Building and Environment 151 (2019) 112–125

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Building and Environment

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Bridging the gap between sustainable housing and affordable housing: The T
required critical success criteria (CSC)
Albert P.C. Chan, Michael Atafo Adabre∗
Building and Real Estate Department, Hong Kong Polytechnic University, Hong Kong

A R T I C LE I N FO A B S T R A C T

Keywords: Studies on specific critical success criteria (CSC) for performance measurement of sustainable affordable housing
Critical success criteria projects are limited. This study aims to identify and classify the various CSC from the views of affordable housing
Affordable housing experts around the world. 21 CSC were identified from a comprehensive literature review followed by a ques-
Sustainable housing tionnaire survey on the identified 21 CSC. With 51 responses, the data were analyzed. Factor analysis indicated
Affordability
that the various CSC can be grouped into six components: household satisfaction CSC, stakeholders' satisfaction
CSC, house operation cost CSC, time measurement CSC, location affordability cost CSC and quality-related CSC.
Practically, the findings of this study can serve as a guide for assessing the performance of affordable housing
projects as well as serving as a guide to developers, NGOs and government agencies in the allocation of resources
for the provision of sustainable affordable housing. Future study would investigate the interrelationship between
critical success criteria and critical success factors for sustainable affordable housing.

1. Introduction economic measure, real estate developers, planners, architects and

governments have encountered challenges of low demand and aban-
Housing is among the basic social conditions which define the donment of housing in the provision of affordable housing [8,9]. For
quality of life and wellbeing of the citizens of any nation. However, in a example, in a developing country China, it was stated that the average
constantly changing and urbanizing world, housing supply has not been housing price-to-income ratio for many major cities was 10.2 in 2013,
able to adequately meet demand [1]. Corollaries of the acceleration in which situated China in a group of severely unaffordable housing
urbanization are increasing affordability challenges among low income market [10]. However, public rental housing which were less than 30%
earners noted in both developed and developing countries [2]. For in- of market rents were abandoned by applicants in Shenzhen, Wuhan,
stance, it has been estimated that the number of poor people living in Nanjing, Zhengzhou and Shanghai [11]. Consequently, 90% vacancy
shantytowns and sub-standard housing in developing countries is 828 rate was reported in the case of Shenzhen [12]. In Malaysia, a study
million. Speculations are that this number will increase to 1.4 billion by indicated the need for affordable housing for low and middle-income
2020 [1,3,4]. A survey conducted among some developed countries earners [13]. Yet, affordable housing that were supplied to these in-
such as USA, Australia, Singapore, Hong Kong (China), New Zealand come categories were left vacant leading to housing overhang [14]. A
and Ireland revealed that out of 293 housing markets surveyed, only 63 Similar situation of housing abandonment has been reported in a de-
were considered affordable [5]. In general, the anticipation of the veloped country United Kingdom [15]. In all these cases, the aban-
world's population growth from 3.6 billion to 6.3 billion in 2050 is an donments of the houses were attributed to other criteria beyond price
indication that more housing will be required to meet the mounting affordability. Thus, these paradoxes of housing needs amidst housing
housing needs [6]. Accordingly, sustainable affordable housing remains overhangs buttress the fact that not all that is affordable is sustainable!
a priority for all governments and other policy makers. Therefore, bridging the gap between sustainable housing and affordable
Many affordable housing policies have been initiated. However, housing is exigent.
whether the housing affordability of low-income earners has been im- Successively, in a study conducted by Mulliner et al. [15]; it was
proved remains a debate [1]. Study by Stone [7] has focused on the concluded that in addition to economic measures, there are non-eco-
economic measure - price affordability - for accessing the success or nomic criteria associated with evaluating success of sustainable af-
improvement of housing policies. Conversely, by solely focusing on the fordable housing projects. These economic and non-economic criteria

∗
Corresponding author.
E-mail addresses: albert.chan@polyu.edu.hk (A.P.C. Chan), 17902405r@connect.polyu.hk (M.A. Adabre).

https://doi.org/10.1016/j.buildenv.2019.01.029
Received 29 November 2018; Received in revised form 6 January 2019; Accepted 21 January 2019
Available online 24 January 2019
0360-1323/ © 2019 Elsevier Ltd. All rights reserved.
A.P.C. Chan, M.A. Adabre Building and Environment 151 (2019) 112–125

or standard are termed critical success criteria (CSC). CSC are the set of The other criterion – satisfaction – was more focused on the owner and
principles or standards through which judgement can be made whereas user of the project. Therefore, they failed to provide detail criteria for
critical success factors (CSF) are the set of circumstances, facts or in- construction companies or contractors [28]. In Baccarini [27]; the cri-
fluences which affect/contribute to the results or CSC (Lim and Mo- teria of project success were grouped into product success and project
hammed, 1992 p.243). For instance, ‘accessibility to shops’ and ‘access management success based on the goal, purpose, output and input. The
to health services’ are examples of CSFs (factors) whereas ‘reduced product success deals with goals and purpose while the project man-
commuting cost or time’ could be used as a CSC (criterion/outcome) agement success deals with output and inputs. Although Baccarini [27]
which is influenced by the CSFs. Furthermore, ‘availability of green flagged some key criteria applicable to construction companies and
public space’ is a CSF whereas ‘household/stakeholders’ satisfaction’ contractors in the project management success criteria, contractors'
and ‘quality housing’ could be used as CSC [16,17]. Moreover, ‘the goals such as revenue and profit, market share and competitive ad-
construction method for a housing facility’ and ‘materials used for vantage were not explicitly stated. Based on this knowledge gap, Al-
construction’ are CSFs which could influence CSC such as ‘maintain- Tmeemy et al. [28] conducted a study on developing a framework to
ability of a housing facility’; ‘technical specification of a housing fa- categorize project success for building projects from contractors' per-
cility’ and ‘environmental performance of a housing facility’ [17,18]. spectives. While maintaining the classification of Baccarini [27]; Al-
Finally, ‘the type of communication among project stakeholders’ could Tmeemy et al. [28] added another category of success – market success.
be a CSF which influences criteria such as ‘reduced occurrence of dis- Therefore, three classes of project success were identified from the
putes and litigation among project stakeholders’ and ‘technology study of Al-Tmeemy et al. [28]. These included: the project manage-
transfer’ in construction projects [19]. ment success which consists of adherence to quality targets, schedule
In addition to the lack of consensus on CSC [1], studies on CSC for and budget; the product success such as customer satisfaction, func-
sustainable affordable housing projects are limited. As such, an in- tional requirement and technical specification; market success such as
vestigation on CSC for sustainable affordable housing projects is im- revenue and profit, market share, reputation and competitive ad-
portant for the following reasons. Knowledge on CSC is required for the vantage. The market success criteria emphasised on the strategic goals
development of sustainable and affordable housing policies to improve of construction companies.
the current and anticipated affordability crises. Besides, real estate Although the identified criteria from previous studies [24,27,28]
developers, governments and international organizations need to be are comprehensive and applicable to most construction projects, not all
apprised of the effective and appropriate CSC to identify affordability might be relevant for housing projects due to differences in project
challenges and innovate measures for successful housing delivery. characteristics. For instance, according to Ahadzie et al. [16] on mass
Moreover, CSC serve as measures to guide developers and governments housing, housing projects involve the construction of domestic re-
to enhance efficient allocation of the limited resources to meeting the sidence. Moreover, mass housing projects are speculative in nature
residential needs of the household [20]. Finally, the categorization of since decisions on land acquisition, design and construction of such
the various CSC will help governments and international policy makers houses are mostly made without a specific customer in mind. Therefore,
on strategies required to bridge the gap between sustainable housing with regard to housing projects, Ahadzie et al. [16] developed four
and affordable housing. clusters of CSC for mass housing projects: environmental impact, cus-
In the light of the background above, the main objective of this tomer satisfaction, quality and overall cost and time. These CSC could
study is to identify the CSC which are required to evaluate success in be appropriate for affordable housing projects based on the similarities
sustainable affordable housing projects. Therefore, a literature review between mass housing and affordable housing. Like mass housing, af-
was conducted to identify the potential set of CSC for sustainable af- fordable housing projects involve the construction of domestic re-
fordable housing projects, which forms section two of this study. Then, sidence and are also speculative in nature. Despite the similarities in
Section Three presents a thorough description of the research metho- project characteristics, definitional difference between them suggests
dology adopted for the study. Furthermore, statistical analysis of the that the CSC for mass housing are not comprehensive CSC for affordable
survey responses together with discussion of results was conducted in housing projects. In Ahadzie et al. ([16] p. 678), mass housing is de-
the penultimate section, Section Four. Finally, some concluding re- fined as “the design and construction of speculative standardized house-
marks are stated in Section Five. units usually in the same location and executed within the same project
scheme.” However, “affordable housing is housing that is reasonably
2. Literature review adequate in standard and location for a lower or middle-income
household and does not cost so much that such a household is unlikely
The identification of key project CSC is important so that con- to be able to meet other basic living costs on a sustainable basis [29].
struction managers, project managers and policy makers can appro- The rule-of-thumb is that housing is affordable if low income household
priately plan resource allocation [20]. Irrespective of the type of con- spent less than 30% of their income on housing. Therefore, mass
struction projects, the iron triangle of time, cost and quality have been housing projects are affordable provided they meet the affordability
widely recognized as the fundamental CSC in many studies [21–23]. criteria/requirements. Otherwise, mass housing cannot be considered
However, it is a fact that some determinants of success are likely to be affordable housing and therefore different CSC maybe required for as-
distinctive among projects. Moreover, studies have revealed that the sessing the sustainability of affordable housing.
iron triangle criteria are non-exhaustive [24–26]. Therefore, studies Findings of the study by Ahadzie et al. [16] cannot be considered as
have been conducted to comprehensively identify CSC for project complete CSC for affordable housing projects. For example, price of
monitoring and control in the construction industry [24,27]; Ahadzie housing and rental cost of housing in relation to household income
et al., 2011; [28]. which are important criteria for affordable housing [15] were not
In general construction project, Lim and Mohamed [24] explored considered among the criteria in their study. Besides, transportation
the criteria of project success from different perspectives of stake- cost in relation to the income of households [30] was also not listed
holders. The identified criteria were grouped into two categories. These among the criteria identified in their study. Based on these caveats, it is
included the macro and micro perspectives. Project completion and necessary to find out the exclusive CSC for sustainable affordable
satisfaction were the criteria that defined the macro viewpoint of pro- housing projects. Studies have been conducted on identifying these
ject success while the micro viewpoint was solely defined by the com- specific criteria. The traditional ratio criterion measures affordability in
pletion criterion. Thus, the classification by Lim and Mohamed [24] terms of the ratio of housing cost to income. However, Chaplin et al.
highlighted an overlap between the categories. For instance, the com- [31] and Bogdon and Can [32] stated that though the ratio approach is
pletion criterion was common to both the macro and micro viewpoints. simple to compute and widely used, it is not adequate enough to assess

