marketing

ORIGINAL EMPIRICAL RESEARCH

How consumer shopping orientation influences perceivedcrowding, excitement, and stress at the mall

Julie Baker & Kirk L. Wakefield

Received: 5 June 2009 /Accepted: 19 August 2011 /Published online: 10 September 2011# Academy of Marketing Science 2011

Abstract While a few researchers have started to chipaway at the notion that retail density is always negative,extant studies do not empirically address the question ofwhy some shoppers respond negatively to a specific levelof density while others respond positively. We examine thisissue by drawing upon field theory (Lewin 1939) to shedlight on how shoppers vary in terms of deeper motives(McClelland 1953) to seek control or intimacy with othersin retail mall settings, and whether these motives influenceshopping orientations. Shopping orientation is then hypoth-esized to affect perceptions of crowding, and, in turn,subsequent affective responses to the mall shoppingexperience. Moreover, we examine whether individualdifferences (gender and age) can help retailers segmentthose with different shopping orientations and the motivesthat influence these orientations. We found that task andsocial shopping orientations were influenced by deepermotives for control and intimacy. The causal relationshipsbetween shopping motive, shopping orientation, and con-sumers’ affective responses of stress and excitement werealso discovered. Finally, we address theoretical and mana-gerial implications of our results.

Keywords Excitement . Stress . Shopping orientation .

Shopping motivation . Crowding

All actions are based on the ground the personhappens to stand upon.

Kurt Lewin (1935)

Retail crowding is a complex phenomenon, in whichconsumer response to human density (for brevity we will referto “density” throughout the paper) is influenced by manyfactors, including personal factors, expectations, tolerance forcrowding, and shopping motivation (viz., Eroglu et al. 2005).Thus, within the retail setting, when two individuals viewexactly the same physical cues, one may decide it’s toocrowded and another decide it’s just right. Why? What kindsof shoppers are excited while others are stressed to be in amall setting where others are shopping?

By definition, perceived crowding is described innegative terms (confined, constrained, restricted) and as anegative psychological reaction to the physical density in asetting (Stokols 1972). As such, prior investigations ofretail crowding caused by perceptions of density havelargely focused on negative affective and behavioral out-comes (e.g., Eroglu and Harrell 1986; Eroglu et al. 2005;Bateson and Hui 1992). Beginning with Harrell and Hutt(1976), research on retail crowding has examined consumerresponses under varying density conditions, finding thatrelatively higher human density results in stimulus overloadand negative responses (Grewal et al. 2003; Grossbart et al.1990; Harrell et al. 1980; Machleit et al. 2000; Menz andMullen 1981). Hence, positive effects of retail density haverarely been examined in the marketing literature.

Nevertheless, a few studies suggest positive effects mayoccur with certain types of people. In a conceptual paper,Eroglu and Harrell (1986) posit that when a particular

J. Baker (*)Department of Marketing, Neeley School of Business,Texas Christian University,Fort Worth, TX 76129, USAe-mail: [email protected]

K. L. WakefieldDepartment of Marketing, Hankamer School of Business,Baylor University,PO Box 98007, Waco, TX 76798, USAe-mail: [email protected]

J. of the Acad. Mark. Sci. (2012) 40:791–806DOI 10.1007/s11747-011-0284-z

amount of personal intimacy is desired, shoppers tend toseek high-density environments. Experimentally, Erogluand Machleit (1990) find that shoppers placed in a task-oriented shopping scenario perceive the setting with thehighest density as being more crowded compared to thoseshoppers not placed in a task-shopping context. Researchby Eroglu et al. (2005) indicates a positive effect of humancrowding on shopping satisfaction when otherwise account-ing for the negative affective response from human andspatial crowding effects.

Other studies suggest the retail context may determinehow people perceive density. For example, Hui and Bateson(1992) find that density has a more positive effect onperceived control in a hedonic setting (bar) than in autilitarian setting (bank). Similarly, using a hypotheticaldisco setting, Pons et al. (2006) find a positive impact ofcrowds on subjects’ evaluations of their experience. On theother hand, the negative effects of density (i.e., crowding)have been found in more utilitarian settings (e.g., Eroglu etal. 2005; Harrell et al. 1980; Machleit et al. 1994).

While these studies have started to chip away at thenotion that retail density is always negative, they do notempirically address the question of why some shoppersrespond negatively to density while others respond posi-tively. More specifically, how and why can shoppers viewexactly the same store setting with some interpreting theplace as too crowded and stressful while others see thesame place as inviting and exciting? One important key tounderstanding this difference may lie in how consumersapproach the retail experience. In our study, we propose thatpeople differ in their general orientations to a mall shoppingexperience: some view it as utilitarian while others view itas hedonic.

We also draw upon field theory with respect to life space,social space, and personal space (Lewin 1939) to shed light onhow shoppers vary in terms of deeper motives (McClelland1953) to seek control or interaction with others in retail mallsettings, and whether these motives influence shoppingorientations. Moreover, we examine whether individualdifferences (gender and age) can help retailers segment thosewith different shopping orientations and the motives thatinfluence these orientations. The results of this researchshould provide deeper insights for academics into the factorsthat determine when human density is a positive or negativeexperience for consumers. From a retail organization’sperspective, understanding factors driving some to avoidmalls while others seek them out can help management tailormarketing strategies to address the needs of both groups.

Our research offers several important contributions to themarketing literature. First, whereas malls are designed toattract crowds to a central shopping location, elements ofthis design have served to alienate certain shoppers nowopting to shop elsewhere, such as lifestyle centers and the

Internet (see Nanney 2009; Smith and Rupp 2003).Understanding the motivations and resulting shoppingorientations of those who avoid the mall is one goal ofour study. Second, past research has focused almost entirelyon the negative effects associated with human density inretail settings. We offer theoretical and empirical evidencedemonstrating that some individuals perceive the presenceof others in their social space at the mall as acceptable andsubsequently respond favorably. Third, understanding thecontrasting social-shopping and task-shopping orientationsallows retailers to recognize individual shopping motivesand types and to adjust marketing activities to fit each. Inparticular, our research finds that age and gender differ-ences help us characterize those who seek control in theshopping experience and those seeking affiliation and socialbonding in the mall shopping experience. Finally, priorcrowding work has focused almost entirely on the storelevel, although perceived crowding at the mall is apt topredicate patronage of all stores in that mall.

Theoretical background and hypotheses

Our central hypothesis is that perceptions of and affectiveresponses to the same density level in a setting will varydepending on whether shoppers are task oriented or sociallyoriented, and that these orientations are motivated by basicneeds associated with power and affiliation. Field theory(Lewin 1939) and motivational theory (McClelland 1953)suggest that individuals see personal space as a boundaryregulation mechanism to achieve desired privacy levelswithin a social space, such as a mall (Altman 1975). Fieldtheory suggests subjective views of personal and socialspace may induce an individual to view others as either ahelp or hindrance in obtaining one’s goals. This view maythen influence whether shoppers tend to be stressed orexcited at the mall and their subsequent patronageintentions. Figure 1 illustrates the expected relationships.

Affective responses to the physical environment

Various measures of affect have been used in past retailcrowding studies. Researchers have investigated the relation-ships between perceived crowding and pleasure (Hui andBateson 1991), satisfaction (Eroglu and Machleit 1990),several facets of emotion (Eroglu et al. 2005), and affectiveevaluation (Pons and Laroche 2007; Pons et al. 2006).

For this study we draw on research by Russell and hiscolleagues (Mehrabian and Russell 1974; Russell and Pratt1980; Russell et al. 1981) specifically designed to measureaffective responses to the physical environment (includingthe number of people within a space; Baker 1987), focusingon consumers’ primary affective states of pleasure and

792 J. of the Acad. Mark. Sci. (2012) 40:791–806

arousal. Scholars have noted that crowding results in highlevels of arousal (e.g., Eroglu and Harrell 1986; Worcheland Yohai 1979). Accordingly, we draw on the circumplexmodel of affect (Russell and Pratt 1980; Russell et al. 1981)to investigate two different levels of pleasure combinedwith high levels of arousal. In this model, high levels ofarousal combined with high levels of pleasure reflectfeelings of excitement. In contrast, high levels of arousalcombined with low levels of pleasure equate to feelings ofstress. Regarding the latter, we focus on psychologicalstress, which Lazarus and Folkman (1984) define as arelationship between a person and an environment that isperceived by the person as taxing or exceeding his or herresources.

