Modern Economy, 2011, 2, 9-17
doi:10.4236/me.2011.21002 Published Online February 2011 (
Copyright © 2011 SciRes. ME
Housing Choice in an Affluent Shanghai – Decision
Process of Middle Class Shanghai Residents
Linghin Li
Department of Real Estate and Construction, University of Hong Kong, Hong Kong, China
Received August 29, 2010; revised September 10, 2010; accepted Se pt em ber 20, 2010
While most papers on housing choice concentrate on relatively disadvantaged groups in the society con-
strained by financial ability, this paper looks at the affluent population in Shanghai. In examining their own
perception of the relative importance of difference factors affecting such choice by way of an Analytical Hi-
erarchy Process, we are able to understand that currently, most affluent households still regard proximity to
the city centre as an important factor when making housing choice. More importantly, there seems to be a
marked difference in the ranking of these factors between the upper middle class and the average middle
class in this city. Our analysis shows that the upper middle class households place more importance on the
transportation network and neighbourhood infrastructure, while the average middle class have more concern
on the housing attributes.
Keywords: Housing Choice, Housing Market, Shanghai
1. Introduction
Housing market is a very unique market in the sense that
it can be simply defined as a market for a simple com-
modity, namely domestic housing unit, with a very wide
price range. In this way, it may not be entirely different
from other commodity markets such as motor cars or
clothing. On the other hand, it can be completely segre-
gated into very different segments in accordan ce with the
household’s socio-economic background (or collectively
known as affordability); tenure modes (purchase and
rental); physical design (such as multi-level apartments
and detached houses) and geographical sub-markets.
Housing choice therefore can be deciphered from very
different perspectives based on different research focus,
such as aging society [1]; housing choice and race [2] as
well as housing choice and senior citizens [3].
Housing choice attracts academic attention because
there is a certain social element attached to the study of
the market mechanism for this real asset. Housing in-
variably means shelter for most people, especially for the
lower working class in most societies. Housing also
represents a core element in human settlement. Owusu [4]
for example finds that new immigrants from Ghana to
Canada tend to choose sub-urban areas to settle down. In
addition, they tend to concentrate within certain nei-
ghbourhood and even residential apartments, due to
mainly affordability. Jones, et al. [5] examine the rela-
tionship between mobility and housing sub-markets in
Glasgow. They express doubts on standard hedonic
models in examining such situation and instead advocate
the use of case-study based migration analysis to under-
stand such relationship as well as the dynamics of local
housing market better.
Colom and Molés [6] look at housing choice (in terms
of tenure choice and size of dwelling) in Spain in the
decade before year 2000 and find that housing choice
changes in response to changes in social, economic and
demographic factors such as age, education and income
level. Based on Self-Congruity theory, Sirgy, et al. [7]
explain the personal factors that may be specific to dif-
ferent individuals such as experience, involvement and
time pressure often play an important role in housing
choice decision. Moreover, they also note that psycho-
logical factor such as occupant’s image affects home-
buyer’s evaluation process, which coupled with other
factors shape the final housing choice. Because of the
growing importance of the personal factors in the whole
housing choice literature, this paper intends to examine
further this aspect by investigating the “perception” of
major factors when middle class households in Shanghai,
China are contemplating intra-urban housing choice de-
L. H. LI
Copyright © 2011 SciRes. ME
1.1. Housing Choice in China
Over the last decades, substantial literature has been de-
voted to the analysis of residents’ mobility and housing
tenure. In the recent years, with the emergence of more
data and analytical tools, more structured analyses have
been carried out on the correlation between intra-urban
mobility and housing choice. In addition, China with its
immense economic growth and vast urban development
also attracts academic interests in exploring such issue in
this country. This is almost a natural progression in re-
search agenda as residents’ mobility is more or less posi-
tively correlated with the econo mic growth. Li and Siu’s
[8] study is one of the first few atte mpts to try this angle
by linking residential mobility in Chinese cities to the
way housing provision is structured under market transi-
tion. Li [9] finds that work unit and the housing bureau
act as the major determinant in relocating residents to
urban fringe. Moreover, he also finds that during the
housing reform period in China, whether the housing is
subsidized or not also influence significantly the direc-
tion of move.
