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The influence of in-store lighting on consumers' examination of merchandise in a wine store
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International Journal of
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Research in Marketing
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J. of Research
in Marketing
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The influence of in-store lighting on consumers’ examination of merchandise in a wine store Charles
S. Areni
*, David Kim
Marketing Department, College of Business Administration, Texas Tech. University, Lubbock, TX 79409, USA
Abstract Several studies examining the impact of illumination on behavior are reviewed in this article. Hypotheses are derived regarding the impact of in-store lighting on various aspects of shopping behavior. As part of a field experiment in a large US city, the lighting (soft versus bright) in a centrally located retail establishment was varied over a two month period. The results of an ANOVA indicated that brighter lighting influenced shoppers to examine and handle more merchandise, though sales were not influenced. These findings are discussed in terms of their implications for creating a functional store environment as well as an appropriate store image. 1. Introduction Kotler (1973-1974) coined the term atmospherics to refer to “the effort to design buying environments to produce specific emotional effects in the buyer that enhance his purchase probability” (p. 50). He identified visuaE (color, brightness, size, shape), aural (volume, pitch), olfactory (scent, freshness), and tactile (softness, smoothness, temperature) dimensions of store atmosphere, and suggested that further research was needed regarding the impact of these in-store factors on purchase behavior. Yet, almost eighteen years have passed since the publication of Kotler’s initial article, and the academic literature regarding the impact of various atmospheric elements is still rather sparse.
* Corresponding author. Telephone (806) 742-3238. The authors wish to thank Shelby D. Hunt and five anonymous U&W reviewers for their helpful comments on an earlier draft of this article. 0167-8116/93/$07.00 0 1993 Elsevier SSDI 0167-8116(93)E0044-A
Science
Only a small subset of the in-store dimensions identified by Kotler has been studied empirically. Further, the range of the consumer reactions examined has been rather narrow. Researchers have tended to emphasize overt “quantitative indicators” (i.e. dollar amount spent, time spent, etc.), while largely ignoring other aspects of shopping behavior (Eroglu, et al. 1991). Finally, due to the difficulties of conducting atmospheric research in the field, much of the emergent research has relied on verbal (i.e. Gardner and Siomkos, 1986) or visual (i.e. Eroglu and Machleit, 1990) simulations of retail environments. While these laboratory simulation techniques offer the advantages of methodological expediency and experimental control, their ability to realistically capture the desired store atmosphere is suspect. The literature on atmospherics would, therefore, be enhanced by research examining the impact of some of the untested dimensions of Kotler’s framework on a wider range of consumer behavior in an actual retail setting. Consistent with this objective, this research reviews the liter-
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ature regarding the impact of illumination (i.e. Kotler’s brightness), a variable yet untested in the marketing literature, on various aspects of human and animal behavior. Borrowing from research examining arousal theory and &on theory, the two most prominent theories in the environmental psychology, ergonomics, and animal behavior literature, predictions are made regarding the impact of in-store illumination on shoppers’ search, purchase, and consumption behaviors. These hypotheses are tested via a field experiment in which: (1) the number of shelf items shoppers examined, handled, and purchased, (2) the shelf location of the items examined, handled, and purchased, (3) the total dollar amount of the merchandise purchased, (4) the total amount of time spent shopping, and (5) the frequency with which shoppers consumed merchandise on site were observed under two lighting conditions (soft versus bright) in a downtown wine store.
2. The literature
on lighting
effects
Although the importance of illumination in store design has received some attention in the marketing literature (see, for example, Schewe, 19881, its effects on consumers has yet to be examined empirically. Much of the research reviewed below has, instead, appeared in the environmental psychology and animal behavior literature. Mehrabian (1976) has interpreted the influence of lighting in terms of its ability to arouse individuals. An individual who is highly aroused “will become stimulated, jittery, alert,” whereas a person in a nonarousing environment “will feel relaxed, calm, sluggish, or sleepy.” Moreover, a highly aroused individual will exhibit “increased heart rate, muscle tension, and lowered skin temperature” (p. 21). Mehrabian suggests that lighting is an extremely important determinant of the environment because “brightly lit rooms are more arousing than dimly lit ones” (p. 89). In support of this conceptualization of the effects of illumination, Kumari and Venkatramaiah (1974) found that higher illumination levels were associated with increased cardiovascular activity in college students. Further, Gifford (1988) found that college students expended more effort on an experi-
mental task when illumination levels were higher. In the context of retailing environments, Birren (1969, p. 91) recommends “really bright light” for impulse purchases, where high levels of arousal are likely to be facilitating (Rook, 1987). Markin, et al. (1976) suggest that retailers wishing to induce patrons to peruse more of their merchandise should employ soft lighting in order to reduce the level of customer “stimulation” (i.e. arousal), and hence, slow the pace at which they move through the store. This suggests that retailers can influence the amount of time customers spend shopping via their-selection of in-store lighting levels. However, at least one variable would appear to moderate the influence of instore lighting on behavior, the presence of a romantic partner. Butler and Biner (1987) asked undergraduate students to rate combinations of household settings and behaviors (i.e., bedroom-sleeping; bathroom-brushing teeth, etc.) in terms of their illumination preference (i.e., very dark, dark, bright, and very bright). They found significant differences in preferred lighting levels across behaviors, settings, and individuals. However, the presence of a romantic partner consistently lowered subjects’ preferred lighting levels. Evidently, romantic couples prefer environments that induce low levels of arousal, (perhaps because the situation is already arousing enough). ’ Biner, et al. (1989) asked college students to indicate their lighting level preferences across a number of situations that varied regarding: (1) the visualness of corresponding activities, (2) the complexity of the corresponding activities, and (3) the social context (i.e. friend present, romantic partner present, group of friends present). Similar to Butler and Biner (1987), subjects consistently preferred lower lighting levels when romantic partners rather than platonic friends were present. 2 ’ A reviewer suggested that demand effects may have driven Butler and Biner’s (1987) results regarding romantic settings. Subjects may have guessed that they were supposed to prefer low lighting levels when a romantic partner was present. ‘Although the results of Delay and Richardson (1981), Butler and Biner (1987), and Biner et al. (1989) suggest a gender difference in optimal in-store lighting levels, specific hypotheses could not be tested due to the low frequency of individual male and female patrons.
