ArticlePDF Available

Shining Light on Atmospherics: How Ambient Light Influences Food Choices



Retail atmospherics Is emerging as a major competitive tool, and It Is especially notable in the restaurant industry, where lighting is used to create the overall ambience and influence consumer experience. In addition to influencing overall experience, can ambient light luminance have unintended consequences in terms of influencing what diners order? The results of a field study at multiple locations of a major restaurant chain and a series of lab studies robustly show that consumers tend to choose less healthy food options when ambient lighting is dim (vs. bright). Process evidence suggests that this phenomenon occurs because ambient light luminance influences mental alertness, which in turn influences food choices. While restaurant and grocery store managers can use these insights and their ambient light switches to nudge consumers toward targeted food choices, such as healthy or high-margin signature items, health-conscious consumers can opt for dining environments with bright ambient lighting.
Shining Light on Atmospherics: How Ambient Light Influences Food Choices
Forthcoming in Journal of Marketing Research (2016)
* Dipayan Biswas ( is Professor of Marketing, University of South Florida,
Tampa, FL 33620. Courtney Szocs ( is Assistant Professor of Marketing,
Portland State University, Portland, OR 97201. Brian Wansink ( is John S.
Dyson Professor of Marketing, Dyson School of Applied Economics and Management, Cornell
University, Ithaca, NY 14850. Roger Chacko ( is Chief Marketing
Officer at Carlson Rezidor (Radisson) Group of Hotels. The authors thank Don Lehmann and the
JMR review team for helpful comments and suggestions.
Shining Light on Atmospherics: How Ambient Light Influences Food Choices
Retail atmospherics is emerging as a major competitive tool, and it is especially notable in the
restaurant industry where lighting is used to create the overall ambience and influence consumer
experience. However, can ambient light luminance have unintended consequences on what a
diner orders? The results of a field study at multiple locations of a major restaurant chain and a
series of lab studies robustly show that consumers tend to choose less healthy food options when
ambient lighting is dim (vs. bright). Process evidence suggests that this phenomenon occurs
because ambient light luminance influences mental alertness, which in turn influences food
choices. While restaurant and perhaps grocery store managers can use these insights and their
ambient light switches to nudge consumers toward targeted food choices, such as healthy or
environmentally friendly foods or high margin signature items, health conscious consumers can
opt for dining environments with bright ambient lighting.
Keywords: ambient light, retail atmospherics, luminance, healthy and unhealthy food choice,
sensory marketing.
If a restaurant makes its ambient lighting brighter versus dimmer, would the patrons order
differently? Along with having implications for consumer health and wellbeing, this is a
managerially relevant research question since retail and restaurant managers are increasingly
focusing on atmospherics to influence consumer experiences and to differentiate themselves
from competitors (Broniarczyk and Hoyer 2006; Carroll 2012; Weitz and Whitfield 2006). More
broadly, marketers are placing greater emphasis on in-store ambience and displays as strategic
marketing tools (Chandon et al. 2009). Ambient factors can be especially critical since managers
can make subtle and inexpensive changes to the store or restaurant ambience on a regular basis,
and sometimes at different times of the day.
While prior research has extensively examined different critical aspects of atmospherics
(Spence et al. 2014), such as scent (Morrin and Ratneshwar 2003), music (Baker et al. 2002;
Bruner 1990), flooring (Meyers-Levy, Zhu, and Jiang 2010), and ceiling height (Meyers-Levy
and Zhu 2007), little is known about how ambient lighting levels might influence specific
product choices. This is especially noteworthy since in many retail/restaurant contexts, managers
can control the ambient light luminance (brightness or dimness) level with relative ease and with
minimal monetary investment by merely adjusting a dial or flipping a switch.
Accordingly, this research examines how increasing versus decreasing the luminance of
ambient light might influence choices between food items that are considered healthy versus
unhealthy. Our findings have both conceptual and practical implications. From a conceptual
perspective, the findings of our studies robustly document how ambient light luminance impacts
choices between healthy and unhealthy food options. They thus contribute to the findings of a
wider set of studies, examining choices for healthy/unhealthy options, focusing on such factors
as mode of decision-making (Shiv and Fedorikhin 1999), temptation (Dhar and Wertenbroch
2012), self-control (Baumeister 2002; Kivetz and Simonson 2002), display patterns (Romero and
Biswas 2016), and health claims (Chandon and Wansink 2007), among others. We contribute to
this literature stream by examining the role of atmospherics, such as in the form of ambient light
luminance, in influencing choices between healthy/unhealthy options.
Following a brief background on how lighting has influenced general, non-choice
behavior (such as quantity of food consumed), we build our conceptual framework and then test
our hypotheses through five experiments (with one conducted at several locations of a chain
restaurant and four conducted in the lab). We also conducted another experiment, reported in the
Web Appendix. We first examine the main effects of ambient light on product choices through a
field experiment (Study 1a) as well as through controlled lab experiments (Studies 1b and 1c)
and find that preference for healthy food options is higher when choices are made in bright (vs.
dim) ambient light luminance. Studies 2a-2b provide process evidence for the proposed
theorization by examining the moderating effect of inducing alertness. We also report the results
of an additional study, in the Web Appendix, where we examine the moderating effects of
inducing sleepiness (i.e., reduced alertness).
Ambient Lighting and Behavior
Ambient lighting can influence stimulation levels, cognitive associations, and overall
behavior in general (Spence et al. 2014) and hence can be a potentially effective tool for
marketers. Moreover, since it is easy and inexpensive to alter ambient lighting, not surprisingly,
stores and restaurants vary greatly in terms of ambient light luminance. Light luminance is
measured in lux (lumens per square meter) (Thimijan and Heins 1983). To put things in
perspective, the luminance of full outdoor daylight is approximately 10,000 lux and twilight is
approximately 10 lux (Nielsen, Svendsen, and Jensen 2011; The Engineering Toolbox 2012;
Thorington 1985). Common light luminance levels for clerical tasks at offices range from 750–
2,000 lux (Bosworth Instruments 2013), and some states even mandate that health care treatment
and surgery rooms be at least 1614 lux ( 2010).
In the context of restaurants, based on anecdotal evidence, dimly lit restaurants tend to
have ambient light luminance between 10 and 40 lux; however, some restaurants have more
extreme levels of ambient light luminance. For example, Qi, a restaurant in New York City (near
Times Square) has such dim ambient lighting that many people find it difficult to read the menu
inside the restaurant. Along similar lines, the menus at Cero’s Speakeasy (a restaurant in Tampa,
Florida) come with reading lights attached since the ambient lighting is so dim that diners could
otherwise not see the menu. At an even more extreme level, it is literally pitch dark at the
Opaque restaurant chain and the company capitalizes on the idea of dark dining as a point of
differentiation (Sala 2010).
Incidentally, there are norms and expectations associated with lighting and other aspects
of atmospherics; for example, fast food restaurants tend to have bright lights and fast music
while fine dining restaurants tend to have dim lights and relaxing music (Wansink and van
Ittersum 2012). There might also be self-selection issues, whereby certain consumers might
prefer restaurants with dimmer versus brighter lighting (Spence et al. 2014).
The limited research examining the effects of ambient light has had a much different
focus than on choice. For instance, Wansink and van Ittersum (2012), in an experimental study at
a Hardee’s fast food franchise restaurant, softened the lighting and music in the restaurant to
create a relatively fine dining experience condition and found that consumers spent more time
and ate less in the “fine dining” area than in the main dining area. Since these consumers were
assigned to the lighting (bright or dim) condition after they had selected food, it is not known if
such a change would have influenced initial food choices. Along the same lines, research shows
that soft or warm lighting tends to cause people to stay longer and enjoy an unplanned dessert or
drink (Wansink 2004). However, from these studies, it is unclear as to how lighting might
influence the healthfulness of the ordered foods and beverages.
A series of studies in “dark restaurants” (Scheibehenne, Todd, and Wansink 2010;
Wansink et al. 2012) manipulated visual cue availability of food items by having diners eat in
either the presence versus absence of light. They found that consumption volume was higher
when participants ate in the absence of light (in total darkness) than in the presence of light. In
these studies, all participants ate the same food items and hence it is again not clear how ambient
light might influence food choices.
Prior studies have also examined the effects of light on consumers’ wall color perceptions
and subsequent product evaluations. For instance, Oberfeld et al. (2009) found that white wine
tasted better in rooms where lighting was used to make the walls seem blue or red. Similarly,
Areni and Kim (1994) found that bright versus soft ambient light led to consumers handling and
examining more bottles of wine, with the effects being moderated by shelf level of the wine; it is
not clear though what the light luminance levels were across the conditions or how lighting
influenced choices.
Although these prior studies demonstrate interesting findings, none of these studies
focused on ambient light luminance level and its potential effects on choices involving healthy
and unhealthy items. As a result, it remains unclear how ambient light luminance level might
influence consumers’ choices between healthy versus unhealthy food options. Moreover, our
studies differ from these prior studies because we do not examine the absence versus presence of
light (i.e., total darkness vs. presence of lighting) nor do we examine the effects of light color on
wall color perceptions. Instead, in our studies, across all conditions, light is present and is of the
same color but varies only in the level of luminance (i.e., brightness/dimness).
We next discuss factors that can influence choices between relatively healthy and
unhealthy foods. Following this, there is a discussion of how ambient light might influence
product choices by affecting decision making modes, alertness levels, inhibition, and one's focus
on self-presentation.
Making Choices between Healthy and Unhealthy Options
When choosing between healthy and unhealthy options, consumers are in essence
choosing between options that dominate on affective/hedonic dimensions and thus appeal to the
heart (i.e., unhealthy options) and options that dominate on cognitive/utilitarian dimensions and
thus appeal to the mind (i.e., healthy options) (Khan, Dhar, and Wertenbroch 2005; Shiv and
Fedorikhin 1999). When faced with conflicts of the heart and mind, the consumer’s decision-
making mode plays an influential role in determining the choice outcome. Specifically, when
choices are made in a more deliberate (or cognitive) manner, there is increased preference for
virtues or healthy food options (Shiv and Fedorikhin 1999). As a result, there tends to be a
positive correlation between the degree of attentional resources devoted to the choice task and
preference for the healthy option (Dhar and Wertenbroch 2012). Along similar lines, research
shows that mindful eating leads to healthier food consumption (Wansink 2006). Moreover, at a
broader level, choices between healthy and unhealthy options are often influenced by trade-offs
between short-term benefits in terms of taste/pleasure and long-term benefits in terms of
health/wellbeing (Romero and Biswas 2016). Greater degree of deliberate and cognitive
processing tends to enhance focus on long-term benefits (Dhar and Wertenbroch 2012; Gardner
et al 2014).
