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STUDY OF

HOUSING ADJUSTMENT IN RIYADH, SAUDI ARABIA

A THESIS

SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL

OF THE UNIVERSITY OF MINNESOTA

MOSAID ABDULLAH AL-SADHAN

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

PROF. DENISE A. GUERIN, ADVISOR

JULY, 1999

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MOSAID ABDULLAH AL-SADHAN

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In the Name of God, the Compassionate, the Merciful

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ACKNOWLEDGMENTS

The completion o f this work would not have been possible without the

valuable guidance and mentoring o f my advisor, Dr. Denise Guerin, whose

insightful feedback and input brought this research effort to completion. I am very

grateful and wholeheartedly thankful to her for everything she has done through

my graduate studies and this study in particular.

I am equally thankful and grateful to Dr. Earl Morris; without his feedback

on this work and intelligent suggestions in running the data and conducting the

analysis, the successful completion of this study would have been difficult. Dr.

Morris opened his house in Ames to me and assisted me, despite his various

commitments, when I needed him most. Both Drs. Guerin and Morris have

shown extraordinary understanding by accepting different versions of this study

to read on short notice.

My thanks and gratitude also go to professors John Cummings, Roger

Clemence, and Marian-Ortolf Bagley; their courses were provocative, while their

thoughtfulness and concern about my family and myself were appreciated. I am

very fortunate to have caring and experienced professors who agreed to serve

on my committee even after their retirement.

Special thanks go to the office of Saudi Arabian Cultural Mission in

Washington.DC, especially my advisors there, Hydar Elawad and Dr. Ahmad Al-

Aswad, whose relationships served as moral support and encouragement for this

work.

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I am grateful to the King Saud University in Riyadh, Saudi Arabia for hiring

me as a teaching assistant and giving me this opportunity to pursue my higher

education with a full scholarship that pays for tuition and living expenses. Without

this help, this entire project would not have been possible.

In the School of Architecture and Planning, I am thankful to Dr. Mohamad

Ben Saleh for encouraging me to pursue my higher education and to Prof. Faraht

Tashkandie, Dr. Ahmad Al-Olet, Dr. Ebraheem Al-Jowair for their input about the

study in its early stages. Words of thanks also go to Dr. Ahmed Al-Saif and his

students for distributing the questionnaires.

Other kinds of support for this study came from Ali Al-Shuaibi and

Abdulrahman Al-Husainie from Beeah Group who opened their doors and made

their office resources available during my field trip. They offered me all types of

support and showed endless encouragement.

Thanks to my friends in the United States and Saudi Arabia, especially

Mohamad Ben Gaith from the municipality of the City of Riyadh, for the lengthy

discussion about different housing issues in Riyadh.

Finally, my special thanks go to my wife who stood beside me and

tolerated me and provided endless support, kindness, and patience. My mother,

brothers, and sisters, as well as my wife’s family also deserve to be appreciated

for their encouragement and prayers. My love goes to my children Mohamad and

Nora who shared with their dad his computer, papers, and pens.

iii

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ABSTRACT

Saudi Arabia in general and Riyadh City in particular experienced an

increased demand for housing during the last twenty-five years because of

population growth and economic development. To boost housing development,

the Saudi government established several agencies, among which are the Real

Estate Development Fund (REDF) to provide cash loans and The Ministry of

Public Work and Housing (MPWH) to build ready-to-move-in houses. Shortly

after the households moved into houses funded by either agency, they started to

adjust their houses. This adjustment behavior suggests a low level of household

satisfaction.

This study explores the differences in households housing adjustment

behavior between the two housing types, with satisfaction being part of such a

behavior. Using the Morris and Winter Model of housing adjustment as a

theoretical framework, it was hypothesized that there was no difference in

housing adjustment between the two housing types, no significant effect of the

predictors (households’ variables, housing construction variables, previous

adjustment variables) in each housing type on housing characteristic variables

and housing adjustment behavior variables, and no sequential effect among

housing adjustment behavior variables.

Data were collected for both types of the houses in Riyadh with a sample

size of 230. The analytical method consisted of a quantitative survey analysis

using multiple regression. Descriptive analysis focused on all variables in the

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model. A correlation coefficient revealed the bivariate associations between

variables included in the models.

Significant differences were found between the two types of houses and

certain predictors of housing characteristics and household adjustment behavior

in each housing type were identified. The study also found partial sequential

effect among adjustment behavior variables, which are household deficit,

satisfaction, propensity to adjust, and expected future improvement.

The study emphasized the need to have the households involved in the

design and construction process. It also validated and extended the Morris and

Winter model. The findings benefit interior designers, architects, and housing

policy makers by enlightening them about the phenomena of household

adjustment behavior and its variables, thus making a positive contribution to

housing design and development in Saudi Arabia.

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TABLE OF CONTENTS

Acknowledgments........................................................................................................... ii

Abstract............................................................................................................................iv

Table of Contents..........................................................................................................vi

List of Figures................................................................................................................. x

List of Tables..................................................................................................................xi

Chapter 1: Introduction..................................................................................................1

Housing in Saudi Arabia.............................................................................1

Statement o f the Problem......................................................................... 4

Purpose and Significance of the Study....................................................5

Outline of the Study................................................................................... 6

Introducing the Country.............................................................................7

Location and Topography.............................................................. 8

Climate.............................................................................................. 8

Demography.................................................................................. 10

Migration......................................................................................... 12

Internal Migration...........................................................................13

Other Demographic Data............................................................. 13

Social L ife ..................................................................................................14

Culture and Religion..................................................................... 14

Fam ily............................................................................................. 16

Housing Styles..........................................................................................18

Traditional Houses........................................................................ 18

Contemporary Houses..................................................................21

Organizations Contributing to Housing Development......................... 26

Government Support of Housing...........................................................27

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Chapter 2: Literature Review.....................................................................................31

The House as a Human Space............................................................. 31

Characteristics o f Space Use...................................................... 32

Organization of the House.......................................................... 35

Housing Evaluation in General................................................... 36

Housing Adjustment Studies..................................................................38

The Case of Korea....................................................................... 39

The Case of Mexico..................................................................... 40

The Case of the United States....................................................41

Housing Adjustment in Saudi Arabia....................................................44

Limitations of Previous Studies............................................................. 48

Adjustment and Adaptation Theory......................................................49

Overall Concept o f the Theory....................................................49

Definitions of Concepts................................................................50

The housing norm s.......................................................... 51

Current housing conditions...............................................51

Normative deficits..............................................................51

Satisfaction or dissatisfaction.......................................... 52

The intention of adjustment behavior............................. 52

The actual adjustment behavior......................................52

The constraints..................................................................52

The values..........................................................................53

Theoretical Model o f Housing Adjustment.................................53

Housing Setting in R iyadh..................................................................... 57

Research Model...................................................................................... 60

Chapter 3: Method......................................................................................................63

Assumptions of the M odel..................................................................... 63

The Null Hypotheses..............................................................................64

vii

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Research Instrument..............................................................................67

Questionnaire Design and Development.................................. 68

The First Draft................................................................... 69

The Second Draft............................................................. 70

The Final D ra ft..................................................................71

The Variables..........................................................................................72

Independent Variables.................................................................72

Household variables......................................................... 72

Housing construction variables...................................... 74

Previous adjustment variables........................................75

Dependent Variables................................................................... 76

Physical housing characteristics variables.................... 76

Housing adjustment behavior variables.........................77

Data Collection Procedures................................................................... 79

Site Selection................................................................................ 79

Distribution of the Questionnaires.............................................. 81

Site Observation............................................................................82

Data Entry.............................................. 83

Chapter 4: Analysis and Findings.............................................................................85

Analytical Procedure...............................................................................85

Sample Description................................................................................. 87

Household Variables.................................................................... 87

Housing Construction Variables................................................. 90

Previous Adjustment Variables.................................................. 92

Physical Housing Characteristics Variables.............................. 93

Housing Adjustment Behavior Variables....................................95

Household deficit...............................................................95

Housing satisfaction......................................................... 99

viii

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Propensity to adjust.........................................................100

Expected future improvements...................................... 101

Discussion of Sample Distributions......................................................102

Correlation Coefficients........................................................................ 107

Regression Analyses.............................................................................112

Physical Housing Characteristics Variables.............................114

Size of the house ............................................................ 114

Condition of the house................................................... 116

Housing Adjustment Behavior Variables.................................. 118

Household deficit............................................................. 119

Housing satisfaction........................................................122

Propensity to adjust.........................................................124

Expected future improvement....................................... 126

Hypothesis Testing................................................................................ 128

Discussion of the Findings....................................................................138

First Theme.................................................................................. 139

Second Theme.............................................................................142

Third Theme................................................................................. 150

Chapter 5: Conclusions, Limitations, and Implications........................................ 151

Conclusions............................................................................................ 151

Limitations of the S tudy........................................................................ 154

Implications............................................................................................. 156

References................................................................................................................ 159

Appendixes................................................................................................................ 166

Appendix A: English Version of the Questionnaire...................................... 166

Appendix B: Arabic Version of the Questionnaire........................................179

Appendix C: Abbreviation and Conversion Equivalents..............................192

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Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

LIST OF FIGURES Map of Saudi Arabia and neighboring countries..................................... 9

A traditional house in Riyadh, Saudi Arabia......................................... 19

A contemporary house in Riyadh, Saudi Arabia................................... 22

An aerial view o f neighborhood of traditional houses in Riyadh,

Saudi Arabia .............................................................................................23

An aerial view o f neighborhood of contemporary houses in Riyadh,

Saudi Arabia.............................................................................................. 23

Making adjustment by adding a room, Riyadh, Saudi Arabia............. 46

Making adjustment by raising the fence, Riyadh, Saudi Arabia..........46

Theoretical Model of Housing Adjustment............................................. 54

Research Model of Housing Adjustment in Riyadh, Saudi Arabia 61

Variables and their corresponding question numbers in housing

adjustment in Riyadh, Saudi Arabia....................................................... 73

The significant predictors and their coefficients of both REDF and

MPWH houses with shared variables (Model 1)................................. 140

The significant predictors and their coefficients of the MPWH houses

with shared variables (Model 2)............................................................ 143

The significant predictors and their coefficients of the REDF houses

with shared variables (Model 3)............................................................ 145

The significant predictors and their coefficients of the REDF houses

with all variables (Model 4).................................................................... 148

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LIST OF TABLES

Table 1 The process of building and living in a house as it applies to houses

built through the financial assistance of the REDF...............................58

Table 2 The process of building and living in a house as it applies to prototype

houses built by the MPWH...................................................................... 59

Table 3 The four models and the related variables............................................ 66

Table 4 Distributions of household variables........................................................ 88

Table 5 Distributions of housing construction variables...................................... 91

Table 6 Distributions of previous adjustment variables....................................... 93

Table 7 Distribution of the housing size variable............................................... 94

Table 8 Distribution of the housing condition variable...................................... 95

Table 9 Distribution of household deficit measured by privacy features and

the perceived sufficiency of guest space...............................................96

Table 10 Distribution of housing satisfaction........................................................ 99

Table 11 Distribution of propensity to make changes to current house.......... 100

Table 12 Distribution of propensity to move from the current house............... 101

Table 13 Distribution of expectation about future improvements..................... 102

Table 14 Pearson product-movement correlation coefficient matrix of the

MPWH and REDF combined houses for Model One.........................108

Table 15 Pearson product-movement correlation coefficient matrix of the

MPWH houses for Model Two..............................................................109

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Table 16

Table 17

Table 18

Table 19

Table 20

Table 21

Table 22

Pearson product-movement correlation coefficient matrix of the REDF

houses for Models Three and Four...................................................... 110

Regression analysis of size of the house on the household variables,

housing construction variables, previous adjustment variables, and

housing type variable............................................................................. 115

Regression analysis of condition of the house on the household

variables, housing construction variables, previous moving adjustment

variables, and housing type variable................................................... 117

Regression analysis of household deficit on the household variables,

housing construction variables, previous adjustment variables,

physical housing characteristics variables, and housing type

variable....................................................................................................120

Regression analysis of housing satisfaction on the household

variables, housing construction variables, previous adjustment

variables, physical housing characteristics variables, housing type,

and household deficit.............................................................................123

Regression analysis of propensity to adjust on the household

variables, housing construction variables, previous adjustment

variables, physical housing characteristics variables, housing type,

household deficit, and housing satisfaction.......................................125

Regression analysis of expected future improvement of housing

situation on the household variables, housing construction variables,

previous adjustment variables, physical housing characteristics

variables, housing type, household deficit, housing satisfaction, and

propensity to adjust...............................................................................127

XII

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Chapter 1

Introduction

This chapter describes the housing situation in Riyadh, Saudi Arabia. It

gives a statement of the problem, followed by a brief description of the purpose

and significance of the study. An outline oFthe study is then given followed by a

general introduction of the country, including its location, its topography, and

some demographic data. This chapter also describes the Saudi social life at the

cultural, religious, and family levels. The housing style consisting of traditional

and contemporary houses is then explained. The Chapter introduces the various

organizations contributing to housing development, followed by a brief

description of government support of housing development.

Housing in Saudi Arabia

Over the last twenty-five years, Saudi Arabia in general and the city of

Riyadh in particular, have experienced a huge and rapid growth in housing. This

rapid growth in housing construction was due to the increase of oil revenue in

the mid-1970s. This revenue helped the Saudi government establish different

agencies to assist in creating adequate and affordable housing for its rapidly-

growing and youthful population. The fact that traditional houses were outdated

due to lack of modem facilities also accelerated the construction of contemporary

houses.

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To assist with this increase in housing construction, the Saudi government

established two agencies in 1974. First, the Real Estate Development Fund

(REDF) agency, which is attached to the Ministry of Finance and National

Economy. The main goal o f the REDF is to assist in the development of private

sector housing by providing long term, interest free loans to Saudi citizens that

are repaid in annual installments over twenty-five years. Second, the government

established the General Housing Department (GHD) to implement its housing

program. The GHD was also attached to the Ministry of Finance and National

Economy. In 1975, one year after its establishment, the GHD converted to an

independent agency now known as the Ministry o f Public Works and Housing

(MPWH).

The MPWH’s intent was to build ready-to-move-into multilevel apartment-

type units. In the late eighties, it also started to build single-family, detached

housing developments. The MPWH did not have a method to fairly distribute

their units to the citizens. As a result, their houses were left vacant for a number

of years until the government decided to transfer these units to the REDF

agency, which had a seven-year waiting list. The REDF offered its applicants the

option of purchasing the MPWH houses. The cost of the houses was considered

an REDF loan. Many applicants’ names that were at the top o f the waiting list

were pleased with the offer and chose to purchase a ready-to-move-into house,

that would save them the effort of building their own houses. Others chose this

offer for business purposes, such as offering it for rent in the market or even

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selling it within a few weeks o f the purchase because it had higher market value

than the initial purchase from the government. In general, both the REDF and

MPWH supported the citizens to move from their traditional houses and to build

or purchase new houses using new materials and following new building

regulations.

The citizens were choosing to leave their traditional houses because of

the inability of these houses to satisfy the families’ growing needs, such as the

need for wider streets. Traditional neighborhoods in the city of Riyadh were not

developed for modem transportation because of their narrow streets designed

for pedestrians and animals. In addition, traditional houses are not equipped

with modem bathrooms, nor do they have spacious rooms. For many occupants,

making changes to modernize these traditional houses would require major

renovation that could not be supported by the structure of these traditional

houses, hence the need to acquire a modern house.

For hundreds of years, Riyadh residents have lived in traditional houses

that were built using local building materials such stone, adobe bricks for the

walls, and palm thatch for the roofing. They had developed sophisticated local

construction techniques as well as being respectful of building regulations

inspired by their religious and cultural principles (Akbar, 1984). However, these

traditional construction practices and regulations changed after the emergence

of new concepts o f land subdivisions, zoning, and building laws (Akbar, 1984; Al-

Hathloul, 1981).

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An international planning firm, Doxiadis Associates, was commissioned by

the Saudi government to develop a Master Plan for the city o f Riyadh including

subdivision of newly developed land as well as developing building regulations

for new houses (Doxiadis, 1971). The Council of Ministries, the highest authority

in the country, approved the Master Plan in 1973. In 1981, a French planning

firm, SCET International, was hired by the government to update Doxiadis’

Master Plan and to include guidelines to local municipalities to subdivide the land

(SCET, 1981). This Master Plan gave the REDF and MPWH the planning

principles and building regulations to support a massive housing development for

the citizens.

The oil revenue gave the government the resources and the ability to

implement these plans. Citizens were choosing to leave their traditional houses

because of their inability to satisfy the families’ growing needs, such as wide

streets for car accessibility, spacious rooms, modern bathrooms, and kitchen

equipment.

Statement of the Problem

The citizens built their new houses with the financial assistance of REDF in

the approved land within the master plan and under its building regulations. Then

they started making changes to their houses. Additionally, many households who

received ready-to-move-into houses began making changes to their houses. For

both groups, many adjustments were made before the families even moved into

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the units. The local municipalities were overwhelmed with applicants trying to

obtain construction permits to make certain construction changes to their new

units (Riyadh Daily, 1995). This trend suggests that there was considerable

dissatisfaction with their units, leading the residents to seek adjustments to these

units. The level of dissatisfaction and the reasons for the adjustments need to be

determined.

Purpose and Significance of the Study

The purpose of this study is to gain a better understanding of the housing

adjustment phenomenon in Riyadh, Saudi Arabia. A post-occupancy evaluation

was conducted to assess the residents’ perspectives and their attitudes towards

their units and to measure the level o f satisfaction for each type of housing. In

addition, an attempt was made to discover the major variables affecting housing

adjustment practices and processes.

The study has implications for housing practice of the REDF and the

MPWH. In addition, the results of the study can have implications for the

residents and their attitudes towards their housing. The results can raise the

level o f awareness of all the stakeholders involved in housing development

about changes in the household and its housing characteristics over time.

Designers could then consider these determinants of housing adjustment when

planning housing developments. As far as the residents are concerned, better

decisions can be made when developing ideas about new houses. In brief, the

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findings of this study could be used to better understand residential adjustment

behavior and how it might affect the individual households and the society as a

whole. By being aware of the attitudes and preferences driving the housing

adjustment behavior of Saudi citizens, housing planners, architects, and

designers can make better decisions in dealing with existing houses or when

planning for future ones.

Another important aspect of the study is to test the validity of the Housing

Adjustment and Adaptation Theory, which originated in the United States. The

Housing Adjustment and Adaptation Theory deals with changes made to the

dwelling by the households while living there to rectify their space and other

normative deficits. The theory was developed over the last thirty years by Morris

and Winter (1978,1994). It has been used and enriched by many researchers

who applied it, or some aspects of it, to their research studies in the United

States, Mexico, Poland, and Korea. By testing the theory in Saudi Arabia, the

flexibility of the theory can be determined for implementation in cultural settings

similar to that of Saudi Arabia, such as other Arabian Gulf countries and other

Arabic countries (e.g. Egypt, Morocco, Tunisia, and Lebanon).

Outline of the Study

The study is organized into five chapters. Chapter One deals with the

nature of the problem, the importance of the study, and implications. It gives the

background of Saudi Arabia, in terms of its location, topography, climate,

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population, and the culture in general. Chapter Two reviews the literature on

housing studies by looking at the issues related to housing, such as

characteristics and organization of housing space and its evaluation. Chapter

Two also reviews studies about housing adjustment in general and in Saudi

Arabia in particular. This is followed by discussion of the Adjustment and

Adaptation Theory. The variables of the study are identified and a research

model is formulated. Chapter Three deals with the methods used in conducting

the study, starting with defining the housing setting of the research and the

hypotheses. The procedures used for data collection, including the research

study instrument, questionnaire design, and development are all included. The

independent and dependent variables are defined. Chapter Four examines the

data and analyzes it. It includes frequency distributions and other basic statistical

analyses of the variables, followed by regression analyses of the models and

testing of the hypotheses. The Chapter ends with a discussion of the findings

and their significance. Finally, Chapter Five gives some concluding remarks

drawn from the research, the implications of the results, and the limitations of the

study.

Introducing the Country

The housing conditions in Saudi Arabia cannot be seen in isolation from

several determinants, among which are the location, climate, and demography.

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This section describes these determinants in ways that help understand the

motives driving housing adjustment practices.

Location and Topography

As shown in Figure 1, Saudi Arabia is bordered by the Red Sea on the

West; by the Persian Gulf on the East; Jordan, Iraq, and Kuwait on the North;

and Yemen and Oman border it on the South. It lies between 16' N and 32' N,

with an area of 2.25 million square kilometers. The natural setting could be

divided into six regions. The Rub-al-Kali and other deserts in the Central and

Northern regions make up 50% of the geographical area. The Central Plateau

where Riyadh, the capital city, is located, comprises 32% of the land. The Hijaz

and Assir Mountains comprise 7%, Tihama and the Western coastal plain

comprise only 2%, the Eastern lowlands 5%, and the Northern Plain and Jouf

region comprise 4% of the total geographical area (Al-Hatloul & Edadan, 1993).

Climate

Under the influence of a sub-tropical high-pressure system, rainfall over

Saudi Arabia is normally scarce. The summer is hot and dry with annual rainfall

about 131.2 millimeters (0.43 ft). Extremely high temperatures (120° F) with

dramatic daily variations are found in the interior parts of the region, where

Riyadh City is located, especially during the summer. In winter, the effect of the

high-pressure system is reinforced by an occasional intrusion of higher pressure

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Iraq

Iran

Kir

Arabian . Gulf

Bahrain

QatarRiyadhMadinah

Saudi ArabiaJiddah Mecca Oman

Red Sea

Sudan

/Eritrea Arabian SeaYemen

SOO250

Kilometers

EthfopFa 300150Djibouti Miles

Somalia

Figue 1 • Map of Saudi Arabia and neighboring countries (Maplnfo, 1998).

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from the cold Siberian region, bringing in lower temperatures over the country.

Thus, except along the coastal strip, which is under the moderating influence of

the adjoining seas, the winter is generally cold (32° F) and dry (Daghistani,

1985).

Demography

The official census is conducted every ten years. The most recent one is

from 1992. According to this census, the total population, including Saudis and

non-Saudis, is 16,929,294. The number of Saudis is 12,304,835, representing

72.7% of the total population in Saudi Arabia. Saudi males equal 6,211,213,

representing 50.5% of the population, while Saudi females equal 6,093,222,

representing 49.5% of the Saudi population. The total number of non-Saudis is

4,624,459, representing 27.3% of the total population. Non-Saudi males are

3,255,328, representing 70.4% of non-Saudi population, while the number of

non-Saudi females are 1,369,131, representing 29.6% of the non-Saudi

population. There are 2,791,044 houses. The majority of these houses are

occupied by a large number of inhabitants ranging from 5 to 10 people (Central

Department of Statistics, 1992).

These are the only current data available. There are no up-to-date

statistics about fertility, mortality, or migration, which are the three elements that

determine the population size of a specific area at a specific time (Morris, 1994).

When a thorough and high quality census is unavailable, many planning

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problems related to housing, such as poor estimation o f the housing growth, are

likely to emerge.

Given the importance of knowing the population in a specific city or town,

and because the population census is carried out at long intervals, Ali (1993)

developed a method of estimating the population of Riyadh. The method he used

is based on the analysis of aerial photographs and consists o f black-and-white

format images covering the city of Riyadh and the surrounding area. The results

show that the estimated population of Riyadh is 2,055,954 (Ali, 1993). Al-Otebi

(1993) pointed out the lack of accurate projected census data. He argued that

the population of Riyadh as of 1990 had grown to 1.4 million during the past 15

years, contrary to what has been projected (around 1.1 million by the year 2000).

Al-Otebi’s numbers about the population of Riyadh are not consistent with that of

Ali’s, since the latter based his population estimate on analysis of aerial

photographs.

According to Al-Otebi (1993), it is necessary that development plans be

adjusted to accommodate the increase in Saudi population. The mechanisms

underlying population change have been outlined by Morris (1994) who stated

that:

The population at one time point is the result of adding to the

population at an earlier time the number of births that occurred

from the first time point to the second, subtracting the number of

deaths, adding the number of immigrants, and subtracting the

number of emigrants. There is no other way for the population [the

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number o f inhabitants] to change from one time to another except

by birth, death, immigration, and emigration, (p. 19)

In a study about the pattern of human resource development in Saudi

Arabia, Looney (1991) concluded that the Saudi population is very youthful. He

also indicated that the private sector seeks to attract and mobilize large numbers

of cheaper workers who usually come from Far East Asian countries.

Migration

Because of the high number of foreign workers in Saudi Arabia, the World

Bank ranked Saudi Arabia as having the fourth highest migration rate in the

world, with a migration rate of 325 in every thousand (World Bank, 1990). In

contrast, the Central Intelligence Agency reported a zero (0) migration rate in

Saudi Arabia.

This contradiction between the two sources can be explained by the fact

that migration was defined differently by the two institutions. The World Bank

(1990) defines migrants as being “individuals who have resided for at least a

year in countries other than their previous residence” (p. 10). The number of

foreigners who entered Saudi Arabia was 4,847,250 in 1989. These people were

considered migrants in the World Bank report. In the CIA report, those

individuals were considered a labor force that entered the country by working

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visa and not migrants who settled and lived there for the rest of their lives.

