On Store Design and Consumer Motivation

Abstract

Research testifies to the influence of environmental factors in shopping environments. However, few studies examine effects of store design in interaction with shoppers’ motivations. The authors propose that task-oriented shoppers prefer stores that are spacious, whereas recreational shoppers enjoy and prefer the arousing properties of color. To provide controlled tests of these hypotheses, we created visual simulations of stores that varied by color (arousing red vs. less arousing blue) and layout (spacious vs. cluttered), and induced either task-oriented or recreational shopping motivations. Customers at a clothing store responded to one of these four store video displays. Results showed that motivations interact with environmental factors. Task-oriented shoppers preferred shopping in spacious stores, whereas recreational shoppers preferred high-arousing store environments. These findings suggest that store managers could increase arousal levels using ambient design elements, such as colored lights, when shoppers are likely recreationally oriented and provide spacious environments to appeal to task-oriented shoppers.

Keywords

arousal spatial control interior color layout shopping motivation

Studies in environmental psychology and retailing testify to the importance of environmental design for creating pleasurable consumer experiences, conveying a desired store or service image, and promoting specific behaviors. For instance, high arousing colors may increase the likelihood of (impulse) purchases (Bellizzi & Hite, 1992), uplifting music may promote prosocial (i.e., helping) behaviors (North, Tarrant, & Hargreaves, 2004) and steer perceptions of “store personality” (d’Astous, 2003), and a spacious, as opposed to a cluttered or secluded, layout can heighten pleasure in retail and leisure settings (Finlay, Marmurek, Kanetkar, & Londerville, 2010; Machleit, Eroglu, & Mantel, 2000).

Generally, such effects of environmental design on consumer responses can be traced to the fact that environmental factors may impact cognitive responses (e.g., interior design variables affecting symbolic meaning attributions), physiological responses (e.g., aversive lighting conditions resulting in fatigue or discomfort), and, of particular interest to current undertaking, affective responses (e.g., color or spatial design affecting feelings of arousal or control; cf. Bitner, 1992). As a result, customers may want to stay longer, spend more, or engage more readily in social interactions. However, research addressing effects of environmental store factors is inconclusive, in part because environmental settings comprise complex configurations of different types of stimuli (including nontangible, ambient variables, such as color and scent, and tangible or spatial variables, such as layout and interior design elements; Bitner, 1992), and because effects of environmental factors are highly context dependent. In particular, insights in how environmental factors interact with consumer characteristics are limited (cf. Morrin & Chebat, 2005).

Arguably, this latter state of affairs foremost relates to a one-sided focus on the environment as the unit of investigation at the expense of the individual, thereby ignoring dispositional (i.e., personality-related) and situational influences that may qualify environmental effects. In line with this notion, previous research indicates that environmental effects vary with consumer personality (e.g., Dijkstra, Pieterse, & Pruyn, 2008; Kwallek, Soon, & Lewis, 2007; Van Rompay, Vonk, & Fransen, 2009) and that store environments should fit customers’ shopping styles (i.e., person–place congruency; Morrin & Chebat, 2005). In addition to personality, and of particular relevance to current research, the intention or situational goal that motivates people–environment interactions may also qualify environmental effects. For instance, in retail environments (the context of present research), customers may or may not enter a store with a specific product purchase in mind, and, hence, may be more attuned to some environmental factors than to others.

In addition to incorporating two different types of environmental store variables, the objective of this article is therefore to explore the interaction between store design and situational goals that underlie customer–(store) environment interactions. Specifically, the research presented addresses effects of interior color and store layout and argues that their effects on shopping pleasure and behavioral intentions vary depending on whether shoppers entertain task-oriented or recreational shopping goals.