So between high and low levels of ambient light luminance, which condition would
facilitate a higher degree of mindful or deliberate cognitive decision-making versus mindless or
affective decision-making? Research suggests that dim (vs. bright) ambient light reduces mental
alertness (Cajochen 2007), inhibition (Hirsch, Galinsky, and Zhong 2011), and self-presentation
(Kasof 2002; Zhong, Bohns, and Gino 2010). As will be discussed in detail below, these
theoretical accounts would predict greater preference for healthy options in bright (vs. dim)
ambient light.
Ambient Light and Mental Alertness
Sleep research as well as ergonomics research show that bright lighting increases mental
alertness because among other physiological changes, bright light suppresses melatonin, which is
the primary controller of circadian (day/night) sleep bio-rhythms (Lowden, Åkerstedt, and
Wibom 2004). For instance, bright lighting leads to enhanced alertness and subsequently
enhances task performance (Crowley et al. 2003; Daurat et al.1993). In contrast to the alerting
effects of bright lighting, low levels of light luminance (i.e., dim lights) have been shown to
increase sleepiness and reduce alertness (Badia et al. 1991; Lowden, Åkerstedt, and Wibom
Overall, ambient light influences physiological reactions in terms of melatonin
production, core body temperature, heart rate, and cortisol production, all of which are correlated
with alertness levels (Lockley et al. 2006). Specifically, bright (vs. dim) light influences human
psychophysiology instantaneously by inducing endocrine, leading to suppression of melatonin
and an increase in cortisol levels, along with physiological changes in terms of enhanced core
body temperature, and also psychological changes in the form of reduced sleepiness and
enhanced alertness (Rüger et al. 2006).
In the context of the present research, these literature streams suggest that consumers will
be less mentally alert in dimly (vs. brightly) lit environments due to psychophysiological factors.
Additional research across different domains has established a positive relationship between
mental alertness, attention, and cognitive performance (Lim and Dinges 2008; Thomas et al.
2000). In fact, emerging research in neuroscience shows that ambient light can modulate cortical
activity related to alertness, which in turn can stimulate cognitive functions and activity (Virginie
et al. 2015). In essence, a higher level of mental alertness enhances cognitive performance.
Therefore, it can be proposed that in dim (vs. bright) ambient light, consumers will be less alert
mentally and hence less likely to rely on cognitive processing when choosing between the
healthy and unhealthy food options.
When consumers choose between healthy and unhealthy food items, a lower level of
cognitive availability tends to lead to greater preference for unhealthy options (Dhar and
Wertenbroch 2012; Shiv and Fedorikhin 1999). Moreover, research also shows that reduced
mental alertness leads to mindless decisions (Janssen et al. 2008) and mindless decisions tend to
lead to unhealthy behavior (Wansink, Just, and Payne 2009). Thus, based on our preceding
discussions, we propose that in dim (vs. bright) lighting there will be greater preference for the
unhealthy food item. In other words, there will be greater preference for the healthy option when
ambient light is bright (vs. dim). Formally stated:
H1: When given a choice between healthy and unhealthy options, consumers will have
greater preference for healthy options when ambient light luminance is bright (vs. dim).
Ambient Light, Self-Presentation and Inhibition
Theories related to self-presentation and inhibition also predict similar behavioral
outcomes to that predicted by H1. Research in the domain of self-presentation suggests that
focus and concern about self-presentation is enhanced in the presence of bright light (Kasof
2002; Zhong, Bohns, and Gino 2010). Since enhanced focus on self-presentation is likely to lead
to greater degree of preference for healthy options, there should be higher choice likelihood of
the healthy option when ambient light is bright (vs. dim), consistent with H1’s prediction.
In a related vein, research in the domain of inhibition suggests that consumer decision-
making will be more disinhibited in dim (vs. bright) ambient light. This is mainly because dim
lighting gives people a sense of perceived illusory anonymity, which in turn encourages moral
transgressions (Zhong, Bohns, and Gino 2010). In the context of choosing between healthy and
unhealthy product options, disinhibition is likely to enhance preference for the unhealthy (vs.
healthy) option since enhanced disinhibition would imply reduced self-control, which in turn
would reduce the likelihood of choosing the healthy option. In other words, theories related to
inhibition would also suggest that preference for the healthy option should be higher when
ambient light is bright (vs. dim). In essence, research on self-presentation and inhibition would
make similar predictions as H1.
It might be noted though, that as demonstrated by studies across different domains,
although mental alertness and disinhibition are different constructs, they can have a causal
(Baumeister, Heatherton, and Tice 1994; Herman and Polivy 1993) or correlational relationship
(Verwey and Zaidel 2000). That is, reduced mental alertness can lead to disinhibition
(Baumeister, Heatherton, and Tice 1994; Herman and Polivy 1993). Similarly, extraneous factors
can affect both these constructs; for instance, a high level of intoxication not only leads to
reduced mental alertness, but also reduces inhibition (Heinz et al. 2011; Steele and Josephs
1990). Along similar lines, self-presentation focus influences inhibition, whereby focusing on
self-presentation tends to make people more inhibited (Heatherton, Striepe, and Wittenberg
1998; Leary and Atherton 1986).
In summary, building on research related to alertness, inhibition, and self-presentation,
H1 predicts higher preference for the healthier option when ambient light is bright (vs. dim). We
test this hypothesis in Study 1a.
Study 1a was a field experiment conducted at four different locations of a restaurant
chain, in collaboration with the corporate management. The restaurants where the study was
conducted are part of a major casual dining chain with over 1200 locations in 23 countries. The
four locations where the study was run are all based in the same metropolitan area of a major city
in the US, and these locations are in close proximity to each other. This study was a single factor
between-subjects experiment with two manipulated conditions of ambient light luminance
(bright vs. dim).
The experiment was conducted at the four restaurant outlets on a single random weekday.
The study was undertaken on a single day to avoid potential confounds related to weather and
other extraneous variables. The study was run between 6 and 8 pm. Two of the restaurants had
dim lighting while the other two had bright lighting. In the dim ambient light condition, the
restaurants had a low light luminance level of 25 lux while in the bright ambient light condition,
the light luminance was set at 250 lux. The light luminance levels were based on a pretest using
interactive feedback from the restaurant staff (at a different location than where the main studies
were conducted). Specifically, the restaurant staff at the pretest site felt it was too dark below 25
lux and anything above 250 lux was deemed as too bright for the restaurant. The usual luminance
level at these restaurants varied between 100 and 125 lux and all these locations had similar
layout and decor.
To avoid implicit demand effects, none of the researchers were involved with selecting or
approaching participants; restaurant employees were asked to randomly approach restaurant
patrons and ask them to fill out a short survey. The staff members at these locations did not have
any information about the hypotheses or purposes of the study. Senior executives from the
corporate office oversaw the procedure to ensure consistency across the four locations. Each
restaurant was told to get approximately forty completed surveys. This led to a total of one
hundred sixty restaurant patrons (51% females), completing the survey (N = 78 for the dim light
restaurants and N = 82 for the bright light restaurants), across the four locations.
The study survey asked participants which menu item(s) they ordered and the restaurant
staff unobtrusively verified whether the item indicated on the survey matched the actual order.
Participants were also asked about their alertness level, with a reverse-coded measure (1 = very
alert, 7 = not at all alert). Patrons also indicated their age in brackets, with 19% being between
21-29, 16% between 30-39, 19% between 40-49, 23% between 50-59, 17% between 60-69, and
6% at 70+.
The researchers, a priori, coded each item on the restaurant menu as healthy versus
unhealthy based on prior commercial standards (Pope et al. 2014). Specifically, grilled and baked
fish, white meat (chicken and turkey), and vegetables were coded as healthy while fried food
items, and red meat (beef and pork) were coded as unhealthy. Each restaurant patron’s order was
accordingly coded as healthy versus unhealthy. If somebody ordered an unhealthy item,
irrespective of whether they ordered something healthy along with it, the overall meal was coded
as “unhealthy” ordering (e.g., Chernev 2011). For example, if someone ordered a steak and a
salad, it was coded as “unhealthy” ordering. We also computed the calorie content for the
ordered food item(s).
Main tests for choice and alertness. Consistent with H1, for the restaurant locations with
bright (vs. dim) ambient light, a higher proportion of patrons ordered healthy foods (52.44% vs.
34.62%; χ2 = 5.16, p < .05). Figure 1 graphically presents the key findings. Also, consistent with
our theorizing, mental alertness was higher in the bright (vs. dim) ambient light condition (5.28
vs. 3.99; F(1, 158) = 16.42, p < .01).
Since females (vs. males) tend to choose healthier options (Wardle et al. 2004), we ran
the analysis with gender as a covariate to rule out the alternative explanation of the effects being
driven by gender distribution differences across the conditions. Including gender as a covariate
made the effects stronger (χ2 = 5.66, p < .02). We also examined the effects of gender, as an
independent variable, on food choices. While gender had directional main effects on food
choices, with females (vs. males) directionally choosing healthier options to a greater extent, the
effects were not significant (49.35% vs. 37.84%; χ2 = 2.03, p = .15). There was no interaction
effect between gender and ambient light on food choice (p > .45).
Main tests for calories. We also analyzed the data with total calories ordered, as a
continuous variable. The results of an ANOVA reveal a significant effect of ambient light on
total calories purchased (F(1, 158) = 16.09, p < .001), with calorie purchases being higher for
dim (vs. bright) lighting (1336.49 vs. 962.56). Overall, customers in dim ambient light settings
purchased 38.85% more calories than those in bright ambient light settings.
Mediation tests. Mediation analysis using Preacher and Hayes’s (2008) PROCESS macro
Model 4 with 5,000 bootstrapped samples (Hayes 2012) shows indirect effects of ambient light
luminance on food choices, with the effects being mediated by mental alertness (B = -.226, SE =
.136, 95% CI: -.571, -.029), as evidenced by the CI (confidence interval) excluding zero. Similar
indirect mediation effects emerged for calories ordered (B = -52.106, SE = 32.229, 95% CI: -
136.555, - 1.619).
<Insert Figure 1 about here>
The results of Study 1a demonstrate that consistent with our hypothesis, restaurant
patrons tend to order healthier items and fewer calories when dining in a brightly (vs. dimly) lit
restaurant. Process evidence shows that mental alertness mediates the effects of ambient light on
food choices and calories purchased. Specifically, these results support the theoretical premise of
mental alertness being higher in bright lighting, which in turn leads to higher degree of ordering
of healthy options, and lower level of calories purchased, in bright (vs. dim) ambient lighting. It
should be noted though that since alertness was measured after customers placed their orders,
this might be a correlational effect instead of a causal effect. Since Study 1a was conducted
across four different locations, there might have been potential differences across these locations,
such as in clientele profiles that could have had confounding effects. Hence, next, Study 1b
replicates the key findings of Study 1a in a controlled lab setting.
