Role of Kaplan's Preference Matrix in the Assessment of Building façade, Case of Gorgan, Iran

Abstract

Buildings play a key role in organization and arrangement of city appearance. Specially, their facades have profound impact on the quality of urban landscapes while playing an important role in assessing urban environments by citizens. The introduction of superior building facades in terms of popular preferences is mostly based on visual elements of building facades. Furthermore, aesthetic preferences should not be explored without investigating the consequences of their interaction with environment which forms mental concepts; whereas, few studies have explored building facades based on preference of observer. Therefore, current research has been conducted as a survey in order to evaluate the role of each variables in Kaplan's preference matrix on building façade preferences. Our questionnaire was based on information factors including "coherence", "complexity" and "mystery", while excluding "legibility". In this survey, 100 respondents have rated their preferences for 48 building façades located in Grogan, via a photo questionnaire. Data collected from the questionnaire were analyzed by using SPSS software. According to the correlation test, there was a significant correlation between preference and triple information factors (coherence-complexity-mystery). Furthermore, according to the regression test, the model consisting triple information factors (coherence-complexity-mystery) can predict 62.3% of preference toward building facades. In addition, it was revealed that complexity and mystery are significant in predicting the preference for building facades compared to cohesion. Finally, it is suggested that the focus of design on building facades should be based on complexity and mystery as they make building facades to be more preferred.

Full text

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Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
ISSN: 2008-5079
EISSN: 2538-2365
Role of Kaplan’s Preference Matrix in the Assessment of
Building façade, Case of Gorgan, Iran
Sanaz Memari1 and Mahdieh Pazhouhanfar2*
1 M.A. of Architecture, Faculty of Engineering, Golestan University, Gorgan, Iran.
2 Assistant Professor of Architecture, Faculty of Engineering, Golestan University, Gorgan, Iran.
Received 21 February 2016; Revised 24 April 2017; Accepted 20 May 2017
ABSTRACT: Buildings play a key role in organization and arrangement of city appearance. Specially,
their facades have profound impact on the quality of urban landscapes while playing an important role
in assessing urban environments by citizens. The introduction of superior building facades in terms
of popular preferences is mostly based on visual elements of building facades. Furthermore, aesthetic
preferences should not be explored without investigating the consequences of their interaction with
environment which forms mental concepts; whereas, few studies have explored building facades based
on preference of observer. Therefore, current research has been conducted as a survey in order to evaluate
the role of each variables in Kaplan’s preference matrix on building façade preferences. Our questionnaire
was based on information factors including “coherence”, “complexity” and “mystery”, while excluding
“legibility”. In this survey, 100 respondents have rated their preferences for 48 building façades located
in Grogan, via a photo questionnaire. Data collected from the questionnaire were analyzed by using SPSS
software. According to the correlation test, there was a signicant correlation between preference and
triple information factors (coherence- complexity- mystery). Furthermore, according to the regression
test, the model consisting triple information factors (coherence-complexity-mystery) can predict 62.3%
of preference toward building facades. In addition, it was revealed that complexity and mystery are
signicant in predicting the preference for building facades compared to cohesion. Finally, it is suggested
that the focus of design on building facades should be based on complexity and mystery as they make
building facades to be more preferred.
Keywords: Pollution, Visual Preference Coherence, Complexity, Urban Landscape, Mystery, Visual.
* Corresponding Author Email: m.pazhouhanfar@gu.ac.ir
INTRODUCTION
The design process for city is never accomplished
and details at every morphological level are disposed to
constant change (Lynch, 1960). Some people believe in
positive effects of the changes on context of cities since
they address its political and nancial benets (Gjerde,
2011). On the other hand, the speed of this change is so
rapid that there isn’t sufcient time and opportunity to
consider citizens’ opinions and utilize them into design.
Therefore, the designer plays the key role in the process
of designing. Parts of this negative change the urban area
are associated with neglected aesthetic aspects which
are essential to improve the quality of building facades.
Consequently, the real visual needs of citizens toward
building facades are mostly ignored. Thus, the necessity
of conducting research on building façade preferences
should be emphasized.
Desired urban scope encompasses rich visual
structures. The rich visual structures are organized
elements which can be detected by observers through
reviewing the general form, the focal points in the detailed
parts or in the inconsistencies in the middle or cornerstone.
Moreover, the use of ornaments and decorative elements
can divide the facade into different scales and affect its
visual perception profoundly (Salingaros, 2003). Even
if building facades, according to minimalist point of
view, would be considered merely as an exterior wall,
contemporary building facades neither have a positive
role in improving the visual quality of the urban scape,
nor make feelings of joy, satisfaction, and vitality among
citizens which are the most important indicators of desired