Environmental Psychology and Emotional Experience

Mehrabian and Russell’s (1974) framework (in which pleasure, arousal, and dominance are put forward as affective mediators of environmental factors on behavior) inspired various research projects in the retail context. But although the importance of the pleasure and arousal dimensions for explaining consumer behavior is generally acknowledged, the dominance dimension has received only limited empirical support, inspiring some to propose a revised version (of the original model) limited to pleasure (affective valence) and arousal (e.g., Baker, Grewal, & Levy, 1992; Donovan & Rossiter, 1982; Donovan, Rossiter, Marcoolyn, & Nesdale, 1994). These factors resemble the dimensions of Russell’s (2003) more general emotion framework. However, others have shown that dominance does affect consumer behavior (Hui & Bateson, 1991; Van Rompay, Galetzka, Pruyn, & Moreno-Garcia, 2008; Ward & Barnes, 2001), in particular in (retail) settings in which customers entertain well-defined goals. For instance, Van Rompay et al. (2008) showed that feelings of control (a construct closely related to dominance) mediate the relationship between spatial crowding and shopping pleasure, indicating that environmental factors may negatively impact consumer response by restricting free movement and wayfinding.

Arguably then, a more narrow definition of dominance (from now on referred to as spatial control) as the extent to which customers can engage in, or bring to completion, interactions required for goal attainment is appropriate in the retail context. By consequence, the importance of spatial control should vary with the degree to which consumers have specific shopping tasks to accomplish in the first place; sometimes a shopping trip is motivated by the need for a specific product, at other times a store is entered without a product purchase in mind. Hence, one aim of this article is to test whether the effects of store design vary with the extent to which customers entertain well-defined shopping goals.

With respect to arousal, Berlyne’s (1976) classic writings on the relationship between arousal and preference are useful in the context of retail environments as well. For instance, Donovan and Rossiter’s (1982) findings indicate that arousal is an important determinant of shopping enjoyment and purchase behaviors. Generally, customers prefer moderate levels of stimulation (arousal) to excessive stimulation (resulting in stress and information overload) or low levels of stimulation (giving rise to boredom). However, high arousal is not always detrimental to consumer responses. For instance, Sherman, Mathur, and Smith (1997) showed that in fashion stores, arousal may increase purchase intentions and spending behavior. For obvious reasons, high arousal is conductive to consumer experiences in hedonic or leisure services such as bars and discos where customers explicitly value stimulation and arousal. Hence, in these settings, customers are likely to value arousal-inducing stimuli such as eye-catching colors and stimulating music.

These findings indicate that effects of spatial control and arousal on affective experiences and behavior vary depending on the nature of consumer goals, and, of particular importance for the current undertaking, on whether customers entertain a specific shopping task to begin with. Depending on whether this is the case, environmental factors may positively or negatively affect shoppers’ affective experiences and behaviors. Before elaborating on how effects of environmental factors vary with shopping motivations, the next section introduces the store variables central to the current study and proposes a distinction between ambient factors on the one hand (i.e., store color) and spatial, functional design variables (i.e., store layout) on the other (cf. Baker, Parasuraman, Grewal, & Voss, 2002; Bitner, 1992).

Color and Arousal

In the context of store and service design, color is one of the most influential ambient variables (e.g., Countryman & Jang, 2006). The most salient color dimension deals with color warmth (i.e., wavelength, see Valdez & Mehrabian, 1994 for a discussion on color dimensions) with people generally preferring cool (short-wavelength) colors, such as green and blue, to warm (high-wavelength) colors such as yellow and red (Valdez & Mehrabian, 1994; Whitfield & Wiltshire, 1990; Yildirim, Akalin-Baskaya, & Hidayetoglu, 2007). Generally, warm, as opposed to cool, colors elicit higher levels of anxiety (Jacobs & Suess, 1975) and present greater distraction levels (Gerard, 1957). In line with these findings, research indicates that high arousing colors such as yellow and red connote excitement, tension, and stimulation, whereas low arousing colors such as blue and green trigger associations with calm, security, and peacefulness (Levy, 1984; Stone, 2003; Wexner, 1954).

Underlining the importance of color in the retail context, Bellizzi, Crowley, and Hasty (1983) showed that consumers consider red (i.e., high arousing) retail environments unpleasant, tension-inducing, and less attractive compared with blue (i.e., low arousing) retail environments, arguing that high-arousal colors may overstimulate buyers, thereby impairing purchase deliberations and buying decisions. However, low-arousing colors have been shown to facilitate focus on, and attention to, the task at hand (Stone & English, 1998). In short, these findings suggest a straightforward relationship between color warmth or wavelength on one hand and arousal on the other (with “red” as the prototypical high-arousal hue and “blue” as the prototypical low-arousal hue).

