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Building and Environment 42 (2007) 3233–3240
Effects of indoor color on mood and cognitive performance
K. Yildirim
a,
, A. Akalin-Baskaya
b
, M.L. Hidayetoglu
c
a
Department of Furniture & Decoration,Gazi University, Besevler, Ankara, Turkey
b
Department of Architecture, Gazi University, Maltepe, Ankara, Turkey
c
Department of Interior Architecture, Selcuk University, Selcuklu, Konya, Turkey
Received 13 October 2005; received in revised form 15 June 2006; accepted 31 July 2006
Abstract
In this study, the impact of indoor color use, gender and age on mood and cognitive performance was examined. It was hypothesized
that indoor color for decoration in stores is an effective source that may convey emotional meanings differentiated by gender, age, or
both. In order to study this, a two-stage work was carried out in a cafe
´/restaurant, in which interior yellow walls were changed to violet.
In both stages, furniture and decorations remained the same. Each appearance (yellow and violet) was tested by using visual attributes
through the use of bipolar scales. Results from approximately 250 participants for each stage showed that violet interiors were more
positively perceived when compared to yellow. Compared to females, male users evaluated the space more positively. In addition, young
customers had a more positive tendency than older customers towards the perception of atmospheric attributes, including color of store
interiors.
r2006 Elsevier Ltd. All rights reserved.
Keywords: Color; Store atmosphere; Cafe
´/restaurant; Perception
1. Store atmosphere and the impact of color on consumers
According to Baker [1], atmospheric attributes for
interior spaces consist of three components: ambient
factors (temperature, noise, scent, music, and lighting),
design factors (architecture, color, materials, pattern,
texture, and layout of the store), and social factors
(customers and employees). Research examining the effect
of atmospheric attributes on customer evaluations has
predominantly been focused on the critical influence of
atmospheric attributes and has been concerned with the
attractiveness, pleasantness and spaciousness of retail
facilities such as department stores, supermarkets and
restaurants. The influence of atmospheric attributes in
marketing contexts is based on the premise that the design
of an environment through a variety of means such as
temperature, sounds, layout, lighting, and colors can
stimulate perceptual and emotional responses in consumers
and affect their behavior [2]. Most of this research has
examined the effects of individual pleasant stimuli such as
music [3–5], lighting [6–8] or smell [9] on consumer
behavior, but, surprisingly, little research has addressed
how a store’s predominant color affects consumer reactions
[10,11]. In this work, the indoor perceptual quality of a
cafe
´/restaurant is tested regarding alternative color usage.
The study intends to reveal the effect of color on
customers’ perceptions of store atmospheric attributes. It
is still ambiguous how the application of various colors and
color schemes in stores affect customers’ perceptions of
atmospheric attributes, whether they vary in different
customer segments, and whether the differences of percep-
tion among them are statistically significant or not. There
are few studies relating to how customers’ perceptions of
store atmospheric attributes are affected by an environ-
ment’s use of different colors, which can very much
influence customers’ shopping decisions and behavior.
The effect of color on human performance and cognitive
interpretation provides important evidence suggesting
potential consumer reactions (e.g., [12]). Crowley [11]
reviews this literature and concludes that color influences
ARTICLE IN PRESS
www.elsevier.com/locate/buildenv
0360-1323/$ - see front matter r2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.buildenv.2006.07.037
Corresponding author. Tel.: +90 312 212 6820/1515;
fax: +90 312 212 0059.
E-mail address: kemaly@gazi.edu.tr (K. Yildirim).
both consumers’ evaluation-related affect (affective tone)
and activation-related affect (arousal), which is generally
consistent with retailing research.
A color’s hue or gradation is determined by its
wavelength. Short wavelengths are associated with ‘cool’
colors, with violet being most extreme followed by blue.
Long wavelengths are associated with ‘warm’ colors, with
red being most extreme followed by orange. Experimental
research suggests that cool-colored store environments are
preferred over warm-colored store environments [10,11].
