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    The differential effects of retail density: An investigation of goods versus service settings

    Yue Pan a,,1, Jennifer Christie Siemens b,1,2

    a 812 Miriam Hall, University of Dayton, 300 College Park, Dayton, OH 45469-2271, United Statesb 810 Miriam Hall, University of Dayton, 300 College Park, Dayton, OH 45469, United States

    a b s t r a c ta r t i c l e i n f o

    Article history:

    Received 26 December 2008

    Accepted 10 February 2010

    Keywords:

    Crowding

    Density

    Retail

    Goods

    Services

    Two studies investigate the impact of retail density and time pressure on shoppers' store attitudes and

    behavioral intentions. In a goods setting, experiment 1 results show a curvilinear pattern as the level of retail

    density increases. That is, individuals prefer a medium level of crowding to a store with low or high

    crowding. This inverted-U shaped crowding effect has not previously been tested in the retailing literature.

    Experiment 2 employs a service setting, where the relationship between retail crowding and outcome

    variables is found to be linear rather than curvilinear, except under conditions of time pressure. In contrast to

    the goods setting, individuals have more favorable attitudes and expect to pay more for a service as the level

    of crowding increases. Thus, our study ndings suggest that the optimal level of crowding depends on the

    type of retail setting.

    2010 Elsevier Inc. All rights reserved.

    1. Background

    Several studies have investigated consumption under conditions

    of crowding, suggesting that a crowded environment can lead to

    attributions of resource scarcity (Jain, 1987), stress (Stokols, 1978),and negative shopping behavior (Harrell et al., 1980). The crowding

    literature seems to converge on an information processing explana-

    tion, positing that people experience information overload under high

    density conditions (Eroglu and Machleit, 1990). Confronted with

    inadequate space, a person feels reduced control over the situation

    and experiences stress and arousal that, in turn, eventuate in feelings

    of being crowded (Rustemli, 1992).Rompay et al. (2008)suggest that

    perceived control mediates the effects of spatial density on pleasure

    and approach behaviors, and there is an overall negative relation

    between spatial density and perceived control.

    Manning Theory in ecological psychology (Barker, 1963), investi-

    gates the behavioral and cognitive consequences ofundermanning,

    a condition where store personnel are fewer than the number

    typically required to maintain a setting at an expected, optimal

    level. Extreme undermanning may produce a sense of hopelessness

    and frustration, adversely affecting staff attitudes and behaviors

    (Vecchio and Sussmann, 1981). Perception of crowding is often

    associated with the scarcity of resources (e.g., spatial restrictions,

    understaffed store) and its subsequent negative outcomes (e.g., poor

    service), feeling cramped, and loss of control and privacy. Retail

    crowding has been shown to reduce shopping satisfaction and lead to

    avoidance behavior (Eroglu and Machleit, 1990; Machleit et al., 1994;

    Pons et al., 2006; Pons and Laroche, 2007).

    Conversely, low levels of crowding are also undesirable in shapingshopping expectations. Shoppers often rely on simple, easily acces-

    sible social cues for forming inferences about product value when

    they lack the time to examine complex information, or when such

    information is lacking (Baker et al., 1994; Bloom, 1990). Similarly,

    categorization theory states that consumers use available information

    (e.g., crowding) to help them draw inferences about possibly missing

    information (e.g., price, quality) by comparing the target stimulus

    with their category knowledge (Baker, 1998). Thus, shoppers may

    gauge the attractiveness of a store by the number of people shopping

    there. Similarly, marketing semiotics proposes that the store

    environment provides symbols that may characterize product

    attributes. A retail outlet with few patrons may present an image of

    being overpriced, having poor product quality, or simply unappealing

    merchandise. Conceptual and empirical support for the symbolic

    nature of store environmental cues abounds in the literature (e.g.,

    Baker, 1998; Baker et al., 1988; Bitner, 1990; Grossbart et al., 1990).In

    summary, low retail density may incur negative perceptions of the

    store and hence less motivation to patronize the retailer. However,

    too many shoppers could also be undesirable. Beyond a threshold,

    crowding may be seriously dysfunctional, whereby shoppers may

    experience high cognitive demands and frustration.

    Surprisingly, few controlled studies have investigated medium

    levelsof crowding. Instead, research hasfocused on conditions of high

    crowding and the subsequent negative consequences of such. Are

    there times when a moderately crowded setting can lead to more

    favorable results? A medium level of crowding might enhance an

    Journal of Business Research 64 (2011) 105112

    Corresponding author. Tel.: +937 2291773; fax: +937 229 3788.

    E-mail addresses:[email protected](Y. Pan),

    [email protected](J.C. Siemens).1 Authors' names are listed alphabetically. Both authors contribute equally to this

    study.2 Tel.: +937 229 1086; fax: +937 229 3788.

