Post on 27-Apr-2019
STRUCTURAL EQUATION MODELING OF ENERGY CONSUMPTION IN
RESIDENTIAL BUILDING
JIBRIN HASSAN SULEIMAN
UNIVERSITI TEKNOLOGI MALAYSIA
STRUCTURAL EQUATION MODELING OF ENERGY CONSUMPTION IN
RESIDENTIAL BUILDING
JIBRIN HASSAN SULEIMAN
A thesis submitted in fulfilment of the
requirements for the award of the degree of
Doctor of Philosophy (Civil Engineering)
Faculty of Civil Engineering
Universiti Teknologi Malaysia
APRIL 2017
iii
Dedication
To Almighty ALLAH, My beloved Parents, My Family, My Respected Supervisors,
Relatives, and Friends.
iv
ACKNOWLEDGEMENT
Praise and infinite gratitude be to the Allah S. W. T, the Most Gracious, Most
Merciful. May His endless mercies and blessings be upon his Messenger Muhammad
(Peace Be upon Him) and all his family and companions. I feel short of speech when
it adds up to thanking my supervisors in the person of Professor Engineer Dr. Rosli
Mohamad Zin and Dr. Ali Keyvanfar for their precious guidance, immense patience,
constant encouragement, and reinforcement. It will always remain indebted for their
efforts not merely in making this work done, but also for enhancing my learning
skills and improving my confidence as a researcher.
I am likewise thankful to all faculty members in the department of structures
and materials, particularly those in the UTM Construction Research Centre (UTM
CRC), Institute for Smart Infrastructure and Innovative Construction (UTM ISIIC)
and the management of the school of graduate studies of Universiti Teknologi
Malaysia for granting me the opportunity to undergo this rigorous research training.
I am thankful to my Institution Federal College of Education (Technical) Gombe
Nigeria, particularly my Provost in Person of Dr. Adamu Gimba Abbas, the college
Registrar, Alhaji Ahmed Mohammed Dukku, the Bursar, Mallam Nuhu Ya’u
Palladan, Mr. Istifanus Andrew and the entire staff of the institution. On the other
hand, I thank TEDFUND for the fiscal funding of this research.
My sincere appreciation goes to my mother Hajiya Halima Jibrin Suleiman,
my wife Zainab Gabdo Abdulkadir and my children (Abdulrauf and Zainab) for their
prayers and understanding with me throughout my program period. I equally value
the endeavor of my mother-in-law Hajiya Zainab Tanko Aliyu Girei for her support
and prayers. My friends, family, and well-wishers are all considered as time will not
permit me to shortlist your names. I thank you all and God bless.
v
ABSTRACT
Building energy consumption has become a serious issue due to increased energy
demand, which contributes heavily to global warming. Based on the reports published
by Energy Information and Administration of USA in 2015, Malaysia Green House Gas
(GHG) emission is expected to increase by about 74% from 2005 to 2020 if proper
mitigation is not put in place. Among the major contributor is building sector, which is
generating a massive 40% of total greenhouse gas emitted. There are many literature
describing the effect of carbon emissions by residential buildings. Nevertheless, lack of
study focus on building energy consumption in relation to socioeconomic, dwelling and
climate components. The aim of this study is to establish a structural relationship of
socioeconomic, dwelling and climate factors on residential building energy
consumption. Four objectives were identified to achieve the aforementioned aim. The
first objective was to identify the independent and dependent factors affecting energy
consumption in residential buildings. The second objective was to analyze and establish
the critical independent factors of energy consumption in residential buildings. The third
objective was to analyze and establish the critical dependent factors of energy
consumption by residential building occupants. The fourth objective was to formulate a
structural relationship based on the established critical independent and dependent
factors as a strategy for improving energy consumption in residential buildings. Three
benchmarked independent and six dependent factors were established. The descriptive
research design employed in the study lead to the structural model development as the
central focus of the study. A structured questionnaire consisting of 80 items were used
for data collection. The research population was Johor residents and the survey
employed 425 returned questionnaires. The collected information was analyzed using
descriptive and Confirmatory Factor Analysis. The outcome of the five (5) hypothesized
research questions show that Climate Factor has a significant and direct effect on
building energy consumption and dwelling. Furthermore, results indicate that
Socioeconomic and Dwelling factors have neither significant no direct effect on building
energy consumption. Based on the results, a Building Energy Consumption structural
relation was established using Structural Equation Modeling (SEM). The established
structural relation was validated using convergent and construct validity. The structured
model provides useful information to the Malaysian Construction Industry through
improved design and awareness on issues related to residential building energy
consumption.
vi
ABSTRAK
Penggunaan tenaga bangunan telah menjadi satu isu yang serius disebabkan oleh
peningkatan permintaan tenaga yang menjadi penyumbang besar kepada pemanasan
global. Berdasarkan laporan yang diterbitkan oleh Maklumat dan Pentadbiran Tenaga
Amerika Syarikat pada tahun 2015, pelepasan Gas Rumah Hijau (GHG) di Malaysia
dijangka meningkat sebanyak 74% dari tahun 2005 ke 2020 jika langkah mitigasi tidak
dilakukan dengan betul. Antara penyumbang utama adalah sektor bangunan, yang
menjana 40% daripada jumlah gas rumah hijau yang dikeluarkan. Terdapat banyak
literatur yang menerangkan kesan pelepasan karbon oleh bangunan kediaman. Walau
bagaimanapun, kurang kajian khusus tentang penggunaan tenaga bangunan yang berhubung
dengan sosioekonomi, kediaman dan komponen iklim. Tujuan kajian ini adalah untuk
membangunkan hubungan struktur terhadap sosioekonomi, kediaman dan faktor-faktor iklim
ke atas penggunaan tenaga bangunan kediaman. Empat objektif telah dikenalpasti untuk
mencapai matlamat di atas. Objektif pertama adalah untuk mengenal pasti faktor-faktor
bebas dan bergantung yang menjejaskan penggunaan tenaga dalam bangunan kediaman.
Objektif kedua adalah untuk menganalisis dan menentukan faktor-faktor bebas yang kritikal
daripada penggunaan tenaga dalam bangunan kediaman. Objektif ketiga adalah untuk
menganalisis dan menentukan faktor-faktor bergantung yang kritikal daripada penggunaan
tenaga oleh penghuni bangunan kediaman. Objektif keempat ialah untuk merumuskan
hubungan struktur berdasarkan faktor-faktor kritikal bebas dan bergantung yang ditubuhkan
sebagai strategi untuk meningkatkan penggunaan tenaga dalam bangunan kediaman. Tiga
tanda aras tidak bersandar dan enam faktor bersandar telah dikenal pasti. Rekabentuk kajian
deskriptif yang digunakan membawa kepada hubungan struktur model sebagai tumpuan
utama kajian. Soal selidik berstruktur yang mengandungi 80 item telah digunakan sebagai
alat untuk pengumpulan data. Populasi kajian adalah penduduk Johor dan kajian
menggunakan 425 soal selidik berstruktur yang dikembalikan. Maklumat yang dikumpul
dianalisis menggunakan analisis deskriptif dan analisis pengesahan faktor. Hasil daripada
lima soalan (5) hipotesis kajian menunjukkan bahawa, Faktor Iklim mempunyai kesan yang
besar dan secara langsung terhadap penggunaan tenaga bangunan dan kediaman. Tambahan
pula, keputusan menunjukkan bahawa faktor Sosioekonomi dan Faktor Kediaman tidak
mempunyai kesan ketara atau kesan langsung ke atas penggunaan tenaga bangunan.
