THE INFLUENCE OF DAYLIGHT ON NUMBER OF PATRONAGE TO
SHOPPING COMPLEX
AHMAD FARIHAN BIN SUDIRMAN
UNIVERSITI TEKNOLOGI MALAYSIA
THE INFLUENCE OF DAYLIGHT ON NUMBER OF PATRONAGE TO
SHOPPING COMPLEX
AHMAD FARIHAN BIN SUDIRMAN
A thesis submitted in fulfillment of the
requirements for the award of the degree of
Master of Architecture
Faculty of Built Environment
Universiti Teknologi Malaysia
MAY 2008
To my beloved family
ACKNOWLEDGEMENTS
Thank you Almighty Allah s.w.t for the blessings and guidance. I wish to
express my sincere appreciation to my main thesis supervisor, Assoc. Professor Dr.
Nor Haliza Madros, for encouragements, guidance, words of wisdom and above all,
for having faith in me. I am also very thankful to my co-supervisor, Assoc. Professor
Dr. Ibrahim Busu for his guidance and advice. Without their continued support and
interest, this thesis would not have been the same as presented here.
I would like to dedicate my undying gratitude to Kasteriya for your support
and assistance, my sister Ili for your perseverance in editing this thesis and my
beloved friends; Syukri and Daniel for kind advices and your faith in me. My sincere
appreciation also extends to all my colleagues and others who have provided
assistance at various occasions. Unfortunately, it is impossible to list all of them in
this limited space. I am grateful to all my family members.
ABSTRACT
The research explores the effects of daylight components in the interior of
shopping complex on influencing the number of patronage. The research objective is
to show that shopping complexes with more daylight attract more patronage. The
research hypothesis is that commercial buildings with more daylight components will
have more patronage or customers. The research began with a building framework
that functions as the structure for the building selection. A building inventory was
formed to assist in the building selection. Prior to the building framework, topics
such as definition of shopping complex, basic benchmarking, factors affecting
patronage and lighting was covered. Based on these research, Subang Parade and
Summit USJ were chosen as case studies. Selected shopping complexes with similar
characteristics and attributes that bear the controlled variables or factors that could
affect people to come to shopping complexes other than light was selected and then
compared with the one and only variable left which was light. This was based on the
fact that light affects human behaviors. Data collected for this research were
luminance level and patronage count. The research found that shopping complex
with daylight components had higher patronage count compared to shopping
complex with no daylight component. It is hoped that this research would contribute
to the awareness on the value of daylight in buildings especially in shopping
complexes in Malaysia.
ABSTRAK
Kajian ini dibuat untuk mengkaji kaitan komponen cahaya siang di dalam
gedung membeli-belah terhadap jumlah pengunjung yang mengunjungi bangunan
tersebut. Objektif kajian adalah untuk menunjukkan bahawa gedung membeli-belah
yang mempunyai komponen cahaya siang yang lebih besar di ruang dalamannya
mampu menarik lebih ramai pengunjung. Hipotesis kajian ini adalah gedung
membeli-belah yang mempunyai komponen cahaya siang yang lebih tinggi mampu
menarik lebih ramai pengunjung. Kajian bermula dengan membuat satu rangka
penyelidikan bangunan yang berfungsi sebagai struktur untuk pemilihan bangunan
kajian. Inventori bangunan telah dibuat untuk membantu pemilihan bangunan kajian.
Sebelum rangka penyelidikan bangunan dilakukan, beberapa topik penting telah
dikaji seperti definasi gedung membeli-belah, asas tanda aras, kajian terhadap faktor
yang mempengaruhi pengunjung ke gedung membeli-belah, dan faktor yang
mempengaruhi pengcahayaan. Berdasarkan penyelidikan yang telah dibuat, Subang
Parade dan Summit USJ telah dipilih sebagai kajian kes. Kajian ini hanya memilih
gedung membeli-belah yang memiliki ciri-ciri yang sama untuk dibandingkan.
Perbezaan antara bangunan yang dipilih hanyalah sistem pengcahayaan. Data yang
akan diambil adalah kadar pengcahayaan dan bilangan pengunjung. Penemuan kajian
ini menunjukkan bahawa gedung membeli-belah yang memiliki komponen cahaya
siang yang lebih tinggi mampu menarik lebih ramai pengunjung. Adalah diharapkan
kajian ini dapat menyumbang kepada kesedaran terhadap nilai cahaya siang di dalam
bangunan terutamanya gedung membeli belah di Malaysia.
TABLE OF CONTENTS
CHAPTERS
1
TITLE
PAGE
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENTS
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xi
LIST OF FIGURES
xiii
INTRODUCTION
1
1.0
Research background
2
1.1
Scope of research
3
1.2
Research hypothesis
3
1.3
Research aim and objectives
4
1.4
Research questions.
4
1.5
Research assumptions
5
1.6
Research organization
5
7
2
THE REVIEW OF LITERATURE
2.0
Introduction
7
2.1
10
The relation of the human being towards
light.
2.11
The relation of human behaviour towards
10
light
2.1.2
The relation of the human psychology
15
towards light.
2.1.3
The relation of the human physiology
16
towards light.
2.2
The Relation of Light and Commercial
20
Buildings
2.3
3
Conclusion
24
RESEARCH METHODOLOGY
25
3.0
Introduction
25
3.1
Research overview
26
3.2
Building framework
29
3.2.1
Definition of shopping complex
30
3.2.2
Factors affecting lighting
31
3.2.3
Factors affecting patronage
31
3.2.4
Basic benchmarking
33
3.2.5
Building inventory
34
3.2.6 Building selection
44
3.3
Data collection
49
3.3.1
Review on lighting variable
51
3.3.1.1 Digital camera in image processing study
51
3.3.1.2 Concept of illumination in computer graphics
51
3.3.1.3 Image processing program review
54
3.3.1.4 Digital camera and luminance meter
59
comparison
3.3.2
Review on patronage count
73
3.3.3
Physical measurements
77
3.3.3.1 Condition and time for data collection
77
3.3.3.2 Research instrument
79
3.3.3.3 Patronage count
80
3.3.3.4 Luminance reading
82
3.4
Data analysis
82
3.4.1
Tabulation of patronage count and luminance
83
level
3.42 Comparison of data of Summit USJ and
83
Subang Parade
4
5
6
3.5
Pilot Study
84
3.6
Amendments on data collection
87
3.6.1 Amendments on patronage count
88
3.6.2 Amendments on luminance reading
91
3.7
92
Amendments on data analysis method
RESEARCH ANALYSIS
93
4.0
Introduction
93
4.1
Building description
93
4.1.1
Subang Parade
93
4.1.2
Summit USJ
98
4.2
Description of data
103
4.2.1
Subang Parade
104
4.2.2
Summit USJ
116
4.3
Daylight component analysis
130
BEHAVIORAL SURVEY STUDY
131
5.0
Introduction
131
5.1
Survey set up
131
5.1.1 Sampling and questionnaire design
131
5.1.2
Data collection
134
5.2
Survey finding and analysis
134
5.2.3
Conclusion
157
CONCLUSION AND RESEARCH
159
METHODOLOGY REVIEW
6.0
Introduction
159
6.1
Conclusion of research
160
7
6.2
Review of research methodology
160
6.3
Recommendation for future research
162
BIBLIOGRAPHY
165
LIST OF TABLES
TABLE NO.
TITLE
PAGE
3.1
Table showing building inventory checklist
36
3.2
Table showing anchor tenants of shopping complexes
38
3.3
Table showing type of lighting used at shopping
39
complexes.
3.4
Table showing rating of shopping complexes
40
3.5
Luminance level represented in each pixel that builds up
53
the image above
3.6
Mixed background readings – Set 1
62
3.7
Mixed background readings – Set 2
63
3.8
Dark background readings – Set 1
64
3.9
Dark background readings – Set 2
65
3.10
Data Filtering for Red Set
67
3.11
Data Filtering for Blue Set
68
3.12
Data Filtering for Green Set
70
3.13
Data Filtering for Yellow Set
71
3.14
Overall background readings
72
3.15
Table showing luminance level of each pixel that builds
87
up the picture
4.1
Table below indicates luminance value of Subang Parade
111
– 1st floor
4.2
Table below indicates luminance value of Subang Parade
– Ground floor and lower ground floor.
112
4.3
Pattern of light distribution at 1st floor of Subang Parade
113
4.4
Pattern of light distribution at ground floor and lower
114
ground floor of Subang Parade.
4.5
Table showing patronage count for Subang Parade
116
4.6
Table showing patronage count for Summit USJ.
124
4.7
Table showing pattern of light distribution for Summit
126
USJ.
4.8
Table showing pattern of light distribution for Summit
127
USJ.
4.9
Table showing patronage count for Summit USJ.
128
4.10
Table showing patronage count for Summit USJ.
129
5.1
Table showing survey on factors that affect patronage in
133
Subang Parade
LIST OF FIGURES
FIGURES NO.
2.1
TITLE
Diagram showing relation of topics discussed in the
PAGE
9
review
2.2
Diagram showing relation between light and work
13
3.1
Table showing organization of the research
28
methodology
3.2
Table showing rating system by Darling (2004)
35
3.3
Table showing retail trade analysis of Waupaca
46
district.
3.4
Map showing population distribution of Klang Valley
47
3.5
Map showing location of shopping complexes within
48
Klang Valley
3.6
Map showing location of Subang Jaya & schedule of
49
population distribution.
3.7
An image with a resolution of 1375 x 1402 pixels
52
3.8
Illustration on how luminance reading is taken using
54
a luminance meter.
3.9
Lux reading versus digital camera mean
72
3.10
Infodev counting process.
75
3.11
Infodev’s horizontally located and vertically located
76
counting sensors.
3.12
Hourly global illuminance for Klang Valley,
78
Malaysia
3.13
Handheld manual counter used to count patronage
80
3.14
Counting stations (green) overlooking imaginary
81
count line (blue)
3.15
Plan showing checkpoints for patronage count of
81
Subang Parade.
3.16
Sidelit atria (left) and toplit atria (right)
84
3.17
Picture of lighting condition processed using PCI
85
Geomatica
3.18
Histogram showing frequency of different luminance
86
value
3.19
Table showing general properties of processed
86
picture
3.20
Counting stations (green) overlooking imaginary
89
count line (blue)
3.21
Plan showing checkpoints for patronage count of
90
Subang Parade.
3.22
Plan showing checkpoints for patronage count
90
Summit USJ.
3.23
Picture taken using fish eye lens gives a wider angle
91
(left) while common lense is limited to either a
horizontal or a vertical view only
4.1
Lower ground plan, ground floor plan and 1st floor
95
plan of Subang Parade.
4.2
Perspective showing front, right and left elevation of
95
Subang Parade
4.3
Location plan & openings to side-lit atrium of
96
Subang Parade
4.4
View of side-lit atrium from inside
97
4.5
Top-lit atrium at Subang Parade
97
4.6
Top-lit atrium at west wing of Subang Parade
98
4.7
Types of artificial light used at Subang Parade
99
4.8
Floor plans of Summit USJ- lower ground to second
100
floor
4.9
Floor plans of Summit USJ- third to fourth floor
101
4.10
Location plan & main entrance to Summit USJ.
101
4.11
Perspective showing left, right and front elevation of
102
Summit USJ
4.12
Incandescent downlights on typical floor and
103
concealed incandescent light at ground floor level.
4.13
Luminance level of pictures taken at Subang Parade –
104
1st floor
4.14
Luminance level of pictures taken at Subang Parade –
Ground floor
107
4.15
Luminance level of pictures taken at Subang Parade –
110
Lower ground floor
4.16
Plan indicating patronage count checkpoints of
Subang Parade.
115
4.17
Luminance level of pictures taken at Summit USJ –
117
3rd floor
4.18
Luminance level of pictures taken at Summit USJ –
119
2nd floor
4.19
Luminance level of pictures taken at Summit USJ –
120
1st floor
4.20
Luminance level of pictures taken at Summit USJ –
122
ground floor
4.21
Luminance level of pictures taken at Summit USJ –
123
lower ground floor
4.22
Plan indicating patronage count checkpoints at
129
Summit
5.1
Pie chart & schedule showing feedback for question
135
1
5.2
Pie chart & schedule showing feedback for question
136
2
5.3
Pie chart & schedule showing feedback for question
3
137
5.4
Pie chart & schedule showing feedback for question
138
4
5.5
Pie chart & schedule showing feedback for question
139
5
5.6
Pie chart & schedule showing feedback for question
140
6
5.7
Pie chart & schedule showing feedback for question
141
7
5.8
Pie chart & schedule showing feedback for question
142
8
5.9
Pie chart & schedule showing feedback for question
143
9
5.10
Pie chart & schedule showing feedback for question
144
10
5.11
Pie chart & schedule showing feedback for question
145
11
5.12
Pie chart & schedule showing feedback for question
146
12
5.13
Pie chart & schedule showing feedback for question
147
13
5.14
Pie chart & schedule showing feedback for question
148
14
5.15
Pie chart & schedule showing feedback for question
149
15
5.16
Pie chart & schedule showing feedback for question
150
16
5.17
Pie chart & schedule showing feedback for question
151
17
5.18
Pie chart & schedule showing feedback for question
152
18
5.19
Pie chart & schedule showing feedback for question
19
153
5.20
Pie chart & schedule showing feedback for question
154
20
5.21
Pie chart & schedule showing feedback for question
155
21
5.22
Pie chart & schedule showing feedback for question
22
156
CHAPTER 1
INTRODUCTION
The Malaysian shopping scene, especially within the Klang Valley district
has shown a rise in the development of shopping complexes due to the rise in
consumer demand as in rise in shopping trend (Selat, 1995). The main dilemma of
shopping complexes in Malaysia is seen in its declining life span serving as a
commercial centre which in the end needs to be revitalized and revived as quoted by
Zulkhafiz (2002) & Fauzan (2000). Shopping complexes tend to experience
decreasing amount of customers as it age turning it into white elephants. The Johore
shopping scenario for instance has witnessed several accounts of the failures of
shopping complexes such as Bestworld Plaza, Kemayan City and the recently opened
Lot 1 Shopping Centre. This stresses even more on the importance of looking into
factors that contributes to attracting customers to shopping complexes. According to
Tauber (1972) on different motives for shopping, he found out that people shopped
not merely out of necessity or a desire to satisfy a physical need but even includes
the need for social interaction outside of the home such as encounters with friends or
salesperson. Tan (1991) studied on shopping behaviours in Singapore and the
implications for property managers found that a friend’s perception of the shopping
centre could also contribute to retail patronage.
In finding the relation on factors that contributes to attracting customers to
shopping complexes, the subject of human reaction, light, and commercial building
2
has been selected as the main subject of the research. It is widely known that human
being react to light. Human being or within this context; the customers, is also
closely related to the subject of commercial buildings such as shopping behavioural
patterns and what triggers them. It is also known that light plays an important role in
affecting human behavioural pattern and psychological response. According to Ruck
(1989) on the subject of the construction of human perception, the quantity and the
quality of light received by the human visual receptors, which is the eyes, have a
direct influence on how people see things, which could contribute to one’s
impressions of an interior by giving character and atmosphere. Research done by
Sudirman (2001) regarding human perception towards the usage of daylight in
shopping complexes, shows that shopping complexes with higher degree of daylight
usage evokes positive feelings/emotions in building users within its interiors
compared to shopping complexes with less daylight usage. The research would like
to look whether daylight affects the number of customers in a shopping complex.
1.0
Research background
The rise of shopping complexes in Malaysia poses a threat to the
environment. It is feared that without proper study on the effects of these
developments towards the environment, a surplus of shopping complexes might arise
and this will give a negative impact to the environment. This scenario would lead to
numerous environmental issues such as a rise in energy demand as to operate
buildings, rise in building material and even the urban heat island phenomena. Rise
in energy demand occurs as these buildings operate. Common practice of mechanical
ventilation and artificial lighting contributes to demand in energy. The rise will also
increase the urban heat island phenomena as more shopping complexes are built.
Furthermore, if the shopping complex cease to operate and left unused, the vacant
building will still continue to contribute to the urban heat island effect.
3
1.1
Scope of research
The research would look into the affects of daylight component in
commercial building on number of customers. The research should reflect the
shopping complex development scenario of Malaysia. Therefore, the research should
include samples of shopping complexes throughout Malaysia.
However, the reseach has selected Klang Valley as the extent of research
field. Klang Valley has been chosen as the research field because it has the largest
amount of shopping complexes (Kamiso & And, 2004). The research will look into
the basic dimensions, which determine retail patronage. The research will also look
into different motives of shopping that explains why people go to shopping
complexes to work out these variables. After verifying these variables, the researcher
will select shopping complexes with the most similar characteristics and attributes
that bear the controlled variables (factors that could affect people to come to
shopping complexes other than light) to then compare the one and only variable left
which is light.
1.2
Research hypothesis.
Commercial buildings with more daylight components will have more
patronage/customers. This ideology is based on the fact that light affects human
behaviour.
4
1.3
Research aim and objectives.
The main objective of the research is to demonstrate that commercial
buildings with higher components of daylight in its interior attract more customers.
The research is crucial especially to individuals that are connected to the commercial
business such as property owners, property managers and shareholders to name a
few.
The aim of the research is to promote awareness on proper check and balance
between shopping complex development and the environment to avoid a surplus in
shopping complexes. Usage of daylighting in shopping complexes could lessen and
save energy consumption used to operate artificial lighting. A better understanding of
the proper application of daylighting strategies in shopping complexes in Malaysia
could benefit both developers and customers.
1.4
Research questions.
In achieving the objective of the research, one must ask how to work things
out as in how to carry out the required actions and methods. Some research questions
have been identified as a mean of aid to accomplishing the research objective. They
consist of:
i.
What are other contributing factors that could affect people to come to
shopping complexes other than light?
ii.
Do commercial buildings with higher daylight components in its
interior attract more customers?
5
The main intention of the research is to investigate the relationship between
the usages of daylight in the interiors of commercial buildings on its capability to
attract more customers. It is hoped that better understanding and application of
daylight would contribute to more retail patronage.
1.5
Research assumptions
(a) The outdoor illuminance reading is constant from 11am to 2.30 pm (Zain,
2001). The selection of timeframe will be discussed in chapter 3.3.3.
(b) The affects of daylight towards Malaysian is as equivalent as of those
from temperate countries. This is to substantiate the use of journals and
research done in temperate countries on affects of daylight towards
human being behaviour.
1.6
Research organization.
The thesis is organized in 6 chapters. Chapter 1 will discuss on the
introduction of the research. Chapter 2 reviews the literature on the relation of the
human being towards light, and the relation of light and commercial buildings. The
review on the relation of the human being towards light is broken down to three
categories which consist of the relation of light towards human behaviour, human
psychology and human physiology. This is to illustrate and fortify the statement that
light affects human being.
6
Chapter 3 discusses on the research methodology. The chapter discusses on
how the study will be carried out. It explains the stages of the methodology which
includes, building framework, data collection, pilot study and the analysis method.
The building framework will discuss on shopping complex definition, factors
affecting patronage and lighting and basic benchmarking. These studies are done as
to substantiate the building selection.
Chapter 4 will discuss on the research analysis. Chapter 5 discusses on
behavioural survey study. The final chapter which is Chapter 6 will discuss on the
conclusion and recommendations for future research.
CHAPTER 2
THE REVIEW OF LITERATURE
2.0
Introduction
Numerous researches have been done between lighting and commercial
building. However, most researches usually highlight the topic of energy savings and
how daylighting helps reduce energy cost. This is due to the fact that artificial
lighting consumes 50% of energy consumption of commercial and industrial
buildings (Bouchey, 2002) and savings can be achieved by integrating daylight
strategies (Veitch, 1997, Thomas, 1992, Henry, 1990, Cooke, 2004). Daylight has
been closely related to energy efficiency in commercial buildings (Serra, 1996,
McHugh, 1998, Helms, 1991, Azni Zain, 2000). According to Digert (1999) in his
research on the development and effects of advanced optical daylighting systems on
commercial buildings, the usage of daylighting technologies in commercial buildings
can save up to 310 billion kWh in illumination cost annually. Park (2004) in his
research on an illuminance ratio prediction method for daylighting control of
buildings also mentioned about achieving energy efficiency by using windows to
control solar radiation. The soaring urge for alternative energy source due to the high
consumption on energy and depletion of fossil fuel only heightens the importance of
such research. There are numerous researches done within the context of energy
efficiency in commercial buildings such as done by Katz (2005), Wilson (2001) and
Cooke (2002). Apart from energy efficiency; much research has been done on the
8
effects of light towards human factors such as productivity, physiology and
psychology as revealed by Boyce (2003), Helms (1991), Sucov et.all. (1975),
Hathaway (1987), Shepherd et.all. (1992), Cawthorn (1991 ) and Wurtman (1975).
The literature review will address three main subjects that consist of the
human being, light and commercial building. The relation of these three subjects will
be discussed in this chapter. The selection of these subjects is based on the premise ;
if light affects human being in more than one way and if lighting plays a significant
role in commercial buildings, why can’t light (through lighting) affect patronage
(human being) of a commercial building (shopping complex)?. The relation of all
three subjects is shown in the Figure 2.1. The review will show that human being is
connected to light and light is also related to commercial buildings. However, the
connection between the effects on lighting in commercial buildings on human being
is absent.
The literature review will start off with reviewing researches that shows the
connection between human being and light. The aim is to reveal that human being is
closely related and affected to light (Guzowski, 1999). Next, the literature review
will look into the relation between light and commercial building. Reviews on
researches on light and commercial building is done to have a broader scope of data
and to show that light is closely related to commercial buildings 1 . The aim is to
reveal that most researches done are mostly hard science 2 not vice versa. 3 The
literature review will prove the lack of study done on the effect of lighting towards
human behaviour in commercial buildings. With this, the researcher would like to
1
The researcher felt that it is important to broaden the literature review scope to commercial buildings
as this will help to build the case and to later show that light plays a significant role in commercial
building; which includes shopping complexes. Scoping down the review to shopping complexes will
result to lack of background study for the chances of finding the relation between light and
commercial building is higher compared to only shopping complexes.