Wu [10] examines intra-urban mobility in Shanghai
and Beijing and finds that mobility is not driven by the
need for tenure or amenity. Based on a regression analy-
sis, Wu concludes that job opportunities account for a
major reason for such mob ility incentive and institution al
barriers such as Hukou (or household qualifications) con-
tinue to pose as problems for most of the intra-urban
movers who do not possess skills or capital. In this re-
spect, Wu’s analysis pays relatively less emphasis on the
factor of mobility of those who do possess skills and
Zheng, et al. [11] find that in China, a majority of
households face three obstacles in making housing choice
decisions, namely blurred or incomplete property rights
leading to problems in reselling their own hous e; limited
access to housing finance and mortgage facilities; and
mis-match between the job-market and housing-market
locations. They therefore conclude that to remove hin-
drances, individual households and the government need
to target at these three prob lems, such as providing more
land for higher-density housing development. Liu, et al.
[12] examine the housing affordability issue in Beijing,
China and conclude that with the rapid economic devel-
opment, housing prices increase more substantially than
income level leading to an increasing gap of housing
affordability. Con sequently, either the government has to
provide financial assistance or rental sector remains a
major source of housing choice for the majority of
As mentioned above, this paper intends to investigate
the issue of intra-urban housing choice in Shanghai by
examining the perception of the elative importance of
different factors affecting housing choice decisions
among middle class households in this city. Middle class
households are being examined as this group possesses a
relatively better financial position to actually make a
“choice”. As such, this paper does not aim at examining
the problem of affordability but rather the issue of mak-
ing housing choice at will and how households who can
make a choice perceive the factors affecting this decision
making process. We assume that the target group in the
study has a larger degree of flexibility of choice and
hence they tend to look at a broader set of housing at-
tributes when making a housing choice. But we need to
emphasize that affordability remains an important ele-
ment for all levels of households as there are always
housing products beyond the reach of a certain social
group. This paper is therefore trying to fill the gap that
while most of the literature concentrates on affordability
in housing choice, we need to look at a wider spectrum
of factors in order to understand how these various fac-
tors are being weighed by households who are able to
make a choice-based decision that is not limited entirely
by affordability.
This paper also hopes to contribute to this discussion
of intra-urban mobility among different districts within a
major metropolitan in China, namely Shanghai. In limit-
ing the housing choice analysis within the same urban
city, it helps to understand the more realistic housing
choice factors facing most households. By focusing on
the same urban city boundary, respondents in the analy-
sis can actually relate to the issues more easily and hence
provide a better-informed input into the dataset as these
households will not need to hypothesize the conse-
quences of finding a new job and school; losing family
and social ties; as well as cultural and climatic differ-
ences when considering housing choice in other parts of
the country. Since this paper aims at analysing the “per-
ception” of the relative importance of various factors, the
thought process of conjuring up these “perceptions”
needs to be realistic enough.
Shanghai as the growth engine in the current Chinese
economy has received substantial attention in the aca-
demic world, especially in relation to its urban and
housing development [13-15]. Within the current urban
districts in Shanghai, Pudong New Area is the largest in
terms of land area. While Huangpu is the traditional
CBD of Shanghai, other urban districts also become
more and more popular due to the active effort of various
district governments in the decentralisation process of
urban development [16]. As such, new residential pro-
jects with high standard of development details are evi-
L. H. LI
Copyright © 2011 SciRes. ME
dent everywhere to attract local residents and buyers
from other cities.
Table 1 shows the intra-district (urban districts only)
mobility of households with registered Hukou in Shang-
hai in 2007. All urban districts had witnessed net in-
crease of registered households in 2007, with Xuhui,
Yangpu, Putuo and Zhabei districts having the largest net
increase (except for Pudong New District, given the rela-
tive large size in terms of land area). Although this rela-
tive mobility of households signifies movement of
households among these urban districts, given that all
urban districts experienced net increase, this indicates a
net suburb-to-urban migration in Shanghai (see Figure 1
for the relative location s of urban and sub-urban districts
in Shanghai). Since Table 1 indicates mobility of resi-
dents with registered Hukou only, it is not impossible, if
supported with verifiab le d ata, to expect a mo re in tens ive
movement among households if we take into account of
other population not within the Hukou system. In this
respect, we regard the study of housing choice in Shang-
hai a significant step in understanding the relative im-
portance of the factors.