Consequently, the migration rate, according to the CIA report, amounts to zero.

Huyette (1985) indicates that roughly three million of the expatriate

community lived in Saudi Arabia in 1993. They represent a wide variety of

nationalities and a full gamut of occupational types. They were attracted by

financial incentives and most of them leave when they have saved enough

money to enjoy a better life in their home countries.

Internal Migration

Internal migration deals with the migration rate within the country. A brief

report based on a comprehensive survey for the city of Riyadh indicated a high

level of internal migration. Only 25% of the heads of the households spent their

childhoods in the city of Riyadh. It is also noted that 75% of Saudi heads of

households moved to their current dwelling within the past five years. The main

reason for moving was to occupy a new house they had built or because of the

increasing number of their family members (High Commission, 1987).

Other Demographic Data

The birth rate is 38.59 births/1,000. As for the death rate, it amounts to

6.05 deaths/1,000. As a result, the growth rate is 3.25%. The infant mortality rate

is 55.3 deaths/1,000. The life expectancy for males is 65.71 years and 69.01

years for females, making the life expectancy for the total population equal to

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67.32 years. Ninety percent o f the population are Arabs and 10% are Afro-Asian.

The labor force percentage by occupation is as follows: government 34%,

industry and oil 28%, services 22%, and agriculture 16% (CIA, 1993).

Social Life

Culture and Religion

Turner (1982) defined culture as “a system of meaningful symbols that

people in a society create, store, and use to organize their affairs” (p. 125). In a

large and complex country like the United States, there are subcultures whose

members have the same values and beliefs that may differ from those of the

majority. As an example, there are religious groups, such as the Amish, who live

in separate communities, creating societies within a society.

Culture is reflected in people’s perceptions, beliefs, values, norms,

customs, and behaviors and is manifested in objects and the physical

environment. Home design, layouts of villages, communities, cities, public

buildings, and places are manifestations of the values and beliefs of a culture

(Pandey, 1990).

Religion has two universal functions: first, it reinforces critical norms, and

second, it alleviates and mitigates anxiety and tension. Religious values are the

conception that people hold about what is good or bad, appropriate or

inappropriate. Norms that have been ordained by a people’s god are less likely

to be violated (Turner, 1982).

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In the case of Saudi Arabia, there are remarkably few distinctions

between the religious and the secular. Religious values and norms play a major

role in shaping people’s norms. Additionally, there is the umbrella of cultural

norms that also cover tradition- and custom-based norms. Both culture and

religion are shapers of a people's house form.

Changes have been observed in Saudi households' housing norms in

terms of the appropriate size of the bedrooms and amount of living space in

general. These changes seem to be driven by the change of housing supplies

and household resources. However, there has been little change in housing

norms related to religious principles such as privacy, which here means a

separation of genders for those who are not part of the immediate family. In a

Saudi house, there are two separate places for receiving visitors, one for males

and another for females. They are separated visually and acoustically: ‘The

impact o f Islamic tradition is important in understanding Saudi Arabia because

the Koran, its holy book, is the equivalent of a secular constitution" (Kirk, Martin,

& Palmer, 1993, p. 37).

Pawell (1983) asserts that discussion of Saudi Arabia requires a

discussion of Islam. Islam is not simply a creed but is a comprehensive way of

life. The following verses from the Koran are examples of the basic principles

regulating the Muslim community: “You who believe! Enter not houses other than

your own, until you have asked permission and greeted those in them, that is

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better for you, in order that you may remember” (p. 1011). A commentary by Ifta

(1990) states that:

The rule about dwelling-houses is strict, because privacy is

precious, and essential to refined, decent and well-ordered life.

Such a rule o f course does not apply to houses used for other

useful purposes, such as an inn or caravansary, or a shop or a

warehouse. But even here, of course, implied permission from the

owner is necessary as a matter of common sense. The question in

this passage is that of refined privacy, not that of rights of

ownership, (p. 1011)

Family

Many researchers have conducted studies about the development of the

family and its transition from tradition to modernity in Saudi Arabia. In his

dissertation, Al-Juwayer (1983) made the following conclusions: “We found a

complementary blend of religious beliefs and modem impulses, e.g., continued

high religiosity, but some tempering of tradition rigidity, continued family

solidarity” (p. 9).

It seems that most family values and practices are guided by a

combination of religion and tradition. The extended family used to be the norm

for Saudi families. Today, the setting is slightly different, with many families living

in households consisting of a husband, wife, and children, as well as the

husband’s father and mother. For example, a mother, a father, or both, who are

in their sixties or older with several married daughters and sons and no single

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children, have one of their married sons stay with them along with his family.

Other married children have their own separate houses and try to locate their

houses as close as possible to their parents. Sometimes an elder single parent

moves to the son’s home where he or she gets full respect from the head of the

household as well as from the grandchildren.

The elderly have a status of considerable prestige and remain the

head o f the family until death. Respect for the elders comes from beliefs in

their prayer efficacy and curses (Kirk, et al., 1993). In certain societies, the

knowledge and experience of the elderly make them a valuable resource

for the younger members of the home (Turner, 1982). It seems that the

main reason for respecting parents is actually part of following the

instructions of the Koran, the holy book of Muslims. Other reasons, which

are considered secondary in the Saudi culture, include the belief in the

efficacy of their prayers and the benefit of their knowledge and wisdom.

There are numerous verses in the Koran emphasizing the need to respect

parents and the elderly and the reward associated with that. In this regard,

the Koran states that “...if one of them or both of them attain old age in

your life, say not to them a word o f disrespect, nor shout at them but

address them in terms of honor (p. 782).

These cultural and religious norms influence the behavior of the

Saudi households, which in turn are reflected in design and style of their

housing. A discussion of the relationship of housing style follows.

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Housing Styles

Based on building layout and structure style, houses in Riyadh, Saudi

Arabia, can be classified as either traditional or contemporary. The traditional

houses continue to decrease in number and are on the verge of distinction while

contemporary houses are gaining ground rapidly and becoming more popular.

Saudi citizens are seemingly becoming more attracted to new types of housing

that are different in terms of spatial organization and building materials and are

labeled as contemporary houses or villas. Both housing styles, traditional and

contemporary, are described below.

Traditional Houses

Traditional houses are built from local building materials such as adobe

and the trunks of the palm trees. They were developed through inter-

generational experiences in ways that cope with the regional climate, meet

residents' needs, and fit well with the culture and religion. The design of the two-

story traditional house is based on a courtyard concept (see Figure 2). The

courtyard is surrounded by different types of rooms, such as the family room, the

kitchen, the bedrooms, and the bathroom.

Traditional houses consist of two separate domains guided by cultural

norms governing gender relationships. Male guests not related to the immediate

family and female family members are strictly separated through the use of two

separate domains; family domain and public domain. The public domain, which

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( ’ found Jloor plan

Figure 2.

ROOF

m ROOF

guest room

i'irs l f lo o r p lan I

Section

A traditional house in Riyadh, Saudi Arabia (Kilical, 1986). 19

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is represented by the guest room o f the house, is normally located close to the

entrance and on the first floor. It is used to meet the multiple needs o f the guest,

such as dining and sleeping. The family domain consists of all other spaces.

Family rooms are normally located on the ground floor close to the kitchen. The

bedrooms are located in the ground floor and used during the winter season for

sleeping at night. During the summer, household members use the roof for

sleeping. These traditional houses are usually occupied by an extended family

and when the size of the family increases further, more bedrooms could be

added in the first floor. The average square area of a room ranges from nine to

12 square meters («100 -130 square feet).

The kitchen is located on the ground floor and is used for daily cooking

and food storage. To allow for air circulation, and because these houses were

designed prior to the introduction of electricity in the country, there is usually an

opening in the roof of the kitchen. The bathroom is normally located in a corner

or under the stairs and is made easily accessible to occupants in both floors

including guests.

Among the salient features o f traditional houses is the fact that they are

attached to each other, with one fagade facing the street (see Figure 4). These

houses do not have windows in the ground floor overlooking the street to

maintain household privacy. These rooms get light and ventilation through the

inside courtyard. Rooms in the first floor tend to have many small windows

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overlooking the street. The windows are located above the eye level to ensure

adequate privacy.

Contemporary Houses

Contemporary houses or villas started to appear in Riyadh at the

beginning of the 1950s (see Figure 3). They have become the dominant type of

houses built by the REDF since 1974. Reinforced concrete is used for the main

structure of these houses. Cement, plaster, and paint are used for finishing.

This type of housing design is influenced by western ideas in terms of materials,

building codes, and regulations that play a major role in setting new norms for

residences in Saudi Arabia.

The design of the contemporary house follows the rules that govern the

setback and the floor area ratio, which are determined by Riyadh Master Plan

guidelines. The house must be detached from the surrounding neighbors’ lots by

at least two meters (6.6 feet), providing a yard space. To maintain privacy and

security for the household, the lot itself has to be bounded by a wall as high as

eye level and sometimes even higher. However, the surrounding wall fails to

maintain visual privacy for residents who use the front and the back yard, from

neighbors’ first floor windows.

In theory, the concept of the contemporary design reversed the concept of

traditional houses where the private center courtyard is replaced by a setback

that provides a front and back yard (see Figure 4 and 5). However, these

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First Floor Plan

- i i-

Ground Floor Plan

10 15 m

Figure 3. A contemporary house in Riyadh, Saudi Arabia (Al-Saif, 1994).

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Figure 4. An aerial view of neighborhood o f traditional houses in Riyadh,

Saudi Arabia (Daghistani, 1985).

Figure 5. An aerial view of neighborhood of contemporary houses in Riyadh,

Saudi Arabia.

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setback regulations do not provide privacy from neighbors’ windows. On the

other hand, household privacy within the interior space seems to be considered.

It consists mainly o f a family domain that is separated from the guest domain. In

most houses, the family domain consists o f a living room, a women’s reception

room, bedrooms, bathrooms, a kitchen, and a storage room. The guest domain

consists of men’s reception room(s), a dining room, a guest hand washing area,

and one bathroom.

The major government support programs in Riyadh produce two types of

contemporary houses. First, houses that are built with the assistance of the

REDF. Second, houses that are built completely by the MPWH.

The building materials in both types of houses are the same, but the

construction method is not the same. The REDF house uses reinforced concrete

for its skeleton, including columns, beams, and slabs and cement blocks for the

wall. The MPWH houses use a load bearing wall system with prefabricated

concrete walls and ceiling elements.

The entrance to a typical REDF house starts from the fence where there

are usually two doors: the main door and the secondary door. The main door

leads to another door of the main structure where the guest domain is located.

Male guests normally use this door. The secondary door is normally used by

family members and female guests. It leads to another door of the main

structure where the family domain is located and where the kitchen and food

storage are easily accessible.

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MPWH prototype houses are somewhat similar to the REDF houses in

terms of applying the idea of a setback with the exception that the setback is

surrounded by a three-sided wall versus four sides in the REDF houses. The

fourth side of an MPWH house is attached to the neighbor's house. The main

difference is that the MPWH houses are built with one floor only while the houses

built with the assistance of REDF are built with two floors. In addition, MPWH

houses have a total square area (the core and the surrounded yard) of 484 m2,

while the REDF houses vary, ranging from 400 m2to 1000 m2 and even higher in

some cases (High Commission for the Development of Arriyadh, 1987).

In MPWH houses, the idea o f creating two types of domains, one for the

family, and the other for the guest, is applied only to a certain extent. The two

doors are close to each other. Having to build on one floor only limits the size of

the total area of spaces. The typical house lacks kitchen storage area and a

guest washing area as is commonly needed for Saudi families. This space

deficiency has led to a much adjustment behavior in the MPWH houses.

In brief, there are two types of houses that represent modem housing in

the city o f Riyadh in particular and the Saudi Arabia in general, and these are the

MPWH and the REDF houses. There is a need to determine whether and to

what extent the household living in these two types of houses are exhibiting

similar adjustment behavior, such as housing satisfaction, household propensity

to adjust, and housing expected future improvement.

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Organizations Contributing to Housing Development

Several organizations are involved in contemporary housing planning and

development These organizations are diverse in their practices and contribute to

housing development in several ways. Knowing these agencies can provide

insights into current housing planning and development in Saudi Arabia and

more specifically into housing adjustment behavior.

The first agency contributing to housing development is the Ministry of

Planning, which sets and designs Saudi Arabia’s development plans. The first

development plan covered the period of 1970-1975. It concentrated on

developing a basic infrastructure for the whole country. The second plan

covering the period of 1975-1980, established many of the essential features of

Saudi development, such as the Real Estate Development Fund (REDF) and

Ministry of Public Works and Housing (MBWH). The third plan, 1980-1985,

advanced the development process a step further by recommending more funds

for these housing agencies. The emphasis of the fourth plan, 1985-1990, was on

the efficient use of resources such as recommending city limits (Farsi, 1989).

The fifth and the sixth plans, 1990-2000, concentrated on maintaining and

improving the infrastructure and encouraging the private sector to get more

involved in the development process of the country.

The second contributor to housing is the Ministry of Urban and Rural

Affairs. It is responsible for the provision and management of all relevant facilities

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in cities, towns, and villages, including setting standards and making regulations

and enforcing them through local municipalities.

The third is the Real Estate Development Fund, which was founded in

1974 to provide long-term interest-free loans to citizens to finance the

construction of their homes. The Ministry of Public Works and Housing (MPWH)

is the fourth housing contributor. It is involved in building housing complexes to

be subsidized and allocated to qualified applicants. All houses built by the

MPWH were transferred to the REDF for distribution to qualified applicants with

the price of the house treated as a financial loan.

The fifth contributor consists o f government agencies such as the Ministry

o f Defense, the National Guard, King Saud University, Imam Mohammed ben

Saud University, and the Arabian American Oil Company (ARAMCO). All of them

contribute to building houses for a limited number of their employees at a

minimal charge. These houses cannot be owned and their leases are tied to

working for the agencies that own them.

Government Support of Housing

Most houses in Saudi Arabia are built in a formal way where government

regulations are strictly implemented in the building of any type of housing. An

individual landowner has to obtain a construction permit from a local municipal

authority for any kind o f construction on the land. The Saudi government has

been successful in enforcing construction permits. While curbing any kind of

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illegal housing, the government has provided solutions to the housing problems

with availability o f huge financial resources by utilizing the following strategies:

1. Granting land to people who meet certain criteria.

2. Founding the Real Estate Development Fund (REDF).

3. Supporting factories that produce building materials such as cement

blocks so they would be available at a reasonable price.

4. Providing utilities such as electricity and water to a new house. A

resident has to provide the utility company with a letter of compliance with

local municipality regulation.

5. Building actual housing complexes and subsidizing the houses for

qualified people.

6. Providing housing for some employees of government organizations.

All these factors enticed Saudi households to build their houses in a

formal way. The government housing support programs are applied directly and

indirectly. In evaluating urban housing policy in Saudi Arabia, Fadaak (1984)

concluded that indirect housing assistance programs are more effective than

direct housing programs.

Indirect housing assistance appeared mostly in the establishment of the

REDF. The REDF was established in 1975 after the recognition of housing as a

major constraint to the implementation of the Second Development Plan (1970-

80). It is a lending institution under the Ministry of Finance and National

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Economy. The REDF’s goals are to fulfill the quantitative and qualitative housing

needs by providing two types of loans: private and investment loans. The private

loans target low- and middle-income landowners for private housing

construction. These loans are long-term, interest-free, and do not exceed 70% of

new housing cost or 300,000 Riyals ($80,000). The investment loan, on the other

hand, is provided for multi-unit investment projects. It is also an interest-free loan

that does not exceed 50% of the unit cost with an upper limit of 10 million Riyals

($2.67 million). The source of capital for the REDF comes from government

allocations as well as loan repayments from the borrowers.

The direct assistance program has been presented as a form of a public

housing project. It is managed through the General Housing Department and

was restructured to become the Ministry of Housing in 1975. A number of public

housing units were constructed in the main cities (Riyadh, Jeddah, and

Dammam). Most of the early units were built as high-rise buildings. However, the

later projects include single-family detached housing units.

In 1993, the Ministry of Planning indicated that the major achievements of

the housing sector had two important accomplishments: an increase in the

supply o f housing and the limiting of rent increases. In addition, the total housing

units constructed by government assistance throughout Saudi Arabia since 1975

were estimated at 728,100 units. A total of 483,500 units were built by the private

sector with the financial assistance of the REDF and more than 23,000 units by

the MPWH. Other government agencies, such as the Ministry of Defense, the

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National Guard, the Arabian American Oil Company (ARAMCO), King Saud

University, and Imam Mohammed ben Saud University, constructed about

221,600 units for their employees to live with minimal rent.

To set up the boundaries for this study of housing adjustment behavior,

the focus will be on houses built through the REDF and MPWH, which came to

be owned by the citizens. The study does not address houses built by other

government agencies where citizens rent or live free of charge for a period of

time without owning the unit.

In conclusion, there was a shortage of housing problem in Riyadh, Saudi

Arabia. The REDF and MPWH were created to solve it. But people were making

changes to the unit before they moved in or shortly after, suggesting that new

units were not meeting their needs. Why not? What is the Housing Adjustment

phenomenon? What are the various determinants underlying this phenomenon

in different parts of the world? Understanding the nature of a house as a human

space and its characteristics is essential to the study of adjustment phenomenon

because the house is the place where adjustment behavior takes place. Housing

Adjustment Theory will be discussed to provide background for the study of

Housing Adjustment in Saudi Arabia.

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Chapter 2

Literature Review

The literature review consists of four sections. The first section is a review

of the house as a human space, its characteristics, and the need to evaluate it.

The second section deals with the outcome of household evaluation as a form of

housing adjustment. Adjustment studies point to certain predictors of housing

adjustments in different countries of the world, mainly Korea, Mexico, and the

United States. The third section is a review of previous studies that examined the

motives behind housing adjustment, thus offering insights into housing

adjustment behavior in Saudi Arabia. The fourth section offers a thorough review

of the theory of housing adjustment and adaptation that will be used to formulate

the model of this study. The fifth section specifies the two types of common

houses built in Riyadh, Saudi Arabia, which will be the subject of this study. The

sixth section outlines the limitations of previous studies. In light of those studies,

a research model is formulated that includes the major predictors of housing

adjustment.

The House as a Human Space

The house can be looked at as an occupied human space. According to

Webster’s definition, space is T h e unlimited or indefinitely great three-

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dimensional expanse in which all material objects are located and all events

occur...a room in three dimensions” (Webster’s, 1992, p. 1362).

This study is concerned with the last part of the definition, namely the fact

that space is “a room in three dimensions.” The focus of the present study is the

use of space as a shelter in the form of a physical architectural structure, where

the inhabitants live and perform many types of activities. To improve its

habitability, households engage in adjustment and adaptation processes. That is,

they either make changes to the space so it fits their needs or they make

changes to the household to meet their needs (Morris & Winter, 1978).

Throughout history, human beings have searched for habitable space starting

with occupying natural caves with some adjustment made to them. The search

continues into the present state, generally consisting of detached single family

houses with a front yard, a back yard, and a variety of interior spaces that fulfill

household needs.

Characteristics of Space Use

The characteristics of space use in the house are based on different

aspects of space. For example, the perception of space emphasizes visual

perception such as height and width. Another way to approach the concept of

space is to look at it as a territory or personal space, where varying distances

between individuals are distinguished (Hall, 1966).

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Perception as used in this context refers to experiencing some things by

means of a human sense organ. So, humans have different types of perception

depending on the sense being used (Hesselgren, 1975). Visual perception is the

most common one, where the eyes are used to perceive a certain space. It deals

with the shape and dimension of space, the containing of objects, and surface

features (Scuri, 1995).

Privacy is a practical way of creating territory and personal space.

Holahan (1982) defined territoriality as the pattern of behavior associated with

ownership or occupation of place by an individual or group. It involves

personalization and defense against intrusion. Personal space is defined as the

space with an invisible boundary surrounding the person’s body into which

others may not enter (Sommer, 1969).

According to Altman (1975), privacy is a human mechanism for social

control. It maximizes individuals’ options to present themselves to others as they

choose. A study by Finighan (1980), which involved interviews with people living

in detached villas in Melbourne, Australia, found that in a living space various

levels of privacy appear to be enforced by household members. The first level is

personal privacy inside the dwelling, which is based on social norms of privacy

and is met unconsciously by the respondents and becomes part of the structure

of the family tradition. The second level of privacy deals with visibility from

outside the dwelling. Respondents try to prevent such visibility by using outside

barriers such as trees, shrubs, and fences. In addition, the respondents create

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visual privacy by closing their bedroom and living room curtains when the light is

on.

Physical access is the third level of privacy identified by Finighan (1980).

In his interviews, most of the respondents were concerned with physical

accessibility to the dwelling because of property and personal security. This type

of privacy also involves the level of the neighborhood and coping with some

neighbors’ behaviors, such as dropping by and borrowing, as well as some

neighbors’ undesirable lifestyles and personal habits. As a result, respondents

use a fence or a gate to indicate the boundaries between their private territory

and public space. By using the gate, visitors are directed to a preferred location

in the house by which to enter, allowing household members to be aware of such

visitors’ presence.

The fourth level of privacy of space has to do with the outdoor living area.

Most of the respondents thought that the level o f privacy available in the front

and the back area determines the possibilities of using them. That is why less

than 30% of the respondents in Finighan study (1980) used the front area while

more than 85% used the back area for social activities, since the back yard

would be acknowledged by the neighbors as a private area.

All four levels o f privacy classified by Finighan are culturally specific. It is

possible, therefore, that the findings will be different depending on the cultural

norms of the selected people, such as Americans, Saudis, Koreans, or any other

group of people. This being the case, it is expected that housing types that do

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not respect the concept of privacy in its cultural context will be met with some

resistance resulting in some sort o f housing adjustment behavior.

Organization of the House

Hanson and Hiller (1982) noted that one of the most practical principles

when organizing space in a house is the hierarchy of spatial domains ranging

from circulation o f public spaces at one end, to the private interior of the

residential unit at the other end. This is a trend that the United Kingdom’s

Department of Housing and Local Governments emphasize as a basic

requirement when designing residential units. Space is organized gradually from

the outside to the inside, starting from the public realm of the street, to the semi

public realm, and then followed by the semi-private realm and the private realm

of the dwelling. However, based on a comparison of two contemporary spaces

belonging to two different socioeconomic status owners, Hanson and Hiller

(1982) concluded that, due to socioeconomic status, the order of the dwelling

interior and the way it relates to the exterior could easily differ within and

between societies.

Even though socioeconomic status may be one reason for spatial

organization in western societies, other reasons, such as religious beliefs, may

have a strong influence on spatial organization in other cultures, such as that of

the Middle or the Far East. In these cultures, the household may seek to adjust

their houses to satisfy their norms. For instance, a study of residential

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resettlements in Singapore conducted by Chua (1988) emphasized the role of

religious practice in adjusting space in the organization of new homes. The

residents from three ethnic backgrounds, Chinese, Hindu, and Malay, were

resettled from ethnically specific house forms to standardized high rise

apartments. Each group tried to create new ways to keep the main elements of

its own belief system within the standardized space allocated to all groups in

term of spatial and symbolic behaviors. In addition, giving up cultural norms that

are dictated by religion due to constraints imposed by the built environment is

very difficult for residents to accept. Turner (1982) noted that there were two

universal functions of religion: first, reinforcing critical norms, and second,

alleviating and mitigating anxiety and tension. In the case of Saudi Arabia, where

the study was conducted, Islam dominates its social system, creating explicit

social roles that govern social interaction in the built environment.

Housing Evaluation in General

Identifying occupants’ attitudes toward their houses can be determined by

conducting post-occupancy evaluation. Occupants are defined as all individuals

living in a housing unit hereafter these occupants will be referred to as a

household. The head of the household is one of the individuals in the household

in whose name the house is owned or rented. Not surprisingly, most evaluation

of household attitudes’ towards space is conducted once the space itself

becomes occupied, which can then be called the occupied environment. Shibley

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and Schneekloth (1988) concluded that there are two reasons to evaluate the

design of an occupied environment. The first is to generate knowledge that deals

with the relationship between the occupants and their environment. The second

is to inform and facilitate action toward improving the quality of life for the people.

Systematic evaluation studies o f completed design settings are referred to

as post-occupancy evaluations (POEs). Post-occupancy evaluation has become

widely recognized as influential in design evaluation and programming. They are

sponsored and performed by designers who are responsible for construction

programs and large building management where the choices concerning certain

developments in space design and arrangement involved many different design

options (Zimring, Wineman, & Carpman, 1988).

The most common methods of carrying out post-occupancy evaluations

are: (a) the integration of behavioral research and evaluation methods into the

design process (difficult to conduct due to limitations of funding and time

between the start and the end of construction), (b) experimental or quasi-

experimental studies to meet formal and established criteria of success, (c)

independent audits, and (d) pretest studies (Wener, 1988).