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An alternative and, in retrospect, intuitive interpretation of the impact of illumination on behavior has been advanced by Biner et al. (1989). They suggest that illumination drives preference and performance not only via arousal, but also through its effect on vision and the scope of an individual’s perceptual field (see also Birren, 1973). They found, for example, that the tendency for romantic couples to prefer lower lighting levels was attenuated when the social setting involved visually oriented activities. Biner et al. (1989) concluded that illumination affects task performance and preference in two relatively dismay be tinct ways: “. . . the [arousal] mechanism working in both visual and nonvisual situations, but uisuaZne~~ of the activity may be setting limits on the process” (p. 13, insert and italics ours). In other words, individuals prefer illumination levels that produce appropriate levels of arousal, unless that illumination level reduces visual acuity below the point needed to complete environmental tasks. Veitch and Kaye (1988) offer further evidence for this interpretation. They found that the conversation among female college students engaged in a mock job applicant evaluation task was louder under conditions of low versus high illuminance. The reduced visual acuity in the low illuminance condition may have inhibited nonverbal communication, thus necessitating more intense (i.e. louder) aural stimuli in order to compensate. Dannenmann et al. (1984-1985) extend the notion of visual acuity to include the scope of the perceptual field in interpreting the impact of illumination on the behavior of calves: 3 one can conclude that at [the lowest levels of lighting] the animals were not able to see some
3 Arousal theory predicts that the perceptual field narrows as arousal increases (see Easterbrook, 1959). Thus, arousal theory and vision theory make disparate predictions regarding the impact of illumination on the size of an individual’s perceptual field. This would appear to be a fruitful direction for researchers interested in testing the two theories against one another.
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of the more distant stimuli. At [moderate levels of lighting] the visual capacity of the eye is better, so that all stimuli can be perceived, but need closer examination for a final recognition. All objects or stimuli could be recognized quickly at [the highest levels of lighting]. The reactions of play and sexual behavior and other social behavior patterns underline this assumption (pp. 256-257, insert ours). In the context of retail settings, these findings suggest that shoppers will be less likely to engage in visually oriented activities (i.e. checking prices, reading labels, etc.) when in-store lighting levels are lower.
3. Field experiment
setting
The study was conducted in a downtown restaurant in a large southeastern city. The restaurant featured a wine cellar, clearly visible through a glass section of the floor, that was open to patrons who wished to just visit, sample some wines, or purchase some bottles of wine. This area of the restaurant contained hundreds of bottles of wine, shelved horizontally in typical wine cellar fashion, as well as a small dining area for patrons who wished to sample some wines by the glass. This unique setting afforded the opportunity to examine the impact of in-store lighting on consumers’ reaction to the cellar, their actual purchase behavior, and their tendency to remain in the cellar to sample wines.
4. Hypotheses Given the shelf requires examining suggests
that the examination of merchandise off (i.e. to read labels, check prices, etc.) some level of visual acuity, the research the effect of illumination on vision the following hypothesis.
Hypothesis 1: Patrons will examine and handle more merchandise when the lighting is bright rather than when it is soft.
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The work of Birren (1969, pp. 45-47) implies that relatively low levels of illumination are adequate when the stimulus to be processed is within a few feet. Merchandise on eye level shelves would certainly be within this range. Hence, it is likely that the increase in the number of items examined and handled would come from merchandise on the high and low level (i.e. low visual acuity) shelves. The following hypothesis reflects this moderating influence. Hypothesis
2: The effect of lighting on the number of items examined and handled will be observed for merchandise on the high and low level shelves, but not for merchandise on the eye level shelves.
Research examining the effects of illumination on arousal suggest that lower levels of in-store lighting slow the pace with which shoppers move through a store. The following hypothesis is based on this reasoning. Hypothesis
3: Patrons will spend more time in the cellar when the lighting is soft rather than when it is bright.
Butler and Biner (1987) and Biner et al. (19891, however, have found that romantic couples prefer lower levels of illumination. If it is assumed that patrons would be willing to spend more time, and perhaps sample some wine, in more preferable environments, then the following hypothesis is suggested. 4: Couples will spend more time in the wine cellar and be more likely to sample wine when lighting is soft rather than when it is bright.
in-store lighting are, therefore, likely to be reduced (Gorn, 1982; Bruner, 1990). Thus, no specific hypotheses are offered regarding the effect of in-store lighting on the number of items purchased and total sales.
5. Method 5.1. Procedure All observations were recorded between 6 p.m. and 11 p.m. on successive Fridays and Saturdays beginning May 4, 1990 and ending July 28, 1990. Each of the two experimental conditions (i.e., bright versus soft lighting) was counterbalanced with respect to the day of the week via random assignment of the latter to the former. Further, no data were collected on dates where the researchers were able to identify exogenous factors (i.e., holidays, special events, etc.) likely to influence demand. This resulted in 171 observations over sixteen nights. The data were collected via direct observation. Each consumer was observed as s/he entered the wine cellar. The observer, who was naive to the research hypotheses, stood behind a counter labeled “Employees Only” and posed as an inventory keeper. From that position he was easily able to observe each consumer as s/he perused the merchandise in the cellar. Since the wine cellar averaged eleven customers per evening, there was rarely more than one customer in the store at any time, making observation of behavior a relatively easy task.
Hypothesis
Although it is tempting to hypothesize that couples should spend more money when the lighting is soft, such a prediction may be inappropriate in the context of the present study. Because the decision process for wines is usually somewhat involving (Areni and Kim, in press), it entails some deliberate thought (Baker and Lutz, 1987). The effects of an atmospheric variable like
5.2. Independent variables Manipulated variables Bright versus soft lighting was manipulated
by altering the number and, more importantly, the wattage of the lamps in the cellar on a nightly basis. Prior to the study, twenty-two 50 watt bulbs lighted the merchandise and a single 75 watt bulb lighted the dining area of the wine cellar. In the soft lighting condition, the 75 watt bulb over the dining area was removed, leaving the twenty-two
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50 watt bulbs to illuminate the wine cellar. In the bright lighting condition, the experimenter replaced the 75 watt bulb over the dining area, and in every third lamp over the merchandise, the 50 watt bulb was replaced by a 75 watt bulb. The intention was to create an observable difference in illumination in both the dining and merchandise areas of the wine cellar. Employees who worked in the cellar on a regular basis commented that the difference between the the soft lighting condition and the bright condition was quite apparent Measured variables Customer type was measured by classifying patrons as being either single male, single female, a male/female couple, or a group of people not consisting of male/female couples. 5.3. Dependent variables Similar to Hoyer (1984), the observer recorded various aspects of subjects’ inspection of the merchandise on the shelves. Specifically, the observer counted the number of items examined. This was defined as the sum of all items (i.e. wines) for which the customer: (1) stopped to read the shelf label for more than three seconds, (2) pointed to the bottle on the shelf, and/or (3) touched the bottle on the shelf. The observer also counted the number of items handled. In order to qualify as being handled, an item must have been pulled from the shelf by a customer. Finally, the observer recorded the number of items purchased. Since the wine bottles were stored at three distinct shelf levels, with the middle level corresponding to the “eye level” of an adult of average height, the observer was able to record the shelf location of items examined, handled, and purchased. As mentioned earlier, even a single observer could measure these variables accurately because the number of patrons in the cellar at any given time was low (usually one or zero). 4 The observer also recorded whether patrons sampled wine, the amount of time each customer spent in the cellar, and the total dollar amount of each customer’s purchase.