2
Hard science is a term which often is used to describe certain fields of the natural sciences, usually
physics, chemistry, and many fields of biology. The hard sciences are said to rely on experimental,
quantifiable data or the scientific method and focus on accuracy and objectivity. (Wikipedia,2006)
3
The literature review will show that most researches done between lighting and commercial
buildings are mostly in relation to energy efficiency and technical lighting advancements.
9
point out the research gap within the context of light and commercial building; thus
justifying the need of the research.
The literature review is divided into two sections, which consist of the
relation of the human being towards light, and the relation of light and commercial
buildings (refer Figure 2.1). The review on the relation of the human being towards
light is broken down to three categories which consist of the relation of light towards
human behaviour, human psychology and human physiology. This is to illustrate and
fortify the statement that light affects human being.
Light
Human
being
Figure 2.1
Commercial
buildings
Diagram showing relation of topics discussed in the review
10
2.1
The relation of the human being towards light.
Human react to its environment with the aid of sense organs; also known as
the five senses such as touch, taste, smell, sight and sound. Light plays a significant
role in stimulating the sense of sight. The relation of human being towards light is
divided to three segments that consist of the relation of human behaviour towards
light, the relation of the human psychology towards light and the relation of human
physiology towards light.
2.1.1
The relation of human behaviour towards light.
According to Steffy (1990) lighting plays a significant role in the human
behaviour. Steffy (1990) stated that lighting affects the human sensory response,
desired impressions, expectations and subjective impressions (visual clarity,
spaciousness, relaxation, and sense of privacy). John Flynn as quoted by Gordon
(2003) pointed out that changing patterns of brightness contrast would result to
change in the strength of visual stimuli that will alter the impression of space.
Lighting also has the power to direct activity. Taylor and Sucov (1975) explored the
effect of lighting on the choice of which passageway people would use. They found
that the more brightly lit passage was the one that was used by most people.
According to Lam (1977) the presence of sunlight provides clues about threedimensional form and orientation in addition to indicating the state of the weather.
DiLouie (1995) also suggested that effective lighting is capable of creating a safer
environment. Sanders et all (1974) measured the effect of illuminance and light
distribution on the noise produced by a group of people talking whilst waiting in an
assembly room. They found out that low, uneven illuminance pattern was associated
with less noise than a higher, more even illuminance pattern. Miller et all (1998)
studied on the effects of maximising sunshine as a light source in the customer
service center of the Sacremento Municipal Utility District. One hundred and fifty
11
six employees were surveyed or interviewed about their impressions and experiences
with the lighting and they were generally quite satisfied with the appearance of the
lighting in the open offices and more than half believed the lighting was better than
similar workspaces in other buildings. This proves that higher usage of daylight
evoked positive perceptions in human being.
There have been several researches done in the field of education with
regards to the aspect of light and how it affects students. In a study done by
Innovative Design entitled analysis of the performance of students in daylit schools,
(Engineered Systems,1997), libraries with superior light resulted in significantly
lower noise levels. La Guissas and Perney (1974) observed the duration of attention
school children paid to a display card, when it was of the same luminance of the rest
of the room and when its luminance was much higher. They found that the attention
was much greater for the highlighted display. Research done in three schools in
California, Colorado and Washington used multivariate linear regression in gauging
the performance of 21000 students (Heschong, 1999). The outcome of the research
shows that classes with more daylight is 201% faster in solving mathematical papers,
26% faster in reading and understanding questions compared to other classes with
less daylight usage. Among all three, the class with the most daylight is ahead of
others in overall exam marks ranging from 7% to 18%. A research using light
spectrum as a variable to differentiate students in a classroom with full light
spectrum and a classroom with a conventional artificial lighting has been conducted
for two years in Alberta, Canada shows that students from the classroom with the full
light spectrum has the least absentees and an increase in the students well being
(health) compared to students in classrooms lit with conventional artificial lighting.
According to Thomas (1992), students transferred to a daylit school outperformed
their counterparts at an older school by 5% after one year and 14% after three years.
Discussing on effective illumination, DiLouie (1995) pointed out that effective
lighting is capable of decreasing absenteeism. Reports on the studies conducted by an
engineering firm in North Carolina which shows that schools who provided
daylighting make sense from a financial investment standpoint and improve student
performance (Engineered Systems, 1997). Hale (2000) discusses on the benefits of
daylighting systems to improve the efficiency of a school facility. Through the
12
correlation between the use of daylighting and student performance on standardized
tests, she discovered that daylighting brings positive effects on the learning
environment. According to Stewart (1981) and his research on attitudes of school
children to daylight and fenestration, he discovered that a significant proportion of
children choose to sit or work near windows, the chief factor being the amount of
daylight. Hathaway (1987) did a study on the effects of types of light on children
discovered that students under the high-pressure sodium vapour lamps had the
slowest rates of growth and development as well as the poorest attendance and
achievement. In an article entitled ‘Seeing Daylight’, Wilson (2000) found out that
students in classrooms with the most daylight learned roughly 25 percent faster than
students in classrooms with only electric light. This clearly shows how significant the
role of light in affecting human development.
Research on effects of luminous environments on workers productivity in
building spaces have shown that with an increase in the illumination level, accuracy
increases exponentially while time to perform decreases also exponentially (Ossama,
1997). Russell et al (1990) in his research regarding human response and variability
in the luminous environment indicates that there was no significant difference in
preferred illumination levels at different times of the day for reading or listening
tasks. However, there is evidence that preferred light levels are higher for reading
tasks than for listening tasks, an initial light level setting affects the preferred light
level, males prefer higher light levels than females and subjects who normally go to
sleep before midnight prefer lower light levels than those who stay up later. Thomas
(1992) also agreed that the usage of daylighting not only increases morale but also
increases workers job satisfaction and productivity. Loveland (2002) in his article
entitled daylighting and sustainability, he also agrees that lighting a space with
daylight can turn people to become more productive. According to DiLouie (1995)
on affective illumination, because some 85 percent of human impressions are visual,
improper quantity and quality of light can result in poor human performance.
Referring to a research done by the Building Owners and Managers Association,
DiLouie (1995) point out that better human performance can be achieved through
effective lighting. According to Boyce (2003), human performance can be enhanced
by understanding the relationship between light and work (refer Figure 2.2)
13
Figure 2.2
Diagram showing relation between light and work 4
Daylight also has the ability to encourage people to meet and gather in different ways
(Guzowski, 1999). Human social connections can be achieved with the aid of
daylight. She wrote that people gather in places with distinct qualities of light; in a
warm climate, people might pause under the dappled light of a tree-lined plaza; in a
cold climate, they might sit in a pool of warm sunlight from a south-facing window.
Architect Christopher Day as quoted by Guzowski (1999) argues that: “To quite a
large extent how people meet is supported or hindered by the environment.” This
4
Boycs, Peter.R, “Human Factors In Lighting – Second Edition” London & New York: Taylor &
Francis, 2003, pg. 124.
14
reflects back to the type of places and particularly what “places of light” you are
drawn to for different types of social interactions. Professor J. Stephen Weeks of the
University of Minnesota as quoted by Guzowski (1999) distinguishes between “ the
place for one, the few and the many.” The place of light for one is an intimate
experience such as the reading carrels at the Exeter Library designed by Louis Kahn.
The places of light for the few refers to small communal activities that might contain
pockets or pools of light and shadow that gather and hold several people such as
Tadao Ando’s Soseikan Tea House that uses low horizontal windows to define a
space of light for the master of the tea ceremony and the seated participant. The
places of light for the many unify and draws a larger community which is applied at
the gallery/reception area of the Weisman Art Museum by Frank Gehry which
defines a volume of light that surrounds the visitors and provides visual connections
to the Mississippi River, Minneapolis skyline and larger community.
Guzowski (1999) also suggest that daylighting supports or undermines social
hierarchies and power structures. Rosalyn Lindheim as quoted by Guzowski (1999)
states that daylight can be equated with power: “The location of the secretarial office
is routinely predictable: the boss occupies the outer office with the windows and
views; the support staff is clustered in the interior.”
Daylighting also has the
capability to encourage people to participate in and interact with their social, built
and natural environment. As Diane Ackerman explains in Guzowski (1999) on her
book entitled A Natural History of the Senses: “Even people who have been blind
since birth are greatly affected by light, because, although we need light too see, light
also influences us in subtle ways. It affects our moods, it rallies our hormones, it
triggers our circadian rhythms”. Research done by Innovative Design discovered that
full-spectrum lighting induced more positive moods in students (Engineered
Systems,1997) while Hollwich (1977) as cited by So (1998) discovered that an
increase in illumination level could increase hormone production. DiLouie (1995)
pointed out that effective lighting is also capable of reducing errors, improving
morale and help create mood.
15
Energy efficient lighting is also capable of producing positive effects in
occupants. Research by Veitch and Newsham (1997) on lighting quality and energy
efficiency effects on task performance, mood, health, satisfaction and comfort shows
that parabolic-louvered luminaries provide better verbal-intellectual and clerical task
performance than recessed luminaries. The research revealed that verbal-intellectual
task performance and visual performance were better under electronic ballasts than
magnetic ballast, regardless of lighting systems.
2.1.2
The relation of the human psychology towards light.
So (1998) in his research on indoor lighting design incorporating human
psychology found that light affects the human being psychologically. In a study done
by Innovative Design entitled analysis of the performance of students in daylit
schools, (Engineered Systems,1997), full-spectrum lighting induced more positive
moods in the students. Ruck (1989) and Hughes (1983) agreed that the illuminated
environment acts as a vital role in shaping our mood, reactions and even
psychological well being (Madros, 1998). Katz (2005) and his research on daylight
harvesting technologies found that daylighting is capable of improving the human
morale. According to Loveland (2002) on the topic of daylighting and sustainability,
people feel happier in a space lit with daylight. Monotony and uniformity in the
distribution of light in a building should be avoided for it would contribute to the
perception of gloom (Shepherd, 1992).
Research shows that among other factors, lights play an important role in
affecting and influencing human psychologically.
Human perception and its
behavioural pattern; when positioned within an enclosed space tend to change due to
light. According to Flynn (1972), lighting has the capability to influence ones
subjective impression or perception. In other words, light can be manipulated to
control or direct peoples actions. The fact that human being responds to light might
16
be due to the vast properties of light itself. The existence of light has been proven to
project positive effects in human being. According to Aktiengese Iisschaft (1995),
light plays a vital role in determining ones experience and perception. Negative
effects such as depressive moods are related to the usage of balanced light and the
interplay of shadow. The capabilities of light in influencing the human perception
might suggest why people tend to gather in brightly lit spaces compared to dark
spaces. The ability of light in influencing occupant’s perception of appearance of a
space as stated by Shepherd (1992) supports this idea. Dark spaces have also been
associated with crime. According to Henry (1990), muggers, vandals and burglars
are attracted to dark buildings, and avoid those that are well-lit. This suggests that
dark spaces encourage negative human behaviour. Light is also known for its
capability of creating different environment for a space in an instant as stated by
Svaboda (1985). The heightened feeling of pleasure achieved from good composition
that enhances clarity (Erhart, 1994) suggests why people opt for spaces with more
light. Erhart quoted from IESNA Lighting handbook as saying, “ Light profoundly
affects our feeling of well being, of awe and wonder, of mood, of comfort and
motivation”. The ability of light in evoking positive effects in the human being might
render the subconscious mind to respond to it; such as going to places with more
light instead of vice-versa without realising the act.
2.1.3
The relation of the human physiology towards light.
The fact that human well being and light is interrelated could be a
contributing factor to why the human being reacts and responses to light. For
example, radiant energy accepted through the eye or as it penetrates living tissue,
stimulates glandular response, metabolism, hormone development and the entire
autonomic system-respiration, heart action and even appetite (Birren, 1972). Steffy
(1990) stated that apart from vision, light is also capable of influencing hearing and
thermal sensation. Katz (2005) in his research on daylighting harvesting technologies
pointed out that daylighting helps satisfy the human needs for natural light, which
17
promotes various health and performance benefits. This statement is also supported
by Loveland (2002) where he pointed out that spaces that are lit with daylight is
capable of making people feel happier. According to Leslie (2003) in his article
entitled capturing the daylight dividend in buildings, he agreed that daylighting
supports human health and activities. Hollwich (1977) as cited by So (1998)
discovered that an increase in illumination level could increase hormone production,
in particular, the stress hormone cortisol. In a study done by Innovative Design
entitled analysis of the performance of students in daylit schools (Engineered
Systems,1997), students exposed to a full spectrum of light were healthier and
attended school 3.2 to 3.8 days more per year than comparative non daylit schools.
According to Lam (1977), the presence of sunlight satisfies a basic biological need.
In a study done by Innovative Design entitled analysis of the performance of students
in daylit schools, (Engineered Systems,1997), because of the additional vitamin D
received by the students in full-spectrum light, students had nine times less dental
decay and grew an average of 2.1 cm more over a two year period, than students
attending school with average light. Hathaway (1987) did a study on the effects of
types of light on children and found out that students under full spectrum fluorescent
with ultraviolet supplements developed fewer dental cavities and had better
attendance, achievement and growth and development than students under other
lights. Birren (1988) as cited by So (1998) stated that haemoglobin in the blood
could be increased by light and decreased under darkness that would lead to why
people normally feel sleepy under a dimmer environment. The presence of light
plays a significant role in determining human well being. Lack of exposure to
daylight and even sole dependency to artificial light could cause harm not only to
human but even other living beings. There is now clear evidence that incomplete or
unbalanced light could have hostile effects. A mouse or a man could not thrive if
exposed solely on mercury or sodium vapour light (Porter, 1977), which is widely
used as the main substance in artificial lighting. However, the problem of low
lighting conditions in buildings shouldn’t be easily resolved by using artificial
lighting such as fluorescent lamp illumination for it might cause several illnesses
such as asthenopia (Lindner, 1993). Kuller (1992) and his research on the impact of
fluorescent light on endocrine, neurophysiological and subjective indices of well
being and stress found out that fluorescent light of high illuminance may arouse the
central nervous system and that this arousal will become accentuated if the lamps are
18
of the ‘daylight’ type. He suggested that the practical implication might be that
people should not be exposed to fluorescent light of high illuminance for a prolonged
period of time. Artificial lighting such as fluorescent lamps for example shouldn’t be
used commonly for it poses negative effects towards human well being and
behavioural patterns.
Holmes (1975) stated that excessive brightness can impair vision and more
often cause real tiredness and complaint. According to Evans (1981), excessive
brightness ratios in the field of view should be avoided which suggests that the best
visual conditions are achieved in a uniform environment, but lack of change is
inconsistent with the natural capabilities and tendencies of people. He stated that one
of the strongest elements in the establishment of a sense of orientation and wellbeing is the presence of direct sunshine in buildings. Evans came to a point that
changing nature of daylight automatically and naturally responds to the need of the
body and mind for change of stimuli or mood. Evans also discussed on the need for
human body to be able to relate to its natural surrounding both physically and
mentally. He pointed out that aviators who lose contact with the horizon and the
exterior surrounding in adverse weather are subject to vertigo and must use
instruments to maintain level height. Wilson (1972) as quoted by Evans (1981)
reports on a study of hospital rooms that patients in windowless rooms experienced
an increase in stress levels and exhibited a doubling post-operation delirium cases.
Poor lighting impacts older adult by decreasing quality of life and independence, as
well as compromising safety. It is believed that light acts as an essential intervention
for Alzheimer’s disease (Noell et. all, 2002). Wotton (undated) in his research on the
visual environment and its contribution to the quality of life of the elderly; discussed
on the therapeutic effect of light. He stated that light has long been recognized as a
form of treatment for stress caused by the dark days of winter which affects the
quality of sleep of the elderly.
Evans (1981) states that ultraviolet ray that comes from daylight is essential
to human welfare. When the body is exposed to ultraviolet rays, there is a dilation of
the capillaries of the skin. In addition to a feeling of well being, there is a quickening
19
of the pulse rate and appetite, plus a stimulation of energy activity, which might
actually increase work output.
Begemann (1996) conducted a study on visual and biological responses of a
group of people in an office towards daylight and artificial light. The results show
that most people prefer to follow a daylight cycle instead of a constant level.
Prolonged exposure to artificial lighting such as the fluorescent lamp could
lead to diminished visual acuity occurring after lengthy periods of fatigue and stress,
manifest in terms of eyestrain, opthalmalgia, eye fatigue and headache; also known
as asthenopic. Lindner (1993) studied asthenopic complaints associated with
fluorescent lamp illumination and found out that it affect predominantly female, aged
20-30 years, and possess a higher than normal psychovegetative ability, diminished
power of concentration, enhanced light sensitivity in cases of flicker sensitivity and
reduced binocular and stereoscopic vision.
Iwata, Hatao and Shukuya (1994) set up a structural model for evaluation of
visual comfort in the daylit luminous environment with their objective, which is to
find a way to create a comfortable and ideally pleasant daylit luminous environment.
The results derived as a relationship between overall evaluation and sensory
responses in the hierarchical model suggests that one of the keys to designing a
comfortable lighting environment is to eliminate the darkness or the excessive
brightness which occupants feel on the desk.
20
2.2
The Relation of Light and Commercial Buildings.
Savings in energy consumption can be achieved by incorporating daylight in
lighting commercial buildings (Thomas, 1999, Madsen, 2002, McHugh, 1998,).
Numerous researches have been done to utilize and harvest the energy saving
benefits of daylighting (Digert, 1999). The depletion of fossil fuel which results to
the increase in energy costs, results to the rise in research within the field of
alternative energy. Some researchers turn to daylighting in hope of finding a solution
(Wilson, 2001). Electric lighting in commercial buildings costs ten percent of the
electricity used in the United States each year (Johnson, 2004). Bouchey (2002) cited
that artificial lighting accounts fifty percent of the energy consumption of
commercial and industrial buildings. Claridge (1994) in his research on benefits of
energy retrofits in commercial buildings; highlights on the potential of proper
lighting in energy conservation. Lockheed Martin manages to save seventy five
percent in its electricity cost after applying daylighting in their building (Bouchey,
2002). According to Johnson (2004), the America’s Department of Energy has
shifted their investment from photovoltaics to hybrid lighting since it yielded higher
energy gain. Sunlight collected from a parabolic mirror connected to optical fibres is
used to light buildings in hybrid lighting system (Muhs, 2004, Wiebusch, 2000).
Daylit commercial buildings are also capable of reducing capital costs by cutting on
glazing and minimising solar heat gain by carefully designing windows (Loveland,
2002). Some even suggest bringing in lighting audits and using daylighting in
commercial buildings as to cut energy consumption (Feldman, 2004). The increase of
research in daylighting strategies in commercial buildings also help in producing new
and cheaper methods of daylighting in buildings (ASHRAE, 2004). This is another
contributing factor on the rise of researches in energy conservation through
daylighting. Chirarattananon, (1996) in his research on daylighting applications in
commercial buildings in a tropical climate in Thailand
found that lighting of
buildings can be optimized and cooling loads can be minimized by using daylighting
through proper design of the building envelope. Research has also been done in
energy efficient lighting in Thai commercial buildings (Busch, 1993) in light of
reducing energy consumption cost. Lighting also plays a very important role in
increasing face value and adding aesthetic appeal. According to Henry (1990), façade
21
lighting would make the building more attractive resulting to a more valuable
building with more valuable renting space. In other words, the value of a building
can be increased with the use of lighting.
Apart from other factors that might contribute to why people go to shopping
complexes; the usage of light in building with higher light components could
subconsciously attracts customers as well. In a research conducted by the Heschong
Mahone Group in California on the effects of daylight towards retail sales, Wilson
(2000) in his article stated that daylighting was found to boost sales by an average of
40 percent with a 99 percent degree of statistical certainty. Pierson (1995) looked at
the advantages of increased light in commercial buildings in the United States and
found out that increased daylighting results in decreased absenteeism and fewer error
and defects. According to Loveland (2002) citing on reports by Business Week and
Fast Company, daylighting has been underscored as a factor in attracting and
retaining workers. Daylight benefits such as increased workplace productivity might
be the reason to why American retailers such as Walmart and Costco have
implemented daylight strategies decades ago.
According to Bean (1992), through surveys, many workers are still
dissatisfied with the quality of their artificial lighting, despite the fact that in many
cases, their lighting meets the basic requirements of the CIBS Code for interior
design. This suggests that higher degree of lighting doesn’t ensure human
satisfaction. Pierson (1995) looks at the advantages of increased light in commercial
buildings. Report done by the Rocky Mountain Institute concluded that increased
daylighting results in decreased absenteeism and fewer errors and defects; thus
increasing the productivity level of workers in commercial buildings. The report,
`Greening the Building and the Bottom Line,' which describes companies specific
gains in daylighting. Wilson (2000) reveals the results of a study in California that
natural light boosts human productivity in retail sales and school performance with
average increase is sales due to daylighting. Increased level of lighting in a building
doesn’t result to ultimate human satisfaction but the usage of daylighting has shown
positive effects towards human performance. In a research conducted in Lawrence
22
Berkeley Laboratory, University of California, Berkeley, CA 94720, U.S.A.
(Ne’eman et al, 2003) on office workers response to lighting and daylighting: issues
in workspace environments, they reported levels of importance and satisfaction
associated with lighting controls and other environmental conditions in workspaces
and how they relate to physical features of the building and selected sociodemographic characteristics. They found out that most respondents considered the
majority of their workspace conditions important and satisfactory. They even suggest
that careful integration of these lighting and related control technologies with worker
values and priorities is essential if potential benefits are to be realized.