1.2. The Analysis
As evident above, most of the studies examining the re-
lationship between urban mobility and housing choice
rely on regression models. While statistical models allow
a much more objective and scientific way of analysing
the problems, they all depend on the nature of data and
they do not reflect the decision making process of the
urban residents.
This paper on the other hand, relies mainly on the
Analytic Hierarchy Process (AHP) to help the research
team understand better the decision making process of
housing choice made by the interviewees in the sample
groups. Interviewees are selected from two income groups
in Shanghai, namely those with monthly income between
10,000 to 30,000 RMB and those with monthly income
above 30,000 RMB1. According to the Shanghai Statis-
tical Yearbook 2009, average monthly salary in the
whole city by the end of 2008 was about RMB 3,290.
But that was an averag e figure only with the highest pay
scale at a level close to RMB 10,500 and on the other
side of the scale, the lowest level was aro und RMB 1,400 .
Taking into account of other subsidiary incomes which
are common in the labour market in Main land China, we
therefore set the monthly income range of average mid-
dle class at RMB 10,000-RMB30,000; and upper middle
class at the level above this. Middle class households are
selected as target group because the wealthiest group
does not normally need to consider a large set of factors
when making a housing choice among different districts
within an urban city as they will normally gravitate to-
wards the most expensive district, while the very poor
cannot make such choice at all due to the obvious reason
of affordability. For the middle class households, given
the growing economy, they are the most flexible and
mobile group who can find job opportunities in most
districts and are flexible enough to take either public or
private transportation to work.
Source: ts_gif.gif
Figure 1. Map of urban districts in Shanghai.
Table 1. Relative intra-district mobility of residents in 2007 in Shanghai.
Size (
(in 10,000 persons) Inflow of new households
from other districts Outflow of households to
other districts
Pudong New Area 532.75 305.36 686 294
Huangpu 12.41 52.19 88 78
Luwan 8.05 26.8 33 17
Xuhui 54.76 96.59 248 99
Changning 38.3 65.02 78 51
Jingan 7.62 25.21 32 18
Putuo 54.83 113.4 245 142
Zhabei 29.26 74.39 303 133
Hongkou 23.48 78.17 327 151
Yangpu 60.73 117.51 506 326
Sources: Statistical Yearb ook of Shan ghai 2008, Shanghai : Shanghai Statistical Bureau
1At the time of writing, 1 US$ is about 6.7 RMB
L. H. LI
Copyright © 2011 SciRes. ME
AHP can be characterized as a multi-criteria decision
technique in which qualitative factors are of prime of
importance. A model of the problem is developed using a
hierarchical representation. At the top of the hierarchy is
the overall goal or prime objective one is seeking to ful-
fill. In this project, it is the housing choice among dif-
ferent urban districts in Shanghai. The succeeding lower
levels then represent the progressive decomposition of
the problem. The knowledgeable parties complete a pair-
wise comparison of all entries in each level relative to
each of the entries in the next higher level of the hierar-
chy. The composition of these judgments fixes the rela-
tive priority of the entities at the lowest level relative to
achieving the top-most objective.
AHP has been adopted widely in the an alysis of situa-
tions in which decision-makers face different choices
with a set of interrelated attributes. Housing choice
therefore falls into this category of situation naturally.
Ball and Srinivasan [17] present a model of housing se-
lection process using the AHP, which allows buyers to
consistently evaluate property attributes. Schniederjans
et al. [18] also present a Goal Programming model that
utilizes the AHP to evalu ate property attributes and make
an optimal house selection decision.
The AHP addresses complex problems on their own
terms of interaction. It allows people to lay out a problem
as they see it in its complexity and to refine its definition
and structure through iteration. To identify critical prob-
lems, to define their structure, and to locate and resolve
conflicts, the AHP calls for information and judgments
from several participants in the process. Through a
mathematical sequence it synthesizes their judgments
into an overall estimate of the relative priorities of alter-
native courses of action. The priorities yielded by the
AHP are the basic units used in all types of analysis; for
example, they can serve as guidelines for allocating re-
sources or as probabilities in making predictions.