Study 1b was a single factor between-subjects design experiment with two manipulated
conditions (ambient light luminance: bright vs. dim). One hundred thirty university students
(average age 23 years, 53.5% females) participated in the experiment in exchange for course
credit. It should be noted that across all our studies, the key dependent variable is food choice
and the average sample size for each condition is over 35 participants; this target sample size was
determined based on approach adopted in prior research with choice (a dichotomous variable) as
the DV (e.g., White et al. 2016). Also, across all our studies, the entire data was collected in one
round and all the analyses were conducted only after all the data were collected.
In Study 1b, all the participants responded to the question on food choice but two of the
participants did not respond to some of the other questions, including the questions on inhibition
and the alertness task; these two participants were retained in the sample. The bright and dim
lighting conditions had 50.0% and 57.38% females, respectively. The experiment was conducted
in a laboratory with technological options to have any level of ambient light luminance between
0 and 1200 lux, uniformly throughout the lab.
In order to ensure ecological validity, in the dim ambient light condition, the lab had a
luminance of 10 lux while in the bright ambient light condition, the luminance was set at 900
lux. Thus, the manipulations of dim and bright lighting conditions were more extreme in this
study than in Study 1a. This is because, unlike field studies, which have managerial constraints,
lab studies allow greater flexibility in the experimental manipulations. Importantly, based on
luminance measurements taken by the researchers at various restaurants in a major metropolitan
area in the US, a couple of very dim restaurants in the metropolitan area had luminance levels
around 10 lux while a couple of very brightly lit restaurants had luminance levels of around 900
lux. Hence, the chosen luminance levels of 10 lux and 900 lux for Study 1b have ecological
For the experiment, participants first arrived at a waiting area and were then brought into
the main lab by a research assistant. After participants entered the lab, they were seated at a
table. In the initial few minutes, participants were asked if they needed any pens/pencils and they
were also told to switch off their cell phones and also to be quiet during the entire duration of the
study; they were then handed a survey. After this, they were asked to choose between two food
options – 100-calorie Oreos and chocolate covered Oreos. These food items have been used in
prior studies to represent healthy and unhealthy options respectively (Wilcox et al. 2009).
Participants were told they could have only one of these food options and they were told to
record their preference on the survey. We also measured inhibition by asking participants to
indicate their level of agreement (1 = strongly disagree, 7 = strongly agree) to a statement on
behavioral inhibition (“right now, I feel inhibited”) (Duke and Bègue 2015).
Study 1a had self-reported measures of alertness, which provided mediating evidence for
the underlying process. In Study 1b, we attempted to examine the effects of ambient light on
objective measures of mental alertness. Specifically, we measured mental alertness level at the
beginning of the study by using a digit span task, employed in prior research (Irmak, Block, and
Fitzsimons 2005). That is, participants’ mental alertness levels were assessed by showing them a
series of numbers (between 1 and 99) displayed on a screen. Each number sequence was
automatically timed to be displayed for exactly half a second, following which, participants were
asked to reproduce the numbers on the surveys, in the exact order in which they were displayed
on the screen. Four such sets were displayed, with each set having a sequence of five numbers
initially, progressively going up to eight numbers by the fourth set. In essence, a total of 27
numbers were displayed across the four sets.
Results and Discussion
Main tests. Consistent with the findings observed in Study 1a, a higher proportion of
participants preferred the healthy option with bright (vs. dim) ambient light (68.12% vs. 49.18%;
χ2 = 4.74, p < .05). The results of Study 1b again support H1. We also ran the analysis with
gender as a covariate. The results of this analysis show that having gender as a covariate leads to
equivalent result patterns for main effects of ambient light on food choice (χ2 = 4.67, p < .05).
We also examined the direct effects of gender on food choice. There was a main effect of gender
on food choice, with females (vs. males) choosing healthier options to a greater extent (66.18%
vs. 49.15%; χ2 = 3.77, p < .06). There was no interaction effect between ambient light and gender
on food choice (p > .40).
The self-reported measure of behavioral inhibition was similar across the two ambient
lighting levels (5.60 vs. 5.46; F(1, 126) = .32, p = .57), which suggests that disinhibition was not
a dominant factor in influencing the effects of ambient light on food choices.
Assumption checks. We theorized that ambient light influences mental alertness, which in
turn would influence choices between healthy versus unhealthy options. The digit span task,
although unrelated to the food choice task, gave an objective measure of alertness level. The
number of correct responses from the digit span task was recorded. Results from the digit span
task show that participants were able to observe and reproduce the numbers (that were displayed
for half a second) with greater accuracy when they were in bright (vs. dim) ambient light (Mbright-
light = 10.94 vs. Mdim-light = 9.98; F(1, 126) = 4.88, p < .05).
Study 1b replicated the key findings of Study 1a in a controlled lab setting, and also
provided additional evidence for our theorizing. Specifically, while Study 1a had self-reported
measure of alertness, Study 1b tested our theoretical claims with an objective measure of
alertness. Next, Study 1c examines if the effects of Study 1b hold when participants are made to
indicate their choices aloud.
Study 1c was similar to Study 1b in terms of procedure, with the only difference being
that while in Study 1b participants anonymously recorded their food preference on a paper
survey, in Study 1c participants also had to indicate their choices aloud. The objective behind
this approach was to examine if eliminating the perceived anonymity of choices might change
the pattern of results observed in Study 1b. In a group setting, indicating preferences aloud
(instead of just recording preferences on a survey) draws attention to the self, which in turn
reduces perceived anonymity. Moreover, reduction of perceived anonymity enhances inhibition
(Fern 1982).
To enhance the robustness of the findings across studies, a different set of food options,
chocolate versus granola bar (Laran 2010), was used in this study. Similar to the approach used
in Study 1b, participants first arrived at a waiting area and were then randomly assigned to a
session and the ambient lighting for each session was also randomly determined. In the lab, all
the participants were seated at a large, rectangular table.
After the initial few minutes (similar to the procedure used in Study 1b), participants
were told that there were two food items, a chocolate bar and a granola bar, and that that they
could choose only one of these for eating. A sample of each food item was displayed at the
center of the table. Participants were told to indicate their response on the survey and then raise
their hand and indicate their preference out loud to the researcher. A research assistant then
brought the participant her/his preferred item. Seventy-one university students (average age 22.4
years, 47.7% females) participated in the experiment in exchange for course credit. In the bright
and dim light conditions, there were 41.2% and 58.4% females, respectively.
Results and Discussion
Consistent with the findings observed in Studies 1a-1b and as predicted by H1, there was
greater preference for the healthy option with bright (vs. dim) ambient light (54.29% vs. 30.56%;
χ2 = 4.10, p < .05). Including gender as a covariate enhances the effect (χ2 = 6.26, p < .02). There
were no main effects of gender on food choice (χ2 = .32, p = .57) and neither were there
interaction effects between gender and lighting on food choice (p > .70).
Study 1c had two objectives. First, it replicated the effects of Studies 1a and 1b with a
different set of product options. Second, the results of Study 1c highlight how mental alertness,
as opposed to (dis)inhibition, is likely to have been a more dominant force in determining the
outcomes of Studies 1a-1b. That is, if inhibition had a more dominant role in determining the
food choice outcome, then the pattern of results should have been different when participants had
to indicate their choice aloud. However, indicating choice aloud led to the same pattern of results
as observed in Study 1b when participants recorded their responses anonymously on a survey.
Although this does not technically rule out the role of inhibition as an underlying process, it does
highlight that factors that enhance inhibition levels do not necessarily change the pattern of
results related to effects of ambient light on food choices. Moreover, Study 1b provides a similar
conclusion with self-reported measures of inhibition. Next, Studies 2a-2b provide additional
evidence for the process driving the effects of ambient light on food choices by examining the
moderating effect of manipulated mental alertness.
The results of Studies 1a-1c support a mental alertness based theory of explanation for
the effects of ambient light on product choices; Studies 2a and 2b provide more direct evidence
for this proposed theorization. Specifically, we theorized that mental alertness would be lower
when ambient light is dim (vs. bright), which in turn will lead to unhealthier choices under dim
(vs. bright) ambient light. If our conceptualization holds, then this differential effect of dim
versus bright ambient light on food choices would get attenuated when consumers’ mental
alertness level is enhanced. That is, we propose that the effects predicted by H1 and
demonstrated in Studies 1a-1c, would hold under regular mental alertness levels but will get
attenuated when mental alertness is enhanced.
Formally stated:
H2: Under regular mental alertness levels, when given a choice between healthy and
unhealthy options, consumers will have greater preference for healthy options when
ambient light luminance is bright (vs. dim).
Under enhanced mental alertness, these effects will get attenuated, whereby the
preference pattern will be the same across bright and dim ambient lights.
H2 was tested in Study 2a with the help of a 2 (ambient light luminance: bright vs. dim)
X 2 (mental alertness level: regular vs. high) between-subjects experiment. The procedure was
similar to Studies 1b-1c whereby participants first arrived at a waiting area and were then
brought into a lab and seated at a table. The ambient light luminance in the lab was manipulated
in the same manner as in Studies 1b-1c (10 lux for dim ambient light and 900 lux for bright
ambient light). Mental alertness level was manipulated through placebo effects, associated with
sampling a beverage, consistent with the approach adopted in prior studies (Biswas, Grewal, and
Roggeveen 2010; Shiv, Carmon, and Ariely 2005). Participants were first given a beverage,
which was identical across all conditions. In the “high alertness” conditions, participants were
told that the beverage contained a high level of caffeine. No such statement was provided in the
“regular alertness” conditions. A pretest (N = 34; mean age 24.59; 50% females) was conducted
to see if providing such a statement did indeed enhance mental alertness. The results of the
pretest showed that participants reported that they felt more alert (measured on a 1-7 scale, where
1 = low alertness and 7 = high alertness) after sampling the beverage when they were told it
contained caffeine versus when they were not (Mcaffeine-present = 5.67 vs. Mcaffeine-absent = 4.26; F(1,
32) = 9.97, p < .01).
In the main study, participants were asked to drink the beverage, and to avoid hypothesis
guessing, they were asked a few questions about the taste of the beverage. After this, participants
completed the focal task, which involved choosing between a healthy (baked potato) and an
unhealthy food item (fries) (Wilcox et al. 2009). They were also asked how mentally alert they
felt at that point (with 1 = not at all alert, 7 = extremely alert).