Close (1996) introduced ways to optimise daylighting in high-rise
commercial developements in South East Asia by using computer programmes as a
design tool. He discovered that computer modelling offers opportunities for
comparing options and varying designs to meet requirements of different orientations
with different solar considerations. According to Serra (1998) both architecture and
we who inhibit are different by day and by night, there for it makes no sense to try to
imitate the effects of natural light with artificial light: the results will be mediocre.
Furthermore, he stated that it is difficult to combine the two kinds of light, due to
their different chromatism and the fact that when the eye is accustomed to natural
levels of light, it finds artificial light poor and gloomy, whereas at night it seems
ideal.
Collins et al (1990) did a research on evaluation of the role of luminance
distributions in occupant response to lighting indicated that occupant satisfaction
could be related to patterns of luminance, lighting characteristics and presence of
daylight in the office. Surveys by Ruys (1970) and Somner (1969) as indicated by
Evans (1981) stressed out the importance of human connection with daylight through
openings. Wells reported that in a study of office workers, 69 percent believed that
daylight provided a better quality of illumination than ‘artificial light’. Evans (1981)
also quoted on Pritchard (1964) suggesting that among factory workers in
windowless spaces, the level of complaint might be inversely related to the amount
of money the employee was making. According to Michel (1996) as quoted by Zain
23
(2000) daylight satisfies the psychological and physiological needs of the occupants
of a building leading to increased productivity in work places and proven to increase
academic performance of students in schools.
Veitch (1997) did a research on lighting quality and energy efficiency effects
on task performance, mood health, satisfaction and comfort concluded that energy
efficient lighting and good quality lighting can be compatible. She also found out
that parabolic-louvered luminaries provide better verbal-intellectual and clerical task
performance than recessed luminaries. Verbal-intellectual task performance and
visual performance were better under electronic ballasts than magnetic ballasts,
regardless of lighting systems. This shows that proper usage of lighting boosts task
performance in office workers. People also require not only good, comfortable task
lighting conditions, but a lit environment that is apparently ‘light’ and one that is
‘visually interesting’, and the level of these two conditions will vary depending on
the particular situation. (Loe, 1994)
Based on the review, it is fair to conclude that research regarding lighting and
commercial buildings is more concentrated on energy conservation and energy
efficiency. However, there is a lack of awareness in the use of biological lighting for
illumination that will help to sustain life (Birren, 1974). Research has shown that
light affects the human being and lighting plays a significant role in commercial
buildings. It is possible that light can affect the users of a commercial building.
Hypothetically, light should produce or induce the same effect of physiological,
psychological and behavioural change towards human being regardless of location. If
school children experience better result, better health and lesser absenteeism by
exposing them to daylight (Heschong, 2000), theoretically, users or patrons of a
shopping complex equipped with daylighting should reap the same positive benefits.
Research has shown that naturally lit buildings are more comfortable for human
occupation and produces positive influence on operating income, resulting in
increases in asset valuation (Katz, 2005). Patients in windowless hospital rooms
experience an increase in stress levels and exhibited a doubling post-operation
delirium cases (Evans, 1981). This suggests that deprivation of daylight could
24
promote negative effects on human being. If daylight gives countless health benefits
to human beings (Evans, 1981, Begeman, 1996), why should patrons of shopping
complexes deprived from it? The researcher felt that the lack of research in the
effects of daylight towards human being in shopping complexes is due to the fact that
the search of alternative energy and energy conservation is considered as a global
issue and of great priority.
2.3
Conclusion
The review in section 2.1 concluded that relation between human being and
light exists. Section 2.2 concluded that light is also related to commercial buildings.
However, most of the topic discussed on the relation between light and commercial
buildings points out the issue of energy savings. Moreover, no research has been
done on the effects of light towards patrons of a commercial building.
There is no literature at present that directly supports the hypothesis that
commercial
buildings
with
more
daylight
components
will
have
more
patronage/customers. However, research by Heschong (2003) regarding daylighting
and retail sales is the only connection between the effects of daylight components
towards patronage. The research focuses on the connection between skylighting and
retail sales. Heschong found out that Wal-Mart chainstores that has their building
equipped with skylight experienced an increase of up to 40% in gross retail sales
compared to Wal-Mart chainstores without skylight. Based on the literature review, it
is suggested that there is a possible connection between daylight components and
how it affects patronage. It is observed that most of the research regarding daylight
and the affects towards human behaviour or reaction is conducted abroad and not in
Malaysia. The research intends to study the affects of daylight towards he number of
patronage within the daylight condition in Malaysia.
CHAPTER 3
RESEARCH METHODOLOGY
3.0
Introduction
The research methodology is divided to four sections. These sections are:
(a) Building framework
(b) Data collection
(c) Pilot study
(d) Analysis method
The building framework functions as the structure for the building selection.
It is divided to two main subtopics which consist of building inventory and building
selection. Other topics that are discussed in this section includes:
(a) Definition of shopping complex
(b) Factors affecting lighting
(c) Factors affecting patronage
(d) Basic benchmarking
26
The objective of building inventory is to find similarity between buildings.
This is carried out with the help of a building inventory survey. The survey is created
with the help of a study on benchmarking for shopping complexes. The building
selection discusses on how the selection of building for the research is done. Prior to
the building selection, factors affecting lighting and factors affecting patronage are
discussed. Data collection section discusses data required for the research which
consist of luminance level and patronage count. In acquiring data for luminance
level, 4 studies is done. These studies clarifies the method of acquiring luminance
level. These studies will be further discussed in the data collection section. Next, the
pilot study is done to test the methodology opted and to detect any anomalies and
blind spots. This section ends with pilot study and amendments to the methodology.
The final section will discuss on the analysis method.
3.1
Research overview
The first task of the building framework is forming a building inventory. The
building inventory is used to assist building selection. However, the question of how
and what to be documented surfaced. This is due to the fact that no standard on
benchmarking shopping complexes exists unlike hotels, offices and schools.
Therefore, verification and selection of shopping complexes is done by defining the
term ‘shopping complex’ itself through literature review. Verifying buildings that
falls into the shopping complex category is important for this is the scope of the
research. Only buildings identified as a shopping complex will be used for the
research. Other building typologies will be ruled out. Shopping complex listings
provided by local authorities and municipalities helps the verification process.
However, some of the shopping complexes was not listed by local authorities
especially areas between the borders of each district which are usually considered as
grey areas. This complicates the process of selecting and gathering of shopping
complexes to be surveyed.
27
Next, a building inventory checklist is devised as to collect information of
shopping complexes for the building inventory. Therefore, a review on
benchmarking is done to get an overview on how to collect information and what
information is required for the building inventory. A rating system on downtowns
and shopping centres done by the Kansas State University (Darling,2004) helped to
form a building inventory checklist. The collected information will be used to form
an inventory of all the shopping complexes surveyed.
The building inventory is important to the research in properly selecting
buildings to be studied. The building inventory will show a list of shopping
complexes available within Klang Valley. The building inventory will then aid the
building selection. However, the issue of how many buildings to be studied surfaced.
The main dilemma of selecting buildings to be studied is to find two (or more)
buildings that are very similar to each other and what separates it apart is the lighting
system used. However, trying to find a pair of shopping complex that is very similar
to each other is very rare. Most shopping complexes are built very different from
each other. Even if it is possible to find more than one building that is highly similar
to each other, the second dilemma would be the limited ability of performing the
research. Selecting too many buildings to be studied would be beyond the ability of
the researcher. Selected buildings will be studied rigorously. Studies that consist of
picture taking and patronage count will be done throughout the entire building.
Therefore, the researcher was unable to select too many buildings to be studied.
28
RESEARCH
METHODOLOGY
Building
Framework
Definition
of shopping
complex
Factors
affecting
lighting
Factors
affecting
patronage
Basic
benchmarking
Building
inventory
Data
Analysis
Method
Data Collection
Review on
lighting
variable
Review on
patronage
variable
1. Digital camera
in image
processing
study.
2. Concept of
illumination in
computer
graphics.
3. Image
processing
programme
review.
4. Digital camera
& luminance
meter
comparison
study.
Physical
measurements
1. Condition
& time for
data
collection
2. Research
instrument
3. Patronage
count
4. Luminance
reading
Building
selection
Pilot Study
Amendments to
data collection
Figure 3.1
Amendments to
data analysis
Table showing organization of the research methodology
29
3.2
Building framework
This section is divided to two main subtopics which consist of building
inventory and building selection. The building inventory and the building selection is
discussed towards the end of this section. Prior to the building inventory and the
building selection, four topics are discussed:
(a) Definition of shopping complex
(b) Factors affecting lighting
(c) Factors affecting patronage
(d) Basic benchmarking
Klang Valley has been chosen as the experimenting ground for it has the
largest amount of shopping complex compared to other states throughout Malaysia.
The current commercial scene in Klang Valley supports this statement. Based on
market research and feasibility studies done by Raine & Horne International Zaki +
Partners Sdn Bhd, Selat (1995) in his report on trends of shopping complex
developments in greater Klang Valley towards 2005 stated that Klang Valley will
remain the fastest growing regional economy in Peninsular Malaysia. According to
Kamiso and Ang (2004) on their report on local retail industry gearing towards a
mini boom, shopping complexes listed under the Malaysia Mega Malls are all
located within the vicinity of Klang Valley which includes 1 Utama, Sunway
Pyramid, Suria KLCC, MidValley, Berjaya Times Square, Ikea, Ikano, The Curve
and Cineleisure. Half of the Malaysia Mega Malls have prepared themselves for
future extension of commercial space to accommodate the growing consumer needs
(Kamiso and Ang, 2004). This further validates the appropriateness of Klang Valley
as the experimenting ground.
30
3.2.1
Definition of shopping complex
The definition of the term ‘shopping complex’ according to McKeever
(1953), is defined as a group of commercial establishments planned, developed and
managed as a unit, with off-street parking provided on the property and related in
location, size and type of shops to the trade area that the unit serves generally in an
outlaying sub-urban area.
He also categorized types of shopping complex by functions, which consist of
three typologies:
(a)
Neighbourhood Centres – these centres provide for sale of daily
living needs (convenience goods). It needs 1000 families for support
and 5-10 acres for site area.
(b)
Community or Suburban Centres (or District Centres) – these centres
in addition to convenience goods and personal services, provide for
sale of soft lines (apparels etc.) and hard lines (hardware equipments,
etc.). It requires at least 5000 families for support and 10-25 (or even
more) acres of site area.
(c)
Regional Centres – it should have at least a department store for their
core and offer shopping goods in full depth and variety including
fashion items and house furnishings. It requires more than 100,000
people for support and a site area of at least 35 acres. It is also called
“one-stop-shopping”, meaning customer is able to do all kinds of
buying in just one place.
According to Northen (1977), shopping complex or retail premises can be
divided to 14 typologies. Northern defined the word ‘mall’ to describe a
pedestrianised shopping street almost certainly originated in North America in an
effort to convey a greater sense of space, quality and elegance than is normally
associated with arcade.
31
3.2.2
Factors affecting lighting
Factors affecting lighting are classified as independent variable. The
buildings selected for the study must have different application of lighting. This is
crucial as the study would like to compare patronage count of two near identical
shopping complex with different lighting application. The only concern for the
building selection is that one must have a combination of daylighting and artificial
lighting while the other building has to have lower component or even no daylight at
all. The assessment on the level of daylight used in a shopping complex is based on
visual assesment of the researcher towards available openings. Only luminance level
on daylight component is considered in the research. This reflects back to the scope
of the research which focuses on the effects of daylight towards the number of
customers in a shopping complex. Information on luminance level is reflected in
pictures taken using a digital camera that has been processed using an image
processing programme called ERDAS.
3.2.3
Factors affecting patronage
According to Webster’s Ninth New Collegiate Dictionary, the word
patronage means the support or influence of a patron. It can also be defined as
business or activity provided by patrons. According to Foss (undated) citing on
Reily’s Law on Retail Gravitation, attractiveness or ability of a centre to attract
customers is proportional to how big it is and how far it is from its competition.
Distance however has a greater impact than size.
Factors affecting patronage need to be made constant in order to study the
effect of different lighting applications towards the number of customers. However,
there are countless factors that attract customers to a shopping centre. This
32
complicates the study. Thus, an overview on the topic of factors that attract
customers should be done before any decision is made on how to select the building
for the study.
According to McKeever (1953), there are eight factors that make a good
shopping centre. They consist of research, location, site, layout, parking, structure,
tenants and management. There are several factors that might contribute to “why
people go to shopping centres” (Tan,1991). Through a series of in-depth interviews,
Tauber (1972) studied different motives for shopping and he found out that people
shopped not merely out of necessity or a desire to satisfy a physical need but
included the following:
•
Diversion- from the daily routine of life.
•
Self gratification- based on the buying process itself.
•
Learning about new trends- when visiting the store.
•
Physical activity- since an urban environment provides little opportunity to
exercise.
•
Sensory stimulation- such as handling the merchandise, trying it on etc.
•
Social interaction- outside the home such as encounters with friends or
salesperson.
•
Pleasure of bargaining or bargain hunting- as a means to make a wise
purchase.
Discussing on shopping behaviour and implications on property managers,
(1991) he stated that it would be useful to note the following eight basic dimensions,
which determine retail patronage:
•
General shopping centre characteristics (reputation in community, number of
stores)
•
Physical characteristics of the centre (décor, cleanliness, check out service,
ambience)
33
•
Convenience in reaching the centre (time required, access, parking)
•
Products offered (variety, dependability, quality)
•
Prices charger in the centre (value, special sales, image)
•
Sales personnel (courteous, informative, helpful)\advertising by the store
(informative, appealing, believable, appropriate image relative to customer
base)
•
Friends perception of the centre (well-known, liked, recommended)
In essence, there are countless factors that affects patronage of a shopping
centre. In order to keep factors that affect patronage constant, the researcher needs to
look for two (or more) samples of shopping complex that are identical. The only
factor that is different would be the lighting application. Therefore, the researcher
needs to look into other means of selecting building other than using the building
inventory.
3.2.4
Basic benchmarking
According to Webster’s dictionary (1986) a benchmark is defined as a point
of reference from which measurements may be made or something that serves as a
standard by which others may be measured.. According to Camp (1989), citing
David T. Kearns, benchmarking is defined as the continuous process of measuring
products, services and practices against the toughest competitors or those companies
recognized as industry leaders. Longmire (1993) stated that the word “benchmark”
and “benchmarking” is often misinterpreted as having the same meaning. In the
quality improvement lexicon, a benchmark is a “best-in-class” achievement. This
achievement then becomes a reference point or recognized standard of excellence
against which similar processes are measured. While benchmark is a measure,
benchmarking is a process of
measurement. It is a business process that can
34
contribute to achieving competitive advantage (Longmire , 1993, pg. 4). The review
on benchmarking helps to form the building inventory checklist which will be used
for the building inventory. This is to determine data to be collected and how to make
an inventory of shopping complexes.
3.2.5
Building inventory
A building inventory of shopping centres within the research area (Klang
Valley) is conducted. The objective of the inventory is to develop a list of shopping
complexes within Klang Valley and to collect physical data of the building using a
building inventory checklist. The building inventory will be used to facilitate the
building selection which will be further studied in the research.
The building inventory checklist is formulated with the help of reviews on
benchmarking and a shopping centre rating checklist done by Darling (2004). The
building inventory checklist requires information that describes the physical
attributes of the building. These information includes main anchorage, type of
lighting system used, rough estimation on opening, building material/structure and
number of floors. The building inventory checklist also incorporated the rating
system devised by Darling (2004). The rating system also helps in giving an
overview on the spatial condition of the shopping complex. The building inventory
checklist is also enclosed with pictures showing the interior and the exterior view of
the building surveyed to further help describe the building. Figure 3.2 represents the
rating schedule by Darling while Table 3.1 represents the building inventory
checklist used.
35
Figure 3.2
Table showing rating system by Darling (2004)
36
Table 3.1
Table showing building inventory checklist
BUILDING INVENTORY CHECKLIST
Data checklist
Building 1
Building 2
1. Anchorage
2. Type of lighting used
3. Rough estimation on opening
4. Building material/structure
5. Floors
6. Compactness
*Spaces are all fit together. The place
has a visual impact & well designed.
7. Compatibility
*Stores & offices are arranged in a way
that minimizes shopping time. One type
of business logically fits well to the other.
8. Convenience
*Every aspect of the building gives
convenience to the users.
9. Coordination
*Stores & offices work together so that
the shopping center functions as a
coordinated group.
10. Cleanliness
11. Courteousness
The sales people & office personnel who
Met the public are pleasant & helpful.
12. Colorfulness
13. Creativity
*The place has an original, interesting
& attractive atmosphere.
Digital picture checklist
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Main lobby
Secondary lobby
Wing 1
Wing 2
Wing 3
Atrium 1
Atrium 2
Atrium 3
Food court
Square/open space
Arcade
Low
1
2
3
4
High Low
5
1
1
2
3
4
5
1
2
3
4
1
2
3
1
2
1
High
5
2
3
4
1
2
3
4
5
5
1
2
3
4
5
4
5
1
2
3
4
5
3
4
5
1
2
3
4
5
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
*Other spaces(pls.state)
37
Data collection for the building inventory stage required a group of research
assistant to collect information. Twenty-five research assistants have been assigned
to cover one or two shopping centres each. The total amount of shopping complex to
be surveyed is 40 units throughout Klang Valley. Data is taken during mid-noon for
this is when the outdoor illuminance is at its longest (Zain,2001). The data collection
is done in a day’s period. Before running the task, research assistants have been
briefed by the researcher on what to be collected and the location of the shopping
complexes. First, each and every research assistant is required to collect data based
on the building inventory checklist provided by the researcher. Secondly, they are
also required to photograph the interior and exterior of designated shopping
complexes using digital cameras. This is to illustrate the physical condition of the
building. Research assistants are allowed to use digital cameras of any brand and
resolution but they have to avoid using the flash. On the day of the data collection,
research assistants are gathered at a checkpoint, which is KL Sentral. The researcher
will supervise the research assistants via two-way communication (public phone,
mobile phone, SMS) throughout the exercise. This ensures constant connection,
which is crucial in assisting any occurring problems. In the end of this stage,
information collected will be used to produce the building inventory.
In essence, the objective of the elimination is to select two shopping
complexes that are highly similar to each other which will be compared during the
building selection stage. The only aspect that separates the selected buildings is the
lighting application. Only two buildings will be selected for the field study due to the
problem of controlling the building sample size. Data of surveyed shopping
complexes are broken down to twelve categories. These categories are found in the
building inventory sheet. The building inventory survey provides the researcher with
the information of shopping complexes available within Klang Valley that is
probable candidate for the field study. Below are the list of the building inventory
survey.
38
Table 3.2
Anchorage
Parkson Ria
Plaza Metro
Kajang
Table showing anchor tenants of shopping complexes
Parkson
Grand
The Mall
Subang
Parade
Plaza OUG
Wisma Atria
Klang Parade
Giant
Carrefour
Metrojaya
Jusco
Plaza Metro
Kajang
Plaza Shah
Alam
UE3
The Weld
Ampang Point
Mid Valley
Mid Valley
Mid Valley
Endah Parade
BB Plaza
IOI Mall
Cold Storage
Bangsar
Shopping
Complex
Ikano
Debenhams
Berjaya
Times
Square
Sogo
Permas Sogo
FOS
Maju Junction
Bukit Raja
1 Utama
Anchorage
The Store
Plaza Alam
Sentral
D'Choice
UE3
Xtra
Klang Parade
City Square
Anchorage
Ocean
Selayang Mall
Bintang
Selayang
Capital
Spectrum Mall
Royel
Ampang Point
Aero Pub
Plaza
Ampang
City
39
Table 3.3
Table showing type of lighting used at shopping complexes.
Type of lighting
Mix
Plaza Metro Kajang
Mid Valley
The Mall
UE3
The Weld
Bangsar Shopping Complex
Pearl Point
Paragon Point
Cheras Leisure Mall
Central Market
Subang Parade
Kota Raya
Berjaya Times Square
Plaza OUG
Endah Parade
IOI Mall
Wisma Atria
1 Utama
Ikano
Selayang Mall
Selayang Capital
Permas Sogo
Maju Junction
Spectrum Mall
Yow Chuan Plaza
Artificial
Wilayah Complex
Plaza Shah Alam
Plaza Alam
Sentral
Campbell
Complex
Plaza Armada
Klang Parade
Bukit Raja
S&M Plaza
Pudu Plaza
BB Plaza
Imbi Plaza
Plaza Ampang
City
Ampang Point
Low Yat Plaza
City Square
Sumit USJ
40
Table 3.4
Tables showing rating of shopping complexes.