Psychologists have long been interested in measuringpsychological levels of stress and excitement (c.f.,Boggs 1904), given their physiological and behavioralconsequences. This emphasis continues today in hopes offinding effective means of stress management (e.g., Diehland Hay 2010), emotion regulation (Tamir, Chiu andGross 2007), and assessing co-morbidity of excitement-seeking behaviors and pathological behaviors such asgambling (e.g., Vachon and Bagby 2009). Excitement andstress also capture relatively extreme levels of affectcompared to affective measures in some previous crowd-ing studies. This is important for scholars and managersbecause it tests important boundaries of affect thatexpressly elicit approach/avoidance behaviors, comparedto more moderate affective states characterized by milderlevels of arousal. Surprisingly, few studies have investi-gated excitement or stress related to retail shopping (seed’Astous 2000; Wakefield and Baker 1998).

Shopping orientations, life-space, personal space,and needs-based motives

We first define social- and task-oriented shopping orienta-tions, followed by the theoretical underpinnings explainingwho the individuals are that may adopt either of theseorientations, and why they may adopt one or the other. Wealso include hypothesized paths in our model explainingaffective response and behavioral intentions.

Shopping orientation is defined as a person’s mentalframework of responses designed to navigate the shoppingenvironment to achieve personal goals. As such, theshopper’s orientation includes learned and innate responsestypifying the person’s approach to the mall, consistent withthe notion of an enduring shopping predisposition (Babin etal. 1994). Shopping orientation is different from a consumermotivation defined by the situation (i.e., “I have to buy agift by tomorrow”). There is also a difference betweensituational motives and the tendency for someone to bemore of a social or a task shopper (e.g., someone couldtypically be a social shopper, but for a specific shoppingtrip exhibit task shopping behaviors).

Prior studies have found two fundamental consumerorientations relevant to retail shopping. Hedonic orienta-tions include shopping for fun and enjoyment, andshopping to satisfy needs unrelated to the purchase ofproducts (e.g., Babin et al. 1994; Bellenger and Korgaonkar1980; Westbrook and Black 1985). In this study, thehedonic orientation we are specifically interested in issocially-based (referred to herein as “social shopping”),which is a subset of hedonic shopping motivations (Arnoldand Reynolds 2003). Social shoppers prefer to shop in the

Fig. 1 Proposed model

J. of the Acad. Mark. Sci. (2012) 40:791–806 793

presence of other people because it adds to their enjoymentof the experience. In contrast, task-based orientations(“task shopping”) involve the economic and utilitarianreasons people shop, with no inherent pleasure derivedfrom the shopping experience—other than completing theshopping trip itself. The main goal of these shoppers is topurchase the needed products rather than to necessarilyenjoy the shopping trip (e.g., Babin et al. 1994; Dawson et al.1990).

While individuals may exhibit either, or both, hedonicand utilitarian characteristics during any given shoppingtrip, research has consistently shown that a shopper’spredisposition will primarily reflect one or the other (Blochet al. 1994; Leondari and Gonida 2007; Midgley et al.1995; Westbrook and Black 1985). Evidence from studiesrelated to goal theory indicates people tend to be task orsocially oriented and that task orientation declines as socialgoals increase (Leondari and Gonida 2007; Midgley et al.1995). In the management field, a task-oriented manage-ment approach is theoretically and empirically opposed to arelationship-oriented approach (e.g., Guthrie et al. 1998).Therefore, we propose:

H1: Social shopping orientation has a negative associationwith task shopping orientation.

Why might some individuals approach malls with asocial shopping orientation while others approach mallswith a task orientation? When there are other people at themall, why do some shoppers perceive that a mall iscrowded, while others do not? Also, why might someshoppers react with excitement and others with stress to thesame setting? We begin this section by summarizingpertinent elements of Lewin’s (1935, 1939) work in fieldtheory and life-space applied to the fields of socialpsychology and then turn our attention to issues related topersonal space and needs-based motivational theory toexplain differences in responses to mall environments thatare perceived to be crowded.

Lewin’s field theory (1939) holds that one’s behavior is afunction of the person and the environment (Be=F [P, E])and that this interdependency between person-environmentforms one’s life-space. When an individual has a well-defined mental framework about a place or environmentand a course of actions within that place, that particularaspect of one’s life-space is well-established. Time alsoinfluences one’s current life-space, since an individual mustplan to organize time such that his or her goals are achievedgiven the immediate physical environment and mentalconstructions about that space. Some individuals developrelatively wide life-spaces in terms of geography (e.g.,worldwide traveling, nature hiking, metropolitan shopping)and social surroundings (exposure to various political,occupational, or other social groups), while the scope of

others remains limited. Instability is introduced as uncer-tainty occurs in any of the life-space elements (environ-ment, person, time), and stress can arise from shifts orchanges in the environment or from the person (or both).Hence, “all actions are based on the ground the personhappens to stand upon” (Lewin 1935).

Based on what we know about personal space, “the groundone stands upon” can be viewed from the perspective of howindividuals manage the distance between self and others tomaintain desired comfort levels (Sommer 1959). In dealingwith social settings, people develop schemata to structuresituations involving other humans (Kuethe 1962), and theydiffer in their response to others regarding comfortableinterpersonal distance and interaction (Hall 1964). A person’sneeds, traits, and social learning dictate the form of theschemata against which an occasion is compared. Relative toone’s personal space associated with one’s life-space, we canexpect individuals to differ with respect to schemata forcoping with social settings, including those encountered in amall.

Considerable research has been devoted to studyingdifferences in social schemata for spacing persons. AsPedersen and Shears (1973) report across a wide varietyof experiments, encountering others in a social settingactivates a person’s efforts to deal with the “perceivedstimulus … to modulate, enhance, reduce, or discharge theemotional arousal.” According to Sommer (1965, 1967),due to these differences in social schemata, persons willseek to interact or avoid interaction with others. Returningto field theory, we can expect some persons to view thepresence of others in a shopping setting as fitting. At thesame time, we might also expect some to view thepresence of others as being in conflict with their goals.

The questions we seek to answer with this study revolvearound why some people develop schemata or orientationsthat more positively perceive the presence of others in theshopping setting, while others follow schemata intended toavoid interaction, and who these people are. Our under-standing of life-space and personal space, coupled withneeds-based motivational theory (McClelland 1953) allowsus to theorize why some persons approach shopping centerswith a social shopping orientation versus a task shoppingorientation. We now turn to a brief review of two basicneeds likely to motivate behavior in the mall shoppingcontext: the need for power and the need for affiliation.

McClelland (1953) identified the three basic needs forachievement, power, and affiliation in motivating individualapproaches to goal attainment. In the present study, wefocus on the latter two to explain why individuals mayapproach shopping occasions with either more of a taskversus a social shopping orientation. The need for power isprimarily concerned with influencing and controllinginteractions with others. The need for affiliation focuses


on maintaining social relationships and enjoying intimacy,understanding, and friendly interaction with others. In the mallshopping context that is the focus of this study, we representthese needs as shopping control and shopping intimacy.

Influences on task and social shopping orientations

We propose that shopping intimacy and shopping controlaffect social and task shopping. In addition, becauseresearch has shown that gender and age may moderate therelationships between shopping orientation and control/intimacy, we include hypotheses for these demographics aswell.

Shopping control and task-shopping We define the need forshopping control as the need to influence or controlinteractions with others in order to achieve shopping goals(McClelland and Burnham 1976). Individuals tend to havethe need for personal control, to manipulate the surroundingenvironment. Furthermore, the need intensity varies basedon the event or surroundings (see Langer 1983). In short,when a person feels out of control, the individual reacts torestore control (Greenberger et al. 1988). Since individualshave been shown to differ in the need for control andbecause the physical and social stimuli within the context ofshopping centers are apt to lead some (not) perceiving alack of control, we expect some persons to have a high(low) need for control during the shopping trip. At atheoretical level, this need is founded in the social schematalearned to maintain one’s personal space in the context ofone’s life-space.