AHP enables decision makers to represent the simul-
taneous interaction of many factors in complex, unstruc-
tured situations. It helps them to identify and set priori-
ties on the basis of their objectives and their knowledge
and experience of each problem. Normally, consumers’
feelings and intuitive judgments are probably more rep-
resentative of their thinking and behavior than are their
verbalizations of them.
AHP determines the priority any alternative has rela-
tive to the overall problem of the issue. The analyst/user
creates a model of the problem by developing a hierar-
chical decomposition representation. At the top of the
hierarchy is the overall goal or prime objective one is
seeking to fulfill. The succeeding lower levels then rep-
resent the progressive decomposition of the problem.
The analyst completes a pair-wise comparison of all the
elements in each level relative to each of the program
elements in the next higher level of the hierarchy. The
composition of these elements fixes the relative priority
of elements in the lowest level (usually solution alterna-
tives) relative to achieving the top-most objective.
The following four steps are used to solve a problem
with the AHP methodology:
Build a decision “hierarchy” by breaking the gen-
eral problem into individual criteria.
Gather relational data for the decision criteria and
alternatives and encode using the AHP relational scale.
Estimate the relative priorities (weights) of the de-
cision criteria and alternatives.
Perform a composition of priorities for the criteria
which gives the rank of the alternatives (usually lowest
level of hierarchy) relative to the top-most objective.
2. Data
In the summer of 2009, we carried out questionnaire
surveys with 30 identified middle class respondents, all
of them work in the service industry or professional
fields. 14 of them have a monthly income above 30,000
RMB (the Upper Middle Class Group) and 16 of them
have a monthly income of 10,000 to 30,000 RMB (the
Middle Class Group). The size of the sample looks small
but given the nature of the questionnaire, almost each
respondent was interviewed individually with a detailed
explanation of pair-wise comparison given to them pre-
ceding the filling in of the questionnaire.
Pair-wise comparison is the cornerstone of the AHP
philosophy and allows the user to systematically deter-
mine the intensities of interrelationships of a great num-
ber of decision factors. Respondents are asked to indicate
their preference of these factors and categories, which
means they need to indicate which one of the two cate-
gories or factors is more important than the other, and
then indicate the extent of the difference in importance.
When making the pair-wise comparison, the respondent
has to first choose which attribute is more important or
has greater influence in the hierarchy. Secondly, the re-
spondent decides the intensity of that importance. The
intensity assessment is translated to a given scale. In this
research, a five-point scale is used. The adapted scale is
shown in Table 2.
Table 2. Scale of preference on built environment attributes
used in this survey.
Degree of Importance Definition
1 Equal Importance
2 Slightly more importance
3 Moderate importance
4 Strong importance
5 Absolute importance
L. H. LI
Copyright © 2011 SciRes. ME
2.1. Housing Choice Factors
In this paper, we build the hierarchy of factors on previ-
ous studies related to housing choice factors. Li [19]
examines the level of Shanghai residential satisfaction,
and devises a ten-factor scale including: dwelling size;
interior design ; public utilities; broadband network ; light-
ing and ventilation; hygiene and maintenance of public
space; building quality; privacy; noise; fire and other
safety facilities. He concludes that “Shanghai people are
usually pragmatic in their assessment of residential sat-
isfaction”. In addition, he also finds that location of resi-
dence is regarded as a major consideration of residential
satisfaction, since location affects commuting cost.
Li [20] conducts a research on the factors of Hong
Kong residents’ attachment to their own housing com-
munity by using AHP approach and multiple regression
models. The study indicates that there are connections
between housing choice and community attachment.
Apart from financial considerations, two major variables
are found to influence the residents’ attachment to their
community, namely the degree of safety of the commu-
nity and the sense of belonging.
Lawis and Salem [21] show that perceptions of envi-
ronemental problems usually increase the concern of
local residents, consequently raise the likelihood of a fear
of crime, the paper argues that the level of social inter-
greation normally associates with the fear of crime.
Therefore residents tend to gravitate towards communi-
ties with high level of social integration. This echos with
the study by Baba and Austin [22].
