30420130403003

International Journal of Industrial Engineering
INTERNATIONAL JOURNAL4, Research and Development ENGINEERING
OF INDUSTRIAL (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume Issue 3, September - December (2013), © IAEME
RESEARCH AND DEVELOPMENT (IJIERD)

ISSN 0976 – 6979 (Print)
ISSN 0976 – 6987 (Online)
Volume 4, Issue 3, September - December (2013), pp. 30-49
© IAEME: www.iaeme.com/ijierd.asp
Journal Impact Factor (2013): 5.1283 (Calculated by GISI)
www.jifactor.com

IJIERD
©IAEME

AN AHP MODEL FOR MATCHING LEAGILE STRATEGIES FOR
THE OFF-SITE MANUFACTURE IN AUSTRALIA
Sherif Mostafa1 and Jantanee Dumrak2
1

(PhD Candidate/Staff, School of Natural and Built Environments, University of South
Australia, City East Campus, GPO Box 2471 Adelaide SA 5001, Australia)
2
(Lecturer, International Institute of Business and Information Technology (IIBIT),
Federation University, Adelaide, South Australia 5000, Australia)

ABSTRACT
Australian housing supply has not been responsive commensurately to the growing
demand. The residential sector challenges this issue by actively developing and effectively
using new materials, processes, and practices to strengthen their competitive advantage against
other construction sectors. Three main factors affecting the housing supply and demand are
house completion time, cost of finished house, and customer preferences. The best current
solution could be introducing the lean and agile concepts to manage the off-site manufacture
(OSM) house building supply chain. In this paper, four strategies are introduced to balance the
trade-offs between the housing supply and demand. This study presents an example on
matching the strategies with the imbalance factors in the Australian house building using
Analytical Hierarchy Process (AHP). The AHP model was developed using Expert Choice©
software package. The results from the AHP model show the benefits of each strategy with
respect to each factor tested.
Keywords: Australian Housing; OSM; Leagile Strategies; Customer Order Decoupling Point,
AHP.
I. INTRODUCTION
The construction industry is a key economic component of Australia. The productivity
of the industry has been continuously expanding. It was accounted for 7.7 per cent of the
country’s gross domestic product (GDP) with the gross value added (GVA) reached AUD
30

International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 3, September - December (2013), © IAEME

102 billion in the financial year 2010-2011 [1]. Australian construction industry includes the
private and public sectors that are engaged in three broad activities; residential building, nonresidential building, and engineering construction. In Australia, the residential building
contributed significantly to the national economy with the overall production value as
reported at AUD 47 billion in 2010 and 2011. The Australian residential sector involves
many independent building organisations to construct separate houses and other residential
buildings including semi-detached houses, townhouses, flats, units and apartments.
Nevertheless, the values of work commenced in residential building are likely to be less
responsive to the growth of other construction activities [1]. This situation may be influenced
by housing supply and demand factors. The housing supply has been found not keeping in
pace with the housing demand as reported by [2, 3].
Some studies have examined the shortage of housing supply situation [2,4,5,6]. These
studies focus mainly on housing demand side rather than the housing supply challenges [7].
This paper, therefore, addresses the undersupply of the Australian housing from both housing
supply and demand perspectives. The housing supply should be considered as a chain
containing all house building stakeholders. Lack of coordination between the stakeholders and
management of this chain may lead to housing shortage [8]. Three main factors contributing to
the Australian housing supply and demand imbalance are been identified in this paper. The
factors are house price, house completion time and house customisation. The off-site
manufacture (OSM) is a modern method of construction which involves two working sites:
off-site factory and onsite construction. Elnaas, Gidado, and Ashton [9] highlight the key
themes of decision factors to OSM. Time, quality and cost were the highly important themes
for adopting OSM in UK. Some studies in Australia focus on the OSM uptake in house
building and develop new housing technologies in home building [10-13]. It has been revealed
that the opportunities of OSM in Australia are centred on detached housing, high-density
multi-residential complexes, and public facilities such as hospitals, schools, and prisons [14].
It is suggested that some manufacturing concepts such as lean and agile can and should
to be transferred to house building production [15, 12]. Selecting an appropriate strategy to
meet specific housing house supply and demand requires a systematic selection process. This
study, additionally, associates four leagile strategies to manage the two working sites of the
OSM supply chain. The suggested strategies are Make to Stock (MTS), Make to Order (ATO),
Design to Order (DTO), and Self-building Houses (SBH). The strategies aim to improve the
overall performance and competitiveness of the Australian housing sector.
The aim of this article is to identify the main factors contributing the imbalance of
housing supply and demand, and to match the four leagile strategies with housing supply
factors to improve the house building performance in Australia. The analytic hierarchy process
(AHP), a multiple-criterion decision making (MCDM) approach developed by Saaty[16], is
employed to form the analysis and deliver the most suitable strategy from the obtained data.
AHP serves as a framework for prioritising the four leagile house building strategies with
respect to the studied three factors. This article is structured into seven consecutive sections.
After the introduction, the second section reviews the related literature to Australian housing
supply and demand, lean, agile and leagile concepts, and OSM house building supply chain.
Section three explains the four leagile house building strategies and the related case studies.
The fourth section summarises the research methodology. The fifth section introduces the
proposed AHP model which is applied to study four strategies using data obtained from the
five largest house builders in five Australian states. The sixth section discusses the results
delivered by the AHP model. In the final section, the research conclusion is given with
recommendations for further research.
31