    0148-2963/$ see front matter 2010 Elsevier Inc. All rights reserved.

    doi:10.1016/j.jbusres.2010.02.011

    Contents lists available at ScienceDirect

    Journal of Business Research

    http://-/?-http://-/?-http://-/?-mailto:[email protected]:[email protected]://dx.doi.org/10.1016/j.jbusres.2010.02.011http://www.sciencedirect.com/science/journal/01482963http://www.sciencedirect.com/science/journal/01482963http://dx.doi.org/10.1016/j.jbusres.2010.02.011mailto:[email protected]:[email protected]://-/?-http://-/?-http://-/?-
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    individual's attitude toward the store, increasing their behavioral

    intentions. Although they do not empirically test it, Eroglu et al.

    (2005) suggest that there is a general positive effect of human

    crowding on shopping satisfaction after certain mediating variables

    are accounted for. They propose that there might be an inverted-U

    relationship between crowding and satisfaction, whereby an ex-

    tremely crowded or uncrowded condition will be undesirable. While

    Michon et al. (2005)measure high, medium, and low crowding, they

    focus on the effects of ambient odor as an atmospheric variable. Thepurpose of this research is to further investigate the possibility of a

    desirable density level for retail settings, specically whether a

    curvilinear relationship between crowding and shopping outcomes

    exists.

    2. Exploratory study

    First, an exploratory study was conducted in foundational business

    classes. Students were given class credit as an incentive for

    participation (n =48). They received an email from the researcher,

    randomly directing them to one of three websites where they read a

    brief introduction to the study and were asked to imagine themselves

    leisurely browsing the stores. Participants were then shown one

    picture of a clothing store, which contained either low, medium, orhigh crowding. Participants were instructed to write down any

    thoughts they had about the store and their potential to shop there.

    2.1. Stimulus development and pretest

    In order to present participants with realistic shopping environ-

    ments to evaluate, three photos were developed with varying degrees

    of crowding. Using photographs as a manipulation of perceived retail

    crowding, a common method in the marketing literature, has been

    shown to have ecological validity (Bateson and Hui, 1992; Eroglu and

    Machleit, 1990). When choosing the retail establishment, careful

    consideration was made regarding the merchandise selection, layout

    and location of the store. In order to eliminate bias from prior

    experience with a recognized store,the chosenstorewas in a differentstate and was not a chain retailer. The store contained both men's and

    women's clothing so that merchandise type would not bias store

    perception. Shopping volunteers were recruited for the pictures,

    which enabled control over the picture content and layout. Thirteen

    pictures of varying levels of crowdedness were used in a pretest.

    Pretest subjects (n =89) were presented with all thirteen pictures

    and were asked to evaluate them with three, seven-point likert items

    with endpoints strongly disagree/strongly agree: The store seems

    very crowded to me, The store is very busy,and There are a lot of

    customers in the store (Machleit et al., 1994). Three color photos

    were chosen based on their signicantly different results for the likert

    items. These photos were shot from the same area of the store, with

    the same type of merchandise shown in each picture. This allows

    control over crowding perceptions due to differences in spatialdensity. These photos show varying degrees of human density (from

    one shopper to ve shoppers).

    2.2. Exploratory study analyses and results

    Half of the respondents exposed to a low crowding picture

    (n =8) indicated no interest in shopping in the clothing store. Of the

    16 respondents who viewed a highly crowded store, the majority

    (n =12) expressed no intention to enter the store. A review of the

    responses revealed their negative feelings towards the store (e.g.,

    messy, unkempt,and not well-maintained).

    In contrast, of the 16 respondents assigned to the medium

    crowding level, the majority indicated favorable attitudes (n =13) or

    intentions (n =12) toward the store. Positive adjectives such as

    sophisticated, classy, organized, and rened were use to

    describe the store.

    In summary, this exploratory study reveals differences in store

    perceptions and purchase intentions across the three crowding levels.

    While respondents were not asked to specically examine retail

    density, their open-ended responses suggested that crowding level

    was an important factor. The preliminary ndings provide the

    foundation for a controlled experiment. Specically, the following

    hypotheses are offered:H1. The effect of retail density on subjects' intentions to enter a store

    will follow an inverted-U shaped trend, where intention to enter is

    greatest when the store exhibits a medium level of crowding

    compared to either low or high crowding levels.

    H2. H2a) The effect of retail density on subjects' intentions to

    browse in a store will follow an inverted-U shaped trend,

    where intention to browse is greatest when the store

    exhibits a medium level of crowding compared to either

    low or high crowding levels.

    H2b) Furthermore, subjects will intend to browse longer in the

    retail store when there is a medium level of crowding

    compared to low or high levels.

    H3. The effect of retail density on subjects' attitudes toward the store

    will follow an inverted-U shaped trend, where attitudes are more

    positive when the store exhibits a medium level of crowding

    compared to either low or high crowding levels.