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6. Results Because this study was conducted in the field rather than the laboratory, individual subjects were not randomly assigned to each lighting condition. Rather, the researchers employed a counterbalanced experimental design wherein the successive Fridays and Saturdays of the sixteen weeks of the period of the study were randomly assigned to experimental conditions. Thus, illumination (soft versus bright) and day of the week (Friday versus Saturday) were completely crossed experimental factors with individual shoppers nested within day of the week. The AVOVAS reported below included these three factors. A major threat to internal validity of the study concerns exogenous events (i.e. a professional basketball game at a nearby arena) that might have influenced store traffic on a given night. In order to remove variance in each dependent variable due to differences in levels of store traffic, average behaviors rather than total behaviors constituted the observations for a given night. Table 1 presents the means and standard deviations for each dependent variable by lighting condition. An ANOVA revealed a significant effect of in-store lighting on: (1) the number of items examined (F,,,,, = 5.43, p < 0.02), and (2) the number of items handled (F, i6i = 6.66, p < 0.01). An examination of the means for each condition revealed that, consistent with Hypothesis 1, customers examined and handled more items under bright lighting conditions than under soft lighting conditions. Further, the predicted lighting x shelf level interaction was also significant. 5 However,
4 The distinct activities of the individuals
within a couple or group were difficult to discern. In these cases the activities of the persons were combined to form the observation. Not surprisingly, observations regarding several of the dependent measures were higher for groups and couples. However, since the chi-square statistic for the customer type X fighting condition did not approach significance, this cannot account for the reported findings. 5 The result that patrons examined and handled far more merchandise from the middle shelf level offers further support for the emphasis that sales managers place on obtaining “eye level” shelf space for their company’s products.
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122 Table 1 Means and standard
deviations
by lighting Soft
Number of items examined (Upper level shelf) (Middle level shelf) (Lower level shelf)
a
Number of items handled (Upper level shelf) (Middle level shelf) (Lower level shelf) Number
of items purchased
Total sale (in U.S. dollars) Time Spent (in minutes)
b
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condition Bright
3.04 0.66 2.06 0.32
(3.53) (1.20) (2.26) (0.59)
4.42 0.87 3.28 0.28
(4.02) * * (1.48) (2.87) * (0.62)
0.69 0.13 0.33 0.23
(1.15) (0.45) (0.74) (0.61)
1.54 0.30 0.88 0.36
(2.89) * (0.91) (1.56) * (1.04)
0.10 (0.33)
0.17 (0.81)
4.57 (13.16)
3.88 (5.70)
10.48 (20.94)
8.87 (10.25)
a To be read: subjects examined an average of 3.04 shelf items when the lighting was soft and 4.42 items when the lighting was bright. b To be read: 1.0 bottles of wine were purchased for every 10 customers when the lighting was soft and 1.7 bottles of wine were purchased for every 10 customers when the lighting was bright. * : p < 0.05. **: p < 0.10.
to Hypothesis 2, the number of items examined and the number of items handled from the high level [F,,,,, = 1.05, p < 0.31 (examined) and low and F1,161 = 2.65, p < 0.11 (handled)] level [F,,,,, = 0.24, p < 0.63 (examined) and F,,,,, = 0.89, p < 0.35 (handled)] shelves were not affected by in-store lighting. Instead patrons examined (F,,,,, = 9.08, p < 0.003) and handled (F, 161 = 9.22, p < 0.003) more eye level merchandise when the lighting was bright rather than soft. The main effect of lighting on the amount time spent in the cellar suggested by Hypothesis 3 was not significant (F,,,,, = 0.38, p < 0.54). The customer type X illumination interaction implied by Hypothesis 4 did not emerge for the amount of time spent shopping (F3,159= 0.49, p < 0.69). Mean comparisons revealed that there was little or no effect of lighting on the amount of time couples spent in the cellar (F,,,, = 0.22, p < 0.64). There was, however, a main effect of customer type (F, 16o= 6.50, p < 0.01) wherein couples spent sigiificantly more time in the wine cellar (X = 12 min) than did the other groups of customers combined (X = 7 min). Also contrary contrary
to Hypothesis 4, there was little or no effect of lighting on the likelihood that couples sampled some wine (chi-square = 0.52, p < 0.47). Again, however, a main effect of customer type emerged with couples being significantly more likely to sample wines than noncouples (chi-square 4.60, p < 0.04). A correlation of 0.49 was found between the number of items examined and the number of items handled. This should have been expected since, given the operational definitions, the handling of an item generally necessitated its examination. Further, both could be considered indicators of information processing activity. When these two dependent variables were combined in a MANOVA, the results revealed a significant difference between the mean vectors by lighting condition (F,,,,, = 3.96, p < 0.02).