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the affordability situation of household. Affordability must involve financial criteria. Although Mulliner et al. [15] broadened the scope of
whether a household has enough income left over for other needs of life sustainable affordable housing criteria and contributed significantly,
after paying housing bills. If the household cannot meet their non- they failed to differentiate critical success criteria (CSC) from critical
housing needs such as food, medical care and clothing at some success factors (CSFs). Out of the twenty-one criteria, only five criteria
minimum level of adequacy after paying for housing bill, then the namely, house price in relation to income, rental costs in relation to
household is ‘shelter poor’. Thus, unlike the ratio criterion which looks income, safety (crime), quality of housing and energy efficiency can be
at housing affordability only as a matter of housing cost, the ‘shelter termed as critical success criteria. However, the other 16 criteria are
poor’ or ‘residual’ approach takes into account the full amount required critical success factors [24].
for housing and other basic needs [7]. However, the residual income Similarly, Gan et al. [1] aimed at identifying key sustainability
approach and the shelter poverty concept have a practical challenge of performance indicators (KSPIs) from three stakeholder groups such as
being translated into an operational affordability scale. It is a problem developers, government and academics. Using the fuzzy set theory and
setting the minimum standard of adequacy for non-shelter items [32]. variance analysis, 24 KSPIs were conclusively highlighted from 42
Moreover, the conventional ratio and residual approaches focus more sustainability indicators of affordable housing. Among the KSPIs, some
on the economic issues of price affordability of housing. This solely of the CSC include affordable price/rent, reduced transport cost, cost
does not bridge the gap between sustainable housing and affordable effectiveness and energy efficiency. However, like in previous study by
housing. For example, though the prices of a housing facility might be Mulliner et al. [15]; some of the 24 identified indicators are possibly
affordable, it is not truly affordable if it located in a remote area with critical success factors rather than critical success criteria. For instance,
high transportation cost [6]. In a study conducted by Isalou et al. [30]; ‘providing human resource for economic development’, ‘ensure balance
it was found out that suburban household spent about 57% of their housing market’, ‘availability of green public space and adequate living
income on housing and transportation which was significantly higher space within small size unit’ are critical success factors [24].
compared to 45% of housing and transportation expenditure spent by It can be concluded from the above literature review that studies on
households in the urban areas. CSC for bridging the gap between sustainable housing and affordable
Yet, the price of a housing facility and transportation cost do not housing are limited. Therefore, a comprehensive investigation of CSC
give a complete view of the required CSC for measuring the success of for performance assessment of sustainable affordable housing and for
sustainable affordable housing projects [1,15]. According to Mulliner bridging the gap between sustainable housing and affordable housing is
et al. (2013 p. 270), to improve quality of life and community sus- worthwhile.
tainability, aside the economic assessment criteria, “the environmental
and social sustainability of housing must be taken into consideration”.
Using the COPRAS method of Multi-Criteria Decision Making (MCDM), 3. Research methodology
twenty-one criteria were used to assess the affordability of an area.
These criteria in descending order of their mean scores include: house 3.1. Establishing potential CSC for sustainable affordable housing
price in relation to income, rental costs in relation to income, interest
rates and availability of mortgages, social and private rented accom- To establish the relevance of the various CSC for sustainable af-
modation availability, homeownership products availability, access to fordable housing, a thorough review of the literature on CSC was first
employment opportunities, public transport services accessibility, conducted. Consequently, a set of 20 CSC that are apposite for sus-
quality school accessibility, access to shops, access to health services, tainable affordable housing was developed. Then a pilot study was
access to child care, open green public space accessibility, quality of conducted by sending out the list of CSC to affordable housing experts
housing, energy efficiency of housing, availability of waste manage- with sufficient research and/or industrial experience. This was carried
ment facilities, appeal of neighborhood area, deprivation in area and out to review the completeness and clarity of the CSC. Both experts
presence of environmental problems. It was concluded that considering from academia and industry confirmed the comprehensiveness of the
social and environmental criteria can critically influence the estimation CSC with minor corrections on the appropriateness of the words to
of the affordability in an area as compared to focusing solely on the convey meaning without ambiguity. Moreover, the criterion - waiting
time of applicants before being allocated a housing unit – was suggested

Table 1
Potential CSC for sustainable affordable housing.
No. CSC for Sustainable Affordable Housing References