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Memari, S. et al.
and favorable urban spaces. Instead, most of current
building facades with poor design qualities cause anxiety,
tension and distress and affect observant negatively.
Problem Statement
Despite all research on building facades which have
evaluated them from expert perspective, less attention has
been paid to the preferences of people. In previous studies,
many efforts have been made to introduce superior
building facades in terms of visual elements. Since
perception of beauty is always associated with personal
emotions and the individual’s mental background, the
aesthetic preferences could not be considered apart from
the investigation of the mental concepts of individuals
towards the environments. Therefore, current paper
aims to examine the visual preferences of people toward
building facades in terms of variables of Kaplan’s
preference matrix.
In a meta-analysis study, exploring relationship
between preferences of environment including
natural and built kinds and four variables in Kaplan’s
preference matrix and three more variables (complexity,
coherence, and mystery), it was revealed that there is a
correlation between them. While, results reported a weak
relationship between legibility and preference, legibility
does not have direct linear relation with preference and
there is a weak link between them (Stamps Iii, 2004).
Other studies have also reported the limited impact of
legibility on preferences (e.g., Gimblett, 1990; Herzog,
1989; R. Kaplan & Kaplan, 1989; Pazhouhanfar &
Mustafa Kamal, 2014). Thus, in current study by omitting
legibility, the role of other three variables, including
coherence, complexity and mystery in public preferences
are explored. The purpose of this paper is to identify and
compare the components of Kaplan’s preference matrix
which are effective in preference. As a result, through
considering and implementing effective components in
designing building facade, the visual quality of urban
scape will be improved. This result is important since
people are affected by these perspectives every day.
Research Background
Environmental comfort is one of the factors that is
very vulnerable and has a sensitive nature against various
pollutions. These pollutions could cause environmental
degradation and negative effect on the perceptions of
individuals of the surrounding environments. Some of
these pollutions are recognized as physical pollution,
symbolic and legibility pollution, visual pollution,
visual pollution, color pollution, and light pollution.
The concept of visual pollution refers to the presence of
any kinds of disturbance and poor visual quality in the
city (including views, forms, volume of buildings, and
windows, etc.). The visual pollution of the environment
is one of the factors that can make the perception of the
environment monotonous (Carmona & Tiesdell, 2007).
In general, the way in which contemporary urban scape
perceived by people is mostly different with the aesthetic
aspects in designer’s viewpoint. Consequently, citizens
are unwittingly tolerant of a poor urban environment and
poor visual qualities which are not preferred by them.
However, lack of aesthetic satisfaction impacts nervous
system negatively (Porteous, 2013). Negative effects of
undesirable landscapes and boring environments along
the roads and the outskirts of the city can make people
impassive and indifferent, and less responsive to the
environments. Since people do not like their surrounded
environments, they are not trying to maintain its vitality.
Consequently, such environments have been abandoned
(Bell, 2012). All of these negative outcomes are due to
creating an environment and urban landscapes regardless
of preferences of the citizens.
Preference and selective choice are emotional
reections to a part of the surrounding environment.
Preference is identied as part of the cognitive processes
and product of perception that should be understood in
order to study human perception while encountering
with the environment. In other words, individuals by
virtue of preference for a place or a landscape make
communication and interaction with their surroundings
and experience sense of place for specic settings.
Preference is an indicator of human perception and his
behavior (Nasar, 1997). Studies regarding preference have
focused on analysis the reactions of ordinary people (non-
specialists) toward content of the environment and their
spatial understanding as well. The reaction of individuals
as a unit of analysis is used to create a predictive model
(psychophysical models) or a framework for explaining
aesthetic experiences (cognitive model). In conceptual
models, some studies use judgments based on preferences
as indicators to distinguish the place or things that are
of importance to users (Galindo & Hidalgo, 2005).
Preference studies are a practical and systematic approach
that can be useful to measure people’s preferences
and to identify environmental characteristics which
make a scene desirable. In general, it can be concluded
that the concept of preference is identied as a simple
conceptual response to a particular place by individuals
(Abbasalizadeh Rezakolai, Samadi, & Tabatabaian,
2015). Previous related studies have examined different
research gaps (e.g., Importance of aesthetics and visual

