An Analysis of Quality Attributes of Housing Environment in Guangzhou

China, Using Expert Judgments

Fan WuPhD Candidate

Dept. of Real Estate and Construction, the University of Hong Kong

Supervisor: Dr. L. H. Li

Introduction

Housing environment is not only about residential surroundings, but also presents the attitudes towards lifestyle.

With the rapid development of economy and higher expectation on quality of life, people devote themselves in pursuing high quality of housing environment.

The rapid progress of urbanization and suburbanization brings a large number of urban problems which might reduce living quality and housing environment of urban residents.

Housing environment

When buying a house, consumers purchase a variety of environmental attributes as well as services at a particular location, rather than a concrete box (Kain & Quigley 1970).

Three typical levels of housing communities in Guangzhou, China

Housing Environment

schools

services

neighbors

neighborhood environment

accessibility to employment

retails

clinics

sense of belonging

Research Background:

House quality(Association & Housing 1945; Fiadzo, Houston & Godwin 2001; Rindfuss et al. 2007)

Residential satisfaction(Adriaanse 2007; Fang 2006; Kellekci & Berkoz 2006)

Housing environmental quality (Ha & Weber 1994)

Attractiveness of residence (Kauko 2006; Linneman 1981)

Neighbourhood attachment(Hays & Alexandra 2007; Karien 2007; Li 2008)

Social capital (Kevin 2003; Kleinhans, Priemus & Engbersen 2007; Middleton, Murie & Groves 2005)

In the context of Guangzhou, China

Guangzhou is probably the earliest city to experience the onslaught of global market forces, largely because of its proximity to Hong Kong (Li & Li 2006).

The city area now covers 7,434 square kilometers with an official population of around 7.7 million (statistics in 2007).

Objective

This research try to find out the preference of housing environment for housing consumers and experts by analyzing three major issues related to housing, namely, mobility, community facilities, and community social capital.

Hypothesis

The housing environmental performances are influenced by the correlative issues, namely: mobility, community facilities, community social capital.

The preference of housing environment by housing consumers and industry experts are the same.

Research Methods:

Hedonic pricing model Geographic Information Systems (GIS) Analytic Hierarchy Process (AHP) Objective and subjective

Analytical Hierarchy Process

Multi-attribute modeling is a suitable method for evaluation of other than monetary values.

The AHP is a specific technique within this approach. Bender et al. 2000) (see for example (Chen 2006; Ho, CD 2000; Ho, D, Newell & Walker 2005).

AHP has been used extensively in research on built environment, house selection, and housing quality, see (Ball & Srinivasan 1994; Bender et al. 2000; Ho, D, Newell & Walker 2005; Kauko 2003, 2006; Schniederjans, Hoffman & Sirmans 1995).

Full mathematical details of the AHP methodology are given in Bender et al. (1999) and (Saaty 1994).

Table 1 The studied factors and sub-factors

Mobility Public traffic networkPrivate traffic networkProximity to urban centerProximity to workplace

Community Facilities

Education FacilityMedical and Health FacilityRetail ServiceSports FacilitiesGreen Space and View

Community Social Capital

Sense of safetySense of belongingNeighborlinessDensity

Table 2 Definition of the attributes

Public traffic network (PUT)

The public traffic network refers to the level of public transport system connected to the neighbourhood

Private traffic network (PIT)

The private traffic network means the level of private transport system of the neighbourhood, like the convenience of private car parking and close to expressway exits.

Proximity to urban center (PUC)

Proximity to urban center is the proximity to urban center where concentrates the commerce and service trade of a city.

Proximity to workplace (PTW)

Proximity to workplace refers to the proximity to employment for residents.

Education Facility (EDF)

A high level of education facility refers to high quality of kindergartens, primary schools, high schools and libraries near neighbourhood.

Medical and Health Facility (MHF)

A high level of medical and health facility relates to the quantity and quality of clinics and hospital near neighbourhood and the neighbourhood hygiene.

Retail Service (RES) The retail service degree relates to the presence of adequate number of shops, stores, markets, and supermarkets.