Those possessing schemata that include controllinginteractions with others in the shopping setting are likelyto be oriented toward completing the task of shopping. Therelationship between the need for power/control and a taskorientation is well-established (c.f., Fiedler 1967; Stewartand Manz 1995). Further, within a work context, males tendto exhibit more need for power and to control via a task-oriented approach than do women (for a review, see Duehrand Bono 2006).

In a retailing context, scholars have found that men tendto perceive shopping trips as a distasteful task best carriedout as quickly and efficiently as possible (Dittmar et al.2004). Men are more likely to desire control and tocomplete the goal inherent in the shopping task (e.g., Otnesand McGrath 2001), which typically means getting into astore quickly, making a purchase, and getting out.

Therefore:

H2: Need for shopping control is positively associatedwith task shopping orientation.

H3: Compared to females, males will have higher (a) needfor shopping control, and (b) task shopping orientation.

Individuals whose approach to the shopping mall isessentially to avoid the place, or at least to minimizethe time spent in the setting, are expected to be lessfrequent mall shoppers. Individuals who associate a taskwith stress are apt to avoid the task (Matthews andCampbell 2009). Thus, in general, we expect individualswho frequently shop at the mall are unlikely to be taskshoppers.

H4: Frequency of mall shopping is negatively associatedwith task shopping orientation.

Intimacy and social shopping Affiliation and intimacy(physical distance, interpersonal interaction, and nonverbalcommunication) are closely related (Argyle and Dean1965). Theriault (1998) indicates intimacy between friendsincludes the extent to which exchanges between individualsclarify ideas communicated, express feelings, and result inunderstanding, listening, and “endless” talking. Within theshopping context, we define shopping intimacy as the needfor dyadic relationships to discuss, listen, and offer supportin the buying decision process.

Individuals with social schemata placing high value onintimate interactions in terms of interpersonal distance andverbal/ nonverbal communications in the shopping milieuare expected to adopt a social shopping orientation. Anindividual with a social shopping orientation has developeda response set or mental framework that includes thepresence of others while shopping. This may or may notinclude intimate discussion of the details of the shoppingtrip or that others support one’s shopping decisions.However, it does follow that if one seeks intimacy in theshopping process, one is likely to have a social shoppingorientation.

The tenant mix for shopping malls (clothing, cosmetics,gifts) is predominantly aimed at females, suggestingwomen will have more well-defined life-spaces incorporat-ing shopping mall interactions. In many ways, women areon their home turf and men are likely to learn to be morecircumspect in navigating the shopping center environment.Furthermore, in keeping with the previously cited researchregarding male tendencies toward control and task orienta-tion, prior empirical studies in management and psychologyconfirm the tendency of females to express higher need foraffiliation and intimacy and to be more relationship oriented(i.e., less task oriented) in achieving their goals (Duehr andBono 2006; Mansfield et al. 2005; van Wagner andSwanson 1979).

Prior research has also found that women are higher inhedonic motivations than are men (e.g., Arnold andReynolds 2003; Wesley et al. 2006). Josephs et al. (1992)argue that women base self-esteem on levels of socialconnectedness. Therefore, women may see retail settings


as a social venue in which social interaction is asecondary, if not the primary, goal. Hence:

H5: Need for shopping intimacy is positively associatedwith social shopping orientation.

H6: Compared to males, females will have a higher (a)need for shopping intimacy, and (b) social shoppingorientation.

Shoppers who approach the setting as a place to socializeand interact with others are likely to frequently patronizemalls as a form of entertainment or enjoyment. Hence:

H7: Frequency of mall shopping is positively related withsocial shopping orientation.

Age and shopping motives One’s life-space becomes morewell-defined and less ambiguous or uncertain with age. Ingeneral, more mature individuals feel less out of controlthan do younger individuals, meaning they have less needto control to regain balance. Accordingly, research hasshown that as individuals grow older, they have less of aneed for control (Maroda 2004). Older individuals tend toreduce intimate relationships to a select few (Carr 2004). Ingeneral, studies have found that need for intimacy tends todecrease with age (e.g., Brown et al. 1986). Conversely,younger individuals have fewer experiences and exposureto various environments with less well-defined life-spacesand appropriate social schemata to manage the context.Within the shopping mall setting, we expect these tenden-cies to persist.

H8: Age decreases the need for shopping control.H9: Age decreases the need for shopping intimacy.

Shopping orientation and affect

Arousal theory suggests that people desire a certain level ofarousal in certain circumstances or settings (Berlyne 1960).We propose that social shoppers will experience excitementwhen shopping at the mall, whereas task shoppers willexperience stress.

A task orientation reflects a work rather than a playmentality (Hirschman and Holbrook 1982). Prus andDawson (1991) find that when people described shoppingas work, they used words that typically also describe stress,such as “difficult, rushed, and frustrating.” Task shoppershave characteristics in common with individuals that Blochet al. (1994) classify as reluctant mall shoppers who engagein few activities while there. Many consumers who are timepressed try to avoid malls (Wakefield and Baker 1998), butthis may be hard to do if the mall is the only place in whichthey can complete their tasks. Task shoppers may thus find

mall shopping stressful. Consistent with this reasoning,Babin et al. (1994) find that the correlation betweenpleasure and arousal and utilitarian shopping value issubstantially less than the magnitude of the correlationsbetween these two emotions and hedonic shopping value.Despite the implications of previous research, the influenceof task shopping on stress has not been empiricallyexamined. Based on the extant evidence, we hypothesize:

H10: Task shopping increases feelings of stress.

The need for control is typically associated with stress.When approaching problem-solving contexts, those whoare more flexible experience less stress and those moreconstricted in their approach feel more stressed (Hardisonand Purcell 1959). Further, those who feel out of control orcontrolled by external circumstances are more likely to beanxious or stressed (Donovan et al. 1975). When they arefacing the prospect of shopping, we expect those seekingcontrol to feel more stress than those not seeking control.

H11: Shopping control increases feelings of stress.

Individuals predisposed to shop for social reasons shouldbe more excited about shopping at the mall. Affiliationtheories of human motivation (McGuire 1974), which suggestthat people are cohesive and affection- and acceptance-seeking in interpersonal relationships, support social shop-ping as a primary orientation. Prior research in marketing hasrecognized the importance of social shopping motives (e.g.,Reynolds and Beatty 1999; Tauber 1972). However, neitherthe influence of a social shopping orientation as a driver ofexcitement nor how social shoppers react to crowding hasbeen examined in marketing.

Studies have shown that heightened positive arousal and theseeking of high sensory stimulation are associated withrecreational shopping (e.g., Prus and Dawson 1991), of whichsocial shopping is a component. Similarly, Bloch et al. (1994)found a positive correlation between mall enthusiasts andpeople who shopped for social benefits. Feinberg et al. (1989)note that social motives may be particularly strong in thecontext of mall shopping. Together, the evidence suggests:

H12: Social shopping orientation increases feelings ofexcitement.

Intimacy in relationships is inherently associated withexcitement (Livingston 1999). We expect it to be nodifferent when shopping at the mall.

H13: Shopping intimacy increases feelings of excitement.

Shopping orientation and crowding

The tenets of field theory and personal space researchsuggest perceptions of crowding result from the belief that


task performance is limited. Prior empirical research hasfound that under high density conditions, task-oriented shop-pers perceive increased crowding compared to non-task-oriented shoppers (Eroglu and Machleit 1990). Similarly,individuals seeking social interaction have been found toexperience less perceived crowding than do those who arenot seeking interaction with others (Baum and Davis 1976;Peay and Peay 1983). Consistent with this research, wehypothesize:

H14: Task shopping orientation increases perceivedcrowding.

H15: Social shopping orientation decreases perceivedcrowding.

Arousal due to perceptions of crowding tends toheighten the emotions of shoppers (Gaumer and LaFief2005; Saegert et al. 1975). Thus:

H16: Perceived crowding (a) increases feelings of stressand (b) reduces feelings of excitement.