However, arousal may differentially impact affective experiences and behaviors depending on the type of task. For instance, previous research suggests that participants engaged in monotonous tasks prefer high-arousing colors (i.e., the color red) for their stimulating qualities (Stone, 2003; Stone & English, 1998). Recreational shoppers, seeking fun and (sensory) stimulation, may likewise value high-arousing colors for the excitement they bring. However, task-oriented shoppers may value low-arousing colors as they are less distracting and therefore do not interfere with task execution. In line with this assumption, Stone (2003) showed that participants engaged in high-demand tasks performed better in a blue, as opposed to a red, environment.

Store Layout and Spatial Control

Store layout refers to the positioning of physical elements such as racks and product displays throughout the store environment. In contrast to (nontangible) ambient factors (such as color), layout is a tangible, spatial design factor, directly impacting behaviors (cf. Bitner, 1992; Moore, 1986; Turley & Milliman, 2000; Wineman & Peponis, 2010). Its direct impact on consumer behavior notwithstanding, surprisingly few studies have studied effects of layout on shopping behaviors (Turley & Milliman, 2000), underlining the importance of systematically investigating effects of different layout conditions. Here it is argued that depending on the configuration of tangible elements such as racks and product displays, consumers perceive a store environment as either spacious or cluttered. As for the relationship between physical elements and control perceptions, Van Rompay et al. (2008) demonstrated that physical obstructions (i.e., pillars) located in shopping aisles reduce control, thereby lowering shopping pleasure. Hence, (store) layout may negatively affect feelings of spatial control and pleasure by reducing free movement throughout the environment and impairing wayfinding.

Similar to the way in which effects of color may vary with shopping goals, effects of store layout may vary depending on the extent to which consumers enter a retail environment with a specific goal (i.e., product purchase) in mind. After all, when fulfilling shopping tasks for which free movement and overview over the store environment are a prerequisite, a cluttered store layout is an obstacle to goal fulfillment. Hence, a spacious layout should be of particular importance when consumers are task oriented. In line with the notion that layout may hinder or facilitate task execution, Chaudhury, Mahmood, and Valente (2009) stressed the importance of adequate space and layout conditions allowing for free movement and overview in (highly functional) acute care settings. To elaborate on the relationship between store design and task fulfillment in retail settings, the next section addresses the role of shopping motivations.

Shopping Motivation

Consumers go shopping for different reasons; sometimes shopping is a goal-directed activity with a clear end goal (i.e., purchase of a product) in mind, at other times shopping is a recreational activity and the fun is in the shopping activity itself rather than in acquiring a desired product. Stone (1954) was among the first to categorize shopping goals, differentiating, for instance, between economic consumers, paying close attention to quality and price differences among products, and personalizing consumers, rather in search of pleasant contact or “chit chat” with retail personnel. Following this classification, research identified different shopping motives in the years that followed, culminating in a general distinction between a task-oriented motivation and a recreational motivation. These two motivations underlie commonly made distinctions in literature such as economic versus recreational shoppers (e.g., Bellenger & Korgaonkar, 1980) and utilitarian versus hedonic shopping value (e.g., Babin, Darden, & Griffin, 1994; Jones, Reynolds, & Arnold, 2006).

Task-oriented shoppers visit a store to obtain a specific product and derive little or no satisfaction from the shopping activity itself but exclusively from the outcome of the shopping activity (obtaining the desired product). Consequently, these shoppers have little or no interest for (or may even display a negative attitude toward) nonfunctional aspects of retail environments such as store ambience (Korgaonkar, 1981). After all, when focused on task completion, high-arousal environments may be unpleasant as they tax the senses and distract from goal fulfillment (cf. Stone, 2003).

However, for recreational shoppers, high-arousing stimuli may add to the fun of a shopping trip by increasing excitement and sensory stimulation (Jones et al., 2006). In other words, for these shoppers, high-arousing stimuli add to the richness or hedonic value of the shopping episode (Kaltcheva & Weitz, 2006). In line with these observations, research indicates that these shoppers are more likely to continue shopping (i.e., browse the store) after making a purchase, place a higher importance on store ambience, and overall place less value on acquiring a product (Eroglu & Machleit, 1990). Based on the foregoing, it is predicted that

Hypothesis 1: Effects of store color on pleasure and behavioral intentions vary with shopping motivations.