    H4. The effect of retail density on subjects' purchase intentions will

    follow an inverted-U shaped trend, where intention to purchase is

    greatest when the store exhibits a medium level of crowding

    compared to either low or high crowding levels.

    However, these proposed relationships are subject to an important

    caveat. Reactionsto crowding arenot the same for all people, and may

    depend on other environmental factors. Crowding is experienced

    when the environment is judged as being dysfunctionally dense; thesejudgments will vary across individuals depending on factors such as

    time pressure (Eroglu and Harrell, 1986). Time-constrained shoppers

    may be more sensitive to crowded conditions (Eroglu and Machleit

    1990), and may view crowding more negatively as it prevents

    effective goal achievement. As such, we propose that as the amount of

    time pressure increases, the negative impact of retail crowding on

    shopping attitudes and intentions is likely to be enhanced.

    H5. Time pressure will interact with retail density for all dependent

    measures. Under the condition of time pressure, the effect of retail

    density on subjects'

    H5a) intentions to enter the store,

    H5b) intentions to browse in the store,

    H5c) attitudes toward the store andH5d) purchase intentions will follow a negative linear trend.

    Generally, subjects will generally prefer a less crowded

    store under conditions of time pressure.

    3. Experiment 1

    3.1. Subjects, design and procedure

    Subjects were 270 undergraduates at a Midwestern university(see

    Table 1 for demographics). Subjects were randomly assigned to one of

    six conditions in a 2 (no time pressure vs. time pressure)3 (high,

    medium, and low crowding) between-subjects design. Written

    instructions were read by the experimenter to ensure equality of

    106 Y. Pan, J.C. Siemens / Journal of Business Research 64 (2011) 105112

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    experience across conditions. Subjects read the following shopping

    scenario: It is Saturday and you are browsing the stores. You are

    thinking of buying something. However, since this day is not the only

    stretch of time that you can devote to shopping, you are in no hurry

    (no time pressure conditions). For subjects assigned to the timepressure condition, they instead read, Since this day is the only

    stretch of time that you can devote to shopping, you are pressed for

    time and are in a hurry.They were presented with one of the three

    pretested retail photos, and then answered the dependent measures.

    3.2. Dependent measures

    Attitude towardsthe store wasassessedwith a six-item, seven-point

    semantic differential scale. Intentions to enter the store, browse, and

    make a purchase were assessed with separate three-item, seven-point

    scales (seeTable 2). Participants were also asked to list the length of

    time in minutes that they would spend shopping in the store.

    The measurement model was assessed for convergent and

    discriminant validity. The joint con

    rmatory factor analysis (CFA)lends strong support to the convergent validity of all measures (see

    Table 2). CFA results show an acceptable model t (2(125)=242.71,

    pb0.001; CFI =0.988; RMSEA=0.062; SRMR= 0.067). Thus, the

    proposed model (i.e., joint CFA with all constructs included simulta-

    neously) provides a reasonable explanation of the observed covari-

    ance among the constructs. All estimated item loadings are signicant

    (pb0.05) and greater than the recommended 0.6 cutoff (Bagozzi and

    Yi, 1988). Furthermore, all constructs show satisfactory levels of

    average variance extracted (with all AVE's above the recommended

    0.5 level,Fornell and Larcker, 1981) and composite reliability (all CR's

    higher than the 0.7 cutoff recommended byNunnally and Bernstein,

    1994). The internal validity of the measurement model seems

    adequate. We then conduct Fornell and Larcker's (1981) test for

    discriminant validity by comparing the AVE estimates for each

    construct with the squared correlation between any two constructs.

    All AVEs are larger than any squared correlation between any two

    constructs. Therefore, discriminant validity is established. Intolerance

    for crowding was identied as a potential covariate (Machleit et al.,

    2000, 3-item, e.g., I avoid crowded stores whenever possible).

    Table 1

    Demographic characteristics of respondents.

    Experiment 1 (n =270) Experiment 2 (n =403)

    Demographic characteristics Frequency/Mean Frequency/Mean

    Gender

    Female 125 209

    Male 144 194

    Age 21.2 27.6

    Household income

    0$20,000 (%) 4 93

    $20,001$40,000 (%) 17 14

    $40,001$60,000 (%) 28 18

    $60,001$80,000 (%) 36 41

    $80,001$100,000 (%) 43 67

    Over $100,000 (%) 132 155

    Table 2

    Construct measures and CFA results.