II. LITERATURE REVIEW
II. I. FACTORS AFFECTING THE AUSTRALIAN HOUSING SUPPLY AND
DEMAND
The Australian housing supply does not respond adequately to the growing demand
especially in capital cities [2]. This situation has been confirmed by the housing industry
alliances such as the National Housing Supply council (NHSC), Housing Industry Association
(HIA), and Master Builders Australia [17]. The latest report on Housing to 2020 produced by
ers
HIA [5], indicates the gaps between underlying demand and supply in housing over the
periods until 2020 ranging from low-, medium-, and high-build rate scenarios as presented in
low
build
Fig.1.
It can be seen from all build rate scenarios that the gaps between demand and supply
do exist. It is forecasted that in 2016 the difference between demand and supply will reach
543,300, 372,100 and 213,200 dwellings in low, medium and high build rate respect
respectively. At
the year 2020, the expected shortage of dwellings will be 808,900, 500,900, and 214,700
respectively. According to a report of NHSC [3], delivering capacity of the public sector in
housing supply will sharply decline in the near future as the recent housing outputs evidently
recent
decrease from the units produced in the last decades. The Australian housing undersupply is
influenced by both housing supply and demand factors. The three main factors include house
price, house completion time, and house cus
customisation.

Figure 1. Projected dwelling shortage at national level
II.I.I. HOUSE PRICE
The house price refers to residential construction costs, taxes on new housing and land
release [7,3]. House price is a critical element determining the new housing construction [7].
housing
In Australia, house prices have increased in all locations at similar rate of growth [2, 18].
According to the Australian Future Tax System (AFTS) report, the median house prices have
risen from three times compared to the average household income in 1990 to around five times
household
in 2010 [19]. The house price includes land price and construction costs (material and labour
costs) [7]. The Housing Supply and Affordability Reform (HSAR) states that the growth of
house prices is driven by the increase in the prices of established houses [2]. However, AFTS
crease
[19] views that the construction costs are responsible for a higher proportion of the increase in
32