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Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
preferences of people on built or natural environments -the
role of preference in promoting quality of environments
and strengthening the relationship between individuals
and environment- interaction between individuals and
their surrounding environments which comes from their
preference). Therefore, during the last few decades, more
attention has been paid to landscape assessment issues.
Specially, many studies have been conducted on the
assessment of the built and natural environments. Some
studies have also compared the natural environments
with built environments in terms of preference. It was
revealed that people prefer natural environments rather
than built environments (Kaplan & Kaplan, 1989; van
den Berg, Koole, & van der Wulp, 2003). Moreover,
studies indicated that the presence of water can have a
positive effect in the environmental preference (Yang &
Brown, 1992). Further, due to effectiveness of natural
environments on improving the health of individuals
and reducing stress, visiting natural environments
can contribute to preference on natural environments
compared with built environments (Ulrich et al., 1991).
Studies have indicated that complexity has a positive
effect on preference (e.g., Falk & Balling, 2010; Ode &
Miller, 2011). According to previous studies, mystery also
has a signicant effect on preference among other three
variables of preference matrix (complexity, coherence,
and legibility; Kaplan & Kaplan, 1989). In another
research it was claimed that individuals are more likely
to prefer scenes which are high in mystery specially in
natural environments (Gifford, 2007).
Concepts and Theoretical Framework
Prior to examine the building façade preference, its
theoretical framework should be reviewed. One of the
most environmental psychology theories which have been
studying widely for years is the Theory of Environmental
Preference. The preference matrix is a theoretical tool
based on principles of evolutionary psychology (Kaplan
& Kaplan, 1983). Kaplans have introduced humans
as information processors, which is developed from
evolutionary psychology. First an individual must be able
to recognize objects in the environment in order to be able
to survive, then make predications and nally evaluate
the consequences. This process builds a mental construct
which is called a cognitive map.
The key dimensions make an environment desirable
recognized as follow: (1) whether an individual can make
sense of the environment and (2) whether an individual
can be involved with the environment through learning
and/or exploration (Paxton, 2006). Making sense and
involvement can both be examined from the standpoint
of time (present/future). In General, the preference matrix
is composed of two binary dimensions. Together, these
two dimensions dene four contain variables which
are conceptually distinct predictors of environmental
preference. The theory of preferences is based on the
assumption that people have two basic needs in relation
with the environment: one is perception and the other
one is cognition. When these two needs meet with two
levels of consciousness, there become four factors.
These two levels of consciousness can be summarized
in two categories of quick and immediate perception
and inferential perception. These four variables
called “information variables”: coherence (immediate
perception), complexity (immediate cognition),
legibility (exploratory perception), mystery (exploratory
cognition). These four variables have been introduced as a
predictor of preference. In addition to this categorization,
there is another classication that separate environmental
information to two dimensions and three dimensions. Thus,
“coherence” and “legibility” are among the perceptual
variables that make the environment meaningful to the
individual, and “complexity” and “mystery” are other
variables of environmental preference that by providing
variation in the content of the environment attracts
people. On the other hand, “coherence” and “complexity”
are considered as two-dimensional factors. Moreover,
“legibility” and “mystery”, on the contrary, requires a
three-dimensional insight to be completely understood.
Table 1. Kaplan’s Preference Matrix
The Framework of the Proposed Kaplan Model for Human Preferences
Information Specication
Perception
Make Sense
(Understanding)
Cognitive
Involvement
(Exploration)
Present Quick Info Two-dimensional Coherence Complexity
Future Predictable
Information Three-dimensional Legibility Mystery

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Role of Kaplan’s Preference Matrix in the assessment of Building façade
These four variables, considered as information variables, each have an operational denition as follows:
Table 2. Denition of Information Variables in the Kaplan’s Preference Matrix
Coherence Legibility
Coherence comes from immediate revealed information,
which is two-dimensional and perceptive. The coherence
of environment or setting is related to the ordering and
organizing of its elements. If the setting is homogeneous
and consistent, users can easily understand and interact
with it. Kaplan believes that cohesion can be achieved by
repeating the same context of texture, while some degree of
contradiction can also contribute to coherence. Coherence is
similar to Gestalt’s principle of organizing, which refers to
the fact that elements in the form of a group are recognized
to be unique. In fact, the goal of applying coherence is to
systematize the setting through integrating identical groups
which achieved by repetition or replication of components,
and conict reduction.
The concept of legibility is about navigation. Clearing
and identifying paths is very important since it creates
a sense of security in the individual. Legibility is
about reading the environment and understanding
it. The understandable ambience of the environment
is contributing to its legibility. Therefore, any sign,
landmark or focal point can enhance the environmental
legibility. When the setting is experienced for the rst
time, one analyzes the environment in order to read it.
Prospect can also have a positive effect on reading the
environment through opening up the landscape. Even
texture compositions have played an important role in
improving legibility through getting a context more
recognizable.
Complexity Mystery
Complexity refers to the degree of diversity of elements in
the environment. The more complex the environment, the
more information is available. According to the Kaplan
theory, more diversity in the environment encourages
individuals to explore more in the environment. The two
concepts of coherence and complexity should not be used
interchangeably, since an environment with high coherence
can be very complicated at the same time. Moreover,
multiplicity of colors, textures and shapes are some examples
of complexity.
Mystery is one of the factors that leads to more
exploration in the environment. Mystery provide lot of
information that by thinking and contemplating in the
environment can be achieved. Mystery makes it easy
for users to explore the environment in order to learn
more about it. There are several ways to create mystery
in the environment, including the creation of winding
paths and purposeful use of vegetation for blocking the
line of sight.
(Kaplan & Kaplan, 1989)
Each of above-mentioned qualities creates a qualitative
environment that makes it attractive and preferable
compared to others. Clear or simple prospects make a
quick recognition and an organizing implementation by
the observer while in landscapes which have high levels
of complexity, environmental perception decreases due
to the increased information received by the observer.
Legible perspectives provide security. Therefore, through
legibility environment reassure viewers that they will
not feel lost and are able to navigate easily. Mysterious
prospects through encourage the viewer to explore
the environment, improve their learning capacity and
provide them more experiences. However, in Kaplan’s
view, in addition to complexity, cohesion, mystery and
legibility, the environmental familiarity is also effective
factor in preference. The optimal level of these factors
can lead to a preference for a landscape, environment or
location. In general, it can be concluded that in Kaplan’s
theory of environmental preferences, human beings are
considered as information processors who are trying
to get acquainted with cognitive processes and related
variables that determine preferences for the environment.
In this theory, information plays a key role in human
experiences and the source of this information is also
available in the environment (Paxton, 2006).
METHOD
Participants
100 undergraduate and graduate students at Golestan
University were selected randomly and asked to answer
the photo questionnaire voluntarily.