Post-occupancy evaluation studies have proven to be insightful by helping

to understand the built environment in general and housing in particular. First,

they draw attention to correctable aspects of the physical setting that may

suggest certain changes. Second, they provide insights into a new project in

terms of planning and programming. Third, POEs may generate new concepts

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for the future setting o f a prototype project. Fourth, the studies are most likely to

provide information that could affect standards and codes o f future similar

projects. Fifth, they may be used to answer basic environment-behavior

questions that could have further implications (Zimring, et al. 1988).

To assist in conducting POE studies, researchers usually use a theoretical

model as a framework. The model helps organize and integrate variables of

specific issues. Households instinctively perform an ongoing POE for their

dwellings, usually as a result of being satisfied or dissatisfied with the current

housing situation. Such dissatisfaction results in the intention to do something

about a perceived deficit. The actual changes are then made to achieve an

equilibrium status of satisfaction. By examining the instinctive post-occupancy

evaluations initiated by the households themselves, one can identify the major

determinants underlying housing adjustment behavior.

Housing Adjustment Studies

Studies conducted in different parts of the world have identified various

determinants that underlie housing adjustment behavior conducted by the

household. Such studies have revealed differences as well as similarities in

predictors of housing adjustment behavior. Similarly, studies conducted within a

particular country sometimes yielded inconclusive findings about predictors of

housing adjustment behavior. This situation can be illustrated through the

following examples.

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The Case of Korea

Since the late 1970s, many Korean families have started to live in

apartment housing complexes as a way of increasing the efficiency of land use

and the desire for higher housing quality with better facilities and lower prices

compared to detached houses. Detached houses, nevertheless, have been

viewed as the ideal structure-type norm for Korean household (Khil, 1991).

Oh (1983) studied the relationship between previous and future housing

adjustment and the degree of satisfaction with current housing as it relates to

socio-demographic and housing characteristics. She found a positive relationship

between housing satisfaction and previous adjustment behavior. Thus, the

higher the household’s satisfaction with their houses, the less likely they will

engage in future adjustment behavior.

Hong (1984) concluded that alteration or addition to the existing space is

popular among apartment residents in Korea. Hong noted that households with

higher housing satisfaction are more likely to make alterations, or additions, to

current housing than to move to a different house.

Park (1987) also studied housing alteration behavior of people who lived

in apartment buildings and found that households who live in these apartments

are highly satisfied and want to continue living in their units with some alteration

made to them. They have made adjustments to their apartments 3.6 times during

the time they spent in these units. They are more likely to change the social

spaces such as the living and the dining rooms as well as the workspace than

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their private spaces. The study also found that the duration of residence, unit

size, and age are the driving forces for adjustment plans in these apartments.

Lee (1995) explored the factors influencing the Korean households’

residential remodeling and found that the size and the condition of the dwelling

affect satisfaction that is directly related to the propensity of the household to

alter its dwelling.

Cutler (1997) studied Korean households’ living arrangements and their

intentions to engage in compositional adaptation. The study defined co

residence as being two adult generations related as parent and child, and living

together in a dwelling as a single household. Cutler also found that

intergenerational co-residents is more likely to take place among older

respondents, less educated respondents, larger households, those who perform

ancestor worship, those in larger dwellings, and in dwellings with poor condition.

It was concluded that co-residence is negatively related to satisfaction with

current living arrangement and positively related to the expected duration of

current living arrangement.

The Case of Mexico

Most of the adjustment studies conducted in Mexico were driven by the

phenomenon of high rural-urban migration. Suh (1988) studied the relative

contribution of the determinants of the propensity to engage in residential

improvements and tested the applicability of the model of Morris and Winter to

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housing adjustment in Oaxaca, Mexico. Suh concluded that households have a

tendency to conduct housing improvements to raise the quality aspects of their

houses and the amount of space they have. Garcia (1989) conducted a similar

study and indicated that home owners have a higher propensity to make

alterations than do renters.

The study of Selman, Mom's, Winter and Murphy (1994) illustrated that the

quality of housing in Oaxaca is a dynamic process of improvement over time,

reflecting a long-term commitment of the people toward housing improvements.

However, the study found that the level of satisfaction by households who

improved the quality of their dwelling was lower than expected, especially when

compared with households who experienced a decrease or exhibited no quality

changes in their dwelling.

The Case of the United States

Most studies in the United States concerned with housing adjustment

have concentrated on residential mobility. In some studies, residential alterations

have been treated as a substitute for residential mobility. With the amount of

research, the findings about the relationship among the predictors are tentative

and sometimes inconsistent.

Studies by Brass (1975) and Yockey (1976) found that there is a

curvilinear relationship between age and residential alteration activity. This

means that up to a certain age of the head of the household, 50 - 65 years,

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alteration activities increase with age. The trend reverses as the head of the

household gets older, with residential alteration becoming less likely. Other

studies indicated that as the age of the household increases, alteration and

addition activities decrease, suggesting a negative relationship between age and

alteration (Crull, Morris & Winter, 1976; Harris, 1976). Niemeyer (1982) found

that older heads of the households are less likely than younger household heads

to alter the dwelling to satisfy energy conservation purpose of their houses.

Household size also seems to correlate with satisfaction. According to

Galster and Hesser (1981) and Gamer (1983), household size tends to have a

negative correlation with satisfaction and positive correlation with self-production

of home repairs. Seek (1983) found that the increase in household size is likely

to enhance the desire of adding structural improvements to the current housing.

Many studies in the Unites States showed that residential alterations and

additions tend to be performed primarily by home owners, especially those who

live in a single family house that meets the household’s needs (Brass, 1975;

Meeks & Firebaugh, 1974; Morris & Winter, 1978, 1994). Residential alteration or

improvement could also be named residential remodeling, where residents’

renovation is done for improvement and beautification purposes.

Speare (1974) indicated that even though a higher education level may

increase family norms for housing, it affects housing behavior through family

norms as intervening variables and does not directly relate to housing

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satisfaction. In terms of actual adjustment action, Parrott’s study (1988) found

that higher education was associated with the use o f professionals to do the

planning and remodeling while lower level of education was associated with

more household’s planning and remodeling.

Meeks and Firebaugh (1974) found that the desire for home improvement

increases as the level of occupational status increases. Thus, households with

members in skilled labor did more of do-it-yourself remodeling than households

headed by professionals (Parrot, 1988).

When it comes to income as a predictor of alteration behavior, research

findings showed mixed relationship between the two variables, leading some

researchers to propose different interpretations. While Brass (1975) and Meeks

and Firebaugh (1974) found that there was no relationship between income and

expenditure on alteration, Winger (1973) concluded that the two variables are

positively related.

Shonrock (1975) and Yockey (1976) found a curvilinear relationship

between education and alteration. In addition, the studies showed that middle-

class households who are highly educated tend to do more alterations than

either upper- or lower- class groups whose educational levels are lower.

Concerning the length of residence in the house and its relation to

adjustment behavior, Yearns (1972) found that the length of residence in a

house is related to both satisfaction and residential alteration desire and •

activities. The high level of satisfaction can be expected to decline with longer

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residence. Brass (1975) found that there is a negative relationship between

length of ownership and residential alteration.

Brass (1975), Harris (1976), and Yockey (1976) used the concept of

normative deficits in the analysis of residential alterations or the interest to make

alteration. The consensus is that the household with normative space and quality

deficits would be more likely to make alterations and additions to eliminate such

deficits. Morris and Winter (1978) studied the effect of housing satisfaction on the

propensity to engage in residential alteration. They tentatively concluding that

housing satisfaction has a curvilinear relationship to alteration and addition,

which means that both types of households who are highly satisfied or highly

dissatisfied make more alteration than others.

Housing Adjustment in Saudi Arabia

The single family detached house is regarded as the structure-type norm

for Saudi households (Ministry of Planning, 1993). Few studies about housing

satisfaction in Saudi Arabia have addressed the subject of adjustment in Saudi

houses. The adjustment process carried out in houses in the city of Riyadh,

Saudi Arabia is illustrated by the two pictures taken by the author during a field

trip to Riyadh (see Figures 6 and 7).

Bahammam’s (1992) study addressed the issue of adjustment or

modification and its relation to sociocultural housing needs of the households in

REDF- assisted housing in Riyadh. He interviewed 26 heads of households who

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lived in houses built with the help of the REDF. He concluded that there is a

practice of modification by households as a reaction to the contemporary house’s

inability to fulfill residents’ needs. Bahammam also found that privacy that is

guided by Islamic teaching comprises one of the main reasons for households to

modify their houses. Some of the practices used to provide such privacy entail

raising the surrounding fence of the contemporary house (villa). The new fence

blocks visual access from the neighbors’ upper floor windows to the front and the

back yard of the house.

Bahammam also indicated that this modification in the house seems to be

motivated by economic changes and the adaptation of a new way of life. The

study focused on the qualitative approach of research, making it difficult to draw

solid conclusions about the importance of predictors of housing modifications,

such as the age of the heads of the households, their income, and education,

and the extent to which these predictors account for housing modification.

Al-Saati (1987) studied residents’ satisfaction with houses built with the

help of the REDF in Saudi Arabia. Based on a survey, he found that most

respondents were satisfied because of the fact that they are now owners of their

new houses, after they had been renters. In addition, when compared to their

previous homes, most respondents felt that their present dwellings offered them

larger spaces and more facilities than did their previous houses.

According to Al-Saati, households engage in modifying their houses

shortly after moving into them to satisfy their increased privacy needs and to

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Figure 6. Making adjustment by adding a room, Riyadh, Saudi Arabia.

Figure 7. Making adjustment by raising the fence, Riyadh, Saudi Arabia.

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increase the built areas. In general, the results of the study suggest that

households were satisfied with the REDF housing units despite certain problems

that caused them to make some modifications in their houses.

Al-Tassan (1986) studied residents’ satisfaction with the employers’

housing programs in Saudi Arabia. He found that aspects of privacy, dwelling

size, and construction quality were the most important variables influencing the

residents’ housing satisfaction. Other variables, such as cost of living, social

climate, maintenance, and location also contributed to residents’ satisfaction.

Al-Tassan’s study was limited to government houses built for the families of

employees. These houses are different from houses built with the assistance of

the REDF and MPWH housing programs because they were designated for

certain government agencies and could not be owned by their employees who

were required to pay a minimal rent.

Aldakheel (1995) studied residents’ satisfaction with prototype houses that

were built by the MPWH in the city of Buraidah, Saudi Arabia. He questioned the

degree to which prototype designs met the residents’ housing needs, claiming,

among other things, that the residents’ housing needs were not the same due to

their size. For instance, a childless couple prefers a single bedroom, a small

living room, and a bigger garden, while a larger family preferred several

bedrooms and a large living room. Aldakheel developed a very extensive self

administered questionnaire and conducted in-depth interviews with the residents

to measure their overall satisfaction. Among his findings was the fact that

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personal characteristics did not contribute significantly to satisfaction and that the

people who chose to live in these types of houses were younger than the

average household in the city of Buraidah. The study stressed satisfaction as a

function of the size of the dwelling, house design layout, and its flexibility in

shaping residents’ satisfaction.

Limitations of Previous Studies

Studies on housing adjustment in different parts of the world overlap to

some extent in terms of the suggested determinants of housing adjustment

behavior. Predictors of housing adjustment behavior tend to differ as a result of

the location of the selected households who may have different cultural norms

and socioeconomic status. For instance, there is a trend in Korea to live in

apartment buildings. Saudis, on the other hand, tend to live in single family

detached houses built through different types o f government support. Given the

different contexts in which housing adjustment behavior takes places, it is difficult

to identify a definite set of predictors as well as their power of predicting housing

adjustment behavior that can be applied equally to different types of countries.

In Saudi Arabia, studies on housing satisfaction, which sometimes

included housing adjustment behavior, tended to be limited to one type of

housing development. For instance, Bahamam (1992) and Al-Saati (1987)

studied REDF houses, while Aldakheel (1995) studied MPWH houses. Both

types of houses constitute the core of the government support program. No

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study attempted to address the issue of housing adjustment behavior in both

types of houses to investigate the differences and similarities between them.

Because they are the main type of housing built, there is a need to conduct a

comparative study of both REDF loan houses and MPWH public houses in Saudi

Arabia to highlight some aspects of housing adjustment behavior as they relate

to both types of houses. Such a study would allow for further explanation of

housing adjustment behavior occurring under two different types of housing that

constitute the backbone of government housing support programs.

Such a comparative study calls for the formulation of a model that could

serve as a basis for explaining housing adjustment behavior. The model needs

to include all relevant predictors of housing adjustment behavior ranging from

age, to income, to education, and to size of the household, to mention a few.

One of the widely recognized models in housing research is the one based on

the housing adjustment and adaptation theory that will be explained in detail as

part of setting the stage for the research model used in this study.

Adjustment and Adaptation Theory

Overall Concept of the Theory

The Adjustment and Adaptation Theory was developed by Morris and

Winter (1978, 1985, 1994). The theory emanated mainly from previous studies of

housing conducted by Riemer (1945), Rossi (1955), and Brown and Moore

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(1970). The main premise of the theory is that households tend to engage in

housing adjustment or adaptation. Adjustment is part o f the everyday behavior of

the households to fulfill their housing needs by making adjustments in the

housing conditions. It could take place by moving to a different dwelling or by

making alterations or additions to the current unit. In contrast, adaptation

consists of making changes in the household itself. It involves many techniques

such as changing the household’s norms, changing the composition of the

household, reorganizing household roles, or improving and increasing the

household’s resources.

The theory has been used in research studies in the United States,

Mexico, Korea, and Poland. This suggests that the theory is flexible and has the

potential to be used and tested in studying housing adjustment behavior in other

areas of the world such as Saudi Arabia.

Definitions of Concepts

There are eight concepts used in Morris and Winter’s housing adjustment

model. They consist o f (1) housing norms (both cultural and family norms), (2)

satisfaction or dissatisfaction with (3) current housing conditions, (4) normative

deficit, (5) the propensity to engage in adjustment behavior, (6) actual

adjustment behavior, (7) constraints that inhibit or facilitate the sequences of

household adjustment, and (8) values. To understand these concepts, each one

will be defined as it relate to housing adjustment.

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The housing norms

Housing norms are social pressures in the form of rules for behavior and

life conditions that are combined with related sanctions. The norms are applied

by the household to evaluate current housing conditions and are weighted based

on their relative importance to the family for each housing characteristic. There

are three levels of norms. The first level being society’s cultural norms, which are

rules or standards, formal and informal. Here, there may also be subculture

norms for certain groups within the society. The second level is family norms,

which are the family’s specific standards with respect to its own behavior and

conditions that its members apply to themselves. The third level consists of

preferences, which are the result of interactions between norms and constraints.

Current housing conditions

Current housing conditions are the conditions in which the household lives

are dictated by cultural norms. They are appropriate for study to the extent that

they relate to norms, goals, or preferences of the household.

Normative deficits

Normative deficits are the indicators of unmet needs, which are a result of

differences between unmet housing conditions and the actual housing norms.

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Satisfaction or dissatisfaction

Satisfaction or dissatisfaction is a measure of the household’s emotional

state with respect to the degree to which current housing meets the norms.

There are two approaches that have been used to measure housing satisfaction.

The first approach uses a general measure of overall satisfaction with the

dwelling. The second approach uses a measure of specific characteristics of the

dwelling. In research, the two ways of measurement are sometimes combined

into a scale of general satisfaction.

The intention of adjustment behavior

The intention of adjustment behavior is the first reaction to the state of

dissatisfaction. It is the state o f motivation to perform the actual adjustment

behavior.

The actual adjustment behavior

The actual adjustment behavior involves two options: moving to another

dwelling or altering the present dwelling.

The constraints

The constraints are the sources that may inhibit the household from

successfully performing the adjustment process. They affect the perception of

normative deficits, the development of dissatisfaction, the propensity of

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adjustment, and the actual adjustment. Six classes of constraints were described

earlier which include predispositions, organization, resources, market,

discrimination, and culture.

The values

Values are used for evaluating and choosing among various

characteristics of housing or with respect to other household needs. They are

used to explain the translation of norms into preferences and are measured by

the relative importance of various domains of life and housing.

Theoretical Model of Housing Adjustment

According to the model shown in Figure 8, alteration and addition

behavior operates within a number o f constraints. Here, constraints are defined

as those factors that can hinder or promote adjustment behavior. An explanation

of each type of constraints follows. Predisposition constraints consist of the

psychological dimension of the household similar to personality of the individual,

such as achievement motivation. Household organizational constraints include

the ability to marshal resources, make decisions, and implement them, all of

which are functions of allocation of roles within the household, the effectiveness

of the role performance of the individual members, and the effectiveness of the

overall performance of the household as a unit. Resource constraints could be

either material or human. Material resources include money, whereas human

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Dependent VariablesIndependent Variables DEFICIT

CONDITIONS PREDISPOSITION

ORGANIZATION

SATISFACTION/ DISSATISFACTION

RESOURCES

PROPENSITY TO MOVE/ALTER

MARKET

DISCRIMINATION

MOVE/ALTER CULTURE

Figure 8. Theoretical Model of Housing Adjustment (Morris & Winter, 1994).

resources include skills and education. Market constraints include prices and

supplies of housing, material, land, and financing. Discrimination constraints

include societal sanctions against a particular race or sex, especially when the

society values one race more highly than others and therefore grants more or

less ready access to various rewards of the society. Cultural constraints are

based on the idea that a particular culture is likely to have different norms,

values, current housing conditions, and satisfaction.

When these constraints are severe, adjustment behavior is not likely to

occur, causing chronic dissatisfaction and leaving the household with three

choices: (1) adaptation, which is making some change in the structure of the

household (normative, power, role, and compositional structure), (2) pathology,

which tends to occur when adaptation has not occurred, when the household is

not able adapt, or (3) social action, which tends to occur when the household

chooses not to adapt.

Constraints, however, can promote adjustment behavior that appears to

develop in stages, starting with a perceived deficit, to dissatisfaction, to a desire

to reduce the deficit by means of a specific behavior, to an expectation that the

behavior can be accomplished, and finally to the occurrence of the behavior

itself. At each stage, constraints operate to promote or prevent some households

from proceeding to the next stage. This process is represented in the form of a

path diagram showing the connection among these concepts (see Figure 8).

The model is divided into two parts: (1) the relation among the dependent

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variables (adjustment behavior, adjustment intention, satisfaction/dissatisfaction,

and the deficits) and (2) the relationship of the independent variables (the

constraints to the dependents).

The dependent variables are assumed to be related in a chain from

deficits to satisfaction to behavioral intention to adjustment behavior. Thus a

household that has one or more deficits would have a reduced level of

satisfaction. A dissatisfied household would have the intention to engage in

adjustment behavior. A household with intentions would engage in adjustment

behavior.

Independent variables are assumed to have three types of effects on the

dependent variables. First, they may have direct effect on the dependent

variable. For instance, households that have fewer resources than others are

more likely to have deficits, low satisfaction, adjustment behavior intention, and

exhibit adjustment behavior. Second, independent variables may have an

indirect effect on the dependent variable. For instance, households with fewer

resources than others are likely to have more deficits and, therefore also have

lower satisfaction. There may be interaction effects on the relationship between

pairs of dependent variables. The household with fewer resources is likely to

have a weaker relationship between deficit and dissatisfaction. It is important

now see how this theory may relate to the housing adjustment problem in

Riyadh.

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Housing Setting in Riyadh

The major government support programs in Riyadh produce two types of

houses: houses that are built with the assistance of the REDF and houses that

are built completely by the MPWH. In both methods, household members end up

owning the home. The study does not address houses built by other government

agencies where a household lives in the house for free or minimal rent, but will

never own the home.

The researcher’s observations and interviews with government officials

and local architects in Riyadh indicate that the occupant may think of conducting

an adjustment when experiencing deficits after living in a home, which is the

case in houses built by the assistance of the REDF.

As shown in Table 1, the process of building the REDF house starts with

acquiring a lot. Here, the household normally takes into consideration the

location, the size, and the price of the lot. It is not unusual for the head of the

household in consultation with his wife and children to purchase land that is not

too far from the household parents. Once a lot is acquired, the head of the

household obtains a construction permit from the local municipality. The permit

defines the permissible setback, which is generally two meters from the

neighbors, and one fifth of the street width on the street side.

The next step is to design the house. Here, the household has different

options. They can either purchase a replicated blueprint from the municipality,

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borrow one from a friend, or hire a design firm to provide a custom design for the

house. The third option is the most common practice.

Table 1

The process of building and living in a house as it applies to houses built through

the financial assistance of the REDF.

The process of: The performer The potential effect on:

Obtaining the lot Household Location, land size

Granting a permit Municipality Setback. F.A.R.

Designing the house Designer Shape, space allocation, quality of blueprint

Applying for finance Household Following REDF rules

Supplying the loan REDF Building progress

Actual construction Contractor Building progress, errors, modification

Moving in Household Living

Assessment of norms Household Deficit

Experiencing housing deficit Household Dissatisfaction

Adjustment intention Household Adjustment or adaptation

Actual adjustment Household Satisfaction

Once the construction of the house is completed and the house is

furnished, the household moves in. After some time, the household may

determine that their cultural and space norms lead to a perceived deficit, and

therefore to a state of dissatisfaction, which in turn leads to adjustment intention,

ending with actual adjustment, including adding more rooms, or changing the

exterior, interior, or both.

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Table 2 describes the process of building and living in the MPWH house.

The MPWH determines the location of the project, hires the designer and the

contractor, and makes the house habitable. It is not unusual to hire international

firms, many of which may not be well acquainted with Saudi cultural norms, to do

the housing design. Then these housing units are made available to the REDF

loan applicants to purchase. The household may conduct adjustment even

Table 2

The process of building and living in a house as it applies to prototype houses

built bv the MPWH.

The process of: The performer The potential effect on:

Determining location of the project MPWH Location

Hiring a designer MPWH Quality of design

Designing the house International firm Shape, space allocation

Hiring the contractor MPWH Quality of the house

Finishing the project, selling houses to MPWH Availability of the house

REDF applicants REDF

The choice of purchasing the house or Household Purchasing the house

obtaining the cash loan

The choice of selling, renting or moving in Household Decision of living in the house

Getting ready to move to the house Household (Evaluation the house)

Satisfaction, dissatisfaction

Adjustment intention Household Adjustment or Adaptation

(before moving in) (before moving in)

Moving in and living Household Living

Changing of housing situation Household Deficit

Experiencing housing deficit Household Dissatisfaction

Adjustment intention Household Adjustment behavior

Actual adjustment Household Adjustment or adaptation

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before moving to their newly acquired house to meet their space and culture

norms. Local municipalities where the MPWH are located are usually

overwhelmed by requests to obtain construction permits to the newly received

units (Riyadh Daily, 1995). Once the pre-moving adjustment is completed, the

household moves in. After some time, the cycle of adjustment behavior is

repeated due to recognition that the house does not meet the household’s

cultural and space needs.

Research Model

On the basis of the literature review of this chapter, and in light of the

housing adjustment model (Morris & Winter, 1978, 1994), the two tables of

housing adjustment process were reconstructed in an effort to develop the

empirical research model that is presented graphically in Figure 9. The model

has two categories of variables: independent and dependent variables. The

independent variables consist of several categories, including household

variables, namely household size, age of the household head, household

income, and education of the head of the household. Other independent

variables are the housing construction variables, which include changes during

the construction of the house by the owner, contractor, or both; building

regulation; loan requirements; and the designer of the house. The previous

adjustments are also independent variables that include pre- and post-moving

adjustment variables.

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PREVIOUS ADJUSTMENT VARIABLES

POST-MOVING ADJUSTMENT HOUSEHOLD VARIABLES

HOUSUNG ADJUSTMENT BEHAVIOR VARIABLES

PRE-MOVING ADJUSTMENTHOUSEHOLD SIZE

DEFICIT AGE OF THE HEAD

HOUSEHOLD INCOME SATISFACTION

DISSATISFACTIONEDUCTION OF THE HEAD

PROPENSITY TO ADJUST/ADAPTHOUSE CONSTRUCTION VARIABLES

O) OWNER CHANGES

CONTRACTOR CHANGES EXPECTED FUTURE

IMPROVEMENTBUILDING REGULATION

PHYSICAL HOUSING CHARACTERISTICS VARIABLESLOAN REQUIREMENTS

SIZE OF THE HOUSE DESIGNER

CONDITION OF THE HOUSE

Figure 9. Research Model of Housing Adjustment in Riyadh, Saudi Arabia.

The physical housing characteristic variables, size and the condition of the

house, are considered independent variables that may affect the dependent

variables. They are also considered dependent variables that are affected by

other independent variables. Other dependent variables are the housing

adjustment behavior variables, which include household deficit, satisfaction,

propensity to adjustment, and expected future improvement. The housing

adjustment behavior variables are assumed to be related by the following

assumptions, with the condition of the absence of any constraints. First, the

household that has one or more deficits has a reduced level of satisfaction.

Second, a dissatisfied household is more likely to have the intention to engage in

adjustment behavior. Third, the intention to engage in adjustment behavior

encourages the household to engage in actual adjustment behavior leading to

high expectations of future housing improvement. The relationships between the

independent variables and the dependent variables are assumed to be linear

and additive and the errors are not correlated. Multiple regression is the suitable

statistical technique used to analyze this model.