7. Discussion Based on the reasoning that even soft lighting provides enough visual acuity for customers to “eye level” merchandise (see Birren, examine 1969), we predicted that the impact of lighting on information search would be greatest for merchandise from the “high” and “low” shelves. The result that lighting had a significant effect only suggests that pafor “eye level” merchandise trons’ visual acuity in the soft lighting condition was below the level needed to perform various search activities. Perhaps, in attempting to create an “appropriate” (i.e. soft lighting) atmosphere, management may have adopted a lighting scheme that inhibited customers from examining the merchandise. Although Kotler (1973-1974) has noted the importance of in-store lighting in determining a consumer’s perception of store image, these results suggest that attention must also be given to the impact of lighting on more functional aspects (i.e. the ability to examine merchandise) of the purchase process. For example, restaurants typically employ soft lighting in order to create a “romantic” setting. Although this may produce a desirable dining mood for couples, it may also render the menu difficult to read. The issue of
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“image” versus “function” is relevant for other atmospheric variables as well. Audio stores and record stores, for instance, typically play popular selections in the foreground, presumably in order to demonstrate various products and create a positive purchase environment. However, if customer-employee interaction is impaired by the loud music, potential sales may be lost. The use of atmospheric variables to create the appropriate store image is certainly an important endeavor, but concern must also be given to their impact on the purchase process. Of course, the impact of lighting on the number of items examined and handled may have been mediated by processes other than visual acuity. One possibility is that the soft lighting, which was somewhat lower than that commonly observed in the store, may have suggested that touching the merchandise was inappropriate. A second possibility, suggested by a reviewer, is that the soft lighting served as a cue regarding the quality of the merchandise (see Gorn, 1982). Soft lighting may have implied high quality, especially for customers lacking the knowledge to evaluate the wine selection on other criteria. Since measures of visual acuity and subjects’ perceptions of the store were not included in the present study, it is difficult to distinguish among these explanations. The finding that illumination level had no significant effect on either time spent in the cellar, the likelihood of sampling, or total sales may be attributable to the goals of the patrons upon entering the cellar. Many stated aloud that they had never visited a wine cellar and were curious as to its appearance. Further, a majority did not purchase or consume wine. A customer with a clear goal of purchasing a nice, light bottle of Chenin Blanc would likely prefer a well illuminated cellar that enhances visual acuity and facilitates the examination of merchandise. On the other hand, a customer exploring the wine cellar with no clear purchase intention in mind might prefer the softer lighting to enhance his or her experience. We might have captured this variable by comparing the behavior of individual customers (i.e. purchase directed) to the behavior of couples (i.e. experience directed). However, as
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reported above, too few individual shoppers visited the cellar during the study to allow for statistically reliable comparisons. 7.1. Arousal
theory versus vision theory
Though the experimental hypotheses were based upon research examining the effects of illumination on arousal and visual acuity, the two were not tested against one another directly as mediators of the observed effects. At least two recommendations can be offered for researchers concerned with directly testing arousal theory against vision theory. First, as discussed briefly above, the two theories make opposite predictions regarding the effects of increased levels of illumination on the extent of the perceptual field. Although, as one reviewer notes, these predictions may unfold along different ranges of the illumination continuum, in a controlled laboratory setting with substantial pretesting, it may be possible to isolate the levels of lighting appropriate for testing each prediction. Second, as noted by another reviewer, the habituation effect first discovered by Brookshire and Riesler (1967) is applicable to arousal theory, but not vision theory. Thus, a study that observed the effect of illumination on shopping behavior over time would be better able to distinguish between the two perspectives.
8. Limitations As with any field experiment, this study is limited by two distinct but related shortcomings affecting internal validity. The first concerns a selection bias. Since subjects were “assigned” to experimental conditions on the basis of having happened to enter the wine store on a particular day for any given reason, it is possible that mean differences in information search behavior, purchase intentions, etc. existed among the experimental groups quite independent of the actual treatments. We attempted to assess selection bias by examining the distributions of customer age and customer type within each lighting condition. However, numerous other differences may have
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existed between the two groups, thus biasing our interpretation of the observed variation in search behavior by lighting condition. The second threat to internal validity concerns the inability to control for exogenous factors that might have influenced the amount of store traffic on a given night. Since the dependent variables of the study were average rather than total behaviors, external influences on store traffic need not have influenced the results directly. However, the literature suggests that an individual shopper’s behavior depends on the number of other customers present in the store. Further, this research implies that the presence of other shoppers may produce either beneficial (Milgram, et al., 1969) or detrimental (Harrell et al., 1980; Eroglu and Harrell, 1986; Eroglu and Machleit, 1990) effects for the retailer. Although the wine cellar rarely contained more than two customers, the interpretation of the results should be tempered somewhat due to the failure to control for these social environmental variables. A second shortcoming of this research concerns the inability to assess the reliability of the observational measures due to reliance on a single judge. Although single observers have been employed in previous research on atmospherics (see Milliman, 19821, the behaviors to be recorded were simple in nature (i.e. time spent in a specified area) ensuring a reasonable degree of reliability (see Carlsmith, et al., 1976). The observational measures of information processing activity in the present study were somewhat more complex. Hoyer (1984), however, relied on a single observer to measure the information search and choice processes of supermarket shoppers. Like Hoyer, the authors of the present research attempted to minimize measurement error by developing: (1) highly specific descriptions of the behaviors to be observed, and (2) a coding scheme that was easy to implement. It was hoped that these precautions, combined with the low number of customers on a per hour basis, would produce an acceptable level of accuracy. Finally, the lighting manipulation was reported as a 50% increase in the wattage of every third light bulb in the store. The reactions of the employees of the wine cellar indicated that this
manipulation did indeed produce a noticeable difference in illumination. However, it is much more common in the studies reviewed above to measure illumination in terms of luxs. A lux is the illumination of an area of one square meter produced by a luminous flux of one lumin. An instrument called a luxmeter allows a researcher to assess illumination in luxs (see Dannenmann et al., 1985), and hence to provide a more precise estimate of its impact on visual acuity (see Birren, 1969). Even in the absence of a luxmeter, a subjective measure of brightness (see Butler and Biner, 1987; Biner et al., 1989) could have been employed in a pretest prior to the main study. Future studies should attempt to varify the impact of lighting manipulations on subjective perceptions and visual acuity.
9. Conclusion This investigation found that brighter in-store lighting influenced shoppers to examine and handle more of the merchandise in a wine store. This effect was most pronounced for “eye level” merchandise. The effect of lighting on the amount of time spent in the store and total purchases was, however, nonsignificant. These results are in accord with an increased visual acuity interpretation of the lighting manipulation. Future research should provide a more direct assessment of the internal reactions (i.e. mood, arousal, visual acuity) that mediate the effect of in-store lighting and other atmospheric variables on various aspects of consumer behavior.