Berdasarkan keputusan, hubungan struktur Model Penggunaan Tenaga Bangunan telah
dibangunkan menggunakan Pemodelan Persamaan Struktur (SEM). Hubungan struktur
ditubuhkan telah disah menggunakan kesahihan menumpu dan membina. Model berstruktur
menyediakan maklumat yang berguna kepada Industri Pembinaan Malaysia melalui reka
bentuk yang lebih baik dan kesedaran mengenai isu-isu yang berkaitan dengan kediaman
penggunaan tenaga bangunan.
vii
TABLE OF CONTENTS
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES xx
LIST OF FIGURES xxvii
LIST OF ABBREVIATIONS xxx
LIST OF APPENDICES xxxiii
1 INTRODUCTION 1
1.1 Background of the Research 1
1.2 Problem Statement 3
1.3 Research Questions 6
1.4 Aim and Research Objectives 6
1.5 Research Hypothesis 7
1.6 Scope of the Research 7
1.7 Significance of the Research 9
1.8 Research Process Framework 10
1.9 Structure of the Thesis 11
1.10 Summary of the Chapter 13
2 LITERATURE REVIEW 14
2.1 Introduction 14
viii
2.2 Construction Industry 15
2.2.1 Malaysian Construction Industry 16
2.3 Building Energy 17
2.3.1 Residential Building Energy 19
2.3.2 Building Energy Model 20
2.3.3 Top-down and Bottom-up Models 21
2.4 Socio-Economic Related Factors of Building Energy
Consumption (BEC) 23
2.4.1 Age of the Household Head 23
2.4.2 Gender of the Household Head 25
2.4.3 Marital Status of the Household Head 25
2.4.4 Number of Children in the Household 26
2.4.5 Education Level of the Household Head 27
2.4.6 Level of Literacy of the Household Head 28
2.4.7 Employment Status of the Household Head 28
2.4.8 Income Status of the Household Head 29
2.4.9 Number of People in the Household
(Household Size) 30
2.4.10 Religion Background of the Respondents 30
2.4.11 Ethnicity of the Household 31
2.4.12 Living Habit of the Household 31
2.4.13 Family Composition (Presence of Children,
Teenagers etc) 32
2.4.14 House Ownership (Rented or Owner
Occupier) 32
2.4.15 Summary of the Socio-Economic Related
Factors of Building Energy Consumption 33
2.5 Dwelling Related Factors of BEC 36
2.5.1 Dwelling Type 36
2.5.2 Dwelling Size 37
2.5.3 Number of Rooms in the Dwelling 38
2.5.4 Size of Rooms 38
2.5.5 Total Floor Area 39
2.5.6 Dwelling Orientation 40
ix
2.5.7 Dwelling Age 40
2.5.8 Number of Floors 41
2.5.9 Design Features 41
2.5.10 Location of the Dwelling 42
2.5.11 Dwelling Insulation 43
2.5.12 Summary of the Dwelling Related Factors
of BEC 43
2.6 Climate Related Factors of BEC 45
2.6.1 Temperature 46
2.6.2 Humidity 47
2.6.3 Atmospheric Pressure 48
2.6.4 Rainfall 48
2.6.5 Wind 49
2.6.6 Sunshine and Solar Radiation 50
2.6.7 Summary of Socio-Economic, Dwelling,
and Climate Related Factors of BEC 51
2.7 Electrical Home Appliances 52
2.7.1 Air-Condition System 53
2.7.2 Refrigeration System 54
2.7.3 Kitchen Appliances 55
2.7.4 Lighting 55
2.7.5 Laundry and Bathroom Appliances 55
2.7.6 Other Home Appliances 56
2.7.7 Summary of the Electrical Home
Appliances Related Factors of BEC 58
2.8 Research Gap 58
2.9 Conceptual Framework of the Independent and
Dependent Factor in Relation to Residential Building
Energy Consumption 58
2.10 Summary of the Chapter 59
3 RESEARCH METHODOLOGY 61
3.1 Introduction 61
3.2 Research Design 61
x
3.3 Research Method Process 62
3.4 Survey Question Development 64
3.4.1 Pilot Study 64
3.5 Research Study Population 65
3.6 Sampling Design 66
3.6.1 Research Sampling Technique 66
3.6.2 Research Instrument 68
3.6.3 Validity of the Research Instrument 69
3.6.4 Reliability of the Research Instrument 69
3.7 Method of Data Collection 70
3.7.1 Area of the Study 70
3.7.2 Johor Bahru 71
3.7.3 Data Cleansing 72
3.7.4 Methods of Data Analysis 73
3.7.5 Structural Equation Modeling (SEM) 75
3.7.6 Goodness of Fit Indices in Structural
Equation Modeling (SEM) 76
3.7.7 Structural Equation Modeling Assumptions 77
3.7.8 Sample Size Criteria in SEM 77
3.7.9 Procedures for Structural Equation
Modeling 78
3.7.10 Assessing Unidimensionality 79
3.7.11 Model Evaluation in Confirmatory Factor
Analysis (CFA) 80
3.7.12 Normality Estimate in Confirmatory Factor
Analysis (CFA) 80
3.7.13 Standardized Residuals in Confirmatory
Factor Analysis (CFA) 81
3.7.14 Modification Indices in Confirmatory
Factor Analysis (CFA) 82
3.7.15 Validity of the Model 82
3.7.16 Reliability of the Model 83
3.8 Summary of Chapter 86
xi
4 RESULTS AND DISCUSSION 87
4.1 Introduction 87
4.2 Demographic Responses 87
4.2.1 House Head Age 88
4.2.2 House Head Gender 89
4.2.3 House Head Ethnicity 90
4.2.4 House Head Religion 91
4.2.5 House Head Education Level 92
4.2.6 House Head Marital Status 94
4.2.7 House Head Income 95
4.2.8 Building Type 96
4.2.9 Number of Rooms in the Household 96
4.2.10 Monthly Electricity Bill of the Respondents 97
4.2.11 Summary of Demographic Responses 97
4.3 Analysis of the Pilot Study 98
4.3.1 Cronbach’s Alpha Reliability Coefficient 98
4.3.2 Cronbach’s Alpha Analysis of Socio-
Economic Factor 98
4.3.3 Cronbach’s Alpha Analysis of Dwelling
Factor 100
4.3.4 Cronbach’s Alpha Analysis of
Refrigeration System 101
4.3.5 Cronbach’s Alpha Analysis of Kitchen
Devices 102
4.3.6 Cronbach’s Alpha Analysis of Air-
Condition System 103
4.3.7 Cronbach’s Alpha Analysis of Bathroom
and Laundry Appliances 105
4.3.8 Cronbach’s Alpha Analysis of Lighting
Appliances 106
4.3.9 Cronbach’s Alpha Analysis of Home
Appliances 107
4.3.10 Summary of the Pilot Study Analysis 108
4.4 Analysis of Independent Factors 108
xii
4.4.1 First-Order Measurement of Socio-
Economic Factors (SEF) 109
4.4.2 Normality of Initial First-Order
Measurement of SEF 111
4.4.3 Standardized Residual Covariance of Initial
First-Order Measurement of SEF 111
4.4.4 Covariance of Initial First-Order
Measurement of SEF 113
4.4.5 Exploratory Factor Analysis of the
Research Independent Factors 114
4.4.5.1 Exploratory Factor Analysis
(EFA) of SEF 115
4.4.5.2 Factorised SEF Variables 116
4.4.5.3 Validity of Factorised SEF
Variables 117
4.4.6 The Second Order Measurement Model
(Initial) of SEF 118
4.4.7 Normality of Initial Second-Order
Measurement of SEF 118
4.4.8 Standardized Residual Covariance of Initial
Second-Order Measurement of SEF 119
4.4.9 Covariance of Initial First-Order
Measurement of SEF 121
4.4.10 Modified Second-Order Measurement of
SEF 122
4.4.11 Normality of Modified Second-Order
Measurement of SEF 123
4.4.12 Standardized Residual Covariance of
Modified Second-Order Measurement of
SEF 123
4.4.13 Content Validity of Modified Second-Order
Measurement of SEF 124
4.4.14 Covariance of Modified Second-Order
Measurement of SEF 124
xiii
4.5 First-Order Measurement of Dwelling Factor (DF) 124
4.5.1 Normality of Initial First-Order
Measurement of DF 125
4.5.2 Standardized Residual Covariance of Initial
First-Order Measurement of DF 126
4.5.3 Covariance of Initial First-Order
Measurement of DF 127
4.5.4 Exploratory Factor Analysis of DF 128
4.5.5 Factorised DF Variables 129
4.5.6 Validity of Factorised DF Variables 130
4.5.7 Initial Second-Order Measurement of DF 130