Three hundred fifty three university students (average age 23 years; 49.6% females)
participated in this experiment in exchange for course credit. In the “caffeinated” (i.e., high
alertness level) condition, there was an equivalent proportion of females in the bright and dim
light conditions (40.30% and 45.78%) and there was a similar pattern for the “non-caffeinated”
(i.e., regular alertness level) condition as well (55.56% and 53.47%).
Main tests. The results of a 2 (ambient light luminance: bright vs. dim) X 2 (mental
alertness level: regular vs. high) logistic regression revealed a significant interaction effect on
food choice (Wald χ2 = 6.34, p < .05). Including gender as a covariate leads to a similar level of
interaction effect (Wald χ2 = 6.56, p < .05). There was no main effect of gender on food choice
(χ2 = .62, p = .43) and there was no interaction effect between gender and ambient light on food
choice (p > .60).
Follow-up tests showed that consistent with H2, when no caffeine information was given,
choice for the healthy item was higher with bright (vs. dim) ambient light (49.0% vs. 32.67%; χ2
= 5.55, p < .05) but the effects got attenuated when participants were given a “caffeinated”
beverage (46.27% vs. 54.12%; χ2 = .92, p = .34). It is interesting to note that consistent with our
theorizing, with bright ambient light, the choice pattern for healthy versus unhealthy items
remained the same irrespective of whether the alertness level was regular versus high (49.0% vs.
46.27%; χ2 = .12, p = .73); with dim ambient light, the preference for healthy food was enhanced
when mental alertness was high (vs. regular) (54.12% vs. 32.67%; χ2 = 8.69, p < .01). These
findings are consistent with our conceptualization and predictions. That is, in bright ambient
lighting, mental alertness level was high by default and hence the “caffeinated” beverage did not
have any effect. In contrast, in dim ambient lighting, mental alertness level was lower and the
“caffeinated” beverage helped in enhancing the alertness level and thus the preference of the
healthy item.
Test of moderated mediation. Moderated mediation analysis using Preacher and Hayes’s
(2008) PROCESS macro Model 8 with 5,000 bootstrapped samples (Hayes 2013) shows
moderated mediation of alertness for the interaction effect between ambient light and “caffeine”
condition on food choice (B = .193, SE = .109, 95% CI: .030, .464). Consistent with our
expectations, for the “caffeine absent” condition, the indirect effects of ambient light on food
choice was significantly mediated by alertness (B = .144, SE = .076, 95% CI: .028, .329); there
was no such significant mediation effect for the “caffeine present” condition (B = -.049, SE =
.068, 95% CI: -.206, .066). These results again highlight the role of alertness as the underlying
Ruling out alternative explanations. As mentioned earlier, alternative explanations for the
observed effects can be provided by theories related to inhibition and self-presentation focus,
which predict the same behavioral outcomes for dim versus bright ambient lighting as mental
alertness theories. While Study 1b examined the effects on self-reported measures of inhibition,
Study 2a examined the effects on self-reported measures of self-presentation focus. In order to
examine the role of self-presentation, participants were asked to indicate their level of agreement
with three statements (adapted from Fenigstein, Scheier, and Buss 1975) such as “Right now, I
am very concerned about the way I am presenting myself,” “Right now, I am worried about
making a good impression,” and “Right now, I am aware of what other people think of me”
(1=strongly disagree, 7=strongly agree). One participant did not respond to the self-presentation
questions. A 2 (ambient light luminance) X 2 (mental alertness level) ANOVA showed a non-
significant interaction effect on self-presentation focus (F(1, 348) = 1.55, p = .21). Follow-up
tests showed that self-presentation level was similar across bright (vs. dim) ambient lighting
(Mbright = 3.33 vs. Mdim = 3.14; F(1, 350) = 1.13, p = .29). These results provide further support
for the contention that mental alertness, as opposed to self-presentation focus, is the dominant
underlying process for the effects observed in Studies 1a-1c.
We also examined if having an alerting “caffeinated” beverage might trigger thoughts of
healthier lifestyle. Accordingly, towards the end of the survey, we measured health orientation
by asking participants to indicate the extent to which they disagreed/agreed (1 = strongly
disagree and 7 = strongly agree) with two items: “Calorie levels influence what I eat” and
“Eating healthy is important to me” (Chandon and Wansink 2007). Four participants did not
respond to the health orientation questions. The mean score on these two items were similar
across the “caffeinated” and “non- caffeinated” conditions, both in the bright light (4.75 vs. 4.44;
F(1, 345) = 1.79, p = .18) and dim light (4.82 vs. 4.63; F(1, 345) = .77, p = .38) conditions.
Study 2a provides additional evidence regarding the role of mental alertness in
influencing the effects of ambient light luminance on choices between healthy and unhealthy
options. Under regular mental alertness, similar to the effects observed in Studies 1a-1c, there is
greater preference for the unhealthy option when ambient light was dim (vs. bright). However,
when mental alertness was enhanced through a placebo effect, the effects got attenuated. While
enhancing mental alertness did not have any effect in the case of bright ambient light, it did
influence choices in the case of dim ambient light. Specifically, with dim ambient light, there
was greater preference for the healthy option when mental alertness was enhanced. Tests of
moderated mediation provide further empirical support for our theorizing.
While Study 1b examined the role of inhibition level, Study 2a examined the potential
effects of self-presentation focus and also the moderated mediation effects of alertness. The
results of both these studies suggest that although inhibition and self-presentation make similar
prediction as H1, mental alertness seems to be the dominant underlying process. Next, Study 2b
replicates the findings of Study 2a using a direct manipulation of inducing alertness.
Study 2b was a 2 (ambient light luminance: bright vs. dim) X 2 (induced mental alertness
level: regular vs. enhanced) between-subjects experiment. While in Study 2a, mental alertness
level was manipulated through a placebo effect, Study 2b manipulated mental alertness in a more
direct manner. Specifically, in the “enhanced mental alertness” conditions, mental alertness was
manipulated by asking participants, at the beginning of the study, to be mentally alert while
undertaking the tasks in the study. No such instructions were given in the “regular mental
alertness” conditions.
Continuing with the objective of having different food choice scenarios across the
studies, mainly to ensure robustness, in Study 2b, participants had the option of choosing
between raisins and M&Ms (Salerno, Laran, and Janiszewski 2014). Mental alertness was
measured in a similar manner as in Study 2a. One hundred forty nine university students
(average age 22 years; 53% females) participated in this experiment for course credit. In the
bright and dim lighting conditions, 51.3% and 54.8% were female, respectively. The procedure,
with the exception of the mental alertness manipulation and food choices, was similar to Study
Food choice. The results of a 2 (ambient light luminance) X 2 (mental alertness level)
logistic regression revealed a significant interaction effect on product choice (Wald χ2 = 4.73, p <
.05). Including gender as a covariate keeps the overall effect and chi-square value unchanged (at
χ2 = 4.73). There was no main effect of gender on food choice (χ2 = 1.40, p = .24) and there was
no interaction effect between gender and ambient light on food choice (p > .50).
Follow-up tests showed that choice of the healthy item was higher with bright (vs. dim)
ambient light when there was no “alertness” inducement (27.45% vs. 7.50%; χ2 = 5.87, p < .05)
but the effects got attenuated when mental alertness was enhanced (28.0% vs. 30.30%; χ2 = .04,
p = .85). It is interesting to note that consistent with our theorizing, with bright ambient light, the
choice pattern for healthy versus unhealthy items remained the same irrespective of whether the
induced alertness level was regular versus high (27.45% vs. 28.0%; χ2 = .003, p = .96); with dim
ambient light, the preference for healthy food was enhanced when mental alertness was induced
(vs. regular) (30.30% vs. 7.50%; χ2 = 6.42, p < .05). These findings are consistent with our
conceptualization. That is, for bright ambient lighting, mental alertness level was high by default
and hence enhancing alertness did not have any effect. In contrast, for dim ambient lighting,
enhancing mental alertness increased preference of the healthy item.
Alertness measure. The results of a 2 (ambient light luminance) X 2 (mental alertness
level) ANOVA revealed a significant interaction effect on self-reported alertness level (F(1, 145)
= 4.79, p < .05). Follow-up tests show that inducing (vs. not inducing) alertness led to higher
perceived alertness level (5.52 vs. 4.23; F(1, 145) = 30.86, p < .01). Also, consistent with our
theorization, self-reported mental alertness level was higher for bright (vs. dim) ambient light in
the absence of induced alertness (4.67 vs. 3.68; F (1, 145) = 10.85, p < .01) with the effects
getting attenuated when alertness was induced (5.48 vs. 5.55; F(1, 145) = .03, p = .86).
The results of Study 2b replicate the findings of Study 2a using a different type of mental
alertness manipulation and again highlight the role of mental alertness as the dominant
underlying factor in influencing the effects of dim versus bright ambient lighting on food
The results of five experiments (one conducted as a field study at multiple locations of a
major restaurant chain and four in labs) show that consumers have greater preference for
unhealthy options when the luminance of ambient light is dim (vs. bright). Process evidence
suggests that dim (vs. bright) ambient light reduces the level of mental alertness, which in turn
leads to greater preference for unhealthy options. These results contribute to the growing
literature on choices between healthy and unhealthy options and also to the literature on how
ambient factors influence food choices. While prior studies have examined different factors that
can influence choices between healthy and unhealthy product options (Chandon and Wansink
2007; Dhar and Wertenbroch 2012; Romero and Biswas 2016; Shiv and Fedorikhin 1999), the
present research is the first to examine how ambient light influences such choices.
It might be noted though that several factors influence choices between healthy/unhealthy
options and ambient light luminance is only one such factor that can nudge consumers towards
more healthful choices. It also needs to be emphasized that we are claiming relative effects of
ambient light instead of absolute effects. In other words, changing the ambient light can lead to
relatively higher/lower level of unhealthy choices; however, depending on context and food
options, the overall choice pattern might still be unhealthy. In fact, the results of our Study 2b
demonstrate such a pattern, whereby bright lighting leads to only 27.45% healthy choices;
however, that is still significantly better than dim lighting, which had 7.50% healthy choices.
Even in our field experiment at the restaurants (Study 1a), bright ambient light leads to 52.44%
healthy choices, but it is significantly worse at 34.62% with dim ambient lighting.
The findings of our research contribute to the literature on choice construction in general.
Prior studies examining choice and preference construction have often focused on the role of
product attributes (Amir and Levav 2008) and there have been only a limited number of studies
examining the role of ambient factors in influencing choice construction. The present research
takes an important step in highlighting the role of ambient factors in influencing product choices.