CSC01 Timely completion of project Chan and Chan [23]; Bassioni et al. [22]; Ahadzie et al. [16]
CSC02 Construction cost performance of housing facility Al-Tmeemy et al. [28]; Osei-Kyei and Chan [33]
CSC03 Quality performance of project Atkinson [21]; Lim and Mohamed [24]; Cox et al. (2003)
CSC04 Safety performance Wai et al. [34]; Kylili et al. (2016); Ngacho and Das (2014)
CSC05 End user's satisfaction with the housing facility Torbica and Stroh [17]; Bryde and Robinson (2005)
CSC06 Project team satisfaction with the housing facility Yan et al. [35]
CSC07 Environmental performance of housing facility (Eco-friendly) Lim and Mohamed [24]; Atkinson [21]; Rankin et al. [18]
CSC08 Reduce life cycle cost of housing facility Wai et al. [34]; Ahadzie et al. [16]
CSC09 Maintainability of housing facility Wai et al. [34]
CSC10 Energy efficiency of housing facility Wai et al. [34]; Ahadzie et al. [16]
CSC11 Reduced occurrence of disputes and litigation Osei-Kyei and Chan [33]
CSC12 Reduced public sector expenditure on managing housing facility Osei-Kyei and Chan [33]
CSC13 Functionality of housing facility Chan and Chan [23]; Chan et al. [36]
CSC14 Technical specification of housing Chan and Chan [23]; Osei-Kyei and Chan [33];
CSC15 Aesthetically pleasing view of completed house Chan and Chan [23]
CSC16 House price in relation to income Mulliner et al. [15]; Ahadzie et al. [16]
CSC17 Rental cost in relation to income Mulliner et al. [15]
CSC18 Commuting cost from the location of housing to public facilities Hamidi et al. [37]
CSC19 Technology transfer Ahadzie et al. [16]
CSC20 Waiting time of applicants before being allocated a housing unit Chiu [38]
CSC21 Take up rate of housing facility (marketability of housing facility) Pullen et al. [39]

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by one of the experts and upon further consultation with other experts Table 2
and reading of the literature, it was added. Therefore, a total of 21 Responses from various countries.
sustainable affordable housing CSC were established. These are pre- Countries Number of Response
sented in Table 1 with their respective references.
USA 12
Australia 5
3.2. Data collection
Malaysia 5
Italy 4
A questionnaire survey was conducted for data collection from af- Hong Kong 3
fordable housing experts around the world. Questionnaire survey has Sweden 3
been used to seek professionals' views in construction related research China 3
Canada 3
[40]. These experts were selected based on two major criteria as used in
Ghana 2
previous studies [33,41]. New Zealand 2
Singapore 2
1. Respondents who had broad research and/or industrial experience Brazil 1
India 1
in affordable housing were selected
Spain 1
2. Respondents who have in-depth knowledge on affordable housing South Africa 1
projects were contacted to participate in the survey. Japan 1
Norway 1
Considering the selection criteria for experts, it is believed that Papua New Guinea 1
Total 51
these experts will offer insight on the relevance of the CSC for sus-
tainable affordable housing projects.
The targeted respondents for this survey included experts in aca-
Table 3
demia, contractors or developers and consultants. Experts were sourced Respondents' category, profession, years of experience and housing type han-
and identified from affordable housing related publications in top-tier dled.
academic refereed journals and databases (member directories) of af-
Category, Profession, years of experience and Number of Percent
fordable housing experts. Like snowballing, potential respondents of the
housing type handled Response
questionnaire were implored to forward the questionnaire to any af-
fordable housing expert they deemed suitable to answer the ques- Category
tionnaire. Therefore, it will be a herculean task to state the exact Academia/research institute 37 72.5
Consulting firm 5 9.8
number of questionnaires administered. However, approximately 200
Public sector agency/department 3 5.9
questionnaires were administered. Emails were sent to the participants Private developer/contractor 2 3.9
with the questionnaire attached together with a web-link option for Others 4 7.8
responding to the questionnaire through a “survey monkey”. These Profession
flexibility options provided convenient means for experts to respond to Academic/researcher 28 54.9
Architect 9 17.6
the questionnaire to enhance the response rate. Experts were asked to
Quantity Surveyor 3 5.9
rate on a five-point Likert scale (1 = not important, 2 = less important, Project/Construction manager 2 3.9
3 = neutral, 4 = important, 5 = very important) the level of im- Engineer 1 2.0
portance of each CSC in measuring success in sustainable affordable Others 8 15.7
Years of Experience
housing projects. Fifty-three responses were received. However, two
1–5 years 9 17.6
respondents skipped most of the questions on the CSC and were 6–10 years 11 21.6
therefore excluded from the number of responses, lowering the number 11–15 years 6 11.8
of responses to 51 with a response rate of 26%. Despite the low re- 16–20 years 4 7.8
sponse rate, the sample size is deemed appropriate for further analysis > 20 years 21 41.2
Housing Type Handled
when compared with the response rate of previous study [42]. Besides,
Social housing 37 40.2
low response rate is not unusual with online questionnaire surveys. For Public housing 35 38.0
instance, Osei-Kyei and Chan [33] received 42 responses out of 310 Cooperative housing 14 15.2
participants (a response rate of 18%). As argued in Chan et al. [40]; a Others 6 6.5
minimum sample size of 30 is regarded as representative of the popu-
lation. Moreover, despite the small sample size, the aim of the study
could be achieved. Table 2 shows the number of responses received Fig. 1. It reveals the stages, research process, research methodology and
from various countries. It shows that most of the responses are from the findings for the study.
United States of America, Australia, Malaysia and Italy.
4. Data analysis and results
3.3. Profiles of respondents
The Statistical Package for Social Science (SPSS) version 20 was
Table 3 is a summary of the profile of respondents. Most of the re- used to conduct statistical analysis of data. Three statistical analyses
spondents (72.5%) are in the category of academia/research institute were conducted: descriptive analysis, factor analysis and Pearson
followed by respondents in the consulting firms (9.8%). About 5.9% Correlation, as shown in Fig. 1. Before conducting the statistical ana-
and 3.9% of the respondents are public sector agencies and private lysis, the internal consistency reliability and how well the set of 21 CSC
developers/contractors, respectively. With regard to profession, most of are correlated to one another were checked using the Cronbach's Alpha
the respondents are researchers (54.9%) as shown in Table 3. Many of (α). A Cronbach's Alpha of 0.720 was obtained. According to Field [43];
the respondents (41.2%) had over 20 years of experience in affordable a Cronbach's alpha of 0.70 is considered acceptable. Therefore, the
housing projects. Generally, all the respondents indicated that they Cronbach's alpha gives indication that the 21 CSC are internally con-
have been involved in affordable housing research and/or have in- sistent and well correlated to one another. Then, the descriptive ana-
dustrial experience with affordable housing projects. lysis was used for ranking the various criteria based on their computed
A summary of the research framework for the study is shown in means and standard deviation values. Moreover, the Pearson

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A.P.C. Chan, M.A. Adabre Building and Environment 151 (2019) 112–125

Fig. 1. Research framework for the study.