    Experiment 1 Experiment 2

    Construct, scale items, and source Factor loadings CR AVE Factor loadings CR AVE

    Store attitude (Golden et al., 1987) 0.915 0.63 0.922 0.67

    The retail store/salon shown in the picture is:

    Unfavorablefavorable 0.844 0.869Badgood 0.860 0.883

    Not likablelikable 0.866 0.883

    Uninterestinginteresting 0.622 0.723

    Unpleasantpleasant 0.806 0.824

    Low-qualityhigh-quality 0.718 0.698

    Intention to enter (based onSpears and Singh, 2004)

    How likely would you be to enter the store/salon shown in the picture? 0.960 0.83 0.968 0.91

    Denitely notdenitely 0.888 0.931

    Not very likelyvery likely 0.931 0.983

    Probably notprobably 0.915 0.946

    Intention to browse (based onSpears and Singh, 2004)

    How likely would you be to browse in the store shown in the picture? 0.971 0.86

    Denitely notdenitely 0.913

    Not very likelyvery likely 0.942

    Probably not

    probably 0.923

    Purchase intention (based onSpears and Singh, 2004) 0.964 0.84

    How likely would you be to buy something from the store shown in the picture?

    Denitely notdenitely 0.892

    Not very likelyvery likely 0.962

    Probably notprobably 0.901

    Crowding perception (Machleit et al., 1994) 0.905 0.73 0.910 0.77

    The store/salon seems very crowded to me. 0.831 0.814

    The store/salon is very busy. 0.919 0.959

    There are a lot of customers in the store/salon. 0.808 0.854

    Intention to recommend (based on Spears and Singh, 2004) 0.951 0.87

    How likely would you be to recommend this salon to a friend?

    Denitely notdenitely 0.913

    Not very likelyvery likely 0.984

    Probably notprobably 0.894

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    Finally, a manipulation check was conducted to ensure the treatment

    of store crowding was effective. A one-way ANOVA was signicant,

    and LSD post-hoc tests showed signicant differences across all three

    levels of crowding (F (2, 266)=114.68, pb0.001; Mlow crowd =2.2,

    Mmid crowd =2.6 and Mhigh crowd =4.8). This indicates that the

    crowding manipulation was successful.

    3.3. Results

    MANOVA with LSDpost-hoccomparisonswas used for all analyses

    unless otherwise noted. The overall MANOVA was signicant for both

    crowding level (F(10, 468)= 3.32,pb0.001) and time pressure (F(5,

    234)=11.48,pb0.001, seeTables 3 and 4). In support ofH1, subjects

    exhibited a greater intention to enter the store under the medium

    density condition compared to the low or high crowding conditions

    (pb0.001). Furthermore, intentions to enter the store increased

    between the low and medium density conditions but then decreased

    as density reached a high level. Post-hoc comparisons revealed

    signicant differences in intentions to enter thestorebetween thelow

    and medium crowding conditions, and the medium and highcrowding conditions (p'sb0.001). Intention to enter the store did

    not signicantly differ between the low and high crowding condi-

    tions. This demonstrates support for the inverted-U relationship

    proposed inH1.

    Supporting H2a, intentions to browse were greatest under

    conditions of medium crowding. Intentions to browse increased

    between the low and medium density conditions, but then decreased

    in the high crowding condition. Post-hoc comparisons showed a

    signicant difference in intentions to browse between the low and

    medium crowding conditions and between the medium and high

    crowding conditions (p'sb0.001, Fig. 1). Furthermore, individuals

    were equally likely to browse in the store under conditions of low and

    high crowding (ns).

    Intolerance for crowding was signicantly correlated with thedependent measure of intentionto browse, and thus wasassessedas a

    covariate. ANCOVA results showed a signicant effect of crowding

    level on intention to browse (F (2, 255)=9.31, pb0.001). Respon-

    dents intended to browsesignicantly longerwhen crowding wasat a

    medium level compared to either low or high crowding levels

    (p'sb0.001,Mlow =9 min,Mmed =14 min,Mhigh =11 min). This sup-

    portsH2b.

    A signicant effect of retail crowding on attitudes toward the store

    was also found (pb0.01). Despite an inverted-U shaped pattern,

    attitudeswere equally positive in both the low and medium crowding

    conditions. Post-hoc comparisons demonstrated that store attitudes

    were signicantly different between the medium and high (pb0.001)

    and the low and high crowding conditions (pb0.05), but were not

    signicantly different between the low and medium crowding

    conditions (seeFig. 1).

    Finally, the results indicated a signicant effect of retail crowding

    on purchase intentions (pb0.001). Post-hoc comparisons showed a

    signicant difference between low and medium crowding conditions,

    and between the medium and high crowding conditions (p'sb0.001,

    Fig. 1), whereas individuals were equally likely to make a purchase

    under conditions of low and high crowding (ns). Therefore,H4is also

    supported. The overall MANOVA shows no interaction between

    crowding and time pressure (p =0.13), refuting H5. Regardless ofwhether subjects were in a hurry, they always preferred the medium-

    crowded store.

    3.4. Discussion

    Although they only examine two levels of human density

    crowding,Machleit et al. (2000) lead to speculation about a oor

    and ceiling effectof retail crowding. Eroglu et al. (2005) also propose

    that some level of human crowding might positively affect shopping

    satisfaction. However, neither of these studies assesses the boundaries

    of this effect or empirically substantiates the claim. Most prior

    research on crowding compares two crowding dimensions: low

    versus high (e.g., Eroglu and Machleit, 1990; Rustemli, 1992; Machleit

    et al., 2000). These studies have led to the general conclusion that asretail density increases, consumers encounter conditions that nega-

    tively affect their shopping experience.