Figure 9 also shows the interconnectedness of the variables and their

direct and indirect effects on each other in the model. The model lays the ground

for testing the hypotheses posited in Chapter Three. It will be tested using the

data from respondents who live in Riyadh, Saudi Arabia. The respondents are

people who live in houses built with the help of the REDF as well as houses built

by the MPWH.

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Chapter 3

Method

This Chapter consists of five sections and presents the procedures used

in this study. The first section presents the assumptions of the research model

and states the research null hypotheses that were constructed based upon the

literature review and the research model conducted in the preceding chapter.

The second section describes the operational definitions of the variables

included in this analysis. The third section describes the research instruments,

including the discussion of the questionnaire design and development. The

fourth section deals with data collecting procedures, consisting of survey

instruments developed and used to collect data from REDF and MPWH

households in Riyadh, Saudi Arabia. The chapter ends with a description of the

data entry technique.

Assumptions of the Model

This study of housing adjustment in Riyadh tested the comparative-static

version of the model of housing adjustment developed by Morris and Winter

(1978, 1985, 1994). The research model (see Figure 9) is built on five

assumptions. First, the household tends to maintain a state of equilibrium to

maintain the quality of life. Second, the household’s cultural norms are used to

evaluate the current housing conditions. Third, the process of housing

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adjustment behavior is cognitive because only perceived deficits produce

consensus dissatisfaction, which encourage the motivation to remove the deficit.

Fourth, the process of housing adjustment behavior is voluntary. Fifth, it is also

consensual in the sense that the household makes a decision on the basis of a

consensus among the household members who share and produce more or less

common views of housing norms and culture.

The Null Hypotheses

The study proposed nine hypotheses centered around three themes.

Hypothesis 1 targets the first theme that deals with the differences between the

two types of houses. Hypotheses 2 to 8 target the second theme that deals with

the determinant predictors of each type of house. Hypotheses 9 to 10 looked

closely at the third theme dealing with the sequential flow of the effect of

adjustment behavior variables on each other.

Null hypothesis 1. There is no significant difference in housing adjustment

behavior between MPWH prototype houses and REDF loan

assisted houses.

Null hypothesis 2. The physical housing characteristics of each housing type

are not significantly affected by any of the shared variables

including the household variables and the previous

adjustment variables.

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Null hypothesis 3.

Null hypothesis 4.

Null hypothesis 5.

Null hypothesis 6.

Null hypothesis 7.

The housing deficit of each housing type is not significantly

affected by any o f the shared variables including the

household variables, the previous adjustment variables, and

the physical housing characteristics variables.

The housing satisfaction of each housing type is not

significantly affected by any of the shared variables including

the household variables, the previous adjustment variables,

the physical housing characteristics variables, and the

housing deficit variable.

The propensity to adjust in each housing type is not

significantly affected by any of the shared variables including

the household variables, the previous adjustment variables,

the physical housing characteristics variables, the housing

deficit, and the housing satisfaction variables.

The expected future improvement in each housing type is

not significantly affected by any of the shared variables

including the household variables, the previous adjustment

variables, the physical housing characteristics variables, the

housing deficit, the housing satisfaction, and the propensity

to adjust variable.

The housing construction variables in the REDF houses

have no significant effect on the physical housing

characteristics variables, the housing deficit, the housing

satisfaction, the propensity to adjust variable, and the

expected future improvement.

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Null hypothesis 8. The housing satisfaction in each housing type is not directly

related to household deficit.

Null hypothesis 9. The propensity to adjust in each housing type is not directly

related to housing satisfaction.

Null hypothesis 10. The expected future improvement in each housing type is

not directly related to housing satisfaction.

As represented in Table 3, both types of houses, MPWH and RED have to

be tested against the same set o f variables to determine whether and to what

Table 3 The four models and the related variables

Categories Variables

Model 1 MPWH &

REDF

Shared variables

Model 2 MPWH Houses

Shared variables

Mode! 3 REDF

Houses

Shared variables

Model 4 REDF

Houses

AH variables

1. Household size • • • • Household 2. Age of the head • • • • Variables 3. Household income • • • •

4. Education of the head • • • • 5. Changes by owner •

Housing 6. Changes by contractor # Construction 7. Building regulation •

Variables 8. REDF regulation • 9. Designer •

Previous Adj. 10. Pre-moving adjustment • • • • Variables 11. Post-moving adjustment • • • •

Physical H. C. 12. Size of the house • • • • Variables 13. Condition of the house • • • •

14. Housing type • Housing 15. Housing deficit • • • •

Adjustment 16. Housing satisfaction • • • • Behavior 17. Propensity to adjust • • • • Variables 18. Expected future improv. • • • •

2-6 2-6 7 Null-hypotheses as related to model: 1 8-10 8-10 8-10

• = Variable applied to the model

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extent there is a difference between housing adjustment behavior for each

housing type. This relationship between the two types o f houses is addressed in

the first null hypothesis (see Model 1). The two housing types, MPWH and

REDF, will then be tested separately with the shared variables to address the

null hypotheses two through six and eight to ten (see Model Two and Three).

Finally, the REDF houses will be tested with the addition of the housing

construction variables to address the null hypothesis seven as well as the set of

hypotheses eight to ten (see Model Four).

Research Instrument

The resident survey consisted of a self-administered questionnaire

completed by the occupants who live in houses built with the help of the REDF

loan and prototype houses built completely by the MPWH (see Appendix A). This

survey was intended to measure household perceptions, needs, and intentions

about a number of aspects related to occupants’ housing environments. It

generated knowledge regarding household adjustment behavior, requiring

certain information about demographic characteristics, housing conditions,

housing satisfaction, and the propensity to make adjustments or adaptations.

The decision to use a survey was justified by the fact that it was the best

means available for describing certain characteristics o f a large population based

on a small sample of the REDF and MPWH recipients, as opposed to other

research methods. In addition, the survey technique made it possible to test

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hypotheses under certain circumstances of housing finance and construction

process. The results of the survey yielded a statistical comparative format,

allowing for establishing and ranking relationships among a large number of

predictors.

The translation of the questionnaire into Arabic was conducted by the

researcher considering Detusher’s suggestion that the researcher be familiar

with the actual cultural milieu, o f which language is a part, and the effort should

be directed to obtain conceptual equivalence without major concern for lexical

comparability (Detusher, 1968).

Questionnaire Design and Development

The questionnaire was developed on the basis of several previous

studies, especially the study of Housing and the Household Province of Lublin,

Poland (Moms & Winter, 1994) and the study of Housing and the Family, City of

Dae-Jeon, Korea (Lee, 1995).

The questionnaire started with an introduction letter that identified the

purpose of the questionnaire (see Appendix A). The first page also explained the

response system, with emphasis on the issue of the confidentiality o f the

respondents. The last page of the questionnaire was left blank for the

respondents to write any comments or observations. The questionnaire was

designed to get the most possible data about household characteristics and

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behavior toward housing in Riyadh, Saudi Arabia. It tried to elicit answers from

the participants pertaining to housing adjustment behavior.

The self-administered questionnaire gave an appropriate level of control in

structuring issues and responses. It also gave the household the convenience of

choosing the time and place to respond.

The questionnaire consisted of 40 questions organized in five groups. The

first group obtained some general information about housing situations, including

the month and the year of building and moving into the house, method of owning

the home, and method of designing the home. The second group focused on

elements that have an effect on the process of housing design and construction,

such as Owner changes, contractor changes, municipality regulations, and

REDF requirements. The third group of questions dealt with adjustments or

thinking about adjustments made by the household in the house.

The fourth group of questions obtained information about household

attitudes toward housing and the households’ socioeconomic status. The last

question of this group was intended to obtain some information about

characteristics of household members, such as gender, age, marital status, level

of education, occupation, and employment status.

The First Draft

The first draft of the questionnaire was developed in the spring of 1995. It

was submitted to five Saudi households from the city of Riyadh living in

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Minneapolis and St. Paul, Minnesota at the time of the study. The households

were invited to fill out the questionnaires. The researcher consulted the

respondents about the clarity of the language and listened to their suggestions in

an effort to refine and improve the final version of the questionnaire. The results

of the preliminary questionnaire revealed that:

1. The respondents proposed some minor change in the language of the

questionnaire for the sake of clarity,

2. There was a consensus among the respondents that including the

name of the respondent in the questionnaire, even with a written assurance of

confidentiality, would minimize the cooperation of the household to complete the

questionnaire. Since the age and income were considered by the respondents to

be a private matter, it was necessary to eliminate the question asking for the

respondent’s name completely. It was hoped that this would enhance the rate

return as well as the accuracy of the responses.

3. The respondents recommended reducing the number of pages to make

the questionnaire look short. This suggestion led the researcher to present the

questionnaire in the form of a booklet with questions on both sides of the page.

The Second Draft

The second draft of the questionnaire incorporated all suggestions made

by the five participants by improving the sequence and the wording of the

questionnaire. A pilot study was conducted to test the second draft of the

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questionnaire. Fifteen booklets o f questionnaires were sent to Washington, DC

where there was a large number of Saudi households. Each booklet was

inserted into a 9 X 13 envelope with the name of the study. All 15 envelopes

were sent to a friend of the researcher who was asked to distribute them to

Saudi households. The household members were asked to answer the

questionnaire, then to put it back in the paid, self-addressed envelope, and to

seal it. All 15 envelopes were sent back to the researcher. A similar procedure

was done for seven other questionnaires sent to Carbondale, Illinois, where

some Saudi students lived. A total o f 22 questionnaires were collected from both

cities. The respondents were asked to answer the questions as if they were still

living in their homes in Saudi Arabia.

A preliminary analysis of the questionnaire was conducted using the

Statistical Package for the Social Sciences (SPSS) for Windows. In addition, a

close examination of the respondents’ answers produced by the pilot study was

necessary to produce a final version of the questionnaire.

The Final Draft

The final draft of the Arabic version of the questionnaire (see Appendix B)

was presented in an 8.5 X 11 inch booklet with a cover page bearing the name

of the College o f Architecture and Planning, King Saud University, and the name

of the study. The second page of the questionnaire, including information about

the purpose of the research, was kept unchanged. The only addition made was

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to remind the respondents that they did not need to put their names on the

questionnaire.

The Variables

Figure 10 shows the independent and dependent variables of the study as

they fit the Housing Adjustment Model previously developed. The Figure also

shows that each variable is represented by one or more designated questions in

the questionnaire.

Independent Variables

The independent variables include all household variables, housing

construction variables, previous alteration/addition behavior, size and condition

of the house.

Household variables

Household variables are represented in (Q. 40), which asks for the size of

the household. This variable is continuous and is measured by the total number

of the household members who lived in the house during the time of the study. It

does not include any member of the family who lived in a different house.

Other household variables include age of the head of the household,

education of the head of the household, and the household income. Age of the

household is measured by years and is therefore a continuous variable. It is

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without perm ission.

PREVIOUS ADJUSTMENT VARIABLESQ16Q40

Q14b Q14cPOST-MOVING ADJUSTMENT Q17 Q14a HOUSEHOLD VARIABLES

Q40 Q15aPRE-MOVING ADJUSTMENT HOUSUNG ADJUSTMENT

y. BEHAVIOR VARIABLES HOUSEHOLD SIZE

Q15b Q19Q18AGE OF THE HEADQ39 DEFICIT

Q27

HOUSEHOLD INCOME Q28

SATISFACTION DISSATISFACTION

Q40 EDUCTION OF THE HEAD Q31

Q26PROPENSITY TO ADJUST/ADAPT

HOUSE CONSTRUCTION VARIABLES

OWNER CHANGES Q20 Q10

Q21 -5 CONTRACTOR CHANGES Q9 ' ---------------------------------------------------- EXPECTED

FUTURE IMPROVEMENT

Q11 Q22BUILDING REGULATION

Q24PHYSICAL HOUSING CHARACTERISTICS VARIABLES

Q12

LOAN REQUIREMENTS Q13 SIZE OF THE HOUSE Q27

Q30 DESIGNER

CONDITION OF THE HOUSE Q25

Figure 10. Variables and their corresponding question numbers in housing adjustment in Riyadh, Saudi Arabia.

represented in (Q. 40). Education of the head of the household, is an ordinal

variable and is measured by the highest degree completed or the degree

enrolled in. Household income is the total monthly income earned by all of the

household members from all sources. It is gathered in (Q39) by giving the

respondents a question containing a series of income categories and asking the

person to indicate the category into which their income fell.

Housing construction variables

The housing construction variables include changes by owner, changes

by contractor, constraint of building regulations, constraint of REDF regulation,

and design method. Changes by owner during the construction are represented

by (Q. 6) and are assigned the code “1" for participation in making a suggestion

or making actual alterations and the code “0” for none. Changes by contractor

also assigned the code “1” for participation in making a suggestion or making

actual alterations and the code “0” for none, which is presented by (Q. 7).

The constraint of building regulations during building the home

construction is represented by (Q. 8) and is assigned the code “1” for the

existence of the difficulty in meeting building regulations and the code “0” for the

absence of difficulties. Loan requirements variable is represented by (Q. 9). This

variable is assigned the code “1” for the difficulties of complying with REDF

regulations and the code “0” for the absence of difficulties. Designer of the house

is the last variable o f the housing construction represented in (Q. 5) and is

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measured by four categories, each assigned a separate code: The code “1" is

assigned to the house pre-designed from the municipality. The code “2” is

assigned to the house designed by a professional. The code “3” is assigned to

the house designed through a free copy obtained from a friend. The code “4” is

assigned to houses designed through any other method.

Previous adjustment variables

The previous adjustment variables consist of pre-moving and post-moving

adjustment variables. The pre-moving adjustment variable, which is the

adjustment conducted by the household prior to moving to the house, is

represented by (Q. 12) and is assigned the code “1” for making actual

adjustment and the code “0” for not making any adjustment. The types of pre

moving adjustment are presented by (Q. 13) and consist of adding one or more

rooms, raising the height of the surrounding fence, making major improvement to

the exterior, making major improvement to the interior, or making any other type

of adjustment. The pre-moving adjustment consists of the total number of

adjustment activities done by the household prior to moving in.

Likewise, the post-moving adjustment, which is the adjustment conducted

by the households after living in the house, is represented by (Q. 14) and is

assigned the code “1” for making actual adjustment and the code “0” for none.

This type o f adjustment, presented by (Q. 15), consists of adjustment made by

the household to their house at one or more of the following levels: adding one

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or more rooms, raising the height of the surrounding fence, major improvement

to the exterior, major improvement to the interior, other type of adjustments. The

post-moving adjustment variable, which ranges from 0 to 5, uses the total

number of adjustment done by the household after moving in.

Dependent Variables

The dependent variables include the physical housing characteristics

variables (size and the condition of the house) and the housing adjustment

behavior variables (household deficit, housing satisfaction, propensity to adjust,

and expected future improvement of housing situation). These dependent

variables are imbedded in the different types of questions included in the

questionnaire (see Figure 10).

Physical housing characteristics variables

The physical housing characteristics are presented by two different

variables: the size of the house variable and the condition of the house variables.

The size of the house is measured by the total size of the land, which is

represented in (Q. 20) and measured by square meters. In addition, the total

number of bedrooms is represented in (Q. 23). In this study, it is assumed that

the total square area of the land does not give a good indication of the size of the

house, as does the number of bedrooms, because the total square area includes

the setbacks and front and backyard in addition to the core building. This being

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the case, the number o f bedrooms is used as an indication of the size of the

house variable.

The condition of the house is represented in (Q. 21) and measured by an

ordinal ranked scale from one to five. Very poor condition (not sound enough to

rehabilitate) is scaled “1”, “2” for poor condition (needs some major repairs), “3”

for adequate condition (needs many repairs but mostly minor ones), “4” for good

condition (needs some minor repairs), and “5” for excellent condition (no repairs

needed).

Housing adjustment behavior variables

The housing adjustment behavior variables consist of the household

deficit variable, the housing satisfaction variables, the propensity to adjust

variable, and the expected future improvement variable. Household deficit is

defined as being the mismatch between cultural norms of the household and the

housing condition. Household deficit is a scale created from responses to a

number of questions (Q. 11 through Q.17) about the impacts of cultural and

space norms related to housing through household perceptions about certain

features in their houses, such as guest and family domains and visual privacy.

Housing satisfaction is represented in (Q. 22) and is measured by a five-point

scale ranging from 1 to 5, with “1” being very dissatisfied, " 2 " dissatisfied, “3”

neither satisfied nor dissatisfied, “4” satisfied, and “5” very satisfied.

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The propensity to adjust is the desire or the expectation for future change,

addition, or alteration and is represented by (Q. 16) where the household chose

to change, alter, or add to the current house. It is also presented by (Q. 17)

where the household chose to move to a different house. It could remain as a

future plan with no action, but when constraints are eliminated, and the

resources are available, the propensity is followed by actual adjustment

behavior.

The propensity of the household to change, alter, or add is represented by

(Q. 16) and is measured by four categories. These categories are as follows: “1"

household has definite plans to make changes to this house in the next year, “2”

household expects to make changes to this dwelling in the next year, “3”

household has thought about making changes to this dwelling, and “4”

household has never thought about making changes.

The propensity of the household to move is represented by (Q. 17) and is

measured by four categories. These categories are as follows: “1" household has

definite plans to move from this house in the near future, “2” household expects

to move in the near future, “3" household want to move in the near future, “4”

household has thought about moving from this house, and “5” household has

never thought about moving.

Given the relationship o f these two variables: the propensity of the

household to change, add, and alter and the propensity o f the household to

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move from their current house, the two variables have been combined under a

broader variable, namely the propensity to adjust variable.

Expected future improvement o f the housing situation in the next five

years is represented by (Q. 26). It is measured by a five-point scale in terms of

the expectation o f a housing situation, where “1” will get much worse, “2” will get

somewhat worse, “3” will stay the same, “4” will get somewhat better, and “5” will

get much better.

Data Collection Procedures

Site Selection

The study sample was drawn from the city of Riyadh, which was selected

as a site for the study for several reasons. First, it is the capital city of Saudi

Arabia that has political, economic, administrative, and planning commitments to

improve housing quality, and any decision making in Riyadh would significantly

influence the housing environment in other cities in Saudi Arabia. Second,

Riyadh’s natural physical context is representative of most regions in the country.

Third, it is the city where the researcher was born and grew up and practiced

architecture in general and housing design in particular, making it easy to obtain

information and to use background knowledge to assist with the research project.

While selecting the samples representing the two types of houses, the

MPWH houses and REDF houses, the choice was limited to the MPWH houses

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since there was only one major public housing project that is located in the

eastern side of Riyadh and named AIJAZIRAH project. In the case of the REDF

houses, the choice was widely open due to the availability of scattered REDF

houses all over Riyadh.

Surveys in general require a large sample size to have a sufficient

variability in characteristics that adequately reflect any variation existing in the

total population. A sample size of 230 households was used in this study to allow

for generalization and representation of the total population.

The two samples were drawn from two different types o f houses located in

two different sites: MPWH houses and REDF houses. The MPWH houses

comprise the public housing project located only on one site of the eastern side

of Riyadh. Once the map of the area was obtained, the sample of the houses

was drawn through a systematic sampling technique. Specifically, the procedure

was executed by choosing, skipping, and marking the houses in a sequential

order. The number of skipped houses was dependent on the total number of

houses in the neighborhood. The size of the sample amounted to approximately

three hundred houses.

The other sample represents the REDF-assisted loan houses that were

scattered all over Riyadh. It was not possible to recognize the REDF houses

simply by looking at the map o f Riyadh or by examining the physical structure of

the home. The only alternative was to distribute the questionnaires through

network groups to get the right type of housing. The map of the city was divided

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into ten sections. In each section, a sample of the REDF houses was determined

by a person familiar with area.

Distribution of the Questionnaires

One of the difficulties associated with the distribution of surveys in Saudi

Arabia in general and in Riyadh City in particular has to do with the fact that

mailing in Saudi Arabia is delivered through mailboxes not by home address.

Another difficulty has to do with the fact that Saudi households are very

conservative in terms of giving away any type of personal information or attitude

about their houses to strangers. As a result, the questionnaires had to be

delivered or handed in person through a friendly conversation that helps to

explain verbally the purpose and nature of the study. Emphasizing the academic

nature of the study helped to eliminate suspicion associated with municipality

adjustment regulations on the one hand and in getting accurate responses and a

high rate of participation on the other hand.

The researcher contacted the College of Architecture and Planning (the

sponsor of the study) and obtained a letter from the school explaining the

purpose of the questionnaire and encouraging households to participate in the

study. In addition, the researcher received support from an instructor at the

College o f Architecture and Planning in King Saud University in Riyadh who

asked his students to participate in distributing the questionnaires as an optional

assignment. The researcher met with the students and went over the details of

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the questionnaire and the method o f distributing and collecting them and

arranged for group visits to the sites.

The students were provided with maps showing marked houses where

the questionnaires were to be distributed. The students were instructed to make

a doorstep visit and explain to the head of the household the nature and

rationale of the questionnaire. The time of this visit was chosen carefully to make

sure that the households were available. In case the head o f the household was

not available, the students were instructed to revisit the site as many times as

needed.

As far as the REDF houses are concerned, and as mentioned earlier, it

was not possible to know which houses were built by this agency. The map of

the ten prepared sections of the city of Riyadh were presented to the students

who were then asked to select the section where they happened to know friends

or relatives whose houses were built by REDF loan. Each student was then

handed a set of questionnaires to be delivered to and collected from the

assigned households.

Site Observation.

After directing the students to the site of MPWH housing, the researcher

himself made individual field trips to the MPWH and REDF housing. The

researcher obtained a letter from the Dean of the School of Architecture along

with an identification card that was presented to the local authorities as well as

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the household members. The documents explained the nature of the study and

invited the residents to cooperate with the researcher. The visits were

videotaped and some pictures of the houses were taken to observe the changes

that might have taken place or were taking place during the time of the visit. This

observation made it possible to understand the interaction between households

and their houses and to recognize certain adjustment to the houses. Visiting the

houses that were being studied and engaging in casual conversations with some

heads of households were documented with notes to shed more light on the

nature of these houses and on the household adjustment behavior. These notes

are used to provide further explanations of the quantitative findings.

In case of the REDF houses, while many changes had occurred over the

years, the ongoing actual adjustment was hardly visible, since these houses had

been inhabited for some time. On the other hand, the ongoing actual adjustment

of the MPWH ready-to move-into houses was taking place during the time of

study; the households had just moved to these prototype houses.

Data Entry

At the end of the field trip made to Saudi Arabia, the collected

questionnaire booklets, other supporting materials, and illustrations were brought

back to the Unites States. The supporting materials were used to carry out the

study.

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The sample size for the statistical analysis consists of 230 households

extracted from the total number of 350 questionnaires originally distributed. The

other 120 cases were excluded because they were incomplete and failed to

meet the criteria of the analysis. The questionnaire data were translated into

numbers and scores guided by a coding book that was written along with the

questionnaires. This would specify how each variable was scored. For example,

in the case of the gender variable, the male was assigned the code “0” whereas

the female was assigned the code “1”. All variables were named and labeled

using the SPSS program. In addition to being user friendly, the SPSS program

was used because of its capability to perform the type of statistical computing

needed for this study.

A good rule of thumb is to record the data at a molecular level, thus

making it possible to aggregate the codes later for testing the suggested

hypotheses of the research model. During and after data entering, verification for

accuracy was performed on a regular basis. Recoding, computing, and verifying

the data laid the ground for making data description, analyses, and hypotheses

testing. Regression analysis was used to assess the amount of variation in the

dependent variables that was explained by the independent variables

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Chapter 4

Analysis and Findings

Chapter Three presented the hypotheses and addressed the method and

the procedure of data collection and entry. The present chapter presents the

analysis o f the data. First, the procedure used to conduct the analyses is

presented, followed by a descriptive analysis focusing on the variables of the

Models for each housing type. A discussion of the sample distributions is then

presented followed by an examination of the correlation coefficients to reveal the

bivariate associations between pairs of variables included in the models.

The results of the regression analyses are reported in this chapter

followed by a presentation of the results of hypothesis testing along with the

analysis o f the relationship among the different variables. The chapter ends with

a discussion of the findings and their significance.

Analytical Procedure

Two samples were used in this study totaling 230 cases. The first sample

consisted of 115 cases representing houses built with the help of the REDF

agency. The second sample included 115 houses built by MPWH. For the purpose

of hypothesis testing, both sets of data were analyzed together and separately.

Descriptive statistics are shown first to illustrate the characteristics of each

sample used in the study. The percentage distribution of each of the variables for

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each sample provides an overview and preliminary comparison of the two types

of houses. Two kinds of tests were used to determine whether and to what

degree the differences between the two types of houses are significant. For non-

categorical data, reflected in Tables 4 and 7, the t-test (t) was used. For

categorical data, reflected in Tables 5, 6, 8 to 13, the Chi-square test was used.