Based on the above, factors in the first level of the hi-
erarchy are grouped into four major categories, namely
transportation network; neighbourhood infrastructure;
community environment and housing attributes. Under
each category, sub-attribute factors are designated so that
a matrix of factors is developed for comparison. In terms
of transportation network, these sub-attribute factors in-
clude availability and access to public transportation;
ease of private transportation such as road network;
proximity to CBD, namely the Bund Area and Lujiazhui
finance district; and proximity to work location.
In the neighbourhood infrastructure category, these
factors include availability of desirable schools; hospi-
tal/health care facilities; retail shops/shopping centres;
and other leisure facilities as well as landscaped areas.
Under community environment, respondents are asked to
compare sub attributes as the sense of security; sense of
belonging; relationship with their neighbours as well as
neighbourhood development density. Finally, for the
housing attributes, factors include housing type, size,
number of bedrooms and po tential for value appreciation
are compared. This is explained in Figure 2 below. With
these two levels of hierarchy, respondents are asked to
fill in a questionnaire and the results are to be explained
in the following section.
2.2. The Analysis
After collecting the factor weights from all respondents,
the consistency ratio (CR) is then computed. Inconsis-
tency indicates the variability of human perception.
Generally, if CR is less than 0.1, the result is acceptable
(Saaty, 1994). The lower the CR is, the better the results.
The inconsistency of pair-wise comparisons, as an-
other important quantity in an AHP application, is meas-
ured by the consistency ratio (CR). CR is a tool for con-
trolling the consistency of pair-wise comparison. One of
Intra-city Housing Choice in Shanghai
T ransportation
-Public transportation
-Private transportation
-Proximity to CB D
-Proximity to work
-Educat i on facilities
-Health care/clinics
-Retail facilities
-Sports facilities
-Sense of security
-Sens e of belonging
-neighbour relationship
-neighbo urho od density
Housing Attributes
-Housi ng t ypes
-No. of rooms
-Va lu e appreciation
Figure 2. Hierarchy of factors.
L. H. LI
Copyright © 2011 SciRes. ME
the advantages of AHP is its ability to allow subjective
judgment, and with intuition playin g an important role in
the selection of the best alternative, absolute consistency
in the pair-wise comparison procedure should not be
expected. The acceptable CR only means the decision is
logically sound and not a random prioritization.
In this research, we calculate the CR on the aggregate
level by analysing the geometric mean. Geometric mean
is calculated to analyze the group aggregated preferences
of the perceptions. In this case, the CR is accessed ac-
cording to the two target in come groups and the two lev -
els of hierarchy of attributes. The results are shown in
Table 3 below:
The figures show an acceptable level of consistency in
the answers. We then examine th e relative importance of
each factor. In the first level of the hierarchy, the relative
importance of the four categories is shown below:
It shows that both groups place higher importance on
the two categories, namely Transportation Network and
Housing Attributes, although the Upper Middle Class
group has a more evenly-distributed spread of relative
importance among the four categories. Nevertheless, it
does not imply that these two groups do not differentiate
among these four categories of factors. When examining
Table 4 below, it is obvious that the Upper Middle Class
group are more concerned with Transportation Network
and Neighbourhood Infrastructure while the Middle Class
group are more inclined to look at Housing Attributes.
Of the top ten most important factors out of the total of
18, the Upper Middle Class group only placed two fac-
tors from the Housing Attributes category while the
Middle Class group had all the sub-attribute factors in
this category.
When we move down to the sub-att ri but es, we discover
a larger degree of differential in terms of the relative
importance of the more specific factors placed by these
two income groups. This is shown in Table 5 belo w.
Table 3. Consistency ratios of various factors.
First Level 4 cate gories Sub-attribute 18 factors
Upper Middle Class0.051 0.024
Middle Class 0.023 0.021
Table 4. Geometric means of factors between the two target
Upper Middle Class
(Geometric Mean
factor weight)
Middle Class
(Geometric Mean
factor weight)
Transportation Network0.299 0.305
Infrastructure 0.247 0.16
Environment 0.209 0.176
Housing Attributes 0.246 0.36
Consistency ratio 0.051 0.023
Table 5. Comparison of factor weights between the two target groups.