As a result, it has generally been concluded that blue
environments evoke better feelings than do orange
environments [13]. In addition, experimental research using
a hypothetical television purchase suggests that a blue
background can decrease the likelihood of postponing a
purchase compared to a red background [14]. According to
Babin et al. [15], it is generally expected that violet/blue
interiors will produce higher levels of positive affective tone
and increased purchase intentions than red/orange inter-
iors. Interestingly, plenty of research has evaluated the
indirect impact of environments of different colors by
dealing with the perceptual quality of spaces [16–18].In
two experiments, Stone [19] manipulated environmental
color and view to determine their effects on mood,
satisfaction, motivation, and performance. The findings
of this work suggest that blue is a calming color and red is a
stimulating color, which may interact with other environ-
mental factors. As Canter [20] mentions blue makes things
seem farther away and red makes them seem nearer. In
another study [21], when college students worked anagrams
in colored rooms, most of the students in the blue room
rated themselves as calm or in good moods. Yet, most of
the students also rated their mood as good in the red room
relative to the yellow and neutral rooms. In contrast,
Kwallek and Lewis [22] found that individuals who worked
in a red environment as opposed to a white or green
environment had a lower amount of confusion and
bewilderment. As seen above, research surrounding the
meanings people associate with color paints a confusing
picture. Yellow, for instance, has been suggested as a
good color for libraries and classrooms, as it was thought
to stimulate the intellect, but art therapists have
observed that suicidally inclined patients tend to use yellow
pigment generously in their paintings (as indeed, did Van
Gogh) [23]. Besides there will be a difference in emotional
reaction to a red bus as opposed to a red breast and as
Canter [20] mentions there is no reason to suppose that in
many other examples there will be more convergence of
response.
2. Research considerations
The specific aims of this experiment were (1) to assess the
visual satisfaction of a cafe
´-patisserie/restaurant located in
Ankara, Turkey and (2) to develop a model that can be
utilized by designers to describe the desired attributes. The
research focuses on determining the effects of various color
applications on customers. In this spirit, the main
hypothesis of the study was that the perceived quality of
space would be significantly greater and a more positive
image would be received for cafe
´/restaurants decorated
with cool colors (violet) than warm colors (yellow). As
suggested, warm colors make a space feel smaller, lower,
and depressing, compared with cool colors. For that aim a
two-stage work was carried out, with the only difference
between these two stages being the color of the walls. In the
first stage of the experiment, the walls of the cafe-
restaurant were yellow (Experiment 1) and in the second
stage, the walls were violet (Experiment 2).
Another one of the objectives of the present study was to
expand the effects of gender as an important independent
variable on perception. In particular, the task was to
investigate men’s and women’s reactions to a space with
various color usage. It is believed that space is perceived
differently by men and women, i.e. male customers are
more positive than the female customers. In fact, gender
researchers have attributed the differences between men
and women to a variety of social and biological factors
[24]. In the literature, the concept of gender-role identifica-
tion is central and is considered to be a major factor in the
development of behavioral differences. Some scholars
suggest that male–female differences in aptitude and
personality traits often reflect traditional gender roles in
society [24]. Researchers have found that regardless of the
traditional image of a described product, and regardless of
the actual gender of the perceiver, consumers prefer
products described in terms that matched the gender
attributes that they perceived as both characteristic of
and important to themselves [25]. According to Putrevu
[24], men seem more analytical and logical since they focus
on a few salient attributes and women seem more
subjective and intuitive since they look for relationships
between all the available attributes. In fact, compared with
men, women seem more accurate in decoding nonverbal
attributes [26] and are considered to be more visually
oriented, more intrinsically motivated, and more romantic
[27]. Another study by Dube and Morgan [28] found that
women’s satisfaction judgments were largely influenced by
their initial negative emotions, whereas men’s satisfaction
judgments depended on their first positive emotions,
suggesting a primacy effect for both genders. Therefore,
the literature suggests that men and women think and
behave differently due to the alternative roles they play in
society.
Depending on age, the responses given about the
perceptual quality of space were also expected to differ-
entiate, i.e. younger customers (under 30 years of age) were
most likely to be concerned about the physical qualities of
space negatively, whereas older customers (over 30) were
more likely to be positive. This hypothesis was generated
from several studies, including Holbrook and Schindler
[29], a study that found that age played an important role
in participants’ perceptions of space in aesthetic prefer-
ences of retail environments.