4.5.7.1 Normality of Initial First-Order
Measurement of DF 131
4.5.7.2 Standardized Residual
Covariance of Initial Second-
Order Measurement of DF 132
4.5.7.3 Covariance of Initial First-Order
Measurement of DF 133
4.5.8 Modified Second-Order Measurement of
DF 134
4.5.8.1 Normality of Modified Second-
Order Measurement of DF 134
4.5.8.2 Standardized Residual
Covariance of Modified Second-
Order Measurement of DF 135
4.5.8.3 Covariance of Modified Second-
Order Measurement of DF 135
4.6 First-Order Measurement of Climatic Factors (CF) 136
4.6.1 Normality of Initial First-Order
Measurement of CF 137
4.6.2 Standardized Residual Covariance of Initial
First-Order Measurement of CF 137
4.6.3 Covariance of Initial First-Order
Measurement of CF 138
xiv
4.6.4 Exploratory Factor Analysis of CF 138
4.6.5 Modified First-Order Measurement of CF 139
4.6.6 Normality of Modified First-Order
Measurement of CF 140
4.6.7 Standardized Residual Covariance of
Modified First-Order Measurement of CF 140
4.6.8 Summary of the Independent Factors 140
4.7 Analysis of Dependent Factors 143
4.7.1 Initial First-Order Measurement of
Refrigeration System (RS) 143
4.7.2 Normality of Initial First-Order
Measurement of RS 144
4.7.3 Standardized Residual Covariance of Initial
First-Order Measurement of RS 144
4.7.4 Covariance of Initial First-Order
Measurement of RS 145
4.7.5 Modified First-Order Measurement of RS 146
4.7.6 Content Validity of Modified First-Order
Measurement of RS 146
4.7.7 Normality of Modified First-Order
Measurement of RS 147
4.7.8 Standardized Residual Covariance of
Modified First-Order Measurement of RS 147
4.7.9 Covariance of Modified First-Order
Measurement of RS 147
4.8 Initial First-Order Measurement of Kitchen Devices
(KD) 148
4.8.1 Normality of Initial First-Order
Measurement of KD 149
4.8.2 Standardized Residual Covariance of Initial
First-Order Measurement of KD 149
4.8.3 Covariance of First-Order Measurement of
KD 150
4.8.4 Modified First-Order Measurement of KD 150
xv
4.8.5 Content Validity of Modified First-Order
Measurement of KD 151
4.8.6 Normality of Modified First-Order
Measurement of KD 151
4.8.7 Standardized Residual Covariance of
Modified First-Order Measurement of KD 151
4.8.8 Covariance of Modified First-Order
Measurement of KD 152
4.9 Initial First-Order Measurement of Air-Condition
System (ACS) 152
4.9.1 Normality of Initial First-Order
Measurement of ACS 153
4.9.2 Standardized Residual Covariance of First-
Order Measurement of ACS 154
4.9.3 Covariance of First-Order Measurement of
ACS 154
4.9.4 Modified First-Order Measurement of ACS 155
4.9.5 Content Validity of Modified First-Order
Measurement of ACS 156
4.9.6 Normality of Modified First-Order
Measurement of ACS 156
4.9.7 Standardized Residual Covariance of
Modified First-Order Measurement of ACS 157
4.10 Initial First-order measurement of Bath and Laundry
Appliances (BLA) 157
4.10.1 Normality of First-Order Measurement of
BLA 158
4.10.2 Standardized Residual Covariance of First-
Order Measurement of BLA 159
4.10.3 Covariance of Initial First-Order
Measurement of BLA 159
4.10.4 Modified First-Order Measurement of BLA 160
4.10.5 Content Validity of Modified First-Order
Measurement of BLA 161
xvi
4.10.6 Normality of Modified First-Order
Measurement of BLA 161
4.10.7 Standardized Residual Covariance of
Modified First-Order Measurement of BLA 162
4.11 Initial First-Order Measurement of Lighting
Appliances (LA) 162
4.11.1 Normality of Initial First-Order
Measurement of LA 163
4.11.2 Standardized Residual Covariance of First-
Order Measurement of LA 164
4.11.3 Covariance of Initial First-Order
Measurement of LA 165
4.11.4 Modified First-Order Measurement of LA 166
4.11.5 Content Validity of Modified First-Order
Measurement of LA 166
4.11.6 Normality of Modified First-Order
Measurement of LA 167
4.11.7 Standardized Residual Covariance of
Modified First-Order Measurement of LA 167
4.12 Initial First-Order Measurement of Home Appliances
(HA) 167
4.12.1 Normality of First-Order Measurement of
HA 168
4.12.2 Standardized Residual Covariance of First-
Order Measurement of HA 169
4.12.3 Covariance of Initial First-Order
Measurement of HA 170
4.12.4 Modified First-Order Measurement of HA 170
4.12.5 Content Validity of Modified First-Order
Measurement of HA 171
4.12.6 Normality of Modified First-Order
Measurement of HA 171
4.12.7 Standardized Residual Covariance of
Modified First-Order Measurement of HA 172
xvii
4.12.8 Results of the Analysis of Dependent
Factors 172
4.12.9 Summary of Findings 175
4.13 CFA of the Six (6) Identified Dependent Factors of
Building Energy Consumption 176
4.13.1 Discriminant Validity of Building Energy
Consumption 176
4.13.2 Second Order Model of Building Energy
Consumption 177
4.14 Discussion on Structural Model of Building Energy
Consumption 178
4.15 Summary of the Chapter 180
5 STRUCTURAL RELATIONSHIP OF BUILDING
ENERGY CONSUMPTION 181
5.1 Introduction 181
5.2 Socio-Economic Energy Structural Model (SEESM) 181
5.2.1 The Initial Socio-Economic Energy
Structural Model 182
5.2.2 Modified Socio-Economic Energy
Structural Model 185
5.3 Dwelling Energy Structural Model (DESM) 188
5.3.1 Initial Dwelling Energy Structural Model 188
5.3.2 Modified Dwelling Energy Structural
Model 191
5.4 Climatic Energy Structural Model (CESM) 194
5.4.1 Initial Climatic Energy Structural Model 194
5.4.2 Modified Climate Energy Structural Model 197
5.5 Structural Equation Modelling of Building Energy
Consumption Model 200
5.5.1 The Initial Structural Model of Building
Energy Consumption Model 202
5.5.2 Regression Weights of Initial Structural
Equation 205
xviii
5.5.3 Normality of Initial Structural Equation
Model 206
5.5.4 Variance of Initial Structural Equation
Model 207
5.5.5 Standardized Residual Covariance of Initial
Structural Equation Model 209
5.6 The Modified (Final) Structural Model 209
5.6.1 Regression Weights of Modified Structural
Equation Model 211
5.6.2 Standardized Regression Weights of
Modified Structural Equation Model 212
5.6.3 Variances of Modified Structural Equation
Model 213
5.6.4 Squared Multiple Correlations of Modified
Structural Equation Model 215
5.6.5 Assessment of Normality of Modified
Structural Equation Model 216
5.6.6 Standardized Residual Covariance of
Modified Structural Equation Model 217
5.6.7 Overall Model Fit Indices for Structural
Equation Model 217
5.6.8 Discussion on the Structural Model
Development 218
5.7 Summary of Chapter 223
6 CONCLUSION AND RECOMMENDATION 224
6.1 Introduction 224
6.2 Summary of the Research 224
6.3 Conclusion 225
6.3.1 Objective 1: To Identify the Independent
and Dependent Factors affecting Energy
Consumption in Residential Buildings 225
6.3.2 Objective 2: To Analyze and Establish the
Critical Independent Factors of Energy
xix
Consumption in Residential Buildings
Based on Socio-economic, Dwelling and
Climate Grouping 226
6.3.3 Objective 3. To Analyze and Establish the
Critical Dependent Factors of Energy