Rank Upper Middle Class
(Geometric Mean factor weight) Middle Class
(Geometric Mean factor weight)
1 Value appreciation (0.11) Value appreciation (0.104)
2 Proximity to work (0.097) Public Transportation (0.1)
3 Sense of security (0.094) Sense of security (0.076)
4 Proximity to CBD (0.091) Proximity to CBD (0.073)
5 Retail facilities (0.076) Housing size (0.073)
6 Public Transportation (0.073) House age (0.07)
7 Neighbourhood view/landscape (0.058) Private transportation (0.066)
8 Housing size (0.055) Proximity to work (0.066)
9 Neighbourhood density (0.048) Housing Type (0.062)
10 Availability of health care/clinic (0.045) Number of rooms (0.051)
11 Availability of sports facilities (0.041) Retail facilities (0.047)
12 Private transpo rtation (0.037) Availability of health care/clinic (0.041)
13 Neighbourhood relationshi p (0.035) Sense of Belonging (0.037)
14 Sense of Belonging (0.032) Neighbourhood density (0.036)
15 Number of r ooms (0.029) Neighbourhood relationship (0.027)
16 Housing Typ e (0.028) Availability of sports facilities (0.024)
17 Education facilitie s (0.027) Education facilities (0.024)
18 House age (0.024) Neighbourhood view/landscape (0.024)
L. H. LI
Copyright © 2011 SciRes. ME
As expected, housing choice is a very specific and
personal decision to be made by all families, to the extent
that it can even be idiosyncratic. Therefore, we do not
find any significant differences between the two target
groups in terms of the broadly-defined “categories” of
attributes. Statistically, most people will therefore not be
able to provide a logical explanation of their perception
of the relative importance of these broadly-defined terms.
It is only when these categories are further sub-divided
into more specific factors are respond ents able to config-
ure more meaningful choice. In this stage, differences
between the two income groups in the overall affluent
population become more conspicuous and significant.
Having said that, we find that all middle class (probably
all other) households are majorly and equally concerned
with capital appreciation prospect of their housing choice.
This is understandable as capital appreciation prospect of
housing is basically the aggregate effect of all other fac-
tors affecting popularity of housing units.
For other factors, differences in housing choice per-
ception between the two target groups begin to show.
First of all, the second most influential factor the Upper
Middle Class have considered is “Proximity to work”
while the Middle Class Group ranked “Public Transpor-
tation” as the second factor. While the two factors weight
more or less the same in each group, the implication is
that Upper Middle Class group would more likely be
clustering around commercial districts while the Middle
Class Group would have a much wider choice of housing
location along the very extensive underground network
as well as the ring road system in Shanghai. This is also
reflected in Rank number 4 of both groups. While both
groups placed “Proximity to CBD” as number four factor,
the factor weights differ by more than 20%. Similarly,
the two target groups both ranked the factor “sense of
security” as number three on the list, but the degree of
importance in Upper Middle Class apparently outweighed
Middle Class again by more than 20%.
Further more, we also notice that the factor of the
availability of retail facilities was given a much higher
weighting by the Upper Middle Class group than the
Middle Class Group. This represents cultural differences
between these two groups. It is apparent that higher in-
come households place higher importance on shopping
experience in their daily life because of higher afforda-
bility and relatively more luxurious lifestyle. Such im-
portance also echoes with their need to be near to the
CBD where most high-end retail facilities will b e found.
On the other hand, while we will expect car ownership
ratio is relatively higher among Upper Middle Class
households within the affluent population, they did not
place the factor of Private Transportation in a higher rank.
In fact, judging from the factor weight, the importance of
this factor to the Middle Class outweighs that of the Up-
per Middle Class by more than eighty percent. One pos-
sible explanation is the relative higher degree of impor-
tance of the factor “proximity to CBD” to this group
such that relative travelling time to workplace and other
activities is not a major concern to them. On the other
hand, given the more dispersed pattern of housing choice
manifested by the Middle Class group, travelling time is
a core factor in their daily activities and hence both pub-
lic and private transportation networks are important.