The findings of this research also contribute to the literature on ambient light. While prior
research attests to the importance of ambient light in influencing physiological (Lowden,
Akerstedt, and Wibom 2004), psychological (Schaller, Park, and Mueller 2003), and behavioral
responses (Zhong, Bohns, and Gino 2010), this is the first study to link ambient light luminance
with consumer choices for healthy and unhealthy options. In addition, the findings of this
research contribute to the growing literature on the role of visual cues and availability of light or
the softening of light on food consumption (Scheibehenne, Todd, and Wansink 2010; Wansink
2004; Wansink et al. 2012; Wansink and van Ittersum 2012). These studies found for example,
that softening the light in conjunction with the music led to stronger perceptions of a finer dining
experience and lower consumption volume (Wansink and van Ittersum 2012), and that the
absence of light led to a greater amount of food consumption due to the non-availability of visual
cues (Scheibehenne, Todd, and Wansink 2010; Wansink et al. 2012). We extend this literature
stream by demonstrating how dimming of ambient light enhances choice likelihood for
unhealthy options.
The present research is also possibly the first study to examine the interaction effects
between ambient light and placebo effects (or even induced factors) related to enhancing mental
alertness. As the results of Studies 2a-2b show, factors that can enhance consumer mental
alertness can diminish the effects of ambient light on product choices. We also conducted an
additional experiment (reported in details in the Web Appendix) where we examined the
moderating effects of inducing sleepiness through a priming task and examined choice from a
menu of food options. The results of this study show that inducing sleepiness (which is
conceptually similar to reducing mental alertness) attenuates the effects observed in Studies 1a-
1c, whereby higher level of sleepiness enhances choice likelihood of unhealthy options. Other
factors that can potentially influence mental alertness can be certain types of alerting and sleep-
inducing ambient scents (Spangenberg, Crowley, and Henderson 1996) and music with certain
tempos and volumes (Mattila and Wirtz 2001). Clearly, additional work is needed to examine
how these other ambient factors (scent and music) might interact with ambient light and
influence product choices.
This research also has important potential implications for sensory marketing and retail
atmospherics. While prior studies in the domains of sensory marketing and retail atmospherics
have examined different types of sensory cues (Biswas et al. 2014; Knoferle et al. 2012; Krishna
2012), the present research is the first to examine the effects of ambient light on product choice.
Moreover, while there has been extant work examining the effects of other sensory cues, such as
ambient scent and music, hardly any work has examined the effects of ambient light on product
choices. In fact, the findings of our research have implications for cross-modal influences,
whereby ambient light, which is processed through the visual system influences food choices,
which relate to the gustatory system.
Limitations and Future Research
As discussed earlier, theories related to inhibition and self-presentation focus make
similar predictions as those related to mental alertness. The findings of our research provide
process evidence in favor of the dominant role of mental alertness. The results of our studies did
not provide evidence for the role of inhibition or self-presentation focus as alternative underlying
processes. However, we just had self-reported measures of self-presentation focus and inhibition,
and in the case of inhibition, Study 1c just had a response elicitation method that enhances
inhibition and yet the pattern of results from this study were similar to that of the other studies.
In other words, we did not empirically rule out the roles of inhibition and self-presentation focus
as underlying processes; we just found direct empirical evidence for the role of mental alertness.
In fact, it is possible that although mental alertness is the dominant underlying process, inhibition
and self-presentation focus might play supporting roles. This is especially likely since these
variables are interlinked (Baumeister et al.1994; Carver and Scheier 1978; Heatherton, Striepe,
and Wittenberg 1998; Heinz et al. 2011). Future research should examine the link between these
variables and their respective roles, in the context of ambient light luminance, in greater depth.
Along these lines, bright ambient light can potentially heighten social desirability concerns,
which in turn might influence food ordering. Additional research is needed to examine this in
greater depth.
While we did provide empirical evidence regarding the underlying process related to
mental alertness, one limitation of our studies is that alertness was measured after participants
made their food choices. This was done to avoid hypothesis guessing or suspicion from
responding to alertness questions before making the food choice. Accordingly, the mediation
effects demonstrated in our studies might be more correlational, than causal, in nature.
Our field study was conducted at a casual dining restaurant with food options that varied
significantly in terms of healthfulness levels and our lab studies were conducted with young
adults, who have varied levels of health goals. The findings of our studies may not hold in the
context of fast food restaurants, where most of the consumers tend to visit with the mindset of
ordering something unhealthy; along similar lines, not surprisingly, frequency of fast-food
restaurant visits is associated with higher BMI levels (Rosenheck 2008). To further examine this
issue, we conducted an online (MTurk) study with thirty participants (57% females; average age
= 33 years), asking them whether they go to a fast-food place with the goal of ordering
something healthy or unhealthy. Overall, 90% (10%) of the participants indicated they go in with
a goal of ordering something unhealthy (healthy) (χ2 = 19.20, p < .01) when they visit fast-food
places. With such a strong tendency for ordering something unhealthy while visiting a fast-food
restaurant, ambient lighting is unlikely to make a significant difference.
Research in the domain of threat management systems suggests that, humans
instinctively become more vigilant in dimly lit environments due to enhanced perception of
vulnerability to threat/danger in darkness (Neuberg, Kenrick, and Schaller 2011). It can be
speculated that vigilance might be more at play in novel and/or unfamiliar environments. For
example, dining as a tourist at an unfamiliar restaurant in a new place can be a good catalyst for
enhancing vigilance level when the ambient light is dimmed. Can effects of enhanced vigilance
be consistent with those of enhanced mental alertness? Future research needs to examine if the
main effects of ambient lighting observed in our studies might get changed for studies conducted
in unfamiliar or novel settings. Similarly, self-presentation focus might have been a more
influential factor in dining contexts where impression management is key. So for dining
experiences in the contexts of dating or job interviews, ambient lighting might influence self-
presentation focus to a greater extent than that observed in our research (e.g., in Study 2a).
In our studies, we focused on aggregate choices without factoring in individual
personality or behavioral traits, which can be potentially relevant moderators. For instance, an
individual’s healthiness perspective can moderate the effects observed in our studies. Along
similar lines, the time of day might influence consumers’ alertness levels and also the luminance
levels outside the stores and restaurants. Moreover, time of day can be associated with different
types of meals, which in turn can influence consumption outcomes (Khare and Inman 2006).
Hence, time of day can potentially moderate the findings observed in our studies. Along similar
lines, incidental affect can potentially influence alertness levels and also food choices (Garg,
Wansink, and Inman 2007). Future research should examine the role of such potential
moderators that can be managerially relevant.
We examined choices involving healthy and unhealthy food items only. Future research
should examine the effects of ambient light luminance on non-food product choices in other
domains. For instance, would indulgences in terms of high priced purchases be greater when a
store has dim (vs. bright) ambient light? How about purchases of utilitarian versus hedonic
products across different ambient light luminance levels? Additional studies are needed to
answer these research questions.
We focused on the effects of ambient light. However, retail atmospherics entail several
other elements (such as music, scent, wall color, and overall décor). Hence, it might be
interesting to examine the interaction effects between ambient light and these other elements of
retail atmospherics. Along similar lines, while we study effects of ambient light luminance, there
are other elements of ambient light, such as color of the light, that are potentially interesting. For
instance, Lehrl et al. (2007) showed that keeping luminance levels constant, blue (vs. yellow)
light leads to greater alertness and faster information processing. Can this in turn influence
product choices? Given the dearth of research in the marketing literature examining the effects of
ambient light on product choices, this is relatively uncharted territory with potential for
significant additional work.
Managerial and Consumer Implications
Since managers of retail outlets and restaurants can usually control the retail atmospheric
elements (such as the luminance level of the ambient light) with relative ease, it is important to
understand how changing such elements influences choice. In essence, since ambient light
influences consumer choices, marketers can potentially manipulate the ambient light luminance
level to drive preferences towards signature items or high-margin items.
The findings of our research can be of interest to regulators as well. Regulators have
often expressed concerns about widespread obesity and have often tried to encourage healthy
eating through restrictive mechanisms, such as for example, in the recent case related to
restricted sales of sugary beverages in New York City (Strauss and Castagna 2013). However,
restrictive policies are often met with consumer reactance, as was the outcome in the New York
City beverage case (Saul 2013). Instead of having restrictive policies, which often lead to
consumer reactance, a more effective strategy to encourage healthy eating would be through the
use of subtle factors, such as ambient light. Since ambient light luminance influences choices
between healthy and unhealthy options, employing certain ambient light luminance levels can be
an effective strategy to influence choices for healthy versus unhealthy food items. In addition,
ambient light luminance being a subtle environmental factor and not being restrictive in nature,
is less likely to be met with consumer reactance.
While we demonstrate the effects of ambient light on food choices across a robust set of
experiments and thus provide existence proof of ambient lighting effects, care must be taken
when generalizing across all types of restaurant or store settings. As previously mentioned, there
can be several settings where the effects of our studies may not hold (e.g., Dairy Queen has very
bright ambient lighting while some fine vegan restaurants have dim lighting). This is especially
likely to be the case since several other factors, apart from ambient light, such as brand image,
type of restaurant, and availability of options, among others, influence food choices. Moreover,
alertness levels can moderate the effects. That is, very high and very low levels of alertness
attenuate the effects, as demonstrated by Studies 2a and 2b and the study reported in the Web
In terms of consumer wellbeing, dining in brightly lit ambient settings might be a good
option if the goal is to enhance choice likelihood for healthy options. Since dim (vs. bright)
ambient light reduces mental alertness level, dining in dimly lit environments might lead to
greater likelihood of yielding to the temptation of going for the sumptuous, but unhealthy,
chocolate dessert. Hopefully, our study has shed some light on the effect of ambient light on
product choices and will trigger further research in this topic domain.
Amir, On and Jonathan Levav (2008), “Choice Construction versus Preference Construction:
The Instability of Preferences Learned in Context,” Journal of Marketing Research, 45
(2), 145–58.
Areni, Charles S. and David Kim (1994), “The Influence of In-Store Lighting on Consumers’
Examination of Merchandise in a Wine Store,International Journal of Research in
Marketing, 11 (March), 117– 25.
Badia, P., B. Myers, M. Boecker, J. Culpepper, and J. R. Harsh (1991), “Bright Light Effects on
Body Temperature, Alertness, EEG, and Behavior,” Physiology & Behavior, 50 (3), 583–
Baker, Julie, A. Parasuraman, Dhruv Grewal, and Glenn Voss (2002), “The Influence of
Multiple Store Environment Cues on Perceived Merchandise Value and Store Patronage
Intentions,” Journal of Marketing, 66 (April), 12041.