It is important to note that the distributions o f some variables were recoded

temporarily for illustrative purposes. For instance the age variable was recoded

into four categories (less than 35, 35 — 49, 50 - 64, and 65+). However, the

reported mean, standard deviation, t-tests, and the chi-square test with their p-

values and the degree of freedom were based on the original frequency

distribution, ranging from age 27 to 80.

For each set of data, Pearson correlation coefficients were calculated to

measure the relationships of all pairs o f variables presented in the proposed

model. Regression analysis was used to assess the amount of variation in the

dependent variables that was explained by the independent variables. The

overall regression model was evaluated by examining the R2and the

corresponding F-values. R2 represents the proportion of variance explained by

the independent variables. If the computed F-value is higher than the tabular-

value, the regression of the dependent variable on the independent variables is

considered statistically significant. The null hypotheses was accepted or rejected

based on the level of significance.

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Sample Description

The following section describes the different sets of variables included in

the models varying from the independent variables (household variables,

housing construction variables, and previous adjustment variables) to the

dependent variables (physical housing characteristics variables and the housing

adjustment behavior variables).

Household Variables

Table 4 shows the percentage distribution for household variables

including household size, age of the household head, household income, and

education of the household head. Since all household variables were non-

categorical, t-tests were used to determine the level of differences between the

two types of houses.

The size of the REDF household ranged from two to 17 members with a

mean of 7.36, whereas the size of the MPWH households ranged from two to 11,

with a mean o f 5.99. Large household size amounting to eight persons or more

tended to be more common in REDF houses (42.7 percent) than it did in the

MPWH houses (26.1 percent). This difference between the two types of houses

in terms of household size was not statistically significant at the level of .05 (t =

4.357).

The ages of the REDF household heads ranged from 27 to 80 years, with

a mean o f 45.97 years and a standard deviation of 11.95. The ages of the

MPWH household heads ranged from 28 to 65 years, with a mean of 37.76 and

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a standard deviation of 6.42. Household heads living in MPWH houses, whose

age was less than 35 years, were twice as many as the household heads living

Table 4

Distribution o f household variables.

REDF MPWH Household Variables Houses Houses

N=115(%) N=115 (%) Household size

2-3 persons 5 (4.3) 12 (10.4) 4-7 persons 61 (53.0) 73 (63.5) 8+ persons 49 (42.7) 30 (26.1) Mean, Std. Dev. 7.36 2.61 5.99 2.12 Total 115 (100.0) 115 (100.0) t-value, p., df. 4.357 0.061 228

Age of the head Less than 35 24 (20.8) 48 (41.7) 35-49 54 (47.0) 59 (51.3) 50-64 21 (18.3) 7 (6-1) 65+ 16 (13.9) 1 (0.9) Mean, Std. Dev. 45.97 11.95 37.76 6.42 Total 115 (100.0) 115 (100.0) t-value, p., df. 6.495 0.00 0** 228

Household income Less than SR 3,999 2 (1.7) 6 (5.2) SR 4,000 -7,999 26 (26.6) 60 (52.2) SR 8,000 -11,999 45 (39.1) 33 (28.7) SR 12,000 -15,999 26 (22.6) 13 (11.3) SR 20,000-23,999 12 (10.4) 3 (2.6) SR 24,000 + 4 (3.6) 0 (0.0) Mean, Std. Dev. 11,120 1.09 8,160 0.86 Total 115 (100.0) 115 (100.0) t-value, p., df. 5.710 0.04 1* 228

Education of the head Informal 13 (11.3) 4 (3.5) High school or less 39 (33.9) 63 (54.8) Some bachelor or higher 63 (54.8) 48 (41.7) Total 115 (100.0) 115 (100.0) t-value, p., df._______________ 1.173_________0.148_________ 228

•Significant at p < .05 ** Significant at p < .01

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in REDF houses (41.7 percent vs. 20.8 percent). In contrast, household heads

living in MPWH houses, and whose age was 50 years or older, were smaller in

number than household heads living in REDF houses (7 percent vs. 32.1

percent). This difference between the two types of houses in terms of the age of

the household heads was highly significant at the level o f .01 (t = 6.495).

When it comes to household income, Table 4 also revealed a significant

difference between the two household samples at the level o f .05 (t = 5.710).

This means that the average household monthly income for the REDF

households was significantly higher than that of the MPWH households. The

income o f the REDF households ranged from less than SR 3,999 (US $1,066) to

more than SR 24,000 (US $6,400), with a mean of SR 11,120 (US $2,965), and

a standard deviation of 1.09. The income of the MPWH households ranged from

less than SR 3,999 (US $1,066) to less than SR 24,000 (US $6,400), with a

mean of SR 8,160 (US $2,176) and a standard deviation of 0.86.

Education was temporarily recoded into three categories, including

informal education, high school or less, and higher education. Informal education

refers to traditional education that existed prior to formal, government-run

educational programs that emerged in the 1950s. Informal education used to be

offered in mosques and was intended, among other things, to help children

acquire basic reading and writing skills. Informal education is normally

associated with older household heads. The percentage of household heads

with informal education who lived in REDF houses was higher than the

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percentage of household heads living in MPWH houses (11.3 vs. 3.5 percent).

With regard to formal education, the table shows that the percentage of

household heads living in REDF houses with at least one year o f higher

education amounted to 54.8 percent. This percentage was higher than that of

household heads living in MPWH houses with the same level of education (41.7

percent). This difference, however, is not statistically significant as can be seen

from the t-test (t = 1.713).

Housing Construction Variables

The next set of variables has to do with the various factors affecting the

final construction outcome of REDF houses. The distribution of each variable is

illustrated in Table 5. These variables of housing construction were limited to the

REDF houses, where the household manages the house construction. These

variables included the changes made by the owner of the house during the

construction, the changes made by the contractor during the construction, the

constraints imposed by building regulations, the constraints imposed by the

REDF regulations and the house designer.

It should be noted that 21.7 per cent of the cases were not included in

these variables because they consisted of households who were either renters or

buyers of already completed REDF houses. In terms of the alterations made by

the owner, 50 respondents, accounting for 43.5 percent of the respondents,

indicated that they did not make any alteration during construction, whereas 40

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respondents, accounting for 34.8 percent, indicated that they did make

alterations in their houses during construction. Concerning the alterations

introduced by the contractor, the table shows that only 12 respondents (10.4

percent) indicated that the contractor introduced alterations to the original design

of the house, whereas the majority of the respondents (67.8 percent) indicated

that the contractor introduced no alterations whatsoever.

Table 5

Distribution of housing construction variables.

Housing construction variables N

REDF Houses =115 (%) Owners

Owner changes during construction No 50 (43.5) Yes 40 (34.8) NA 25 (21.7)

Contractor changes during construction No 78 (67.8) Yes 12 (10.4) NA 25 (21.7)

Constraints of building regulation No 67 (58.3) Yes 23 (20.0) NA 25 (21.7)

Constraints of REDF regulation No 78 (67.8) Yes 12 (10.4) NA 25 (21.7)

Designer of the house Design firm 78 (67.8) Others 12 (10.4) NA 25 (21.7)

NA = Not Applicable

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In response to the question of whether the building regulations had a

constraining effect on the design and the construction of the house, 58.3 percent

of the respondents gave a positive response. The other 20 percent of the

respondents felt they did not have any constraint imposed by the building

regulations. With respect to the question of whether the REDF regulations had a

constraining effect on the design or the shape of the house, only 10.4 percent of

the respondents gave a positive response. Other respondents (67.8 percent) felt

they did not have any constraints imposed on them. Concerning the designer of

the house, the findings showed that most of the respondents (67.8 percent) hired

a firm to design their houses. Other respondents (10.4 percent) chose other

design methods.

Previous Adjustment Variables

Table 6 presents the distribution of the two variables dealing with previous

adjustment behavior, namely pre-moving adjustment and post-moving

adjustment. The pre-moving adjustment consisted of the adjustment conducted

by the household prior to moving to the house. The post-moving adjustment was

the adjustment conducted by the households after living in the house.

The table indicates that 91.3 percent of the households in MPWH houses

made some adjustment to their houses prior to moving into them. In the case of

REDF houses, however, only 25.2 percent of the households engaged in some

sort of adjustment to their houses. This difference in terms of pre-moving

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adjustment between the REDF houses and the MPWH houses turned out to be

statistically significant at the level o f .01 (t = 103.3).

When it comes to adjustment made after the household moved into their

new houses, the t-test yielded significant difference between the two types of

houses at the level o f .01 (Chi-square = 33.4). While 59.1 percent of the REDF

households engaged in some kind of adjustment behavior, only 21.7 percent of

the MPWH households engaged in such adjustment.

Table 6

Distribution of previous adjustment variables.

Physical housing characteristics REDF Houses N=115(%)

MPWH Houses N=115 (%)

Total

Pre-moving Adjustment No 86 (74.8) 10 (8.7) 96 Yes 29 (25.2) 105 (91.3) 134

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 103.3 0.000** 1 Post-moving Adjustment

No 47 (40.9) 90 (78.3) 137 Yes 68 (59.1) 25 (21.7) 93

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 33.4 0.000** 1

•Significant at p < .05 ** Significant at p < .01

Physical Housing Characteristics Variables

The physical housing characteristics variables consisted of size and

condition of the house. Table 7 shows that the number of bedrooms in the REDF

houses was larger than that o f the MPWH houses. About 54 percent of the

REDF houses had between four to five bedrooms, whereas only 9.5 percent of

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the MPWH houses had that many bedrooms. In addition, 41.7 percent o f the

REDF houses had six bedrooms or more as opposed to the MPWH houses

where such a number of bedrooms was virtually non-existent. Only 4.3 percent

of the REDF houses had three bedrooms, whereas most MPWH houses (72.4

percent) tended to have three bedrooms. The difference between the two types

of houses in terms of number of rooms was statistically significant at the .01 level

(t = 16.867). This difference could be explained by the fact that MPWH houses

had a prototype design consisting of three bedrooms, whereas the REDF houses

were built by their owners who were able to erect as many bedrooms as needed,

which turned out to be large in most cases. Some households (17.4 percent)

chose to convert one of the three bedrooms to another guest room and ended up

having two bedrooms only. Others (9.5 percent) pursued the opposite approach

and converted the living room to a bedroom and ended up with four bedrooms in

their houses.

Table 7

Distribution of the housing size variable.

Housing size REDF Houses N=115 (%)

MPWH Houses N=115 (%)

2 bedrooms 0 (0.0) 20 (17.4)

3 bedrooms 5 (4.3) 84 (73.1)

Number of bedrooms 4-5 bedrooms 62 (53.9) 11 (9.5)

6-7 bedrooms 32 (27.8) 0 (0.0)

8+ bedrooms 16 (13.9) 0 (0.0)

t-value, p., df._________________________ 16.867 0.000** 228 'Significant at p < .05 ** Significant at p < .01

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In terms of the conditions of the house, Table 8 shows that the

overwhelming majority of both REDF and MPWH households found their houses

in good or excellent condition (90.5 percent and 87.8 percent respectively). The

Chi-square test yielded no significant difference between the two housing types

in terms of the condition of the house.

Table 8

Distribution of the housing condition variable.

Condition of the house REDF Houses N=115 (%)

MPWH Houses N=115 (%)

Total

Poor 1 (0.9) 3 (2.6) 4

Adequate 10 (8.7) 11 (9.6) 21

Good 58 (50.4) 55 (47.8) 113

Excellent 46 (40.0) 46 (40.0) 92

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 1.127 0.770 3

‘Significant at p < .05 ** Significant at p < .01

Housing Adjustment Behavior Variables

Household deficit

Household deficit was comprised of two types of deficit, one having to do

with culture and the other with space. Table 9, which deals with variables

measuring cultural deficit, shows that approximately half of the respondents

(43.5 percent) perceived a deficit in their housing when asked whether the

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neighbor could invade their privacy from the upper floor windows to the front and

the backyard. The other half of the respondents did not express their concern

about privacy. Privacy invasion was not an issue in the MPWH houses, which

consisted o f only one floor.

Table 9

Distribution of household deficit measured bv privacy features and the perceived

sufficiency of quest space.

Household cultural deficit REDF Houses N=115 (%)

MPWH Houses N=115 (%)

Total

Provision of household privacy for the front and back yards

No 50 (43.5) NA NA Yes 65 (56.5) NA NA

The ability to look through first floor windows with comfort.

No 104 (90.4) NA NA Yes 11 (9.6) NA NA

Provision of adequate separation between family and guest domain No 19 (16.5) 37 (32.2) 56

Yes 96 (83.5) 78 (67.8) 174 Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 7.648 0.006** 1 The sufficiency o f guest reception room No 18 (15.7) 49 (42.6) 67

Yes 97 (84.3) 66 (57.4) 163 Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 20.239 0.000** 1 The sufficiency o f guest dining room No 20 (17.4) 42 (36.5) 62

Yes 95 (82.6) 73 (63.5) 168 Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 10.687 .00 1** 1

NA = Not Applicable ‘ Significant at p < .05 ** Significant at p < .01

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The other form of cultural deficit had to do with the degree o f comfort of

the household female members when looking through the upper floor window to

the street. Here, the overwhelming majority of the REDF respondents (90.4

percent) expressed their disapproval o f the design setting that leads to this

discomfort. In the case of the MPWH, this perceived cultural deficit did not exist

because this type of housing had only one floor.

Another feature of privacy had to do with the degree to which the house

provided adequate separation between the family and the guest domain,

allowing a male guest to get in and out without causing any discomfort to the

females in the home. Here, 83.5 percent o f the REDF household respondents

expressed their comfort with the existing level of separation. Similarly, the

degree of comfort with the level of separation in the case of the MPWH

households turned out to be high (67.8 percent) although not as high as that of

the REDF households. The difference between the two types of houses in terms

of providing adequate separation between the family and the guest domain was

statistically significant at the .01 level (Chi-square = 7.688).

Another cultural issue had to do with the perceived sufficiency of the

reception room. Because of the strong family ties existing in the Saudi culture,

and because of the frequent social gatherings, Saudis tend to prefer reception

rooms that can accommodate a large number of guests. The REDF houses and

the MPWH houses differed significantly in terms of their ability to provide

sufficient space in reception room size. This difference was statistically

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significant at the level of .01 (Chi-square = 20.239). REDF houses provided

sufficient space in reception rooms as evidenced by the fact that 84.3 percent of

the respondents felt that the existing total area was sufficient. When it comes to

the MPWH houses, just over half of the households (57.4 percent) felt that they

had sufficient reception room. The other respondents (42.6 percent) felt there

was a lack of reception room sufficiency.

The same conclusion could be made regarding the guest dining room

area. As Table 5 shows, the difference between the two housing types in

providing sufficient space in guest dining room turned out to be statistically

significant at the level of .01 (Chi-square = 10.687). About 82.6 percent of the

REDF respondents, versus 63.5 of the MPWH respondents, felt that the total

area of the guest dining room was sufficient.

The other type of household deficit had to do with space. The space

deficit variable was measured by subtracting the total number of existing

bedrooms from the total number of needed bedrooms. To apply the housing

deficit variables to hypothesis testing and use them in the regression analysis,

the last three variables in Table 5 were combined to create a housing deficit

scale at the cultural level. These variables were added to the space deficit

variable to create a deficit scale totaling four variables to be used in comparative

hypotheses testing for both housing types combined together (Model 3) and for

the REDF houses with shared variables (Model 1). The deficit scale with four

variables was also used in testing hypotheses dealing with MPWH houses only

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(Model 2). As to REDF houses (Model 4), the space deficit variable was added to

all five variables in Table 5 to create a deficit scale totaling six variables.

All five cultural deficit variables, some of which were interrelated, were

weighted equally to the space deficit variable in the regression analysis of Model

4. Similarly, the three cultural deficit variables in Models 1, 2, and 3 were

weighed equally to the space deficit variable.

Housing satisfaction

Table 10 presents the distribution of the level of housing satisfaction of

the two samples. It is clear that the majority of the households in the two types of

houses, REDF and MPWH, were either satisfied or very satisfied with their

houses (45.2 + 44.3 = 89.5 percent and 34.8 + 52.2 = 87 percent respectively).

The Chi-square test shows that the difference between the two types in terms of

the level of households’ satisfaction was not statistically significant.

Table 10

Distribution of housing satisfaction.

Housing satisfaction REDF Houses N=115 (%)

MPWH Houses N=115 (%)

Total

Dissatisfied 10 (8.7) 7 (6.1) 17

Neither nor 2 (1.7) 8 (7.0) 10

Satisfied 52 (45.2) 40 (34.8) 92

Very satisfied 51 (44.3) 60 (52.2) 111

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df._______________ 6.424_______.093_________3

•Significant at p < .05 ** Significant at p < .01

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Propensity to adjust

Propensity to adjust could be expressed in two ways: making alteration or

addition to the house or moving to a different one. This propensity to adjust is

reflected in Tables 11 and 12.

Table 11 shows the distribution of the responses to propensity to make

alterations or additions to the current house. The desire to engage in this type of

Table 11

Distribution of propensity to make changes to current house.

Expected changes REDF Houses N=115 (%)

MPWH Houses N =115(%)

Total

Never thought about 63 (54.8) 23 (20.0) 86

Have considered 21 (18.3) 15 (13.0) 36

Plan to change 31 (25.0) 77 (66.9) 108

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df.________ 39.426 0.000**_______ 3

’ Significant at p < .05 ” Significant at p < .01

adjustment behavior was expressed by 66.9 of the MPWH households,

compared to only 26 percent of REDF households who expressed their desire to

engage in adjustment behavior. The difference between the two housing types in

terms of the households’ desire to engage in alterations or additions to the

current house turned out to be statistically significant at the level of.01 (Chi-

square = 39.426). This pattern in MPWH houses may be due to the fact that the

occupants had moved to ready-to-move-into houses designed and built without

their input.

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In terms o f the propensity o f moving to a different house, Table 12 shows

that 78.3 percent of the MPWH households never thought of moving out o f their

houses. The percentage of the REDF households who never thought of moving

amounted to 51.3. The Chi-square test (23.125) yielded a significant difference

between the two housing types in terms o f the households’ desire to move from

the current house. This difference was significant at the .01 level.

Table 12

Distribution of propensity to move from the current house.

Expectation about moving REDF Houses N=115 (%)

MPWH Houses N=115 (%)

Total

Never thought about 59 (51.3) 90 (78.3) 149

Expect, want, or have thought 45 (39.1) 23 (20.0) 68

Definite plan 11 (9.6) 2 (1.7) 13

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df.______________ 23.125 0.000**_______ 4

’ Significant at p < .05 ** Significant at p < .01

Expected future improvements

Table 13 shows that the difference between REDF and MPWH

households in terms of their expectations about the future improvement in

housing situation turned out to be statistically significant at the level of .01 (Chi-

square = 49.500). Among the REDF households, 33.9 percent thought that their

housing situation would stay the same. A large number of the MPWH

households (98.3) expected their housing situation to get better. A relatively high

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number of REDF households (60.9 percent) expressed the same level of future

expectations.

Table 13

Distribution of expectation about future improvements.

Expectation about future impr. REDF Houses MPWH Houses Total N=1 15 (%) N=1 15 (%)

Will get worse 6 (5.2) 0 (0.0) 6

Will stay the same 39 (33.9) 2 (1.7) 41

Will get better 70 (60.9) 113 (98.3) 183

Total 115 (100.0) 115 (100.0) 230 Chi-square, p., df. 49.500 O.CI00 3

'Significant at p <.05 ** Significant at p <.01

Discussion of Sample Distributions

The previous section presented some of the findings of this study as they

relate to housing adjustment behavior in both MPWH and REDF houses. In light

of these findings, an attempt will be made to interpret and draw some

conclusions from these findings.

The REDF houses and MPWH houses differ from each other in terms of

housing adjustment behavior variables. With respect to household variables, the

two housing types differ from each other significantly in terms of age of the head

of the household and household income.

The difference between the two housing types in terms of the age of the

household head could be explained by the fact that the MPWH houses were

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constructed in the 1990’s, making them newer than REDF houses, which started

to be constructed in the mid-1970’s and 1980’s. Younger households obtained

MPWH houses, partly because they were available at the time when they applied

for housing and partly because the size of these houses tend to be smaller and

therefore cheaper than that of the REDF houses. Therefore, the MPWH houses

fit the needs of the younger household heads that are at an early and middle

stage of their family life.

As to the income variable, the REDF households tended to have

significantly higher income than the MPWH households. One explanation for this

difference is that some REDF households tended to have an extra income

generated by younger household members in addition to the income o f the

household head.

The education of the head turned out to be not significant, suggesting that

the level o f education is not related to the housing type for the household. This

means that households with informal as well as highly educated households

have access to both REDF and MPWH houses.

Pre- and post-moving adjustment variables differ significantly between the

two houses. The fact that the MPWH households conducted pre-moving

adjustment at a level significantly higher than that of the REDF household can be

explained by the deficit experienced by the MPWH households during their first

evaluation of their ready-to-move-in houses. At the same time, the high

percentage of me MPWH households who did not conduct any post-moving

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adjustment could be explained by the possibility that they had already conducted

pre-moving adjustment to their houses. Another possible explanation for the lack

o f post-moving adjustment could be that it was still too early for these

households to conduct such an adjustment, keeping in mind that the

questionnaires were distributed less than two years after they had moved to their

ready-to-move-into houses.

Concerning housing size, the study found a significant difference between

the two housing types. REDF houses tended to have larger numbers of

bedrooms than did MPWH houses. This finding can be explained by the fact that

the design and construction o f the MPWH houses is standardized, consisting of

three bedrooms only. The REDF houses, however, tended to have a larger

number of rooms ranging from three to eight and more. These houses were built

by individual owners who were driven by their space and cultural norms when

determining the number of desired rooms. The MPWH households did not have

that option because of the prototype design of their houses, causing some

households (17.2 percent) with a small number of members to transform one of

their bedrooms to a guest room. Other households (9.5 percent), with a large

number of members, chose either to transform the guestroom to a bedroom to

satisfy their needs, or enclosed an area on the roof as an additional bedroom, or

attached an annex to the building.

With regard to the household cultural deficit, the households of the MPWH

did not have major privacy problems because they had houses with only one

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floor. In terms o f REDF households, and as shown in Table 5, half of the

respondents did not perceive a deficiency in their privacy, apparently because

they have successfully tackled this problem by increasing the height of the

existing fence. Another way of tackling the invasion of privacy caused by

neighbors’ upper floor windows is by requesting the neighbors to raise the level

of their window, making it hard to see through them while at the same time

allowing light and air to get through. Another explanation for lack of concern

about privacy invasion among the second half o f the respondents may be the

high degree of trust that they have toward their neighbors

Concerning the perceived lack of sufficiency in the reception room area,

the study found that, in the case of the REDF houses, 84.3 per cent of the

respondents found the size of guest room sufficient. In the case the MPWH

houses, however, only 57.4 per cent felt they had sufficient room. Similar results

are shown in the guest dining room area, where 82.6 percent of the REDF

households, versus 63.5 of the MPWH households, found the guest dining room

sufficient. This discrepancy in the percentage of the household perception of

guest room and dining room sufficiency could be explained by the fact that the

REDF houses were designed and erected by individual households. The MPWH

houses, however, were designed by an international firm that may not be well

acquainted with Saudi cultural norms.

There is a high level of overall housing satisfaction among both types of

households reflected in Table 9. This degree o f satisfaction, which amounts to

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89.6 percent in the case of REDF houses, and 87.0 percent in the case of

MPWH houses, could be explained by the fact that the respondents in both types

of houses actually liked their houses. This seemingly high degree of satisfaction

could also be explained by the fact that, in the religion o f Islam, Muslims should

not complain about their living conditions publicly, even if they might be

dissatisfied internally. They must instead be thankful and grateful to their creator.

It is not unusual, therefore, to find that many needy and poor people refrain from

complaining publicly about their living conditions and pretend to be thankful and

satisfied. With this high level of satisfaction of both REDF and MPWH

households, the Chi-square test revealed no significant deference between the

two types of households.

When it comes to the expectation of future improvement, there is a

significant difference between the two housing types. A high level of expectation

about housing improvement in the MPWH houses can be explained by the

intention of some of the households to add a second floor with more space to

reduce the level of their space deficit.

In brief, this section examined the differences between the two housing

types with respect to individual variables, such as age o f the household head,

education, income, satisfaction, and future expected improvement. The next

section tries to determine the differences between the two housing types in terms

of the physical housing characteristics variables as well as the housing

adjustment behavior variables when considering all the predictors in the models.

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This was achieved by using regression analysis procedures. First, correlation

coefficients were calculated to detect any multicollinearity that might exist

between the independent variables of the models.

Correlation Coefficients

The correlation matrix, consisting of correlations between all pairs of

variables used in the model, is shown in Table 14 for the combination data of

both houses, the MPWH and the REDF, Table 15 for the MPWH data, and Table

16 for the REDF data. The usefulness of the correlation matrix lies in showing

the directions of the relationship between the pairs of variables.

