits suggest that some cultures are more prone and equipped to negotiate and deal with crowd (Feinberg and Meoli, 1991). On the other hand, the findings may also be partially explained by more endemic differences due to specific national differences between Canada and Mexico. To some extent, geographic differences may contribute to the explanation of the results. Indeed, Canada is one of the largest countries in the world, somewhat larger than the US (9,093,507 sq. km), and Canada's population is about 31.6 million. Canada's openspace and relatively low population density assuredly contributes to its lower tolerance level for crowd. These country-specific issues are important to clearly understand the results. They truly represent differences between the two countries at stake, but they also are limitations to any larger cross-cultural generalizations regarding reactions to crowd. Nevertheless, this study signals to practitioners and researchers that culture should be considered as a potential moderator to the retail crowding model. This variable is becoming critically important as diversity has revealed itself to several western countries, in which consumers from all origins interact in the marketplace. Retailers should deal with crowding issues to reduce the negative consequences for their customers. Therefore, they need to know how to address cultural groups with different ways of dealing with crowded settings. Furthermore, future research should aim at developing typologies of conditions leading to specific patterns of reactions to crowded retail settings. References Altman I. The environment and social behavior. Calif.: Brooks/Cole: Montererey; 1975. Altman I, Vinsel AM. Personal space: an analysis of E. T, hall’s proxemics framework. In: Altman I, Wohlill J, editors. Human Behavior and Environment: Advances in Theory and Research, vol. 2. New York: Plenum; 1977. Anderson JC, Gerbing DW. Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull 1988;103:411–23. Baum A, Epstein YM. Human response to crowding. Gillsdale, NJ: Wiley & Sons; 1978.

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