house prices in some regions. The study of Liu and London [7] explore the relationship
between new housing supply and construction costs in Australia. Their study concludes that
construction costs are a key component of the poor performance of the Australian new housing
supply.
II. I. II. HOUSE CUSTOMISATION
Customer preferences reflect customising the house design to suit house customer
needs. The preferences may vary from person to person based on the residential desirability
and acceptability. Customer preferences include the design and location of a house [20]. The
house design includes the internal (floor area) and external (façade width) design for the
house. The average floor area of the Australian dwellings has been increased. The average
floor area of new detached houses increased from 162.4 square meters to 248.0 square meters
from 1984 to 2009. Whereas, new other residential dwellings increased from 99.2 square
meters to 140.8 square meters [21]. It is evident from an examination of volume builders that
double-story houses and more complex street facing façades have increased [22].
II. I. III.HOUSE COMPLETION TIME
The house completion time is a key factor indicating the quality of housing delivery to
house customers. The house completion time can be defined as the time period between the
first and last physical building activities to produce a house and make it ready for occupation
[17]. The average Australian house completion time has increased while the production rate
has been relatively stable [4]. The average Australian house completion time rose from 1.8
quarters to 2.4 quarters from 2000 to 2008 [23]. Dalton et al. [17] identify three factors that
might explain the lengthening of house completion time. The first factor is the construction
method to manage all activities within house building processes. It also includes coordination
and scheduling between the stakeholders as house building is generally delivered through a
chain of stakeholders Therefore, building a house needs a successful construction method for
meeting the planned schedule to deliver the house. The second factor is concerned with the
level of skilled labour which affects the quality of a finished house. Most of the house builders
employ quality assurance systems. Nevertheless, they have undergone a poor quality record
[17]. The construction managers and supervisors have to arrange with the contractors and subcontractors for remediate defects. The remediation extends the planned construction time of
the house. The third factor is the number of houses under construction. The study of Gharaie,
Wakefield, and Blismas [24] shows a positive correlation between the number of houses under
construction and completion time.
II.II. OFF-SITE MANUFACTURE
Off-site manufacture (OSM) is a modern method of construction which has been
adopted to improve the performance of house building industry [25]. It refers to the production
of house components in an off-site factory as well as their subsequent activities in a
construction site [26]. OSM provides several benefits to all stakeholders involved in the house
building process [10]. It improves onsite safety by providing cleaner and tidier environment to
the construction site as well as enhances quality of the house components under factory
production. Moreover, OSM reduces environmental effects by reducing waste generation,
shortening lead time and increasing the efficiency and productivity [27-29]. There are four
categories of OSM based on the degree of off-site works including component manufacture
and sub-assembly, non-volumetric pre-assembly, volumetric pre-assembly, and modular
building [30,31] as shown in Table 1.
33


Table 1. Four categories of OSM.
Level Category
Definition
Component manufacture Items always made in a factory and never considered
1
and sub-assembly
for onsite construction (e.g. door furniture, windows)
Non-volumetric
pre- Pre-assembled units which do not enclose usable space
2
assembly
(e.g. cladding wall panels, structural frames)
Pre-assembled units which enclose usable space and are
typically fully factory finished internally, but do not
3
Volumetric pre-assembly
form the buildings structure (e.g. toilet pods, shower
rooms)
Pre-assembled volumetric units which also form the
4
Modular building
actual structure and fabric (e.g. prison blocks, motels)
In Australia, some studies positively address the OSM. For instance, the Construction
2020 report suggested OSM as a key vision for improving the construction industry [11. Two
research projects carried out by Blismas[10]and Manley, Mckell, and Rose [32] reveal the
future of OSM in the Australian built environment. The findings of the two projects confirmed
that OSM has capability to produce high-volume, high-quality houses based on the
efficiencies of the manufacturing principles.In spite of the benefits of the OSM, the factory
physical production has several forms of non-value added activities or wastes. Ohno[33]
enumerate seven forms of waste commonly found in factories physical production are overproduction, waiting time, transportation, over-processing, excessive-inventories, defective
products, and unnecessary movement. Moreover, the customisation of prefabricated house
makes the design specifications become more complex. Such complexity leads to slower
response to achieve customer requirements. Three emerging challenges for a construction
organisation derive from the management of two working locations simultaneously. The first
challenge is the broken junction between the off-site and on-site activities. The second is the
jumbled on-site processes due to difference between the production flow at off-site factories
and construction flow on-site. The third challenge is the vague demands from unclear
customers [34].
Some attempts have been made to address the shortcomings of OSM house building by
adopting successful concepts from the manufacturing industry to house building [13],
particularly in lean and agile concepts [35-38]. Lean and agile can manage the OSM supply
chain as it does in manufacturing [39]. The combination of lean and agile is known as leagile.
In this paper, four leagile strategies are proposed to manage the OSM supply chain as
discussed in section three.
II. III. AHP FOR MATCHING LEAGILE STRATEGIES WITH IMBALANCE
HOUSING FACTORS
It is contended that the housing supply and demand factors mentioned in the prior
sections influence on the shortage situation of Australian housing. Moreover, these factors
impact on the selection of house building supply chain strategies. To identify the solutions that
can improve the housing shortage situation, AHP is suggested. AHP is a suitable application
where the goal and the set of potential criteria and alternatives are made available [40]. AHP is
a multiple-criterion decision making (MCDM) developed by Saaty[16] which takes into
account of qualitative and quantitative judgements. AHP can be applied by using Expert
34