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International Journal of
me
El
Research in Marketing
p
ELSEVIER
Intern.
J. of Research
in Marketing
ll(1994)
117-125
The influence of in-store lighting on consumers’ examination of merchandise in a wine store Charles
S. Areni
*, David Kim
Marketing Department, College of Business Administration, Texas Tech. University, Lubbock, TX 79409, USA
Abstract Several studies examining the impact of illumination on behavior are reviewed in this article. Hypotheses are derived regarding the impact of in-store lighting on various aspects of shopping behavior. As part of a field experiment in a large US city, the lighting (soft versus bright) in a centrally located retail establishment was varied over a two month period. The results of an ANOVA indicated that brighter lighting influenced shoppers to examine and handle more merchandise, though sales were not influenced. These findings are discussed in terms of their implications for creating a functional store environment as well as an appropriate store image. 1. Introduction Kotler (1973-1974) coined the term atmospherics to refer to “the effort to design buying environments to produce specific emotional effects in the buyer that enhance his purchase probability” (p. 50). He identified visuaE (color, brightness, size, shape), aural (volume, pitch), olfactory (scent, freshness), and tactile (softness, smoothness, temperature) dimensions of store atmosphere, and suggested that further research was needed regarding the impact of these in-store factors on purchase behavior. Yet, almost eighteen years have passed since the publication of Kotler’s initial article, and the academic literature regarding the impact of various atmospheric elements is still rather sparse.
* Corresponding author. Telephone (806) 742-3238. The authors wish to thank Shelby D. Hunt and five anonymous U&W reviewers for their helpful comments on an earlier draft of this article. 0167-8116/93/$07.00 0 1993 Elsevier SSDI 0167-8116(93)E0044-A
Science
Only a small subset of the in-store dimensions identified by Kotler has been studied empirically. Further, the range of the consumer reactions examined has been rather narrow. Researchers have tended to emphasize overt “quantitative indicators” (i.e. dollar amount spent, time spent, etc.), while largely ignoring other aspects of shopping behavior (Eroglu, et al. 1991). Finally, due to the difficulties of conducting atmospheric research in the field, much of the emergent research has relied on verbal (i.e. Gardner and Siomkos, 1986) or visual (i.e. Eroglu and Machleit, 1990) simulations of retail environments. While these laboratory simulation techniques offer the advantages of methodological expediency and experimental control, their ability to realistically capture the desired store atmosphere is suspect. The literature on atmospherics would, therefore, be enhanced by research examining the impact of some of the untested dimensions of Kotler’s framework on a wider range of consumer behavior in an actual retail setting. Consistent with this objective, this research reviews the liter-
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ature regarding the impact of illumination (i.e. Kotler’s brightness), a variable yet untested in the marketing literature, on various aspects of human and animal behavior. Borrowing from research examining arousal theory and &on theory, the two most prominent theories in the environmental psychology, ergonomics, and animal behavior literature, predictions are made regarding the impact of in-store illumination on shoppers’ search, purchase, and consumption behaviors. These hypotheses are tested via a field experiment in which: (1) the number of shelf items shoppers examined, handled, and purchased, (2) the shelf location of the items examined, handled, and purchased, (3) the total dollar amount of the merchandise purchased, (4) the total amount of time spent shopping, and (5) the frequency with which shoppers consumed merchandise on site were observed under two lighting conditions (soft versus bright) in a downtown wine store.
2. The literature
on lighting
effects
Although the importance of illumination in store design has received some attention in the marketing literature (see, for example, Schewe, 19881, its effects on consumers has yet to be examined empirically. Much of the research reviewed below has, instead, appeared in the environmental psychology and animal behavior literature. Mehrabian (1976) has interpreted the influence of lighting in terms of its ability to arouse individuals. An individual who is highly aroused “will become stimulated, jittery, alert,” whereas a person in a nonarousing environment “will feel relaxed, calm, sluggish, or sleepy.” Moreover, a highly aroused individual will exhibit “increased heart rate, muscle tension, and lowered skin temperature” (p. 21). Mehrabian suggests that lighting is an extremely important determinant of the environment because “brightly lit rooms are more arousing than dimly lit ones” (p. 89). In support of this conceptualization of the effects of illumination, Kumari and Venkatramaiah (1974) found that higher illumination levels were associated with increased cardiovascular activity in college students. Further, Gifford (1988) found that college students expended more effort on an experi-
mental task when illumination levels were higher. In the context of retailing environments, Birren (1969, p. 91) recommends “really bright light” for impulse purchases, where high levels of arousal are likely to be facilitating (Rook, 1987). Markin, et al. (1976) suggest that retailers wishing to induce patrons to peruse more of their merchandise should employ soft lighting in order to reduce the level of customer “stimulation” (i.e. arousal), and hence, slow the pace at which they move through the store. This suggests that retailers can influence the amount of time customers spend shopping via their-selection of in-store lighting levels. However, at least one variable would appear to moderate the influence of instore lighting on behavior, the presence of a romantic partner. Butler and Biner (1987) asked undergraduate students to rate combinations of household settings and behaviors (i.e., bedroom-sleeping; bathroom-brushing teeth, etc.) in terms of their illumination preference (i.e., very dark, dark, bright, and very bright). They found significant differences in preferred lighting levels across behaviors, settings, and individuals. However, the presence of a romantic partner consistently lowered subjects’ preferred lighting levels. Evidently, romantic couples prefer environments that induce low levels of arousal, (perhaps because the situation is already arousing enough). ’ Biner, et al. (1989) asked college students to indicate their lighting level preferences across a number of situations that varied regarding: (1) the visualness of corresponding activities, (2) the complexity of the corresponding activities, and (3) the social context (i.e. friend present, romantic partner present, group of friends present). Similar to Butler and Biner (1987), subjects consistently preferred lower lighting levels when romantic partners rather than platonic friends were present. 2 ’ A reviewer suggested that demand effects may have driven Butler and Biner’s (1987) results regarding romantic settings. Subjects may have guessed that they were supposed to prefer low lighting levels when a romantic partner was present. ‘Although the results of Delay and Richardson (1981), Butler and Biner (1987), and Biner et al. (1989) suggest a gender difference in optimal in-store lighting levels, specific hypotheses could not be tested due to the low frequency of individual male and female patrons.