More specifically,

Hypothesis 1a (H1a): A low-arousing (blue-colored), as opposed to a high-arousing (red-colored), environment positively affects shopping pleasure and behavioral intentions of task-oriented shoppers.

Hypothesis 1b (H1b): A high-arousing (red-colored), as opposed to a low-arousing (blue-colored), environment positively affects pleasure and behavioral intentions of recreational shoppers.

A similar line of reasoning may apply to the interactive effects of store layout and shopping motivations. That is, having a specific goal in mind (i.e., shopping for a specific product located somewhere in the store environment) for which (visual) overview and unobstructed movement are a prerequisite, task-oriented shoppers may consider a cluttered (as opposed to a spacious) store layout a nuisance as it decreases perceptions of spatial control. However, for recreational shoppers, wayfinding, (visual) overview, and unobstructed movement are arguably less of an issue as they have no specific route to follow or product to locate. Store layout should, thus, not affect shopping pleasure and behavioral intentions for recreational shoppers. Hence, it is predicted that

Hypothesis 2: Effects of store layout on pleasure and behavioral intentions vary with shopping motivations.

Hypothesis 2a (H2a): More specifically, a spacious, as opposed to a cluttered, store layout positively affects shopping pleasure and behavioral intentions for task-oriented shoppers.

Hypothesis 2b (H2b): Recreational shoppers’ responses do not vary as a function of store layout.

To test these hypotheses, store layout and store color were manipulated in videos taken in a Dutch clothing store, resulting in a full factorial 2 (interior color: red vs. blue) × 2 (store layout: spacious vs. cluttered) × 2 (shopping motivation: task-oriented vs. recreational) between-subjects design.

Method

Participants

Participants were 123 shoppers (76 female, 47 male; age range = 16-71 years; mean age = 38.3 years) of a local Dutch clothing store.

Procedure

Participants were approached individually on passing by, leaving or entering the store, and asked to participate in an evaluation trial of store designs in the context of a pending store renovation. Next, participants were guided to a quiet corner (near the entrance hall) of the store where they were seated behind a laptop computer and asked to follow the instructions presented on screen. Instructions explained that store management was interested in recording shoppers’ first impressions of a new store design and that participants were therefore about to view a short (10-s) video presenting a walkabout through the store. Before presentation of the video, participants were presented with a scenario either inducing a task-oriented focus or a recreational focus. After presentation of the video, participants filled out a questionnaire comprising the dependent variables.

The task-oriented scenario read:

You have a party tonight and have nothing to wear. It’s 14:45 and the store closes in 15 min. Imagine yourself entering the clothing store (you are about to see on video) and making a go-around in search of a proper outfit.

The recreational scenario read:

You are out in the city with a friend. You happen to pass by a clothing store and decide to have a look inside. Imagine yourself entering the clothing store (you are about to see on video) and making a go-around.

Store Design Manipulations

Four different videos were created comprising the manipulations of store layout and interior color. Color selection was based on previous research findings showing that red and blue most clearly differentiate on arousal induction (e.g., Bellizzi & Hite, 1992; Stone, 2003). To manipulate store color, the walls of the store were covered with either blue-colored (red, green, and blue (RGB): 71, 80, 118; low arousal) or red-colored (RGB: 168, 36, 39; high arousal) fabric. As for store layout, positioning of clothing racks throughout the store was varied. Clothing racks were either placed alongside the walls (spacious store layout) or placed in the center of the store (cluttered layout), thus blocking visual overview and impeding free movement (see Figure 1 for screenshots of the videos used in the experiment). In both conditions, the exact same number of racks and merchandise were present in the store.

Figure 1.

Screenshots taken from the videos used in the experiment

Of all four conditions, an identical walk around was recorded. The video was shot in a fluid motion. In all four videos a man and a woman were present in the store (in each video occupying the same position) so as to create a realistic shopping episode. Furthermore, all videos were shot from the same angle and showed exactly the same scene. In addition, all videos were edited for environmental sound resulting in four videos with identical background “store” noise (i.e., babbling noise). Previous research indicates that videos can accurately simulate real-life environments and hence, that responses correlate highly with responses obtained in the field (Bateson & Hui, 1992; Finlay et al., 2010), thereby attesting to the ecological validity of our approach (see Stamps, 1990; 2011 for an extensive discussion on simulation validity).