Compactness
1
Compatibility
1
Yow Chuan
Plaza
2
3
4
5
MidValley
Plaza Alam Sentral
Plaza Metro Kajang
The Mall
Wilayah Complex
Campbell Complex
BSC
Plaza Shah Alam
UE3
Summit USJ
Plaza Armada
Endah Parade
Selayang Mall
Plaza Ampang City
Pearl Point
Paragon Point
Central Market
Berjaya Times Square
IOI Mall
BB Plaza
Ikano
Selayang Capital
Permas Sogo
Spectrum Mall
Low Yat Plaza
City Square
Cheras Leisure Mall
Plaza OUG
Klang Parade
Bukit Raja
S&M Plaza
Pudu Plaza
1 Utama
Maju Junction
Ampang Point
Yow Chuan Plaza
The Weld
Subang Parade
Kota Raya
Wisma Atria
Imbi Plaza
2
3
4
5
Plaza Armada
The Mall
MidValley
Plaza Metro Kajang
Pudu Plaza
Summit USJ
Selayang Mall
Selayang Capital
Plaza Ampang City
Wilayah Complex
Plaza Shah Alam
BSC
Paragon Point
Subang Parade
Kota Raya
Plaza OUG
Endah Parade
IOI Mall
Wisma Atria
S&M Plaza
BB Plaza
Permas Sogo
Spectrum Mall
City Square
Plaza Alam Sentral
UE3
The Weld
Campbell Complex
Pearl Point
Cheras Leisure Mall
Central Market
Berjaya Times Square
Klang Parade
Bukit Raja
Ikano
Maju Junction
Ampang Point
Low Yat Plaza
Imbi Plaza
1 Utama
41
Convenience
1
Plaza Alam
Sentral
2
Plaza Metro
Kajang
Plaza Shah Alam
UE3
Kota Raya
Plaza OUG
S&M Plaza
Pudu Plaza
Plaza Ampang City
Yow Chuan Plaza
Coordination
1
Wilayah Complex
S&M Plaza
3
The Mall
Wilayah Complex
BSC
Pearl Point
Plaza Armada
Central Market
Endah Parade
IOI Mall
BB Plaza
Imbi Plaza
1 Utama
Ikano
Selayang Mall
Selayang Capital
Spectrum Mall
City Square
2
Plaza Metro Kajang
Mid Valley
Megamall
Summit USJ
Plaza Armada
Plaza Ampang City
Yow Chuan Plaza
4
Mid Valley
Megamall
The Weld
Campbell Complex
Paragon Point
Cheras Leisure Mall
Summit USJ
Subang Parade
Wisma Atria
Klang Parade
Bukit Raja
Permas Sogo
Maju Junction
Ampang Point
Low Yat Plaza
3
The Mall
Plaza Shah Alam
Plaza Alam Sentral
The Weld
Pearl Point
Cheras Leisure Mall
Kota Raya
Plaza OUG
Endah Parade
IOI Mall
1 Utama
Ikano
Selayang Mall
Selayang Capital
City Square
4
UE3
Campbell
Complex
BSC
Paragon Point
Subang Parade
Wisma Atria
Klang Parade
Bukit Raja
Pudu Plaza
BB Plaza
Imbi Plaza
Permas Sogo
Maju Junction
Ampang Point
Spectrum Mall
Low Yat Plaza
5
Berjaya Times
Square
5
Central Market
Berjaya Times
Square
42
Cleanliness
1
2
3
Campbell Complex
Wilayah Complex
Plaza Metro Kajang
Central Market
Spectrum Mall
Yow Chuan Plaza
UE3
Kota Raya
Plaza OUG
Wisma Atria
S&M Plaza
Summit USJ
Pudu Plaza
Imbi Plaza
Permas Sogo
Maju Junction
Ampang Point
The Mall
Plaza Shah Alam
Plaza Alam Sentral
Pearl Point
Paragon Point
Cheras Leisure Mall
Plaza Armada
Berjaya Times Square
Endah Parade
IOI Mall
Klang Parade
Bukit Raja
BB Plaza
1 Utama
Selayang Mall
Selayang Capital
Plaza Ampang City
Low Yat Plaza
City Square
Courteousnes
s
1
2
Plaza Shah
Alam
S&M Plaza
Summit USJ
3
4
5
4
Mid Valley
Megamall
The Weld
BSC
Subang Parade
Ikano
5
Plaza Alam Sentral
Plaza Metro Kajang
The Mall
The Weld
BSC
Cheras Leisure
Mall
Kota Raya
IOI Mall
Wisma Atria
Klang Parade
Pudu Plaza
Imbi Plaza
Ikano
Permas Sogo
Maju Junction
Plaza Ampang City
Ampang Point
Yow Chuan Plaza
City Square
Mid Valley Megamall
Wilayah Complex
Campbell Complex
UE3
Central Market
Subang
Parade
Pearl Point
Paragon Point
Plaza Armada
Berjaya Times Square
Plaza OUG
Endah Parade
Bukit Raja
BB Plaza
1 Utama
Selayang Mall
Selayang Capital
Spectrum Mall
Low Yat Plaza
43
Colourfulness
1
Imbi Plaza
Creativity
1
2
Plaza Armada
Wisma Atria
Selayang Capital
Plaza Ampang City
Yow Chuan Plaza
3
Wilayah Complex
Plaza Shah Alam
UE3
Campbell Complex
Central Market
Plaza OUG
Endah Parade
Summit USJ
IOI Mall
S&M Plaza
Pudu Plaza
BB Plaza
1 Utama
Selayang Mall
Spectrum Mall
4
Plaza Metro Kajang
Mid Valley Megamall
The Mall
Plaza Alam Sentral
The Weld
Pearl Point
Paragon Point
Cheras Leisure Mall
Subang Parade
Kota Raya
Berjaya Times Square
Bukit Raja
Ikano
Permas Sogo
Maju Junction
Low Yat Plaza
City Square
2
3
4
Plaza Shah Alam
Plaza Metro Kajang
Plaza Alam Sentral
Imbi Plaza
Wilayah Complex
UE3
Mid Valley
Megamall
The Mall
Spectrum Mall
Campbell Complex
Pearl Point
The Weld
Plaza Armada
Paragon Point
Plaza OUG
Central Market
Pudu Plaza
Summit USJ
Selayang Mall
Plaza Ampang City
Kota Raya
Endah Parade
IOI Mall
Wisma Atria
Klang Parade
S&M Plaza
Selayang Capital
Permas Sogo
Maju Junction
Low Yat Plaza
Cheras Leisure
Mall
Berjaya Times
Square
Bukit Raja
BB Plaza
1 Utama
Ikano
Yow Chuan Plaza
City Square
5
BSC
Klang Parade
Ampang Point
5
BSC
Subang
Parade
Ampang
Point
44
3.2.6
Building selection
A few different approach of building selection has been formulated. The first
attempt of selecting the buildings for the field study is through a Boolean process.
Shopping complexes is then grouped to each category as in the inventory sheet. Each
category containing data of shopping complexes will then be overlapped with other
categories in hope of finding buildings which is most similar to each other. However,
this approach failed. Overlapping the list of categories didn’t manage to select the
buildings. The biggest drawback was that there were too many buildings and too
many categories too match. The large difference the huge variety of main anchor
tenants became the biggest drawback.
The second option was comparing two outlets of the same anchor tenants.
Instead of comparing the shopping complexes in all categories, only one is selected.
The logic behind this option was that outlets of the same anchor tenants should have
the same layout and would sell the same merchandise. Comparing two outlets of the
same anchor tenants (such as Parkson and Parkson) would minimise dissimilarity
that occurs when comparing shopping complexes of different anchors. However, this
option failed. Major anchors in Malaysia (such as Parkson, Jusco, Isetan and
Metrojaya) do not have many outlets operating within its own premises without any
supporting tenants within the building. Through observation, most anchors operate
within a shopping complex which also provides retail space for smaller tenants. This
is unlike the phenomenon that can be found in London where major anchors have
numerous outlets throughout the state operating by itself within its own premises
such as Harrods. 1 With the lack of Malaysian anchors operating within its own
premises, the researcher was unable to find any two (or more) similar anchors of the
same company (e.g Jusco and Jusco) with different lighting application.
1
With regards to discussion with Haliza, she stated that there are numbers of outlets of major tenants
such as Harrods, operating by itself within its very own building without any tenants.
45
The third option was to compare two hypermarkets of the same company
(such as Giant). The logic behind this is that more uncontrollable factors can now be
controlled. Hypermarkets are not shopping complexes. However, to obtain two
buildings that are highly similar to each other with the lighting application being the
only factor that sets it apart is difficult; given the retail scenario of Malaysia. 2 The
most ideal research scenario would be comparing the same exact building but having
the ability to change the lighting condition entirely. 3 Comparing two hypermarkets is
the best research scenario that is viable compared to getting the permission to use a
single building and to alter its lighting application. Unlike shopping complexes,
hypermarkets in Malaysia operate within its own premises. These hypermarkets are
also large in numbers. The design of these hyperarkets is also very similar to each
other. In a nutshell, many uncontrollable factors can be minimised and controlled
when comparing hypermarkets. The idea is to compare two hypermarkets of the
same establishment with different lighting application.(e.g one Giant outlet with
artificial lighting compared to one Giant outlet with natural lighting) However,
Haliza do not aggree with this method. The argument was that incoming patronage to
hypermarkets have the same intention which is to shop for bargain. It is afraid that
people would not be bothered by the lighting application used since the main
objective is to shop at wholesale price. It would be hard to say that patrons of
hypermarkets would want to stay longer than necessary due to architectural values or
even lighting application in that matter due to the nature of shopping at hypermarkets
which is to shop at wholesale, bargain price. Even though there are many
hypermarket outlets, no significant difference is to be found on the lighting system
used. Upon observation, most of the hypermarkets were entirely artificially lit. Thus,
the attempt to compare hypermarkets also failed.
The fourth attempt of the building selection is by using Riley’s Law of Retail
Gravitation. Reily’s Law of Retail Gravitation is a theoretical means of trade area
2
Upon observation, there aren’t any retail anchors that operate by itself in a single building here in
Malaysia.
3
Bashri suggested that in order to control endless factors, use a single building and then change the
lighting condition; one scenario being fully artificially lit while the other being fully naturally lit.
However, to obtain such privilege is nearly impossible due to authorization and legal procedures. (e.g
obtaining permission to change the existing lighting application, cost of manpower to change the
lighting application)
46
definition. It is based on the premise that people are attracted to larger places to do
their shopping, but the time and distance they must travel influence their willingness
to shop in a given city. In other words, people are more likely to travel shorter
distances when possible. Additionally, customers are more likely to shop in larger
communities, as they provide a greater opportunity for goods and services. Reily’s
Law provides a mathematical formula that can be used to calculate hard numbers
relating the distance people will travel. A simple map and common sense can be
combined to generate retail trade area boundaries. By knowing each of the
population and distribution of the communities, a simple trade area can be drawn. An
example done by the University of Wisconsin on the retail trade analysis of Waupaca
district clearly shows its trade area.
Figure 3.3
Table showing retail trade analysis of Waupaca district.
The researcher finally used Riley’s Law on shopping complexes in Klang
Valley to aid the building selection process. First, shopping complexes that is
included in the inventory will be plotted on a map of Klang Valley. This is to clearly
indicate the location of each building. This will also reveal the distance of each
shopping complex to each and every district within Klang Valley.
47
Next, data on population and community distribution will be obtained from
government bodies and several municipal councils. Shopping complexes and data of
population distribution will be overlapped to identify retail trade area.
Figure 3.4
Map showing population distribution of Klang Valley
48
Figure 3.5
Map showing location of shopping complexes within Klang Valley
Based on acquired information, it is evident that Kuala Lumpur rated the
highest density of population compared to other districts within Klang Valley.
Results of the location of shopping complexes (refer Figure 3.5) shows that
approximately 80% of the shopping complexes surveyed are located in the Kuala
Lumpur district. Most of the shopping complexes are located very close to each
other. Moreover, a trade area analysis is unable to be produced within one district
with so many shopping complexes concentrated within the same district. Finally,
after undergone the elimination process and with the help of Riley’s Law, two
shopping complexes located within Subang Jaya have been chosen. The shopping
complexes selected for the field study are The Summit USJ and Subang Parade.
Eventhough each building is located in Subang Jaya, they serve two different
communities. Subang Parade’s trade area encompasses the older part of Subang Jaya
(SS 12 to SS 19) while Summit USJ’s trade area caters for the newer half of Subang
Jaya (USJ) .Therefore, Subang Parade and Summit USJ has been found fit for the
research.
49
Figure 3.6
Map showing location of Subang Jaya & schedule of population
distribution.
3.3
Data collection
The data collection section is divided to three subtopics. These topics are:
(a) Review on lighting variable
(b) Review on patronage variable
(c) Physical measurements
50
Prior to the method of physical measurement of data collection, studies on
lighting variable and patronage variable is done. Study on lighting variable is done as
to substantiate the method of data collection on luminance level. The researcher
focuses only on level of luminance because the research involves the affect of
daylight towards patronage that is linked to the process of visual perception.
According to Boyce (2003), luminance is the luminous flux emitted in a given
direction. In other words, luminance is light reflected by a surface. According to Lam
(1977), visual perception begins when the eye receives a visual stimulus which is the
amount of light reflected by a surface of an object which translates to luminance.
Thus, the research only focuses on luminance level. The common method of
acquiring luminance level is by using a luminance meter. However, the research uses
a digital camera and an image processing programme (ERDAS) in acquiring
luminance level. The explanation on the selection of digital camera will be discussed
in chapter 3.3.1.2 regarding concept of illumination in computer graphics. Studies
regarding lighting includes:
(a) Digital camera in image processing study
(b) Concept of illumination in computer graphics
(c) Image processing programme review
(d) Digital camera and luminance meter comparison
The next step would be the review on patronage variable. This section
discusses on several methods of tabulating patronage. In the end of this section, the
method for patronage count is chosen. The final section of the data collection is the
preparation for physical measurements of acquiring data on luminance level and
patronage count.
51
3.3.1
Review on lighting variable
3.3.1.1 Digital camera in image processing study
The first section of the lighting variable review starts off with basic
understanding of digital camera in image processing. The ability of the digital
camera in recording light values wil be discussed. One of the tasks that will be
carried out during the research is luminance reading. Luminance reading of shopping
complex interiors is to be documented for it will be used later in the research to
identify the light intensity of each building. This will give an indication of which
building has the most or the least component of daylight.
Through the recent years, the imaging industry has been developing in a rapid
pace. Now, the digital camera offers more than just picture taking. Digital cameras
has been equipped with countless functions. This relates how the camera is capable
of carrying out the task of a luminance meter in obtaining luminance readings. The
discussion on the capability of the digital camera is closely linked with the principles
and practice of computer graphics.
3.3.1.2 Concept of illumination in computer graphics
A digital camera captures the whole visual scope at one time and at one
snapshot. A picture taken using a digital camera contains luminance level that lie in
the amount of pixel that make up the picture. According to Folley et al (1990), pixels
or pels (a short for ‘picture elements’) is ones and zeros representation of the
52
rectangular array of points.
4
The ones and zeros representation of the rectangular
array of points bares information of luminance of the whole picture that it resembles.
An image-processing program later decrypts these points into luminance levels. In
other words, the higher the image definition of a picture, the more luminance value
can be obtained from a single picture alone. (refer Figure 3.7 & Table 3.5)
Figure 3.7
4
An image with a resolution of 1375 x 1402 pixels
Introduction, Computer Graphics: Principles and Practice, second edition.
53
Table 3.5
Luminance level represented in each pixel that builds up the image
above
Figure 3.7 is a sample of an image with a resolution of 1375 x 1402 pixels
which sums up to 1,927,750 pixels. Table 3.5 represents 1,927,750 luminance level
reading from each pixel from a single photo. An image processing programme is
capable of translating digital pictures to luminance levels. The luminance level that is
embedded in the pixel that builds up a picture is capable of producing a more
accurate luminance reading compared to luminance level taken using and luminance
meter. As for the luminance meter, the data collection starts of with a built up of an
imaginary grid of a space. The imaginary grid is imposed on the view. Then, the
luminance meter gun will be pointed at each and every box of the grid. Readings will
be produced. There are two limitations to this method. First, the imaginary grid
cannot be subdivided to too many boxes for this will complicate the researcher to
aim the luminance meter to obtain luminance reading. This will lead to the second
limitation which is the time needed to collect luminance reading from each box. The
shifting from one box to the other consumes time. Data taken from each box using
the luminance meter is affected by the changing condition of the sun since it requires
a long time moving from one box to the other.
54
Figure 3.8
Illustration on how luminance reading is taken using a luminance
meter.
Unlike the luminance meter, the digital camera is not affected by the
limitations of a luminance as discussed above. Luminance level of a space can be
acquired simultaneously in a single snapshot using a digital camera unlike the
luminance meter. The present set up and lighting condition of a space is made
constant by using digital camera.
3.3.1.3 Image processing program review
Before the image-processing phase is executed, a review of potential image
processing programs will be done. This is to ensure that the most comprehensive and
reliable program is chosen to process the pictures taken. Pictures of spaces in
commercial complexes, which are taken using a digital camera, is uploaded into an
image-processing program. The main objective of running this exercise is to show
the luminance reading of pictures taken using a digital camera. This method is much
55
more efficient and can be done in a shorter period of time compared to the
conventional way of conducting luminance reading using a luminance meter such as
the Minolta luminance meter.
A review of several image-processing programs available is done. The
selection of the program is based on its compatibility and ability to process images
based on the needs of this exercise which is to identify the luminance readings.
Hence, a compatibility test has been done on two image-processing programs. This
section discusses the pros and cons of each program. The programs are:
(a) PCI Geomatica.
(b) Radiance.
(c) Erdas
(a)
PCI Geomatica.
PCI Geomatica is a computer software which is widely used in the field of
remote sensing. This program is used as a tool in topographical studies such as land
and sea surveying. In general, this programs functions with the aid of digital
topographical imaging taken mainly from satellites in space. Digital images uploaded
into the program will be analyzed with an array of ways/methods, which caters to
numerous usage/needs. In a nutshell, raw data in the form of digital pictures is
analyzed to obtain related data that could contribute to a research. A component of
this program also includes light analysis. The interface of the program is moderately
simple and user friendly.
56
Basic program sequence.
Pictures of interiors of commercial complexes taken using a digital camera is
uploaded into the program. Next, specifications of the digital camera used will be
keyed. This procedure is crucial as the program analyzes the given data based on the
instrument used. Consequently, the desired image processing elements will be
selected in the Algorithm Librarian section. There are two types of image processors,
which consist of:
( i ) Image Processing.
( ii ) Image Correction.
There is a list of sub-processors under each category of processors. After
selecting the desired image processor, click on the ‘run’ button to initiate the image
processing sequence. At the end of this exercise, raw digital images will be translated
into a list of result showing luminance level.
The nature of the program itself that caters to numerous remote sensing needs
tends to confuse the researcher due to the terms used in the program, which is
different from the built environment, even though it bares the same meaning at times.
(b)
Radiance.
Radiance is a 3D modeling program that emphasizes on the aspect of lighting.
It works as a plug-in to CAD programs such as AutoCAD. Radiance comes in two
versions; desktop version and a professional version. The difference that sets apart
the two is that the professional version comes equipped with more functions
compared to the desktop version, which is targeted to beginners and non-professional
users. One of the many features of this program is its capability to emulate realistic
57
artificial and even natural lighting 3D computer renderings. 3D computer renderings
will portray a near realistic outcome thanks to its new feature that enables users to set
up each and every object that’s in the scene to its utmost detail such as the type of
material used and the reflectance level of each object. Program users are also
equipped with a light analysis function that manipulates rendered images to colour
bands indicating light intensity in a space. This feature provides a rough indication of
light acceptance/intensity in the 3d generated space.
Basic program sequence.
This programme starts with a 3D generated model. This is how the program
works; with the aid of 3D computer-generated models. Unlike PCI Geomatica,
Radiance can not work on its own and does not have the capability to process images
in identifying light levels/intensity in a space. 3D generated models can be made
using AutoCad or other compatible CAD programs that can be converted into
AutoCad format such as 3D Studio Max. The 3D generated models should resemble
exactly to the actual space. Information of the space such as dimensions, materials,
reflectance and so forth; should be keyed into the program. Data should not be
restricted only to the space but also any objects that exist within it such as apertures,
furniture, openings and so forth. This stage will require some time depending on the
size of the space and the amount of material used in the space. It is crucial to include
all data regarding each and every object within the 3D generated space for this will
effect the outcome of the process. Insufficient data may result to unrealistic
attenuation of light. Next, define the desired lighting in the space by identifying the
type of light used such as artificial light, daylight or even a mixture of both. From
here onwards, the 3D model will be rendered. Rendered images will produce near
life-like lighting effects. The major drawback of this program however lies in its
dependency on the 3D generated models. In other words, in order to obtain desired
data on light intensity of a space; one must start with making 3D models of the
acquired space from scratch. This is somewhat impractical for the research for it
involves not only one space but also a large number of buildings. Making 3D models
of each and every space of the buildings would most probably be a waste of time
58
since the researcher could work only with digitally taken pictures of spaces with the
aid of PCI Geomatica.
(c)
ERDAS Imagine 8.5
ERDAS Imagine 8.5 is a geographic imaging software and is also used in the
remote-sensing field. ERDAS is very similar to PCI Geomatica. However, this
program has a high degreee of administration flexibility, space-saving features,
import and export utilities, mobility for fieldwork, mosaicking functions and
advanced 3D visualization and scene creation capabilities. ERDAS is also capable of
processing raw data in the form of digital pictures to acquire luminance level. The
interface of the program is very user friendly compared to PCI Geomatica and
Radiance.
Basic program sequence.
First, pictures in JPG format are uploaded into the program. Next, from the
‘Raster’ tab, the ‘Set Layer Combination’ option is used to configure the layer. Next,
the picture is saved in another format called IMG format. This enables the picture to
be processed later. Finally, from the ‘Viewer’ window, click on the ‘Information’
tab. This information tab will give out statistical analysis of the picture. This
statistical analysis reflects the luminance level of the image. The analysis also
produces a histogram showing light intensity level. Based on the review on all 3
image processing program, it is found that ERDAS is the simplest program to be
used. Therefore, ERDAS has been chosen for this research for it is more practical
and less time consuming compared to Radiance and PCI Geomatica. As to date, this
research would be the first to use ERDAS in acquiring luminance level.
59
3.3.1.4 Digital camera and luminance meter comparison
An experiment between readings from computer processed pictures taken
with a digital camera and readings from a luminance meter is conducted to identify
the accuracy of digital camera in acquiring light levels. However, the luminance
meter could not be obtained. Other apparatus of acquiring light levels have to be
considered. The lux meter is the next best option to substitute the luminance meter.
The logic of the selection of the lux meter as a substitute to the luminance meter is
best explained by the basic formula of luminance. According to Hopkinson (1966),
luminance is equivalent to:
L (luminance) = E (illuminance) x R (reflectance)
According to Boyce (2003), reflectance is defined as the ratio of the luminous
flux reflected from a surface to the luminous flux incident on it while illuminance is
defined as the luminous flux/unit area at a point on a surface .