Patronage intentions

The relationship between positive and negative affect onbehavioral intentions in retail settings is well established(Szymanski and Henard 2001; Wakefield and Baker 1998;Wakefield and Blodgett 1999). Consistent with this litera-ture we hypothesize:

H17a: Stress decreases patronage intentions.H17b: Excitement increases patronage intentions.

Method

Design

To test the hypotheses, we implemented a quasi-experimental approach using an online survey method.The selected panel research firm maintains a database of 1.6million adult consumers and rewards participation insurveys using drawings and cash payments. Panel membersmirror national demographics, albeit skewed slightly lowerin age and higher in income. Before presenting subjectswith a mall shopping scenario, we measured demographics,shopping frequency, need for shopping control, need forshopping intimacy, social shopping, and task shoppingorientations. The scenario instructions were:

You are going shopping on a Saturday morning at11:00 am. You are at the shopping center you areviewing. Your plan is to shop and get something toeat. Please view the scenes imagining you are there.

The scenario was accompanied by pictures of the insideand outside (including the parking lot) of an unidentifiedshopping mall (cf., Hui and Bateson 1991), taken during atime when a moderate number of shoppers was present (seeFig. 2). After viewing the pictures and reading the scenario,respondents answered questions about perceived crowding,affective responses, and patronage intentions. In keepingwith Hair et al. (2011), we analyzed the measurementmodel and structural model using a partial least squaresapproach, employing smartPLS (Ringle et al. 2005).

Sample

Study respondents were 300 adults from a national samplenearly evenly split according to gender (52.7% female),with median age of 39 (range 18–79) and medianhousehold income of $50,000–74,999. Most were married(53.3%), while 30.7% were single, and 16.0% divorced orwidowed. Respondents resided in large cities of over500,000 (34.0%), small cities under 50,000 (29.7%), and

Fig. 2 Exterior and interior depiction of shopping center


were otherwise distributed across city sizes in-between(36.3%). Similar to other studies (e.g., Nicholls et al. 2002),our measure of shopping frequency revealed that relativelyfew respondents patronized shopping centers on a weeklybasis (23.3%). The remaining respondents visit once(20.3%), twice (18.3%), three times (12.7%), or less thanonce a month (25.3%). None of the constructs measureddiffered significantly according to city size, income, ormarital status.

Measures

Table 1 contains all of the items (7-point scales) used in thisstudy. Excitement (a=.94) and stress (a=.95) were drawnfrom Russell and Pratt’s (1980) work on environment-related affect. Perceived crowding (a=.95) was measuredwith items based on Hui and Bateson (1991). Arnold andReynolds’ (2003) measure of social shopping (a=.85) wasadapted to focus on the experience with shopping com-panions. Patronage intention (a=.92) was measured withscales common to retailing and services (cf., Stafford 1996).

Based upon Mehrabian and Russell’s (1974) assessmentof dominance, we developed a scale measuring the need forshopping control emphasizing control, influence, domi-nance, autonomy, and being in charge within the shoppingsetting (a=.82). Need for shopping intimacy was based onan overview of the intimacy literature in social psychology,adapted for the context of shopping. Similar to Levy-Tossman et al. (2007) assessment of friendship intimacy, wefocused on the importance the subject placed on listening,discussing, talking, supporting, and offering opinions,specifically regarding purchases and shopping (a=.93).Researchers have shown interest in assessing psychologicaltraits of employees with respect to task versus interactionorientations. Drawing from this field of study, workconducted by Ray (1973) provides the basis for our taskshopping scale. Ray’s 27-item scale captures the breadth ofcharacteristics of an individual who is task-oriented across avariety of contexts. Following a pretest including the otherscales used in this study, we selected six items amenable toadaptation to a mall shopping context. The resulting scalewas reliable (a=.85).

In addition to the Cronbach alpha scores, Table 1contains the composite reliability (CR) and the averagevariance extracted (AVE) and descriptive data for eachconstruct. Demonstrating reliability, all values for CR areacceptable (ranging from .89 to .96), as are the AVE values(ranging from .58 to .84). Furthermore, evidence ofdiscriminant validity (Fornell and Larcker 1981) is shownin Table 2, in that the square root of the AVE for eachconstruct is greater than the squared correlations with theother constructs. Table 3 provides the factor loadings andcross loadings. Each item loads higher on its respective

construct than on any other, offering further support for themeasurement model.

Results

A bootstrapping procedure using 500 re-samples of thedataset (N=300) was applied prior to running the PLSalgorithm and estimating the structural model. Gender wascoded as a dummy variable, and the results reflect theappropriate sign or direction of the gender effects. Theresults of the model estimation are shown in Table 4.Overall, the model explains 42.4% of the variance inpatronage intentions, 68.6% of stress, 25.5% of excite-ment, 12.8% of perceived crowding, 30.9% of socialshopping, and 27.0% of task shopping. The demographics(gender and age) alone explain 5.2% of the variance inshopping control and 7.5% of the variance in shoppingintimacy.

The results of the structural model largely support ourhypotheses, with exceptions as noted. As expected, socialshopping orientation is negatively related to task shoppingorientation (H1, −.309, t=5.61) support H1. Those feeling agreater need to control the shopping experience were prone tobe task shoppers, supporting H2 (.304, t=3.84). Furthermore,males tended to seek shopping control (H3a, .138, t=2.26)and were more likely to be oriented toward task shopping(H3b, .196, t=3.67). Less frequent mall shoppers were alsoprone to be task shoppers (H4, −.130, t=2.34). In contrast,we expected females to be prone to seek shopping intimacy,but this effect was not significant (H6a, .074, t=1.35).However, females were more likely to be social shoppers(H6b, .150, t=3.13), and shopping intimacy strongly influ-enced social shopping orientation (H5, .513, t=10.53). Asexpected, those who more frequently shop at mallswere more likely to have a social shopping orientation(H7, .094, t=1.78). Age was inversely related to the needfor shopping control (H8, −.193, 2.21) and shoppingintimacy (H9, −.259, t=4.71).

We expected the general relationships between taskorientation and the need for control with feelings of stressto have direct effects within the shopping environment.This was not the case, as increased task shoppingorientation had a positive, but not significant, relationshipwith stress (H10, .066, t=1.39). The need for shoppingcontrol had no significant relationship with feelings ofstress associated with the mall scenario (H11, −.015, t=0.42).Within the data, shopping control is correlated withstress (r=.113, p=.05), as is task shopping (r=.307, p<.01).However, as we see shortly, the effects of perceivedcrowding are so strong on feelings of stress (H16a) thatthese factors do not explain any additional variance in thestructural model.


Table 1 Constructs, descriptives, and reliabilities

Item Mean(Std) CronbachAlpha

AVE CompositeReliability

Shopping Control (When I shop with others:) .829 .604 .882

con1 I like to be in charge. 3.28 (1.81)

con2 I like to influence what we do. 3.87 (1.58)

con3 I like to dominate. 3.32 (1.77)

con4 I like to be in control. 3.63 (1.71)

con5 I like to be autonomous. 2.94 (1.66)

Shopping Intimacy (When or while you shop, how important is it to you:) .931 .745 .946

si1 To listen to what friends or family say as they discuss each purchase? 3.63 (1.67)

si2 That friends or family listen to your feelings about what you buy? 3.60 (1.69)

si3 To be able to talk through decisions about products, brands or stores with friends or family? 3.90 (1.64)

si4 That friends or family are supportive of what you buy or where you want to shop? 3.73 (1.73

si5 That friends or family are there to offer their opinions about what you’re thinking aboutbuying?

3.62 (1.70)

si6 That friends or family care what you think about products, brands, or stores? 3.59 (1.66)

Social Shopping Orientation .854 .775 .911

ss1 I enjoy interacting with others when I shop. 4.07 (1.76)

ss2 Shopping with others is a bonding experience. 3.95 (1.74)

ss3 When I shop, I really enjoy the social interaction that I experience with others. 4.07 (1.69)

Task-Shopping Orientation .852 .579 .891

t1 The first task of shopping for me is to get done. 4.54 (1.95)

t2 You should concentrate on getting the shopping done rather than looking around at whateverelse catches your fancy.