Choice© software. The software has advantages including a user friendly environment, an
evaluation of inconsistency index of assessments, and a sensitivity analysis of results. The
AHP approach assists in evaluating and ranking the leagile strategies of OSM supply chain
with respect to the factors.
AHP has widely utilised in many multiple criteria situations including operations
management decisions based on customer requirements, construction contractor selection,
supplier selection process, improving construction productivity, identifying design
development factors in Australian public-project-partnership projects, new product
development and infrastructure projects with social impact [41- 47].AHP facilitates the
decision making process by constructing a hierarchical model presenting the integrated levels
of the problem from the goal to alternatives [48]. AHP includes two basic components. The
first component contains pairwise comparisons among all elements (e.g. criteria, sub criteria,
and alternatives) at all levels of the model to make decision on various alternatives. The
second component is a synthesis and a ranking of the model elements in order to identify the
key elements of the decision making problem [49].
AHP has been used in the construction and house building industry. For instance,
Wang et al. [42] use AHP to weight the decision criteria for selecting the best value
contractors of two construction projects in Taiwan. Doloi[44] uses AHP to examine the causes
of the poor productivity of construction workers in some building construction projects in
Melbourne. Wang and Pan [50] propose an AHP model for spotting the factors affecting using
industrialised house in Wuhan cityin China. Their model comprised four factors government,
enterprise, custom and market. However, the model was not included any strategy for
overcoming the impacts caused by these factors.
In this study, AHP is employed to match the four leagile strategies with the three main
factors contribute to the Australian housing imbalance. The goal (selecting appropriate house
building strategy) is stated and the set of criteria (housing supply and demand imbalance
factors) and alternatives (four leagile strategies) are determined. The house building activities
from commencing the house building until the house is completed and ready for occupation
are in focus. It is because, in the Australian housing context; the number of dwellings
completed is less than number of dwellings commenced [1, 51]. Therefore, this paper
identified the main factors influence Australian housing imbalance situation and associates the
factors with the four suggested strategies.
III. LEAGILE STRATEGIES FOR OSM HOUSE BUILDING SUPPLY CHAIN
Three approaches to operate a supply chain are lean, agile, and Leagile [52]. Lean
approach was first developed in the Toyota production system (TPS). Lean is an integrated
socio-technical system comprising of management practices that can be applied to eliminate
the waste [53]. Lean thinking as an application into the construction environment was first
discussed by Koskela in 1992 [54]. A transformation-flow-value concept of production has
been developed as a new perspective to improve the construction performance [55]. According
to the concept, the construction production consists of three corresponding processes: a
transformation of materials into standing structures, a flow of the materials and information
through various production processes and a value creation for customers through the
elimination of value loss [56].
Agile concept, on the other hand, became popular in 1991. Sharifi and Zhang [57] state
that new competitive environment is a key driver for changes in the manufacturing industry.
The competition qualities are continuous improvement, rapid response and quality
35