Table 14 shows the correlation coefficients for the MPWH and REDF data

as they relate to Model One. Model One combined the two sets of data and dealt

with the relationship among the household variables, previous adjustment

variables, physical housing characteristics variables, household deficit, housing

satisfaction, propensity to adjust, and expected future improvement. The

correlation coefficients among these variables ranged from 0.006 to 0.745.

Table 15 shows the correlation coefficients for the MPWH data as they

relate to Model Two. It dealt with the relationships among household variables,

previous adjustment variables, physical housing characteristics variables,

household deficit, housing satisfaction, propensity to adjust, and expected future

improvement. The correlation coefficients ranged from 0.011 to 0.444.

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Table 14

Pearson product-movement correlation coefficient matrix of the REDF AND MPWH houses for Model One

Variables 1 2 3 4 10 11 12 13 14 15 16 17 18

1. Household size —

2. Age of the head .293“ -

3. Household income .267“ .235“ --

4. Education of the head -.051 -.411“ .203“ --

10. Pre-moving adjustment -.064 -.167* -.157* -.094 -

11. Post-moving adjustment .233“ .302** .270“ .013 -.071 --

12. Size of the house .349“ .465“ .421“ -.071 -.467“ ,371“ - -

13. Condition of the house .006 -.044 .094 .093 -.159“ -.136* .061 -

14. Housing type -.277“ -.395“ -.354“ -.077 ,589“ -.384“ -.745“ -.031 -

15. Household deficit (4 v) .141* -.061 -.146* -.064 .353“ -.010 -.357“ -.303“ .310“ -

16. Housing satisfaction -.050 .034 .107 .040 -.099 -.143* .082 .354“ ,046 -.312“ ~

17. Propensity to adjust .029 .001 -.079 .028 .173“ .039 -.202“ -.293“ .107 .341“ -.311* --

18. Expected future improv, -.210“ -.222“ -.185* -.029 .118 -.232“ -.222“ ,164* .374* -.114 .117 -.093 --

Variables 5-9 do not apply to this set of data, “ Correlation is significant at the 0,01 level. ‘ Correlation is significant at the 0,05 level.

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without perm ission.

Table 15

Pearson product-movement correlation coefficient matrix of the MPWH houses for Model Two

Variables 1 2 3 4 10 11 12 13 15 16 17 18

1. Household size —

2. Age of the head .427“ -

3. Household income -.026 -.019 —

4. Education of the head -.111 -.415“ .444“ --

10. Pre-moving adjustment .101 -.034 .056 -.120 --

11. Post-moving adjustment .133 -.060 .131 .070 .011 --

12. Size of the house -.030 .215“ -.022 -.073 .050 -.208* -

13. Condition of the house .030 .113 .185* .134 -.133 .078 .142 --

15. Household deficit (4 v) .388“ .146 -.062 -.161 ,273“ .045 -.150 -.267“ -

16. Housing satisfaction -.139 .075 .125 .095 -.190* -.095 .241“ .312“ -.354“ -

17. Propensity to adjust .085 -.067 .055 -.036 .104 .159 -.208* -.204* ,177 -.273“ --

18. Expected future imp -.067 -.088 .050 .115 -.214* -.017 .175 .172 -.283“ .151 -.109 -

Variables 5-9 & 14 do not apply to this set of data. “ Correlation is significant at the 0.01 level, ‘ Correlation is significant at the 0.05 level.

Table 16 shows the correlation coefficients for the REDF data as they

relate to Models Three and Four. Model Three dealt with the relationship among

household variables, previous adjustment variables, physical housing

characteristics variables, household deficit, housing satisfaction, propensity to

adjust, and expected future improvement. The correlation coefficients among

these variables ranged from 0.001 to 0.521. Model Four dealt with the housing

construction variables in addition to all the variables in Model Three. The

correlation coefficients among these variables ranged from 0.001 to 0.521. It is

important to note that Models Three and Four differed from each other at the

level of the deficit scale, which was comprised of four variables in the case of

Model Three, and six variables in the case of Model Four.

Correlation coefficient represents the strength and the direction of

relationship between a pair of variables. Inspecting the correlation matrix helps

detect multicollinearity. If high correlations of 0.80 or higher occur among the

predictor variables, the regression may risk multicollinearity, causing a large

standard error when running the regression analysis (Knocke & Bohrnstedt,

1994). The correlation between some independent variables turned out to be

greater than 0.50. In the case of the age and the education of the head, the

correlation coefficient was 0.521 in Models Three and Four. The correlation

coefficient between housing type and the size of the house was 0.745 in Model

Three. None o f the correlation coefficients reached the .80 level in ail four

models, suggesting absence of multicollinearity.

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Table 16 Pearson product-movement correlation coefficient matrix of the REDF houses for Model Three and Four

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 15a 15b 16 17 18

1. Household size

2. Age of the head ,118 —

3, Household income ,326** .168 -

4. Education of the head -.053 -.521** .030 -

5. Changes by owner -.001 -.188 -.002 .165 --

6. Changes by contractor -.051 .064 .044 -.015 .175 --

7. Building regulations .033 .014 -.016 -.012 .142 .145 --

6. REDF regulations ,134 .055 .135 .067 .175 ,327** -.005 --

9. Designer .146 -.094 -.038 -.098 .004 .152 -.066 .052 --

10, Pre-moving adjust .165 .193* .085 -.003 .064 .202 -.117 .172 -.042 -

11. Post-moving adjust .151 .241** .169 -.053 -.012 .265* .128 ,398** -.027 .381** --

12. Size of the house .313** .294** ,349** -.241** -.063 .042 -.023 ,042 .017 -.118 ,203 -

13. Condition of the house -.031 -.172 .007 .056 .140 -.177 .246* -.069 -.123 -.236 -.311** .031 -

15a. Household deficit (4 v) .122 .032 -.022 .068 -.061 .163 -.014 -.052 ,165 .141 .190 -.264** -.364** -

15b. Household deficit (6 v) .094 .038 -.065 .077 -.036 ,183 -.006 -.049 ,160 .120 .174 -.274** ,325** -.965** -

16. Housing satisfaction ,041 .051 ,139 .004 .148 -.029 -.005 .049 -.063 -.116 -.167 .172 -.404** .335** ,325** -

17. Propensity to adjust .045 .100 -.113 .085 -.015 .095 -.108 .009 .003 .182 .060 -.194** .379** -.488** -.473** -.357** -

18. Expected future imp -.147 -.087 -.114 -.053 -.108 .065 -.049 -.122 -.052 -.096 -.130 .075 .216** .272** ,284** .088 -.166 "

Variable 14 does not apply to this set of data. “ Correlation is significant at the 0.01 level. ‘ Correlation is significant at the 0,05 level.

Regression Analyses

Regression analysis is used to assess the amount of variation in the

dependent variables that is explained by the independent variables. In this

section, an attempt will be made to assess the relationships among the variables

using regression analysis procedures. The regressions require that every

variable in the model be arranged as a continuous or dummy variable. Within

each type of housing, the relative contribution of each independent variable in

predicting the dependent variable is evaluated by examining the standardized

regression coefficients (beta) and t-test for the significance of each coefficient.

Beta shows the degree of difference in the dependent variable in response to

differences in the independent variable, as measured in standard deviation units.

To investigate the relationships among the various combinations of

variables, four models were developed based on the three themes of the null

hypotheses formulated in Chapter Three. Model One dealt with both types of

houses with shared variables. Model Two dealt with MPWH houses with shared

variables. Model Three dealt with REDF houses with shared variables, and

Model Four dealt with REDF houses with all variables.

Shared variables consisted of household variables (household size, age

of the head, household income, and education of the head), previous adjustment

variables (pre-moving adjustment and post-moving adjustment), and physical

housing characteristics. They applied to models One, Two, and Three. Model

One, which was a combination of MPWH and REDF household respondents’

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data, consisted o f the type of house variable in addition to the shared variables.

Model Four represents REDF houses with all variables that consisted of shared

variables and housing construction variables, including changes made by the

owner, changes made by the contractor, constraints of building regulations,

REDF regulations and designing method.

The R2 yielded by regression analysis indicates the percentage of

variation in the dependent variables that is explained by all of the independent

variables entered as a group in each model. The F-test is a test of the

significance of the R2and is considered significant if the probability is less than

0.05. The relative effect of each of the independent variables, which is assessed

using the standardized Beta coefficients, helps compare the magnitude of each

coefficient to that of the other variables in the model. The Beta coefficients

cannot be compared directly across the four models since the variances are not

the same in the four models. The result of Model One was reported first, followed

by Models Two, Three, and Four. Stepwise regression procedure of the physical

housing characteristics variables (size of the house, condition of the house), and

the housing adjustment behavior variables (household deficit, housing

satisfaction, propensity to adjust, and expected future improvement) were

computed for each model and presented in Tables 17 through 22. The analysis

of the four models will be followed by the null-hypothesis testing utilizing the

output of these regression analysis tables.

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Physical Housing Characteristics Variables

The following is a presentation of the regression analysis of the two

physical housing characteristics variables that include the size of the house and

the condition of the house. The size of the house was first regressed against the

independent variables to identify those variables that have a significant

relationship with the size of the house. The regression analysis (see table 17) will

be used at the end of this Chapter for null-hypotheses testing. Then the condition

of the house was regressed against the independent variables. The analysis will

be followed by reporting the results of the regression analysis of the household

adjustment behavior variables.

Size of the house

Size of the house is considered one of the housing characteristics

variables. As shown in Table 17, the size o f the house variable was first

regressed on the shared variables for both MPWH and REDF houses, along with

the type of house variable (Model One), and then it was regressed on the shared

variables of the MPWH houses (Model Two). The size of the house variable was

then regressed on the shared variables of REDF houses (Model Three), and

finally the size of the house was regressed on all variables, which included

housing construction variables in addition to the shared variables, of the REDF

houses (Model Four). The overall F-value was statistically significant in all four

models and highly significant in the third model (F = 75.364, 5.165, 8.992, 5.970,

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Table 17

Regression analysis of size of the house on the household variables, housing construction variables, previous

adjustment variables, and housing type variable

Categories Variables

Model (1) MPWH & REDF Shared variables

Model (2) MPWH houses

Shared variables

Model (3) REDF houses

Shared variables

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value Beta t-value

1. Household size 0.093 2.105* -0.114 -1.127 0.224 2.593* 0.200 1.930 Household Variables 2. Age of the head 0.108

2.040* 0.204 2.248* 0.160 1.611 0.197 1.585 3. Household income 0.171 3.700* 0.008 0.083 0.270 3.130* 0.298 3.014*

4. Education of the head -0.105 -2.162* 0.031 0.306 -0.277 -2.802* -0.233 -2.356*

5. Changes by owner NA NA NA NA NA NA -0.024 -0.241 Housing

Construction 6. Changes by contractor NA NA NA NA NA NA 0.066 0.655

Variables 7. Building regulations NA NA NA NA NA NA -0.057 -0.567 8. REDF regulations NA NA NA NA NA NA -0.052 0.510

9. Designer NA NA NA NA NA NA -0.045 -0.451

Previous Adj. 10. Pre-moving adjustment -1.799 0.073 0,060 0.657 -0.258 -2.940* -0.216 -2.188* Variables 11. Post-movina adjustment 0.883 0.378 -0.196 -2.159* 0.210 2.375* 0.172 1.554

14. Housing tvpe -0.624 -13.034* NA NA NA NA NA NA

Constant 5.998 2.313 4.179 5.408 R , adjusted R 0.627 0.619 0.084 0.068 0.292 0,260 0.174 0.145 Df.. F-ratio 5 & 224 75.364* 2 & 112 5.165* 5 & 109 8.992* 3 & 85 5.970*

‘ Significant at p <.05, one-tailed test. NA = Not Applicable.

respectively at the level of p < 0.05). The R2 for all four models amounted to

0.627, 0.084, 0.292, 0.174 respectively.

For Model One, all household variables, including household size,

household income, education of the head, were statistically significant. In

addition, the housing type variable (REDF coded “1”, MPWH coded “2”) had a

negative relationship to size of the house (t = -13.034). The REDF houses

tended to be larger in size than the MPWH houses. For Model Two, age of the

head and post-moving adjustment had significant relationship with size of the

house. For Model Three, most variables (household size, household income,

education of the head, pre-moving adjustment, and post-moving adjustment) had

significant relationships with size of the house. For Model Four, the housing

construction variables, which were added for this model, did not seem to have

any significant relationship to the size of the house. Household income,

education of the head, and pre-moving adjustment were the only three variables

that had a significant relationship with the size of the house.

Condition of the house

In addition to size of the house, condition of the house was considered

another housing characteristics variable. The condition of the house was

regressed against the independent variables to identify the variables that had a

significant relationship with the size of the house. The results of the regression of

condition of the house for all four models are presented in Table 18, which

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Table 18

Regression analysis of condition of the house on the household variables, housing construction variables, previous

adjustment variables, and housing type variable

Categories Variables

Model (1) MPWH & REDF

Shared variables

Model (2) MPWH houses

Shared variables

Model (3) REDF houses

Shared variables

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value Beta t-value

Household Variables

1. Household size 0.475 0.635 0.034 0.371 0.016 0.178 -0.025 -0.258 2. Age of the head -0.453 0.651 0.117 1.267 -0.103 -1.118 -0.180 1.878 3. Household income 1.745 0.082 0.185 2.002* 0.061 0.671 0.030 0.306 4. Education of the head 1.233 0.219 0.065 0.630 0.040 0.444 0.032 0.327

Housing Construction

5. Changes by owner NA NA NA NA NA NA 1.05 1.085

6. Changes by contractor NA NA NA NA NA NA -0.128 -1.280

Variables 7. Building regulations NA NA NA NA NA NA 0.302 3.120*

8. REDF regulations NA NA NA NA NA NA 0.105 1.000 9. Desianer NA NA NA NA NA NA -0.141 -1.196

Previous Adj. 10. Pre-moving adjustment -0.169 -2.609* -0.144 -1.567 -0.137 -1.428 -0.071 -0.639 Variables 11. Post-movina adjustment -0.148 -2.275* 0.055 0.585 -0.311 -3.485* -0.379 -3.918*

14. Housino tvoe 0.250 0.803 NA NA NA NA NA NA

Constant R2, adjusted R2 0.047

4.454 0.039 0.034

3.851 0.026 0.097

4.479 0.089 0,207

4.459 0,188

Df.. F-ratio 2 & 227 5.598* 1 & 113 4.006* 1 & 113 12.143* 2 & 86 11.215*

‘ Significant at p <.05, one-tailed test. NA = Not Applicable.

shows conditions of the house regressed on the four models. The overall F-value

was statistically significant in all four models (F = 5.598, 4.006,12.143, 11.215

respectively at the level o f p < 0.05). The R2 for all four models amounted to

0.047, 0.034, 0.097, 0.207 respectively. An R2of 0.207 indicates that 20.7

percent o f the variance in size of the house is explained by the variables

included in the model.

For Model One, the effect of the pre- and post-moving adjustment

variables on the condition of the house turned out to be statistically significant (t

= -2.609, -2.275). Income of the household, in Model Two, appeared to be the

only variable that had a significant relationship to the condition of the house (t =

2.002). In Model Three, post-moving adjustment was the only variable that was

statistically significant, with a negative relationship to condition of the house (t =

3.485). In Model Four, the condition o f the house appeared to be significantly

related to the existence of building regulation constraint variable (t = 3.120). The

condition of the house also appeared to be significantly related to the post-

moving adjustment variable (t = -3.918).

Housing Adjustment Behavior Variables

A presentation of the regression analysis of the two housing

characteristics variables follows. It includes household deficit, housing

satisfaction, propensity to adjust, and expected future improvement. Household

deficit was first regressed against the independent variables to determine the

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magnitude of the relationship. Similarly, housing satisfaction, propensity to

adjust, expected future improvement were then regressed separately against the

independent variables in all four models for the null-hypothesis testing.

Household deficit

The household deficit scale variable consisted of four variables: the

provision of adequate separation between family and guest domain, the

sufficiency of guest reception room, the sufficiency of guest dining room, and the

existence of bedrooms deficit. This type of household deficit was regressed on

the independent variables as shown in Models One, Two, and Three. The deficit

variable of Model Four took into account these four variables as well as the other

two variables that were the provision of household privacy for the front and back

yards and the ability to look through first floor windows with comfort.

As shown in Table 19, the household deficit variable, which was

composed of four variables, was first regressed on the variables of Models One,

Two, and Three. Household deficit variable, which was composed of six

variables, was regressed on the variables in Model Four. The overall F-value

turned out to be statistically significant in all four models (F = 24.573, 13.536,

11.510, 10.651 respectively at the level of p < 0.05). The R2 for the four models

amounted to 0.304, 0.268, 0.237, 0.199 respectively.

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Table 19

Regression analysis of household deficit on the household variables, housing construction variables, previous

adjustment variables, physical housing characteristics variables, and housing type variable

Categories Variables

Model (1) MPWH & REDF Shared variables

Model (2) MPWH houses

Shared variables onlv

Model (3) REDF houses

Shared variables onlv

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value Beta t-value

Household Variables

1. Household size 0.280 4.687* 0.375 4.595* 0.212 2.423* 0.184 1.873 2. Age of the head 0.056 0.869 0.026 0.285 0.047 0.528 0.022 0.217 3. Household income -0.023 -0.363 -0.018 -0.216 0.028 0.304 0.081 0.806 4. Education of the head -0.037 -0.660 -0.064 -0.768 0.024 0.274 0.080 0.813

Housing Construction

5. Changes by owner NA NA NA NA NA NA -.011 -0.116 6. Changes by contractor NA NA NA NA NA NA 0.142 1.461

Variables 7. Building regulations NA NA NA NA NA NA 0.070 0.702 8. REDF regulations NA NA NA NA NA NA -0.059 -0.611 9. Desianer NA NA NA NA NA NA 0.143 1.475

Previous Adj. 10. Pre-moving adjustment 0.160 2.503* 0.202 2.453* -0.016 -0.180 0.127 1.246 Variables 11. Post-movina adjustment -0.025 -0.356 0.013 0.160 1.134 1.503 0.127 1.235

Physical H. C. 12. Size of the house -0.364 -5.401* -0.116 -1.416 -0.320 -3.661* -0.322 -3.331* Variables 13. Condition of the house -0.257 -4.559* -0.251 -3.056* -0.348 -4.193* -0.301 -3.112*

14. Housing tvpe 0.038 0.417 NA NA NA NA NA NA

Constant R2, adjusted R2 0.304

-0.802 0.292 0.268

-3.196 0.248 0.237

0.333 0.217 0.199

2,709 0.180

Df.. F-ratio 4 & 225 24.573* 3&111 13.536* 3 & 111 11.510* 2 & 86 10.651*

•Significant at p < .05, one-tailed test. NA= Not Applicable.

In Model One, the household size, the pre-moving adjustment, the size of

the house, and the condition of the house, had a significant relationship to

household deficit (t = 4.687, 2.503, -5.401, -4.559 respectively). First, the positive

relationship between household size and household deficit indicates that the

larger the size of the household, the higher the level of household deficit. Second,

the positive relationship between the pre-moving adjustment and the household

deficit indicates that households who have done more adjustments have higher

level of deficit. Third, the negative relationship between the size of the house and

the household deficit indicates that the bigger the size of the house, the lower the

level of household deficit. Fourth, the negative relationship of the condition of the

house to household deficit indicates that the better the conditions of the house,

the lower the deficit experienced by the household, in Model Two, the

relationship between the deficit variable and the variables of the household size,

the pre-moving adjustment, and the condition of the house turned out to be

significant (t = 4.595, 2.453, -3.056 respectively). In Model Three, the household

size, the size of the house, and the condition of the house turned out to have

relationships with household deficit at a significant level (t = 2.423, -3.661, -4.193

respectively).

In Model Four, with the addition of housing construction variables, the size

of the house, and the condition of the house variables turned out to have a

negative effect on the household deficit at a significant level (t = -3.331, -3.112).

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Housing satisfaction

Table 20 shows the result of regression of housing satisfaction in the four

models. It illustrates the regression of housing satisfaction on the variables in

Model One, the regression of housing satisfaction on the variables of Model Two,

the regression of housing satisfaction on the variables in Model Three, and the

regression on the variables in Model Four. The overall F-value was statistically

significant in all four models (F = 17.512, 12.015, 14.330 , 12.395, respectively at

the level of p < 0.05). The R2 for all four models amounted to 0.189, 0.177,

0.204, 0.224 respectively.

The condition of the house had a positive significant relationship with

housing satisfaction across the four models, where the t-value amounted to

4.373, 2.639, 3.591, and 3.314 respectively. This indicates that the better the

condition of the house, the higher the level of satisfaction. The household deficit

also had a negative significant relationship with housing satisfaction across the

four models, where the t-value amounted to -4.103, -3.279, -2.389, -2.418

respectively. This indicates that the higher the level of household deficit, the

lower the level of satisfaction. In Model One, the housing type variable had a

positive significant relationship with housing satisfaction (t= 2.193), where the

housing type was coded (1) for REDF houses and (2) for MPWH houses. This

means that the MPWH households are more likely to have a higher degree of

satisfaction than the REDF households.

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Table 20

Regression analysis of housing satisfaction on the household variables, housing construction variables, previous

adjustment variables, physical housing characteristics variables, housing type, and household deficit

Categories Variables

Model (1) MPWH & REDF Shared variables

Model (2) MPWH houses

Shared variables

Model (3) REDF houses

Shared variables

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value Beta t-value

Household Variables

1. Household size 0.029 0.455 -0.039 -0.415 0.079 0.931 0.001 0.009 2. Age of the head 0.101 1.546 0.096 1.091 0.117 1.372 0.035 0.358 3. Household income 0.104 1.630 0.066 0.753 0.132 1.575 0.082 0.865 4. Education of the head 0.008 0.129 0.018 0.200 0.001 0.008 0.021 0.213

Housing Construction

5. Changes by owner NA NA NA NA NA NA 0.100 1.040 6. Changes by contractor NA NA NA NA NA NA 0.081 0.833

Variables 7. Building regulations NA NA NA NA NA NA -0.093 -0.942 8. REDF regulations NA NA NA NA NA NA 0.063 0.661 9. Desianer NA NA NA NA NA NA 0.045 0.464

Previous Adj. 10. Pre-moving adjustment -0.067 -0.870 -0.085 -0,955 -0.009 -0.103 -0.041 -0.407 Variables 11. Post-movina adjustment -0.067 -1.021 -0.101 -1.178 -0.028 -0.314 -0.024 -0.230

Physical H. C. 12, Size of the house 0.166 1.825 0.170 1.970 0,113 1.298 0.126 1.259 Variables 13. Condition of the house 0.276 4.373* 0.235 2.639* 0.325 3.591* 0.333 3.314*

14. Housing type 0.139 2.193* NA NA NA NA NA NA 15. Household deficit -0.272 -4.103* 0.292 -3.279* -0.216 -2.389* 0.243 -2.418*

Constant R2, adjusted R2 0.189

2.028 0.178 0.177

2.774 0.162 0.204

1.932 0.190 0.224

1.773 0,206

Df.. F-ratio 3 & 226 17.512* 2& 112 12.015* 2 & 112 14.330* 2 & 86 12.395*

•Significant at p < .05, one-tailed test, NA = Not Applicable,

Propensity to adjust

The propensity to adjust variable was constructed using two variables.

The first variable was the propensity to change, alter, or add. The second

variable was the propensity to move. As shown in Table 21, the propensity to

adjust variable was first regressed on the variables of the combined model of

REDF and MPWH houses (Model One), and then it was regressed on the

variables in Model Two. The propensity to adjust variable was then regressed on

the variables in Model Three, and finally the propensity to adjust was regressed

on all variables of the REDF houses (Model Four). The overall F-value turned out

to be statistically significant in all four models at the level of p < 0.05 (F = 16.877,

9.119, 22.315, 16.963, respectively). The R2 for all four models amounted to

0.183, 0.075, 0.285, 0.283 respectively.

Condition of the house, household deficit, and housing satisfaction were

the three variables that had significant effects on propensity to adjust for Model

One. In Model Two, housing satisfaction appeared to have a significant negative

effect on propensity to adjust (t = -3.020). In Model Three, condition of the house

had a significant negative effect on propensity to adjust in addition to household

deficit (t = -2.709, 4.700 respectively). In Model Four, condition of the house and

household deficit were the only two variables that had significant effects on

propensity to adjust (t = -2.053, 4,472 respectively).