    The results of study 1 show that a medium level of crowding may

    actually be optimum for retailers. In fact, the effect of retail crowding

    on subjects' intentions to enter the store, intentions to browse in the

    store, length they intended to browse, and purchase intentions each

    exhibited a curvilinear trend, where shopping outcomes became most

    positive when retail density was moderate. As retail density reaches a

    high level, consumers start to exhibit more negative attitudes and

    shopping intentions. These ndings have implications for retailers

    who attempt to maximize consumers' shopping experience and their

    perceptions of the store. Factors such as store layout and other

    atmospherics can affect the level of perceived crowding, and can be

    manipulated to create an optimal shopping environment.

    Table 4

    Experiment 1 mean values.

    No time pressure Time pressur e

    Dependent measures Low

    crowd

    Medium

    crowd

    High

    crowd

    Low

    crowd

    Medium

    crowd

    High

    crowd

    Store attitude 5.1 5.1 4.3 3.6 4.3 3.8

    Purchase intention 3.1 3.7 2.8 3.4 4.1 3.1

    Intention to enter 3.7 4.5 3.4 3.6 4.3 3.4

    Intention to browse 3.6 4.4 3.6 3.3 4.3 3.3

    Length of browse 11.1 14.0 8.7 11.4 14.8 8.5

    Note. Higher means indicate more favorable ratings. Length of browse means are

    reported in minutes.

    Fig. 1.Experiment 1 results.

    Table 3

    Experiment 1 ANOVA/ANCOVA results.

    F-values anddffor dependent variables

    Independent variables Store

    attitude

    Intention

    to enter

    Purchase

    intention

    Intention

    to browse

    Length of

    browse

    Covariate:

    Crowd tolerance 5.95a

    (1, 255)

    Crowding level 6.04

    b

    9.14

    c

    10.86

    c

    9.52

    c

    9.31

    c

    (2, 255) (2, 245) (2, 245) (2, 244) (2, 255)

    Time pressure 43.51c 0.46 3.84 1.21 0.04

    (1, 255) (1, 245) (1, 245) (1, 244) (1, 255)

    Time pressure

    crowding

    4.51a 0.01 0.25 0.11 0.02

    (2, 255) (2, 245) (2, 245) (2, 244) (2, 255)

    a pb0.05.b pb0.01.c pb0.001.

    108 Y. Pan, J.C. Siemens / Journal of Business Research 64 (2011) 105112

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    A potential limitation ofExperiment 1 istheuseof onlyonetype of

    retail environment. While Experiment 1 investigated the effects of

    retail density within a store selling a tangible product (clothing),

    there may be conditions inherent to a goods setting that are different

    from a service setting. For example, in a crowded retail store selling

    tangible products, a consumer may make inferences about how

    difcult it would be tond what they are looking for, get waited on by

    the salesperson, or check out with their purchase. This may explain

    why individuals view a high level of retail crowding as undesirable.But do the same inferences occur in service settings? Whether

    consumers are purchasing a good or service may determine the

    degree of informational value of the store environmental cues.

    According to Baker (1998), store environment is more likely to have

    a pivotal role in the purchase of services for two reasons. First, the

    intangible nature of services makes it harder for consumers to assess

    value obtained before purchase and consumption. Second, because a

    service involves simultaneous production and consumption,consumers

    often have to enter the service facility. Therefore, retail density not only

    provides extrinsic cues to consumers, it also becomes an intrinsic cue

    that forms parts of the total service experience.

    Well-established differences between tangible and intangible

    products lead to a general expectation that reasons for patronizing a

    store in a service setting might differ from those in a goods setting. For

    example, services are generally inseparable from the service provider,

    do not have inventory, and are nonperishable. In service settings, one

    could make an appointment for service, reducing the likelihoodthat the

    level of crowding will affect the timeliness of service. Furthermore, in

    goods settings, customers mayfeel like they are essentially competing

    for products (i.e., if there are too many people in the store, it might

    reduce the chance that they get the product they want). Previous

    research suggests that products/stores desirability may decrease as a

    resultof productscarcitybecausebuyers cannotachieve a high degreeof

    personal uniqueness (e.g.,Gierl et al.,2008; Worchel, 1992). Consumers,

    by buying a product, equate themselveswithmany other owners of the

    same product. The need to compete with fellow shoppers for a product

    may inhibit many from patronizing a crowded retail outlet. However,

    the outlook for a crowdedservice provider canbe very different. Ponset

    al. (2006) nd that conditions of high human density may enhance,rather than harm, consumer experience in leisure services.