17
Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
Stimulus Material
The tool used for collecting the data is a photo
questionnaire, in which participants respond to questions
regarding to their preferences through watching pictures
that include different building facades. Since previous
studies (e.g., Reeve & Simmonds, 2007) have conrmed
similarity between information received from photograph
of the building facade and the direct observation, in this
study, the photo was used as an alternative for on-site
survey. Moreover, other studies have been considered
it scientically valid to look at the photo to answer the
questionnaire instead of visiting the site (e.g., Rosenthal
& Rubin, 1986; Sanoff, 1991). Therefore, almost ve
hundred photographs of the modern and old three-to-
ve-story building facades in the city of Gorgan were
originally prepared by the author in April 2015. All
photos were taken with a 16-megapixel camera, between
10 to 15 A.M., on sunny days from building facades. All
photos have the same characteristics, including:
1) having high quality, 2) Be taken in height of eyes
level in standing position, 3) common zooming adjustment
in order to contain same portions and decorating details.
Then a professional photographer was invited to
select the 100 photographs among a collection of 500
photographs in order to ensure that only appropriate
and good quality images were selected. Due to avoiding
personal and deliberate choices out of wide range of
different building facades, a group of ve architecture
experts were asked for selection of 48 photographs out of
100 photographs. Samples of these photos are displayed
in Fig. 1. By adding two photos to the rst and two
photos to the end, the number of displayed slides was 52
slides, although the data related to these 4 photos was not
analyzed. The rst two photos were removed due to the
possibility of misunderstanding of the questions and the
last two photos were removed due to the possibility of
tiredness which can lead to invalid response.
Fig. 1. Examples of Photo of the Building Facades Rated in Photo Questionnaire
Procedure
Participants are invited to the conference room. After
a brief explanation of the purpose of the study and how to
ll out the questionnaire by the author, 52 colored slides
were displayed on the screen by means of projector one
after the other. The author did not inuence on participants
in responding to questioner. Thus, the participants
were completely independent in their preference. After
responding to the rst 25 slides, there was a break time.
After the break, participants were asked to resume the
process and respond to the rest of the questions.
Research Design
Dependent variable: The preferences of individuals
toward building facades in this research are considered as
dependent variable.
Independent variables: Coherence, Complexity,
Mystery, and Legibility are the information factors that
make Kaplan’s preference matrix variables. Due to the
ineffectiveness and even the negative effect of Legibility

18
Memari, S. et al.
on preferences, three other variables- Coherence,
Complexity, and Mystery- have been evaluated as
Independent variables.
The conceptual model of this research is illustrated
below as Fig. 2:
Fig. 2. Conceptual Model of Research
As mentioned, due to the negligible effect of legibility
on preference, current study explores Kaplan’s preference
matrix based on three variables: complexity (consisting
of 4 items with reliability of 0.92; sample question: This
building facades contains a good variety of components
that keep me involved), coherence (consisting of 4 items
with reliability of 0.87; sample question: There is a clear
order in the physical arrangement of building facades) and
the mystery (consisting of 4 items with reliability 0.96;
sample question: This building facade makes me feel
there is something interesting to explore). Preference was
evaluated by one question: (I prefer this building façade
over others). Consequently, 13 questions with a seven-
point Likert scale (range from 1 completely disagree to 7
fully agree) were provided to measure overall preference
and components of Kaplan’s preference matrix for each
image. The collected data was used to analyze statistics
including: mean, correlation and regression tests.
The Study Area
The city of Gorgan located in Golestan province-Iran,
has been selected as a case study for the study of building
façade preference. Gorgan is located between 54 degrees 13
minutes to 54 degrees and 45 minutes east longitude and 36
degrees and 31 minutes to 36 degrees and 59 minutes north
latitude, in the southern part of Golestan province. The city
is bounded from the north to the city of Aq Qala, from the
south to Semnan province and the Alborz dynasty, from the
east to the city of Aliabad Katoul, and from the west and
northwest to the Kurdoki and Bandar Gaz cities. The area of
this city is 16152 square kilometers while its height is 36.49
meters above sea level. The population of this city in 2011
was 536 329 and the area of the new city is 3676 hectares. In
addition to neighborhoods of historical context, the city has
neighborhoods that are completely new or integrated from
both contexts. In this paper, most of the construction facades
selected for photography are often located on the streets of
Gorgan Pars, Golshahr and Naharkhoran Blvd, which include
newly built buildings. They can properly demonstrate the
weaknesses and strengths of the current approach in design
of building facades and their impact on urban landscape
quality. The location of Golestan province in the country,
Gorgan city in the province and the mentioned streets are
delineated in the following map as Fig. 3.
Fig. 3. Location of Gorgan City in Map of Political Divisions of the Country (Left) - Location of the Study Area in the
City of Gorgan (Right)