R (reflectance ) = light reflected by a surface
light received by a surface
E (illuminance) = light received by a surface
Based on the definitions above, therefore luminance can be defined as:
L (luminance) = E (illuminance) x R (reflectance)
= light received by a surface x light reflected by a surface
light received by a surface
= light reflected by a surface
A lux meter is capable of acquiring light level reflected by a surface. Thus,
the lux meter has been selected to acquire light readings for the experiment. The
detail usage of the lux meter in acquiring light readings will be discussed further in
this chapter.
60
The experiment of comparing digital camera to lux meter is divided into 3
parts. The experiment is done in a controlled environment with fixed artificial
lighting. The lab used for the experiment is fully artificially lit with 21 fluorescent
light located at the ceiling of the lab. Apertures such as windows and doors are shut
as to ensure controlled lighting condition. The light level reading of the lab has been
taken from the average sum of 5 different light level readings taken from four
corners of the lab and 1 from the centre of the lab using a lux meter. This represents
the existing light level in the lab. Instruments used in this experiment consist of a lux
meter (ISO-Tech ILM 350), a digital camera, and 3 sheets of colour boards.
1. Experiment setup
A white writing board with the size of 1.5m x 2.5m is used to collect data.
The writing board will be covered with three types of paper to simulate different
light intensity reflected by the surface. Brown coloured paper is used to simulate a
dark surface. White coloured paper is used to simulate a bright surface while a
mixture of coloured papers is used to simulate mixed coloured surface. The
hypothesis of the experiment is that readings acquired from the digital camera will be
as same as readings from the lux meter for all three different conditions of surfaces.
A grid made out of 10 horizontal and 10 vertical lines is positioned on top of all 3
different surfaces. The grid is used as a reference to help data collection for the lux
meter. Three different surfaces is used in the experiment to show that the digital
camera should produce the same readings eventhough the surfaces are different in
colour. The grid is divided as such to facilitate data collection using lux meter.
2. Experiment data collection.
The experiment data collection is done using a digital camera and a lux
meter. The process begins with the lux meter. First, the white writing board will be
covered with one of the three types of paper used to simulate different types of
61
background. Then, gridlines will be drawn on the paper. Then, the lux meter is
positioned facing the centre of each grid box. This is done to acquire light level for
each grid that builds up the entire background. Readings for each grid box will be
documented and later summed and averaged to simulate an average reading of the
entire paper used for the background. The whole process is repeated for other
backgrounds
With the same set up, a digital camera is positioned 4.8m away from the
writing board and 1m above the floor. A picture for each type of paper is taken.
Then, pictures will be uploaded into a digital image processing programme (ERDAS)
to acquire light levels. The programme will only process the area within the gridline.
Digital camera is located at 4.8 metres away from the board in order to include the
entire board onto one picture. The distance from the digital camera and the board is
sufficient enough to fit the field of view of the camera. The lux meter reading has to
be taken close to the board since it can’t perform light reading from afar.
3. Data comparison analysis.
Central Tendency Representation is done in the data comparison analysis.
This is to verify which readings should be used for the data comparison, whether
mean, mode or median. A picture taken using the digital camera is used for the
experiment. The programme (ERDAS) gives out readings of light levels in the values
of mean, mode and median. ERDAS will process each grid box within the picture to
give out mean, mode and median values. These readings will be compared with
readings from the lux meter using Microsoft Excell. A line chart is produced to show
the relation between all readings.
62
Four sets of samples is produced and plotted to form a chart. Each set of
samples comprise of 10 readings taken from grid boxes. The first column of the chart
represents samples taken from different backgrounds (refer Experiment Setup). The
second column of the chart represents lux meter reading while the third to fifth
column represents digital camera readings in DN unit. 5 Below are the charts:
Table 3.6
Mixed background readings – Set 1
Mixed background - Set 1
SamplesLux meter readingDigicam mean Digicam mode Digicam median
a1
140
156.113
154
155
b1
117
151.499
151
151
c1
114
149.646
149
149
d1
109
146.771
148
147
a2
100
155.443
155
155
b2
88
153.544
153
153
c2
72
152.218
151
151
d2
90
146.778
148
148
a3
153
185.744
189
188
a4
146
193.143
195
194
Mixed Background-Set 1
250
A1 mixed - 1st set lux
reading
A1 mixed - 1st set
digicam mean
A1 mixed - 1st set
digicam mode
A1 mixed - 1st set
digicam median
Light reading
200
150
100
50
0
a1 b1 c1 d1 a2 b2 c2 d2 a3 a4
Samples
5
DN or digital numbers is a value that gauges light intensity level in a picture when processed using
ERDAS.
63
Table 3.7
Mixed background readings – Set 2
Mixed background - Set
2
SamplesLux meter readingDigicam mean Digicam mode Digicam median
b3
151
187.65
189
189
b4
146
193.606
193
193
c3
142
185.806
187
188
c4
126
191.819
191
191
d3
135
182.068
184
185
d4
116
187.994
188
188
e3
62
152.38
153
153
e4
71
160.695
157
158
f3
51
147.864
150
150
f4
66
153.545
154
248
Mixed Background-Set 2
Light reading
300
250
A1 mixed - 2nd set
lux reading
200
A1 mixed - 2nd set
digicam mean
150
100
A1 mixed - 2nd set
digicam mode
50
A1 mixed - 2nd set
digicam median
0
b3 b4 c3 c4 d3 d4 e3 e4 f3
Samples
f4
64
Table 3.8
Dark background readings – Set 1
Dark background - Set 1
Samples Lux meter reading Digicam mean Digicam mode Digicam median
a1
84
62.886
61
62
b1
73
63.036
62
62
c1
65
61.126
59
60
d1
62
57.32
57
56
e1
74
57.531
57
56
f1
62
53.909
53
53
g1
69
55.453
55
54
h1
72
50.25
49
49
i1
67
49.65
49
49
j1
60
50.718
49
49
Light readings
Dark Background-Set 1
90
80
70
60
50
40
30
20
10
0
lux reading
digicam mean
digicam mode
digicam median
a1
b1
c1
d1
e1
f1
Samples
g1
h1
i1
j1
65
Table 3.9
Dark background readings – Set 2
Dark background - Set 2
Samples Lux meter reading Digicam mean Digicam mode Digicam median
a2
74
59.423
59
59
b2
69
61.858
60
60
c2
72
60.661
59
60
d2
60
56.077
54
54
e2
70
58.029
54
55
f2
62
54.927
52
53
g2
58
54.532
51
52
h2
60
51.913
50
49
i2
59
50.628
49
49
j2
51
51.774
51
51
Dark Background-set 2
80
Light readings
70
60
lux reading
50
digicam mean
40
digicam mode
30
digicam median
20
10
0
a2 b2
c2
d2 e2
f2
Samples
g2
h2
i2
j2
66
Each chart illustrates samples from images processed using ERDAS taken
with the digital camera and readings from a lux meter. Readings of mode, median
and mean derived from ERDAS shows a very high consistency off all three readings.
This is proven by the small difference of light readings of the mode, media and mean
as illustrated in the graph (refer Table 3.6, 3.7, 3.8 & 3.9). The small difference
between mean, mode and median readings shows that normal distribution occurred in
samples processed using ERDAS. The research opted for mean digital camera
reading since it gives the closest reading to the lux meter as illustrated in the graph
(refer Table 3.6, 3.7, 3.8 & 3.9).
In the Mixed Background chart, there is a very big difference between
readings of the lux meter and readings from the digital camera. However, samples
from the Dark Background chart show a very significant similarity and consistency
between both readings. However, data inconsistency is detected in the mixed
background samples. Further observations and analysis suggests that data
inconsistencies between lux meter and digital camera are probably due to local
effects of used instruments. This can be seen in the different method of usage of each
instrument. Readings from a lux meter is taken at a closer distance to the surface thus
resulting to higher level of energy reflected by the surface. Lux meter readings have
to be collected close to the surface to acquire light levels for each grid box. Reading
from a digital camera is taken at a distance of 4.8 meters away from the surface thus
resulting to lower level of energy reflected by the surface. This phenomenon is called
the effect of field size which was discussed by Boyce (2003). Pictures taken using
the digital camera have to be taken at a distance to fit the entire surface background.
Moreover, pictures have to be taken from a distance and not from each grid box since
ERDAS is capable of giving out readings for each grid box.
However, inconsistencies in readings for both instruments occurred due to
local effect. Therefore, Data Filtering has to be done. A mixed background image has
been used for the data filtering process. Four types of coloured paper has been used
for the background which consist of blue, red, green and yellow. Each colour is
singled out and processed individually. The logic behind this is that each individual
67
colour should produce consistent readings regardless of the instruments used. Lux
reading and digital camera mean value of each samples of the same colour group is
plotted together for comparison purposes.
Table 3.10
Data Filtering for Red Set
Red set-1st attempt
Samples
Lux meter readingDigicam mean
a1
140
156.113
b1
117
151.499
c1
114
149.646
d1
109
146.771
a2
100
155.443
b2
88
153.544
c2
72
152.218
d2
90
146.778
e3
62
152.38
e4
71
160.695
f3
51
147.864
f4
66
153.545
g3
47
146.285
g4
70
151.297
h3
59
144.726
h4
55
147.951
i3
50
142.135
i4
62
144.433
j3
50
136.816
j4
56
140.614
MEAN
UPPER LIMIT
LOWER LIMIT
DIFFERENCE
76.45
103.3405677
49.55943229
53.78113541
149.03765
154.789403
143.285897
11.503506
Instrument comparison - red
180
160
120
Red set-1st attempt
lux reading
100
Red set-1st attempt
digicam mean
80
60
40
20
samples
j3
h4
g3
e4
c2
d1
0
a1
light level
140
68
Table 3.11
Data Filtering for Blue Set
Blue set-1st attempt
Samples
Lux meter readingDigicam mean
a7
145
65.428
a8
168
63.623
a9
152
77.384
a10
139
74.571
b7
137
59.703
b8
156
58.913
b9
155
70.158
b10
136
72.514
c7
131
57.893
c8
127
57.212
c9
115
69.214
c10
114
72.775
d7
134
59.964
d8
130
56.015
d9
122
68.585
d10
123
71.312
e1
141
57.354
e2
125
58.078
f1
138
52.201
f2
125
51.628
g1
115
49.951
g2
115
49.562
g5
125
74.505
g6
130
75.548
h1
101
47.954
h2
108
49.878
h5
115
71.657
h6
123
73.712
i1
132
48.703
i2
110
47.664
i5
104
70.3
i6
115
73.047
j1
130
48.234
j2
128
43.351
j5
90
71.287
j6
106
72.7
MEAN
UPPER LIMIT
LOWER LIMIT
DIFFERENCE
126.6666667
143.257542
110.0757914
33.1817506
62.29383333
72.63400531
51.95366136
20.68034395
69
180
160
140
120
100
80
60
40
20
0
Blue set-1st
attempt lux reading
samples
j1
i1
h1
g1
e1
d7
c7
b7
Blue set-1st
attempt digicam
mean
a7
light level
Instrument comparison - blue
70
Table 3.12
Data Filtering for Green Set
Green set-1st attempt
Samples
Lux meter readingDigicam mean
a5
155
141.295
a6
161
140.422
b5
146
137.052
b6
145
137.338
c5
145
136.163
c6
140
137.148
d5
157
130.875
d6
127
127.757
e5
137
127.395
e6
105
128.796
e9
130
129.086
e10
121
125.874
f5
143
121.098
f6
100
123.038
f9
142
124.935
f10
137
120.909
g9
130
122.288
g10
127
118.213
h9
128
119.894
h10
110
117.952
i9
114
116.511
i10
115
114.903
j9
101
110.493
j10
96
107.175
MEAN
UPPER LIMIT
LOWER LIMIT
DIFFERENCE
129.6666667
148.3579031
110.9754303
37.3824728
125.6920833
135.0367638
116.3474028
18.689361
Instrum ent com parison - green
Green set1st attempt
lux reading
150
100
Green set1st attempt
digicam mean
50
sam ples
i9
f1
0
e9
c6
0
a5
light level
200
71
Table 3.13
Data Filtering for Yellow Set
Yellow set- 1st attempt
Samples
Lux meter readingDigicam mean
a3
153
185.744
a4
146
193.143
b3
151
187.65
b4
146
193.606
c3
142
185.806
c4
126
191.819
d3
135
182.068
d4
116
187.994
e7
128
188.688
e8
140
187.605
f7
133
188.148
f8
132
188.238
g7
123
185.659
g8
138
185.002
h7
121
182.2
h8
116
181.434
i7
105
181.971
i8
109
181.453
j7
106
178.797
j8
99
178.244
MEAN
UPPER LIMIT
LOWER LIMIT
DIFFERENCE
128.25
144.328344
112.171656
32.1566888
185.76345
190.1682859
181.3586141
8.8096718
Instrument comparison - yellow
250
Yellow set- 1st
attempt lux reading
150
Yellow set- 1st
attempt digicam
mean
100
50
sam ples
j7
h8
g7
e8
d3
b4
0
a3
light level
200
72
Results show that inconsistencies happens most within the red and blue
samples. Lux readings for red coloured samples show a very distinctive pattern of
inconsistence. Lux readings for blue coloured samples show higher readings
compared to readings processed using ERDAS. Yellow coloured samples and green
coloured samples show consistency between lux meter and ERDAS. Readings off all
four colours seems to conflict each other. This is probably due to the local effect.
However, when the backgrounds are analysed as a whole (instead of processing each
grid box individually), results shows that lux meter reading is consistent with
ERDAS. This can be seen through the chart and graph below:
Table 3.14
Overall background readings
Overall background readings
Lux meter reading Digicam mean Digicam mode Digicam median
Dark
71.21
62.402
55
59
Mixed
117.52
120.018
241
129
White
182.17
161.123
158
162
light levels
Lux reading v/s digicam mean
200
180
160
140
120
100
80
60
40
20
0
lux reading
digicam mean
dark
mixed
w hite
backgrounds
Figure 3.9
Lux reading versus digital camera mean
73
In conclusion, the observations and analysis of these data have shown that
readings taken using digital camera and lux meter are highly connected and this
validates the use of digital camera in acquiring light levels. This is due to the fact that
eventhough local effect produces inconsistencies; the global reading of each
background still remains consistent thus validating the usage of digital camera and
ERDAS programme for the research.
3.3.2 Review on patronage count
Five methods of patronage count has been reviewed. These includes traffic
count system, traffic count computer program (ROMDAS), pedestrian counting
system (Infodev ), Space Syntax by Bill Hillier, Heschong (1999) and her research
regarding skylighting and retail sales and Reily’s Law of Retail Gravitation.
Heschong (1999) used statistical analysis method in her research. She looked into
five main variables that had significant effect on gross sales per store, which consist
of presence of skylight, number of hours the store is open per week, population and
income of the store’s zip code and the number of years since the store has last been
remodelled. However, the major difference in the research field became the biggest
drawback. The selected research field which is Klang Valley, does not provide the
same scenario as in Heschong’s. In Heschong’s research, they have a retailer of
similar designed chain stores with more than 100 outlets with a variety of lighting
application (2/3 with skylight and 1/3 without skylight). They also sought
organizations with pre-existing productivity measurements that could be compared
between buildings with and without skylights (or daylight). Shopping complexes in
Klang Valley however doesn’t provide such commercial setting even though it has
been said to remain the fastest growing regional economy in Peninsular Malaysia
(Selat,1995). As to date, apart from Heschong, no research regarding the affects of
daylight towards patronage has been done.
74
The objective of reviewing other tabulation methods is to look at the issue of
double counting which is feared capable of causing biasness in the patronage count.
The Handbook of Simplified Practice for Traffic Studies (2004) gave an overview on
methods of tabulating traffic. The handbook explains the very basics of conducting
traffic studies. It includes traffic volume counts stages that consist of preparation,
selection of location, completion of study and documentation that could be
implemented in the research. According to the handbook, a manual count study
consist of three steps; perform necessary office preparation, select proper observer
location and label data sheets and record observations. However, both manual and
automatic methods of traffic volume counts does not address the issue of double
counting.
The issue of double counting has not been discussed in the Road
Measurement Data Acquisition System or ROMDAS. The programme uses a
formula to tabulate average daily traffic (ADT) and average annual daily traffic
(AADT) which requires traffic data such as oncoming flow rate (vehicle per hour),
average oncoming vehicle speed (km/h), speed of the ROMDAS survey vehicle
(km/h), distance travelled by the ROMDAS survey vehicle (km) and the number of
vehicles counted travelling in the opposite direction. These data is later uploaded to a
computer to set up ROMDAS. Keys are later assigned in the keycode event file as
traffic count keys. ROMDAS proved unsuitable for the research for it has been
specifically designed for “Moving Traffic Counts”.
Another option for patronage count would be the Infodev pedestrian
monitoring system. The system incorporates both hardware and software in obtaining
data. Counting sensors are installed in doors and passageways and count the persons
passing in their field of view. Next the data loggers receive sensor signals and store
the data to embedded memory. Data from the data loggers are taken by data transfer
devices to the office computer. Finally analysis software called Trends turns data into
useful, useable information. This method also did not stress on the issue of double
counting. However, the method of counting is different from the others. The system
states that it is necessary to implement different levels of accuracy depending on the
75
area. According to the example taken from a shopping centre in Quebec City,
Canada, which uses the Infodev system, the entrances of the shopping centre has
been equipped with highly accurate counting sensors, while areas like the food court
would provide the same quality of data with standalone counters-estimators.
Figure 3.10
Infodev counting process.
76
Figure 3.11
Infodev’s horizontally located and vertically located counting sensors
(source: www.infodev.org).
The most important factor in conducting or choosing the method of tabulation
is the condition of the research set up. Among all reviews patronage counting
methods, Infodev system proved to be the best method do to its computerized data
collection (refer Figure 3.10). Inarguably the Infodev system would provide a
reliable patronage count. However, the research is incapable of funding and
obtaining the expenses for the equipment. Instead, the research adopted Infodev’s
counting method. Infodev has two options of counting which consist of horizontally
located sensors and vertically located sensors (refer Figure 3.11). Patrons crossing
the field of vision of a horizontally placed sensor will hide other people standng
beside them which will affect the count. Vertically placed sensors are more accurate
because they are ‘looking’ at patrons from above.
77
3.3.3
Physical measurements
The physical measurements topic is divided to four sections which consist of:
(a) Condition and time for data collection
(b) Research instrument
(c) Patronage count
(d) Luminance reading
3.3.3.1 Condition and time for data collection
Controlled and non-controlled variables are identified before the fieldwork is
done. Since the field work (Klang Valley) covers a large area, 2843 square
kilometres in total according to Selat (1995), the probability of changing sky
conditions is very high. According to Madros (1998), the lighting condition as a
result of the natural lighting varies with level of exterior daylight, which in turn,
varies, with the time of day, time of year, sun and variance in cloud cover. This will
result to biasness in the data taken since daylight readings keeps on changing.
According to Zain (2001) on daylight availability in Malaysia, she concluded
that the Malaysian sky is mostly cloudy, but not necessarily overcast. A chart of
daylight availability for the Klang Valley produced by Zain serves as a point of
reference for the time of data collection. The date for the data collection has been set
in the month of January 2004 since it has the longest constant illuminance reading
which is from 11am to 2.30pm (refer Figure 3.12). Time of data collection is based
on the daylight availability chart done by Zain (refer Figure 3.12). Illuminance
readings change nearly in an hourly basis in the mornings and evenings (refer Figure
3.12). Readings at 8-9am are at 40,000 lux and it ascends to 60,000 lux from 9-
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10.30am. This phenomenon occurs even in the evenings, which indicates readings of
60,000 lux from 2.30-4pm and descends to 40,000 lux from 4-5pm. Zain indicated
that mid day seems to have the longest length of time with the same outdoor
illuminance reading which is 80,000 lux during mid-day. Thus, the time frame of
data collection has been set from 11am to 2.30 pm since it has the longest period of
time with the same outdoor illuminance reading that could give the researcher ample
time to collect and record data (refer Figure 3.12).
Figure 3.12
Hourly global illuminance for Klang Valley, Malaysia. 6
Controlled variables for the digital camera are as follows:
•
Digital camera’s with the same resolution (as in pixel count) regardless of
brand/type is considered as usable in acquiring data.
•
Do not use flash. The flash option should be turned off. The usage of flash
will temper the real lighting condition of the space.
6
Ahmad,A.Z, “Daylighting: Renewable Energy Source Rediscovered, Akitek Urbanisma Renewable
Energy Workshop Lecture Notes,2000.
79
3.3.3.2 Research instrument
The objective of data collection is to measure luminance level and to tabulate
patronage count. Identification of past instruments usually used to measure lights is
done. Previously used instruments are evaluated and compared to the proposed
method for obtaining data, which is the digital camera. Instruments usually used to
measure lights are:
•
Minolta LS-100 luminance meter
•
Hagner semi-cylindrical cell
•
Hagner EC1 lux meter
Instead of using any of these instruments in measuring light, the research
opted for another method which integrates the use of a digital camera and an image
processing programme. Digital camera and an image-processing programme have
been selected to obtain luminance reading due to several reasons. It has the ability to
obtain data in a shorter period of time. Secondly, is due to the availability of the
instrument. Among all four above mentioned instruments, the luminance meter
would be the best instrument for the research. However, Nanyang Polytechnic,
Singapore owns a unit but it can only be accessed by its students and staffs. Local
universities, government and private bodies (of Malaysia) too do not have the
instrument. Buying the instrument would be too costly and redundant. The luminance
meter is not used in the research due to its limitations. Firstly, it consumes a longer
period of time in obtaining readings. Imaginary grids are required within the visual
scope. Then, readings are taken from each grid. The readings are most likely to be
unreliable since the light (especially daylight) is always changing thus causing
inconsistent readings. The shift from one grid to another takes time and the tendency
of light to change through time is high. (e.g change of daylight due to time of day
[1pm-4pm] and even cloud formations). The advantages of using a digital camera
and an image processing programme and the disadvatages of using a luminance
meter in acquiring luminance reading has been discussed in chapter 3.3.1.2.