correlation analysis was employed to determine how each CSC corre- resisted. This was confirmed by a study conducted by Chan et al. [40] in
lated with one another. Finally, factor analysis was conducted using all which increase in cost was among the main reasons for the low adop-
the 21 CSC to reduce them into components or categories of CSC that tion of green building technologies in both developed and developing
could be measuring the same underlying effect [16]. The steps in the countries. Therefore, Chan et al. [40] concluded that cheaper and ef-
analysis, findings and discussions are presented in subsequent sections. ficient green building technologies should be adopted to improve the
level of success of the other criteria in housing projects (i.e. reduce life
4.1. Mean ranking of CSC cycle cost of housing facility and energy efficiency of housing facility)
without increasing price and rental cost of housing. The five least
The CSC were ranked based on their mean and standard deviation ranked CSC from all responses include: reduced public sector ex-
values (shown in Table 4). The ranking is first based on the mean values penditure on house management (CSC12), reduced occurrence of dis-
of the CSC. However, if two or more CSC have the same mean the CSC putes and litigation (CSC11), project team satisfaction (CSC6), technical
with the lowest standard deviation is ranked the highest. The top five specification of housing (CSC14) and technology transfer (CSC 19)
CSC for responses from all countries include house price in relation to which all had mean values below 3.700. Similarly, in Ahadzie et al.
income (CSC16), rental cost in relation to income (CSC17), maintain- [16] technology transfer was the least ranked critical success criterion.
ability of housing facility (CSC9), end user's satisfaction with housing Furthermore, the means, standard deviation and ranking were cal-
facility (CSC5) and functionality of housing facility (CSC 13) with mean culated separately for both developed and developing countries.
scores of 4.833, 4.771, 4.553, 4.417 and 4.333, respectively. Classification of countries into developed and developing countries was
The high ranking of price and rental cost of housing implies that done with reference to data from Mandelli et al. [44]. China, Malaysia,
though the other criteria are necessary for sustainable affordable Ghana, Papua New Guinea, South Africa, India and Brazil were grouped
housing, priority is most centered on price and rental affordability. as developing countries while USA, Australia, Italy, Hong Kong,
Similarly, in Gan et al. [1] price and rental affordability were highly Sweden, Canada, New Zealand, Singapore, Spain, Japan and Norway
ranked by different stakeholders namely government agencies, devel- were classified as developed countries. Among the developed countries,
opers and academics. Therefore, improvement in any of the CSC, that is priority was given first to rental cost of housing and then house price.
likely to increase price and rental affordability of housing could be However, in developing countries, price of housing was ranked first

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Table 4
Ranking of CSC.
Code All Countries Developed Countries Developing Countries

Mean SD Rank Mean SD Rank Mean SD Rank

CSC16 4.833 .429 1 4.857 .430 2 4.769 .439 1

CSC17 4.771 .425 2 4.857 .355 1 4.539 .519 4
CSC09 4.553 .503 3 4.559 .504 3 4.539 .519 4
CSC05 4.417 .613 4 4.343 .639 4 4.615 .506 3
CSC13 4.333 .724 5 4.286 .750 6 4.462 .660 8
CSC03 4.313 .689 6 4.171 .707 10 4.692 .480 2
CSC02 4.313 .748 7 4.286 .789 5 4.385 .650 9
CSC04 4.292 .544 8 4.200 .531 9 4.539 .519 6
CSC08 4.250 .700 9 4.229 .690 7 4.308 .751 14
CSC18 4.250 .758 10 4.200 .797 8 4.385 .650 9
CSC10 4.167 .694 11 4.086 .612 12 4.385 .870 12
CSC20 4.167 .883 12 4.086 .951 11 4.385 .650 9
CSC01 4.042 .898 13 3.886 .932 13 4.461 .660 7
CSC21 4.000 .905 14 3.882 .946 14 4.364 .674 13
CSC07 3.854 .684 15 3.800 .719 15 4.000 .577 18
CSC15 3.833 .753 16 3.743 .741 16 4.077 .760 17
CSC12 3.688 1.095 17 3.543 1.146 17 4.078 .862 16
CSC11 3.583 .964 18 3.429 .948 18 4.000 .913 20
CSC06 3.575 .853 19 3.412 .857 19 4.000 .707 19
CSC14 3.521 .875 20 3.286 .789 20 4.154 .801 15
CSC19 3.065 1.020 21 2.971 .937 21 3.333 1.231 21

while rental cost was ranked forth. In Gilbert [45]; it was stated that the Bartlett's test of sphericity must be large with a small associated sig-
privatization of public housing due to abysmal low rents, self-help nificance level [47]. The Bartlett's test of Sphericity was 483.120 at a
housing and the cultural preference for ownership among developing significance level of 0.000. This indicates that the population correla-
countries could be the reasons for the preference of price affordability tion matrix was not an identity matrix [43,48]. Therefore, the test re-
over rental affordability. From the findings (as shown in Table 4), other sults of the KMO and Bartlett's Test suggested that the data were sui-
CSC such as commuting cost from location of housing facility to public table for factor analysis.
facilities, maintainability of housing facility and reduce lifecycle cost With the selection of the Varimax Rotation, the Principal
were ranked relatively high among developed countries as compared to Component Analysis was then carried out to identify the fundamental
their rankings from developing countries. It is not surprising given the structures of CSC. Conventionally, only variables with eigenvalue and
disparities in the ranking of these sustainability related criteria. This factor loading at cut-off points of 1.0 and 0.50, respectively, were re-
reflects the high priority devoted to these criteria from developed tained. Since the factor loadings for all the CSC exceeded 0.50 (Shown
countries as compared to developing countries [46]. in Table 7), all the 21 CSC were retained. “The relatively high values of
the loading factors (0.6 for more than four variables) lend support to
4.2. Factor analysis the favorability of the sample size for the analysis” ([16] p. 681). Six
components were extracted (as shown in Table 7). The total variance
Factor analysis was conducted to group the 21 CSC into compo- explained by each component (as shown in Table 7) is as follows:
nents. This was necessary to identify the underlying structures of CSC Component 1 (29.377%); component 2 (13.103%); component 3
for sustainable affordable housing projects. The Principal Component (10.317%); component 4 (7.868%); component 5 (6.790%) and com-
Analysis (PCA) was adopted for the factor analysis. Prior to conducting ponent 6 (5.271%). In sum, the components explained 72.726% of the
the analysis, the suitability of the data for factor analysis was assessed. total variance.
The Kaiser-Meyer-Olkin (KMO) Sampling Adequacy Test and Bartlett's Depending on the underlying variables in each component, the
Test of Sphericity were carried out to determine the data appropriate- components were named as follows: component 1 was named
ness. KMO measures the sampling adequacy as a ratio of the squared ‘Household satisfaction CSC’; component 2: Stakeholders' satisfaction
correlation between the variables to the squared partial correlation CSC; component 3: House operation cost CSC; component 4: Time
between the variables [43]. KMO value of 0 is an indication of the measurement CSC; component 5: Location affordability cost CSC;
unsuitability of data for factor analysis while a value of 1 indicates that component 6: Quality-related CSC.
the data are suitable and will yield reliable and distinct factors in the
factor analysis. A KMO value above 0.5 is deemed appropriate [43]. 4.3. Results of Principal Component Analysis and discussion
Table 5 shows the test results. The KMO measure of sampling adequacy
was 0.63. Thus, this was considered acceptable. Besides, the Bartlett 4.3.1. Component 1: household satisfaction CSC
Test of Sphericity was conducted to check if the original correlation The underlying CSC in this component highlight the criteria that
matrix is an identity matrix. For data suitability for factor analysis, the lead to household satisfaction in a housing facility. This component is
characterized by four main criteria. These four CSC, together with the
Table 5 percentages of their loading in bracket include: functionality of housing
KMO and Bartlett's test. facility (83.9%); end user's satisfaction with housing facility (81.2%);
Kaiser-Meyer-Olkin Measure of Sampling 0.630 maintainability of housing facility (64.1%) and safety performance
Adequacy (61.0%). This component explains most of the variance among the six
components, about 29.377% (please refer to Table 7 for loading and for
Bartlett's test of sphericity Approximate chi-square 483.120
the variance).
df. 210
Sig. 0.000 The correlation matrix (shown in Table 6) revealed significant as-
sociations among the various CSC in this component. For example, the

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Table 6
Correlation matrix of CSC.
CODE CSC01 CSC02 CSC03 CSC04 CSC05 CSC06 CSC07 CSC08 CSC09 CSC10 CSC11 CSC12 CSC13 CSC14 CSC15 CSC16 CSC17 CSC18 CSC19 CSC20 CSC21