improvement. The initiative of agile construction was established in direct response to the
Latham Report published in 1994 [58]. The report highlighted the UK construction industry
requirement to reduce the construction cost by 30 per cent by the year 2000. To achieve this
target, the whole industry needed to change. Benchmarking has been a method used to
stimulate the required change in the construction practices [58]. Naim et al. [38] suggest the
employment of agile principles in the construction supply chains to achieve profitable
opportunities in dynamic markets. Agile construction exemplifies the characteristics of
visibility, responsiveness, productivity and profitability [59].
The integration of lean and agile is the best solution to answer all the production issues
in the world class market competition [60]. Combining lean and agile within the whole supply
chain can be accomplished by using the decoupling point (DP). It is known as leagility. The
leagility term was firstly introduced byNaylor, Naim, and Berry [61]. In general, the DP
separates the leagile supply chain into lean in the upstream and agile in the downstream
[62].For market competition, Christopher and Towill [52]emphasise that supply chains must
be responsive to market demand changes which can be divided into three critical dimensions;
variety, variability (or predictability) and volume. Lean concept is the best alternative where
there are high volume, low variety, and low predictable change environment. On the contrary,
agile concept is the best option where there are high variety, low volume, and high predictable
change environment. The real demand visibility is limited in most supply chains. The supply
chains may be lean prior to DP and agile beyond DP.
There are two DPs in the leagile supply chains [52]. The first DP is the material DP
which should ideally lie as far down stream as possible to be close to the final marketplace.
The second DP is the information DP which should lie as far upstream as possible in the
supply chain. Agility beyond the decoupling point is explained by the principle of
postponement using a generic or modular inventory to postpone the final commitment whilst
the final assembly or customisation depends on real demand. Leagile supply chain has
capabilities to achieve the house customer value through different strategies in accordance
with the DP positions. The leagile house building supply chain mainly focuses on waste
removal and responsive mechanisms through applying the excellence lean and agile
practices.The studies of Childerhouse et al. [53] and Naim and Barlow [15] focus on using the
material DP in the UK house building supply chain. In this paper, the leagile house building
supply chain employs the customer order decoupling point (CODP) or order penetration point
which encompasses both information and materials. The material DP is the stocking point of
finished house modules or components. The information DP is the point where the customer
demand enters the value chain.
The four strategies suggested for leagile house building supply chain are demonstrated
in Fig.3. Two supermarkets have been included. The first supermarket stores the house
elements and lies between supplier and off-site factory. The second supermarket holds the
finished house modules and lies between the off-site factory and construction site. Kanban is
used to smooth the flow of manufacturing and construction activities [63]. Kanban is an
information and material movement system used to define the type and quantity of parts
between processes [64]. The Withdrawal Kanban (WK) is used to authorise movement of
material from the two supermarkets while the Production Order Kanban (POK) is used
replenish the two supermarkets. Four alternative positions for the CODP which are proposed
to be employed in Australian house building supply chain.

36


Figure 3. Four leagile strategies of OSM house building supply chain

III. I. MAKE TO STOCK (MTS) STRATEGY
In MTS strategy, CODP is located after the on-site construction activities and finished
house building. This strategy is commonly known as ‘specs’. The houses are designed and
built ‘speculatively’ based on the builders’ catalogue [17, 38]. Customers have a choice
selection from the available houses based on the location, cost, size, and design. It is found in
Barlow and Ozaki [65] that 25 per cent of new houses in Japan are speculative houses. The
house customers have less or no choice over the house specifications and designs. The market
winner in this strategy is the lower finished house selling price. Panelised house building
designed by Monarch Building Systems presented in Blismas [10] is another example of the
MTS strategy. The house panels are produced and utilised as standard panels in the company’s
building projects. With the MTS strategy, the company can ensure its capacity to serving
large-size accommodation projects within the contracted timeframe. Therefore, the activities
before selling should be lean to fit the costs. Agile is located after the CODP to diminish the
delivery time and to meet the customer satisfaction and the speed of return on investment
(ROI) [35].
III. II. ASSEMBLE TO ORDER (ATO) STRATEGY
In ATO strategy, CODP is positioned at the off-site factory. The customer houses are
built according to the builder’s catalogues. A variety of house designs are included in the
catalogues. Customers have a degree of customisation to select a combination of ‘specs’ to
match their demands. The customers can add extra features to their own kitchen, bathrooms,
external living area, as well as upgrade standard items such as windows and doors[17]. The
house builders’, then, perform the construction activities on-site and assembles the selected
modules to complete the house. Two examples of ATO demonstrated in a work of Höök and
Stehn [37] are from Swedish construction companies. In the first example, the strategy has
37