ARTICLE IN PRESS
K. Yildirim et al. / Building and Environment 42 (2007) 3233–32403234
3. Method
3.1. Subjects
Regarding the two stages, for the Experiment 1 a total of
245 customers who had previously been in the space and
experienced the space less than a year participated in this
research in order to determine their perception of the
particular store atmospheric attributes. After the renova-
tion, the same questionnaire was repeated for the Experi-
ment 2 with another 250 customers. All of the respondents
joining the research were the ones using the space mostly at
the weekends and the weekdays afternoon (1–3 p.m.—peak
time). The samples in each group had a similar diverse
distribution by age and gender. 49% of the respondents
were men, 51% of them were women. 47% of the
respondents were between 18 and 29 years old, 53% of
them were between 30 and 60.
3.2. Experimental setting
For this research, a prestigious cafe
´/restaurant for about
86 was used as the research setting. Deep in the corner of
the store there is a place enclosed by a curved wall 90 cm
high from the ground level for special occasions or to be
used other times for private meetings. The tables, chairs,
and food exhibit units of the cafe
´are made of or framed
with wooden materials and stained in a light walnut color
and then finished with polyurethane varnish (Fig. 1).
This cafe
´/restaurant has a decorative ceiling (height
varies between 300 and 330 cm) covered with white
plasterboard. For interior lighting, 6 13 W lamps hang
210 cm above the floor over the displaying cabinets. In
addition, 60 18 W compact fluorescent lamps, all directed
downwards, and 10 100 W spot halogen lamps are on the
ceiling. On the walls, there are only three incandescent
40 W fixtures in glass brackets 170 cm above ground level.
All the lights can provide approximately 253 lx light when
on at the same time (Fig. 2).
3.3. Control conditions and procedure
Before the experiment, the cafe
´/restaurant was deodor-
ized to eliminate any pre-existing odor. Between the
experimental treatments (1 day for each treatment), the
space was ventilated with air-condition. Cafe
´/restaurant
temperature, ventilation, and lighting were monitored for
consistency during the experiment.
A two-stage work was carried out, with the only
difference between these two stages being the color of the
ARTICLE IN PRESS
KITCHEN
02 m
ÖZSÜT CAFE -PATESSERIE / RESTAURANT
(STORE B)
displaying
cabinet
1
Fig. 1. Main plan.
Fig. 2. Interior pictures of the cafe
´/restaurant (Experiment 1: yellow interior and Experiment 2: violet interior).
K. Yildirim et al. / Building and Environment 42 (2007) 3233–3240 3235
walls. In the first stage of the experiment, the walls of the
cafe-restaurant were yellow (Experiment 1) and in the
second stage, the walls were violet (Experiment 2).
Questionnaires were self-administered, but interviewers
were present to clarify any doubts or queries. The survey
was conducted at 1–3 p.m. peak time of the afternoon,
during weekdays and weekends. Respondents took ap-
proximately 10 min to complete each of the questionnaires.
The data was obtained by face-to-face meetings in the
period of 3 months during 2003–2004. The questions were
categorized into three sub-groups as:
functional quality of the space;
the organization’s identity known by its users;
perception of the space.
The experiment focused on the ordering of visual
atmospheric attributes through the use of bipolar scales.
The customers of the cafe
´/restaurant were asked to
describe to rate visual displays on these scales. The
technique of altering the sets of items from positive to
negative, as previously done by Fiedler [30]; Joyce and
Lambert [31]; Wakefield and Blodgett [32]; Mattila and
Wirts [4]; Eroglu et al. [33]; Baskaya et al. [34] and Yildirim
[35] was adopted to reduce the probability of the
respondents simply marking the scale on either of
the extremes. In compiling an initial list of items, the
researchers tried not to be too specific, but rather to
develop a list of general attributes that would fit the
research subject. The respondents then had to evaluate the
importance of each of the bipolar semantic differential
items on a Likert-type Scale from one (positive) to five
(negative). A total of eight bipolar semantic differentials
(roomy/cramped, high/low, pleasant/unpleasant, attrac-
tive/unattractive, interesting/boring, imposing/poor-look-
ing, calm/restless, warm/cold), measuring the perceptual
quality of the cafe
´/restaurant with yellow and violet
interiors, were evaluated by the respondents after famil-
iarizing themselves with these pairs.