Sports Facility (SPF) Sports facility refers to the presence of arena and gymnasiums near the neighbourhood.

Green Space and View (GSV)

Green space and view refers to the closeness to garden, open areas, or lake and General unobstructed view to surroundings.

Sense of safety (SES) Sense of safety is the degree of safety residents feel. a low degree of victimization corresponds to a high degree of safety.

Sense of belonging (SEB)

Sense of belonging to the community indicates the degree to which residents identify themselves as part of the immediate larger housing community

Neighborliness (NBL) A friendly neighborliness means that residents are in good relation with their neighbors.

Density (DEN) Density refers to the satisfaction of residents to the density of the neighbourhood.

RESIDENCIAL ENVIRONMENT AND THE HOUING IN SUBURBAN CHINA

Community Facilities

Mobility

Community Social

Capital

Housing

ENVIRONMENT

Stage 1

Stage 2

Stage 3

METHOD

Literature

Review

Sub criterions AHP

(Export

Choice)

Questionnaire

Housing Environment

Satisfaction

Index of Importance of the

major housing issues

Relationship

CONCLUTION

SPSS

Relationship

Analysis

Figure 1 Conceptual framework of the study

Data Collection and Analysis

Questionnaire survey and interview are the main approaches for data collection.

30 questionnaires will be delivered to housing experts and 150 questionnaires will be delivered to housing consumers.

Questionnaire surveys will be conducted primarily at face-to-face basis.

Computer package ECproTM version 13 by Expert ChoiceTM Inc. will be used for weighting value manipulation.

Pilot Test

32 questionnaires were sent and answered.

27 of them are for housing consumers (HC) in Guangzhou, 5 of them are for experts (EP) in housing industry.

72% of the responders have consistency radio of 0.1 or less, which is considered very well.

Table 3 The weights of factors on the housing environment by consumers

Factors Weight

Distance to Workplace 0.1390

Public Traffic Network 0.1195

Distance to Urban Center 0.1029

Retail Service 0.0911

Medical and Health Facility 0.0868

Education Facility 0.0862

Sense of security 0.0784

Green Space and View 0.0716

Sports Facilities 0.0589

Privacy Traffic Network 0.0569

Sense of belonging 0.0432

Neighborliness 0.0361

Density 0.0299

Total 1.0000

Figure 2 The weights of factors on the housing environment by consumers

The weights of factors on the housing environment by consumers

0.0000 0.0200 0.0400 0.0600 0.0800 0.1000 0.1200 0.1400 0.1600

Distance to WorkplacePublic Traffic Network

Distance to Urban CenterRetail Service

Medical and Health FacilityEducation FacilitySense of security

Green Space and ViewSports Facilities

Privacy Traffic NetworkSense of belonging

NeighborlinessDensity

Table 4 The weights of factors on the housing environment by experts

Factors Weight

Distance to Urban Center 0.1240

Public Traffic Network 0.1228

Distance to Workplace 0.1204

Neighborliness 0.1074

Retail Service 0.0846

Green Space and View 0.0840

Sense of security 0.0814

Sense of belonging 0.0572

Education Facility 0.0546

Sports Facilities 0.0482

Privacy Traffic Network 0.0444

Medical and Health Facility 0.0392

Density 0.0318

Total 1.0000

Figure 3 The weights of factors on the housing environment by experts

The weights of factors on the housing environment by experts

0.0000 0.0200 0.0400 0.0600 0.0800 0.1000 0.1200 0.1400

Distance to Urban CenterPublic Traffic Network

Distance to WorkplaceNeighborlinessRetail Service

Green Space and ViewSense of security

Sense of belongingEducation Facility

Sports FacilitiesPrivacy Traffic Network

Medical and HealthDensity

Expected Outputs of the Research

Instead of measuring the monetary value of different attributes in the market, the findings of this proposal is hoped to understand the general demand pattern and preferences of consumers in the housing market based on multidimensional values and benefits.

It is hoped that the findings will offer more information for urban planners and housing developers from a social and cultural perspective.

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