Measures

Manipulation checks

To ensure the effectiveness of the color manipulation, a 4-item arousal measure was used comprising the items “In this store I feel stimulated,” “In this store I feel activated,” “In this store I feel drowsy” (reverse coded), and “In this store I feel bored” (reverse coded;α = .82). As for the store layout manipulation, a 4-item spatial control scale was used measuring the extent to which store layout is spacious and allows for free movement, as indicated by the items “In this store, I feel obstructed while shopping,” “In this store I feel restrained,” “In this store I feel suffocated,” and “This store is spacious” (reverse coded; α = .74).

Dependent measures

Shopping pleasure was measured with three items: “I feel happy in this store,” “I feel cheerful in this store,” and “I enjoy shopping in this store” (α = .91). Participants’ behavioral intentions were measured with a scale comprising the items “I would have a tendency to buy something here,” “I would like to return to this store,” and “I want to leave this store as soon as possible” (reverse coded; α = .77). These two outcome measures were positively correlated (r = .82, p < .01).

Results

Manipulation Checks

An analysis of variance (ANOVA) with color and store layout as independent (between-subjects) variables and arousal as dependent variable shows that the main effect of color on arousal is significant, F(1, 119) = 5.00, p = .027, partial η² =.040, indicating that participants experience the blue-colored store environment as less arousing (M = 2.8; SD = 1.2) than the red-colored environment (M = 3.3; SD = 1.2). The main effect of store layout does not reach significance, F(1, 119) = 1.19, p = .28, partial η² =.010, neither does the interaction between color and store layout (F < 1, ns).

With respect to spatial control perceptions, an ANOVA (with color and store layout as independent between-subjects variables) yields a significant effect of store layout, F(1, 119) = 10.58, p = .001, partial η² =.082, indicating that the spacious layout triggers less feelings of behavioral restraint (M = 4.0; SD = 1.2; and, hence, more feelings of spatial control) compared with the cluttered layout (M = 4.8; SD = 1.4). The main effect of store color does not reach significance (F < 1, ns), neither does the interaction between store color and store layout, F(1, 119) = 1.06, p = .31, partial η² =.009. These findings confirm the effectiveness of the manipulations, and hence, the presumed relationship between store color and arousal on one hand and store layout and spatial control on the other.

Hypothesis Testing

To reduce the risk of an inflated Type 1 error, first a multivariate ANOVA (MANOVA) was conducted, with store color, store layout, and shopping motivation as independent (between-subjects) variables and shopping pleasure and behavioral intentions as dependent variables. In line with H1, this analysis yielded a significant multivariate effect of the interaction between store color and shopping motivation, F(2, 114) = 4.29, p = .016, partial η² = .070. Likewise, and in line with H2, the multivariate effect of the interaction between store layout and shopping motivation was significant, F(2, 114) = 4.29, p = .016, partial η² = .070. All other main and interaction effects were nonsignificant (all F’s < 1, except for the interaction between store color and store layout), F(2, 114) = 1.49, p = .231, partial η² = .025.

Shopping Pleasure

An ANOVA with store color, store layout, and shopping motivation as independent (between-subjects) variables and shopping pleasure as dependent variable revealed no main effects of store color, store layout, and shopping motivation (all F’s < 1). However, the significant interaction between store color and shopping motivation, F(1, 115) = 6.42, p = .013, partial η² =.053, indicates that, as expected (H1), the effect of store color on shopping pleasure varies depending on shopping motivation (see Figure 2). (Note that Bonferroni-adjusted significance levels for two dependent variables equal p < .025). Pairwise comparisons show that for task-oriented shoppers, the expected difference (H1a) between the red-colored and blue-colored environment is not significant (M = 2.36, SD = .97 vs. M = 2.85, SD = 1.84; p = .12). However, in line with H1b, recreational shoppers perceived the red-colored store environment as more pleasurable (M = 3.06, SD = 1.25) compared with the blue- colored store environment (M = 2.44, SD = 1.06; p = .048).