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Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
RESULTS
In this section, the data obtained from the photo
questionnaire are analyzed. The ndings are presented
in two sections: Descriptive statistics and Inferential
statistics.
Descriptive Statistics
Participants
100 volunteers were invited from undergraduate
and postgraduate students in Golestan University of
Technology including 90 percent undergraduate students
and 10 percent postgraduates, 81 percent girls and 19
percent boys.
MEAN AND STANDARD DEVIATION
The results of Table 3 indicate the information
including mean and standard deviation. Accordingly,
among three variables of building façade preference,
cohesion is the highest, and complexity and mystery are
in the next priorities in terms of the mean.
Table 3. The Mean and Standard Deviation of the Research Variables
Variable Mean Std. Deviation
Coherence 3.83 1.62
Mystery 2.84 1.56
Complexity 3.08 1.25
Inferential Statistics
Correlation Coefcient Analysis
The correlation coefcient represents the direct
or inverse relationship, as well as the intensity of the
relationship between two or more variables which
range from 1 to 1+. According to the results of the
correlation test in Table 4, two variables of complexity
and mystery have a direct strong relationship with the
dependent variable. Coherence variable, with respect
to the correlation coefcient, has a direct correlation of
0.37, but relatively weak compared to complexity and
mystery with the dependent variable as preference. The
components of preference are also correlated with each
other signicantly.
Table 4. Correlation Matrix between Variables
Preference Coherence Mystery Complexity
Pearson
Correlation
Preference
Coherence
Mystery
Complexity
1.00
0.37
0.71
0.75
0.37
1.00
0.33
0.43
0.71
0.33
1.00
0.73
0.75
0.43
0.74
1.00
Sig. (1-tailed)
Preference
Coherence
Mystery
Complexity
0
0.000
0.000
0.000
0.000
0
0.000
0.000
0.000
0.000
0
0.000
0.000
0.000
0.000
0
Multiple Linear Regression Analysis
The results of Table 5 demonstrate that R value,
which revealed the correlation between the independent
and dependent variables, is 0.789. Therefore, there is
a strong correlation between the preference and the
variables of complexity, coherence and mystery. The R2
value indicates how much preference can be predicted

20
Role of Kaplan’s Preference Matrix in the assessment of Building façade
by independent variables. According to the result,
complexity, coherence and mystery can explain 62.3% of
variations in the preference.
Table 5. Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
Durbin-Watson
1 0.789a 0.623 0.623 0.95026 1.939
a. Predictors: (Constant), Complexity, Coherence and Mystery
b. Dependent Variable: Preference
Table 6 conrm that the regression model can
signicantly predict the variation of the dependent
variable. Since the signicance level in this analysis
is less than 0.05, the regression model is statistically
signicant, and the model is a good predictor of the
dependent variable.
Table 6. Analysis of Variance of Regression
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression
Residual
Total
3875.66
2344.15
6219.82
3
2596
2599
1291.888
0.903
1430.682 0.000b
a. Dependent Variable: Preference
b. Predictors: (Constant), Complexity, Coherence and Mystery
Table 7 gives information on predicator variables. It is
obvious that the constant values and dependent variables
are all statistically signicant in the model (according to
the sig column). Standardized regression coefcient or
Beta in this analysis are 0.054 for coherence, 0.342 for
mystery and o 0.478 for complexity, which indicate the
effect of each of the independent variables on dependent
variable.
Table 7. Coefcientsa
Model Unstandardized
Coefcients
Standardized
Coefcients t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1
(Constant)
Coherence
Mystery
Complexity
-0.607
0.051
0.337
0.590
0.056
0.013
0.018
0.023
0.054
0.342
0.478
-10.779
4.026
19.276
25.771
0.000
0.000
0.000
0.000
0.811
0.462
0.421
1.233
2.166
2.374
a. Dependent Variable: Preference