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An alternative and, in retrospect, intuitive interpretation of the impact of illumination on behavior has been advanced by Biner et al. (1989). They suggest that illumination drives preference and performance not only via arousal, but also through its effect on vision and the scope of an individual’s perceptual field (see also Birren, 1973). They found, for example, that the tendency for romantic couples to prefer lower lighting levels was attenuated when the social setting involved visually oriented activities. Biner et al. (1989) concluded that illumination affects task performance and preference in two relatively dismay be tinct ways: “. . . the [arousal] mechanism working in both visual and nonvisual situations, but uisuaZne~~ of the activity may be setting limits on the process” (p. 13, insert and italics ours). In other words, individuals prefer illumination levels that produce appropriate levels of arousal, unless that illumination level reduces visual acuity below the point needed to complete environmental tasks. Veitch and Kaye (1988) offer further evidence for this interpretation. They found that the conversation among female college students engaged in a mock job applicant evaluation task was louder under conditions of low versus high illuminance. The reduced visual acuity in the low illuminance condition may have inhibited nonverbal communication, thus necessitating more intense (i.e. louder) aural stimuli in order to compensate. Dannenmann et al. (1984-1985) extend the notion of visual acuity to include the scope of the perceptual field in interpreting the impact of illumination on the behavior of calves: 3 one can conclude that at [the lowest levels of lighting] the animals were not able to see some
3 Arousal theory predicts that the perceptual field narrows as arousal increases (see Easterbrook, 1959). Thus, arousal theory and vision theory make disparate predictions regarding the impact of illumination on the size of an individual’s perceptual field. This would appear to be a fruitful direction for researchers interested in testing the two theories against one another.
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of the more distant stimuli. At [moderate levels of lighting] the visual capacity of the eye is better, so that all stimuli can be perceived, but need closer examination for a final recognition. All objects or stimuli could be recognized quickly at [the highest levels of lighting]. The reactions of play and sexual behavior and other social behavior patterns underline this assumption (pp. 256-257, insert ours). In the context of retail settings, these findings suggest that shoppers will be less likely to engage in visually oriented activities (i.e. checking prices, reading labels, etc.) when in-store lighting levels are lower.
3. Field experiment
setting
The study was conducted in a downtown restaurant in a large southeastern city. The restaurant featured a wine cellar, clearly visible through a glass section of the floor, that was open to patrons who wished to just visit, sample some wines, or purchase some bottles of wine. This area of the restaurant contained hundreds of bottles of wine, shelved horizontally in typical wine cellar fashion, as well as a small dining area for patrons who wished to sample some wines by the glass. This unique setting afforded the opportunity to examine the impact of in-store lighting on consumers’ reaction to the cellar, their actual purchase behavior, and their tendency to remain in the cellar to sample wines.
4. Hypotheses Given the shelf requires examining suggests
that the examination of merchandise off (i.e. to read labels, check prices, etc.) some level of visual acuity, the research the effect of illumination on vision the following hypothesis.
Hypothesis 1: Patrons will examine and handle more merchandise when the lighting is bright rather than when it is soft.
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The work of Birren (1969, pp. 45-47) implies that relatively low levels of illumination are adequate when the stimulus to be processed is within a few feet. Merchandise on eye level shelves would certainly be within this range. Hence, it is likely that the increase in the number of items examined and handled would come from merchandise on the high and low level (i.e. low visual acuity) shelves. The following hypothesis reflects this moderating influence. Hypothesis
2: The effect of lighting on the number of items examined and handled will be observed for merchandise on the high and low level shelves, but not for merchandise on the eye level shelves.
Research examining the effects of illumination on arousal suggest that lower levels of in-store lighting slow the pace with which shoppers move through a store. The following hypothesis is based on this reasoning. Hypothesis
3: Patrons will spend more time in the cellar when the lighting is soft rather than when it is bright.
Butler and Biner (1987) and Biner et al. (19891, however, have found that romantic couples prefer lower levels of illumination. If it is assumed that patrons would be willing to spend more time, and perhaps sample some wine, in more preferable environments, then the following hypothesis is suggested. 4: Couples will spend more time in the wine cellar and be more likely to sample wine when lighting is soft rather than when it is bright.
in-store lighting are, therefore, likely to be reduced (Gorn, 1982; Bruner, 1990). Thus, no specific hypotheses are offered regarding the effect of in-store lighting on the number of items purchased and total sales.
5. Method 5.1. Procedure All observations were recorded between 6 p.m. and 11 p.m. on successive Fridays and Saturdays beginning May 4, 1990 and ending July 28, 1990. Each of the two experimental conditions (i.e., bright versus soft lighting) was counterbalanced with respect to the day of the week via random assignment of the latter to the former. Further, no data were collected on dates where the researchers were able to identify exogenous factors (i.e., holidays, special events, etc.) likely to influence demand. This resulted in 171 observations over sixteen nights. The data were collected via direct observation. Each consumer was observed as s/he entered the wine cellar. The observer, who was naive to the research hypotheses, stood behind a counter labeled “Employees Only” and posed as an inventory keeper. From that position he was easily able to observe each consumer as s/he perused the merchandise in the cellar. Since the wine cellar averaged eleven customers per evening, there was rarely more than one customer in the store at any time, making observation of behavior a relatively easy task.
Hypothesis
Although it is tempting to hypothesize that couples should spend more money when the lighting is soft, such a prediction may be inappropriate in the context of the present study. Because the decision process for wines is usually somewhat involving (Areni and Kim, in press), it entails some deliberate thought (Baker and Lutz, 1987). The effects of an atmospheric variable like
5.2. Independent variables Manipulated variables Bright versus soft lighting was manipulated
by altering the number and, more importantly, the wattage of the lamps in the cellar on a nightly basis. Prior to the study, twenty-two 50 watt bulbs lighted the merchandise and a single 75 watt bulb lighted the dining area of the wine cellar. In the soft lighting condition, the 75 watt bulb over the dining area was removed, leaving the twenty-two
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50 watt bulbs to illuminate the wine cellar. In the bright lighting condition, the experimenter replaced the 75 watt bulb over the dining area, and in every third lamp over the merchandise, the 50 watt bulb was replaced by a 75 watt bulb. The intention was to create an observable difference in illumination in both the dining and merchandise areas of the wine cellar. Employees who worked in the cellar on a regular basis commented that the difference between the the soft lighting condition and the bright condition was quite apparent Measured variables Customer type was measured by classifying patrons as being either single male, single female, a male/female couple, or a group of people not consisting of male/female couples. 5.3. Dependent variables Similar to Hoyer (1984), the observer recorded various aspects of subjects’ inspection of the merchandise on the shelves. Specifically, the observer counted the number of items examined. This was defined as the sum of all items (i.e. wines) for which the customer: (1) stopped to read the shelf label for more than three seconds, (2) pointed to the bottle on the shelf, and/or (3) touched the bottle on the shelf. The observer also counted the number of items handled. In order to qualify as being handled, an item must have been pulled from the shelf by a customer. Finally, the observer recorded the number of items purchased. Since the wine bottles were stored at three distinct shelf levels, with the middle level corresponding to the “eye level” of an adult of average height, the observer was able to record the shelf location of items examined, handled, and purchased. As mentioned earlier, even a single observer could measure these variables accurately because the number of patrons in the cellar at any given time was low (usually one or zero). 4 The observer also recorded whether patrons sampled wine, the amount of time each customer spent in the cellar, and the total dollar amount of each customer’s purchase.