In order to test the hypotheses of this study, the model of
the research was formed in a 2 22 factorial design
(color age gender). As a result of this research, the
categorical means of the data are defined with their
standard deviations and t-values. Afterwards, to examine
the effect of differences in color, age and gender variables
on perceptions of store atmospheric attributes in the
context of cafe
´/restaurant, the appropriate technique of
multivariate analysis of variance (MANOVA) was used.
To compare the significant means of the variance in the
analysis, the data is given in graphic form.
4. Data analysis and results
The reliability of the store atmospheric attributes was
tested using Cronbach’s test. The Cronbach alpha coeffi-
cient for the set of eight bipolar semantic differential items
including perceptual quality was 0.74. Additionally,
Cronbach alpha coefficient estimates of internal consis-
tency for each multi-item dependent measure were as
follows: roomy/cramped, 0.71; high/low, 0.71; pleasant/
unpleasant, 0.68; attractive/unattractive, 0.70; interesting/
boring, 0.71; imposing/poor-looking, 0.72; calm/restless,
0.72; warm/cold 0.75. Alpha coefficients of all items were
above 0.60, representing good reliability according to
consumer researchers [36,37]. These items may therefore
be considered to be reliable.
In this part, the statistical relationship between the
different color use of the walls (yellow and violet) in the
cafe
´/restaurant and age (younger, older) and gender (male,
female) groups with customers’ perceptions of store atmo-
spheric attributes were analyzed. The results of the research
questionnaire are given in Table 1 as the mean, standard
deviation and t-value for each of the items of the dependent
variables.
From the evaluation of the means and t-values, it can be
seen that customers had more positive perceptions about
the violet interiors of the cafe
´/restaurant atmospheric
attributes than yellow interiors. Moreover, when younger
ARTICLE IN PRESS
Table 1
Means, SD and t-values of the dependent variables
Dependent variables Colors of walls in store Age of customer Gender of customer
Yellow Violet Younger Older Male Female
Mean
a
(SD) Mean (SD) t-value
b
Mean (SD) Mean (SD) t-value Mean (SD) Mean (SD) t-value
Roomy/cramped 2.31 (1.03) 1.76 (0.86) 33.5* 1.85 (0.92) 2.19 (1.02) 40.2* 2.02 (0.97) 2.04 (1.04) 36.1*
High/low 2.44 (0.96) 2.32 (0.97) 30.1* 2.43 (0.96) 2.33 (0.97) 40.1* 2.23 (0.96) 2.52 (0.92) 37.5*
Pleasant/unpleasant 2.25 (0.93) 1.84 (0.92) 32.2* 2.00 (0.95) 2.08 (0.95) 38.7* 1.92 (0.92) 2.15 (0.96) 34.9*
Attractive/unattractive 2.13 (0.97) 1.92 (1.01) 28.7* 1.83 (1.00) 2.19 (0.97) 40.6* 1.77 (0.90) 2.26 (1.02) 31.2*
Interesting/boring 2.62 (0.94) 1.76 (0.95) 38.2* 1.96 (0.97) 2.38 (1.05) 42.3* 2.02 (1.00) 2.34 (1.05) 33.6*
Imposing/poor-looking 2.67 (1.04) 2.32 (1.01) 32.2* 2.56 (0.87) 2.43 (1.17) 39.1* 2.47 (1.02) 2.50 (1.06) 46.8*
Calm/restless 2.32 (0.99) 2.16 (0.92) 30.1* 2.32 (0.93) 2.17 (0.97) 38.1* 2.36 (0.91) 2.12 (0.99) 42.7*
Warm/cold 2.24 (0.96) 2.50 (1.11) 25.8* 2.32 (1.04) 2.41 (1.05) 40.2* 2.16 (1.02) 2.57 (1.03) 34.7*
Notes:SD¼Standard deviation. * a: 0.001 is the level of significance.
a
Variable means ranged from 1to 5, with higher numbers representing more negative responses.
b
t-Values: It is result of comparison of store atmospheric attributes with color, age and gender variables.