80
3.3.3.3 Patronage count
The researcher adopted the Infodev method by doing it manually. There will
be 1 session for patronage count. The session will run for duration of 1 hour and 30
minutes starting from 11.30 am to 1 pm. The checkpoint of the count is located at the
main entrance of the main anchor tenant. The research has selected the busiest point
of the building to conduct the patronage count. The location of the patronage count is
similar to the location of the Infodev’s count sensors. An imaginary gridline will be
used as a point of reference for the count. Every patron that passes through it will be
counted using a manual hand counter. Checkpoint is located at the same level as the
imaginary grid. This method has been adopted from the Infodev 7 patronage counting
system that counts patrons from the side of entrances. Research assistant are
apppointed to substitute horizontal counting sensors. Assistants are located at the
same level as the patrons and patrons are counted using a manual hand counter (refer
Figure 3.13). An imaginary line is set out on the counting ground as a reference point
of patronage count (refer Figure 3.14, Figure and 3.15)
Figure 3.13 Handheld manual counter used to count patronage.
7
Infodev is a pedestrian monitoring system that has been developed in Canada. The company designs
and manufactures software and hardware that collects and analyses data of patronage. (please visit its
website for further details. www.infodev.ca)
81
Figure 3.14
Counting stations (green) and imaginary count line (blue)
1
Figure 3.15
Plan showing checkpoint for patronage count at Subang Parade.
82
3.3.3.4 Luminance reading
Picture taking will be done twice; once during the day and once during the
night. The amount of locations for picture taking is the same for both buildings (50
locations). The time set for picture taking is done during the same time frame for
each building which is from 11.30 am to 1 pm. Locations of pictures to be taken are
recorded to aid picture taking that will be done twice at the same location. The logic
behind this approach is to obtain daylight component of a building. During the day,
the building is lit by a combination of artificial light and daylight while it is only lit
by artificial light during the night. These pictures will be processed using ERDAS
programme to obtain luminance reading for each picture. According to Shalaby
(2002), level of daylight component can be acquired through graphic, numerical or
physical model techniques and in some case the visual appearance of daylighting
scheme. Method of acquiring level of daylight component through visual appearance
of daylighting scheme was selected for the research. The method was selected
because visual appearance of daylighting scheme is shown in taken pictures.
Therefore, the luminance level for each picture for each time period (day and night)
will be totalled and the average of the sum will represent the luminance level. Now,
there are two sets of luminance readings for each building (Subang Parade and
Summit USJ); one during the day and during the night. In order to obtain the daylight
component for each building, the luminance reading acquired from the pictures taken
during the day will be subtracted with luminance reading acquired during the night.
Data analysis
3.4
The method of the analysis is divided to 2 main parts:
(a)
Tabulation of patronage count and luminance level
(b)
Comparison of data of Summit USJ and Subang Parade
83
The data analysis starts off with tabulating data of patronage count and
luminance levels of both buildings. The data will be used as to compare both
buildings further in the data analysis chapter.
3.4.1
Tabulation of patronage count and luminance level
Patronage count conducted at the busiest point is tabulated. The value of each
building represents the number of patron that visits the building.
The analysis of the luminance level starts with the processing of pictures
using ERDAS. Pictures are uploaded into the program as to obtain luminance level
of each picture. At the end of the practice, a list showing luminance value of pictures
taken is made. Again, the luminance value of each picture is added and later
averaged. This is done as to obtain an average luminance value of the building.
3.4.2 Comparison of data of Summit USJ and Subang Parade
This section is divided to two parts. The first part of the analysis is building
description. This part of the chapter describes the physical attributes and lighting
attributes of Subang Parade and Summit USJ. The second part of the analysis is
called data description. Data collected from both buildings which consist of
luminance level and patronage count is shown here. Next, 3 separate analysis is done
by comparing data from both buildings. These analyses consist of daylight
component study, pattern of light distribution study and patronage study.
84
3.5
Pilot study
The objective of the pilot study is to review the running of the research set
up. Instead of running the pilot study on Subang Parade and Summit USJ, only
Subang Parade has been selected to conduct the pilot study. The pilot study is
conducted as to review the research set up and not to compare data of both buildings.
Subang Parade uses both artificial light and daylight. Sidelit atria stretching
throughout the building and a toplit atria at the east end contributes to daylighting.
(refer Figure 3.16)
Figure 3.16
Sidelit atria (left) and toplit atria (right)
Patronage count and data on luminance level is done during mid-day since it
has the longest length of time as stated by Zain (2001). The outdoor luminance level
needs to be normalized as this will affect the lighting condition of the building.
Change in outdoor luminance level (from the changing sun, sky and cloud formation)
affects the level of daylight in the building. Therefore, based on Zain’s (2001)
research, data collection must be carried out during mid-day. This gives the
researcher reliable data and ample time in taking luminance level readings. Next,
pictures showing lighting condition throughout the building interior are taken using a
digital camera from 11.30 am until 2.30 pm. Pictures are taken from all floors. This
is to illustrate the overall lighting condition of the building. The camera uses a single
85
camera setting throughout the study (shutter speed=1/125, f=3.2, iso=100) and
without using flash as to avoid tempering the data. A total of 57 pictures are taken.
Each photo will be proceseed using an image processing programme called ERDAS
(refer Figure 3.17). The programme will produce histograms indicating frequency of
different luminance value derived from each pixel of a picture (refer Figure 3.18 and
Table 3.19). The programme also gives an average luminance value of each picture.
Finally, average luminance value of each picture will be summed up and later
averaged again. The final average luminance value indicates the luminance level of
the building.
Figure 3.17
Picture of lighting condition processed using PCI Geomatica.
86
.
Figure 3.18
Figure 3.19
Histogram showing frequency of different luminance value.
Table showing general properties of processed picture.
87
Table 3.15
Table showing luminance level of each pixel that builds up the picture
The amount of patronage count during the pilot study is 721 people.
Throughout the pilot study, it is found that the methodology has to be amended.
Amendments of data collection and method of data analysis has to be made. The
patronage count was found to reflect patrons of the anchor tenant only and not
Subang Parade. Therefore, the number of patronage obtained during te pilot study
failed to represent the number of patronage for Subang Parade. Furthermore, pictures
taken do not represent patrons field of view. Amendments on data collection will be
further discussed in chapter 3.6.
3.6
Amendments on data collection
Amendments on the data collection section includes method of patronage
count and method of luminance reading.
88
3.61
Amendments on patronage count
There will be 4 sessions for patronage count. During the pilot study, only one
session is done. The logic behind the increase of sessions for patronage count is due
to the group of people that visits a shopping complex. Doing only one session of
patronage count would result to inadequacy in the collected data. For example, if the
patronage count is done in the morning, it is feared that the count will only tabulate
morning patrons only such as housewives and accompanying children. The research
does not emphasize on one category of people that visits the shopping complex. The
research would like to look into the relation between patronage count and daylight.
Patronage should consist of more than one group of people (e.g. children, teenagers,
adult, elderly). Thus, in order to get a fair patronage count, 4 sessions of count will
be done. Each session will run for duration of 30 minutes. All 4 sessions will be
scheduled from the opening of the shopping complex until sunset. The morning
session will start at 11 am until 11.30 am. The afternoon session will start at 1pm
until 1.30 pm. The third session which is the mid-afternoon session will start at 3 pm
until 3.30 pm while the last session will start at 5.30 pm until 6 pm.
The checkpoint for the patronage count also has been increased to 4 locations.
The logic for increasing the number of count locations is to increase the accuracy of
the count. Executing the count at only 1 checkpoint only gives a view of one section
of the entire building. Thus, more checkpoints have been introduced to give an
overall view of the patron in a shopping complex. A higher increase of checkpoints
would increase the accuracy of the count. Prior to the count, observation has been
done to select checkpoint, which is the busiest points in the shopping complex. An
imaginary gridline will be used as a point of reference for the count. However,
checkpoint won’t be located at the same level as the imaginary grid. Instead, it will
be located a level above the imaginary grid. This method has been adopted from the
Infodev 8 patronage counting system that counts patrons from a higher point to have a
8
Infodev is a pedestrian monitoring system that has been developed in Canada. The company designs
and manufactures software and hardware that collects and analyses data of patronage. (please visit
website for further details. www.infodev.ca)
89
clearer overall view of the count area. This method minimises the risk of
miscounting due to overlapping of patrons. Research assistant are apppointed to
substitute vertical counting sensors. Assistants are located overlooking the counting
ground (refer Figure 3.20) and patrons are counted using a manual hand counter . An
imaginary line is set out on the counting ground as a reference point of patronage
count. There are 4 count locations for each building (refer Figure 3.20 and Figure
3.21)
Figure 3.20
Counting stations (green) overlooking imaginary count line (blue)
90
1
Figure 3.21
2
3
4
Plan showing checkpoints for patronage count of Subang Parade.
2
3
4
1
Figure 3.22
Plan showing checkpoints for patronage count Summit USJ.
Checkpoints for patronage count for Summit USJ and Subang Parade is
shown in figures above (refer Figure 3.21 and Figure 3.22). Finally, all the counts
will be averaged out. Data from all 4 time periods and all 4 locations will be added
91
up and finally an average number is obtained. This will give a rough overview of the
overall patronage count of the building.
3.6.2
Amendments on luminance reading
Digital pictures taken only show one angle of view which is horizontal or
vertical; thus not portraying the field of view. This is due to the use of common
camera lens that was unable to capture wide angle views. The field study will be
using fish-eye lens which shows horizontal and vertical angle in just one picture. The
use of fish-eye lens also simulates human’s eye view. This method solves the
problem of patching two pictures together to form a complete field of view. (refer
Figure 3.23)
Figure 3.23
Picture taken using fish eye lens gives a wider angle (left) while
common lense is limited to either a horizontal or a vertical view only.
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3.7
Amendments on data analysis method
Patronage count are done at 4 different checkpoints instead of just 1
checkpoint. There are 4 different sessions of patronage count and this data will be
averaged. Patronage count of each checkpoint of each time frame is tabulated and
averaged. The average value of each building represents the number of patron that
visits the building.
The analysis of the luminance level remains the same as stated in luminance
reading section . The comparison of data of Subang Parade and Summit USJ is also
maintained.
CHAPTER 4
RESEARCH ANALYSIS
4.0
Introduction
The chapter is divided to two parts. The first part of the analysis is building
description. This part of the chapter describes the physical attributes and lighting
attributes of Subang Parade and Summit USJ. The second part of the analysis is
called data description. Data collected from both buildings which consist of
luminance level and patronage count is shown here. Next, 3 separate analysis is done
by comparing data from both buildings. These analyses consist of daylight
component study, pattern of light distribution study and patronage study.
4.1
Building description
4.1.1 Subang Parade
Subang Parade is located at Jalan SS 15/1A along Jalan Kemajuan of Subang
Jaya. It is geographically located at latitude (3.0821 degrees) 3° 4' 55" North of the
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Equator and longitude (101.5855 degrees) 101° 35' 7" East of the Prime Meridian on
the map of Kuala Lumpur. Subang Parade has 3 levels of retail floor which sums up
to 500,171 square feet of lettable area. It is occupied by Parkson Grand as the anchor
tenant and 160 specialty stores such as Celebrity Fitness, Digital One, Toys ‘R’ Us,
MPH Megastore, HSL Electrical & Electronics, The Reject Shop, World of Sports,
Royal Selangor, Dome Café, TGI Friday’s, Oversea Restaurant, McDonald’s and
The Chicken Rice Shop. It is also equipped with 1300 parking bays.
Subang Parade is a rectangular shaped building. The layout of all 3 floors of
shopping area and a basement carpark are similar in shape. The average floor to
ceiling height for the lower ground floor and the ground floor is 4m while the height
of the first floor is 15m of double volume space. The internal circulation consist of
mezzanines located in front of shoplots. These mezzanines are connected to other
floors using ramps while elevators and escalators serves as the vertical circulation
system. An atrium is located at the centre of the building surrounded by the
mezzanines. The building orientation is parallel to the South-East. The largest
surface of the building is the front and rear elevation. The morning sun contributes
heat gain to the right side of the building while the left side is affected by the evening
sun. Subang Parade has been strategically orientated to minimize heat gain by
positioning its smallest building surface (right and left sides) aligned to the sun’s
orientation.
95
Figure 4.1
Figure 4.2
Lower ground plan, ground floor plan and 1st floor plan of Subang Parade.
Perspective showing front, right and left elevation of Subang Parade.
96
N
Figure 4.3
Location plan & openings to side-lit atrium of Subang Parade.
Openings in Subang Parade consist of side-lit atrium, top-lit atrium, fixed
windows and display windows. Side-lit atrium is located throughout the stretch of the
building at first floor (refer Figure 4.3). The side lit atrium uses a 3m high fixed glass
opening which spans throughout the building. The top-lit atriums are located at both
ends of the building furnished with fixed glass windows. Both top-lit atriums use
spaceframe tubular steel structure to hold the fixed glass. The size of the top-lit
atrium is 6m long and 3m wide with the height of 1.5m. The design of the building
implemented fixed glass windows with the size of 1m by 1m commonly used
throughout all floors. These windows are positioned 2.5 m from the floor. Selected
retailers such as Dome, Pet’s Wonderland, TGI Fridays and Giordano located at
ground floor made renovations and implemented ceiling height display windows.
Restaurants such as Esquire Kitchen and Sate Yanti located at lower ground floor
also used ceiling height display windows.
97
Figure 4.4
Figure 4.5
View of side-lit atrium from inside.
Top-lit atrium at Subang Parade
Subang Parade uses both artificial lighting and daylighting. Daylighting in
Subang Parade is contributed by openings such as atriums, fixed windows and
display windows. Atriums used in the building consist of top-lit atrium and side-lit
atrium. The side-lit atrium is located at the center of the building. The length of sidelit atrium as long as Subang Parade. Daylight from the side-lit atrium contributes to
the lighting of the atrium area located in the center of the building (refer Figure 4.6).
Two top-lit atriums are located at the east wing and west wing. Both atriums are
located at the escalator area that connects each floor. The top-lit atrium at the east
wing is located within the anchor tenant which is Parkson (refer Figure 4.5). The
98
other top-lit atrium is located at the west wing. Both top-lit atriums are able to bring
in daylight from the 1st floor until the lower ground floor (refer Figure 4.6).
Figure 4.6
Top-lit atrium at west wing of Subang Parade
Artificial lighting such as tungsten halogen lamps located at ceiling level
functions as the main lighting system. Incandescent downlights and incandescent
uplights is used throughout the building as a secondary lighting system. The main
and secondary lighting system operates from 10am untill 10pm. Shoplots uses a
combination of incandescent downlights and fluorescent lamps. LED and decorative
lights are also used by these shoplots as signages. Artificial lighting from shoplots
act as the tertiary lighting system. It operates concurrent with the operational hours
of each respective shop which differs from one another.
99
Tungsten halogen
Incandescent downlight
LED/decorative lights
Incandescent
uplight
Figure 4.7
Types of artificial light used at Subang Parade
Patrons of Subang Parade experience an unobstructed field of view. The
design of the main circulation area which is located at the center of the building,
which does not have any obstruction, contributes to an unobstruced field of view
(refer Figure 4.7). The building layout that locates shoplots on the periphery of the
centralized circulation area also contributes to an unobstructed field of view.
4.1.2
Summit USJ
Summit USJ is located at USJ 2/2 along Jalan Kewajipan of Subang Jaya. It
is geographically located at latitude (3.0605 degrees) 3° 3' 37" North of the Equator
and longitude (101.5934 degrees) 101° 35' 36" East of the Prime Meridian on the
Map of Kuala Lumpur. The Summit Subang USJ is located at the southern end of
Subang Jaya. It has an amount of 800,000 square feet of retail space. The occupant of
the building consist of Fajar Supermarket as the main anchor tenant and 418 other
specialty tenants ranging from food vendors to educational facilities. Tenants of
Summit USJ are England Optical, McDonald’s, Starbucks Coffee, Fitness First,
100
Popular Bookstore, MSC College, Prime College and Golden Screen Cinema to
name a few.
Figure 4.8
Floor plans of Summit USJ- lower ground to second floor
101
Figure 4.9
Floor plans of Summit USJ- third to fourth floor
The Summit USJ is a shopping complex with 6 levels of shopping area and a
basement car park. The building has an L-shape form. The average floor to ceiling
height for all floors are 4m. The internal circulation is located at the center of the
building as seen at lower ground and ground floor level. However, shoplots are
placed in the middle of the circulation area at first, second, third and fourth floor
(refer Picture 4.7). An atrium located at the center of the building devides the
building to two wings. Floors are connected by escalators and elevators. The building
orientation is almost parallel to the North-South orientation. The largest surface of
the building is the front and rear elevation which faces the morning and the evening
sun.
N
Figure 4.10
Location plan & main entrance to Summit USJ.
102
Figure 4.11
Perspective showing left, right and front elevation of Summit USJ.
There are very little openings in Summit USJ. The front elevation of the
ground floor is the only area that has large openings. The area used ceiling height
fixed glass display windows. However, the display window is recessed 8m from the
floor above. Openings at other floors consist of rectangular fixed windows. Almost
all of the windows are covered with blinds by shop owners. Through observation,
nearly 80% of the building’s surface is covered.
Summit USJ uses artificial lighting throughout the building. Artificial
lighting such as incandescent downlights acts as the primary lighting system
throughout all floors. Ground floor level has been equipped with concealed
incandescent light located at the celing (refer Picture 4.11). It operates from 10am
untill 10pm. Shoplots uses a combination of incandescent downlights and fluorescent
lamps. LED and decorative lights are also used by these shoplots as signages.
Artificial lighting from shoplots act as a complimentary lighting system. It operates
concurrent with the operational hours of each respective shop which differs from one
another.
103
Figure 4.12
Incandescent downlights on typical floor and concealed incandescent
light at ground floor level.
Patrons of Summit USJ do not experience unobstructed field of view. This is
due to the design of shoplots that are located in between circulation areas (refer
Picture 4.7 & 4.8). The layout introduces corners and dead ends that prohibits light
from reaching further into the building. Therefore, more lighting apperture is needed
to light dark corners.
4.2
Description of data
This section will discuss on data obtained from Subang Parade and Summit
USJ. Data consist of pictures taken from Subang Parade and Summit USJ showing
luminance level indicated at the bottom end of each picture and patronage count. The
data will be discussed in 3 subtopics which consist of daylight component study,
pattern of light distribution study and patronage study.
104
4.2.1 Subang Parade
The following are pictures of Subang Parade taken during the day. Pictures
are taken from the same point but at two different time frames (day and night). The
average luminance level is indicated at the bottom end of each picture.
Figure 4.13
Luminance level of pictures taken at Subang Parade – 1st floor
105
86.631 DN
83.823 DN
93.804 DN
105.876 DN
97.273 DN
86.691 DN
Figure 4.13
Luminance level of pictures taken at Subang Parade – 1st floor
106
Ground floor - Subang Parade
93.826 DN
166.822 DN
137.844 DN
67.722 DN
77.573 DN
87.704 DN
86.92 DN
86.698 DN
143.811 DN
107
122.515 DN
89.361 DN
89.106 DN
80.537 DN
Figure 4.14
90.689 DN
Luminance level of pictures taken at Subang Parade – Ground floor
108
Lower ground floor - Subang Parade
157.112 DN
81.178 DN
97.077 DN
86.981 DN
73.209 DN
73.209 DN
76.008 DN
109
77.577 DN
187.493 DN
77.169 DN
132.28 DN
73.801 DN
94.846 DN
110
95.829 DN
57.756 DN
Figure 4.15
115.479 DN
82.972 DN
69.806 DN
Luminance level of pictures taken at Subang Parade – Lower ground floor
3.083 DN
46 DN 83.083 DN
111
82.972 DN
56.876 DN
The first floor level of Subang Parade is the brightest compared to its ground
and lower ground floor. This is due to contributing daylight from the side-lit atrium
that spans throughout the building. All of the main circulation area are lit with
daylight and artificial light (refer Figure 4.13). The ground floor area is the second
brightest. Daylight is introduced into the building by fixed glass window display and
glass door entrances/exits. Visitors can easily identify an entrance because it is well
lit. Top-lit atriums located at the east and west wing also contributes to daylight.
Escalators positioned within top-lit atriums can be easily found since it is also well lit
(refer Figure 4.14). The lower ground floor demonstrates a higher dependence
towards artificial lighting. This is due to the lack of openings to allow daylight.
Usage of fixed glass window display at two restaurants at this level brings in
daylight. Secondary entrances/exits also allow daylighting into the building. Daylight
from the side-lit atria does reach the lower ground floor area.
The schedule below indicates locations of pictures taken and a comparison of
luminance level readings during the day and night. Each value represents the average
luminance value from each photo.
Table 4.1
Table below indicates luminance value of Subang Parade – 1st floor
Subang Parade (locations)
1st
Floor
Toilet facing Toys 'R' Us
Lift facing Optic Subang
Fitness Concept facing Cellini
Yamaha looking upwards
Hair salon facing upwards
Parkson facing hair salon
Subang Parade office facing
upwards
House of Leather facing Yamaha
Little Egypt facing Toys 'R' Us
Escalator facing Subang Furnishing
Dynasty facing Toys 'R' Us
Dynasty facing Cellini
Lyli handicraft facing Cellini
GDO facing Yamaha
BCB facing hair salon
Day
Night
143.027
73.737
78.447
89.071
87.65
83.083
42.316
52.106
42.558
39.197
42.376
21.913
73.864
110.301
93.76
86.631
83.823
93.804
105.876
97.273
86.691
41.242
43.984
44.788
41.95
58.185
47.748
34.913
50.139
30.608
112
Table 4.2
G.Floor
Lower
Ground
Table below indicates luminance value of Subang Parade – Ground
floor and lower ground floor.