been employed in construction of official and commercial buildings. The second example
targets at developing standard modules for multi-family dwelling and students lodgings. Both
companies emphasise on encouraging their customers to select building designs within their
existing catalogues. Another example of ATO strategy is given in Pan and Goodier [27] from
the UK house builders. Classic private house builders are claimed offering their customers
with an alteration in house configuration based on the site and geographical areas. The market
winners in this strategy are the house pricing and designs of house modules, and the
completion time. It is suggested for the ATO strategy to employ lean within the off-site
factories. Agile should be employed in stages of shipments and on-site construction to ensure
more responsiveness in delivering the houses.
III. III. DESIGN TO ORDER (DTO) STRATEGY
In the DTO strategy, the customer demand enters the value stream at the design stage.
Therefore, customers have a relatively high degree of customisation. They can specify the
design of their own house modules. They have the flexibility to change the predesigned
modules to fit their needs. In Japan, about 75 per cent of new detached houses are built on the
existing land owned by the house owners. These new houses are designed based on the
standard floor plan, but provides the house owner with flexibility to any degree of
customization [65]. An example of the DTO strategy comes from Australian experience
demonstrated inBlismas [10]. The construction procedure assimilated to the DTO strategy was
chosen to build Prep classrooms in the State of Queensland. The design team was obliged to
deliver specific features to be incorporated to the modules. Thus, a mock-up and two
prototypes were prepared prior to the module production. The modules were, then, produced
according to the approved design. The market winner in this strategy is high customisation.
Therefore, the house building stages require a combination of lean and agile. Lean is suitable
for supplying the material and running the off-site factories whilst other related activities need
to be more agile.
III. IV. SELF-BUILDING HOUSE (SBH) STRATEGY
The final strategy is SBH. This strategy is suitable for the self-building houses which a
homeowner is intimately involved in every aspect of the house building. This strategy is
developed on a similar concept of the house building and the personal computer assembly
[15]. The Australian houses are built by small to large organisations. In 2009, the largest 100
builders commenced approximately 37 per cent of all residential dwellings [17]. Sixty-three
per cent of all residential dwellings were constructed either by small builders or in the form of
self-building houses. In Victoria State, the Department of Human Services [66] introduces
group self-build initiative to support individuals to build their own houses. The group usually
consists of 12 homes within or nearby area. Each group of participants receives a bridging
loan from the director of housing to purchase land and build their houses. The customers are at
their own responsibilities to hire an architect for house designing and builders to assist them
with some onsite construction activities. Likewise, the self-building houses model has been
adopted in the UK housing sector where approximately 20 per cent of total housing supply is
delivered by the house owners with(out) an outsourcing contract for design and built (D&B)
[67]. In this strategy, the key role of house building organisations is to supply the house
modules and components to the suppliers. House building organisations should aim at making
the house assembly as simple as possible. The organisations should provide variable designs to
meet different types of house needs. Lean is suitable to run the house modules factory while
agile is the best option for quick responses to demands of self-build house suppliers.
38


IV. RESEARCH METHOD
The use of AHP in this study was to design the model combining the suggested four
leagile house building strategies and the key factors contributing to the housing undersupply in
Australia. This included selecting and scrutinising a number of possible criteria. Data and
information were collected from various resources related to the Australian housing including
peer reviewed journals, references books, websites, and Australian housing authorities
including National Housing Supply Council (NHSC), Housing Industry Association (HIA),
Australian Bureau of Statistics (ABS), Australian Housing and Urban Research Institute
(AHURI), and Council of Australian Governments (COAG). The collected materials were
carefully examined and allocated reference number. After that, the possible factors (criteria
and sub-criteria) affecting the imbalance between housing supply and demand in Australia
were determined.
After the AHP model constructed, pairwise comparisons were used to rate all child
elements with respect to the parent element according to nine point scale developed by Saaty
[16]. The validity of the pairwise comparisons process was performed using the AHP
consistency test. This process was carried out through the determination of inconsistency
index of the pairwise comparisons which could be calculated in the Expert Choice© software.
In general, the Consistency Ratio (CR) less than 0.1 indicates a satisfactory degree of
consistency [68]. The new set of acceptable CR values has been modified by Saaty [69] where
the values work in association to the size of the matrix. For a 3×3 matrix, 4×4 matrix and
larger matrices the CR value should be 0.05, 0.08 and 0.10 respectively. Afterwards, the AHP
priorities were generated using the Expert Choice© software. The local priorities were
synthesised from the goal while the overall priorities were calculated. The relative weights
were used to identify the key factors (criteria and sub-criteria). Moreover, the overall rating of
the four house building strategies was determined. After that, a series of sensitivity analyses
were performed in the Expert Choice© software to investigate the impact of changing the
importance of the criteria on the overall rating of the four strategies.
V. ILLUSTRATIVE EXAMPLE
V. I. THE AHP MODEL
The AHP approach began with constructing the model of the decision problem. The
first level was set as the goal of the model. The second level consisted of the three selected
criteria: (1) house completion time; (2) house price; and (3) house customisation. Each
criterion was further subdivided into eight sub-criteria. The three sub-criteria under house
completion time were number of houses under construction, shortage of skilled labour, and
construction method. Whereas, two sub-criteria were located under house price construction
material and labour costs. Three sub-criteria came under house customisation; house floor
area, house location, and façade width. The four strategies were placed at the bottom level of
the hierarchy as decision alternatives. After setting all elements of the AHP model, the model
was developed usingExpert Choice© as shown in Fig.4
V. II. FOUR LEAGILE STRATEGIES
The imbalance between the housing supply and demand has occurred in all Australian
states and territories (COAG, 2012; NHSC, 2012). The Housing 100 Report for 2013
presented the Australia’s the most active 100 builders (HIA, 2013). Their main housing
activities contributed around 75 per cent of the housing supply for detached houses and multi39