K. Yildirim et al. / Building and Environment 42 (2007) 3233–32403236
and male customers are compared with older and female
customers, respectively, the young and male customers had
a more positive perception of the yellow/violet interior of
the cafe
´/restaurant in most of the attributes. The differ-
ences between these dependent variables of store atmo-
spheric were tested using MANOVA. These results are
given in Table 2.
According to the MANOVA results, the main variables
(color, age and gender), the effects of double interaction
(color age, color gender, age gender) and triple inter-
action (color age gender) were found to be significant
(Po0:001 level). In conclusion, it can be said that
differences among yellow/violet interiors of cafe
´/restau-
rant, customers’ age and gender are effective on store
atmospheric perception. More specifically, it can be said
that differences between the colors of the walls in the store
are effective on store atmospheric evaluations. Moreover,
when variance analyses are examined, it is seen as
‘‘reliable’’ among the total perceived degrees of dependent
variables. When the F-values calculated in the table of
variance analyses are examined, it can be said that all these
dependent variables have a strong effect on customers’
perceptions in the cafe
´/restaurant. It is understood that
there are also differences in the perception of atmospheric
attributes according to age and gender groups.
The graphic of differences between customers’ evalua-
tions of various colors of interiors (yellow and
violet), depending on their perceptions of store atmo-
spheric attributes for perceptual quality items, are given in
Fig. 3.
As seen in Fig. 3, the relationship between the
independent variables (yellow and violet interiors) and
the dependent variables (store atmospheric attributes) for
the items ‘‘roomy/cramped’’ (F¼41:79, df ¼1, Po0:001),
‘‘pleasant/unpleasant’’ (F¼24:32, df ¼1, Po0:001), ‘‘at-
tractive/unattractive’’ (F¼5:29, df ¼1, Po0:05), ‘‘inter-
esting/boring’’ (F¼100:4, df ¼1, Po0:001), ‘‘imposing/
poor-looking’’ (F¼13:91, df ¼1, Po0:001) and ‘‘warm/
cold’’ (F¼7:42, df ¼1, Po0:01) were found to be
significant. It is understood that the most effective factor
among the variables on customers’ perceptions of yellow/
violet interiors was the ‘‘interesting/boring’’ scale. It can be
said that this difference results from the yellow and violet
interiors. According to this result, it was found that the
perceptions of each of the two different colors of the walls
in the cafe
´/restaurant were statistically different with
regards to the perceptual quality variables and the range
of colors of the walls differ from the most positive value to
the most negative value arranged as ‘‘violet interiors4yel-
low interiors’’.
These graphics of differences between age and gender
groups in customers’ perceptions of store atmospheric
attributes for perceptual quality items are given in Figs. 4
and 5, respectively.
As seen in Fig. 4, for each of the dependent variables,
younger customers reported the lowest values (positive),
while older customers reported the highest (negative)
values. As a result, the store atmospheric attributes
‘‘roomy/cramped’’ (F¼14:19, df ¼1, Po0:001), ‘‘attrac-
tive/unattractive’’ (F¼16:98, df ¼1, Po0:001) and ‘‘in-
teresting/boring’’ (F¼20:73, df ¼1, Po0:001), which
form the dependent variables, were found to be significant.
According to this result, there seems to be a statistically
meaningful relationship among the customers of different
ARTICLE IN PRESS
Table 2
MANOVA of the dependent variables of the store atmosphere
Independent variables Fdf Sig. Results
Color 25.45 8 0.000* Po0:001
Age 11.53 8 0.000* Po0:001
Gender 10.14 8 0.000* Po0:001
Color Age 13.24 8 0.000* Po0:001
Color Gender 16.33 8 0.000* Po0:001
Age Gender 6.12 8 0.000* Po0:001
Color Age Gender 13.75 8 0.000* Po0:001
Notes:*a: 0.001 is the level of significance.