Consumption by Residential Building
Occupants 226
6.3.4 Objective 4. To Formulate a Structural
Relationship based on the Critical
Established Independent and Dependent
Factors as a Strategy for Improving Energy
Efficiency in Residential Buildings 227
6.4 Limitation of the Research 228
6.5 Contribution of the Research 228
6.5.1 Contribution of the Research to the
Construction Industry 229
6.5.2 Contribution of the Research to the Body of
Knowledge 229
6.6 Recommendation 230
6.6.1 Recommendation for Construction Industry 230
6.6.2 Recommendation for Future Research 231
6.7 Conclusion Remark 231
REFERENCES 232
Appendices A-D 254-276
xx
LIST OF TABLES
TABLE NO. TITLE PAGE
2.1 Authors Responses on Socio-Economic Factor in Relation to
Building Energy Consumption 34
2.2 Authors Responses on Dwelling Factors in Relation to
Building Energy Consumption 44
2.3 Record of Daily Average Temperature and Relative
Humidity of Malaysia 48
2.4 Electricity Consumption by Sectors in GWh, 2012 52
3.1 Number of Living Quarters and Households by State and
Administrative District, 1991, 2000 and 2010 66
3.2 Sample for Quantitative Data Collection 68
3.3 Summary of Data Analysis Procedures 74
3.4 Goodness of Fit Statistics Used in Model Determination 77
3.5 SEM Sample Size Based on Construct and Items 78
3.6 Conditions of Validity 83
3.7 Internal Reliability, Composite Reliability (CR) and Average
Variance Extracted (AVE) 84
3.8 Valid Factor Loadings, Cronbach’s Alpha, CR and AVE 85
4.1 Analysis of House Head Age 88
4.2 Analysis of House Head Gender 89
4.3 Analysis of House Head Ethnicity 90
4.4 Analysis of House Head Religion 91
4.5 Analysis of House Head Education Level 93
4.6 Analysis of House Head Marital Status 94
4.7 Analysis of House Head Income 95
xxi
4.8 Analysis of Building Type 96
4.9 Analysis of Number of Rooms in the Household 97
4.10 Analysis of Monthly Electricity Bill of the Household 97
4.11 Summary of Cronbach’s Alpha Analysis of SEF 99
4.12 Summary of Cronbach’s Alpha Item-Total Statistics on SEF 99
4.13 Summary of Cronbach’s Alpha Analysis of DF 100
4.14 Summary of Cronbach’s Alpha Item-Total Statistics on DF 100
4.15 Summary of Cronbach’s Alpha Analysis of RS 101
4.16 Summary of Cronbach’s Alpha Item-Total Statistics on RS 101
4.17 Summary of Cronbach’s Alpha Analysis of KD 102
4.18 Summary of Cronbach’s Alpha Item-Total Statistics on KD 103
4.19 Summary of Cronbach’s Alpha Analysis of ACS 103
4.20 Summary of Cronbach’s Alpha Item-Total Statistics on ACS 104
4.21 Summary of Cronbach’s Alpha Analysis of BLA 105
4.22 Summary of Cronbach’s Alpha Item-Total Statistics on BLA 105
4.23 Summary of Cronbach’s Alpha Analysis of LA 106
4.24 Summary of Cronbach’s Alpha Item-Total Statistics on LA 107
4.25 Summary of Cronbach’s Alpha Analysis of HA 107
4.26 Summary of Cronbach’s Alpha Item-Total Statistics on HA 108
4.27 The Socio-Economic Factors of the Study 109
4.28 Normality of Initial First-Order Measurement of SEF 111
4.29 Standardized Residual Covariance of First-Order
Measurement of SEF 112
4.30 Covariance of Initial First-Order Measurement of SEF 113
4.31 KMO and Bartlett’s Test of SEF 115
4.32 Communalities and Factor Matrix of SEF 115
4.33 Factorised SEF Variables 117
4.34 Normality of Initial Second-Order Measurement of SEF 119
4.35 Standardized Residual Covariance of Initial Second-Order
Measurement of SEF 120
4.36 Covariance of Initial First-Order Measurement of SEF 121
4.37 Normality of Modified Second-Order Measurement of SEF 123
4.38 Standardized Residual Covariance of Modified Second-Order
Measurement of SEF 123
xxii
4.39 Content Validity of Modified Second-Order Measurement of
SEF 124
4.40 Covariance of Modified Second-Order Measurement of SEF 124
4.41 Normality of Initial First-Order Measurement of Dwelling
Factor 126
4.42 Standardized Residual Covariance of Initial First-Order
Measurement of DF 126
4.43 Covariance of Initial First-Order Measurement of DF 127
4.44 KMO and Bartlett's Test of DF 128
4.45 Communalities and Factor Matrix of DF 128
4.46 Factorised DF Variables 129
4.47 Normality of Initial Second-Order Measurement of DF 132
4.48 Standardized Residual Covariance of Initial Second-Order
Measurement of DF 132
4.49 Covariance of Initial First-Order Measurement of DF 133
4.50 Normality of Modified Second-Order Measurement of DF 135
4.51 Standardized Residual Covariance of Modified Second-Order
Measurement of DF 135
4.52 Covariance of Modified Second-Order Measurement of DF 136
4.53 Normality of Initial First-Order Measurement of CF 137
4.54 Standardized Residual Covariance of Initial First-Order
Measurement of CF 137
4.55 Covariance of Initial First-Order Measurement of CF 138
4.56 KMO and Bartlett's Test of CF 138
4.57 Communalities and Factor Matrix of CF 139
4.58 Variance Explained of CF 139
4.59 Normality of Modified First-Order Measurement of CF 140
4.60 Standardized Residual Covariance of Modified First-Order
Measurement of Climate Factor 140
4.61 Descriptive Statistics of SEF 141
4.62 Descriptive Statistics of DF 142
4.63 Descriptive Statistics of CF 142
4.64 Normality of Initial First-Order Measurement of
Refrigeration System (RS) 144
xxiii
4.65 Standardized Residual Covariance of Initial First-Order
Measurement of RS 145
4.66 Covariance of Initial First-Order Measurement of RS 145
4.67 Content Validity of Modified First-Order Measurement of RS 146
4.68 Normality of Modified First-Order Measurement of RS 147
4.69 Standardized Residual Covariance of Modified First-Order
Measurement of RS 147
4.70 Covariance of Modified First-Order Measurement of RS 148
4.71 Normality of Initial First-Order Measurement of Kitchen
Devices (KD) 149
4.72 Standardized Residual Covariance of Initial First-Order
Measurement of KD 149
4.73 Covariance of First-Order Measurement of KD 150
4.74 Content Validity of Modified First-Order Measurement of
KD 151
4.75 Normality of Modified First-Order Measurement of KD 151
4.76 Standardized Residual Covariance of Modified First-Order
Measurement of KD 152
4.77 Covariance of Modified First-Order Measurement of KD 152
4.78 Normality of Initial First-Order Measurement of Air-
Condition System (ACS) 154
4.79 Standardized Residual Covariance of First-Order
Measurement of ACS 154
4.80 Covariance of First-Order Measurement of ACS 155
4.81 Content Validity of Modified First-Order Measurement of
ACS 156
4.82 Normality of Modified First-Order Measurement of ACS 157
4.83 Standardized Residual Covariance of Modified First-Order
Measurement of ACS 157
4.84 Normality of First-Order Measurement of Bath and Laundry
Appliances (BLA) 159
4.85 Standardized Residual Covariance of First-Order
Measurement of BLA 159
4.86 Covariance of Initial First-Order Measurement of BLA 160
xxiv
4.87 Content Validity of Modified First-Order Measurement of
BLA 161
4.88 Normality of Modified First-Order Measurement of BLA 161
4.89 Standardized Residual Covariance of Modified First-Order
Measurement of BLA 162
