structural equation modeling of energy...

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


3 RESEARCH METHODOLOGY 61

3.1 Introduction 61

3.2 Research Design 61

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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

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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

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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


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



Second-Order Measurement of SEF 119



4.4.10 Modified Second-Order Measurement of

SEF 122

4.4.11 Normality of Modified Second-Order


4.4.12 Standardized Residual Covariance of

Modified Second-Order Measurement of

SEF 123

4.4.13 Content Validity of Modified Second-Order


4.4.14 Covariance of Modified Second-Order


xiii

4.5 First-Order Measurement of Dwelling Factor (DF) 124


Measurement of DF 125


First-Order Measurement of DF 126



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


4.5.7.2 Standardized Residual

Covariance of Initial Second-

Order Measurement of DF 132

4.5.7.3 Covariance of Initial First-Order


4.5.8 Modified Second-Order Measurement of

DF 134

4.5.8.1 Normality of Modified Second-


4.5.8.2 Standardized Residual

Covariance of Modified Second-


4.5.8.3 Covariance of Modified Second-


4.6 First-Order Measurement of Climatic Factors (CF) 136


Measurement of CF 137


First-Order Measurement of CF 137



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



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


Measurement of RS 144


First-Order Measurement of RS 144



4.7.5 Modified First-Order Measurement of RS 146

4.7.6 Content Validity of Modified First-Order





Modified First-Order Measurement of RS 147

4.7.9 Covariance of Modified First-Order


4.8 Initial First-Order Measurement of Kitchen Devices

(KD) 148


Measurement of KD 149


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






Modified First-Order Measurement of KD 151

4.8.8 Covariance of Modified First-Order


4.9 Initial First-Order Measurement of Air-Condition

System (ACS) 152


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






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


Order Measurement of BLA 159


Measurement of BLA 159

4.10.4 Modified First-Order Measurement of BLA 160



xvi




Modified First-Order Measurement of BLA 162

4.11 Initial First-Order Measurement of Lighting

Appliances (LA) 162


Measurement of LA 163


Order Measurement of LA 164



4.11.4 Modified First-Order Measurement of LA 166






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


Order Measurement of HA 169


Measurement of HA 170

4.12.4 Modified First-Order Measurement of HA 170






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


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


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


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


5.6.5 Assessment of Normality of Modified



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


2.2 Authors Responses on Dwelling Factors in Relation to


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


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


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


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


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


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


4.52 Covariance of Modified Second-Order Measurement of DF 136

4.53 Normality 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



4.66 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



4.70 Covariance of Modified First-Order Measurement of RS 148

4.71 Normality of Initial First-Order Measurement of Kitchen

Devices (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



4.77 Covariance of Modified First-Order Measurement of KD 152

4.78 Normality of Initial First-Order Measurement of Air-

Condition System (ACS) 154



4.80 Covariance of First-Order Measurement of ACS 155


ACS 156

4.82 Normality of Modified First-Order Measurement of ACS 157



4.84 Normality of First-Order Measurement of Bath and Laundry

Appliances (BLA) 159



4.86 Covariance of Initial First-Order Measurement of BLA 160

xxiv


BLA 161

4.88 Normality of Modified First-Order Measurement of BLA 161



4.90 Normality of Initial First-Order Measurement of Lighting

Appliances (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



4.96 Normality of First-Order Measurement of Home Appliances

(HA) 169



4.98 Covariance of Initial First-Order Measurement of HA 170


HA 171

4.100 Normality 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


xxv

5.2 Regression Weights of Modified Socio-Economic Energy


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


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


5.13 Variances of Modified Structural Equation Model Exploring


Consumption 214

5.14 Squared Multiple Correlations of Modified Structural

Equation Model Exploring Relationship of SEF, DF, CF and


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


Consumption 217

5.17 RMSEA of Modified Structural Equation Model Exploring


Consumption 218

5.18 AIC of Modified Structural Equation Model Exploring


Consumption 218

5.19 ECVI of Modified Structural Equation Model Exploring


Consumption 218

5.20 HOELTER of Modified Structural Equation Model Exploring


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


Dwelling Factor and Building Energy Consumption 189


of Dwelling Factor and Building Energy Consumption 192

xxix


Climate Factor and Building Energy Consumption 195


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



Socio-Economic Factor, Dwelling Factor and Climate Factor

in Relation to Building Energy Consumption 204


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

xxxii

US - United State

UTM - Universiti Teknologi Malaysia

VCR - Video Cassese Recorder

.

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.

232

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233

׳

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