1.5
2
2.5
3
roomy /
cramped
high / low pleasant /
unpleasant
attractive /
unattractive
interesting /
boring
imposing /
poor-looking
calm /
restless
warm / cold
Semantic Differential Items
Means of Items
Yel l ow
Violet
Fig. 3. The effect of colors on the perceptions of atmospheric attributes. Notes: Variable means ranged from 1 to 5, with higher numbers representing
more negative responses.
K. Yildirim et al. / Building and Environment 42 (2007) 3233–3240 3237
age groups and their atmospheric attributes perception.
It appears that the study’s expectations regarding the effect
of age on customers’ perceptions of store atmospheric
attributes were basically confirmed.
As seen in Fig. 5, for each of the dependent variables,
male customers received the lowest values (positive), while
female customers received the highest (negative) values. As
a result, the atmospheric attributes ‘‘high/low’’ (F¼11:06,
df ¼1, Po0:001), ‘‘pleasant/unpleasant’’ (F¼6:93,
df ¼1, Po0:01), ‘‘attractive/unattractive’’ (F¼32:20,
df ¼1, Po0:001), ‘‘interesting/boring’’ (F¼12:49,
df ¼1, Po0:001), ‘‘calm/restless’’ (F¼7:89, df ¼1,
Po0:01) and ‘‘warm/cold’’ (F¼19:42, df ¼1, Po0:010),
which form the dependent variables, were found to be
significant. According to this result, there seems to be a
statistically meaningful relationship among customers of
different gender groups and their atmospheric attributes
perceptions. Therefore, based on the results regarding the
effect of gender groups on customers’ perceptions of
atmospheric attributes, those attributes noted for their
perceptual quality items is supported.
5. Concluding remarks
The results of this study help in the understanding of
how the color design of commercial interiors influences
customers’ perceptions of store atmospheric attributes. The
results show that customers’ perceptions of two different
colors of an interior regarding its atmospheric attributes
are different and statistically significant (Po0:001 level).
According to the results, customers have a more positive
perception of violet interiors (Experiment 2) than yellow
interiors (Experiment 1). This result supports the definition
of Valdez and Mehrabian [13] that short wavelength
colors—associated with ‘cool’ colors—like violet or blue
are preferred, leading to a linear association between
affective tone and wavelength. The results of this work also
have some parallels with Swedish studies and Grandjean
ARTICLE IN PRESS
1.5
2
2.5
3
roomy /
cramped
high / low pleasant /
unpleasant
attractive /
unattractive
interesting /
boring
imposing /
poor-looking
calm /
restless
warm / cold
Semantic Differential Items
Means of Items
Younger
Older
Fig. 4. The effect of age on the perception of atmospheric attributes. Notes: Variable means ranged from 1 to 5, with higher numbers representing more
negative responses.
1.5
2
2.5
3
roomy /
cramped
high / low pleasant /
unpleasant
attractive /
unattractive
interesting /
boring
imposing /
poor-looking
calm /
restless
warm / cold
Semantic Differential Items
Means of Items
Male
Female
Fig. 5. The effect of gender on the perceptions of atmospheric attributes. Notes: Variable means ranged from 1 to 5, with higher numbers representing
more negative responses.
K. Yildirim et al. / Building and Environment 42 (2007) 3233–32403238
[38], who suggest that lighter colors are judged as being
friendlier, brighter, more cultured, seems to make life easier
and more pleasant, and also appear more beautiful.
Besides, the results of this work supports the findings of
Babin et al. [15] generally believing that violet/blue
interiors will produce higher levels of positive affective
tone and increased purchase intentions than red/orange
interiors. However, compare to the stimulating effects of
yellow as a warm color, the definition of Grandjean [38]
about violet being an aggressive and depressing cold color
conflicts with the results of this study. Regarding this
study, however, it can be said that if the differences in the
colors of the walls commercial environments are taken into
account in their interior design, it can positively affect
customers’ store choice and use of a store’s environment
and product purchase.