    Among the few studies that have mentioned an enhancement of

    the service experience as a result of the presence of other consumers

    in the service setting (e.g., Eastman and Land, 1997; Holt, 1995; Pons

    et al., 2006; Price et al., 1995), all have essentially dealt with

    experiential and hedonic consumption (e.g., sports spectatorship,

    bars). We suspect that the positive inuence of crowds on consumers'

    service experience can be extended beyond the context of hedonic

    services, for the following reasons. First, services cannot be invento-

    ried and demand may not be easily predicted. Waiting before

    receiving a service is a common experience (Baker and Cameron,

    1996), and customersmay be more tolerant of crowding in stores that

    offer services than those that carry goods. Second, retail density in a

    service setting signals the desirability of services provided, with anunderstanding that they do not necessarily need to face the

    dysfunctional consequences of crowding. For example, shoppers can

    avoid the adverse effects of crowding by setting an appointment and

    visiting the store at a less busy time. Third, there is less likelihood that

    consumers need to compete for a service. Unlike goods that typically

    come in limited supply, services can last forever as long as the

    provider continues its operation. In a goods setting, scarcity increases

    with each sold unit. Shoppers may undergo pressure to strive for the

    goods when they perceive a limitation of available units. Scarcity due

    to supply is not a concern for services. Therefore, we propose that

    shoppers' adaptation strategy will differ in a highly crowded service

    context. Avoidance behavior is less likely to occur, and favorable

    feelings towards a service provider are more likely to be evoked.

    Hence, the relationship between crowding and satisfaction will be

    linear in a service setting, where consumers' affective evaluation

    becomes more positive as density increases. Specically, we propose:

    H6. In the service setting, the effect of retail density on intentions to

    enter the store will follow a linear trend. That is, intentions to enter

    the store will increase as the level of retail density increases.

    H7. In the service setting, the effect of retail density on intention to

    recommend the store to a friend will follow a linear trend. That is,

    intention to recommend will increase as the level of retail densityincreases.

    H8. In the service setting, the effect of retail density on attitudes

    toward the store will follow a linear trend, where attitudes become

    more positive as the level of retail density increases.

    We chose to again assess the time pressurecrowding interaction

    in the service setting. As argued earlier, the negative effects of

    crowding may be more pronounced when consumers are under time

    constraints than when they are not. Therefore, we propose the

    following hypotheses:

    H9. In the service setting, time pressure will interact with retail

    density. For shoppers under time pressure, the effect of retail densityon their

    H9a) intention to enter the store,

    H9b) intention to recommend the store, and

    H9c) attitudes toward the store will exhibit an inverted-U

    shaped trend. That is, subjects will prefer a medium level

    of crowding when they are under time constraints.

    While attitude toward and intention to enter the store remain

    consistent with those tested in Experiment 1, here the variable

    intention to recommend was included to assess shoppers' behav-

    ioral consequences. This variable replaces two outcome variables (i.e.,

    purchase intention and intention to browse in the store) used in

    Experiment 1, due to the unique features of a service environment

    (e.g., consumers aren't likely to browse in a service setting, andpurchase intention is assumed based on entrance to the store). This

    outcome variable is more appropriate for use in a service setting.

    4. Experiment 2

    4.1. Pretest

    A pretest was conducted to test the manipulation of crowding in

    the service setting (n =59). As inExperiment 1, three photographs of

    a hair salon were selected. Pretest subjects saw a photograph andread

    a description of a service scenario ranging from one to four customers.

    The low crowding condition showed and described only one salon

    customer. The medium crowding condition showed and described

    one customer waiting to get her nails done and one customer havinghis hair washed.The high crowding condition showed and described

    onecustomerwaiting to get her nails done, one getting a haircut, one

    getting his hair washed, and still another customer waiting to be

    served. Perception of crowding was measured with a three-item,

    seven-point likert scale (Cronbach alpha=0.79). Subjects perceived

    signicant differences in crowdedness across the three treatment

    levels (F(2, 56)=27.64,pb0.001).

    4.2. Subjects, design and procedure

    Experiment 2 employed a 3 (low, medium, and high crowding)2

    (time-pressured vs. non-time-pressured) between-subjects design.

    Participants were faculty, staff and students at two Midwestern

    universities. Subjects were sent a mail survey to their campus address

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    and were instructed to return the completed questionnaire in a self-

    addressed, postage-paid envelope. As an incentive to participate,

    respondents were told that their names would be entered into a

    randomdrawing for one of three $30 gift cards. Of the 750 mailed, 403

    completed surveys were returned (53.7%).

    Subjects were shown one of the three pretested photos of the hair

    salon and were instructed to imagine themselves in the following

    scenario:It is a Saturday and you are at a new salon to get a haircut.

    You have plenty of time and are in no hurry

    (for the no time pressurecondition). Subjects in the time pressure condition read, You're

    pressed for time and are in a hurry. After reading the scenario and

    viewing the picture, subjects were instructed to complete a survey

    that included the dependent measures.