Main entrance facing inwards
FOS facing Bata
Bata facing FOS
Ramp facing Daves Deli
MPH facing Daves Deli
Bonia facing Dome
Wings facing Parkson
Coca facing MAA
Entrance facing McDonalds
Digi facing TGI
Startel facing Bonia
Tropical Blues facing Daves Deli
Uncle Lim's facing entrance
House of Leather facing NS
collection
Blush facing Secret Recipe
Royal Selangor facing HSL
Nail Trend facing Delifrance
RHB facing Skaf and Kraf
RHB facing Chicken Rice Shop
Chicken Rice Shop facing Bata
Kenny Rogers facing Nandos
Nandos facing McDonalds
McDonalds facing bubble lift
McDonalds facing Nandos
Memory Lane facing McDonalds
Rasa Thai facing McDonalds
City Chain facing McDonalds
City Chain facing Voir
Voir facing Rasa Thai
McDonalds alley facing Baskin
Robbins
McDonalds alley facing toilet
Cobbler facing Chicken Rice Shop
Grand total
Grand average
Thus, daylight value
93.826
166.882
137.844
67.722
77.573
87.704
86.92
86.698
143.811
122.515
89.361
90.689
89.106
64.567
99.661
66.887
38.985
51.019
44.857
44.992
41.958
71.471
69.299
57.599
54.199
34.511
80.537
157.112
94.816
81.178
86.981
78.176
73.209
76.008
77.577
73.801
77.169
187.493
132.28
94.846
95.829
115.479
48.839
86.423
97.077
65.806
55.213
54.267
55.671
62.287
59.921
45.071
57.661
62.056
74.669
45.145
62.593
88.506
82.972
57.756
69.802
56.876
44.324
26.869
4520.71
96.19
2523.302
53.69
42.5
The daylight component value has been acquired using ERDAS. Each picture
is processed with the use of the program. ERDAS gives out readings on luminance
level based on each pixel that makes the picture. The values for each picture (as
shown in the schedule) represent the average luminance level. At the end of the
113
schedule, a grand average of the luminance level is achieved. Finally, the daylight
component value is acquired by subtracting the average luminance value during the
day with the average luminance value during the night. The daylight component
value for Subang Parade is 42.5 DN (refer Table 4.2). 1
Pattern of light distribution for daylight in Subang Parade is influenced by the
shape of the openings. Light distribution pattern for artificial lighting is affected by
the usage of tungsten halogen lamps which provides ambient lighting and
incandescent down lights with reflective surface backing. Observation of light
distribution pattern is further discussed in schedule below.
Table 4.3
Pattern of light distribution at 1st floor of Subang Parade
Picture location – 1st Floor
Pattern of light distribution
The left area of the picture is brighter
compared to the right area. The brightest
area is the top-left area which is closest
to the side-lit atrium. The darkest area
would be the area closest to the shoplots.
93.76 DN
The middle area of the picture is brighter
compared to the left and right area. The
brightest area is the top area where the
side-lit atrium is located.
86.691 DN
1
DN or digital numbers is a value that gauges light intensity level in a picture when processed using
ERDAS and is equivalent to value of luminance level.
114
Table 4.4
Pattern of light distribution at ground floor and lower ground
floor of Subang Parade.
Picture location – Ground Floor
Pattern of light distribution
The main entrance located in the middle
of the picture is the brightest area. Sidelit atrium located at the upper right end
has a diffused daylight effect. The lower
end of the picture has the least light
component.
122.515 DN
The middle area of the picture is the
brightest compared to other areas. This is
due to the top-lit atrium above the
escalator. Surrounding areas that uses
incandescent
downlights
are
significantly darker compared to the
escalator area.
137.844 DN
Picture location – Lower Ground Floor
Pattern of light distribution
The escalator area is the brightest
compared to its surrounding. White
coloured floor tiles reflect light
throughout the area.
157.112 DN
The middle area of the picture is
significantly darker compared to the
right and left area. The right area is
brightest due to daylight coming from
glass display windows.
94.846 DN
115
Patronage count locations for Subang Parade consist of City Chain (1),
McDonalds (2), Chicken Rice Shop (3) and Giordano (4) (refer plan below). These
locations have been selected for the checkpoint of patronage count since it covers the
entire floor and divides the building evenly. Based on observation, these locations
are considered busiest points and suitable for the patronage count.
Figure 4.16
Plan indicating patronage count checkpoints of Subang Parade.
116
Data of patronage count for Subang Parade is shown in the schedule below (refer
Table 4.4). The numbers indicate people count.
Table 4.5
Table showing patronage count for Subang Parade.
Location
Time
11am - 11.30 am
1 pm - 1.30 pm
3 pm - 3.30 pm
5.30 pm - 6 pm
Total
4.2.2
City
Chain
McDonalds
279
760
309
342
1690
152
643
387
484
1666
Giordano
243
712
304
261
1520
Chicken Rice
Shop
395
673
313
357
1738
Summit USJ
Below are pictures of Summit USJ taken during the day. Pictures are taken
from the same point but at two different time frames (day and night). Average
luminance level is indicated in each picture.
Third floor – Summit USJ
37.694 DN
30.51 DN
37.742 DN
41.089 DN
50.415 DN
44.905 DN
37.824 DN
36.805 DN
Figure 4.17
Luminance level of pictures taken at Summit USJ – 3rd floor
Second floor -Summit USJ
90.285 DN
45.5 DN
44.428 DN
66.527 DN
41.864 DN
55.088 DN
77.184 DN
59.966 DN
52.117 DN
Figure 4.18
Luminance level of pictures taken at Summit USJ – 2nd floor
52.306 DN
First floor – Summit USJ
65.001 DN
80.54 DN
77.795 DN
79.739 DN
70.889 DN
84.045 DN
71.354 DN
51.89 DN
71.924 DN
85.538 DN
Figure 4.19
Luminance level of pictures taken at Summit USJ – First floor
Ground floor – Summit USJ
83.953 DN
125.139 DN
97.131 DN
102.432 DN
91.489 DN
94.838 DN
88.551 DN
102.644 DN
80.874 DN
Figure 4.20 Luminance level of pictures taken at Summit USJ – Ground floor
79.985 DN
Lower ground floor – Summit USJ
86.059 DN
107.013 DN
86.42 DN
92.487 DN
70.789 DN
76.511 DN
72.116 DN
Figure 4.21
102.418 DN
76.306 DN
Luminance level of pictures taken at Summit USJ – lower ground floor
124
Summit USJ has 6 levels of shopping area which uses artificial lighting
system. However, the fourth floor is not included in the research because the level
was closed during the duration of the research. The third floor uses recessed
incandescent uplights embedded in the suspended ceiling as its main lighting system.
This indirect lighting results in a very dark ambience (refer Figure 4.17). The second
and first floor level uses incandescent downlight embedded in the suspended ceiling.
More downlights is used in both floors resulting to a brighter environment compared
to the third floor. Openings such as glass window display and the main entrance
allows daylight to light the building at ground floor level. The ground floor is the
brightest in comparison to other floors because it equipped with recessed uplights
and downlight on the suspended ceiling throughout the floor. The lower ground floor
which uses a combination of recessed downlights and uplights is slightly darker in
comparison to the ground floor area. Daylight can only be seen at ground floor level
only. Fixed windows located at other floors are covered too avoid daylight from
coming in. In short, Summit USJ relies fully on artificial lighting. The schedule
below indicates locations of pictures taken and a comparison of luminance level
readings during the day and night. Each value represents the average luminance
value from each photo.
Table 4.6
3rd Floor
2nd Floor
Table showing patronage count for Summit USJ.
Summit Subang USJ (locations)
GSC facing snooker
Snooker facing GSC
South Precint facing North Precinct
Central Precinct facing North Precinct
Central Precinct facing exit
Central Precinct facing South Precinct
College facing elevator
Chinese Fellowship facing SongBox
GalaxCon facing foodcourt
Best Value facing Central Precinct
Asam shop facing podium
Corporate training centre facing asam
shop
Corporate training centre facing podium
Podium facing South Precinct
South Precint facing podium
South Precinct facing Fajar
Fajar facing Salvation
Summer Bee facing elevator
Day
37.694
30.51
37.742
41.089
50.415
44.905
37.824
36.805
90.285
66.527
77.184
Night
38.337
37.244
51.073
42.926
52.338
34.321
36.74
34.608
50.464
47.115
71.184
45.5
41.864
59.966
44.428
55.088
52.117
52.306
40.589
36.475
51.31
27.351
51.948
40.618
43.922
125
1st Floor
G.Floor
L.G Floor
Dermalogica facing elevator
MK Fashion facing Fajar
Greenland facing Elevator
Elevator facing Central Precinct
Cosmax facing antique shop
Cosmax facing Perintis
Soft World facing Smart Master
Nakashima facing podium
Podium facing bazaar
Live facing bazaar
Sweeties facing Central Precinct
Honey Gal facing Sweeties
Art gallery facing Central Precinct
Lo Hong facing Central Precinct
Century facing Central Precinct
England Optical facing Sri Sentosa
Sri Sentosa facing Fajar
Jutawan Edar facing bazaar
Abuza facing coloured tiles
Coloured tiles facing Abuza
65.001
77.795
70.889
80.54
79.739
84.045
71.354
51.89
71.924
85.538
83.953
125.139
88.551
97.131
102.432
102.644
91.489
94.838
80.874
79.985
60.48
64.025
57.152
79.711
77.689
94.832
77.645
59.3
65.017
71.855
77.253
114.263
90.175
98.341
88.528
91.49
100.103
86.07
71.032
83.699
McDonalds facing Ramen
Ramen facing McDonalds
Teppanyaki facing Penang Asam
House
Exit facing Teppanyaki
Fajar facing 1901
Lazo Diamond facing Ayamas
ATM exit facing Johnny's
McBytes facing Kyros Kebab
Asam shop facing Poh Kong
86.059
107.013
78.409
74.778
70.789
86.42
92.487
76.511
72.116
102.418
76.306
83.429
76.829
82.179
86.017
60.899
96.836
72.943
Grand total
Grand average
3358.119
71.45
3109.42
66.16
Thus, daylight value
5.29
126
Pattern of light distribution for Summit USJ is determined by its artificial
lighting. Light distribution pattern for artificial lighting is affected by the usage of
incandescent downlights with reflective surface backing and incandescent uplights
recessed in suspended ceilings. Observation of light distribution pattern is further
discussed in schedule below.
Table 4.7
Table showing pattern of light distribution for Summit USJ.
Picture location – 3rd Floor
Pattern of light distribution
Generally almost all of the area is dark.
The brightest area is the middle area
which has the recessed incandescent
uplight located in the suspended ceiling.
41.089 DN
The middle area of the picture is the
brightest compared to its surrounding.
Other light source includes signages on
the right and left area of the picture.
44.905 DN
127
Table 4.8
Table showing pattern of light distribution for Summit USJ.
Picture location – 2rd Floor
Pattern of light distribution
The centre area of the picture is the
darkest.
Light
from
recessed
incandescent downlights, shoplots and
signages makes the surrounding looks
bright.
90.285 DN
The circulation area located in the centre
is the darkest area. Downlights along the
circulation area is not as bright as
lighting from signages and surrounding
shoplots.
66.527 DN
Picture location – 1st Floor
Pattern of light distribution
Downlights and LED lights on the sides
of the escalator provide the lighting for
this area.
70.889 DN
The middle area of the picture is the
darkest compared to its surrounding.
Shoplots on the right and left side of the
circulation area is significantly brighter.
80.54 DN
128
Table 4.9
Table showing pattern of light distribution for Summit USJ.
Picture location – Ground Floor
Pattern of light distribution
The brightest area is the centre where all
the recessed downlight is located.
Lighting from surrounding shoplots
contributes to the ambience.
97.131 DN
The middle area of the picture is the
brightest compared to its surrounding.
102.644 DN
Picture location – Lower Ground Floor
Pattern of light distribution
The left side and middle side of the area
is the brightest. However, the low middle
area is darker. This is due to lack of
recessed incandescent downlight.
91.489 DN
The middle area of the picture is the
brightest compared to its surrounding.
The corridor is addressed well with the
lighting above.
94.838 DN
129
Patronage count locations for Summit Subang USJ consist of Starbucks (1),
ground floor concourse (2), McDonalds (3) and England Optical (4) (refer plan
below).
2
3
4
1
Figure 4.22
Plan indicating patronage count checkpoints at Summit
Data of patronage count for Summit Subang USJ is shown in the schedule below.
(numbers indicate people count)
Table 4.10
Table showing patronage count for Summit USJ.
Location
Starbucks
Time
11am - 11.30 am
1 pm - 1.30 pm
3 pm - 3.30 pm
5.30 pm - 6 pm
96
284
209
189
G.F
concourse
136
237
244
294
McDonalds
169
451
365
351
England Optical
146
411
302
372
130
4.3
Daylight component analysis
Comparing the mean value of daylight component for Subang Parade and
Summit USJ, it is found that Subang Parade has a higher value of daylight
component. Subang Parade’s daylight component value is 42.5 DN while Summit
USJ’s daylight component value is 5.29 DN. Subang Parade showed a difference of
37.21 DN in daylight component value. Through observation, large openings such as
the side-lit atrium and the top-lit atrium became the major contributor to daylight
component in Subang Parade. Lack of openings and blocked openings results to very
low penetration of daylight component in Summit USJ.
CHAPTER 5
BEHAVIORAL SURVEY STUDY
5.0
Introduction
The main research analysis established that shopping complex with higher
daylight component which was Subang Parade has higher amount of patronage
compared to shopping complex with a lower daylight component which was Summit
USJ. The aim of the survey is to verify the finding. The additional survey compares
the two factors that affect patronage. This consists of the factor of daylight and any
other factors other than daylight.
5.1
Survey set up
5.1.1
Sampling and questionnaire design
The researcher opted for simple random sampling method. Random sampling
has been used as this overcomes the issue of double counting of patrons. According
to Levin (1988), simple random sampling allow each possible sample to have an
132
equal probability of being picked and each item in the entire population to have an
equal chance of being included in the sample. The population of the survey is the
patron of Subang Parade. According to a survey done by Hectar Group (Hectar,
2008), the number of patrons visiting Subang Parade in a month is 177,795 people.
The researcher will only focus on daily patronage count due to limitation of time.
The average is 5900 patrons.
1
According to Sekaran (2001), the number of sample
must not be less than 6% from the population as to give a fair representation of the
population. As to represent the daily patronage of Subang Parade, the survey has
determined the sample size to be at least 354 people.
Questionnaire design is divided to 2 parts. The first part which is Part A is a
demographic study. The second part which is Part B consists of a series of 22
questions comparing 2 factors that affect patronage. These factors consist of daylight
in affecting patronage and factors other than that can affect patronage. The
questionnaire consists of 11 questions for each factor. The researcher referred to
literature review regarding factors affecting patronage in order to formulate survey
questions (refer Chapter 3.2.3). The researcher randomly selected 12 factors that
affect patronage. These factors consist of products offered, variety of tenants,
influence of current trends, socializing, bargain hunting, accessibility, friend’s
recommendation, customer service, sensory stimulation, creativity in interior
decoration and cleanliness. Literature review on the relation of human behaviour
towards light help formulate questions regarding the affect of daylight towards
influencing patronage (refer chapter 2.1.1). These factors consist of human sensory
response, preference towards level of brightness, duration of time spent in a bright
area, feeling of security in brightly lit areas and the ability of daylight in creating
ambience. A Likert scale is used as a marking scheme to gauge how strongly the
respondents feel about each question. Shown below (refer Table 5.1) is the sample of
the questionnaire.
1
Monthly number of patronage in Subang Parade which is 177,795 people is divided to 30 days in a
month as to find out the daily amount of patronage.
133
Table 5.1
Table showing survey on factors that affect patronage in Subang
Parade
134
5.1.2
Data collection
The survey is conducted in a day throughout Subang Parade. Questionnaires
are given to patrons of Subang Parade and the researcher attends to the patron while
he or she answers the questions. The duration of the survey is throughout Subang
Parade’s operational hours. The survey starts at 10 am and ends at 10pm. Five
research assistants helped with the survey. Research assistants are located at Subang
Parade’s entrances to conduct the survey. Survey papers are later processed using
SPSS programme. The SPSS programme is used to obtain the frequency of both
factors.
5.2
Survey finding and analysis
Data from the survey is processed into 22 frequency tables and 22 pie charts
illustrating frequency analysis for each question. Frequency table and pie chart for
each question is grouped together to show the finding of each question. The first 11
question consist of questions representing the first factor that affects patronage which
is daylight or light. The next 11 questions consist of questions representing the
second factor which is other factors that affect patronage apart of daylight/light.
Frequency tables and pie charts of each question will be reviewed and commented.
135
5.2.1
Analysis on questions representing daylight
Q1
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.1
Frequency
180
Percent
49.9
Valid Percent
49.9
Cumulative
Percent
49.9
127
35.2
35.2
85.0
44
12.2
12.2
97.2
100.0
10
2.8
2.8
361
100.0
100.0
Pie chart & schedule showing feedback for question 1
The first question asks about the importance of light in creating ambience.
Nearly 50% of Subang Parade’s patrons rated strongly agree that light plays an
important role in creating ambience followed by 35.2% agreeing to the matter. Only
15% of the entire sample rated ‘neither agree or disagree’ and ‘disagree’. More than
136
half of the patrons surveyed acknowledged that light do play a significant role in
creating ambience. None of the patrons felt ‘strongly disagree’ with the matter.
Q2
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.2
Frequency
167
Percent
46.3
Valid Percent
46.3
Cumulative
Percent
46.3
138
38.2
38.2
84.5
41
11.4
11.4
95.8
100.0
15
4.2
4.2
361
100.0
100.0
Pie chart & schedule showing feedback for question 2
On the preference whether shopping complexes should be bright, 46.3% rated
‘strongly agree’ followed by 38.2% which rated ‘agree’. Only a mere 11.4% of the
entire sample rated ‘neither agree nor disagree’ and 4.2% rated ‘disagree’. None of
the patrons felt ‘strongly disagree’ with the matter. From this survey, a total of 84.5%
of the entire sample felt that a shopping complex should be bright.
137
Q3
Strongly agree
Agree
Neither agree or
disagree
Disagree
Q3
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.3
Frequency
184
Percent
51.0
Valid Percent
51.0
Cumulative
Percent
51.0
106
29.4
29.4
80.3
62
17.2
17.2
97.5
100.0
9
2.5
2.5
361
100.0
100.0
Pie chart & schedule showing feedback for question 3
The third question is about the preference of shopping. It is found that 51% of
the patrons strongly preferred shopping in a bright shopping complex while 29.4%
also agree with the matter. Only a small portion of the sample disagrees with the
matter which is represented by 2.5%. On another note, 17.2 % rated ‘neither agree
nor disagree’. Most of the patrons prefer to shop in bright shopping complexes.
138
Q4
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Q4
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.4
Frequency
137
Percent
38.0
Valid Percent
38.0
Cumulative
Percent
38.0
138
38.2
38.2
76.2
64
17.7
17.7
93.9
18
5.0
5.0
98.9
4
1.1
1.1
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 4
The fourth question is about the preference of shopping during sales. It is
found that 38% of the patrons strongly preferred shopping during sales in a bright
shopping centre while 38.2% also agree with the matter. However, 5% of the patron
rated ‘disagree’ while another 1.1% rated ‘strongly disagree’. Apparently most of the
139
patrons prefer to shop during sales in bright shopping complexes which were
represented by a majority of 76.2%.
Q5
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.5
Frequency
161
Percent
44.6
Valid Percent
44.6
Cumulative
Percent
44.6
144
39.9
39.9
84.5
49
13.6
13.6
98.1
100.0
7
1.9
1.9
361
100.0
100.0
Pie chart & schedule showing feedback for question 5
On the preference which shopping complexes are more appealing, 44.6%
rated ‘strongly agree’ that shopping complexes that are bright is more appealing
followed by 39.9% which rated ‘agree’. Only a mere 13.6% of the entire sample
rated ‘neither agree nor disagree’ and 1.9% rated ‘disagree’. None of the patrons felt
‘strongly disagree’ with the matter. From this survey, a total of 84.5% of the entire
sample felt that shopping complexes that are bright is more appealing.
140
Q6
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.6
Frequency
120
Percent
33.2
Valid Percent
33.2
Cumulative
Percent
33.2
140
38.8
38.8
72.0
77
21.3
21.3
93.4
24
6.6
6.6
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 6
On the preference of the duration of time spent in a bright shopping complex,
33.2% rated ‘strongly agree’ to spend a longer time in a bright shopping complex
followed by 38.8% which rated ‘agree’. An amount of 21.3% of the entire sample
rated ‘neither agree nor disagree’ and 6.6% rated ‘disagree’. None of the patrons felt
‘strongly disagree’ with the matter. From this survey, a total of 67% of the entire
sample agree on spending more time in a bright shopping complex.
141
Q7
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.7
Frequency
151
Percent
41.8
Valid Percent
41.8
Cumulative
Percent
41.8
100
27.7
27.7
69.5
97
26.9
26.9
96.4
100.0
13
3.6
3.6
361
100.0
100.0
Pie chart & schedule showing feedback for question 7
The seventh question looks into the preference of experiencing ambience in a
daylit shopping complex The sample showed that 41.8% rated ‘strongly agree’
followed by 27.7% which rated ‘agree’. An amount of 26.9% of the entire sample
rated ‘neither agree nor disagree’ and 3.6% rated ‘disagree’. None of the patrons felt
‘strongly disagree’ with the matter. From this survey, a total of 69.5% of the entire
sample likes to shop in a daylit shopping complex because of the ambience.
142
Q8
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.8
Frequency
84
Percent
23.3
Valid Percent
23.3
Cumulative
Percent
23.3
116
32.1
32.1
55.4
130
36.0
36.0
91.4
31
8.6
8.6
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 8
On the influence of shopping in bright shopping complexes, the sample
showed that 23.3% rated ‘strongly agree’ followed by 32.1% which rated ‘agree’. An
amount of 36% of the entire sample rated ‘neither agree nor disagree’ and 8.6% rated
‘disagree’. None of the patrons felt ‘strongly disagree’ with the matter. From this
survey, a total of 55.4% of the entire sample felt that bright shopping complexes
make them shop more.