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6. Results Because this study was conducted in the field rather than the laboratory, individual subjects were not randomly assigned to each lighting condition. Rather, the researchers employed a counterbalanced experimental design wherein the successive Fridays and Saturdays of the sixteen weeks of the period of the study were randomly assigned to experimental conditions. Thus, illumination (soft versus bright) and day of the week (Friday versus Saturday) were completely crossed experimental factors with individual shoppers nested within day of the week. The AVOVAS reported below included these three factors. A major threat to internal validity of the study concerns exogenous events (i.e. a professional basketball game at a nearby arena) that might have influenced store traffic on a given night. In order to remove variance in each dependent variable due to differences in levels of store traffic, average behaviors rather than total behaviors constituted the observations for a given night. Table 1 presents the means and standard deviations for each dependent variable by lighting condition. An ANOVA revealed a significant effect of in-store lighting on: (1) the number of items examined (F,,,,, = 5.43, p < 0.02), and (2) the number of items handled (F, i6i = 6.66, p < 0.01). An examination of the means for each condition revealed that, consistent with Hypothesis 1, customers examined and handled more items under bright lighting conditions than under soft lighting conditions. Further, the predicted lighting x shelf level interaction was also significant. 5 However,
4 The distinct activities of the individuals
within a couple or group were difficult to discern. In these cases the activities of the persons were combined to form the observation. Not surprisingly, observations regarding several of the dependent measures were higher for groups and couples. However, since the chi-square statistic for the customer type X fighting condition did not approach significance, this cannot account for the reported findings. 5 The result that patrons examined and handled far more merchandise from the middle shelf level offers further support for the emphasis that sales managers place on obtaining “eye level” shelf space for their company’s products.
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122 Table 1 Means and standard
deviations
by lighting Soft
Number of items examined (Upper level shelf) (Middle level shelf) (Lower level shelf)
a
Number of items handled (Upper level shelf) (Middle level shelf) (Lower level shelf) Number
of items purchased
Total sale (in U.S. dollars) Time Spent (in minutes)
b
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condition Bright
3.04 0.66 2.06 0.32
(3.53) (1.20) (2.26) (0.59)
4.42 0.87 3.28 0.28
(4.02) * * (1.48) (2.87) * (0.62)
0.69 0.13 0.33 0.23
(1.15) (0.45) (0.74) (0.61)
1.54 0.30 0.88 0.36
(2.89) * (0.91) (1.56) * (1.04)
0.10 (0.33)
0.17 (0.81)
4.57 (13.16)
3.88 (5.70)
10.48 (20.94)
8.87 (10.25)
a To be read: subjects examined an average of 3.04 shelf items when the lighting was soft and 4.42 items when the lighting was bright. b To be read: 1.0 bottles of wine were purchased for every 10 customers when the lighting was soft and 1.7 bottles of wine were purchased for every 10 customers when the lighting was bright. * : p < 0.05. **: p < 0.10.
to Hypothesis 2, the number of items examined and the number of items handled from the high level [F,,,,, = 1.05, p < 0.31 (examined) and low and F1,161 = 2.65, p < 0.11 (handled)] level [F,,,,, = 0.24, p < 0.63 (examined) and F,,,,, = 0.89, p < 0.35 (handled)] shelves were not affected by in-store lighting. Instead patrons examined (F,,,,, = 9.08, p < 0.003) and handled (F, 161 = 9.22, p < 0.003) more eye level merchandise when the lighting was bright rather than soft. The main effect of lighting on the amount time spent in the cellar suggested by Hypothesis 3 was not significant (F,,,,, = 0.38, p < 0.54). The customer type X illumination interaction implied by Hypothesis 4 did not emerge for the amount of time spent shopping (F3,159= 0.49, p < 0.69). Mean comparisons revealed that there was little or no effect of lighting on the amount of time couples spent in the cellar (F,,,, = 0.22, p < 0.64). There was, however, a main effect of customer type (F, 16o= 6.50, p < 0.01) wherein couples spent sigiificantly more time in the wine cellar (X = 12 min) than did the other groups of customers combined (X = 7 min). Also contrary contrary
to Hypothesis 4, there was little or no effect of lighting on the likelihood that couples sampled some wine (chi-square = 0.52, p < 0.47). Again, however, a main effect of customer type emerged with couples being significantly more likely to sample wines than noncouples (chi-square 4.60, p < 0.04). A correlation of 0.49 was found between the number of items examined and the number of items handled. This should have been expected since, given the operational definitions, the handling of an item generally necessitated its examination. Further, both could be considered indicators of information processing activity. When these two dependent variables were combined in a MANOVA, the results revealed a significant difference between the mean vectors by lighting condition (F,,,,, = 3.96, p < 0.02).