Figure 2.

Interaction between shopping motivation and store color on shopping pleasure

The expected interaction (H2) between store layout and shopping motivation did not reach significance, F(1, 115) = 2.56, p = .11, partial η² =.022. No further interactions were obtained.

Behavioral Intentions

Similar to the results for shopping pleasure, an ANOVA with store color, store layout, and shopping motivation as independent (between-subjects) variables yields no main effects on behavioral intentions (all F’s < 1). Again, and in line with H1, the interaction between store color and shopping motivation reached significance, F(1, 115) = 8.64, p = .004, partial η² = .070. Pairwise comparisons (see Figure 3, top panel) show that for task-oriented shoppers the expected difference (H1a) between the red-colored and blue-colored environment is again not significant (M = 2.58, SD = 1.14 vs. M = 3.04, SD = 1.69; p = .10). In line with H1b, for recreational shoppers, the red-colored (as opposed to the blue-colored) environment positively affected behavioral intentions (M = 3.24, SD = 1.32 vs. M = 2.41, SD = 1.36; p = .015).

Figure 3.

Interaction effects on behavioral intentions

In addition, the expected interaction (H2) between store layout and shopping motivation reached significance, F(1, 115) = 6.59, p = .012; partial η² =.054. In line with H2a, pairwise comparisons (see Figure 3, bottom panel) show that for task-oriented shoppers, the spacious (as opposed to the cluttered) store layout positively affected behavioral intentions (M = 3.17, SD = 1.31 vs. M = 2.49, SD = 1.51; p = .026). For recreational shoppers, the difference between the spacious and cluttered store layout was, as expected (H2b), not significant (M = 2.64, SD = 1.34 vs. M = 3.06, SD = 1.43; p = .16). No further interactions were obtained (F’s < 1).

General Discussion

The findings presented largely confirm the relationship between store design and customers’ affective in-store experiences and behavioral intentions. But more important, the findings indicate that effects of store variables vary depending on the goals that customers entertain on entering a retail environment. In addition, they corroborate a distinction between store variables that actually impact functional goal-oriented behaviors (i.e., moving through the store in search of a specific product) and variables that primarily affect customers’ sensory perceptions of the store environment (e.g., perceptions of store color).

Taking note of these distinctions, the findings support the suggestion that task-oriented shoppers are primarily under the influence of spatial, function-related design variables as they most clearly interfere with goal attainment. In other words, because unobstructed movement and (visual) overview are most important for locating a specific product in the store environment, task- oriented shoppers benefit from a well-organized, spacious layout. These customers experience a cluttered store layout as an impediment to goal fulfillment and, hence, express a lowered intention to stay in, or return to, the store. However, the effect of store layout on shopping pleasure did not reach significance, perhaps suggesting that to these shoppers (intent on task completion) shopping pleasure is of lesser relevance. (Note, however, that the two outcome measures, i.e., shopping pleasure and behavioral intentions, were positively correlated and that, although not significant, the results for shopping pleasure mirrored those for behavioral intentions).

In addition, the findings presented indicate that for task-oriented shoppers, ambient variables that do not have a direct impact on behavior (in this study store color) are less influential (i.e., for task-oriented shoppers color differences did not reach significance), thereby suggesting that task-oriented shoppers are not positively affected by nonfunctional aspects of store design (e.g., Korgaonkar, 1981) but do not experience atmospherics as a major source of frustration either. As such, this finding runs against our prediction and previous research indicating that high arousing colors interfere with task completion and, hence, should inspire negative consumer responses. Admittedly, an alternative explanation for the nonsignificant effects of store color (for task-oriented shoppers) may relate to the scenario manipulation, which was perhaps too weak to instill a full-fledged task orientation.

However, for recreational shoppers, the findings are fully in line with predictions. These shoppers (intent on having a good time in an exciting environment) positively respond to ambient design factors (in this study store color) by reporting higher levels of shopping pleasure and a heightened intention to explore and return to the store. As for store layout, recreational shoppers appear to be somewhat indifferent (i.e., for recreational shoppers, effects on shopping pleasure and behavioral intentions did, in line with predictions, not reach significance). Thus, because recreational shoppers do not entertain predefined goals requiring specific actions, obstructions of free movement resulting from store layout are arguably less of a nuisance.