A further observation is noted from the two sub-at-
tribute factors, namely Neighbourhood View/Landscape
and Neighbourhood Density. These two factors ranked
7th and 9th respectively in the Upper Middle Class’ per-
ception, while they only ranked 14th and the last one
among the Middle Class group. This significant differ-
ence represents the importance of “neighbourhood” to
higher income households as a representation of their
socio-economic status. To this group, their perception of
a good housing choice goes beyo nd the ph ysical qu alities
of the housing itself into the community environment
that they can enjoy. Similar to their western counter-part,
they would seek neighbourhood with better landscape
planning and lower density. However, one may find a
certain contradiction here as no ticed from above that this
group of households also prefer city centre than the pe-
3. Conclusions
Housing choice is normally associated with the degree of
affordability. Most of the studies on housing choice
therefore examine how certain groups in the society
make that choice under financial constraints. When a
target group in the society is not entirely constrained by
affordability, their perception of the relative importance
of a wide range of factors represents a more thorough
analysis of the “choice” issue. In this paper, we examine
the “perception” of the relative importance of 18 factors
under 4 categories of attributes in housing choice deci-
sion from the perspective of the relatively affluent
households in Shanghai. We target at this middle class
population as they are the group who would consider
both affordability and other environmental attributes
with more or less equal importance in making housing
We find that the relatively affluent households in
Shanghai are still clus tering around the urban centre as a
housing location close to the CBD and their workplace is
more important than the other factors. This reflects the
current of traffic congestion problem in the city centre
that leads to the affluent class’ unwillingness to move to
sub-urban districts, just like their western counter-parts.
L. H. LI
Copyright © 2011 SciRes. ME
On the other hand, to this group of population, social
identity and aesthetic factor of the neighbourhood are
also important so that it is not unforeseeable that with
improved road system and other infrastructure networks,
an outward migration to lower density communities with
better landscape features will be witnessed, especially
towards the Pudong New District. But that will not hap-
pen shortly.
On the other hand, the ordinary middle class in
Shanghai exhibits a higher degree of flexibility in terms
of housing choice. Their reliance on public tran spor tation ,
especially the underground railway system, allows them
to have a wider choice in most districts, given the highly-
development underground railway system in the city. It
is therefore expected that more and more new communi-
ties or redevelopment projects will be resulted along the
different stations on the underground railway system that
target at this income group, where new housing units
with larger flats can be found.
Given that this affluent population (in general) actu-
ally has the financial and economic ability to move
within the different urban districts in Shanghai, we find
that middle class households in this city still regard
proximity to the CBD and transportation network as im-
portant consideration when making a housing choice.
The differences in the two income groups within this
middle class population represent more on their focus of
daily necessity to commute t o work and shop rather th an
their difference in financial ability in affording a decent
house. The results of this paper have important implica-
tion on the future urbanisation process as well as housing
market development in Shanghai.
4. References
[1] W. A. V. Clark and A. M. C. Deurloo, “Aging in Place
and Housing Over-Consumption,” Journal of Housing
and the Built Environment, Dordrecht, September 2006,
Vol. 21, No. 3, pp. 315-335.
[2] N. Denton, “The Geography of Opportunity: Race and
Housing Choice in Metropolitan America,” Contempo-
rary Sociology, Vol. 36, No. 2, March 2007, pp. 135-136.
[3] K. E. Lahey, M. L. Newman and D. Kim, “Housing
Choices and Mortgage Financing Options for Seniors,”
Journal of Real Estate Portfolio Management, May-
ugust 2006, Vol. 12, No. 2, pp. 103-119.
[4] T.Y. Owusu, “Residential Patterns and Housing Choices
of Ghanaian Immigrants in Toronto, Canada,” Housing
Studies, Vol. 14, No. 1, 1999, p. 77-98.
[5] C. Jones, C. Leishman and C. Watkins, “Intra-Urban
Migration and Housing Submarkets: Theory and Evi-
dence,” Housing Studies, Vol. 19, No. 2, 2004, pp. 269-
283. doi:10.1080/0267303032000168630
[6] M. Consuelo Colom and M. Cruz Molés, “Comparative
Analysis of the Social, Demographic and Economic Fac-
tors that Influenced Housing Choices in Spain in 1990
and 2000,” Urban Studies, Vol. 45, No. 4, 2008, pp.