21
Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
DISCUSSION
In this paper, the components of the matrix of
preference were investigated and the effect of each
component on the preference was analyzed. According
to previous studies, Legibility as independent variable
was excluded due to a small effect on the prediction of
preference. Therefore, in this study of the remaining
three variables (complexity, cohesion and codication)
were evaluated. Results conrm the hypothesis of
this study: There is a relationship between preference
and three variables of coherence-complexity-mystery.
These independent variables predict 62.3 percent of
preference. Both complexity and mystery have a direct,
and strong correlation with the dependent variable.
Moreover, cohesion has a direct relation, but relatively
weak, with preference as dependent variable. There is
general agreement on the fact that complexity, mystery
and coherence are three important effective variables on
preference respectively.
In this study, complexity, with strong correlation
(r = 0.75), was the most important factor inuencing
preference toward building facades that is compatible
with previous studies (e.g., Herzog & Kropscott, 2004;
Tang, Sullivan, & Chang, 2014; Van der Jagt, Craig,
Anable, Brewer, & Pearson, 2014). Moreover, scholars
believe that the perceived complexity of buildings is an
important indicator of determining the attractiveness
of the building facades (Imamoglu, 2000; Rapoport,
1990; Stamps, 2004). Therefore, visual complexity
can improve the quality of a scene (Herzog & Shier,
2000). Moreover, through research, it was revealed that
complexity is as an important variable in appearance
(Berlyne, 1974). The number of perceptible elements
in a scene and the dramatic differences between them
are indicators for measuring visual complexity. Visual
complexity is related to the level of information that is
visible to the observer. In order to better understanding
of complexity, Gestalt’s theory helps with relating
visual stimuli of building facades to regular patterns and
creating a regular structure in the mind that provides a
complete understanding of the environment. Coherent
shape of the building facade and the patterns that exist
in the structural facades are some of the physical factors
that can be of importance in dening the space discipline;
In fact, with more complexity in the facade, the sense of
arousal in the observer is increasing. While, the pleasing
quality of the building facade has a reversed u-shaped
relationship with complexity, it indicates that the median
level of complexity is associated with maximum pleasure
and the level of high or low complexity is associated
with minimal pleasure (Crozier, 1974; Wohlwill, 1968).
However, some studies have revealed that there is a direct
linear relationship between complexity and pleasure
(Stephen Kaplan, Kaplan, & Wendt, 1972; Wohlwill,
1976). This contrasts come from a variety of factors,
such as the impact of familiarity of building facade on
complexity perception (Imamoglu, 2000). In general,
with respect to the relationship between complexity
and the preference, and the importance and priority of
complexity in preference among other variables, it is
recommended to avoid low and high levels of complexity
in design of building facades, which respectively leads
to boredom-indifference and turbulence-visual pollution.
After complexity, the second effective variable
recognized as mystery which is one of the qualities that
leads to more exploration in the environment. Mystery
requires meditation and reection in the surrounding
environment, as there is a lot of information that it
provides. Therefore, the design of building facades
should contain levels of mystery to provide additional
information for the observer to encourage him to discover
through exploring the scene. Moreover, the positive
effect of mystery in predicting the preferences of urban
scape has been conrmed in previous study (Ikemi,
2005). After complexity and mystery, coherence is the
last variable that has an impact on the preference toward
building facades. However, compared to the decisive role
of complexity and mystery, the magnitude of this impact
is small. Meanwhile, in a meta-analysis of 11 studies,
Stamps (2004) has reported that among four components,
coherence has highest correlation with preference. In
current research the correlation between coherence and
preference was revealed weak which is compatible with
previous studies (e.g.,Van der Jagt et al., 2014). The weak
effect of coherence on building façade preference shows
that the overall organization of elements compared to the
other factors, such as complexity and encoding, is less
important in designing of building facades.