4.90 Normality of Initial First-Order Measurement of Lighting
Appliances (LA) 164
4.91 Standardized Residual Covariance of First-Order
Measurement of LA 164
4.92 Covariance of Initial First-Order Measurement of LA 165
4.93 Content validity of Modified First-Order Measurement of LA 166
4.94 Normality of Modified First-Order Measurement of LA 167
4.95 Standardized Residual Covariance of Modified First-Order
Measurement of LA 167
4.96 Normality of First-Order Measurement of Home Appliances
(HA) 169
4.97 Standardized Residual Covariance of First-Order
Measurement of HA 169
4.98 Covariance of Initial First-Order Measurement of HA 170
4.99 Content Validity of Modified First-Order Measurement of
HA 171
4.100 Normality of Modified First-Order Measurement of HA 172
4.101 Standardized Residual Covariance of Modified First-Order
Measurement of HA 172
4.102 Descriptive Statistics of Refrigeration System 173
4.103 Descriptive Statistics of Kitchen Devices 173
4.104 Descriptive Statistics of Air-Condition System 174
4.105 Descriptive Statistics of Bath and Laundry Appliaces 174
4.106 Descriptive Statistics of Lighting Appliances 175
4.107 Descriptive Statistics of Home Appliances 175
4.108 Regression Weight of Structural Model of Building Energy
Consumption 179
5.1 Regression Weights of Initial Socio-Economic Energy
Structural Model 184
xxv
5.2 Regression Weights of Modified Socio-Economic Energy
Structural Model 187
5.3 Regression Weight of Initial Dwelling Energy Structural
Model 190
5.4 Regression Weights of Modified Dwelling Energy Structural
Model 193
5.5 Regression Weight of Initial Climate Energy Structural
Model (CESM) 196
5.6 Regression Weight of Modified Climate Energy Model 199
5.7 Goodness of Fit Measures 201
5.8 Regression Weights of Initial Structural Equation Model
Exploring Relationship of SEF, DF, CF and Building Energy
Consumption. 205
5.9 Normality of Initial Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 206
5.10 Variance of Initial Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 208
5.11 Regression Weights of Modified Structural Equation Model
Exploring Relationship of SEF, DF, CF and Building Energy
Consumption 211
5.12 Standardized Regression Weights of Modified Structural
Equation Model Exploring Relationship of SEF, DF, CF and
Building Energy Consumption 212
5.13 Variances of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 214
5.14 Squared Multiple Correlations of Modified Structural
Equation Model Exploring Relationship of SEF, DF, CF and
Building Energy Consumption 215
5.15 Assessment of Normality of Modified Structural Equation
Model Exploring Relationship of SEF, DF, CF and Building
Energy Consumption 216
xxvi
5.16 FMIN of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 217
5.17 RMSEA of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 218
5.18 AIC of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 218
5.19 ECVI of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 218
5.20 HOELTER of Modified Structural Equation Model Exploring
Relationship of SEF, DF, CF and Building Energy
Consumption 218
.
xxvii
LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 Research Gap 5
1.2 Flowchart of the Research Process Framework 13
2.1 Population of Malaysia from 2010 to 2014, with Projections
to Year 2020 18
2.2 Carbon Emission in Metric Tons Per Capita from 1980-2010 18
2.3 Annual Solar Radiation in Different Towns in Malaysia 51
2.4 Ownership of Washing Machine in Some Selected Countries 56
2.5 Conceptual Framework of the Research 59
3.1 Research Method Process 63
3.2 Graph of Sample Size and Total Population 67
3.3 Johor State Sharing Boundary with Pahang, Melaka, Negeri
Sembilan, Singapore and Maritime Border of Riau Mainland
and the South China Sea. 71
3.4 The Map of Johor Bahru. 72
3.5 Two-stage Structural Equation Model Employed in the
Research 79
4.1 House Head Age of the Respondents 89
4.2 House Head Gender of the Respondents 90
4.3 House Head Ethnicity of the Respondents 91
4.4 House Head Religion of the Respondents 92
4.5 Education Level of the Respondents 93
4.6 Marital Status of the Respondents 94
4.7 Income of the Respondents 95
4.8 Initial First-Order Measurement of Socio-Economic Factor 110
4.9 Validity of Factorised SEF Variables 117
xxviii
4.10 Initial Second-Order Measurement of Socio-Economic Factor 118
4.11 Modified Second-Order Measurement of Socio-Economic
Factor 122
4.12 Initial First-Order Measurement of Dwelling Factor 125
4.13 Validity of Factorised DF Variables 130
4.14 Initial Second-Order Measurement of Dwelling Factor 131
4.15 Modified Second-Order Measurement of Dwelling Factor 134
4.16 Initial First-Order Measurement of Climatic Factor 136
4.17 Modified First-Order Measurement of Climatic Factor 139
4.18 Initial First-Order Measurement of Refrigeration System 143
4.19 Modified First-Order Measurement of Refrigeration System 146
4.20 Initial First-Order Measurement of Kitchen Devices 148
4.21 Modified First-Order Measurement of Kitchen Device 150
4.22 First-Order Measurement of Air-Condition System 153
4.23 Modified Order Measurement of Air-Condition System 156
4.24 Initial First-Order Measurement of Bath and Laundry
Appliances 158
4.25 Modified First-Order Measurement of Bath and Laundry
Appliances 160
4.26 Initial First-Order Measurement of Lighting Appliances 163
4.27 Modified First-Order Measurement of Lighting Appliances 166
4.28 First-Order Measurement of Home Appliances 168
4.29 Modified First-Order Measurement of Home Appliances 171
4.30 Discriminant Analysis of Building Energy Consumption 177
4.31 Initial Second Order of Building Energy Consumption 178
5.1 Initial Structural Equation Model Exploring Relationship of
Socio-Economic Factor and Building Energy Consumption 183
5.2 Modified Structural Equation Model Exploring Relationship
of Socio-Economic Factor and Building Energy Consumption 186
5.3 Initial Structural Equation Model Exploring Relationship of
Dwelling Factor and Building Energy Consumption 189
5.4 Modified Structural Equation Model Exploring Relationship
of Dwelling Factor and Building Energy Consumption 192
xxix
5.5 Initial Structural Equation Model Exploring Relationship of
Climate Factor and Building Energy Consumption 195
5.6 Modified Structural Equation Model Exploring Relationship
of Climate Factor and Building Energy Consumption 198
5.7 Hypothesized Structural Equation Model of the Relationships
between Socio-Economic Factor, Dwelling Factor, Climate
Factor and Building Energy Consumption 200
5.8 Details of Hypothesized SEM of the Relationships between
Socio-Economic Factor, Dwelling Factor, Climate Factor and
Building Energy Consumption 202
5.9 Initial Structural Equation Model Exploring Relationship of
Socio-Economic Factor, Dwelling Factor and Climate Factor
in Relation to Building Energy Consumption 204
5.10 Modified Structural Equation Model Exploring Relationship
of Socio-Economic, Dwelling, and Climate 210
.