CSC01 r 1.000
CSC02 r .392b 1.000
CSC03 r .116 .343a 1.000
CSC04 r .105 .189 .433b 1.000
CSC05 r .161 .174 .441b .521b 1.000
CSC06 r .361a .047 .124 .230 .393b 1.000
CSC07 r -.094 -.200 .370b .231 .402b .365a 1.000
CSC08 r .051 .173 .232 .140 .397b .393b .389b 1.000
CSC09 r -.005 .269 .293a .415b .487b .206 .415b .559b 1.000
CSC10 r .193 .020 .200 .263 .233 .442b .590b .569b .384b 1.000
CSC11 r .414b .155 .072 .358a .192 .365a .132 .284 .156 .297a 1.000
CSC12 r .252 .252 .076 .192 .040 .082 -.062 .271 .208 .098 .479b 1.000
CSC13 r .240 .314a .469b .450b .591b .084 .186 .210 .459b .226 .264 .080 1.000
CSC14 r .540b .429b .430b .389b .301a .597b .272 .339a .352a .449a .364a .204 .324a 1.000
CSC15 r .136 .019 .389b .433b .200 .455b .447b .363a .422b .420b .313a .116 .104 .490b 1.000

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CSC16 r -.202 .033 -.108 .030 -.135 -.200 -.157 .142 -.057 .095 .034 .339a -.160 -.274 -.022 1.000
CSC17 r -.253 -.239 -.041 .111 .048 -.219 -.044 .125 .009 .132 -.082 -.112 .115 -.302a -.122 .369b 1.000
CSC18 r .172 .122 .255 .438b 366a -.030 .113 .281 .303a .243 .349a .507b .426b .056 .186 .261 .248 1.000
CSC19 r .263 .291 .254 .206 -.008 .323a .274 .327a .232 .305a .495b .437b .033 .518b .483b .026 -.227 .150 1.000
CSC20 r .045 -.145 .192 .339a .498b .354a .358a .344a .367a .231 .333a .231 .111 .106 .426b .075 .161 .350a .160 1.000
CSC21 r -.045 -.102 .226 .458b .404b .150 .331a .214 .101 .249 .312a .115 .193 .116 .273a .341a .325a .398b .218 .640b 1.000

r = Value for Pearson correlation.

p = Value of the significance.
(CSC01 = Timely completion of projects; CSC02 = Construction cost performance of housing facility; CSC03 = Quality performance of project; CSC04 = Safety performance; CSC05 = End user's satisfaction with the
housing facility; CSC06 = Project team satisfaction with the housing facility; CSC07 = Environmental performance of housing facility (Eco-friendly); CSC08 = Reduced life cycle cost of housing facility;
CSC09 = Maintainability of housing facility; CSC10 = Energy efficiency of housing facility; CSC11 = Reduced occurrence of disputes and litigation; CSC12 = Reduced public sector expenditure on managing housing
facility; CSC13 = Functionality of housing facility; CSC14 = Technical specification of housing; CSC15 = Aesthetically pleasing view of completed house; CSC16 = House price in relation to income; CSC17 = Rental cost
in relation to income; CSC18 = Commuting cost from the location of housing to public facilities; CSC19 = Technology transfer; CSC20 = Waiting time of applicants before being allocated a housing unit; CSC21 = Take
up rate of housing facility (marketability of housing facility))
a
Correlation is significant at the 0.05 level (2-tailed).
b
Correlation is significant at the 0.01 level (2-tailed).
Building and Environment 151 (2019) 112–125
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correlation between ‘functionality of housing facility’ and ‘end user's disputes that could arise from construction claims. Besides, decrease in
satisfaction’ was significant (r = 0.591, p = 0.01); between ‘function- property values due to affordable housing projects is one of the causes
ality of housing facility’ and ‘maintainability of housing facility’ of public protest which has caused the failure of many affordable
(r = 0.459, p = 0.01) and ‘functionality of housing facility’ and ‘safety housing projects [55,56]. Delays and complete abandonment of projects
performance’ (r = 0.450, p = 0.01). Therefore, the association among due to political reasons could affect the values of neighboring housing
these CSC is coherent since they measure the same factor – household facilities. Such projects are often used as hideouts for criminals. As
satisfaction. such, households in the neighborhood might live in fear of insecurity.
Similarly, in Ahadzie et al. [16]; household satisfaction with Therefore, potential tenants and buyers might perceive such sur-
housing facility emerged as one of the components for mass housing roundings as unsafe. This could lower the rent and price of the neigh-
projects. To bridge the gap between sustainable housing and affordable boring facilities. This leads to dissatisfied neighborhoods who may
housing, meeting household satisfaction is very important. Household disrupt and protest against the construction of subsequent affordable
satisfaction is defined as an assessment of the degree to which the housing project. Accordingly, timely completion of affordable housing
current dwelling of the household and quality of the environment are projects ensures stakeholders' satisfaction by preventing negative social
close to the expectations of their favorite one [49]. Ensuring function- impacts. It also ensures project team satisfaction [57]. This is evident in
ality of housing according to aspirations, safety performance (i.e. se- the statistically significant correlation (as shown in Table 6) between
curity provision features) and ease of housing facility maintenance are ‘timely completion of project’ and ‘project team satisfaction’ (r = 0.361,
relevant for household satisfaction. Functionality is considered a con- p = 0.05). Similarly, ‘reduced occurrence of disputes’ and ‘project team
sequence of the facility. It includes the performance output and the satisfaction’ have a statistically significant association (r = 0.365,
benefits of the facility to the household. Performance output of housing p = 0.05).
facility measures the quality of the housing while the benefit of the
housing functionality is a measure of the household satisfaction [50]. 4.3.3. Component 3: housing operation cost CSC
Functionality can be measured by the level of conformance to client's The total variance accounted by component 3 is 10.3% (as shown in
expectation, with the ultimate goal of achieving fitness for purpose Table 7). The respective criteria and the percentage of the factor
[36]. Functionality should be assessed at the post construction phase, loadings in this component include energy efficiency (85.6%), reduced
when the facility is completed and is in use [36]. lifecycle cost of housing facility (84.2%) and environmental perfor-
Moreover, several features of a house ensure residential satisfaction. mance of housing facility (53.0%) (as shown in Table 7). The criteria
For instance, separate bedrooms for parents and children contribute to showed significant correlation among themselves. The correlation (as
more private space and residential satisfaction [51]. Similarly, Pear- shown in Table 6) between energy efficiency and reduced lifecycle cost
son's correlation conducted by Mohit et al. [52] revealed that re- of housing was significant (r = 0.569, p = 0.01); the correlation be-
sidential satisfaction is highly and positively correlated with dwelling tween energy efficiency and environmental performance was also sig-
unit features followed by the social environment, dwelling support nificant (r = 0.590, p = 0.01). Similarly, reduced life cycle cost and
services and public facilities. Among planning policies, neighborhood environmental performance of housing facility revealed a significant
interaction and safety were dominant predictors of residential sa- correlation (r = 0.389, p = 0.01). These significant associations among
tisfaction. Moreover, maintainability of a housing facility ensures these criteria are not surprising because according to Ruparathna et al.
household satisfaction. In Torbica and Stroh [17], low-cost main- [58]; the environmental impact of a housing facility is determined from
tenance features of house and ease of home maintenance were identi- its lifecycle and its energy consumption. Since all these criteria measure
fied as contributory variables for household satisfaction. the operation cost or impact of a housing facility [59], this component
Although Riazi and Emami [53] found that design principles on was, accordingly, named as housing operation cost CSC.
residential satisfaction had a significant value of 0.183, most of the For sustainable affordable housing, the operations cost of housing is
design features were related to safety and security provisions. Some of worth considering due to its cost saving benefits to low income
these features include lighting of public areas, safety of car parking, household and the environment. Minimizing the operation cost of af-
safety of outdoor parking, safety of indoor space and security for chil- fordable housing projects could be achieved through energy efficient
dren in public areas. Personal security was identified as a feature that housing. The fundamental principle of energy efficient housing is to use
first-time homebuyers look out for in making purchasing decision. the minimum energy for operation (such as cooling, lighting, heating
Crime rate in the neighborhood and whether a neighborhood is gated etc.) without impacting residents' health and comfort [58]. Improving
are significant factors that influence residential satisfaction and the energy efficiency of affordable housing is key to abating the environ-
likelihood of home ownership among first-time homebuyers [14]. mental effects – greenhouse effects – due to CO2 emissions. It also re-
Safety community together with good leisure facilities promotes re- duces the energy use and therefore provides economic benefits such as
sidential satisfaction [51]. savings to low-income earners. Moreover, energy efficient affordable
housing is a requirement to prevent fuel poverty – low income house-
4.3.2. Component 2: stakeholders' satisfaction CSC hold spending beyond 10% of their income on domestic energy [60].
This component consists of ‘timely completion of project’ (78.8%), Studies have been conducted on energy efficient technologies that
‘project team satisfaction’ (68.8%) and ‘reduced occurrence of dispute can be adopted to provide sustainable affordable housing without
and litigation’ (60.7%). These three CSC explained about 13.10% of the rendering household shelter poor [61–63]. On the mechanical compo-
total variance (as shown in Table 7). nents of a housing facility, heating, ventilation and air conditioning
The construction of an affordable housing project involves many (HVAC) system is the most energy consumption component of a
stakeholders including the targeted households, governments, devel- housing facility [64]. Using thermal solar systems for a substitute of an
opers, design team, suppliers and the people in the neighborhoods of electric water heater leads to 80% saving of the cost of heating water as
the project. Stakeholders receive and execute the success criteria. well as ensuring environmental protection [63]. By changing from air-
Therefore, they have the potential to impact the outcome of sustainable cooled to water cooled air-conditioning system, substantial electricity
affordable housing project (Yan et al., 2019). Findings of the study consumption could be reduced [65].
showed that there is a statistically significant correlation between With regard to lighting system, about 15% of the total energy of a
‘timely completion of project’ and ‘reduce occurrence of disputes’ building is spent on lighting. However, installing better luminous effi-
(r = 0.414, p = 0.01) (as shown in Table 6). According to Sambasivan cacy lamps and linking daylight to lighting systems could reduce elec-
and Soon [54]; most disputes in construction projects are the effects of tricity consumption on lighting. Moreover, changing to light emitting
project delays. Timely completion of projects prevents construction diode (LED) light system, replacing incandescent lamps with low