Baumeister, Roy F. (2002), “Yielding to Temptation: Self-Control Failure, Impulsive
Purchasing and Consumer Behavior,” Journal of Consumer Research, 28 (4), 670–76.
———, Todd F. Heatherton, and Dianne M. Tice (1994), Losing Control: How and
Why People Fail at Self-Regulation. New York, Academic Press.
Biswas, Dipayan, Dhruv Grewal, and Anne Roggeveen (2010), “How the Order of Sampled
Experiential Products Affects Choice,” Journal of Marketing Research, 47 (3), 508–19.
———, Lauren Labrecque, Donald Lehmann, and Ereni Markos (2014), “Making Choices
While Smelling, Tasting, and Listening: The Role of Sensory (Dis)similarity When
Sequentially Sampling Products,Journal of Marketing, 78 (1), 112–26.
Bosworth Instruments (2013), “Typical Light Levels” (accessed March 12, 2013),
Broniarczyk, Susan M. and Wayne D. Hoyer (2006), “Retail Assortment: More Better,” in
Retailing in the 21st Century: Current and Future Trends, Manfred Krafft and Murali K.
Mantrala, eds. New York, Springer Publishing, 225–38.
Bruner, Gordon, C. (1990), “Music, Mood and Marketing,” Journal of Marketing, 54 (4), 94–
Cajochen, Christian (2007), “Alerting Effects of Light,” Sleep Medicine Reviews, 11, 453–64.
Carroll, Matthew (2012), “How Retailers Can Replicate the ‘Magic’ of the Apple Store… "
Online,” (accessed February 12, 2013), [available at:
Carver, Charles S. and Michael F. Scheier (1978), “Self-Focusing Effects of Dispositional Self-
Consciousness, Mirror Presence, and Audience Presence,” Journal of Personality and
Social Psychology, 36 (3), 324–32.
Chandon, Pierre and Brian Wansink (2007), “The Biasing Health Halos of Fast Food Restaurant
Health Claims: Lower Calorie Estimates and Higher Side-Dish Consumption Intentions,”
Journal of Consumer Research, 34 (October), 301–14.
——— and ——— (2012), “Does Food Marketing Need to Make Us Fat? A Review and
Solutions,” Nutrition Reviews, 70:10 (October), 571–93.
———, J. Wesley Hutchinson, Eric T. Bradlow, and Scott Young (2009), “Does In-Store
Marketing Work? Effects of the Number and Position of Shelf Facings on Brand
Attention and Evaluation at the Point of Purchase,” Journal of Marketing, 73 (6), 1–17.
Chernev, Alexander (2011), “The Dieter’s Paradox,” Journal of Consumer Psychology, 21 (2),
Crowley, Stephanie, J., Clara Lee, Christine Y. Tseng, Louis F. Fogg, and Charmane I. Eastman
(2003), “Combinations of Bright Light, Scheduled Dark, Sunglasses, and Melatonin to
Facilitate Circadian Entrainment to Night Shift Work,” Journal of Biological Rhythms,
18 (6), 513–23.
Daurat, Agnes, Acacia Aguirre, Jean Foret, Philippe Gonnet, Anne Keromes, and Odile Benoit
(1993), “Bright Light Affects Alertness and Performance Rhythms during a 24-h
Constant Routine,” Physiology & Behavior, 53 (5), 929–36.
Dhar, Ravi and Klaus Wertenbroch (2012), “Self-Signaling and the Costs and Benefits of
Temptation in Consumer Choice,” Journal of Marketing Research, 49 (1), 15–25.
Duke, Aaron A. and Laurent Bègue (2015), “The Drunk Utilitarian: Blood Alcohol
Concentration predicts Utilitarian Responses in Moral Dilemmas,” Cognition, 134, 121–
Fenigstein, Allan, Michael F. Scheier, and Arnold H. Buss (1975), “Public and Private Self-
Consciousness: Assessment and Theory,” Journal of Consulting and Clinical
Psychology, 43 (August), 522–27.
Fern, Edward F. (1982), “Why do Focus Groups Work: A Review and Integration of Small
Group Process Theories,” in NA – Advances in Consumer Research, Volume 9, Eds.
Andrew Mitchell, Ann Arbor, MI: Association for Consumer Research, 444–51.
Gardner, Meryl P., Brian Wansink, Junyong Kim, and Se-Bum Park (2014), “Better Moods for
Better Eating? How Mood Influences Food Choice, Journal of Consumer Psychology, 24,
Garg, Nitika, Brian Wansink, and J. Jeffrey Inman (2007), “The Influence of Incidental Affect
on Consumers’ Food Intake,” Journal of Marketing, 71 (January), 194–206.
Hayes, Andrew F. (2012), “PROCESS: A Versatile Computational Tool for Observed Variable
Mediation, Moderation, and Conditional Process Modeling,” Unpublished White Paper,
Available at:
——— (2013), An Introduction to Mediation, Moderation, and Conditional Process
Analysis: A Regression-Based Approach, New York: Guilford.
Heatherton, Todd F., Meg Striepe and Lauren Wittenberg (1998), “Emotional Distress and
Disinhibited Eating: The Role of Self,” Personality and Social Psychology Bulletin, 24
(3), 301–13.
Heinz, Adrienne J., Anne Beck, Andreas Meyer-Lindenberg, Philipp Sterzer, and Andreas Heinz
(2011), “Cognitive and Neurobiological Mechanisms of Alcohol-related Aggression,”
Nature Reviews Neuroscience, 12 (7), 400–13.
Herman, Peter C. and Janet Polivy (1993), “Mental Control of Eating: Excitatory and Inhibitory
Food Thoughts,” Handbook of Mental Control, Daniel M. Wegner and James W.
Pennebaker eds. Englewood Cliffs, New Jersey: Prentice Hall, 491–505.
Hirsch, Jacob B., Adam D. Galinsky, and Chen-Bo Zhong (2011), “Drunk, Powerful, and in the
Dark: How General Processes of Disinhibition Produce Both Prosocial and Antisocial
Behavior,” Perspectives on Psychological Science, 6 (5), 415–27.
Irmak, Caglar, Lauren G. Block, and Gavan Fitzsimons (2005), “The Placebo Effect in
Marketing: Sometimes You Just have to Want it to Work,” Journal of Marketing
Research, 42 (November), 406–09.
Janssen, Loes, Bob M. Fennis, Ad Th.H. Pruyn, and Kathleen Vohs (2008), “The Path of Least
Resistance: Regulatory Resource Depletion and the Effectiveness of Social Influence
Techniques,” Journal of Business Research, 61 (10), 1041–45.
Kasof, Joseph (2002), “Indoor Lighting Preferences and Bulimic Behavior: An Individual
Differences Approach,” Personality and Individual Differences, 32 (3), 383–400.
Khan, Uzma, Ravi Dhar, and Klaus Wertenbroch (2005), “A Behavioral Decision Theory
Perspective on Hedonic and Utilitarian Choice,” in Inside Consumption: Frontiers of
Research on Consumer Motives, Goals and Desires, S. Ratneshwar and David Glen
Mick, eds. London: Routledge, 144–65.
Khare, Adwait and J. Jeffrey Inman (2006), “Habitual Behavior in American Eating Patterns:
The Role of Meal Occasions,” Journal of Consumer Research, 32 (March), 567–75.
Kivetz, Ran and Itamar Simonson (2002), “Self-Control for the Righteous: Toward a Theory of
Precommitment to Indulge,” Journal of Consumer Research, 29 (September), 199–217.
Knoferle, Klemens, Eric R. Spangenberg, Andreas Hermann and Jan R. Landwehr (2012), “It is
All in The Mix: The Interactive Effect of Music Tempo and Mode on In-Store Sales,”
Marketing Letters, 23 (1), 325–37.
Krishna, Aradhna (2012), “An Integrative Review of Sensory Marketing: Engaging the Senses to
Affect Perception, Judgment, and Behavior,” Journal of Consumer Psychology, 22 (3),
Laran, Juliano (2010), “Goal Management in Sequential Choices: Consumer Choices for Others
Are More Indulgent than Personal Choices,” Journal of Consumer Research, 37
(August), 304–14
Leary, Mark and Susan C. Atherton (1986), “Self-Efficacy, Social Anxiety, and Inhibition in
Interpersonal Encounters,” Journal of Social and Clinical Psychology, 4 (3), 256–67.
Lehrl, S., K. Gerstmeyer, J. H. Jacob, H. Frieling, A. W. Henkel, R. Meyrer, J. Wiltfang, J.
Kornhuber and S. Bleich (2007), “Blue Light Improves Cognitive Performance,” Journal
of Neural Transmission, 114, 1435–63.
Lim, Julian and David Dinges (2008), “Sleep Deprivation and Vigilant Attention,” Annals of the
New York Academy of Sciences, 1129, 305–22.
Lockley, Steven W., Erin E. Evans, Frank A.J.L. Scheer, George C. Brainard, Charles A.
Czeisler, Daniel Aeschbach (2006), “Short-Wavelength Sensitivity for the Direct Effects
of Light on Alertness, Vigilance, and the Waking Electroencephalogram in Humans,”
Sleep, 29 (2), 161–68.
Lowden, Arne, Torbjöjn Åkerstedt, and Roger Wibom (2004), “Suppression of Sleepiness and
Melatonin by Bright Light Exposure During Breaks in Night Work,” Journal of Sleep
Research, 13, 37–43.
Mattila, Anna S. and Jochen Wirtz (2001), “Congruency of Scent and Music as a Driver of In-
Store Evaluations and Behavior,” Journal of Retailing, 77 (2), 273–90.
Meyers-Levy, Joan and Rui Zhu (2007), “The Influence of Ceiling Height: The Effect of Priming
on the Type of Processing That People Use,” Journal of Consumer Research, 34 (2),
———, ———, and Lan Jiang (2010), “Context Effects from Bodily Sensations: Examining
Bodily Sensations Induced by Flooring and the Moderating Role of Product Viewing
Distance,” Journal of Consumer Research, 37 (1), 1–14.
" (2010), “Illumination for Health Care Facilities, Michigan Department of
Licensing & Regulatory Services,” (accessed January 23, 2015). [available at:]
Morrin, Maureen and S. Ratneshwar (2003), “Does It Make Sense to Use Scents to Enhance
Brand Memory?” Journal of Marketing Research, 40 (1), 10–25.
Neuberg, Steven L., Douglas T. Kenrick, and Mark Schaller (2011), “Human Threat
Management Systems: Self-Protection and Disease Avoidance,” Neuroscience and
Biobehavioral Reviews, 35, 1042–51.