7. Discussion Based on the reasoning that even soft lighting provides enough visual acuity for customers to “eye level” merchandise (see Birren, examine 1969), we predicted that the impact of lighting on information search would be greatest for merchandise from the “high” and “low” shelves. The result that lighting had a significant effect only suggests that pafor “eye level” merchandise trons’ visual acuity in the soft lighting condition was below the level needed to perform various search activities. Perhaps, in attempting to create an “appropriate” (i.e. soft lighting) atmosphere, management may have adopted a lighting scheme that inhibited customers from examining the merchandise. Although Kotler (1973-1974) has noted the importance of in-store lighting in determining a consumer’s perception of store image, these results suggest that attention must also be given to the impact of lighting on more functional aspects (i.e. the ability to examine merchandise) of the purchase process. For example, restaurants typically employ soft lighting in order to create a “romantic” setting. Although this may produce a desirable dining mood for couples, it may also render the menu difficult to read. The issue of
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“image” versus “function” is relevant for other atmospheric variables as well. Audio stores and record stores, for instance, typically play popular selections in the foreground, presumably in order to demonstrate various products and create a positive purchase environment. However, if customer-employee interaction is impaired by the loud music, potential sales may be lost. The use of atmospheric variables to create the appropriate store image is certainly an important endeavor, but concern must also be given to their impact on the purchase process. Of course, the impact of lighting on the number of items examined and handled may have been mediated by processes other than visual acuity. One possibility is that the soft lighting, which was somewhat lower than that commonly observed in the store, may have suggested that touching the merchandise was inappropriate. A second possibility, suggested by a reviewer, is that the soft lighting served as a cue regarding the quality of the merchandise (see Gorn, 1982). Soft lighting may have implied high quality, especially for customers lacking the knowledge to evaluate the wine selection on other criteria. Since measures of visual acuity and subjects’ perceptions of the store were not included in the present study, it is difficult to distinguish among these explanations. The finding that illumination level had no significant effect on either time spent in the cellar, the likelihood of sampling, or total sales may be attributable to the goals of the patrons upon entering the cellar. Many stated aloud that they had never visited a wine cellar and were curious as to its appearance. Further, a majority did not purchase or consume wine. A customer with a clear goal of purchasing a nice, light bottle of Chenin Blanc would likely prefer a well illuminated cellar that enhances visual acuity and facilitates the examination of merchandise. On the other hand, a customer exploring the wine cellar with no clear purchase intention in mind might prefer the softer lighting to enhance his or her experience. We might have captured this variable by comparing the behavior of individual customers (i.e. purchase directed) to the behavior of couples (i.e. experience directed). However, as
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reported above, too few individual shoppers visited the cellar during the study to allow for statistically reliable comparisons. 7.1. Arousal
theory versus vision theory
Though the experimental hypotheses were based upon research examining the effects of illumination on arousal and visual acuity, the two were not tested against one another directly as mediators of the observed effects. At least two recommendations can be offered for researchers concerned with directly testing arousal theory against vision theory. First, as discussed briefly above, the two theories make opposite predictions regarding the effects of increased levels of illumination on the extent of the perceptual field. Although, as one reviewer notes, these predictions may unfold along different ranges of the illumination continuum, in a controlled laboratory setting with substantial pretesting, it may be possible to isolate the levels of lighting appropriate for testing each prediction. Second, as noted by another reviewer, the habituation effect first discovered by Brookshire and Riesler (1967) is applicable to arousal theory, but not vision theory. Thus, a study that observed the effect of illumination on shopping behavior over time would be better able to distinguish between the two perspectives.
8. Limitations As with any field experiment, this study is limited by two distinct but related shortcomings affecting internal validity. The first concerns a selection bias. Since subjects were “assigned” to experimental conditions on the basis of having happened to enter the wine store on a particular day for any given reason, it is possible that mean differences in information search behavior, purchase intentions, etc. existed among the experimental groups quite independent of the actual treatments. We attempted to assess selection bias by examining the distributions of customer age and customer type within each lighting condition. However, numerous other differences may have
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existed between the two groups, thus biasing our interpretation of the observed variation in search behavior by lighting condition. The second threat to internal validity concerns the inability to control for exogenous factors that might have influenced the amount of store traffic on a given night. Since the dependent variables of the study were average rather than total behaviors, external influences on store traffic need not have influenced the results directly. However, the literature suggests that an individual shopper’s behavior depends on the number of other customers present in the store. Further, this research implies that the presence of other shoppers may produce either beneficial (Milgram, et al., 1969) or detrimental (Harrell et al., 1980; Eroglu and Harrell, 1986; Eroglu and Machleit, 1990) effects for the retailer. Although the wine cellar rarely contained more than two customers, the interpretation of the results should be tempered somewhat due to the failure to control for these social environmental variables. A second shortcoming of this research concerns the inability to assess the reliability of the observational measures due to reliance on a single judge. Although single observers have been employed in previous research on atmospherics (see Milliman, 19821, the behaviors to be recorded were simple in nature (i.e. time spent in a specified area) ensuring a reasonable degree of reliability (see Carlsmith, et al., 1976). The observational measures of information processing activity in the present study were somewhat more complex. Hoyer (1984), however, relied on a single observer to measure the information search and choice processes of supermarket shoppers. Like Hoyer, the authors of the present research attempted to minimize measurement error by developing: (1) highly specific descriptions of the behaviors to be observed, and (2) a coding scheme that was easy to implement. It was hoped that these precautions, combined with the low number of customers on a per hour basis, would produce an acceptable level of accuracy. Finally, the lighting manipulation was reported as a 50% increase in the wattage of every third light bulb in the store. The reactions of the employees of the wine cellar indicated that this
manipulation did indeed produce a noticeable difference in illumination. However, it is much more common in the studies reviewed above to measure illumination in terms of luxs. A lux is the illumination of an area of one square meter produced by a luminous flux of one lumin. An instrument called a luxmeter allows a researcher to assess illumination in luxs (see Dannenmann et al., 1985), and hence to provide a more precise estimate of its impact on visual acuity (see Birren, 1969). Even in the absence of a luxmeter, a subjective measure of brightness (see Butler and Biner, 1987; Biner et al., 1989) could have been employed in a pretest prior to the main study. Future studies should attempt to varify the impact of lighting manipulations on subjective perceptions and visual acuity.
9. Conclusion This investigation found that brighter in-store lighting influenced shoppers to examine and handle more of the merchandise in a wine store. This effect was most pronounced for “eye level” merchandise. The effect of lighting on the amount of time spent in the store and total purchases was, however, nonsignificant. These results are in accord with an increased visual acuity interpretation of the lighting manipulation. Future research should provide a more direct assessment of the internal reactions (i.e. mood, arousal, visual acuity) that mediate the effect of in-store lighting and other atmospheric variables on various aspects of consumer behavior.
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