3.56 (1.88)

t3 I am happiest when I get done shopping. 4.71 (1.90)

t4 What gets done is more important than how pleasantly it gets done when you shop. 3.40 (1.81)

t5 My primary aim in shopping is to complete the trip as planned. 4.79 (1.75)

t6 The best people to shop with are people who help you get done. 4.72 (1.72)

Perceived Crowding .949 .834 .962

c1 Stuffy 2.81 (1.83)

c2 Cramped 3.01 (1.92)

c3 Crowded 3.91 (2.07)

c4 Restricted 2.92 (1.81)

c5 Confined 2.85 (1.87)

Excitement .945 .821 .956

e1 Exhilarating 3.18 (1.62)

e2 Sensational 3.06 (1.56)

e3 Stimulating 3.53 (1.63)

e4 Exciting 3.51 (1.68)

e5 Interesting 4.21 (1.69)

Stress .951 .838 .963

s1 Frenzied 3.22 (1.94)

s2 Tense 3.05 (1.88)

s3 Hectic 3.45 (1.96)

s4 Panicky 2.57 (1.72)

s5 Rushed 3.16 (1.95)

Patronage Intention .920 .806 .934

p1 Not at all–Very frequent 4.08 (1.52)

p2 Not at all likely–Very likely 4.30 (1.66)

p3 Not probable–Very probable 4.43 (1.63)

p4 Impossible–Very possible 4.51 (1.78)


As anticipated, a person’s shopping orientation influencedperceived crowding and feelings toward the mall. Socialshopping was positively related to excitement (H12, .286, t=4.33), as was shopping intimacy (H13, .263, t=4.18). Thosewith greater task shopping tendencies perceived the slides asdepicting a more crowded shopping environment (H14, .258,t=4.48), while those with more of a social shoppingorientation viewed the setting as less crowded (H15, −.179,t=2.96).

Perceived crowding strongly increased feelings ofstress (H16a, .807, t=29.00) and dampened feelings ofexcitement (H16b, −.093, t=1.78). In turn, stress reducedpatronage intentions (H17a, −.273, t=5.73), while excite-ment strongly influenced intentions to patronize the mall(H17b, .550, t=13.39).

In summary, the findings support the linkages associatedwith a positive life-space including shopping intimacy,social shopping, (less) perceived crowding, excitement, andpatronage at the mall for some. Along parallel lines, butfrom a negative life-space perspective, the results confirmthat the path from shopping control, to task shopping, toperceived crowding leads to stress and a desire to avoid themall for others. Further, the path to excitement at the mall isapt to be walked by younger females while stress comes tothose younger males more likely to seek shopping controland approach their infrequent trips to the mall as a set oftasks to be completed.

Discussion and future research directions

Our results contribute valuable insights to the shoppingorientation and retail crowding literatures. The finding thattask and social shopping orientations are influenced bydeeper motives for control and intimacy help to explainwhy two individuals in a retail setting view the samedensity differently. Task shoppers with a higher need for

control tend to perceive density as crowding, and in turnfeel stressed. Social shoppers, who tend to have a higherneed for intimacy, perceive density positively, and feelexcited. We also show that age and gender differences helpcharacterize those who seek control in the shoppingexperience in order to complete the shopping task andthose seeking affiliation in the mall shopping experience.Further, frequent mall shoppers tend to be socially oriented,while infrequent patrons are prone to be task oriented.

Theoretical implications

Researchers in marketing have established the existence oftask and recreational shoppers (e.g., Arnold and Reynolds2003; Babin et al. 1994). Our study extends this research intwo ways. First, we focused on the social shopper, a type ofrecreational shopper not previously examined in depth.Because shopping for frequent mall customers is a socialactivity (Darden and Dorsch 1990) this shopper type shouldreceive more attention in retail models. Second, integratingtenets of field theory, motivational theory and personalspace theory allowed us to identify the deeper motivationsof shopping control and shopping intimacy that appear toinfluence the tendency of consumers to be either a task orsocial shopper. In particular, research on personal spacetheory has been limited in marketing, but it appears to havepotential to add insight to our discipline.

We found social shopping and task shopping tendenciesrun counter to each other. Further analysis revealed that30.3% of the sample identify themselves as highlymotivated social shoppers (≥5.0 average on the 7-pointscales). Slightly larger is the number (34.3%) who identifythemselves as having high task-shopping tendencies (≥5.0on the 7-point scales). As we would expect from thenegative relationship between the variables, very few(3.3%) identify themselves as both social and task shop-pers. Hence, these shopping tendencies represent distinct

Table 2 Discriminant validity: comparison of AVE with squared correlations with other latent constructs

ShoppingControl

PerceivedCrowding

Excite-ment

ShoppingIntimacy

PatronageIntention

SocialShopping

Stress TaskShopping

Shopping Control .604

PerceivedCrowding

.018 .834

Excitement .008 .039 .821

ShoppingIntimacy

.050 .003 .165 .744

PatronageIntention

.002 .148 .351 .070 .806

Social Shopping .001 .077 .191 .270 .175 .774

Stress .015 .695 .029 .004 .135 .080 .837

Task Shopping .085 .101 .069 .056 .084 .126 .111 .579


segments with distinguishing responses to the shoppingsetting. These findings are consistent with studies indevelopmental psychology finding that individuals proneto social comparison and social goals are less task oriented(Leondari and Gonida 2007; Midgley et al. 1995).Furthermore, while completing a task can result in positiveaffect (Kish et al. 1977), we have shown that shoppers with

a task shopping orientation can be stressed and under whatconditions the stress might be exacerbated.

Our results provide evidence to support the few studiesthat have found positive aspects of human density byshowing that it can lead to excitement among a specificgroup of shoppers. This has theoretical implications forcrowding research because prior studies have emphasized

Table 3 Loadings and cross loadings

ShoppingControl

ShoppingIntimacy

TaskShopping

SocialShopping

PerceivedCrowding

Stress Excitement Patronage

con1 .851 .176 .199 .042 .076 .060 .039 −.027con2 .711 .378 .059 .254 .103 .091 .241 .076

con3 .849 .284 .137 .031 .142 .169 .179 −.077con4 .876 .216 .207 .063 .071 .070 .045 −.040con5 .551 −.073 .425 −.126 .126 .081 −.069 −.043si1 .135 .816 −.296 .440 −.085 −.090 .304 .251

si2 .216 .854 −.204 .434 −.050 −.035 .375 .219

si3 .198 .889 −.215 .486 −.083 −.102 .338 .283

si4 .235 .870 −.193 .461 −.075 −.055 .372 .227

si5 .157 .862 −.196 .445 −.004 −.033 .360 .187

si6 .217 .884 −.122 .421 −.004 −.010 .348 .199

t1 .172 −.246 .818 −.307 .240 .250 −.274 −.255t2 .261 −.211 .803 −.301 .264 .274 −.215 −.258t3 .144 −.187 .795 −.270 .239 .254 −.149 −.255t4 .292 −.130 .659 −.296 .235 .278 −.132 −.213t5 .172 −.244 .799 −.307 .203 .201 −.255 −.243t6 .266 −.054 .676 −.118 .264 .248 −.166 −.084ss1 .034 .428 −.285 .854 −.281 −.289 .337 .399

ss2 .038 .480 −.330 .866 −.241 −.247 .412 .350

ss3 .025 .462 −.321 .919 −.216 −.215 .400 .358

c1 .105 −.047 .288 −.262 .923 .771 −.187 −.388c2 .132 −.020 .248 −.251 .939 .778 −.135 −.332c3 .103 −.127 .311 −.251 .823 .690 −.187 −.283c4 .156 −.037 .332 −.262 .938 .802 −.188 −.371c5 .117 −.040 .275 −.245 .938 .760 −.201 −.376s1 .114 −.039 .288 −.267 .730 .900 −.119 −.340s2 .106 −.046 .337 −.277 .773 .946 −.201 −.364s3 .098 −.095 .305 −.282 .761 .922 −.160 −.329s4 .120 −.022 .285 −.222 .746 .888 −.153 −.339s5 .123 −.084 .305 −.249 .803 .920 −.143 −.311e1 .102 .339 −.211 .388 −.146 −.116 .916 .467

e2 .079 .343 −.184 .373 −.114 −.097 .905 .495

e3 .071 .393 −.291 .421 −.149 −.129 .915 .571

e4 .095 .394 −.284 .405 −.181 −.163 .952 .528

e5 .055 .361 −.205 .384 −.283 −.248 .840 .600

p1 −.038 .262 −.317 .403 −.329 −.280 .613 .848

p2 −.041 .210 −.240 .361 −.370 −.378 .545 .938

p3 −.037 .271 −.284 .415 −.378 −.363 .528 .930

p4 −.041 .196 −.183 .310 −.295 −.294 .412 .873


individuals’ negative affective responses to densely popu-lated physical environments (e.g., Eroglu and Machleit1990; Hui and Bateson 1991; Noone and Mattila 2009;Stokols 1972). Future research should continue to explorethe factors that lead people to view human density aspositive, and perhaps as desirable.