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Table 7
Rotated component matrix.
Code CSC for Sustainable Affordable Housing Components Loading

1 2 3 4 5 6

Component 1: Household Satisfaction CSC

CSC13 Functionality of housing facility 0.839 – – – – –
CSC5 End user's satisfaction with the housing facility 0.812 – – – – –
CSC9 Maintainability of housing facility 0.641 – – – – –
CSC4 Safety performance (crime) 0.610 – – – – –
Component 2: Stakeholders' Satisfaction CSC
CSC1 Timely completion of project – 0.788 – – – –
CSC6 Project team satisfaction – 0.688 – – – –
CSC11 Reduced occurrence of disputes and litigation – 0.607 – – – –
Component 3: Housing Operation Cost CSC
CSC10 Energy efficiency of housing facility – – 0.856 – – –
CSC8 Reduced lifecycle cost of housing – – 0.842 – – –
CSC7 Environmental performance of housing facility (Eco-friendly) – – 0.530 – – –
Component 4: Time Measurement CSC
CSC21 Take up rate of housing facility (marketability of housing facility) – – – 0.802 – –
CSC20 Waiting time of applicants before being allocated housing unit – – – 0.716 – –
CSC2 Construction cost performance of housing facility – – – −0.555 – –
Component 5: Location affordability Cost CSC
CSC12 Reduced public sector expenditure on house management – – – – 0.818 –
CSC16 House price in relation to income – – – – 0.649 –
CSC18 Commuting cost from the location of housing to public facilities – – – – 0.631 –
CSC17 Rental cost in relation to income – – – – 0.506 –
Component 6: Quality-Related CSC
CSC3 Quality performance of project – – – – – 0.686
CSC15 Aesthetically pleasing view of completed house – – – – – 0.665
CSC19 Technology transfer – – – – – 0.658
CSC14 Technical specification of housing – – – – – 0.600

Eigenvalue 6.169 2.752 2.167 1.652 1.426 1.107

Variance (%) 29.377 13.103 10.317 7.868 6.790 5.271
Cumulative Variance (%) 29.377 42.480 52.797 60.665 67.455 72.726

Extraction Method: Principal Component Analysis; Rotation method: Varimax with Kaiser Normalization.

energy fluorescent lamps and installing automated lighting system can face the south. The southern orientation is best for heat gain during
reduce the amount of electricity demanded for lighting [58]. Another wintertime and for regulating solar radiation during summer [59].
important area for energy efficient housing is the building envelope. Shading on buildings also affects the amount of solar radiation gained
Improved insulation minimizes the heat gain or loss from a building by a building. For instance, overhangs over windows prevent the direct
thereby enhancing the thermal performance of the housing facility entry of solar radiation through the window, therefore, it regulates the
[58]. Reflective paint and coating on roofs and walls or insulating paint entry of excessive heat and daylight. However, since overhangs are
with low conduction can be used to improve the thermal performance mostly designed to remain fixed, they could favor energy savings in
of a building. In a location of high temperature difference between day certain times while hindering energy saving at a different time. Thus,
and night, coating of the external surface of the housing facility pro- mobile shading devices provide better energy saving benefits than im-
vides better thermal function. However, in locations of low temperature movable shading devices [72]. Using the net present value appraisal on
difference between daytime and nighttime, housing facilities with in- a uniform evaluation period, Nikolaidis et al. [63] found that insulation
terior insulation do better [66]. of the roof of a building provides better intervention concerning heat
Building codes set the lowest requirement for energy efficiency in insulation than with the replacement of windows and doorframes,
buildings. Notable ones include BREEAM, Leadership in Energy and which yielded low returns on investment.
Environment (LEED) and Green Star. These codes may target one of the Moreover, though mud/baked bricks cannot be used to construct
following building energy concepts: low energy building, passive structural elements, its use for the construction of non-loading bearing
houses, zero energy building, zero carbon building [61]. By making walls could offer energy saving benefits. According to Chel and Tiwari
building energy code mandatory, it was stated that the yearly electricity [73]; internal temperatures of mud houses are moderate throughout the
consumption, for example in Hong Kong, can be lowered by 7.9% [67]. year. This leads to potential energy savings. Mud houses have yearly
Therefore, through the development of localized codes or adoption of heating and cooling energy saving of about 1481 KWh/year and
internationally recognized codes, affordable housing would be energy 1813 kWh, respectively. Moreover, mud-houses can alleviate 5.2 metric
efficient and thus sustainable. tons per year of CO2 emission into the atmosphere.
The shape of a housing facility affects the amount of solar radiation
that the building receives, which consequently influences its total en- 4.3.4. Component 4: time measurement CSC
ergy consumption [68]. The higher the solar radiation received by a The extracted CSC with their factor loading for this component in-
housing unit, the higher the energy required to cool it [69]. According clude ‘take up rate of housing facility (marketability)’ (80.2%), ‘waiting
to Aksoy and Inalli, [70]; 36% of heat energy savings can be obtained time of applicants before being allocated housing unit’ (71.6%) and
by combining the optimization of orientation and shape of a building. ‘construction cost performance of housing facility’ (−55.5%). This
For instance, on quantifying the effects of a building shape on the cluster explained about 7.87% of the total variance (as shown in
amount of energy required to heat and cool a building, Florides et al. Table 7) and was named time measurement CSC.
[71] concluded that the best orientation to maximize the solar benefits The correlation matrix (shown in Table 6) revealed that significant
of a rectangular building is for the lengthiest wall of the housing unit to correlations exist among the criteria in this component. For example,