Nielsen, Martin V., Svend Svendsen, Lotte B. Jensen (2011), “Quantifying the Potential of
Automated Dynamic Solar Shading in Office Buildings through Integrated Simulations of
Energy and Daylight,” Solar Energy, 85 (5), 757–68.
Oberfeld, Daniel, Heiko Hecht, Ulrich Allendorf, and Florian Wickelmaier (2009), “Ambient
Lighting Modifies the Flavor of Wine,” Journal of Sensory Studies, 24, 797–32.
Pope, Lizzy, Andrew S. Hanks, David R. Just, and Brian Wansink (2014), “New Year’s Res-
Illusions: Food Shopping in the New Year Competes with Healthy Intentions,” PLOS
ONE, 9(12): e110561.
Preacher, Kristopher J. and Andrew F. Hayes (2008), “Asymptotic and Resampling Strategies for
Assessing and Comparing Indirect Effects in Multiple Mediator Models,” Behavior
Research Methods, 40 (3), 879–91.
Romero, Marisabel and Dipayan Biswas (2016), “Healthy Left, Unhealthy Right: Can
Displaying Healthy Items to the Left (versus Right) of Unhealthy Items Nudge Healthier
Choices?” Journal of Consumer Research, June, forthcoming.
Rosenheck, Robert (2008), “Fast Food Consumption and Increased Calorie Intake: A Systematic
Review of a Trajectory Towards Weight Gain an Obesity Risk,” Obesity Reviews, 9,
Rüger, Melanie, Marijke C. M. Gordijn, Domien G. M. Beersma, Bonnie de Vries, Serge Daan
(2006), “Time-of-day-dependent Effects of Bright Light Exposure on Human
Psychophysiology: Comparison of Daytime and Nighttime Exposure,” American Journal of
Physiology - Regulatory, Integrative and Comparative Physiology, 290 (5), R1413
Sala, Laurenne (2010), “Dining in the Dark at Opaque: Eat Like Nobody’s Watching,” (accessed
January 30, 2015), [available at
Salerno, Anthony, Juliano Laran and Chris Janiszewski (2014), “Hedonic Eating Goals and
Emotion: When Sadness Decreases the Desire to Indulge,” Journal of Consumer
Research, 41 (1), 135–51.
Saul, Michael H. (2013), “Judge Cans Soda Ban,” Wall Street Journal, 03/11/2013,
Schaller Mark, Justin H. Park, and Annette Mueller (2003), “Fear of the Dark: Interactive Effects
of Beliefs about Danger and Ambient Darkness on Ethnic Stereotypes,” Personality and
Social Psychology Bulletin, 29 (5), 637–49.
Scheibehenne, Benjamin, Peter M. Todd, and Brian Wansink (2010), “Dining in the Dark: The
Importance of Visual Cues for Food Consumption and Satiety,” Appetite, 55 (3), 710–13.
Shiv, Baba and Alexander Fedorikhin (1999), “Heart and Mind in Conflict: The Interplay of
Affect and Cognition in Consumer Decision Making,” Journal of Consumer Research, 26
(3), 278–92.
———, Ziv Carmon and Dan Ariely (2005), “Placebo Effects of Marketing Actions: Consumers
May Get What They Pay For,” Journal of Marketing Research, 42 (November), 383–93.
Spangenberg, Eric R., Ayn E. Crowley, and Pamela W. Henderson (1996), “Improving the Store
Environment: Do Olfactory Cues Affect Evaluations and Behaviors?” Journal of
Marketing, 60 (2), 67–80.
Spence, Charles, Nancy M. Puccinelli, Dhruv Grewal, Anne L. Roggeveen (2014), “Store
Atmospherics: A Multisensory Perspective,” Psychology & Marketing, 31 (July), 472–
Steele, Claude M. and Robert A. Josephs (1990), “Alcohol Myopia: Its Prized and Dangerous
Effects,” American Psychologist, 45, 921–33.
Strauss, Gary and Rebecca Castagna (2013), “NYC Ban on Large Sugary Drinks Fizzles Again,”
USA Today, 07/30/2013, [
The Engineering Toolbox (2012), “Luminance - Recommended Light Levels,” (accessed August
31, 2012) [available at
Thimijan Richard W. and Royal D. Heins (1983), “Photometric, Radiometric and Quantum Light
Units of Measure: A Review of Procedures for Interconversion,” HortScience, 18 (6),
Thomas, Maria, Helen Sing, Gregory Belenky, Henry Holcomb, Helen Mayberg, Robert
Dannals, Henry Wagner, David Thorne, Kathryn Popp, Laura Rowland, Amy Welsh,
Sharon Balwinski, and Daniel Redmond (2000), “Neural Basis of Alertness and
Cognitive Performance Impairments during Sleepiness,” Journal of Sleep Research, 9
(4), 335–52.
Thorington, Luke (1985), “Spectral, Irradiance, and Temporal Aspects of Natural and Artificial
Light,” Annals of New York Academy of Sciences, 453, 28–54.
Verwey, Willem B. and David M. Zaidel (2000), “Predicting Drowsiness Accidents from
Personal Attributes, Eye Blinks and Ongoing Driving Behaviour,” Personality and
Individual Differences, 28, 123–42.
Virginie Gabel, Micheline Maire, Carolin F. Reichert, Sarah L. Chellappa, Christina Schmidt,
Vanja Homes, Christian Cajochen, Antoine U. Viola (2015), “Dawn Simulation Light
Impacts on Different Cognitive domains under Sleep Restriction,” Behavioural Brain
Research, 281 (March), 258-66.
Wansink, Brian (2004), “Environmental Factors that Increase the Food Intake and Consumption
Volume of Unknowing Consumers,” Annual Review of Nutrition, 24, 455–79.
——— (2006), Mindless Eating Why We Eat More Than We Think. New York: Bantam Dell.
———, David R. Just, and Collin R. Payne (2009), “Mindless Eating and Healthy Heuristics for
the Irrational,” American Economic Review: Papers & Proceedings, 165–69.
———, Mitsuru Shimizu, Armand V. Cardello, and Alan O. Wright (2012), “Dining in the
Dark: How Uncertainty Influences Food Acceptance in the Absence of Light,” Food
Quality and Preference, 24 (1), 209–12.
——— and Koert van Ittersum (2012), “Fast Food Restaurant Lighting and Music can Reduce
Calorie Intake and Increase Satisfaction,” Psychological Reports: Human Resources &
Marketing, 111 (1), 228–32.
Wardle, Jane, Anne M. Haase, Andrew Steptoe, Maream Nillapun, Kiriboon Jonwutiwes, and
France Bellisie (2004), “Gender Differences in Food Choice: The Contribution of Health
Beliefs and Dieting,” Annals of Behavioral Medicine, 27 (2), 107–16.
Weitz, Barton and Mary Beth Whitfield (2006), “Trends in U.S. Retailing,” in Retailing in the
21st Century: Current and Future Trends, Manfred Krafft and Murali K. Mantrala, eds.
New York: Springer Publishing, 59–77.
White, Katherine, Lily Lin, Darren Dahl, and Robin J. B. Ritchie (2016), “When do Consumers
Avoid Imperfections? Superficial Packaging Damage as a Contamination Cue,” Journal
of Marketing Research, February, 110–23.
Wilcox, Keith, Beth Vallen, Lauren Block, and Gavan J. Fitzsimons (2009), “Vicarious Goal
Fulfillment: When the Mere Presence of a Healthy Option Leads to an Ironically
Indulgent Decision,” Journal of Consumer Research, 36(3), 380–93.
Zhong, Chen-Bo, Vanessa L. Bohns, and Francesca Gino (2010), “Good Lamps Are the Best
Police,” Psychological Science, 21 (3), 311–14.
Figure 1
Study 1a: The Effects of Ambient Light Luminance on Ordering of Healthy (vs. Unhealthy)
Foods at a Restaurant Chain
... Above all of these, the attention of the consumers is influenced by multiple factors, e.g. food color (Jantathai et al., 2013), saliency (Milosavljevic et al., 2012), music (Szakál et al., 2023), lights (Biswas et al., 2016) or scents (Szakál et al., 2022). In the world of wines, this is particularly true for infrequent consumers (Pomarici et al., 2016). ...
Full-text available
In our study, using a combination of eye-tracking parameter analysis and the van Westendorp method, we investigate whether participants pay more attention to products that they perceive as more expensive or to those that they prefer in the ranking process. The experiment involved 50 participants, a questionnaire with ranking and pricing tasks, and an eye-tracking measurement. Three wine varieties (Irsai Olivér, Rosé and Merlot-Shiraz) and three different label alternatives were tested. When comparing the results of the ranking and the pricing tasks, the product that is considered more expensive is not always the one that is most appealing to the participants. If we compare the results from the analysis of the eye-tracking parameters and the pricing, we can say that in all cases the labels that received the most visual attention were those that were priced more expensively by the participants.
... Specifically, participants were asked to choose between two options. "Given a choice between a vegetable salad and French fries, which one would you choose?" adapted from prior research (Biswas et al., 2017). Pictures of vegetable salad and French fries were shown to participants. ...
Digital marketing tools (e.g., social media and touchscreens) allow consumers to freely interact with food cues and offer multiple ways for marketers to reach consumers. Across a series of six studies, we investigate how, why, and when digital exposure to unhealthy food (vs. nonfood) on social media or touchscreens affects the subse- quent consumption of unhealthy food. The results show that digital exposure to unhealthy food (vs. nonfood) induces a dieting goal (Study 1) and results in lower consumption volumes (Study 2). The reduced consumption is driven by the activation of a dieting goal (Studies 3a & 3b). We also find that the reduced effect does not extend to digital exposure to healthy food (Study 4). Marketers can highlight the different benefits (tasty vs. functional) of unhealthy food. We further demonstrate that the effect of food benefits (tasty vs. functional) on reduced consumption is more likely to occur among smartphone (vs. personal computer) users (Study 5). This research adds to the existing literature on digital marketing and food exposure and offers implications for consumers and marketers to reduce unhealthy consumption.
... Lighting was found to have an influence on impulsive purchase behavior through consumers' psychological mechanisms (Hashmi et al., 2020) and on consumers' desire to stay in the store, which can lead to a store patronage intention (Elmashhara and Soares, 2022). A previous study examined ambient lighting (dim vs. bright) and confirmed its influence on consumers' mental states (alertness and attention) and healthy food choices (Biswas et al., 2017). ...