Finally, affective response is often studied on a displeasure-pleasure continuum. We examined two relative extremes of(dis)pleasure in the presence of high arousal in the forms ofstress and excitement. While affect has been an important partof any number of marketing models, there has been littleresearch related to different levels of pleasure tied to highlevels of arousal. Future work may find that stress andexcitement are more predictive of consumer behaviors thanrelatively moderate levels of pleasure absent arousal.

Managerial implications

Beasty (2005) notes that retailers need to be more creativein designing experiences that attract both task-orientedbuyers and those shopping for social reasons. For manag-ers, building excitement for social shoppers while mini-mizing stress felt by task shoppers, particularly in acrowded venue, is a challenging proposition. Being ableto identify the “who” and “why” associated with task andsocial shoppers should help managers develop strategies tomeet this challenge.

Task shoppers In our study, males, particularly young men,tended to seek control and characterize themselves as taskshoppers. We found that due to a need for control, theseshoppers perceive a given level of density as crowded,consequently feel stressed, and are less likely to patronizethe mall. The basic strategy for marketing to this groupwould be to give more actual or perceived control to thecustomer in the retail setting. This has implications formarketing activities such as advertising, mall design, andthe use of technology.

In order to attract task-oriented shoppers, retailers couldutilize advertising to suggest how shoppers might control themall experience, thereby decreasing stress. For example, adscould focus on shopping during less crowded times andspecifically mention when those times are (e.g., to attractmales, place an ad in the newspaper’s sports sectionsuggesting “Shop from 6:00 pm until 9:00 pm weekdays toavoid crowds”). It would also be important for ads targetingthis group to focus on decreasing stress as opposed toincreasing enjoyment in the shopping experience.

Access control may be an important issue for taskshoppers because it could help them to complete their goalsmore easily. For example, some department stores at mallslocate their men’s departments at street level entrances,which can facilitate the goals of task shoppers who canpark, enter, and exit quickly—rather than being forced towalk through the women’s lingerie or shoe department to

Table 4 ResultsHyp Path Coeff t-value

H1 Social shopping → Task shopping −.309 5.61

H2 Shopping control → Task shopping .304 3.84

H3a Males → Shopping control .138 2.26

H3b Males → Task shopping .196 3.67

H4 Shopping frequency → Task shopping −.130 2.34

H5 Shopping intimacy → Social shopping .513 10.53

H6a Females → Shopping intimacy .074 1.35

H6b Females → Social shopping .150 3.13

H7 Shopping frequency → Social shopping .094 1.78

H8 Age → Shopping control −.193 2.21

H9 Age → Shopping intimacy −.259 4.71

H10 Task shopping → Stress .066 1.39

H11 Shopping control → Stress −.015 0.42

H12 Social shopping → Excitement .286 4.33

H13 Shopping intimacy → Excitement .263 4.18

H14 Task shopping → Perceived crowding .258 4.48

H15 Social shopping → Perceived crowding −.179 2.96

H16a Perceived crowding → Stress .807 29.00

H16b Perceived crowding → Excitement −.093 1.78

H17a Stress → Patronage intentions −.273 5.73

H17b Excitement → Patronage intentions .550 13.39


the escalator to the upper or lower floors, as happens inother stores. Similarly, lifestyle shopping centers that mirrormain streets can increase the perception of shoppingcontrol. This venue might be more effective for retailersin attracting male shoppers than being located in a mall.

North American malls and tenants have been slow toreact to the pressures of Wal-Mart, Best Buy, and Target thatfacilitate task-oriented shopping with self check-out andonline order and pick-up services (cf., Van Riper 2009).These strategies could speed up the shopping process,increase control, and limit social interaction for taskshoppers. In addition, malls and/or retailers could installkiosks (similar to the ones most airlines now use) forfinding items or providing helpful product information forthis group.

Social shoppers Our research also highlights the importanceof the social side of shopping for some customers. In ourstudy, these shoppers tended to be female and young. Socialshoppers tend to enjoy shopping and thus should be relativelyeasier than task shoppers for malls to attract. However, inmany markets competition is strong because shoppers haveaccess to multiple malls. Therefore, strategies for increasingshare of wallet are critical. Implications for attracting andkeeping this group include tenant mix and advertising.

Paying attention to the social context of a retailencounter should help malls more effectively plan andmanage tenant mix. The typical tenant mix and thestructural layout of food courts in malls, for instance, dolittle to facilitate an intimate social interchange (à laStarbucks) that would appeal to social shoppers who wantto combine a leisurely lunch with shopping. Further, whilefood courts allow task shoppers to quickly obtain food, theymust do so in what are often cramped spaces and with noprivacy from others. These dual drawbacks may in partexplain the popularity of shopping centers with a healthymix of sit-down restaurants, coffee shops, and cafes inaddition to fast food.

An approach used outside of North America aimed atappealing to social shoppers is to more purposefully make themall a place to shop and play. While the world’s ten largestmalls in 2004 included five U.S. malls, the 2009 top ten listincluded only one and featured new malls in the Middle Eastand Asia that include hotels, windmills, swimming pools,aquariums, roller coasters, and theme parks that make for moreof an attraction destination (see Van Riper 2009). Whethercertain economic (e.g., prevalence of mass transit) or cultural(family structure) issues make this approach more viableoutside of North America is an issue for further research.

Our findings suggest that advertising to social shoppersshould highlight the opportunities for social interaction andthe presence of others at the mall. For example, ads placed inyoung women’s magazines could use text and pictures to play

up the social aspects of shopping, such as enjoying socialintimacy within a crowded setting, or interacting with friendsor salespeople. Aspects of task shopping, such as conve-nience, may not be as effective in attracting social shoppers.

A risk is that individuals from either shopping camp mayrespond negatively to appeals targeted to the opposingshopper segment. However, a mall or individual store couldsimultaneously implement strategies for both groups with-out detracting from either through effective promotionstrategies and appropriate shopping center design. Forexample, retailers might target social shoppers with abrick-and-mortar store sale to generate crowds, but theycould also offer a simultaneous online promotion aimed attask shoppers (i.e., Best Buy has offered an additional 5%discount to buy online during the holiday sales) so they canavoid the mall. With respect to design and tenant layout,another example might be the case in which a mall has afood court in addition to sit-down restaurants. The mallcould locate the food court near stores where men shop tobe convenient and quick for these likely to be task shoppersand locate the sit-down restaurants near department stores,or stores targeted toward women, who tend to focus onsocial aspects of shopping.

Limitations and future research

First, we acknowledge several limitations inherent in ourresearch. The virtual method we used to place shoppers in themall setting allowed us to control density and experimentalnoise. However, this method may limit the generalizability ofour findings to actual settings. Future research would benefitfrom observing or recording reactions to perceived density atthe point of approach or exit of shopping centers and couldprovide a more accurate picture of reactions to perceiveddensity. Furthermore, different shopping contexts (discountversus upscale tenant mix) or other individual factors that wedid not examine (e.g., culture) may interact to alter reactions tothe presence of others during a shopping trip.