22
Memari, S. et al.
Fig. 4. Five Best Selected Building Facades from Left to Right
CONCLUSION
The creation of visual quality in urban space from the
perspective of aesthetics is one of the great goals to be
perused. This can be achieved through emphasizing the
aesthetic values in order to maintain sense of the place,
creating a physical and visual coherence, and creating
order and visual coordination across the street. Organizing
the scape is the most important concern in urban scape.
Identifying its positive points through the preferences
of people toward building facades can be considered as
constructive steps to reduce visual pollution in urban
scape. In summary, based on the results of current study,
the effective role of each variable including coherence,
complexity and mystery on preferences toward building
facades were conrmed. Accordingly, two factors
including complexity and mystery are signicant in
predicting the preferences of people. After considering
complexity and mystery, coherence is of importance
in preference. It is suggested as guidelines in design
of building facades to move forward in a qualitative
framework. For instance: 1. use complexity in design of
building facades through providing diversity of visual
elements and increasing attractiveness, 2. Utilize mystery
through the combination of elements at different levels
which leads to improvement of the level of information
transmission in order to make building facade interacting
positively and constructively with the observer. As a
result, building facades which are aesthetically rich in
qualitative values were attractive to citizens and create a
pleasant urban scape.
As mentioned in the theoretical framework section,
according to the Kaplan theory, individuals prefer the
kinds of environments and landscapes which meet two
basic needs: quick understanding- exploration. Based on
the results, complexity and mystery are two most key
factors affecting the visual preferences of individuals
toward building facades (Table 1) which are classied as
exploratory factors. Consequently, it can be concluded
that what makes the building be preferred in the citizen’s
perspective is more about cognitive involvement while
exploring them rather than perception and making sense
as quick understanding. Thus, existence of variety of
elements and diversity of visual factors in building
facades (i.e., complexity), which promise to provide more
information to the individual over time (i.e., mystery) are
predictor of building façade preference while coherence
as a quick understanding parameter is placed in the next
priorities.
Transformation of qualities such as complexity
and mystery to guidelines in design of building facades
requires the provision of strategies that are in line with
the implementing rules as physical elements. This study
shed light on identifying the priority of the preferred
parameters in design of building facades. Future studies
should be organized in order to provide design strategies
consistent with the varaibles which are indicated to be
effective in preference. Specically, according to the
result of current study, subsequent studies should focus
on parameters of cognitive involvement and exploration,
including complexity and mystery. As a result, in those
studies building facade will not be considered merely
as a two-dimensional surface but as a potential scene
to understanding the deep layers of perception. Prior to
the identifying practical factors in the systematic design
of building facades, rst it is essential to determine the
factors of preference (which is the aim of current study)
and then the visual factors (proposed research gap for

23
Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
future studies). Although the identication of effective
factors in the Kaplan matrix on preferences, does not
directly contribute to design of building facades, but
it can facilitate the way for proper understanding of
the visual factors of preferred building facades that
can be explored in future studies. In fact, the factors of
preference matrix for execution in practice need to be
transformed into visual factors such as color, material,
form, and etc. Investigating the relationship between
these visual factors and preference can provide designing
solutions for successful urban scape. Therefore, in order
to further exploring the effective factors of the Kaplan
preference matrix, subsequent studies should determine
the visual factors associated with each factor in preference
matrix which lead to introduce the visual characteristics
of preferred building facades. Moreover, according to
the literature, other variables can affect the preference
too. Gender and other demographic information could
be other effective independent variables on preference
which should be investigated in the future studies.