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the correlation between ‘take up rate of housing facility’ and ‘waiting households [74]. The socio-demographics of the household defines the
time of applicant before being allocated a housing unit’ was significant influence of household income on transportation affordability. The
(r = 0.640, p = 0.01). Since both criteria measure the time taken for a built environment (defined by the land use) and urban design influence
household to move into a housing facility, the significant correlation the transportation affordability. There is an association between the
between them is logical. built environment and travel behavior. For instance, low residential
Aside building affordable housing, it is important to measure how density and mono-functional use of land are related to more car travel.
supplied housing is reducing the time spent by low-income earners in However, high density areas such urban centers where the buildings are
the ‘waiting line’ before being allocated affordable housing unit. closer, walking and cycling would be encouraged among many house-
Besides, assessing how affordable housing supplies are meeting the holds especially low-income earners [60]. It is worth noting that ex-
needs of household is very critical. This can be measured using the take- treme cases of compact city and urbanization could increase traffics on
up rate of housing facilities. Houses that are affordable but not ade- the roads thereby increasing the time spent on travelling. Thus, an af-
quate and sustainable are likely to receive low take-up rate by low in- fordable house is not sustainable if the cost and time of transportation
come earners [14]. Take up rate of an affordable housing facility is are very high.
significantly associated with household's satisfaction (r = 0.404,
p = 0.01). The correlation between take up rate and household's sa- 4.3.6. Component 6: quality-related CSC
tisfaction indicates that high expectation for household satisfaction Lastly, the sixth principal component contains four CSC. These CSC
leads to high take-up rate of a housing facility. However, high cost of together with their factor loading are ‘quality performance of project’
housing facility beyond the affordability range of the household could (68.6%), ‘aesthetically pleasing view of completed house’ (66.5%),
lead to low take up rate of the housing facility and increase waiting ‘technology transfer’ (65.8%) and ‘technical specification of housing’
time of applicants for housing unit allocation. (60.0%). This component explains 5.3% of the total variance and is
named quality-related CSC.
4.3.5. Component 5: location affordability cost CSC The findings revealed that some of the four CSC in this component
The principal component 5 contains four CSC: reduced public sector showed statistically significant correlation among themselves. For in-
expenditure on housing management (81.8%); house price in relation stance, the correlation matrix (as shown in Table 6) revealed a sig-
to income (64.9%); commuting cost from the location of housing to nificant relationship between quality performance of project and aes-
public facilities (63.1%) and rental cost in relation to income of thetically pleasing view of completed house (r = 0.389, p = 0.01).
household (50.6%) (as shown in Table 7). This component accounted Besides, the correlation between quality performance of project and
for 6.79% of the total variance (as shown in Table 7). Studies have technical specification of housing was significant (r = 0.430, p = 0.01).
stated that affordability should be measured as location affordability, Moreover, the correlation matrix revealed a significant association be-
that is taking into consideration housing affordability cost and cost of tween ‘technology transfer’ and ‘technical specification of housing’
transportation or accessibility [60,74,75]. Therefore, this component (r = 0.518, p = 0.01). Likewise, the association between technology
was labelled location affordability cost CSC. transfer and aesthetically pleasing view of completed house is sig-
As shown in the correlation matrix in Table 6, a statistically sig- nificant (r = 0.483, p = 0.01).
nificant correlation exists between ‘house price in relation to income’ The significant association between quality performance and aes-
and ‘rental cost in relation to income’ (r = 0.369, p = 0.01). This as- thetically pleasing view of completed house could be attributed to the
sociation between the two criteria is reasonable since both are used to fact that the conventional description of quality is based on issues such
measure the same item – housing affordability. Similarly, there was a as ‘how well a housing facility blends into its environment’, ‘the facil-
significant correlation between the criteria ‘reduced public sector ex- ity's psychological impacts on its inhabitants', ‘the ability of landscaping
penditure on house management’ and ‘commuting cost from the loca- plan to match the theme of nearby structures’ and ‘the use of intriguing
tion of housing to public facilities’ (r = 0.507, p = 0.01). novel design models that capture people's imaginations' [77]. Since the
Previous studies have elaborated on the importance of housing af- aesthetic definition of quality is subjective, there is often no consensus
fordability [16,19]. However, an important cost factor which was on whether quality affordable housing has been achieved or not [78].
overlooked in measuring affordability is the cost of transportation. However, quality performance of housing facility can also be defined
Location affordability incorporates both the cost of housing and trans- objectively as meeting technical specification of the designer, owner
portation. A study conducted by Saberi et al. [76]; revealed that and regulatory organizations [79].
neighbourhoods that seem to be affordable with regard to only housing Due to the subjective and objective assessment of quality, it is im-
cost are not definitely affordable when transportation cost is factored portant to differentiate ‘quality in perception’ and ‘quality in fact’. A
in. Housing facilities at the urban peripheral or in low-residential housing facility that meets client's and household's expectation attains
density areas may appear more affordable yet might suffer from in- quality in perception while a housing facility that meets the technical
adequate access to various amenities and incur high cost on transpor- specification attains ‘quality in fact’ [78]. ‘Quality in fact’ can be
tation in order to access the amenities. Thus, the low housing cost is achieved by meeting two main requirements: product quality and
mostly offset by the high commuting cost which leads to transport process quality [78]. Whereas product quality is ensuring suitable
poverty. A household might be transport poor based on three condi- construction materials, equipment and technology required for the
tions: if the household spends more than 10% of their income on car construction of a housing facility, process quality involves attaining
running costs, if the household lives more than one mile from the clo- quality with regard to the design and construction of the housing fa-
sest bus or station and if it takes more than one hour to access a number cility.
of important services by cycling, walking and public transport (Sus- Achieving both forms of quality is very important. The neglect of
trans, 2012 cited in Ref. [60]). Transportation poverty has many effects. quality in perception has often resulted in abandoned affordable
Individuals can be rendered unemployed due to inability to afford housing facilities [14,78]. Therefore, it is suggested that prior to the
ownership of cars/commuting cost. Besides, most households that are construction of any housing facility, a pilot study should be conducted
able to afford do trade-off transport expenditure against spending on to assess the needs of the intended households. Regular assessment of
other necessities [60]. the needs of the intended households is important since household
It is recommended that policies and plans for housing affordability needs are ephemeral [8]. This assessment will ensure that the expected
should take into account transportation infrastructure supply [76]. quality of a household is met. Though quality is considered a latent
Three main factors influence transportation affordability namely the variable, it could be achieved based on the housing design features.
built environment, policy environment and the socio-demographics of Design principles such as interior layout (i.e. size of living room,

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Fig. 2. A framework for sustainable affordable housing.