    4.3. Dependent measures

    The same scale was adapted from Experiment 1 to measure

    attitude towards the hair salonand intentions to enter the salon.

    Subjects were also asked to evaluate whether they would recommend

    the salon to a friend using a 3-item, 7-point likert scale (see Table 2).

    We conduct CFA to assess convergent and discriminant validity of

    the measurement model. Fit indices provide evidence of a reasonably

    good t (2(84)=266.25, pb0.001, CFI =0.982, SRMR= 0.051,

    RMSEA=0.074). All items signicantly and substantially load onto

    the expected latent construct. AVE and composite reliability are

    calculated, with all above the recommended thresholds, conrming

    convergent validity of the measurement model. Within the CFA

    setting, discriminant validity is assessed by calculating the shared

    variance between constructs and verifying that it is lower than the

    variances extracted for the constructs involved. All AVEs are larger

    than any squared correlation among constructs (largest squared

    correlation=0.42), suggesting that discriminant validity is achieved.

    4.4. Results

    The overall MANOVA with LSD post-hoc comparisons indicates

    signicant effects for crowding level (F(6, 786)=4.63, pb0.001),

    time pressure (F(3, 393)=13.0,pb0.001), and their interaction (F(6,786)=7.99, p b0.001). This suggests that the two treatment factors,

    separately and in combination, affect shoppers' evaluation of the store

    and their behavioral intentions.

    Gender is signicantly correlated with subjects' intentions to enter

    the salon (i.e., females were more likely to enter the salon), but is not

    signicantly correlated with the treatment conditions. As such,

    gender is used as a covariate in the analyses for intentions to enter

    the salon. Age is signicantly correlated with subjects' intentions to

    enter, their intention to recommend, and their attitude toward the

    salon. Therefore, age is used as a covariate in the analyses for these

    variables.

    ANCOVA results show that the level of crowding signicantly

    affects intention to enter the salon (pb0.001,Table 5). However, this

    main effect was qualied by the signicant interaction of time

    pressure and crowding level. For the no time pressurecondition, no

    signicant differences were found across the three levels of crowding,

    despite a linear, upward trend (see Table 6 for means). Thus, H6 is not

    supported.

    Crowding level did emerge as an important factor for predicting

    subjects' intentions to recommend the salon to a friend. Subjects

    under no time constraints were more willing to recommend a salon

    that was more crowded compared to less crowded (Mlow crowd =3.5,

    Mmid crowd =3.9,Mhigh crowd =4.2). Means were signicantly different

    between the low, medium and high conditions (p'sb0.05). Therefore,

    H7is supported.

    Furthermore, signicant differences were found in store attitudes

    between the three levels of crowding (p'sb0.05). In contrast to the

    curvilinear relationship portrayed in the goods setting, subjects under

    no time constraints view the service provider more favorably when

    the salon is more crowded, showing an upward, linear relationship.

    This supportsH8.

    In support ofH9, a signicant interaction of crowding and time

    pressure was found across all three ANCOVA models (p'sb0.001). As

    predicted, under conditions of time pressure, individuals generally

    preferred a salon with medium levels of crowding. Post-hoc

    comparisons revealed that under time pressure, intentions to enter

    the salon were signicantly more favorable with medium crowding

    compared to eitherlow (pb0.05) or high (pb0.001) crowding (Fig. 2).

    This supports H9a. Similarly, under time pressure subjects had a more

    positive intention to recommend the salon when crowding was at amedium level compared to either low (pb0.05) or high (pb0.001)

    levels of crowding, supporting H9b (Fig. 3). Finally, under time

    pressure, attitudes were most favorable when the store exhibited a

    medium level of crowding compared to low or high (p'sb0.001,

    Fig. 4). This supports H9c.

    4.5. Discussion

    Most studies on retail density associate crowding with negative

    affective evaluation of a given dense situation. Only recently, a few

    researchers suggest that in the context of some hedonic services (e.g.,

    disco, bar, and sports game), crowding may favorably inuence

    consumers' service experience (Arnould and Price, 1993; Holt, 1995;

    Table 5

    Experiment 2 ANCOVA results.

    F-values anddffor dependent variables

    Independent variables Store

    attitude

    Intention to

    enter

    Intention to

    recommend

    Covariate:

    Gender 17.58a(1, 393)

    Age 45.12a (1, 393) 11.97a (1, 393) 21.14a (1, 393)

    Crowding level 14.36a (2, 393) 6.87a (2, 393) 5. 64b(2, 393)

    Time pressure 6.2c (1, 393) 2.56 (1, 393) 5.25c (1, 393)

    Time pressurecrowding 24.78a (2, 393) 10.64a (2, 393) 6.93a (2, 393)

    a pb0.001.b pb0.01.c

    pb

    0.05.

    Table 6

    Experiment 2 mean values.