24
Role of Kaplan’s Preference Matrix in the assessment of Building façade
REFERENCES
Abbasalizadeh Rezakolai, S., Samadi, D., &
Tabatabaian, M. (2015). Analysis of Persian Gardens
Using Kaplan’s Landscape Preference Theory (Case
Study: Fin Garden, Shazdeh Mahan Garden, Eram
Garden & El Goli Garden). Iran University of Science
and Technology, 25(1), 6–20.
Bell, S. (2012). Landscape: Pattern, Perception and
Process. Routledge.
Berlyne, D. E. (1974). Studies in the New Experimental
Aesthetics: Steps Toward an Objective Psychology of
Aesthetic Appreciation. Hemisphere.
Carmona, M., & Tiesdell, S. (2007). Urban Design
Reader. Routledge.
Crozier, J.B. (1974). Verbal and Exploratory
Responses to Sound Sequences Varying in Uncertainty
Level. Studies in the New Experimental Aesthetics, 27–
90.
Falk, J.H., & Balling, J.D. (2010). Evolutionary
Inuence on Human Landscape Preference.
Environment and Behavior, 42(4), 479–493. http://doi.
org/10.1177/0013916509341244
Galindo, M.P., & Hidalgo, M.C. (2005). Aesthetic
Preferences and the Attribution of Meaning:
Environmental Categorization Processes in the Evaluation
of Urban Scenes. International Journal of Psychology,
40(1), 19–26.
Gifford, R. (2007). Environmental Psychology:
Principles and Practice. Optimal Books Colville, WA.
Gimblett, H. R. (1990). Environmental Cognition:
The Prediction of Preference in Rural Indiana. Journal of
Architectural and Planning Research, 222–234.
Gjerde, M. (2011). Visual Evaluation of Urban Street
Scapes: How Do Public Preferences Reconcile with those
Held by Experts? URBAN DESIGN International, 16(3),
153–161. http://doi.org/10.1057/udi.2011.10
Herzog, T.R. (1989). A Cognitive Analysis of
Preference for Urban Nature. Journal of Environmental
Psychology, 9(1), 27–43.
Herzog, T.R., & Kropscott, L. S. (2004). Legibility,
Mystery, and Visual Access as Predictors of Preference
and Perceived Danger in Forest Settings without
Pathways. Environment and Behavior, 36(5), 659–677.
Herzog, T.R., & Shier, R.L. (2000). Complexity, age,
and Building Preference. Environment and Behavior,
32(4), 557–575.
Ikemi, M. (2005). The Effects of Mystery on
Preference for Residential Facades. Journal of
Environmental Psychology, 25(2), 167–173.
Imamoglu, Ç. (2000). Complexity, Liking and
Familiarity: Architecture and Non-Architecture Turkish
Students’ Assessments of Traditional and Modern House
Facades. Journal of Environmental Psychology, 20(1),
5–16. http://doi.org/10.1006/jevp.1999.0155
Kaplan, R., & Kaplan, S. (1989). The Experience of
Nature: A Psychological Perspective. CUP Archive.
Kaplan, S., & Kaplan, R. (1983). Cognition and
Environment: Functioning in an Uncertain World. Ann
Arbor, MI: Ulrich’s Google Scholar.
Kaplan, S., Kaplan, R., & Wendt, J. S. (1972). Rated
Preference and Complexity for Natural and Urban Visual
Material. Attention, Perception, & Psychophysics, 12(4),
354–356.
Lynch, K. (1960). The Image of the City (Vol. 11).
MIT Press.
Nasar, J.L. (1997). New Developments in Aesthetics
for Urban Design. Advances in Environment, Behavior
and Design, 4, 149–193.
Ode, Å., & Miller, D. (2011). Analysing the
Relationship Between Indicators of Landscape
Complexity and Preference. Environment and Planning
B: Planning and Design, 38(1), 24–40.
Paxton, J. (2006). The Preference Matrix as a Course
Design Tool. Proceedings of the 6th Baltic Sea Conference
on Computing Education Research, 124–127. Retrieved
from http://dl.acm.org/citation.cfm?id=1315826
Pazhouhanfar, M., & Mustafa Kamal, M. S. (2014).
Effect of Predictors of Visual Preference as Characteristics
of Urban Natural Landscapes in Increasing Perceived
Restorative Potential. Urban Forestry and Urban
Greening, 13(1), 145–151. http://doi.org/10.1016/j.
ufug.2013.08.005
Porteous, J.D. (2013). Environmental Aesthetics:
Ideas, Politics and Planning. Routledge.
Rapoport, A. (1990). History and Precedent in
Environmental Design. Springer Science & Business
Media.
Reeve, A., & Simmonds, R. (2007). EVALUATING
COMMERCIAL SIGNS IN HISTORIC STREETSCAPES :
the Effects of the Control of Advertising and Signage on
User’s Sense of Environmental Quality. Adriana Araujo
Portella Supervisors, (July).
Rosenthal, R., & Rubin, D.B. (1986). Meta-analytic
Procedures for Combining Studies with Multiple Effect
Sizes. American Psychological Association.
Salingaros, N.A. (2003). The Sensory Value of
Ornament. Communication & Cognition.
Sanoff, H. (1991). Visual Research Methods in
Design, Department of Architecture, School of Design

25
Armanshahr Architecture & Urban Development, 10(20), 13-25, Autumn 2017
and Environment, North Carolina University. Van
Nostrand Reinhold, New York.
Stamps, A.E. (2004). Mystery, Complexity,
Legibility and Coherence: A Meta-analysis. Journal
of Environmental Psychology, 24(1), 1–16. http://doi.
org/10.1016/S0272-4944(03)00023-9
Tang, I.-C., Sullivan, W.C., & Chang, C.Y.
(2014). Perceptual Evaluation of Natural Landscapes:
The Role of the Individual Connection to Nature.
Environment and Behavior, (138). http://doi.
org/10.1177/0013916513520604
Ulrich, R.S., Simons, R.F., Losito, B.D., Fiorito,
E., Miles, M.A., & Zelson, M. (1991). Stress Recovery
During Exposure to Natural and Urban Environments.
Journal of Environmental Psychology, 11(3), 201–230.
http://doi.org/10.1016/S0272-4944(05)80184-7
Van den Berg, A.E., Koole, S.L., & Van der Wulp,
N.Y. (2003). Environmental Preference and Restoration:
(How) Are they Related? Journal of Environmental
Psychology, 23(2), 135–146. http://doi.org/10.1016/
S0272-4944(02)00111-1
Van der Jagt, A. P. N., Craig, T., Anable, J., Brewer, M.
J., & Pearson, D.G. (2014). Unearthing the Picturesque:
The Validity of the Preference Matrix as a Measure of
Landscape Aesthetics. Landscape and Urban Planning,
124, 1–13.
Wohlwill, J.F. (1968). Amount of Stimulus Exploration
and Preference as Differential Functions of Stimulus
Complexity. Attention, Perception, & Psychophysics,
4(5), 307–312.
Wohlwill, J.F. (1976). Environmental Aesthetics:
the Environment as a Source of Affect. Behavior
and the Natural Environment, 1, 37–86. http://doi.
org/10.1007/978-1-4684-2550-5
Yang, B.E., & Brown, T.J. (1992). A Cross-cultural
Comparison of Preferences for Landscape Styles and
Landscape Elements. Environment and Behavior, 24(4),
471–507.