xxx
LIST OF ABBREVIATIONS
ACS - Air-Condition System
AMOS - Analysis of Moment Structure
AVE - Average Variance Extracted
BECSM - Building Energy Consumption Structural Model
BLA - Bath and Laundry Appliances
Btu - British thermal unit
CAGR - Compounded Average Growth Rate
CCTV - Closed Circuit Television
CESM - Climatic Energy Structural Model
CETDEM - Centre for Environmental Technology and Development in
Malaysia
CF - Climate Factor
CFA - Confirmatory Factor Analysis
CIA - Central Intelligence Agency
CIDB - Construction Industry Development Board
CO2 - Carbon Emission
CR - Composite Reliability
CRT - Cathode Ray Tube
DESM - Dwelling Energy Structural Model
DF - Dwelling Factor
DSM - Department of Statistics Malaysia
DVD - Digital Versatile Disk
DVR - Digital Video Recorder
EFA - Exploratory Factor Analysis
EIA - Energy Information Administration
EPBD - Energy Performance of Building Directives
FL - Factor Loading
xxxi
GDP - Gross Domestic Product
GFCF - Gross Fixed Capital Formation
GHG - Green House Gas
GWh - Giga Watt hour
HA - Home Appliances
HVAC - Heating Ventilation and Air-Condition
IEA - International Energy Agency
IEO - International Energy Outlook
IMF - International Monetary Fund
KD - Kitchen Devices
KLIA - Kuala Lumpur International Airport
KMO - Kaiser-Meyer-Olkin
KWh - KiloWatt-hour
LA - Lighting Appliances
LCD - Liquid Cristal Display
LED - Light Emitted Diode
LNG - Liquefied Petroleum Gas
MBJB - Majlis Bandaraya Johor Bahru
MOSTI - Ministry of Science Technology and Innovation
MPJBT - Majlis Perbandaran Johor Bahru Tengah
Mtoe - Million ton of energy
NIC - Newly Industrialized Country
PTEM - Physical Technical Economic Model
PWD - Public Works Department
PKK - Pusat Khidmat Kontractor
RS - Refrigeration System
SEDA - Sustainable Energy Development Authority
SEESM - Socio-Economic Energy Structural Model
SEF - Socio-Economic Factor
SEM - Structural Equation Modeling
SPSS - Statistical Package for Social Sciences
TNB - Tenaga Nasional Berhad
TV - Television
UBBL - Uniform Building By-Laws
xxxiv
LIST OF APPENDICES
APPENDIX TITLE PAGE
A1 Main survey Questionnaire 254
A2 Borang Soalan Kaji Selidik 259
A3 Pilot survey Questionnaire 264
B Standardized Residual Covariance of Initial Structural 271
Equation Model Exploring Relationship of Socio
Economic Factor, Dwelling Factor, Climatic Factor
and Building Energy Consumption
C Standardized Residual Covariance of Modified 273
Structural Equation Model Exploring Relationship
of Socio-Economic Factor, Dwelling Factor, Climatic
Factor and Building Energy Consumption
D List of Publications 275
CHAPTER 1
1 INTRODUCTION
This chapter serves as an introductory description of the research outline of the
various sections considered in this research. It comprises of the introduction to the
chapter, background of the research, problem statement, aim and objectives, research
hypothesis, research questions, the scope of the study, and significance of the study as
well as research flowchart.
1.1 Background of the Research
The upward growth of the worldwide population has influenced the increasing
need of buildings globally. These buildings play a vital role in providing shelter and
offices for occupant’s usage. However, it becomes a major issue of concern in the
past decades, due to its role in global energy consumption. Carbon (CO2) and
Greenhouse Gas (GHG) emissions produced by buildings cause depletion of the ozone
layer. This lead to a serious environmental impact which has a direct effect on climate
change and global warming (Luis et al., 2008; Shafie et al., 2011). Buildings
contribute tremendously to GHG emission, it is responsible for 33% of worldwide
energy-related GHG emissions (Robert & Kummert, 2012).
The International Energy Outlook report (2013) on the current position of
global energy consumption reveals that energy will continue to grow by 56% in-
between the year 2010 to 2040. This is due to fast changes in socio-economic and
demographics (EIA., 2013). Despite the continuous campaigns on global energy
2
awareness and mitigation of greenhouse gas emissions in the last 40 years, there is
more than 100% growth in CO2 emissions annually (Nejat et al., 2015). Global
carbon emission is expected to increase to 32 billion tons of CO2 by projection in
2020 (IEA, 2013). This projection is expected to double (64 billion tons CO2) by 2050
if proper climate change measures are not put in place (Nejat et al., 2015; Wada et al.,
2012).
The trend of building energy consumption is on the increase in many countries
around the world. For example, building sector consumes 41% of energy in the
United States (BEDB, 2011). In China, 28.6% of the total energy is consumed by
buildings (Zhu & Li, 2015). In Europe, building sector consumes up to 40% of the
world’s energy and consumes 25% of forest timber including 16% of the world’s fresh
water (Foucquier, 2013). In Malaysia, buildings consume up to 48% of the energy in
the country (Chua & Oh, 2011; Jibrin et al., 2014).
One of the identified areas of energy consumption in a residential building is
the use of electrical appliances. Heating, Ventilation and Air Conditioning (HVAC)
system, domestic appliances and lighting demonstrate a positive consumption of
electricity in residential buildings (McLoughlin, 2012). Electricity consumption in
residential buildings accounted for 6% direct CO2 emission (Olivier et al., 2013) and
11% indirect global CO2 emission (IEA, 2013).
Malaysia has been named among the highest greenhouse gas emitting countries
in the world (Shamsuddin, 2012). A growth of 7.9% Compounded Average Growth
Rate (CAGR) was recorded from 1990 to 2006 (Shamsuddin, 2012). The world fact
book by the Central Intelligence Agency (CIA) reveals that 118 billion kWh of
electricity were produced by the Malaysian Government (CIA, 2013). Tenaga National
Berhad (TNB) reported that the consumption of electricity in the country is
116,353GWh. Buildings in Malaysia consume a total of 54% of electricity in the
country. This is equal to 63,354GWh. Commercial buildings consume 38,645GWh
(33%) and residential buildings consume 24,709 GWh (21%) respectively (Tenaga,
2012).
3
Although residential buildings consume less energy compared to commercial.
This study focuses on residential buildings because the overall energy use per m2 of
residential buildings is half of that of a commercial building (Jiang, 2011). Thus,
building energy consumption analysis towards conservation should concentrate on the
level of the influencing factors (Ma et al., 2017). The influencing factors used in this
research is the socio-economic factor. Socio-economic factors can only have an
influence on residential buildings but not on the commercial building.
Electricity generation in Malaysia is from a mix fuel sources, namely natural
gas, coal and hydro. In 2008, TNB reported that fuel source for electricity generation
is, natural gas 54%, coal, 28% and hydro 17% (TNB, 2008). The current position of
mix fuel for electricity generation in 2014 as reported by TNB is natural gas 54%,
coal, 35% and hydro 10% (TNB, 2014). The increase and substantial dependence of
electricity generation on coal and natural gas have provided reasons for concerns. The
power industry TNB contributed 60 million tons of carbon emission, this is about 32%
of the total emission in 2005, and this will increase to 153 million tons, about 47% in
2020 (Shamsuddin, 2012). This is due to the over dependency on natural gas and coal
for power generation.