The findings of this study also clearly present a
consistent picture of the effects of differences in age groups
on customers’ perceptions of store atmospheric attributes
for perceptual quality items. According to the results,
younger customers had a more positive perception of store
atmospheric attributes than older customers. When eval-
uated generally, it can be said that there is a reverse
relationship between age level and the perception of store
atmospheric attributes. This situation can be explained as
the resistance with which customers display to cultural
change/innovation/modernity, according to their socio-
cultural backgrounds, as related to the generation gap,
their experiences and their knowledge. That is, as age and
experience increases, a more critical attitude is displayed.
This result agrees with the age-related study carried out by
Joyce and Lambert [31] Moreover, this result is quite
important since it determines the validity of atmospheric
attributes in commercial environments are used by
different age groups for different purposes.
The other result of this study is that the difference in
customers’ perceptions of store atmospheric attributes
between the gender groups has been found to be important.
According to the results, male customers had a more
positive perception of store atmospheric attributes than
female customers. In fact, females were more critical than
males about the atmospheric attributes. This situation can
be explained through differences in anatomy, physiology
and psychology. Males and females seem to have different
perceptions based on sentimentality, lifestyles, motivation,
attitude towards decoration and an importance of being
tidy. For example, females can be generalized to be more
sensitive than the males about tidiness, which can cause
them to behave more critically. This result supports the
research of Dube and Morgan [28], which concluded
that women’s satisfaction judgments were largely influ-
enced by their initial negative emotions, whereas men’s
satisfaction judgments depended on their first positive
emotions, suggesting a primacy effect for both genders.
Moreover, Sommer et al. [39] found that women and older
people spent more time in the store than did men or
younger people. From this result, it can be inferred that
women and older people are more critical in their shopping
decisions.
Acknowledgements
The authors would like to thank Christopher Wilson, of
the Faculty of Fine Arts and Design, I
˙
zmir University of
Economics, for his careful proof reading of the English text
and helpful suggestions.
References
[1] Baker J. The role of the environment in marketing services: The
consumer perspective. In: Czepiel J, et al., editors. The services
challenge: integrating for competitive advantage. Chicago: American
Marketing Association; 1986. p. 79–84.
[2] Kotler P. Atmospherics as a marketing tool. Journal of Retailing
1973;49:48–64.
[3] Yalch R, Spangenberg E. Effects of store music on shopping
behavior. Journal of Consumer Marketing 1990;7:55–63.
[4] Mattila AS, Wirtz J. Congruency of scent and music as a driver of in-
store evaluation and behavior. Journal of Retailing 2001;77:273–89.
[5] Caldwell C, Hibbert SA. The influence of music tempo and musical
preference on restaurant patrons’ behavior. Psychology and Market-
ing 2002;19:895–917.
[6] Carter DJ. Synthesis of artificial lighting to satisfy multiple design
criteria. Building and Environment 1983;18:129–34.
[7] Areni CS, Kim D. The influence of in-store lighting on consumers’
examination of merchandise in a wine store. International Journal of
Research Marketing 1994;11:117–25.
[8] Ghisi E, Tinker JA. An ideal window area concept for energy efficient
integration of daylight and artificial light in buildings. Building and
Environment 2005;40:51–61.
[9] Gulas CS, Bloch PH. Right under our noses: ambient scent and
consumer responses. Journal of Business and Psychology 1995;10:
87–98.
[10] Bellizi JA, Crowley AE, Hasty RW. The effects of color in store
design. Journal of Retailing 1983;59:21–45.
[11] Crowley AE. The two-dimensional impact of color on shopping.
Marketing Letter 1993;4:59–69.
[12] Jacobs KW, Suess JF. Effects of four psychological primary colors on
anxiety state. Perception Motor Skills 1975;49:143–61.
[13] Valdez P, Mehrabian A. Effects of color on emotion. Journal of
Environmental Psychology 1994;123(4):394–409.
[14] Bellizi JA, Hite RE. Environmental color, consumer feelings and
purchase likelihood. Psychology and Marketing 1992;9(5):347–63.
[15] Babin BJ, Hardesty DM, Suter TA. Color and shopping intentions:
the intervening effect of price fairness and perceived affect. Journal of
Business Research 2003;56:541–51.