Future research might explore other conditions that mayaffect customers’ responses to density to verify the veracity ofthe effects found in this study. Other tenant mix situations (e.g.,clothing-dominated malls versus hardware/electronics-domi-nated shopping centers), individual differences (e.g., suscepti-bility to interpersonal influence) and retail/service type (goods-based versus service-based; including shopping at grocerystores or health care services). Finally, the type of people orclientele that make up a crowd may determine how customersrespond to density. For example, individuals may reactdifferently to crowds perceived to consist of individualssimilar to self (e.g., fans at a sporting event) compared tocrowds perceived as dissimilar (cf., Bryne, London andReeves 1968).


Future studies in consumption environments should takeinto account the likelihood of both positive and negativeconsequences of perceived human density, particularly invenues where a high level of social interaction is expectedor sought by patrons. The lack of empirical researchattention to the positive aspects of retail density suggeststhat this perspective offers an important and interestingavenue to pursue in the future. Other retailers, such asdiscounters, need to better understand the antecedents toand consequences of positive responses to density.

Theoretically, perceived crowding has been cast as anegative psychological response to human density in asetting. Consequently, measures contain a negative valence(cramped, crowded, restricted, etc.) strongly associated withnegative affect (stress), as demonstrated in this study. Whileperceived crowding and stress are conceptually distinct(Stokols 1972), future research may benefit from focusingmore on the effects of human density (the disparity betweenspace available and space demanded or deemed adequate)on stress in shopping settings.

The shopping motivations of control and intimacy couldbe investigated further. Future studies might investigate therole of these motivations outside the realm of crowding. Forexample, how might knowledge of these consumer moti-vations be used to develop sales strategies for salesassociates? What other retail outcomes might be influencedby these motivations (e.g., value, commitment)?

References

Altman, G. (1975). The environment and social behavior: Privacy,personal space, territory, and crowding. Monterey: Brooks/ColePublishing Company.

Argyle, M., & Dean, J. (1965). Eye-contact, distance and affiliation.Sociometry, 28, 289–304.

Arnold, M. J., & Reynolds, K. E. (2003). Hedonic shoppingmotivations. Journal of Retailing, 79, 77–95.

Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun:measuring hedonic and utilitarian shopping value. Journal ofConsumer Research, 20, 644–656.

Baker, J. (1987). The role of the environment in marketing services:The consumer perspective. In J. Czepiel, C. Congram, & J.Shanahan (Eds.), The services challenge: Integrating for com-petitive advantage (pp. 79–84). Chicago: American MarketingAssociation proceedings series.

Bateson, J. E. G., & Hui, M. K. (1992). The ecological validity ofphotographic slides and videotapes in simulating the servicesetting. Journal of Consumer Research, 19, 271–282.

Baum, A. R., & Davis, G. E. (1976). Spatial and social aspects ofcrowding perception. Environment and Behavior, 8, 527–544.

Beasty, C. (2005), “The Ideal Shopping Experience,” www.destinationcrm.com, January 24.

Bellenger, D. N., & Korgaonkar, P. (1980). Profiling the recreationalshopper. Journal of Retailing, 58, 58–81.

Berlyne, D. E. (1960). Conflict, arousal, and curiosity. New York:McGraw-Hill.

Bloch, P. H., Ridgway, N. M., & Dawson, S. A. (1994). The shoppingmall as consumer habitat. Journal of Retailing, 70(1), 23–42.

Boggs, L. P. (1904). An experimental study of physiologicalaccompaniments of feeling. Psychological Review, 11, 223–248.

Brown, B., Eicher, S. A., & Petrie, S. (1986). The importance of peergroup (‘crowd’) affiliation in adolescence. Journal of Adolescence,9, 73–96.

Bryne, D., London, O. & Reeves, K. (1968). The effects of physicalattractiveness, sex, and attitude similarity on interpersonalattraction. Journal of Personality, 36, 259–271.

Carr, D. (2004). The desire to date and remarry among older widowsand widowers. Journal of Marriage and Family, 66, 1051–1068.

d’Astous, A. (2000). Irritating aspects of the shopping environment.Journal of Business Research, 49, 149–156.

Darden, W. R., & Dorsch, M. J. (1990). An action strategy approach toexamining shopping behavior. Journal of Business Research, 21,289–308.

Dawson, S., Bloch, P. H., & Ridgway, N. M. (1990). Shoppingmotives, emotional states and retail outcomes. Journal ofRetailing, 66(4), 408–427.

Diehl, M., & Hay, E. L. (2010). Risk and resilience factors in copingwith daily stress in adulthood: the role of age, self-conceptincoherence, and personal control. Developmental Psychology,46, 1132–1146.

Dittmar, H., Long, K., & Meek, R. (2004). Buying on the internet:gender differences in on-line and conventional buying motiva-tions. Sex Roles, 50(5/6), 423–444.

Donovan, D. M., Smyth, L., Paige, A. B., & O’Leary, M. R. (1975).Relationships among locus of control, self-concept, and anxiety.Journal of Clinical Psychology, 31(4), 682–684.

Duehr, E. E., & Bono, J. E. (2006). Men, women, and managers: arestereotypes finally changing. Personnel Psychology, 59, 815–846.

Eroglu, S., & Harrell, G. D. (1986). Retail crowding: theoretical andstrategic implications. Journal of Retailing, 62, 346–364.

Eroglu, S., & Machleit, K. A. (1990). An empirical study of retailcrowding: antecedents and consequences. Journal of Retailing, 66,201–222.

Eroglu, S., Machleit, K. A., & Barr, T. F. (2005). Perceived retailcrowding and shopping satisfaction: the role of shopping value.Journal of Business Research, 58, 1146–1153.

Feinberg, R. A., Sheffler, B., Meoli, J., & Rummel, A. (1989). There’ssomething social happening at the mall. Journal of Business andPsychology, 4(1), 49–63.

Fiedler, F. (1967). A theory of leadership effectiveness. New York:McGraw-Hill.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equationmodels with unobserved variables and measurement error.Journal of Marketing Research, 18, 39–50.

Gaumer, C. J., & LaFief, W. C. (2005). Social facilitation: affect andapplication in consumer buying situations. Journal of FoodProducts Marketing, 11(1), 75–82.

Greenberger, D. B., Strasser, S., & Lee, S. (1988). Personal control as amediator between perceptions of supervisory behaviors and em-ployee reactions. Academy of Management Journal, 31, 405–417.

Grewal, D., Baker, J., Levy, M., & Voss, G. (2003). The effects of waitexpectations and store atmosphere evaluations on patronageintentions in service-intensive retail stores. Journal of Retailing,79(4), 259–268.

Grossbart, S., Hampton, R., Rammohan, B., & Lapidus, R. S. (1990).Environmental dispositions and customer response to storeatmospherics. Journal of Business Research, 21(3), 225–241.

Guthrie, J. P., Coate, C. J., & Schwoerer, C. E. (1998). Careermanagement strategies: the role of personality. Journal ofManagerial Psychology, 13(5/6), 371–386.


http://www.destinationcrm.com

http://www.destinationcrm.com

Hair, J. F., Ringle, C.M., & Sarstedt, M. (2011). PLS-SEM: indeed a silverbullet. Journal of Marketing Theory and Practice, 19, 139–151.

Hall, E. T. (1964). Silent assumptions in social communication.Disorders of Communication, 42, 41–55.

Hardison, J., & Purcell, K. (1959). The effects of psychological stressas a function of need and cognitive control. Journal ofPersonality, 27(2), 250–258.

Harrell, G. D., & Hutt, M. D. (1976). Crowding in retail stores. MSUBusiness Topics, 24, 33–39.

Harrell, G. D., Hutt, M. D., & Anderson, J. C. (1980). Path analysis ofbuyer behavior under conditions of crowding. Journal ofMarketing Research, 17, 45–51.

Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption:emerging concepts, methods and propositions. Journal ofMarketing, 46, 92–101.

Hui, M. K., & Bateson, J. E. G. (1991). Perceived control and theeffects of crowding and consumer. Journal of ConsumerResearch, 18, 174–185.

Josephs, R. A., Markus, H. R., & Tafarodi, R. W. (1992). Gender andself-esteem. Journal of Personality and Social Psychology, 63,391–402.

Kish, G. B., Woody, M. M., & Frankel, A. (1977). The development ofa scale to measure task completion motivation. Journal ofClinical Psychology, 33(1), 133–138.