unit apartments. In this paper, the top five potential builders of supplying houses in five
Australian States Western Australia (WA), South Australia (SA), New South Wales (NSW),
Victoria (VIC), and Queensland (QLD) were analysed as shown in Table 2.
The five selected potential builders were capable of adopting the four leagile strategies.
This adopting capacity was enhanced by their house building work in the five states, market
share, decision making and the future trends during the period of 2011-2013 [5, 22] (HIA,
2011, 2013). Selecting a strategy depends on the situations of house market in Australia.
Demand of house customers’ shapes the housing market. Therefore, the builders can respond
to house market changes by adopting the suitable strategy. For example, the builders might
have to build small floor plan house, less customised and with medium price for the Australian
low income groups (increase the housing affordability). This combination could lead to the
employment of one or more strategies proposed in this paper. The Australian medium income
groups might prefer to select house elements and design from the available designs in the
builders’ catalogues. In this case, a suitable strategy for this situation must be carefully
determined. The customers have ability to change the house design to fit their needs.
Therefore, customers are likely to be involved in designing all house elements. Therefore, the
four strategies proposed can cover different customers’ demands. The strategies allow house
builders to make decision to tailor their house building activities. The weightings of the
criteria and sub-criteria for each strategy were performed through a comparison when a
builder employs each strategy. The weighting criteria and sub-criteria for the four strategies
are demonstrated in Table 3.
V. II. I. PAIRWISE COMPARISONS OF THE MODEL ELEMENTS
Pairwise comparisons were performed to associate the relationships between all
elements at all levels of the AHP model. The three criteria were compared with respect to their
importance to the goal. Under each criterion, the sub-criteria were compared according to their
importance to the criterion. All pairwise numerical comparisons were performed in the expert
choice software. The Saaty’s scale allows to compare each two elements in the hierarchy using
verbal or numerical judgments as equally (i.e., has a weight of 1), moderately (i.e., has a
weight of 3), strongly (i.e., has a weight of 5), very strong (i.e., has a weight of 7), extremely
(i.e., has a weight of 9). The intermediate values are used where appropriate as equally to
moderately (i.e., has a weight of 2), moderately to strongly (i.e., has a weight of 4), strongly to
very strongly (i.e., has a weight of 6), very strongly to extremely (i.e., has a weight of 8) [70,
16] (Armacost, Componation, Mullens, & Swart, 1994; Saaty, 1980).
An example of pairwise comparison between MTS and ATO strategies respect of
houses under construction is demonstrated in Fig.5. The data of each comparison is displayed
in a matrix form (e.g. 4×4 matrix in Fig.5). The number of each cell in the matrix represents
the relation between two compared elements with respect to the parent element. In Expert
Choice, the black coloured numbers means that the criterion on the left hand side is relatively
more important than the criterion on the right hand side. Whereas the red coloured numbers
appears, it means the criterion on the right is relatively important than the criterion on the left.
After completing the pairwise comparisons, all priorities of the AHP model were calculated as
shown in Table 4.

40


Figure 4. proposed AHP model for selecting OSM house building strategy

Table 2. Top five Australian house builders attribute [22] (HIA, 2013)
Builder A
HIA top 100 2012/2013

1

st

Builder B
2

nd

Builder C
rd

Builder D
th

Builder E

3

4

5th

WA

WA,VIC

SA, VIC, NSW,
QLD

QLD,VIC,
SA

VIC, SA,
QLD

Builder

Builder and
developer

builder

Builder and
developer

Builder

Houses starts during 2013

3443

3199

2837

2432

1692

House market share

13%

12%

10.7%

9.2%

6.4%

Number of models

224

102

60

56

36

States
House building activity

41


Table 3. Leagile strategies’ weighting in each criterion and sub-criteria
A1: MTS