Full-text available
Purpose The study aims to examine fast fashion consumers' negative in-store experiences focusing on the effect of the two store environment factors, product overload and store ambiance, on their confusion and consequent shopping avoidance behavior. Design/methodology/approach A research model of fast fashion consumers' confusion and store avoidance behavior is proposed using the Stimulus–Organism–Response framework. A pretest and the main online survey with 281 samples are analyzed, and the structural equation modeling (SEM) is conducted to test the proposed model. Findings The SEM results support the proposed paths statistically. Consumers' confusion, measured with the two dimensions, inefficiency and helplessness, is significantly influenced by their perceived product overload and negative perception of store ambiance in the fast fashion shopping environment. Subsequently, fast fashion consumers' confusion results in less time spent in the store. Originality/value The study sheds light on utilitarian shopping value in the fast fashion shopping environment by focusing on the fast fashion consumers' confusion in association with overloaded information caused by too many products and store ambiance. Research limitations/implications The study implies that improving fast fashion stores' inherent issues with too many products and store ambiance might help consumers mitigate their confusion and prevent customer attrition. However, the study includes only two factors. Future studies may include other various fast fashion store factors. Additionally, one of the dimensions of confusion, irritation, did not emerge in this study. More work is needed to investigate fast fashion consumers' confusion, such as using a multigroup analysis by age.
... The wavelength of light has been shown to influence individuals' motivation to eat food, stimulating their appetite and willingness to consume the food presented to them [108,109]. The speed of eating, amount consumed, and preference for healthy or unhealthy food have also been associated with an ambient light environment [110,111]. A randomized trial of 112 participants (50 females and 62 males; 18-58 yrs) exposed to either white, yellow, or blue light (ranging from 9.0 to 13.5 lux) during breakfast demonstrated that blue light decreased the amount of food consumed in men but not in women, while other colors did not alter food intake [112]. ...
Full-text available
Light is an essential part of many life forms. The natural light–dark cycle has been the dominant stimulus for circadian rhythms throughout human evolution. Artificial light has restructured human activity and provided opportunities to extend the day without reliance on natural day–night cycles. The increase in light exposure at unwanted times or a reduced dynamic range of light between the daytime and nighttime has introduced negative consequences for human health. Light exposure is closely linked to sleep–wake regulation, activity and eating patterns, body temperature, and energy metabolism. Disruptions to these areas due to light are linked to metabolic abnormalities such as an increased risk of obesity and diabetes. Research has revealed that various properties of light influence metabolism. This review will highlight the complex role of light in human physiology, with a specific emphasis on metabolic regulation from the perspective of four main properties of light (intensity, duration, timing of exposure, and wavelength). We also discuss the potential influence of the key circadian hormone melatonin on sleep and metabolic physiology. We explore the relationship between light and metabolism through circadian physiology in various populations to understand the optimal use of light to mitigate short and long-term health consequences.
People largely perceive their environment visually. Visual impressions are often available before those of the other senses, for example, due to the fact that one may be outside the range of acoustic or olfactory signals. Therefore, how retail environments are visually designed is an important driver of retailers’ success by guiding consumer behavior and contributing to a generally pleasant atmosphere. Eye-catching designs can draw attention and unique design concepts can communicate a brand’s image. Popular examples are the Hans im Glück restaurant chain and the Apple Stores with their brand-specific visual concepts. Apart from a visual representation of the brand, retailers can further use in-store design elements like secondary placements at the point of sale (POS) and colored (price) tags to direct customers’ in-store shopping route and draw attention to specific offers.
This study aims to understand lighting in a hospitality atmosphere and the landscape of the village of Kandovan Hills and Laleh Kandovan Hotel. The study aims to see the latest design and concepts of the industry and how they can be applied on-site in Kandovan Hills and Laleh Hotel in Iran. This area is both historic and tourist; Therefore, it needs to keep some of the traditional aspects, it should be developed into more sustainable lighting for the environment as Kandovan both lacks the design and sustainable aspect based on Lighting design standards. The other part of the project is the Hotel site which has a very interesting design, yet it vastly lacks properly designed lighting. The purpose of the project is to improve the lighting in this area for both the environment and the aesthetics of the design. The Literature review will help with producing sustainable ways based on current technology to illuminate the landscape and the village hills, which are lacking proper illumination both in terms of aesthetics and sustainable lighting. This study's outcome could result in not only improving the lighting, sustainable aspect, and avoidance of light pollution as much as possible but also if applied correctly, it could be beneficial for tourism as proper lighting can enhance the experience of the tourist.
Full-text available
Companies in the service retailing industry are constantly looking for strategies to provide a customer experience that improves brand perception and increases customer loyalty. This study provides a deeper understanding of customer experience in two coffee stores in Vietnam by providing a multidisciplinary approach, including a quantitative and a neuromarketing approach. Two-hundred participants participated in the study, combining mystery shopping visits with the Brand Association Reaction Time Test (BARTT). Results from the mystery shopping visits confirm the holistic concept of customer experience. Store atmosphere, employee service, drink quality, price, and previous visits significantly impact customer experience. Empirical results also confirm the impact of customer experience on loyalty. Furthermore, the BARTT analysis shows that in-store customer experience can influence customers' short-term brand perceptions. The national brand is associated with friendly, expensive, globalized, and unique, whereas the local brand revealed significant associations with clean, smells good, welcoming, and unique. From the mystery shopping results and the BARTT, we can infer that customer experience needs multi-methodological capturing of its multifaceted aspects. Our findings are relevant to researchers and practitioners seeking to understand and bolster customer experiences, justifying a multidisciplinary approach and the application of new insightful tools.
Visual symbols, such as logos, landmark pictures, and mascots, play a significant role in attracting tourists and improving destination images. However, only a few studies have examined how the basic visual elements of these symbols influence potential tourists’ responses to a destination. This study aims to investigate the role of color lightness in destination visual symbols. Through three experiments, we repeatedly found that lightened visual symbols nudged consumers to evaluate their destination better. Furthermore, positive mental imagery mediated this effect. Nonetheless, the positive effect of lightened visual symbols on destination images was diminished when informational interventions were present. Our study provides new theoretical insights into destination images research by highlighting the positive effect of a fundamental visual attribute—symbol lightness. We suggest that tourism practitioners can make a “big difference” to the destination image by making “small changes,” such as adjusting visual symbol lightness.
Full-text available
Conversion constants and procedures necessary to interconvert photometric, radiometric, and quantum light units are described for sunlight and 9 electrical light sources.
Full-text available
Would laterally displaying a healthy item to the left versus right of an unhealthy item influence choice and consumption? The results of seven studies demonstrate that displaying healthy items to the left (vs. right) of unhealthy items enhances preference for the healthy options. In addition, consumption volume of a healthy item (vis-à-vis an unhealthy item) is higher when it is placed to the left (vs. right) of the unhealthy item. We propose that a “healthy-left, unhealthy-right” (vs. healthy-right, unhealthy-left) lateral display pattern is congruent with consumers’ mental organization of food items varying in healthfulness, which enhances ease of processing, which in turn enhances self-control, thereby leading to relatively higher likelihood of choosing healthy options. While prior studies have examined the role of several factors in influencing choices between healthy and unhealthy options, the present research is the first to demonstrate the effects of lateral display positions of healthy/unhealthy options on choice and healthful consumption. The findings of our research have important implications for designing retail food displays and restaurant menus as well as for conducting research studies involving healthy and unhealthy food displays.
Full-text available
Across six experiments, the authors demonstrate that superficial imperfections in the form of packaging damage can engender negative consumer reactions that shape subsequent attitudes and behaviors in ways that are not always objectively justified. Their findings show that these reactions function in a relatively automatic fashion, even emerging under conditions in which the packaging damage does not convey information about a health and safety threat from the product. The authors extend work on contagion to show that superficial packaging damage can act as a contamination cue, automatically activating thoughts of contamination and health and safety concerns. This tendency to avoid superficial packaging damage can be eliminated by counteracting these thoughts of contamination. This can be done with positive brand associations (i.e., by branding the product as organic) or by creating a physical buffer between the packaging damage and the product itself. The authors close with a discussion of implications for marketers, consumers, and public policy makers.
Full-text available
The results of five experiments reveal that when sampling a series of experiential products (e.g., beverages, music), consumers prefer the product sampled second in a series of two desirable products but relatively prefer the product sampled first in a series of two undesirable products. The underlying process for both outcomes is a recency effect, such that there is better recall for the most recently sampled experiential product. The recency effect observed for experiential products reverses to a primacy effect when sampling nonexperiential products (e.g., scissors). The authors also demonstrate that the placement of an undesirable experiential product in conjunction with two desirable experiential products can exaggerate preference for the later-sampled desirable product (when the undesirable product is sampled first) or result in preference for the earlier-sampled desirable product (when the undesirable product is sampled between the two desirable products). However, the preference for the earlier-sampled desirable product holds only if there is no time delay between the sampling of the products or between the sampling and the choice evaluations.
The popular press has recently reported that managers of retail and service outlets are diffusing scents into their stores to create more positive environments and develop a competitive advantage. These efforts are occurring despite there being no scholarly research supporting the use of scent in store environments. The authors present a review of theoretically relevant work from environmental psychology and olfaction research and a study examining the effects of ambient scent in a simulated retail environment. In the reported study, the authors find a difference between evaluations of and behaviors in a scented store environment and those in an unscented store environment. Their findings provide guidelines for managers of retail and service outlets concerning the benefits of scenting store environments.
Abstract Recent trends in marketing have demonstrated an increased focus on in-store expenditures with the hope of “grabbing consumers” at the point of purchase, but does this make sense? To help answer this question, the authors examine the interplay between in- ...
That music affects human beings in various ways has probably been presumed as long as people have played music. Many marketing practitioners already accept this notion, given that music is increasingly used as a stimulus in the retail environment as well as in radio and television advertising. Yet, fewer than 20 published empirical studies in marketing have music as their focus. The author reviews the small body of marketing literature, surveys relevant literature outside marketing, and provides research propositions to guide future studies.
This article uses the functionalist perspective of emotion to demonstrate that the influence of sadness on indulgent consumption depends on the presence of a hedonic eating goal. Sadness heightens a person’s sensitivity to the potentially harmful consequences of indulgent consumption, which decreases indulgence when a hedonic eating goal is salient. As sadness is often associated with a loss, this protective function is geared toward preventing future losses. The execution of this function is mitigated by feelings of safety, a counterforce to concerns about the harmful consequences of goal pursuit. Alternatively, when a hedonic eating goal is not salient, or a salient goal does not have harmful consequences, sadness results in emotion regulation (i.e., indulging as a means of feeling better). This conceptualization and findings show that the effects of emotions on indulgent consumption can be goal-dependent, and that emotions can aid consumers in the balancing of long-term goals and well-being.