    No time pressur e Time pr essure

    Dependent measures Low

    crowd

    Medium

    crowd

    High

    crowd

    Low

    crowd

    Medium

    crowd

    High

    crowd

    Store attitude 4.2 4.6 5.0 4.6 5.4 4.0

    Intend to recommend 3.5 3.9 4.2 4.4 5.0 4.0

    Intention to enter 4.1 4.2 4.4 4.1 4.8 3.4

    Note. Higher means indicate more favorable ratings.

    Fig. 2.Experiment 2 results for intention to enter.

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    Ponset al, 2006). This study explores the consumption setting of a less

    experiential, less hedonistic service (hair salon). Findings suggest the

    presence of positive consumer responses and the potential contribu-

    tion of fellow participants in creating heightened expectation for the

    service experience.

    Experiment 2suggests that retail density in a service context may

    enhance product desirability, especially for those shoppers under no

    time pressure. This study sheds light on several distinct differences

    between goods and service settings that ultimately affect customers'

    interpretation of the crowded retail environment. Unlike goods,

    quantitative scarcity due to shortage of supply is not a problem for

    services. Theoretically, the supply of a service is endless (whereas a

    good can be sold out), as long as the service provider remains in

    business. Furthermore, a service can be arranged to be delivered at a

    time of a shopper's choice. Therefore, in a service encounter where

    crowding exists, shoppers may not pursue the avoidance strategy as

    they would do in a goods setting. Shoppers have more cognitive

    control, knowing that they are not competing against others for a

    commodity of limited availability. Thus, the negative psychological

    consequences caused by retail density (e.g., emotional discomfort,

    stress) can be largely avoided in a service setting. Furthermore, high

    retail density may cultivate a perception of a high demand for the

    service, thus increasing the service provider's attractiveness in theview of shoppers. A caveat to these ndings is when the consumer is

    pressed for time. When consumers are in a hurry, they typically prefer

    a hassle-free retail environment that does not work against

    completing a shopping task in a timely manner. Conversely, they

    are less favorable towards the store when it exhibits a high level of

    crowding. Nevertheless, they still do not favor low levels of crowding,

    even when under time pressure.

    5. General discussion and future research

    Based on the ndings of two experiments, it appears that intrinsic

    attributes of goods versus service settings might dominate the result

    of a patronage decision. Shoppers rely on heuristic information in

    deriving judgments about the desirability of a retail store. Retail

    density can be interpreted as a heuristic cue. The effect of retail

    density on consumers' store evaluations and purchase intentions,

    however, largely hinges upon the retail setting. When confronted

    with crowding, shoppers may apply different heuristic decision rules

    in a goods vs. a service setting. In a goods setting, a moderately

    crowded store proves to generate the most favorable store attitudes

    and patronage intentions. However, shoppers seem to be more

    tolerant of retail density in a service context, as they, when notpressed for time, tend to favor a crowded store than a less crowded

    one.

    As there are many options relevant for retailers to generate store

    trafc, it seems benecial to identify theconditions under which retail

    density should be applied as an instrument for enhancing favorable

    store attitudes and patronage behavior. The main result of our

    empirical investigations is that retail settings can inuence the

    direction of the effect of crowding on store desirability. Retail

    executives may nd this information particularly relevant and

    interesting, as it could help them determine an optimal crowding

    strategy that is most likely to stimulate favorable valuation and

    purchase intent.

    Another interesting question concerns the effect of the three

    crowding levels on store image formation. Perhaps environmental

    designs can be devised that could enhance store image and consumer

    satisfaction by aiding shoppers to adapt to human and spatial

    crowding in situations where store trafc is higher than usual (e.g.,

    at peak selling times). Specic decisions such as store layout could

    directly affect one's perception of retail density, thereby inuencing

    attitudes and behavioral intentions.

    Future research may look into the psychological effects of retail

    density. Our study suggests different patterns of crowding effects in a

    goods and a service setting. A logical continuation of this research is to

    investigate consumers' reasoning behind their patronage decisions.

    For example, researchers can explore how consumers apply extrinsic

    cues to form a value assessment and make a choice decision. This

    might be accomplished through the use of open-ended surveys or

    interviews with consumers.

    Another area of further research is the interaction of productscarcity with retail density effects. Crowdedness in a store can

    produce an image of strong demand for a product, which can act as a

    double-edged sword. On one hand, consumers may foster a more

    favorable attitude, such as high assumed quality, and thereby

    increased value of the product. On the other hand, they may perceive

    a quantitative scarcity due to demand, as they can view this as an

    indication of a high number of other people who will own the same

    product. Therefore, a high degree of uniqueness can no longer be

    achieved by purchasing this product. An individual may lose their

    sense of autonomy or distinctiveness (Vecchio and Sussmann, 1981).

    In this case, the negative effect of product scarcity can be dominant.

    An empirical testing of how scarcity effects moderate the effect of

    retail density on store patronage would provide many interesting

    insights.

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