[16] Cohen DJ. Visual detection and perceptual independence: assessing
color and form. Perception and Psychophysics 1997;59:623–35.
[17] Khurana B. Visual structure and the integration of form and color
information. Journal of Experimental Psychology: Human Percep-
tion and Performance 1998;24:1766–85.
[18] van der Velde F, van der Heijden AH. On the statistical independence
of color and shape in object identification. Journal of Experimental
Psychology: Human Perception and Performance 1997;23:1798–812.
[19] Stone NJ. Environmental view and color for a stimulated telemarket-
ing task. Journal of Environmental Psychology 2003;23:63–78.
[20] Canter DV. Psychology for architects. London: Applied Science
Publishers; 1974 43-44129-134.
[21] Rosenstein LD. Effect of color of the environment on task
performance and mood of males and females with high or low scores
on the Scholastic Aptitude Test. Perceptual and Motor Skills 1985;
60:550.
ARTICLE IN PRESS
K. Yildirim et al. / Building and Environment 42 (2007) 3233–3240 3239
[22] Kwallek N, Lewis CM. Effects of environmental color on males and
females: a red or white or green office. Applied Economics 1990;21:
275–8.
[23] Porter T. The architect’s eye: visualization and depiction of space in
architecture. London: E & Spon; 1997. p. 58–65.
[24] Putrevu S. Exploring the origins and information processing
differences between man and women: implications for advertisers.
Journal of the Academy of Marketing Science 2001;10.
[25] Worth LT, Smith J, Mackie DM. Gender schematicity and preference
for gender-typed products. Psychology and Marketing 1992;9:17–30.
[26] Everhart DE, Shucard JL, Quatrin T, Shucard DW. Sex-related
differences in event-related potentials face recognition, and facial
affect processing in prepubertal children. Neuropsychology 2001;15:
329–41.
[27] Holbrook M. Aims, concepts, and methods for the representation of
individual differences in aesthetics responses to design features.
Journal of Consumer Research 1986;13:337–47.
[28] Dube L, Morgan MS. Trend effects and gender differences in
retrospective judgments of consumption emotions. Journal of
Consumer Research 1996;23:156–62.
[29] Holbrook M, Schindler R. Age, sex, and attitude toward the past as
predictors of consumers’ aesthetic tastes for cultural products.
Journal of Marketing Research 1994;31:412–22.
[30] Fiedler FE. The leadership game: matching the man to the situation.
In: Gibson JW, Hodgetts RM, editors. Readings and exercises in
organizational communication. Orlando, FL: Academic Press; 1985.
p. 122–30.
[31] Joyce ML, Lambert DR. Memories of the way stores were and retail
store image. International Journal of Retail & Distribution Manage-
ment 1996;24:24–33.
[32] Wakefield KL, Blodgett JG. Customer response to intangible and
tangible service factors. Psychology and Marketing 1999;16:51–68.
[33] Eroglu SA, Machleit KA, Davis LM. Empirical testing of a model of
online store atmospherics and shopper responses. Psychology and
Marketing 2003;20:139–50.
[34] Baskaya A, Wilson C, Ozcan YZ, Karadeniz D. A study in re-
establishing the corporate identity of a post office institution with
gender-related differences in perception of space. Journal of
Architectural and Planning Research 2006;23:43–59.
[35] Yildirim K. The effect of differences in customer characteristics on
the evaluation of a store image. Journal of the Faculty of Engineering
and Architecture of Gazi University 2005;20:473–81.
[36] Bagozzi RP, Yi Y. On the evaluation of structural equation models.
Journal of the Academy of Marketing Science 1988;16:74–94.
[37] Kim JO, Jin B. Korean customers’ patronage of discount stores:
domestic vs. multinational discount store shoppers’ profiles. Journal
of Consumer Marketing 2001;18:236–55.
[38] Grandjean E. Ergonomics of the home. New York: Wiley; 1973.
[39] Sommer R, Wynes M, Brinkley G. Social facilitation effects in
shopping behavior. Environment and Behavior 1992;24:285–97.
ARTICLE IN PRESS
K. Yildirim et al. / Building and Environment 42 (2007) 3233–32403240