arrangement of rooms, size of kitchen, availability of storage room) and quality, secure and healthy housing facilities [81]. The four compo-
privacy of living space (i.e. number of bedrooms, size of bedrooms and nents of CSC for social sustainability are interdependent. Quality-re-
number of bathrooms) are considered very important among low-in- lated CSC could lead to the achievement of both household satisfaction
come households [80]. Among interior design features such as number CSC and stakeholders' satisfaction CSC. Besides, quality-related CSC
of bedrooms, bathrooms and living rooms, living space was the in- could influence high residential take up – one of the time measurement
dicator of quality that had the highest loading and reliability [51]. CSC. A high residential take up rate indicates that the housing facilities
Thus, these quality features should be taken into consideration for are appreciated by the target household [82] whereas a low residential
sustainable affordable housing projects so as to meet household needs. take up of affordable housing facilities may indicate that the housing
The significant positive correlations among technology transfer, facilities need to be improved or other facilities need to be provided to
technical specification and aesthetically pleasing view of housing (as meet household needs. Accordingly, the CSC for social sustainability
shown in Table 6) are logical. In Adinyira et al. [19] technology transfer play an important role in improving the operational performance of
emerged together with cost of individual units. Accordingly, it was affordable housing projects [12].
stated that the benefits of technology transfer could improve the price Economic sustainability in affordable housing projects could be
affordability of housing facilities. In this study, technology transfer measured using the location affordability cost CSC [30]. These criteria
emerged together with quality performance of housing project, aes- are essential for assessing the success of price/rental and commuting
thetically pleasing view of completed house and technical specification cost affordability of housing facilities. Commuting cost of residents
of housing. This implies that aesthetically pleasing view and technical plays a tremendous role on household income [1]. High commuting
specification could be improved through technology transfer. cost could cause high cost burden on household income thereby wor-
sening housing affordability of households. The CSC for economic
sustainability are interdependent on the CSC for social sustainability
4.4. Relevance and integration of the six components of CSC and environmental sustainability. For instance, low location afford-
ability cost CSC due to high accessible locations of housing facilities
Based on the empirical data, six main components are essential for reduces transportation cost which could influence household satisfac-
making affordable housing sustainable. The attainment of the six tion CSC, stakeholders' satisfaction CSC and time measurement CSC
components of CSC will ensure that the three main aspects of sustain- [12]. Besides, low location affordability cost CSC due to accessible lo-
ability – economic, social and environment – are achieved in affordable cation of housing facilities conserves energy and reduces pollution
housing projects. For instance, household satisfaction CSC, time mea- emission (such as carbon dioxide and carbon mono-oxide), which im-
surement CSC, quality-related CSC and stakeholder's satisfaction CSC proves on environmental sustainability [30].
measure success with regard to social sustainability in housing projects. Housing operation cost CSC (such as energy efficient housing
These CSC for social sustainability are essential for ensuring good-

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facilities, reduced lifecycle cost of housing facility and environmental 5. Conclusions

performance of housing facility) are essential for environmental sus-
tainability attainment in affordable housing projects. The housing op- The meaning of success, most often, changes from project to project.
eration cost CSC measure the impacts of housing facilities on the en- Determining whether an affordable housing project is sustainable and
vironment. The construction, maintenance and use of housing facilities therefore a success or a failure is far more complex. This is because
involves the consumptions of an enormous amount of scarce energy and there are inadequate studies on identifying a comprehensive list of CSC
other resources. These could lead to high environmental depletion. for assessing the sustainability and success of affordable housing pro-
However, using energy efficient technologies and environmental jects. Consequently, affordable housing is mostly assessed based on the
friendly materials could improve environmental sustainability of af- price or rental cost, which creates a gap between affordable housing
fordable housing projects [6]. and sustainable housing. Bridging this gap requires sustainable CSC.
Based on the aforementioned components of CSC, bridging the gap This study aimed to investigate the CSC required for the provision of
between sustainable housing and affordable housing requires the fol- sustainable affordable housing. A questionnaire of 21 CSC was ad-
lowing six components of CSC: (1) household satisfaction CSC, (2) ministered globally to affordable housing experts. Ranking, factor
stakeholders' satisfaction CSC, (3) housing operation cost CSC (4) time analysis and Pearson correlation were employed for data analysis.
measurement CSC, (5) location affordability cost CSC, (6) quality-re- Findings of this study revealed that though there is high interest on
lated CSC. To summarize, a framework of sustainable affordable other CSC (such as energy efficiency of housing facility, reduced life-
housing can therefore be established as shown in Fig. 2, which includes cycle cost of housing facility and environmental performance of
the six components of CSC which are essential for sustainable afford- housing facility), price and rental cost CSC are the most highly ranked
able housing. These components are interdependent with important among developed and developing countries. Besides, some of the
relationships among them. identified CSC are significantly correlated with one another.
Furthermore, six factors were developed for bridging the gap between
4.5. Application of the CSC for sustainable affordable housing sustainable housing and affordable housing: (1) household satisfaction
CSC, (2) stakeholder's satisfaction CSC, (3) housing operation cost CSC,
CSC serve as a set of standards by which anything is or can be (4) time measurement CSC, (5) location affordability cost CSC and (6)
judged [24]. The essence of CSC is to develop a set of criteria or stan- quality-related CSC.
dards which serve as guidelines by which policy makers can assess the A limitation of this study is that only the opinions of affordable
outcomes of projects [23]. While some of these CSC (such as location housing experts were considered. The views of households of affordable
affordability cost CSC, housing operation cost CSC and time measure housing units were excluded. For further studies, it is would be inter-
CSC) can be measured objectively through formulae/standard values, esting to analyze the views of households on CSC for sustainable af-
the other components of CSC (such as quality-related CSC, household fordable together with the views of academics and contractor. Besides,
satisfaction CSC and stakeholder's satisfaction CSC) use personal jud- the sample size used for this study is relative small. Therefore, future
gement and subjective opinions of stakeholders of affordable housing study with much larger responses could employ statistical analysis such
projects [8,23]. Concerning the objective CSC, a standard for location as ANOVA to compare and determine any statistical differences among
affordability cost can be established by combining housing and trans- the views of the various affordable housing stakeholders.
portation costs. It has been estimated that housing is affordable if the Though the study has limitations, there are important contributions
combined housing and transportation cost is less than 45% of house- of the findings of the study worth stating. The findings of the study have
hold income. Using this standard, policy makers could be guided on contributed to filling the knowledge gap in the affordable housing lit-
determining an appropriate location for siting an affordable housing erature by providing a comprehensive list of CSC for assessing success
project. Moreover, it could also serve as a guide to household towards in sustainable affordable housing. In addition, the identified CSC are
identifying the best affordable location when choosing a home [30]. evaluation criteria for bridging the gap between sustainable housing
However, one disadvantage of the location affordability cost standard is and affordable housing. Moreover, real estate developers, architects,
that it does not account for the housing operation cost (utility bills) international organizations and government agencies could rely on
likely to be incurred by potential households. Therefore, a new standard these CSC for resource allocation in the provision of sustainable af-
which is a combination of location affordability cost CSC and housing fordable housing. The identified CSC could be used by policy makers for
operation cost CSC could provide more impact on affordable housing identifying suitable locations for affordable housing projects.
policy formulation. However, providing a separate standard for Furthermore, the CSC could be relevant to potential households in
household energy cost, Mattioli et al. [60] stated that in energy efficient identifying the best affordable location and the most energy efficient
affordable housing, 10% or less of household's income on domestic housing facility when choosing a home. Moreover, by using the iden-
energy is the required standard. Therefore, the energy efficient standard tified CSC from this study, policy makers could be informed of the
for households will guide policy makers on the appropriate energy ef- success level of projects and the possible improvement policies to re-
ficient strategies to adopt to reduced high energy cost on household duce affordable housing overhang. Finally, the time-measurement CSC
income in addition to mitigating environmental impacts such as could be used to measure the distributional outcome of affordable
greenhouse gas emission. Concerning time measurement CSC, one of its housing for the achievement of social sustainability. One critical policy
aims is to assess the desirability of a dwelling unit among the target implication of this study is that due to high cost of implementing sus-
households [39]. A high take up rate indicates that the housing facilities tainable housing strategies to attaining the identified six components of
are desirable to the target household [82]. However, low take up rate CSC, incentives from the government could motivate real estate de-
suggests that some aspects of the housing facilities need to be improved. velopers to include energy efficient strategies and other sustainability
Measurement of the subjective CSC – quality-related CSC, household strategies in the design and construction of sustainable affordable
satisfaction CSC and stakeholder's satisfaction CSC – can be conducted housing projects.
by using a Likert scale [23]. For instance, using a five-point Likert scale
(1-not satisfied to 5- very satisfied), the satisfaction of households or Acknowledgement
stakeholders with regard to affordable housing projects could be mea-
sured. A low satisfaction score could serve as a guide to policy makers This paper forms part of a research project entitled “Affordable
that the housing facility needs to be improved. Besides, reasons for low Housing Supply: A Comparative Study between Developed and
satisfaction could serve as a guide for the construction of subsequent Developing Economies”, from which other deliverables have been
affordable housing projects. produced with different objectives but sharing common background

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