Of course, it should be noted that participants in the experiment only watched a short video and did not actually browse the store or were not actually in search of a specific product. However, the usage of videos allowed for experimental control over the store variables and extraneous influences such as crowding levels (also influential with respect to perceptions of control and shopping pleasure; Hui & Bateson, 1991; Van Rompay et al., 2008). However, at the same time, videos shot in an actual store environment display a considerable level of realism, thus providing a reliable approximation of the store variables under discussion and their effects on customer response (Baker et al., 2002; Bateson & Hui, 1992; Finlay et al., 2010; Stamps, 2011). With respect to the scenarios, care was taken to ensure that participants would not read opportunities for recreational browsing in the task-oriented scenario and vice versa. Hence, in the task-oriented scenario, participants were informed that the store would close in 15 min, as such excluding opportunities for recreational browsing. However, doing so introduced “time pressure” as an additional (potentially confounding) factor that participants had to reckon with.

In terms of practical implications, the findings presented clearly highlight the importance of insight in customers’ shopping motivations in specific retail environments. Of course, one could object that clientele is always mixed with respect to shopping motivations: Some customers happen to pass by and enter the store just for fun, or to kill time, whereas others visit the store with a specific purchase in mind. However, the findings presented suggest that ambient variables (store color) and spatial, functional variables (store layout) operate relatively independent from each other. Hence, an improvement of store atmospherics from recreational shoppers’ point of view (e.g., more varied and arousing color usage) arguably has little (or at least a less pronounced) impact on affective experiences of task-oriented shoppers. As for store layout, a better organized or more spacious store layout is likely to reduce negative affect of task-oriented shoppers, without taking away (all of) the fun for recreational shoppers.

That is not to say, however, that ambient design factors cannot impact impressions of tangible variables. For instance, previous research showed that dark, as opposed to light, hues may generate impressions of a smaller and more crowded environment (Baum & Davis, 1976; Yildirim et al., 2007). Likewise, decisions regarding store layout may also affect perceptions of retail crowding, with spacious layout conditions attenuating negative effects resulting from (too) many shoppers visiting the store at the same time. Hence, informed usage of fixed store variables such as color and layout may assist store management in counteracting negative effects stemming from uncontrollable variables such as variable crowding levels.

With respect to color usage, colored light that allows for dynamic adjustments of arousal levels by means of hue selection may be of particular interest to store management. For instance, management may increase arousal levels (by selecting warm hues such as red and yellow) at times when clientele is mostly browsing and arousal levels are generally low (e.g., when crowding is low). At peak hours or before closing time (when task-oriented shoppers are often large in number), cool hues such as blue and green are advisable.

Finally, the study presented addressed only two (albeit important) store variables in a specific retail environment (i.e., a clothing store). Hence, follow-up research is necessary to indicate to what extent the results reported are consistent across different types of retail and service environments. In addition, Chebat and Morrin (2007) showed that effects of color schemes (used in shopping mall décors) on environmental perceptions varied among subculture segments, suggesting that associations triggered by store design may vary depending on target group characteristics such as lifestyle and cultural background. Awaiting follow-up research addressing these and related questions, in the meantime the findings presented testify to the importance of store design for creating pleasurable in-store experiences and to the importance of taking into account goals or intentions that underlie people–environment interactions.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Bios

Thomas J. L. van Rompay, PhD, is an assistant professor at the University of Twente. His research centers on effects of product design and environmental factors on affective consumer experiences and behavior.

Karin Tanja-Dijkstra is a research fellow in the School of Psychology at the University of Plymouth. Her research examines effects of the physical health care environment on health and well-being of patients and health care personnel.

Joost W. M. Verhoeven, PhD, is a postdoctoral researcher at the SWOCC institute, University of Amsterdam. He studies the impact of social media on corporate branding and identity communication in service organizations.

Annemiek F. van Es received her master’s degree at the University of Twente. She is interested in effects of store design on shoppers’ affective experiences and (purchase) behaviors.

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