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Table 21

Regression analysis of propensity to adjust on the household variables, housing construction variables, previous

adjustment variables, physical housing characteristics variables, housing type, household deficit, and housing

satisfaction

Categories Variables

Model (3) MPWH & REDF Shared variables

Model (2) MPWH houses

Shared variables

Model (3) REDF houses

Shared variables

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value Beta t-value

1. Household size -0.013 -0.209 0.048 0.523 -0.012 -0.147 0.003 0.037 Household 2. Age of the head 0.014 0.229 -0.046 -0.510 0.049 0,603 0.088 0.932 Variables 3. Household income 0.011 -0.178 0.091 0.996 -0.102 -1.285 -0.081 -0.888

4. Education of the head 0.066 1.088 -0.010 -0.104 0.072 0.893 0.054 0.583

Housing Construction

Variables

5. Changes by owner NA NA NA NA NA NA 0.020 0.214 6. Changes by contractor NA NA NA NA NA NA -0.024 -0.251 7. Building regulations NA NA NA NA NA NA -0.068 -0.718 8. REDF regulations NA NA NA NA NA NA 0.012 0.131 9. Desianer NA NA NA NA NA NA -0.116 -1.244

Previous Adj. 10. Pre-moving adjustment 0.053 0.825 -0.054 0.585 0.075 0.905 0.073 0.759 Variables 11. Post-movina adjustment -0.006 -0.098 0.134 1.479 -0.099 -1.173 -0.100 -1.028

Physical H. C. 12. Size of the house -0.107 -1.671 -0.151 -1.627 -0.087 -1.044 -0.082 -0.847 Variables 13. Condition of the house -0.157 -2.385* -0.131 -1.384 -0.232 -2.709* -0.199 -2.053*

14. Housing type 0.042 0.650 NA NA NA NA NA NA 15. Household deficit 0.237 3.654* 0.092 0.949 0.403 4.700* 0.432 4.472*

16. Housing satisfaction -0.181 -2.744* -0.273 -3.020* -0.161 -1.812 -0.100 -0.969 Constant R , adjusted R 0.183

7.207 0.172 0.075

5.893 0.066 0.285

7.631 0.272 0.283

7.585 0.266

Df.. F-ratio 3 & 226 16.877 1 & 113 9.119* 2 & 112 22.315* 2 & 86 16.963*

•Significant at p < .05, one-tailed test. NA = Not Applicable.

Expected future improvement

The expected future improvement variable is the last variable of the

housing adjustment model. As shown in Table 22, expected future improvement

was first regressed on the variables of Model One, and then it was regressed on

the variables of Model Two. Expected future improvement was then regressed

on the variables of Model Three, and finally, it was regressed on the variables of

Model Four. The overall F-value turned out to be statistically significant in all four

models (F = 27.998, 9.801, 9.025, 10.598 respectively at the level of p < 0.05).

The R2 for all four models amounted to 0.198, 0.080, 0.074, 0.109 respectively.

Two variables in Model One appeared to have significant relationships

with expected future improvement. Those were the housing type (t = 7.234) and

the household deficit (t = -4.063). The household deficit was the only variable

that had a significant relationship with the expected future improvement in Model

Two (t = -3.131). In Model Three, the household deficit also had a significant

relationship with the expected future improvement (t = -3.004). In Model Four,

household deficit was the only variable that has a significant relationship with

expected future improvements (t = -3.256).

After reporting the findings of the regression analysis, the next section

examines the proposed hypotheses on the basis of the significant levels of the

predictors in all models.

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Table 22 Regression analysis of expected future improvement of housing situation on the household variables, housing construction variables, previous adjustment variables, physical housing characteristics variables, housing type, household deficit, housing satisfaction, and propensity to adjust

Categories Variables

Model (1) MPWH & REDF Shared variables

Model (2) MPWH houses

Shared variables

Model (3) REDF houses

Shared variables

Model (4) REDF houses All variables

Beta t-value Beta t-value Beta t-value

1. Household size -0.056 -0.884 0.050 0.513 -0.115 -1,268 -0.194 -1.936 Household 2. Age of the head -0.070 -1.074 -0.047 -0.519 -0.078 -0.865 -0.094 -0.923 Variables 3. Household income -0.072 -1.125 0.032 0.354 -0.120 -1.332 -0.179 -1.786

4. Education of the head -0.010 -0.164 0.072 0.782 -0.035 -0.379 -0.050 -0.488 5. Changes by owner NA NA NA NA NA NA -0,119 -1.179

Housing 6. Changes by contractor NA NA NA NA NA NA 0.130 1.267 Construction 7. Building regulations NA NA NA NA NA NA -0.050 -0.493

Variables 8. REDF regulations NA NA NA NA NA NA -0.138 -1.367 9. Desianer NA NA NA NA NA NA -0.034 -0.330

Previous Adj. 10. Pre-moving adjustment -0.095 -1.263 -0.147 -1.582 -0.059 -0.643 -0.036 -0.344 Variables 11. Post-movina adjustment -0.073 -1.123 -0.005 -0.051 -0.081 -0.877 -0.111 -1.080

Physical H. C. 12. Size of the house 0.057 0.627 0.135 1.490 0.003 0.033 -0.037 -0,343 Variables 13. Condition of the house 0.112 1.796 0.104 1.110 0.135 1.390 0.081 0.755

14. Housinq tvoe 0.452 7.234* NA NA NA NA NA NA 15. Household deficit -0.254 -4.063* -0.203 -3.131* -0.272 -3.004* -0.330 -3.256* 16. Housinq satisfaction 0.019 0.302 0.058 0.600 -0.004 0.038 -0.099 -0.916 17. Propensity to adjust -0.062 -0.984 -0.061 -0.660 -0.044 -0.419 -0.011 -0.096

Constant 2.663 4.188 3.196 3,136 R , adjusted R 0.198 0.191 0.080 0.072 0.074 0.066 0.109 0.098 Df.. F-ratio 2 & 227 27.998* 1 & 113 9.801* 1 & 113 9.025* 1 & 87 10.598*

‘ Significant at p < .05, one-tailed test. NA = Not Applicable.

Hypothesis Testing

The study proposed ten hypotheses centered around three themes. Null

hypothesis 1 targeted the first theme dealing with the differences between the

two types of houses. Null hypotheses 2 to 7 targeted the second theme dealing

with the determinant predictors of each type of house. Null hypotheses 8 to 10

looked closely at the third theme dealing with the sequential flow of the effect of

adjustment behavior variables on each other including household deficit,

satisfaction, propensity to adjust, and expected future improvement.

The following section reports the results of hypothesis testing along with

the analysis o f the relationship among the different variables. The testing of each

hypothesis was conducted based on the coefficient levels of the predictor

variables from Tables 17 to 22.

Null hypothesis 1. There is no significant difference in housing adjustment behavior between MPWH prototype houses and REDF loan assisted houses.

The housing type that was included in Model One as a predictor o f the

dependant variable of housing adjustment variables (see Tables 17 to 22) turned

out to have a significant relationship with the size of the house, housing

satisfaction, and expected future improvements variables. Housing type did not

seem to have any significant relationship with the condition of the house

variable, the household deficit variable, or the propensity to adjust variable.

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There was a significant negative relationship between the housing type

and the size of the house (t = -13.034). Thus the smaller the size of the house,

the more likely it is to be a MPWH house. A significant positive relationship was

found between the housing type and the housing satisfaction (t = 2.513). This

means that the MPWH households had higher satisfaction level than did the

REDF households. The expected future improvement variable had a significant

positive relationship with housing type variable (t = 7.234). Households who live

in MPWH houses are more likely to expect future improvement than households

living in REDF houses. These differences of household housing adjustment

behavior between REDF houses and MPWH houses led to the rejection of null

hypothesis 1.

Null hypothesis 2. The physical housing characteristics in each housing type are not significantly affected by any of the shared variables including the household variables, and the previous adjustment variables.

The physical characteristics of MPWH houses consisted of the size and

condition of the house which were represented by Model Two (see Tables 17

and 18). The size of the house was significantly affected by age of the head of

the household and by the post-moving adjustment. Age of the head of the

household had a positive significant relationship with the size of the house. The

older the head of the household, the larger the size of the house. The post-

moving adjustment had a positive relationship with the size of the house.

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In terms of the MPWH housing condition, the regression output of Model

Two in Table 18 shows that the household income had a positive effect on the

condition of the house. The condition of the house in this case could be a result

of the improvement and the changes that MPWH households had made to their

units after moving in. The higher their income, the more likely to have better

housing conditions.

As was the case in the MPWH houses, the physical REDF housing

characteristics consisted of the size and the condition of the house, which were

represented by Model Four (see Tables 17 and 18). The size of the house was

significantly affected by five out of 11 variables. These variables were the

household size, the household income, the education of the household head, the

household income, and the pre-moving adjustment. The household size had a

positive effect on the size of the house (t=2.593). The bigger the size of the

household, the higher the size of the house. The household income had a

positive effect on the size of the house (t = 3.130). The higher the household

income is, the more rooms the house has. The education of the household head

had a negative relationship with the size of the house (t = -2.802). The higher the

level of education of the household head, the smaller the size o f the house. The

pre-moving adjustment had a negative relationship with the size of the house (t =

-2.940). Households who engage in pre-moving adjustment are more likely to

have smaller houses. The post-moving adjustment had a positive relationship

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with the size o f the house (t = 2.375). Households who engage in post-moving

adjustment are more likely to have bigger houses.

As shown in Table 18, when it comes to the condition of the house

variable, the post-moving adjustment variable had a significant effect on the

condition of the house (t = -3.485). The higher the number of adjustments, the

lower the conditions of the house.

The hypothesis testing shows that the size and condition of the MPWH

houses (physical characteristics) were significantly affected by age of the

household, post-moving adjustment and the household income. In addition, the

size and condition of the REDF houses were significantly affected by education

of the household, the household income, the pre-moving adjustment, the post-

moving adjustment, hence the rejection of null hypothesis 2.

Null hypothesis 3. The housing deficit in each housing type is not significantly affected by any of the shared variables including the household variables, the previous adjustment variables, and the physical housing characteristics variables.

The variables affecting the housing deficit of the MPWH households were

represented by Model Two (see Table 19). Three out of eight variables had

significant relationships with household deficit. In the same way the condition of

the house had negatively affected the REDF household deficit at a significant

level, it had also a significant negative effect (t = -3.056) on the MPWH

household deficit. In addition, household size variable and pre-moving

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adjustment variable had significant relationships with the deficit o f the MPWH

household. The size of the household had a positive relationship with the

household deficit (t = 4.595). The higher the number of the household, the higher

the deficit level experienced by the household members. The pre-moving

adjustment had a significant positive relationship with the household deficit (t =

2.453). This finding means that the households who do more pre-moving

adjustment are more likely to experience higher deficit.

As shown in Model Three (see Table 19), the results of regression of the

household deficit on the household variables, the previous adjustment variables,

and the physical housing characteristics variables, revealed that the household

size in addition to the two physical housing characteristics (size and condition)

had significant effects on household deficit. The household size had a positive

effect on the household deficit (t= 2.423). The higher the number of the

household members, the higher their level o f deficit. The size of the house had a

significant negative effect on the household deficit (t = -3.661). The bigger the

size of the house, the lower the level of the household deficit. The condition of

the house also had a negative effect on the household deficit at a significant

level (t = -4.193). The better the condition of the house, the lower the level of the

household deficit and the poorer the condition of the house, the higher the deficit

experienced by the household.

The fact that three variables (Household size, pre-moving adjustment, and

condition of the house) had significant effects on the MPWH household deficit,

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and the fact that three variables (household size, size o f the house, and

condition of the house) had a significant effect on REDF household deficit, led to

the rejection of null hypothesis 3.

Null hypothesis 4. The housing satisfaction in each housing type is not significantly affected by any of the shared variables including the household variables, the housing construction variables, the previous adjustment variables, the physical housing characteristics variables, and the housing deficit variable.

The variables affecting the housing satisfaction o f the MPWH households

were represented by Model Two (see Table 20). The condition of the house and

the household deficit were the only two variables that had significant effects on

the housing satisfaction of the MPWH households. The condition o f the house

had a positive effect on housing satisfaction (t = 2.639). The better the condition

of the house, the higher the level of housing satisfaction. Moreover, the

household deficit had a negative effect on the housing satisfaction (t = -3.279).

The higher the level o f household deficit, the lower the degree of housing

satisfaction. The lower the household deficit, the higher the housing satisfaction.

The variables affecting the housing satisfaction of the REDF households

was represented by Model three (see Table 20). Similar to the housing

satisfaction of the MPWH household, the condition of the house and the

household deficit were the two variables that had a significant effect on the

housing satisfaction. The condition of the house had a positive effect on housing

satisfaction at a significant level (t = 3.591). The better the condition of the

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house, the higher the level of housing satisfaction. In addition, the household

deficit had a negative effect on the housing satisfaction (t = -2.389). The higher

the level o f household deficit, the lower the level o f housing satisfaction and the

lower the deficit, the higher the housing satisfaction.

Given the significant effects of the condition o f the house variable and the

household deficit on MPWH housing satisfaction, and in view of the fact that the

condition o f the house variable and the household deficit had significant effects

on REDF housing satisfaction, null hypothesis 4 was rejected.

Null hypothesis 5. The propensity to adjust in each housing type is not significantly affected by any of the shared variables including the household variables, the housing construction variables, the previous adjustment variables, the physical housing characteristics variables, the housing deficit, and the housing satisfaction variable.

The variables affecting the housing satisfaction of the MPWH households

was represented by Model Two (see Table 21). The housing satisfaction turned

out to be the only variable that had a negative effect on the propensity to adjust

at a significant level (t = -3.020). The lower the level of satisfaction, the higher

the propensity o f the household to adjust, and the higher the level of satisfaction,

the lower the propensity o f the household to adjust.

The variables affecting the propensity to adjust o f the REDF households

was represented by Model Three (see Table 21). The condition of the house

variable and the household deficit variable were the only two variables that had

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significant effects on the propensity to adjust The condition of the house had a

negative effect on the propensity to adjust at a significant level (t = -2.709). The

better the condition of the house, the less likely the household propensity to

adjust, and the poorer the condition of the house, the higher the propensity of the

household to make adjustment to their housing. The household deficit had a

positive significant effect on the propensity to adjust (t = 4.700). The higher the

level of the deficit, the higher the propensity of the household to make

adjustments to their housing.

The fact that the housing satisfaction variable had a significant effect on

the propensity to adjust in the case of the MPWH houses, and the fact that the

propensity to adjust was significantly affected by the condition of the house and

the household deficit in the case of the REDF houses, led to rejection of null

hypothesis 5.

Null hypothesis 6. The expected future improvement of the REDF houses is not significantly affected by any of the shared variables including the household variables, the housing construction variables, the previous adjustment variables, the physical housing characteristics variables, the housing deficit, the housing satisfaction, and the propensity to adjust variable.

The variables affecting the housing satisfaction of the MPWH households

was represented by Model Two (see Table 22). , One variable, the household

deficit in the MPWH houses turned out to have a negative effect on the expected

future improvement at a significant level (t = -3.131). This indicates that the

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higher the household deficit, the lower the expectation of future housing

improvement, and the lower the household deficit, the higher the expectation of

the future housing improvement.

The variables affecting the expected future improvement o f the REDF

households was represented by Model Three (see Table 22). Similar to the

finding about the MPWH household, the household deficit, turned out to be the

only variable that had a negative significant effect on the expected future

improvement at a significant level (t = -3.004). Again, this indicates that the

higher the deficit experienced by the household, the lower the household

expectations of future housing improvement.

Because of the significant relationship between the MPWH household

deficit and their expected future improvement, and given the significant effect of

REDF household deficit on the expected future improvement, null hypothesis 6

was rejected.

Null hypothesis 7. The housing construction variables in the REDF houses has no significant effect on the physical housing characteristics variables, the housing deficit, the housing satisfaction, the propensity to adjust variable, and the expected future improvement

A close look at Model Four in Tables 17-22, where the housing

construction variables were taken into account when running the regression

analysis, only one variable, namely the building regulation variable, had

significant effect on the condition of the house (t= 3.120). The stricter the building

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regulation, the better the condition o f the house. There was no significant effect

o f the housing construction variables on the size o f the house. Housing

construction variables also had no significant effect on the housing adjustment

variables, which include the housing deficit, the housing satisfaction, the

propensity to adjust, and the expected future improvement the housing. Because

of the significant relationship between one o f the housing construction variables,

namely the building regulation variable, and the condition of the house, null

hypothesis 7 was rejected.

Null hypothesis 8. The housing satisfaction in each housing type is not directly related to household deficit.

The variables affecting the housing satisfaction of the MPWH household

and REDF households was represented by Models Two, Three, and Four

respectively (see Table 20). In all three models, the housing satisfaction was

directly related to household deficit with negative significant relationship (t = -

3.279, -2.389, -2.418 respectively). This finding led to the rejection of the null

hypothesis 8.

Null hypothesis 9. The propensity to adjust in each housing type is not directly related to housing satisfaction.

The variables affecting the propensity to adjust o f the MPWH household

and REDF household was represented by Models Two, Three, and Four

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respectively (see Table 21). The propensity to adjust of the MPWH household

was directly related to housing satisfaction with negative significant relationship (t

= -3.020). The propensity to adjust however did not have direct relationship with

the housing satisfaction in the case of the REDF household in Model Three and

Four. Finding a significant relationship between the housing satisfaction and the

propensity to adjust in Model Two led to the rejection of null hypothesis 9.

Null hypothesis 10. The expected future improvement in each housing type is not directly related to housing satisfaction.

The variables affecting the expected future improvement o f the MPWH

household and REDF households was represented by Models Two, Three, and

Four (see Table 22). The expected future improvement of the MPWH o f Model

Two did not have direct relationships with the propensity to adjust (t = - 0.600).

Similarly, there was a lack o f significant relationship between the expected future

improvement of the REDF and the propensity to adjust in Models Three and Four

(t = - 0.044, t= - 0.011 respectively). Because none of the models yielded a

significant relationship between the housing satisfaction and expected future

improvement, null hypothesis 10 was not rejected.

Discussion of the Findings

The set of hypotheses that were tested in this study yielded some findings

about three themes. The first theme is the determination of the differences in

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housing adjustment behavior between MPWH prototype public houses and

REDF loan assisted houses. The second theme deals with the effects of each of

the independent variables, namely household variables, housing construction

variables, previous adjustment variables, physical housing characteristics

variables, housing deficit, housing satisfaction, and propensity to adjust variable,

on the dependant variables, namely physical housing characteristics variables,

and housing adjustment behavior variables in each housing type. The third

theme deals with the sequential direct effects of the deficit on satisfaction,

satisfaction on the propensity to adjust, and propensity to adjust on the expected

future improvement in each housing type.

First Theme

In terms of the first theme, which is represented by Hypothesis 1, the

MPWH households differ from the REDF households in their adjustment

behavior in two aspects: the satisfaction and the expected future improvement.

In addition to these differences, the two housing types differ in terms of the

house size (see Figure 11).

The MPWH households are more likely to exhibit a higher level of

satisfaction in their housing than do the REDF households (t = 2.193). One

reason for this relatively high level o f satisfaction might be that the MPWH

households had just moved into a new house whose price was below the market

value. This can be evidenced by the fact that some of the MPWH house

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A O

PREVIOUS ADJUSTMENT VARIABLES

HOUSEHOLD VARIABLES ! HOUSUNG ADJUSTMENT i BEHAVIOR VARIABLES2.503

4.687 -2.275 DEFICIT

-4.103-2.609 -5.401

2.040 2.193

3.700 7.234 2.105 3,654-2.744

-13.034 -2,162

r - PHYSICAL HOUSING \ CHARACTERISTICS

| VARIABLES

4.373 -4.063

-4.559 SIZE OF THE HOUSE

-2.385

HOUSING TYPEHOUSEHOLD INCOME

SATISFACTION DISSATISFACTION

HOUSEHOLD SIZE

AGE OF THE HEAD

EDUCTION OF THE HEAD

POST-MOVING ADJUSTMENT

CONDITION OF THE HOUSE

PRE-MOVING ADJUSTMENT

PROPENSITY TO ADJUST/ADAPT

EXPECTED FUTURE

IMPROVEMENT

Figure 11. The significant predictors and their coefficients of both REDF and MPWH houses with shared variables (Model 1).

recipients not included in the sample were able to sell their houses shortly after

they received them with a high profit. In contrast, REDF households who

exhibited a relatively lower degree of satisfaction had already built their houses

some years ago. These houses might not necessarily comply with the

households’ changing cultural and space norms.

The MPWH households also tend to have higher expectations of future

improvement in their housing than the REDF households (t = 7.234). The

relatively higher expectation o f future improvement of the MPWH household may

be explained by the fact that these households are planning to expand their

housing space by adding a second floor in the near future, as indicated in the

written responses of some questionnaire respondents.

Not surprisingly, the MPWH houses are more likely to be smaller in size

than the REDF houses (t = -13.034). The size of the MPWH houses (in terms of

bedrooms) ranges from two to five bedrooms while it starts from four up to eight

bedrooms or even more in the REDF houses. The MPWH houses were built as a

prototype with three bedrooms. However, some households probably converted

the guestroom to a bedroom or built an additional room on the roof. Still other

households reduced the number o f bedrooms to two and used the third bedroom

for other activities because o f the small household size. In contrast, the REDF

houses were built by households who had determined the number of bedrooms

by themselves.

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Second Theme

The second theme of the hypotheses in this study deals with the important

predictors affecting the physical housing characteristics (size and condition of the

house) as well as the housing adjustment behavior (deficit, satisfaction,

propensity to adjust, expected future improvement) in each housing type (MPWH

and REDF respectively).

In MPWH houses (see Figure 12), the findings indicate that the size of the

house is positively related to the age o f the household (t = 2.248). The older the

head of the household, the bigger the size of the house. Size of the household

turned out to have a negative significant relationship with the post-moving

adjustment (t = -2.159). It is important to note that the MPWH houses are ready-

to-move-in houses and most of them have been owned for just one or two years

prior to the beginning of the study.

Another finding about the MPWH houses indicates that the household’s

income has a positive effect on the condition of the house (t = 2.002). MPWH

households who received the MPWH houses had to improve the condition of

their houses as mentioned if; ihe written responses. Most of MPWH houses

needed internal or external work or both because they had been built for some

time and had not been inhabited. It is not surprising, therefore, that households

with higher incomes are more likely to improve the condition of their houses than

do households with lower income. The MPWH household deficit is mainly

affected by the size of the household (t = 4.595) where the bigger the household

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PREVIOUS ADJUSTMENT VARIABLES

POST-MOVING ADJUSTMENT

HOUSEHOLD VARIABLES HOUSUNG ADJUSTMENT BEHAVIOR VARIABLES2.453

•4.595 DEFICIT

-2.159 -3.131-3.279

2.248 -3.020

-3.056

2.002 PHYSICAL HOUSING

CHARACTERISTIC SVARIABLES 2.639

SATISFACTION DISSATISFACTION

AGE OF THE HEAD

EDUCTION OF THE HEAD

HOUSEHOLD SIZE

HOUSEHOLD INCOME

CONDITION OF THE HOUSE

SIZE OF THE HOUSE

PROPENSITY TO ADJUST/ADAPT

PRE-MOVING ADJUSTMENT

EXPECTED FUTURE

IMPROVEMENT

Figure 12. The significant predictors and their coefficients of the MPWH houses with shared variables (Model 2).

size, the higher the deficit. This finding is not surprising because the MPWH

prototype houses have three bedrooms and the average number of the

household size amounts to 5.99 persons. The MPWH household deficit is also

affected by the condition o f the house (t = 2.639) where the houses in poor

condition tend to increase the level of deficit. The MPWH household deficit is

affected by the pre-moving adjustment (t = 2.453). This finding indicates that

households who have done more pre-moving adjustment are more likely to

experience higher deficit. This result could be explained by the fact that

households who have done these adjustments are still eager to do more within

the houses. As indicated in their written responses, these households are waiting

for the municipality counsel to give them permission to add an additional floor.

As expected, MPWH housing satisfaction is affected by the household

deficit (t = -3.279) whereby the higher the level of deficit, the lower the level of

satisfaction. Satisfaction is also affected by the condition of the house (t = 2.639)

whereby good housing conditions lead to a higher level of satisfaction.

In REDF houses with shared variables (see Figure 13), as expected, the size of

the house is affected positively by the household income, where households with

higher incomes are more likely to have the ability to build houses with more

bedrooms. One of the housing norms of Saudi households is the tendency to

build the so-called “home of life,” which is typically a house with several rooms

some o f which might not be used or needed for the present time. These extra

rooms are used at a later time by household members when they grow up.

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Further reproduction prohibited

without perm ission.

PREVIOUS ADJUSTMENT VARIABLES

POST-MOVING ADJUSTMENT HOUSEHOLD VARIABLES

HOUSUNG ADJUSTMENT BEHAVIOR VARIABLES

PRE-MOVING ADJUSTMENTHOUSEHOLD SIZE

DEFICIT AGE OF THE HEAD

2.423 -2.389

2.375HOUSEHOLD INCOME 2.593

SATISFACTION DISSATISFACTIONEDUCTION OF THE HEAD

i 3.130 4.700

-2.940 PROPENSITY TO ADJUST/ADAPT

-2.802 -3.661

PHYSICAL HOUSING CHi iRACTERISTICS VARIABLES 3.591 -3.004

-4.193 SIZE OF THE HOUSE

EXPECTED FUTURE

IMPROVEMENT n

-2.709 CONDITION OF THE HOUSE

Figure 13. The significant predictors and their coefficients of the REDF houses with shared variables (Model 3).

The REDF original fund is supplemented by an additional amount of money to

build houses for the REDF household. Not surprisingly, the higher the income,

the bigger the size of the house.