For decades, researchers have worked tirelessly on how to tackle issues related
to global warming and carbon emission. However, the future forecast on the issue is
still uncertain as the problem continuously growing over a period of years. Based on
these conclusions, this study appears with the idea of providing a structural
relationship of building, socio-economic and climate factors in providing an
information which will provide the construction industries with information that will
be of benefit in term of energy efficiency improvements and design of residential
buildings.
1.2 Problem Statement
The major component that contributes to climate change is urban development
(construction activities) which is generating a massive 50% of total greenhouse gas
4
discharges (Griggs et al., 2013). The Malaysian construction industry is well
established and is quite inspiring in its role of providing structural development to its
developmental vision of 2020 (Ibrahim et al., 2010). However, the industry is faced
with a series of challenges, particularly its contribution to carbon emission
(Shamsuddin, 2012). The industry is responsible for an environmental threat in terms
of natural resource consumption and is emitting million tons of carbon annually
(Klufallah et al., 2014).
The Malaysian building sector is responsible for the emission of 5,301 ktons of
GHG with an annual growth rate of 6.4% in 2010, this is equivalent to 20% of the total
GHGs emitted in the country (UNDP, 2009; Zaid & Graham, 2012). The forecast is
expected to reach 8,088 ktons of GHG emission in the year 2014 (Zaid et al., 2015).
Another weak point of the industry is its failure to blend the construction production
process and the design process (Ibrahim et al., 2010). The effort achieved by the
Industrialized Countries of the 1970s and 1980s (Hong Kong, South Korea, Singapore
and Taiwan) towards energy efficiency is as a result of meeting the consumer’s
demands (Zaid et al., 2015). This approach is missing in the Malaysian construction
industry. This study found this problem as a matter that needs proper investigation and
possible solution.
In an attempt to provide a better solution to the above problem, this study focus
is on building energy consumption in relation to socio-economic, dwelling and climate
factors. From the previous studies, socio-economic, dwelling and climate are the
major attributes to residential energy consumption. There is numerous literature
describing the influence of socio-economic on building energy consumption (Chen et
al., 2013; Elisha et al., 2015; Elnakat & Gomez, 2015; Permana et al., 2015; Ryan,
2014; Yue et al., 2013). In addition, some researchers focus on Dwelling Factors
(Baker & Rylatt, 2008; Bedir et al., 2013; Kavousian et al., 2013; Ramírez-Villegas et
al., 2016) while others have considered climate as a factor (Aldossary et al., 2014;
Fumo et al., 2010; Huang et al., 2015; Mirrahimi et al., 2016).
5
On the other hand, some researchers consider the influence of building energy
consumption in residential buildings in a hybrid approach. These hybrid approaches
are socio-economic and dwelling, dwelling and climate and socio-economic and
climate (Figure 1.1). Socio-economic and dwelling factors influence on building
energy consumption is studied by (Jones et al., 2015; Kelly, 2011; Longhi, 2015;
McLoughlin, 2012). In addition, dwelling and climate was studied by (Chong, 2012;
Huang et al., 2015; Kavousian et al., 2013; Mirrahimi et al., 2016) and the last group
consider socio-economic and climate (Blázquez et al., 2013; Kavousian et al., 2013;
Rehdanz, 2007; Štreimikienė, 2014). This study identified these 3 factors as the key
influencing factor of energy consumption in the residential building. Residential
building energy consumption can best understand when considering these 3 factors
(Jones et al., 2015). The study realizes that there is no any study conducted which
combine these 3 factors (socio-economic, dwelling and climate) in providing a useful
information on building energy consumption. Figure 1.1 shows a picture of the
previous studies in relation to socio-economic, dwelling and climate.
Socio-Economic
Socio-Economic and Dwelling
???
Climate
Dwelling and Climate
Socio-Economic and
Climate
Dwelling
Figure 1.1 Research Gap
6
A better understanding of the factors of residential building energy
consumption provides a beneficial information. The information can be utilized in two
ways, the first one is on the implementation of energy policy and the second one is to
help in predicting the future energy consumption. Because of this reason, this study
finds it mandatory to further investigate the relationship of these factors and building
energy consumption. This is in order to provide the construction industries with a
reliable managerial information towards building energy consumption.
1.3 Research Questions
The Research Questions in this thesis is poised to fulfill the objectives in order
to achieve the main aim of the research. Four questions were listed as follows:
i. What are the independent and dependent factors influencing consumption of
energy in residential buildings?
ii. To what extent socio-economic, dwelling and climate factors influence
consumption of energy in a residential building?
iii. To what extend occupants understanding influence energy consumption in
residential buildings?
iv. Do the occupants understanding of these factors improve energy efficiency in
residential buildings?
1.4 Aim and Research Objectives
The aim of the study is to identify a structural relationship of socio-economic,
dwelling and climate factors for improving energy efficiency based on the
understanding of the impacts on residential building energy consumption by the
occupants. This can be achieved through the following objectives:
i. To identify the independent and dependent factors affecting energy
consumption in residential buildings.
ii. To analyze and establish the critical independent factors of energy
consumption in residential buildings based on socioeconomic, dwelling and
climate grouping.
7
iii. To analyze and establish the critical dependent factors of energy consumption
based on energy usage by residential occupants.
iv. To formulate a structural relationship based on the critical established
independent and dependent factors as a strategy for improving energy
efficiency in residential buildings.
1.5 Research Hypothesis
The following null hypotheses were tested at 0.05 levels of significance:
H0 1: Socio-Economic Factors have no significance and no direct effect on
residential building energy consumption.
H0 2: Socio-Economic Factors have no significance and no direct effect on the
dwelling.
H0 3: Dwelling Factor has no significance and no direct effect on residential Building
Energy Consumption.
H0 4: Climate Factor has no significance and no direct effect on Dwelling.
H0 5: Climate Factor has no significance and no direct effect on Building Energy
Consumption.
1.6 Scope of the Research
The focus of this research is on residential building energy consumption. This
study focuses on residential buildings because literature proves that there is an
increasing energy consumption in Malaysia (Kubota et al., 2011). Malaysia being a
developing and industrialized nation, energy consumption has doubled in the last 2
decades due to the residential building energy consumption (Klufallah et al., 2014). In
the year 2010 Malaysia had 7.3 million residential buildings this number is expected to
increase by around 150,000 each year (Al-Obaidi et al., 2014). Any attempt in
reduction and suitable utilization of energy usage by residential occupants will be of
great importance to environmental problems and sustainability related issues (Van der
8
Werff & Steg, 2015). This research focuses more on residential buildings because of
this reason.
The residential buildings considered in this research are; Terraced,
condominium and cluster building. These types of buildings were identified as the
main residential building types in Malaysia (Kubota et al., 2011). The central focus of
this study is on “operational energy” (energy used in the building throughout its
lifespan). The study is not for measuring the usage of the appliances (energy auditing)
rather, is on the assumptions of rational energy usage practice according to
individuals’ understanding of building energy consumption.
The research respondents are the household head of the residential houses
types (Terraced, cluster, and condominium) selected in the study. The questionnaire
respondents were Malay, Chinese, Indians as the three main ethnic groups in Malaysia
(DSM, 2015). The target respondents are the residents of Johor Bahru. Johor,
Malaysia.
Johor state Malaysia serves as the data collection area, under two councils
namely MPJBT (Majlis Perbandaran Johor Bahru Tengah) and MBJB (Majlis
Bandaraya Johor Bahru). The two district covers the metropolis of Johor Bahru which
serves as the location of the research area. Johor state is the second largest state in
Malaysia after Selangor and based on the study by (Kubota et al., 2011) on “Energy
Consumption and Air-Conditioning usage in Residential Buildings in Malaysia” which
was conducted in Johor shows that the rate of energy consumption in residential
buildings is on the increase. This study considers the household head of residential
building in Johor, this is in order to come up with new findings with a recent
information on the current situation in residential building energy consumption in
Malaysia.