143
Q9
Strongly agree
Agree
Neither agree or
disagree
Disagree
Valid
Strongly agree
Frequency
174
Percent
48.2
Valid Percent
48.2
Cumulative
Percent
48.2
120
33.2
33.2
81.4
59
16.3
16.3
97.8
100.0
Agree
Neither agree or
disagree
Disagree
Total
Figure 5.9
8
2.2
2.2
361
100.0
100.0
Pie chart & schedule showing feedback for question 9
The ninth question looks into how safe patrons feel in a bright shopping
complex. The sample showed that 48.2% rated ‘strongly agree’ followed by 33.2%
which rated ‘agree’. An amount of 16.3% of the entire sample rated ‘neither agree
nor disagree’ and 2.2% rated ‘disagree’. None of the patrons felt ‘strongly disagree’
with the matter. From this survey, a total of 81.4% of the entire sample felt safer in
shopping complexes that are bright.
144
Q10
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.10
Frequency
7
Percent
1.9
Valid Percent
1.9
Cumulative
Percent
1.9
9
2.5
2.5
4.4
61
16.9
16.9
21.3
192
53.2
53.2
74.5
92
25.5
25.5
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 10
The tenth question looks into the preference of patrons on the frequency of
shopping in a dark shopping complex. The sample showed that 1.9% rated ‘strongly
agree’ followed by 2.5% which rated ‘agree’. An amount of 16.9% of the entire
sample rated ‘neither agree nor disagree’ and while a majority of 53.2% rated
‘disagree’. Furthermore, 25.5% of the sample rated ‘strongly disagree’ with the
matter. From this survey, only a total of 4.4% of the entire sample frequent shopping
145
complexes that are dark. This clearly shows that patrons of Subang Parade do not
frequent dark shopping complexes.
Q11
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.11
Frequency
4
Percent
1.1
Valid Percent
1.1
Cumulative
Percent
1.1
13
3.6
3.6
4.7
40
11.1
11.1
15.8
137
38.0
38.0
53.7
167
46.3
46.3
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 11
The eleventh question looks into the preference of patrons in shopping in
dark or a bright shopping complex. The sample showed that 1.1% rated ‘strongly
agree’ followed by 3.6% which rated ‘agree’. An amount of 11.1% of the entire
sample rated ‘neither agree nor disagree’ and while 38% rated ‘disagree’. A majority
of 46.3% of the sample rated ‘strongly disagree’ with the matter. From this survey, a
total of 4.7% of the entire sample prefer shopping in dark shopping complexes This
clearly shows that patrons of Subang Parade do not prefer to shop in dark shopping
complexes.
146
5.2.2
Analysis on questions representing other factors
Q12
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.12
Frequency
31
Percent
8.6
Valid Percent
8.6
Cumulative
Percent
8.6
125
34.6
34.6
43.2
127
35.2
35.2
78.4
57
15.8
15.8
94.2
21
5.8
5.8
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 12
On the influence of shopping in Subang Parade for the products offered, an
amount of 8.6% rated ‘strongly agree’ followed by 34.6% which rated ‘agree’. An
amount of 35.2% of the entire sample rated ‘neither agree nor disagree’ while 15.8%
rated ‘disagree’. A small number of patrons with a total of 5.8% felt ‘strongly
147
disagree’ with the matter. From this survey, it is found that majority of patrons
neither agrees nor disagrees about wanting to shop in Subang Parade for its wide
range of products. Only 43.2% of patrons are drawn to shop in Subang Parade for its
wide range of products. Therefore, patrons are not influenced to shop in Subang
Parade in reference to the products offered.
Q13
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.13
Frequency
34
Percent
9.4
Valid Percent
9.4
Cumulative
Percent
9.4
129
35.7
35.7
45.2
104
28.8
28.8
74.0
74
20.5
20.5
94.5
20
5.5
5.5
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 13
On the influence of shopping in Subang Parade for the variety of tenants, an
amount of 9.4% rated ‘strongly agree’ followed by 35.7% which rated ‘agree’. An
148
amount of 28.8% of the entire sample rated ‘neither agree nor disagree’ while 20.5%
rated ‘disagree’. A small number of patrons with a total of 5.5% felt ‘strongly
disagree’ with the matter. From this survey, it is found that the minority of patrons
which amounts to 45.2% of the sample, shop at Subang Parade for its variety of
tenants. This is less than half of the entire population. Therefore, patrons are not
influenced to shop in Subang Parade in reference to the variety of tenants.
Q14
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.14
Frequency
42
Percent
11.6
Valid Percent
11.6
Cumulative
Percent
11.6
94
26.0
26.0
37.7
108
29.9
29.9
67.6
90
24.9
24.9
92.5
27
7.5
7.5
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 14
Question fourteenth looks into the influence of shopping in Subang Parade
for fashion trends. An amount of 11.6% rated ‘strongly agree’ followed by 26%
149
which rated ‘agree’. An amount of 29.9% of the entire sample rated ‘neither agree
nor disagree’ while 24.9% rated ‘disagree’. A small number of patrons with a total of
7.5% felt ‘strongly disagree’ with the matter. From this survey, it is found that the
minority of patrons which amounts to 49.3% of the sample, shop at Subang Parade in
search of new trends. Therefore, patrons are not influenced to shop in Subang Parade
in reference to providing trends.
Q15
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.15
Frequency
84
Percent
23.3
Valid Percent
23.3
Cumulative
Percent
23.3
116
32.1
32.1
55.4
57
15.8
15.8
71.2
72
19.9
19.9
91.1
32
8.9
8.9
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 15
150
Question fifteenth looks into the preference of patrons in spending time with
friends in Subang Parade. An amount of 23.3% rated ‘strongly agree’ followed by
32.1% which rated ‘agree’. An amount of 15.8% of the entire sample rated ‘neither
agree nor disagree’ while 19.9% rated ‘disagree’. A small number of patrons with a
total of 8.9% felt ‘strongly disagree’ with the matter. From this survey, it is found
that majority of patrons which amounts to 55.4% of the sample like to spend time
with their friends in Subang Parade. Therefore, patrons are influenced to shop in
Subang Parade in reference to socializing.
Q16
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.16
Frequency
29
Percent
8.0
Valid Percent
8.0
Cumulative
Percent
8.0
65
18.0
18.0
26.0
132
36.6
36.6
62.6
118
32.7
32.7
95.3
17
4.7
4.7
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 16
151
On the influence of shopping in Subang Parade for bargain hunt, an amount
of 8% rated ‘strongly agree’ followed by 18% which rated ‘agree’. An amount of
36.6% of the entire sample rated ‘neither agree nor disagree’ while 32.7% rated
‘disagree’. A small number of patrons with a total of 4.7% felt ‘strongly disagree’
with the matter. From this survey, it is found that the minority of patrons which
amounts to 26% of the sample like to shop in Subang Parade for bargain hunting.
Majority of patrons neither agree nor disagree while 32.7% disagree that Subang
Parade is a good place to bargain hunt. Therefore, patrons are not influenced to shop
in Subang Parade in reference to bargain hunting.
Q17
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.17
Frequency
99
Percent
27.4
Valid Percent
27.4
Cumulative
Percent
27.4
110
30.5
30.5
57.9
85
23.5
23.5
81.4
49
13.6
13.6
95.0
18
5.0
5.0
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 17
152
On the influence of shopping in Subang Parade for the ease of access, an
amount of 27.4% rated ‘strongly agree’ followed by 30.5% which rated ‘agree’. An
amount of 23.5% of the entire sample rated ‘neither agree nor disagree’ while 13.6%
rated ‘disagree’. A small number of patrons with a total of 5% felt ‘strongly disagree’
with the matter. From this survey, it is found that the majority of patrons which
amounts to 57.9% of the sample like to shop in Subang Parade for the easy access.
Therefore, patrons are influenced to shop in Subang Parade in reference to
accessibility.
Q18
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Frequency
Valid
Percent
Valid Percent
Cumulative
Percent
Strongly agree
57
15.8
15.8
15.8
Agree
80
22.2
22.2
38.0
98
27.1
27.1
65.1
100
27.7
27.7
92.8
26
7.2
7.2
100.0
361
100.0
100.0
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.18
Pie chart & schedule showing feedback for question 18
153
On the influence of shopping in Subang Parade due to a friend’s
recommendation, an amount of 15.8% rated ‘strongly agree’ followed by 22.2%
which rated ‘agree’. An amount of 27.1% of the entire sample rated ‘neither agree
nor disagree’ while 27.7% rated ‘disagree’. A small number of patrons with a total of
7.2% felt ‘strongly disagree’ with the matter. From this survey, it is found that the
minority of patrons which amounts to 38% of the sample like to shop in Subang
Parade due to a friend’s recommendation. Therefore, patrons are not influenced to
shop in Subang Parade in reference to friend’s recommendation.
Q19
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.19
Frequency
33
Percent
9.1
Valid Percent
9.1
Cumulative
Percent
9.1
82
22.7
22.7
31.9
150
41.6
41.6
73.4
71
19.7
19.7
93.1
25
6.9
6.9
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 19
154
On the influence of shopping in Subang Parade due to the good customer
service, an amount of 9.1% rated ‘strongly agree’ followed by 22.7% which rated
‘agree’. An amount of 41.6% of the entire sample rated ‘neither agree nor disagree’
while 19.7% rated ‘disagree’. A small number of patrons with a total of 6.9% felt
‘strongly disagree’ with the matter. From this survey, it is found that the minority of
patrons which amounts to 31.9% of the sample like to shop in Subang Parade due to
the good customer service. Most patrons with the amount of 41.6% neither disagree
nor agree and 19.7% disagree with the statement. Therefore, patrons are not
influenced to shop in Subang Parade in reference to good customer service.
Q20
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.20
Frequency
44
Percent
12.2
Valid Percent
12.2
Cumulative
Percent
12.2
103
28.5
28.5
40.7
136
37.7
37.7
78.4
58
16.1
16.1
94.5
20
5.5
5.5
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 20
155
On the influence of shopping in Subang Parade due to the ability of trying out
merchandise, an amount of 12.1% rated ‘strongly agree’ followed by 28.5% which
rated ‘agree’. An amount of 37.7% of the entire sample rated ‘neither agree nor
disagree’ while 16.1% rated ‘disagree’. A small number of patrons with a total of
5.5% felt ‘strongly disagree’ with the matter. From this survey, it is found that the
minority of patrons which amounts to 40.7% of the sample like to shop in Subang
Parade due to the ability of trying out merchandise. Most patrons with the amount of
37.7% neither disagree nor agree and 16.1% disagree with the statement. Therefore,
patrons are not influenced to shop in Subang Parade in reference to the ability to try
out merchandise which is a form of sensory stimulation.
Q21
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Valid
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.21
Frequency
35
Percent
9.7
Valid Percent
9.7
Cumulative
Percent
9.7
121
33.5
33.5
43.2
120
33.2
33.2
76.5
67
18.6
18.6
95.0
18
5.0
5.0
100.0
361
100.0
100.0
Pie chart & schedule showing feedback for question 21
156
On the influence of shopping in Subang Parade due to the nicely decorated
interior and decoration, an amount of 9.7% rated ‘strongly agree’ followed by 33.5%
which rated ‘agree’. An amount of 33.2% of the entire sample rated ‘neither agree
nor disagree’ while 18.6% rated ‘disagree’. A small number of patrons with a total of
5% felt ‘strongly disagree’ with the matter. From this survey, it is found that the
minority of patrons which amounts to 43.2% of the sample like to shop in Subang
Parade due to the nicely decorated interior and decoration. Therefore, patrons are not
influenced to shop in Subang Parade in reference to the creativity in the interior and
decoration.
Q22
Strongly agree
Agree
Neither agree or
disagree
Disagree
Strongly disagree
Frequency
Valid
Percent
Valid Percent
Cumulative
Percent
Strongly agree
48
13.3
13.3
13.3
Agree
88
24.4
24.4
37.7
173
47.9
47.9
85.6
33
9.1
9.1
94.7
19
5.3
5.3
100.0
361
100.0
100.0
Neither agree or
disagree
Disagree
Strongly
disagree
Total
Figure 5.22
Pie chart & schedule showing feedback for question 22
157
On the influence of shopping in Subang Parade due to the state of its
cleanliness, an amount of 13.3% rated ‘strongly agree’ followed by 24.4% which
rated ‘agree’. An amount of 47.9% of the entire sample rated ‘neither agree nor
disagree’ while 9.1% rated ‘disagree’. A small number of patrons with a total of
5.3% felt ‘strongly disagree’ with the matter. From this survey, it is found that the
minority of patrons which amounts to 37.7% of the sample like to shop in Subang
Parade due to its cleanliness. Therefore, patrons are not influenced to shop in Subang
Parade in reference to the state of cleanliness.
5.2.3
Conclusion
In reference to the analysis of questions representing the factor of daylight in
affecting patronage, it is evident that the majority of Subang Parade’s patron
responds positively towards the importance of daylight in a shopping complex. A
total of 85% of patrons agreed that light plays an important role in creating ambience
while 84.5% felt that commercial centres should be bright. An amount of 80.3% of
patrons preferred shopping in bright shopping complexes while 76.2% preferred to
shop during sales in a bright shopping centre. A collection of 84.5% felt that
shopping centres that are bright is more appealing while 72% felt that they like to
spend more time in bright shopping centres. An amount of 69.5% of the sample
would go shopping in shopping complexes with daylight because of the ambience
they experience. However, only 55.5% agrees that bright shopping complex made
them shop more. 81.9% of patrons felt safer in bright shopping complexes. Only
4.4% of patron frequent shopping in dark shopping complexes while 4.7% of patron
preferred shopping in dark shopping complexes instead of bright ones.
Feedback of patrons on other factors that might affect patronage in Subang
Parade yielded weak reviews. Most of the feedback was unable to achieve a 51%
majority. Only 43.2% of patrons are drawn to shop in Subang Parade for its wide
range of products. From this survey, it is found that only 45.2% of the sample shop at
Subang Parade for its variety of tenants. In reference to the power of Subang Parade
57.756 DN
37.694 DN
158
in attracting patrons due to its latest trends, only 37.7% agreed to the matter.
However, it is found that majority of patrons which amounts to 55.4% of the sample
like to spend time with their friends in Subang Parade. The power of Subang
Parade’s attraction in its bargain hunting only scored 26% out of the entire sample. In
reference to patron’s likeliness in visiting Subang Parade due to its accessibility,
57.9% of the sample agreed to this statement. Friend’s recommendation as a factor
on influencing patrons to Subang Parade only scored 38% while only 31.9% of the
entire sample is attracted to Subang Parade due to its good customer service.
Only 40.7% of patrons are drawn to shop in Subang Parade because they are
allowed to try out the merchandise. 43.2% of patrons frequent Subang Parade for its
nicely and creatively built interior and decoration. However only 37.7% of patron
feels that they frequent Subang Parade because it’s well kept and clean.
In the end of this exercise, it is fair to conclude that daylight does give a
stronger affect on patronage in Subang Parade. The positive response of patrons
towards daylight in Subang Parade suggests that shopping complex with higher
daylight component is capable of attracting a higher amount of patronage. This
conclusion will also substantiate the research’s main analysis findings.
CHAPTER 6
CONCLUSION AND RESEARCH METHODOLOGY REVIEW
6.0
Introduction
The chapter is divided to 3 sections:
(a) Conclusion of research
(b) Review of research methodology
(c) Recommendation for future research
This chapter begins with the conclusion of research. Next, the data analysis
review discusses on the outcome of the research analysis chapter, then followed by a
review on the research methodology. It further discusses on probable errors in the
methodology and how it could be rectified. The final section of this chapter is the
recommendations for future research. It discussed on probability of future researches
and suggestions on overcoming errors of research.
160
6.1
Conclusion of research
The research concludes that shopping complex with higher daylight
component attracts more patronage. The research analysis chapter has discovered
that shopping complex with higher daylight component (Subang Parade) yielded
higher amount of patronage as compared to shopping complex with lower daylight
component (Summit USJ). Behavioural survey study chapter also substantiates the
research analysis. The survey concluded that daylight gave a stronger affect towards
patronage compared to other factors. The research analysis and behavioural survey
study also validate the research hypothesis.
The research also concludes that research questions were answered. The first
enquires about other contributing factors that could affect patronage apart from
daylight. The research was able to identify other factors affecting patronage through
literature review. Literature review on other factors affecting patronage was obtained
from journals and books which discusses on shopping behaviour, psychology of
shoppers and motives of shopping. The second research question asks about the
methodology in finding out whether shopping complex with higher daylight
component attracts more patronage. The research methodology chapter has answered
this research question.
6.2
Review of research methodology
The building selection stage went through 4 options. The research had to use
the fourth option which is Riley’s Law of Retail Gravitation due to the failure of
other options of building selection. The pursuit of comparing 2 similar buildings but
with different lighting system application failed. This is due to the fact of inadequate
samples of shopping complexes that are similar. Through the building inventory, it is
161
found that all shopping complexes within Klang Valley have different design. The
ideal research scenario would be comparing 2 identical shopping complexes with
different lighting system (artificial and combination of daylight and artificial
lighting). The research requires the shopping complex to be identical as to control
variables or factors that attract patrons to a shopping complex. However, the research
selected Subang Parade and Summit USJ since it is the most similar to each other in
comparison to other shopping complexes in Klang Valley. Furthermore, Riley’s Law
of Retail Gravitation proves that these buildings are compatible to be compared
based on the retail trade analysis done (refer chapter 3.1.2).
In reference to the building selection, the research could have narrowed down
the scope of research. Two identical building but with different usage of lighting was
required for the research as to compare whether shopping complex with higher
daylight component attracts more customers. However, finding two identical
buildings with different lighting system proved difficult. Narrowing the scope of
research could be beneficial to the research as this will ease the building selection
process. The logic behind this is due to insufficient shopping complexes in Malaysia
that is exactly similar or identical in physical characteristics but different in lighting
system. This can be done by conducting a case study approach. The research can
conduct a survey on the affects of daylight component on affecting patronage by
focusing on a single building. Conducting the study using a single case study might
mitigate the problem of selecting identical shopping complexes.
Literature review assists the researcher in identifying factors affecting
patronage. However, the factors keep building up as more literature review is done
regarding the matter. In chapter 3.1.3, it was acknowledged that these factors were
difficult to be controlled entirely. Therefore, the research controlled the patronage
factor by using Riley’s Law in selecting the buildings. Riley’s Law states that
attractiveness or ability of a centre to attract customers is proportional to how big it is
and how far it is from its competition. Based on this premise, the research managed
to control the issue of factors affecting patronage by forming a retail trade area
analysis as suggested by Riley’s Law.
162
The method of acquiring data on patronage count proved difficult. It is found
that the Infodev human tabulation system proved to be the best solution for patronage
count. However, the Infodev system could not be used due financial constrain.
Therefore, the researcher adopted the Infodev method by conducting the patronage
count manually using a manual counter. The researcher felt that the usage of the
Infodev human tabulation system would give a highly accurate reading on patronage
count. The researcher felt that increasing the patronage count area might give a more
accurate reading. However, the issue of double counting can be avoided entirely only
with a proven human tabulation system such as the Infodev.
A study on digital camera and luminance meter comparison was conducted as
to the check the reliability of the digital camera in acquiring luminance level. Due to
unforeseen circumstances, the research has substituted the luminance meter with a
lux meter. This is due to the fact that a luminance meter was not able to be obtained
from any universities in Malaysia and even private bodies. However, the lux meter
was chosen as a substitute for the study and an additional calculation method was
used as to emulate the luminance reading from a luminance meter (please refer
chapter 3.3.1.4). Nevertheless, it is suspected that there might be a difference in
reading if a luminance meter was used in the study.
6.3
Recommendation for future research
Further research should be done with the following corrections as to
substantiate the research finding:
1.
A comprehensive study on the relation of digital image processing
technology and the possibilities of obtaining information regarding
luminance level using a digital image processing programme such as
Erdas and PCI Geomatica should be done. Preliminary study such as the
163
comparison of luminance meter and digital camera in acquiring
luminance reading should be done in a longer period of time as this will
probably aid the researcher to have a comprehensive understanding of the
matter.
2.
The experiment on digital camera and luminance meter comparison
should be repeated with a luminance meter instead of lux meter.
Repeating this experiment with a luminance meter might yield a different
outcome compared to the lux meter which was used in the experiment.
3.
An in depth study on factors affecting patronage needs to be done.
Another issue would be what and how these factors can be controlled.
Eventhough review on factors affecting patronage to a shopping complex
is done, the researcher was not able to control all factors. A study on how
to control factors affecting patronage would be beneficial to the research.
The patronage count study can be repeated using a system that should
eliminate the problem of double counting. This could result to a more
reliable patronage count.
4.
Lack of information on the perception of Malaysian towards the daylight
also hamper the research. An inventory or a global questionnaire covering
the perception or even reaction of Malaysian towards daylighting could
contribute into understanding the perception towards daylight. It is feared
that Malaysian might have a different perception towards daylight as
compared to individuals from temperate countries.
5.
Test the research methodology and research findings by performing a
study on other building typology. Future research could conduct a study
on other building typologies such as residential or office buildings as to
observe the affect or influence of daylight on selection and buying of
property. Future research could also study the affects of daylight towards
patronage in more than just 2 shopping complexes.
Figure
4.19
Luminance
level of
pictures
164
6.
Analysis on behavioural study can be developed further. Future research
could look into the affect of daylight towards various aspects of human
demographics such as age, sex, race, profession and level of education.
Further study can help identify which group of people are highly affected
by daylight. This study is capable of revealing the Malaysian perception
towards daylight.
165
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