The findings of the study indicate that education o f the household head

has a negative relationship with the size of the REDF houses. This means that

the higher the level of education, the smaller the size of the house. This finding

should be interpreted with some caution because of the nature o f the education

variable, which is explained later in the section dealing with the limitations of the

study. The pre-moving adjustment has a negative relationship with the size of the

house. Households who have done more changes in their homes are more likely

to have smaller houses, possibly suggesting that those households who have

built relatively small houses had the desire to adjust their housing by improving

the look of the interior and the exterior or by landscaping. It is important to keep

in mind that the adjustment is not limited to adding rooms. It involves making

internal, external or both alterations as well.

The post-moving adjustment turned out to have a negative significant

relationship with the condition of the house. Households who engaged in post-

moving adjustment are more likely to have poorer housing conditions. This

finding may suggest that the conditions of REDF houses still do not meet the

expectations of the households even after undergoing some adjustment. Other

REDF houses that are in a good condition, as deemed by the households, do not

undergo any post-moving adjustment.

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The REDF household deficit is affected negatively by the size and the

condition o f the house. Households who live in small houses experience higher

deficit than do households who live in bigger houses. Also, households who live

in houses in good condition experience lower deficit than do households who live

in houses in poorer condition.

The degree of satisfaction of the REDF households is positively affected

by the condition of the house (t = 3.314), suggesting that the better the condition

of the house, the higher the level of satisfaction. Household satisfaction is also

negatively affected by the household deficit, whereby the REDF household who

experience a high deficit are more likely to be dissatisfied with their housing.

The propensity to adjust is affected negatively by the condition of the

house (t = -2.053). REDF households who live in houses that are in good

condition are less likely to exhibit a propensity to make adjustments to their

houses. The propensity to adjust is also affected positively by the household

deficit, whereby the higher the deficit experienced by the households, the higher

the level of propensity to make adjustments to their houses.

The addition of housing construction variables (changes by owner,

changes by contractor, building regulations, REDF regulation, method of design)

to the REDF houses in Model Three yielded a new model, henceforth called

Model Four. In this model (see Figure 14), the housing construction variables

seem to show a slight difference in prediction of physical housing characteristics

variables and housing adjustment behavior variables. The household income,

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PREVIOUS ADJUSTMENT VARIABLES

POST-MOVING ADJUSTMENT HOUSEHOLD VARIABLES

HOUSUNG ADJUSTMENT BEHAVIOR VARIABLES

PRE-MOVING ADJUSTMENTHOUSEHOLD SIZE

DEFICIT AGE OF THE HEAD

-2.418-3.918 HOUSEHOLD INCOME

SATISFACTION DISSATISFACTIONEDUCTION OF THE HEAD

3.014 4.472

HOUSE CONSTRUCTION VARIABLES -2.188 PROPENSITY TO ADJUST/ADAPT

-2.356 -3.331OWNER CHANGES

PHYSICAL HOUSING CHARACTERISTICS VARIABLES 3.314 -3.256CONTRACTOR CHANGES

-3.112 SIZE OF THE HOUSE

BUILDING REGULATION EXPECTED FUTURE

IMPROVEMENT 3.120 -2.053

CONDITION OF THE HOUSELOAN REQUIREMENTS

DESIGNER

Figure 14. The significant predictors and their coefficients of the REDF houses with all variables (Model 4).

education of the head, and pre-moving adjustment continued to have a

significant relationship with the size of the house (t= 3.014, - 2.356, - 2.188

respectively). In terms of the condition of the house, it is significantly affected by

the post-moving adjustment (t = -3.918). In addition, the building regulations

turned out to have a positive effect on the condition of the house at a significant

level (t = 3.120). The stricter the building regulation, the better the condition of

the house. This might be explained by the enforcement of strict rules of the

municipalities and the fact that the owner has to obtain a release stating that the

house has been completed and complies with all municipality regulations. This

release is required so that the electrical company may connect the electricity.

In case o f the household deficit in Model Four of the REDF houses with all

variables, household size does not have a significant effect on the household

deficit as it did in Model Three of the REDF houses with shared variables.

However, size and condition of the house have a significant effect on the

household deficit as they did with REDF houses with shared variables (t = -

3.331, t = - 3.112 respectively).

As it turned out, the variables that have significant effect on housing

satisfaction, propensity to adjust, and expected future improvement in the case

of the REDF houses (Model 4) are the same variables that significantly affected

the REDF houses with shared variables (Model 3). These variables are the

condition of the house and the household deficit for housing satisfaction (t=

3.314, t= -2.418 respectively), the condition of the house and the household

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deficit for the propensity to adjust (t= -2.053, t= 4.472 respectively) and the

household deficit for the expected future improvement (t= - 3.256).

In brief, the addition o f the housing construction variables to the REDF

houses in Model 4 did not make any major improvement on determining the

predictors of REDF houses with shared variables (Model 3).

Third Theme

The third theme deals with the sequential direct effect of the deficit on

satisfaction, effect of satisfaction on the propensity to adjust, and effect of

propensity to adjust on the expected future improvement in each housing type

(see Figures 12,13, and 14). A direct negative effect o f deficit on the housing

satisfaction is found in the case of the MPWH houses (Model 2) as well as the

REDF houses (Model 3 and 4) (t = -3.279, -2.389, -2.418 respectively). The

hypothesized direct effect of housing satisfaction on the propensity to adjust is

supported only in the case of MPWH houses. In the case of the REDF houses,

the propensity to adjust is not directly affected by satisfaction; it is rather affected

directly by household deficit (t = 4.700, t = 4.472 respectively).

Contrary to what has been expected, the hypothesized direct effect of the

propensity to adjust on the expected future improvement is not supported in

MPWH houses as well as REDF houses. The direct effect comes instead from

the household deficit (t = -3.131, t = -3.004, t = -3.256 respectively).

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Chapter 5

Conclusions, Limitations, and Implications

The purpose of this chapter is to review the results of the analysis and to

interpret them to shed light on the housing adjustment behavior in Riyadh, Saudi

Arabia. The chapter has three sections: the conclusions drawn from the

research, the implication of the results, and the limitations of the study.

Conclusions

This study set out to identify the differences in housing adjustment

behavior of the two types of houses, namely REDF and MPWH houses in

Riyadh, Saudi Arabia. The study identified the predictors determining the

differences among the two housing types. The theoretical framework of this

study is the Morris and Winter model o f housing adjustment, explaining how

households behave towards their housing within their current residence. More

precisely, this study explored some o f the determinants of the housing

adjustment behavior of the two housing types.

Multiple regression analysis was used to explore the relationship among

the variables in the model. In addition to hypotheses testing, descriptive analysis

and correlation coefficients were examined. The descriptive analysis served to

describe the households’ variables, housing construction variables, previous

adjustment variables, housing characteristics variables, and housing adjustment

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variables. Correlation coefficients helped reveal the bivariate associations

between variables included in the models.

As mentioned earlier, the study proposed nine hypotheses centered

around three themes. To test these hypotheses, the proposed empirical model of

housing adjustment was recreated into four models where each model included

only the applicable variables for testing.

Using Moms and Winter model, previous studies conducted in the United

States and other parts of the world found that some of household variables have

strong relationship with housing adjustment behavior; household size has a

significant effect on housing satisfaction (Galster& Hesser, 1981; Gamer, 1983).

This study found that satisfaction in both types of houses is significantly affected

by the household size only through the household deficit. In addition, the age of

the household head does not seem to be a significant predictor of housing

adjustment. This study also supports Lee’s finding (1995) who concluded that

housing satisfaction in Korea is affected by size and condition of the house.

None of the previous studies in Saudi Arabia used the theory of housing

adjustment as a framework to study the housing satisfaction phenomenon. Nor

did previous studies investigate the differences between the two types of

houses. The present study, which used Mom's and Winter Model, found some

differences in housing adjustment between the REDF households and the

MPWH households. The MPWH houses are smaller in size compared to REDF

houses and both types of households have a high level o f satisfaction. However,

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the satisfaction levels o f the MPWH households as well as their expectation

about housing improvement are relatively higher than that of the REDF

households.

One study about MPWH houses in another Saudi city (Aldakheel, 1995)

found that the household variables did not have any significant relationship with

satisfaction. While the present study also did not find a significant relationship

between household variables and satisfaction, it did find that some of the

household variables contribute indirectly to housing satisfaction. The effect of

household variables on housing satisfaction occurs through its effect on the size

of the house that affects the deficit, which in turn directly effects housing

satisfaction.

Al-Saati (1987), who limited his study to the REDF houses, found that

the level of satisfaction is high in REDF houses. Likewise, the present study

found a high level o f satisfaction in the REDF households and the MPWH

households as well. Bahmmam (1992) found that REDF households had to

introduce some modifications because of cultural deficits. This study considered

the cultural and space deficits and found a significant level of deficit that drives

the households’ propensity to adjust in their housing.

With the exception of the building regulation variable, the study did find

that housing construction variables have a predictive power of housing

adjustment behavior in the REDF houses. The building regulation variable has a

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direct effect on the condition of the house, which in turn is found to have a direct

effect on the household deficit, housing satisfaction, and the propensity to adjust.

In brief, with the use o f housing adjustment theory, this study was able to

determine predictors in housing adjustment variables, some o f which were found

in previous studies that looked at housing satisfaction in Saudi Arabia. The

present study also accounts for other predictors that indirectly affect housing

satisfaction. This study also helps establish universal knowledge about housing

adjustment behavior by testing the applicability and the generalizability of a

housing theory that originated in the United States when applied to other

cultures.

Limitations of the Study

There are some limitations inherent in the nature of the study to which

attention should be drawn. The first limitation has to do with the generalizability

of the results of this study. The sample of the study was drawn from the City of

Riyadh, the political and financial capital of Saudi Arabia. This being the case,

the conclusions might not be applicable to other smaller cities. In addition, the

study did not account for the location and neighborhood preferences and its

impact on the overall household’s satisfaction.

The second limitation has to do with the distributing method of the

questionnaires and sample selection in the case of the REDF houses. A good

random sampling is not possible because of the absence of home mailing and

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the difficulties of knowing which houses were built with the assistance of the

REDF. A map with sections of the city o f Riyadh were presented to the design

students at the college of Architecture and Planning in Riyadh who were then

asked to select the section where they happened to know friends or relatives

whose houses were built by REDF loan. Each student was then handed a set of

questionnaires to be delivered to and collected from the assigned households.

Some bias may be present in the process of sampling and distribution of the

questionnaires due to the fact that these college students may have friends or

relatives who have higher education, higher income, etc.

The third limitation has to do with variability in task interpretation. Despite

an attempt to make the questions understood in one way only, household

members might have interpreted the questionnaire in different ways, hence the

possibility of different responses in a way that affects the findings of this study.

The fourth limitation is about the education of the household head and the

household income variables. These two variables may not perfectly serve as

good measurement tools when applied to the study of housing adjustment in

Saudi Arabia. The definition of education in this study is not a clear-cut definition

because it includes both formal and informal education. The level of education is

normally determined by the number of years of schooling, varying from

elementary, to high school, to college education. In the case of this study,

however, informal education was also included in the education variable. While

informal education, consisting of traditional Koranic schools, is deeply rooted in

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the tradition of the country, such education started to disappear with the

introduction of government public schools over the last several decades.

In addition, traditional education may vary from basic skills of reading and writing

to high levels of intellectual achievement, making it difficult to give a clear-cut

definition of the education variable in this study.

The income variable in this study does not necessarily reflect the financial

ability of the household as it is normally implied by other housing adjustment

studies. A high-income household has the same eligibility of obtaining a

government loan, as does a low-income household. That is because the REDF

program is supposed to grant the same amount of money to any household

applying for the loan as long as they have a source of income. Loans are paid

back in a minimal yearly payment. The income variable may have an effect on

budgeting for the construction the REDF houses where the households add

more money to the loan to build their houses, but it does not have a major role in

the case of the MPWH houses where the households receive ready-to-move-in

houses.

Implications

The phenomenon o f housing adjustment behavior in different parts of the

world has been observed and studied by many researchers who have tried to

come up with predictors. This study focussed on this phenomenon in the city of

Riyadh that has witnessed a revolution in housing construction since the 1970s,

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in an attempt to investigate housing adjustment behavior among the Riyadh

residents in both REDF and MPWH houses. In addition, this study tried to

identify the main predictors of this phenomenon.

The results of the study can have some implications for government

housing policy and design. City planners and housing policy makers need to

understand why households tend to make certain alterations in their houses.

They also need to be aware of changes in households and their housing

characteristics overtime, leading to further changes in housing demands that

may cause a household deficit to provide housing that meet households’ needs.

Housing rules and regulations need to allow households to engage in making the

desirable adjustment to lower their deficit at the cultural and space levels without

stifling restrictions that are normally enforced by local municipalities.

Accommodating household desires to engage in making adjustments to their

homes could increase the level of housing satisfaction.

Interior designers and architects can also make a positive contribution to

housing adjustment behavior by enlightening the household about potential

future modification and expansion or the possibility of changing the layout of the

design. Interior designers and architects can provide households with visionary

designs, thereby allowing for flexibility in potential future adjustment and helping

to reduce the cost of such adjustment.

The fact that there is an inevitable, ongoing housing adjustment behavior

can also have important implications for the suppliers of building materials. The

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rules of supply and demand of building material and its innovation will determine

and be determined by such ongoing adjustment behavior and the changing

housing norms.

The findings of this study have also shown that the household needs to be

actively involved in housing design to minimize the level of household deficit and

increase the level of housing satisfaction. This has been the case in the REDF

houses, which seem to undergo the least pre-moving adjustment because the

households were most involved in the design and the contraction process.

The result of this study has some implications in terms of further research

in the housing-related studies. By conducting more research on residential

adjustment behavior, the factors driving adjustment behavior could be identified.

In brief, it is hoped that the findings of this study will allow all the stakeholders

involved in housing adjustment behavior to make positive contributions to

housing design and development in Saudi Arabia.

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Appendixes

Appendix A: English Version of the Questionnaire

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King Saud University College of Architecture and Planning & University o f Minnesota Department o f Design, Housing, and Apparel

STUDY OF

HOUSING A DJUSTM EN T IN RIYADH, SAUDI ARABIA

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Dear Household:

You are invited to participate in a study of housing in the city of Riyadh. This

study is being conducted by King Saud University and the University of

Minnesota. You were selected as a possible participant through a scientific

procedure by the researcher. The purposes of this study is to better understand

housing adjustment behavior in Riyadh, Saudi Arabia.

If you agree to participate in this study, you will answer questions from a

prepared questionnaire. The questions do not involve any risk or discomfort to

you. I hope that you feel comfortable enough to tell us any additional information

you think is important. The benefits of participation for you would be the

knowledge that you helped toward a better understanding of housing in Riyadh.

No information that could identify your family will be included in any reports. The

results will be stored in such a way that your family cannot be identified. For the

purpose of the study, the answers of the questionnaires will be handled as

numbers only without any names.

Before you start answering , I would like to draw your attention to the following:

Some questions have a categorized answered, so when you choose the

appropriate answer, mark it with (S ) in front of the corresponding answer. Others

questions have open-ended answers where you need to write your answer or

opinion in a sentence or two.

If you have questions later, you may contact me (Mosaid Al-Sadhan, College of

Architecture and Planning, King Saud University. Telephone No. 231- 2338 ).

Now I would like you to start filling out the questionnaire...

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First Group:

This group of questions asks for some genera! information about your housing situation.

01. In what month and year did you move to this dwelling?

— month — year

02. In what month and year was this dwelling built?

— month — year

03. Which of the following best describes your dwelling ownership?

— 1 I rent this dwelling (Go to Q14) — 2 I live in this dwelling but I don’t own it (Go to Q14) — 3 I own this dwelling — 4 other (please specify)-------------------------------------- -----------------------

04. Which of the following best describes your method of owning this dwelling?

— 1 the unit was built by the Municipality of Public Works and Housing then you owned it through the Real Estate Development Fund (Go to Q14)

— 2 the unit was built by the Municipality of Public Works and Housing then you bought it from an owner (Go to Q14)

— 3 the unit was built by the Real Estate Development Fund then you bought it from an owner (Go to Q14)

— 4 cash funded from the Real Estate Development Fund

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05. Which of the following methods did you use for designing your dwelling?

— 1 pre-designed from the municipality — 2 architect — 3 free copy from friend and stamped from architect — 4 other (please specify) -------------------------------------

Second Group:

This group of questions deals with factors that have contributed to housing design and construction.

06. Have you done any changes to the design during the construction of this dwelling?

— no — yes

07. What did you change? (Please list the most important changes.)

08. Did the contractor make any changes to the original design during the construction?

— no — yes

09. What did he modify? (Please list the most important changes.)

10. During the design or the construction did you find the building regulation of the city constraining?

— no — yes

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11. If you remember them, what are the most important constraints?

12. Did you find the loan requirement of the Real Estate Development Fund constraining in regard to the design and the shape of the dwelling?

— no — yes

13. If you remember them, what are the three most important constraints?

14. Do you think that this dwelling meets your expectation regarding needs and norms of the following

14a. In terms of the dwelling design in relation to your neighbors: Q. Can your neighbor invade your privacy from their upper floor windows?

A. — no — yes

Q. What do you think about this situation?

A . ------------------------------------------------------------------------------------------------------

14b. In terms of using vour upper floor windows:

Q. Can female family members enjoy looking through the upper floor window without any discomfort?

A. — no — yes

Q. What do you think about this situation?

A. -----------------------------------------------------------------------------------------------

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14c. In terms of allocation of interior rooms and services in regard to providing visual privacy for the households and the quests:

Q. Can a male guest get in and out without causing discomfort to the females in the home?

A. — no — yes

Q. What do you think about this situation?

A. -----------------------------------------------------------------------------------------------

15. Do you think that this dwelling meets your expectations regarding your social activities for the following:

15a. In terms of spaces designed for receptions

Q. What is the approximate total square area of men’s reception room?

A. the approximate total square area = ------------- m2

Q. Do you think that this area fulfills your needs

A. ------- no ----- yes

Q. Please tell me why.

A . --------------------------------------------------------------------------------------------------

15b. In terms of spaces designated for dining

Q. In a group gathering, is there enough room for guests to have a group dinner?

A. ------- no yes

Q. Please tell me why. A . ----------------------------------------------------------------------------------------------------

172

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Third Group:

This group of questions deals with changes you may have made to your dwelling or are thinking about doing.

16. Have you made any changes after completion of construction and prior to moving into this dwelling?

— 0 no (Go to Q 18) — 1 yes

17. Which of the following have you done to your dwelling before moving in?

— 1 added one or more rooms — 2 raised the height of the surrounding fence — 3 major improvement to the exterior — 4 major improvement to the interior — 5 other (please specify) —--------------------------------------------------------------

18. Have you ever remodeled or added something onto your dwelling after moving in?

— 0 no (Go to Q20) — 1 yes

19. If the answer is yes, please fill in the following table and mark it with (S ) in front of the corresponding answer to all that apply. Then, write the number of years you spent in your dwelling until this change or improvement occured.

Type of change or improvement Time you spent in the house before you made the change

( ) added one or more rooms ( ) raised the height of the surrounding fence ( ) major repair to the exterior ( ) major improvement to the exterior ( ) major repair to the exterior ( ) major improvement to the interior ̂ ) UUICI oUUI X CIO

173

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20. Which of the following statements best describes your expectation about making changes, alterations, or additions to your present dwelling?

— 1 definite plans to make changes to this dwelling in the next year — 2 expect to make changes to this dwelling in the next year — 3 have thought about making changes to this dwelling — 4 have never thought about making changes (Go to Q22)

21. What are you thinking of doing to your home?

22. Which of the following statements best describes your expectations about moving from or staying in this dwelling?

— 1 have definite plans to move from this dwelling in the near future — 2 expect to move from this dwelling in the near future — 3 want to move from this dwelling in the near future — 4 have thought about moving from this dwelling — 5 have never thought about moving from this dwelling (Go to Q24)

23. Please tell me why.

24. What is the approximate size of your land in square meters (m2 )?

The approximate size of the land = — m2

174

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Fourth Group: This group of questions is about your attitudes toward housing.

25. Which o f the following best describes the condition of your dwelling?

— 1 very poor condition, not sound enough to rehabilitate — 2 poor condition, needs some major repairs — 3 adequate condition, needs many repairs but mostly minor ones — 4 good condition, needs some minor repairs — 5 excellent condition, no repairs needed

26. In general, how satisfied or dissatisfied are you with your current dwelling? — 1 very dissatisfied — 2 dissatisfied — 3 neither satisfied nor dissatisfied — 4 satisfied — 5 very satisfied

27. How many bedrooms in this dwelling do you have right now?

Number of bedrooms = ------ room

28. How many bedrooms do you feel your family needs right now?

Number of bedrooms = ----- room

29. Do you think that your household's housing situation has gotten worse, gotten better, or stayed about the same over the past five years?

— 1 gotten much worse — 2 gotten somewhat worse — 3 stayed the same — 4 gotten somewhat better — 5 gotten much better

30. Do you expect your household’s housing situation to get worse, get beter, or stayed about the same about the same in the next five years?

— 1 gotten much worse — 2 gotten somewhat worse — 3 stayed the same — 4 gotten somewhat better — 5 gotten much better

y 175

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31. Please fill out the following table about number of spaces based on the

original design of the dwelling and not based on the current family actual

use. Example: in terms of bedrooms, suppose you have one bedroom on

the ground flo o r, six bedrooms on the first floor, one bedroom on the roof,

and do not have any bedrooms in the annexes; then, the total number of

bedrooms is eight, and so on...

Number o f spaces in : Spaces Ground

floor First Floor

Annexes Rooftop

Annexes Basement Total

Bedroom Bathroom Women’s reception Men’s reception Dining room Living room Kitchen

Fifth Group:

Now I would like to ask you about the people who live in this dwelling and

some of their characteristics.

32. Are any of your parents living?

— 0 no — 1 both of them are alive. — 2 my father only — 3 my mother only

33. How satisfied are you with your relationship with your parents?

— 1 very dissatisfied — 2 dissatisfied — 3 neither satisfied nor dissatisfied — 4 satisfied — 5 very satisfied

176

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34. Are any of them living with you?

— 0 no — 1 your father stays here sometimes, he has his own room — 2 your father lives here all the time — 3 your mother stays here sometimes, she has her own room — 3 your mother lives here all the time — 4 both live here — 5 other

35. Do you have mam'ed children?

— 0 no — 1 yes

36. Do they live with you in the same dwelling?

— 0 no — 1 yes

37. Please tell me why.

38. In your opinion, who benefits most when parents and their married children live together?

— 1 more benefit for child's family — 2 more benefit for parents — 3 both equally

39. What is your household's total monthly income? Please include all sources of income for everyone who lives in this dwelling?

— 1 less than SR 4,000 — 2 from SR 4,000 to less than SR 8,000 — 3 from SR 8,000 to less than SR 12,000 — 4 from SR 12,000 to less than SR 20,000 — 5 from SR 20,000 to less than SR 25,000 — 6 more than SR 25,000

177

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40. Please list everyone who normally lives in this household. Please start with yourself, then your mother, father, wife, and then each of your children or other relatives who are living in this dwelling beginning with the oldest. If one or more o f your children are living elsewhere, please do not list them on this page.

N Sex Age Relation to respondent Marital status Education Employment

M or F

Mother-Father-Wife - Son-Daughter- Daughter in Law- Grand child-Other relatives- Driver-Maid

M= Married D= Divorced S= Separated W = Widowed N= Never

Current level of education completed

Full-time Part-time Unemp, not looking Unemp, looking Retired

1 Household head 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Dear Sir: If you or any family member have any additional information or suggestions for the questionnaire, please write them down on the next page. Thank you very much for your attention and time.

Mosaid Al-Sadhan , College of Architecture and Planning, King Saud University

178

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Appendix B: Arabic Version of the Questionnaire

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Appendix C: Abbreviation and Conversion Equivalents

General Abbreviations

Gregorian year. Anno Hijrah (arabic year) Example: 1975 Gregorian years is the equivalent year of 1395 in Hij'ra years. It is called and dated after the immigration (Hijra) of Prophet Mohammed from Mecca to Madina and many Islamic countries use it. Arabian American Oil Company General Housing Department Gallons per day. kilometer meter Ministry of Public Works and Housing Post Occupancy Evaluations Real Estate Development Fund Saudi Riyal (Saudi Currency) $ 1 = SR 3.75 Statistical Package for the Social Sciences

Statistical Abbreviations

F Frequency MS Mean square j f Pearson product-moment correlation squared R2 Multiple correlation squared, measure of strength of relationship SD Standard deviation SE Standard Error t Computed value o f t test

Standardized multiple regression coefficient

Conversion Equivalents

1 hectare (ha) = 2.471 acres and 0.01 square kilometers (km2) 1 kilometer (km) = 0.6214 miles 1 meter (m) = 3.28 feet (ft) 1 square Kilometer (km2) = 0.3861 square miles (mile2) 1 square meter (m2) = 10.764 square feet (ft2)

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AD AH

ARAMCO GHD GPD Km m MPWH POE REDF SR SPSS

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