9
1.7 Significance of the Research
This research is set to identify the structural relationship of socioeconomic,
dwelling and climate factors in building energy consumption. The significance of this
research could be seen in three aspects as:
i. Significance to the construction industry,
ii. Significance to residential building occupants and
iii. Significance to academic.
i. The need for this study becomes necessary due to the vibrant importance of
construction industry's efforts attached to building energy practice in the field of
residential buildings. The fact that this discipline plays a vital role in reducing carbon
emission and contributes to energy efficiency development in many countries across
the globe. In line with this, it is hoped that the findings from this study will provide a
better solution to the construction industries in the choice of building design. It will
also assist the construction industry professionals in the modification of the existing
concept towards designing and reduction of carbon emission from the residential
sector.
ii. It is believed that without a significant increase in energy efficiency and
significantly decrease of electricity demand from the domestic sector, it is merely
impossible to lower carbon emission. Therefore, this research provides important
information through empirical research. The most vital factors that donate to the
general understanding of residential building occupants on energy consumption was
provided. Findings of this research will give a better understanding of energy
behavior practice by residential building occupants.
iii. More fundamentally, the fact that building energy practice has been recognized
as one of the strategies that can be used to reduce carbon emission. This research
provides students, researchers, and scholars with literature related to the field of
building energy. The findings from this study will add to the wealth of literature and
serve as a reference information material to researchers and construction industries in
10
the areas of building energy consumption. The government, Construction industries,
estate developers and policy makers can find the outcome of this research useful in
term of energy conservation.
1.8 Research Process Framework
The research process framework employed in this study is classified into three
phases. The first phase is taking about the identification of the main research factors.
The identified factors are reviewed through the sources of Journals, conference papers,
thesis and previous studies related to building energy consumption. The literature
reviewed was classified into five major groups. These are the construction industry,
socioeconomic related factors, dwelling related factors, climate-related factors and
electrical appliances commonly use in residential buildings. From these five groups,
pilot questionnaire items were developed. This is how objective one was achieved.
The second phase is the main survey, which includes data collection and data
analysis. The data, which serve as the backbone of this research was obtained through
a face-to-face administered questionnaire. The descriptive survey approach used was
achieved using a 5-point Likert scale structured questionnaire. The method is fast, less
expensive and efficient in term of large population sample (Creswell, 2012) and it may
produce a more honest response (Stangor, 2011). The range of the 5-point Likert scale
questionnaire is from (1 to 5) with the interpretation of strongly disagree as 1 to
strongly agree as 5. A questionnaire template is shown in appendix A1 and A2.
The questionnaire instrument contains 80 items excluding demographic
section. The 31 items of the questionnaire represent the independent factors. These are
14 items for socioeconomic, 11 items for Dwelling Factors and 6 items of Climate.
The remaining 49 items are the independent factors. These are electrical appliances
commonly used in residential buildings, which are categorized into six different
categories. They are Refrigeration System 9 items, Kitchen Devices 8 items, Air-
Condition System 8 items, Bathroom and Laundry Appliances 7 items, Lighting
11
Appliances 8 items and other Home Appliances 9 items. The data were analyzed
using CFA and EFA. This is how objectives 2 and 3 were achieved.
The last phase is about the development of the structural model, validation
process and concluding remark of the overall study. Factor Loadings (FL), Average
Variance Extraction (AVE) and Composite reliability (CR) were used in validating
the model using convergent validity, construct validity and discriminant validity
between each possible pair of constructs (Byrne, 2010; Zainudin, 2012). Details of the
research methodology step fully explain in research methodology chapter (Chapter 3).
Figure 1.2 shows the research framework flow chart.
1.9 Structure of the Thesis
This research considered socio-economic, dwelling and climate factors in
providing useful information on building energy consumption to the construction
industry. The research consists of six chapters as follows:
i. Chapter 1 is on the Introduction of the Research, this includes a brief
introduction, background of the researcher, problem statement, research questions,
aims and research objectives. In addition, research hypothesis, the scope of the
research, research process framework and brief summary of the chapter.
ii. Chapter 2 is on Literature Review on the general aspects of Building
Construction Industry, buildings energy, socio-economic related factors, dwelling
related factors, climate-related factors and summary of the chapter.
iii. Chapter three is on Methodology of this research which includes, research
design and why it was chosen, research sampling technique, data collection and data
analysis process, the validity and reliability of the research instrument and summary of
the chapter.
iv. The fourth chapter is on Results and Discussion which includes the analysis
and discussion of the pilot study and demographic analysis. It further shows the
12
analysis of the independent and the dependent factors of the study and summary of the
chapter.
v. The fifth chapter is on Structural Equation Modeling development, 4 Structural
models were developed. These are SEESM, DESM, CESM and BESM. In conclusion,
a summary of the chapter was presented.
vi. The sixth chapter is on Conclusion and Recommendation of the research,
limitation, and summary of the research.
13
RESEARCH PROCESS FRAMEWORK
PHASE 1
Journals
Thesis
Conference papers
Previous studies
Research objective 1
PHASE 2
Path Analysis
EFA (Exploratory Factor Analysis)
CFA (Confirmatory Factor Analysis)
Main Questionnaire Survey
Data Collection
Data Analysis
Research objective 2 & 3
PHASE 3
Model development
Validation
Existing Concepts
Factor Loadings (FL)
Average Variance Extraction (AVE)
Composite reliability (CR)
LITERATURE REVIEW
(Formulation / Identification of Main Research Factors)
Socio-Economic
Factors
Dwelling
Factors
Climate
Factors
Electrical
Appliances
Pilot Survey
Questionnaire development
Objective 4
Conclusion
Construction
Industry
Figure 1.2 Flowchart of the Research Process Framework
1.10 Summary of the Chapter
This chapter discusses the problem statements, aim and objectives and the
scope of the research. It equally discusses the significance of the research to the
construction industry, residential building occupants, and the academia. In conclusion,
the next chapter “Chapter 2” discuss the overall literature reviewed in this research.
236
237
Energy Commission (2012). National Energy Balance. Tun Hussein, Precinct 2,
Putrajaya, Malaysia.
239
240
International Bank for Reconstruction and Development (IBRD). (2015). Working
for a World Free of Poverty. 2016(20/3/2016).
244
245
Malaysia Economic Report (MER). (2013). Economic Performance and Prospects.
Ministry of Finance Malaysia.
251
Tenaga Nasional Berhad (TNB). (2008). Tenaga National Annual Report. Jalan
Munshi Abdullah, Kuala Lumpur, Malaysia.
Tenaga Nasional Berhad (TNB). (2014). Tenaga National Annual Reports. Jalan
Bangsar, 59200 Kuala Lumpur, Malaysia.
Tenaga Nasional Berhad (TNB). (2012). National Energy Balance. Jalan Tun
Hussein, Precinct 2, Putrajaya, Malaysia
Torkzadeh, G., Koufteros, X., & Doll, W. J. (2005). Confirmatory Fact
253
Zaid, S., & Graham, P. (2012). The Need for Energy Efficiency Legislation in
Malaysian Building Sector. A Comparative Study of South East Asian
Policies.Proceedings of the Construction, Building and Real Estate
Conference. Las Vegas, pp. 200-215, RICS COBRA 2012, Las Vegas,
United States, 10-13 September.
Zainudin, A. (2012). A Handbook on Structural Equation Modeling. Penerbit
Universiti Teknologi MARA Press.