Kuethe, J. L. (1962). Social schemas and the reconstruction of socialobject displays from memory. Journal of Abnormal and SocialPsychology, 65, 71–742.

Langer, E. J. (1983). The psychology of control. Beverly Hills: Sage.Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal and coping.

New York: Springer.Leondari, A., & Gonida, E. (2007). Predicting academic self-

handicapping in different age groups: the role of personalachievement goals and social goals. British Journal of Educa-tional Psychology, 77, 595–611.

Levy-Tossman, I., Kaplan, A., & Assor, A. (2007). Academic goalorientations, multiple goal profiles and friendship among earlyadolescents. Contemporary Educational Psychology, 32, 231–252.

Lewin, K. (1935). Psycho-sociological Problems of a Minority Group.Character and Personality, III, I75–187. 2I.

Lewin, K. (1939). Field theory and experiment in social psychology:concepts and methods. The American Journal of Sociology, 44,868–896.

Livingston, J. A. (1999). Something old and something new: love,creativity, and the enduring relationship. Bulletin of the Men-ninger Clinic, 99(63), 40–52.

Machleit, K. A., Kellaris, J. J., & Eroglu, S. A. (1994). Human vs.spatial dimensions of crowding perceptions in retail environ-ments: a note on their measurement and effect on shoppersatisfaction. Marketing Letters, 5(2), 183–194.

Machleit, K. A., Eroglu, S. A., & Mantel, S. P. (2000). Perceived retailcrowding and shopping satisfaction: what modifies this relation-ship? Journal of Consumer Psychology, 9(1), 29–42.

Mansfield, A. K., Addis, M. E., & Courtenay,W. (2005). Measurement ofmen’s help seeking: development and evaluation of the barriers tohelp seeking scale. Psychology of Men & Masculinity, 6, 95–108.

Maroda, K. J. (2004). A relational perspective on women and power.Psychoanalytic Psychology, 21, 428–435.

Matthews, G., & Campbell, S. E. (2009). Sustained performanceunder overload: personality and individual differences in stressand coping. Theoretical issues in Ergonomics Science, 10(5),417–442.

McClelland, D. C. (1953). The achievement motive. New York:Appleton.

McClelland, D. C., & Burnham, D. (1976). “Power is the GreatMotivator.” Harvard Business Review (1976), 101–108.

McGuire, W. J. (1974). Psychological motives and communicationgratification. In J. G. Blumler & E. Katz (Eds.), The uses of masscommunications: Current perspectives on gratifications research(pp. 167–196). Beverly Hills: Sage.

Mehrabian, A., & Russell, J. A. (1974). An approach to environmentalpsychology. Cambridge: MIT.

Menz, F. C., & Mullen, J. K. (1981). Expected encounters andwillingness to pay for outdoor recreation. Land Economics, 57(1), 33–40.

Midgley, C., Anderman, E. M., & Hicks, L. (1995). Differencesbetween elementary and middle school teachers and students.Journal of Early Adolescence, 15, 90–113.

Nanney, R. C. (2009). “Dead Malls: Suburban Planning Nightmare orOpportunity?” www.buildingplace.com, May 25.

Nicholls, J. A. F., Li, F., Kranendonk, C. J., & Roslow, S. (2002). Theseven year itch? Mall shoppers across time. Journal of ConsumerMarketing, 19(2), 149–165.

Noone, B. M., & Mattila, A. S. (2009). Consumer reaction tocrowding for extended service encounters. Managing ServiceQuality, 19(1), 31–41.

Otnes, C., & McGrath, M. A. (2001). Perceptions and realities of maleshopping behavior. Journal of Retailing, 77, 111–137.

Peay, M. Y., & Peay, E. R. (1983). The effects of density, group size,and crowding on behavior in an unstructured situation. BritishJournal of Social Psychology, 22, 13–18.

Pedersen, D. M., & Shears, L. M. (1973). A review of personal spaceresearch in the framework of general systems theory. Psycholog-ical Bulletin, 80(5), 367–388.

Pons, F., & Laroche, M. M. (2007). Cross-cultural differences in crowdassessment. Journal of Business Research, 60(3), 269–276.

Pons, F., Laroche, M. M., & Mourali, M. (2006). Consumer reactionsto crowded retail settings: cross-cultural differences betweenNorth American and the Middle East. Psychology and Market-ing, 23(7), 555–572.

Prus, R., & Dawson, L. (1991). Shop ’til you drop: shopping asrecreational and laborious activity. Canadian Journal of Sociol-ogy, 16(2), 145–164.

Ray, J. J. (1973). Task orientation and interaction orientation scales.Personnel Psychology, 26, 61–73.

Reynolds, K. E., & Beatty, S. E. (1999). A relationship customertypology. Journal of Retailing, 75(4), 509–523.

Ringle, C. M., Wende, S., & Will, A. (2005). SmartPLS 2.0, Hamburg,http://www.smartpls.de.

Russell, J. A., & Pratt, G. (1980). A description of the affective qualityattributed to environments. Journal of Personality and SocialPsychology, 38(2), 311–322.

Russell, J. A., Ward, L. M., & Pratt, G. (1981). Affective qualityattributed to environments. Environment and Behavior, 13(3),259–288.

Saegert, S., Mackintosh, E., & West, S. (1975). Two studies of crowdingin urban public space. Environment and Behavior, 7, 159–184.

Smith, A. D., & Rupp, W. T. (2003). Strategic online customerdecision making: leveraging the transformational power of theinternet. Online Information Review, 27(6), 418–432.

Sommer, R. (1959). Studies in personal space. Sociometry, 22, 247–260.

Sommer, R. (1965). Further studies in small group ecology. Psycho-logical Bulletin, 67, 145–152.

Sommer, R. (1967). Small group ecology. Sociometry, 28, 337–348.Stafford, M. R. (1996). Tangibility in services advertising: an

investigation of verbal versus visual cues. Journal of Advertising,25, 13–28.

Stewart, G. L., & Manz, C. C. (1995). Leadership for self-managingwork teams: a typology and integrative model. Human Relations,48, 747–770.


http://www.buildingplace.com

http://www.smartpls.de

Stokols, D. (1972). On the distinction between density and crowding:some implications for future research. Psychological Review, 79,275–277.

Szymanski, D. M., & Henard, D. H. (2001). Customer satisfaction: ameta-analysis of the empirical evidence. Journal of the Academyof Marketing Science, 29, 16–35.

Tamir, M., Chiu, C.-Y., & Gross, J. J. (2007). Business or pleasure?Utilitarian versus hedonic considerations in emotion regulation.Emotion, 7, 546–554.

Tauber, E. M. (1972). Why do people shop? Journal of Marketing, 36,46–59.

Thériault, J. (1998). Assessing intimacy with the best friend and thesexual partner during adolescence: the PAIR-M inventory. TheJournal of Psychology, 132(5), 493–506.

Vachon, D. D., & Bagby, M. R. (2009). Pathological gamblingsubtypes. Psychological Assessment, 21, 608–615.

Van Riper, T. (2009). “The World’s Largest Malls,” Forbes.com,(January 15).

Van Wagner, K., & Swanson, C. (1979). From Machiavelli to Ms:differences in male-female power styles. Public AdministrationReview, 39, 66–72.

Wakefield, K. L., & Baker, J. (1998). Excitement at the mall:determinants and effects on shopping response. Journal ofRetailing, 74, 515–539.

Wakefield, K. L., & Blodgett, J. G. (1999). Customer response tointangible and tangible service factors. Psychology & Marketing,16, 51–68.

Wesley, S. C., LeHew, M. A., & Woodside, A. (2006). Consumerdecision-making styles and mall shopping behavior: buildingtheory using exploratory data analysis and the comparativemethod. Journal of Business Research, 59(5), 535–548.

Westbrook, R. A., & Black, W. C. (1985). A motivation-based shoppertypology. Journal of Retailing, 61, 78–103.

Worchel, S., & Yohai, S. M. L. (1979). The role of attribution in theexperience of crowding. Journal of Experimental Social Psy-chology, 15, 91–104.


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