917-941. doi:10.1177/0042098007088474
[7] M. J. Sirgy, S. Grzeskowiak and C. Su, “Explaining
Housing Preference and Choice: The Role of Self-Con-
gruity and Functional Congruity,” Journal of Housing
and the Built Environment, Vol. 20, No. 4, 2005, pp. 329-
347. doi:10.1007/s10901-005-9020-7
[8] S. M. Li and Y. M. Siu, “Residential Mobility and Urban
Restructuring under Market Transition: Study of Guang-
zhou, China,” Professional Geographer, May 2001, Vol.
53, No. 2, pp. 219-229. doi:10.1111/0033-0124.00281
[9] S. Li, “Housing Tenure and Residential Mobility in Ur-
ban China: A Study of Commodity Housing Develop-
ment in Beijing and Guangzhou,” Urban Affairs Review,
Vol. 38, No. 4, 2003, pp. 510-534.
[10] W. P. Wu, “Migrant Intra-Urban Residential Mobility in
Urban China,” Housing Studies, Vol. 21, No. 5, 2006, pp.
745-765. doi:10.1080/02673030600807506
[11] S. Q. Zheng, Y. M. Fu and H. Y. Liu, “Housing-Choice
Hindrances and Urban Spatial Structure: Evidence from
Matched Location and Location-Preference Data in Chi-
nese Cities,” Journal of Urban Economics, Vol. 60, No. 3,
2006, pp. 535-557. doi:10.1016/j.jue.2006.05.003
[12] M. Liu, R. Reed and H. Wu, “Challenges Facing Housing
Affordability in Beijing in the Twenty-First Century,”
International Journal of Housing Markets and Analysis,
Vol. 1, No. 3, 2008, pp. 275-287.
[13] S. Chen and K. Karwan, “Innovative Cities in China:
Lessons from Pudong New District, Zhangjiang High
Tech Park and SMIC Village,” Innovation: Management,
Policy & Practice, Vol. 10, No. 2-3, 2008, pp. 247-256.
[14] Y. R. Yang and C. H. Chang, “An Urban Regeneration
Regime in China: A Case Study of Urban Redevelopment
in Shanghai’s Taipingqiao Area,” Urban Studies, 2007.
Vol. 44, No. 9, pp. 1809-1826.
[15] J. M. Zhu, “From Land Use Right to land Development
Right: Institutional Change in China’s Urban Develop-
ment,” Urban Studies, Vol. 41, No. 7, 2004, pp. 1249-
1269. doi:10.1080/0042098042000214770
[16] T. W. Zhang, “Decentralization, Localization, and the
Emergence of a Quasi-participatory Decision-Making
Structure in Urban Development in Shanghai,” Interna-
tional Plann i n g S t udies, Vol. 7, No. 4, 2002, pp. 303-323.
[17] J. N. Ball and V. C. Srinivasan, “Using the Analytic Hi-
erarchy Process in House Selection,” Journal of Real Es-
tate Finance & Economics, Vol. 9, No. 1, 1994, pp. 69-
85. doi:10.1007/BF01153589
[18] M. J. Schniederjans, J. J. Hoffman and G. S. Sirmans
“Using Goal Programming and the Analytic Hierarchy
Process in House Selection,” The Journal of Real Estate
Finance and Economics, Vol. 11, No. 2, 1995, pp. 167-
L. H. LI
Copyright © 2011 SciRes. ME
176. doi:10.1007/BF01098660
[19] S. M. Li, Y. L. Song and N. Chiang, “Displacement,
Housing Conditions and Residential Satisfaction: An
Analysis of Shanghai Residents,” The Centre for China
Urban and Regional Studies, Occasional Paper, Vol. 78,
August 2007, pp. 1-24.
[20] L. H. Li, “Community Attachment and Housing Choice
in Hong Kong,” Property Management, 2009, Vol. 27,
No. 1, pp. 42-57. doi:10.1108/02637470910932665
[21] D. A. Lawis and G. Salem, “Community Crime Preven-
tion: An Analysis of a Developing Strategy,” Crime and
Delinquency, Vol. 27, No. 3, July 1981, pp. 405-421.
[22] Y. Baba and M. D. Austin, “Neighborhood Environ-
mental Satisfaction, Victimization, and Social Participa-
tion as Determinants of Perceived Neighborhood Safety,”
Environment and Behavior, Vol. 21, No. 6, 1989, pp.
763-780. doi:10.1177/0013916589216006