A3: DTO

A4: SBH

Low

C1: House customisation

A2: ATO
Moderate

Very high

High

Small floor
area
Flexible
location

Larger floor
area
More
flexible

Suitable for
any floor
area
Highly
flexible
ModerateHigh

C1.1:

House floor area

C1.2:

House location

Small floor
area
Fixed
location

C1.3:

Façade options

Limited

Medium

Large

C2: House price

Low price
range

Moderate
range

High
range

LowModerate
range

Low
Low

Medium
Medium

High
High

low
low

Short

Moderate

Long

ModerateShort

Few

Moderate

Many

Favourable
Medium
labour
intensive

Favourable
Medium to
High labour
intensive

Neutral
Medium to
High labour
intensive

Few
Very
favourable
Requires
less labour
force

C2.1:
C2.2:

Construction material cost
Labour cost
C3: House completion time

C3.1:

Number of houses
construction

C3:2

Construction method

C3:3

Level of skilled labour

under

Figure 5. Example of pairwise comparison of two strategies

42


Table 4. Weighting of the criteria, sub-criteria and alternatives
Alternatives (strategies)
ATO

DTO

MTS

SBH

Total Priority
of criteria
and subcriteria

Construction method (0.333)

0.011

0.006

0.011

0.039

0.067

Level of skilled labour (0.333)

0.008

0.005

0.017

0.036

0.066

Number of houses
construction (0.333)

0.009

0.005

0.022

0.03

0.066

House completion time (Total Priority)

0.028

0.016

0.05

0.105

0.199

Façade width (0.260)

0.012

0.034

0.009

0.049

0.104

House floor area (0.413)

0.032

0.016

0.078

0.039

0.165

House location (0.327)

0.016

0.035

0.008

0.073

0.132

0.06

0.085

0.095

0.161

0.401

Labour costs (0.333)

0.013

0.012

0.039

0.069

0.133

Material costs (0.667)

0.05

0.022

0.122

0.073

0.267

House price (Total Priority)

0.063

0.034

0.161

0.142

0.400

Total Priority of alternatives

0.151

0.135

0.306

0.408

Criteria

House
completion
time

House
customisation

Sub-criteria

under

House customisation (Total Priority)
House price

For the house completion time criterion, the sub-criteria had the same priority of 0.333.
The house customisation sub-criteria priorities were 0.26 for façade width, 0.413 for house
floor area and 0.327 for house location. The house price sub-criteria were rating as 0.333 for
the labour costs and 0.667 for the material costs. The priorities of the criteria with respect to
the goal were calculated. House customisation received the highest priority with 0.401,
followed by house price with 0.400 and house completion time with 0.199. The inconsistency
index of the judgements was checked to ensure that it is lower than or equal 0.1. Finally, the
ranking of the four strategies were calculated with respect to the sub-criteria under each
criterion. The weightings of the sub-criteria in each strategy were decided on each strategy
adopted by the five builders (see Table 3).
V. II. II. SYNTHESISING THE RESULTS
After pairwise comparisons, the local priorities were synthesised from the goal while
the overall priorities were calculated. The overall priorities of the four house building
strategies are displayed in Fig.6. The distributive mode was selected. From the test results, the
SBH strategy was considered as the best alternative which received the highest rating of 0.407.
The second best strategy was MTS which scored 0.306, followed by ATO with a score 0.151.
The last one was the DTO strategy with a score of 0.136.

43


Figure 6. Overall priorities of alternatives in distributive mode
VI. RESULTS AND DISCUSSION
The sensitivity analysis was performed to examine the change results occurred in the
priorities of the criteria. A performance summary of each house building strategy interacting
with the three factors is shown in Fig.7. Overall, it is projected that the self-build housing
(SBH) strategy was considered as the best strategy. However, SBH did not perform as the best
strategy on individual criteria. It can be seen from Fig.7 that SBH strategy performed its best
in house customisation and house completion time factors while it ranked the second on house
price factor. On the other hand, the MTS strategy individually performed its best in house
price.

Figure 7. Performance sensitivity graph of house building supply chain strategies

44


VI. I. THE MAIN CRITERIA FOR STRATEGY SELECTION
The priorities of importance for criteria and sub-criteria under each strategy are
presented in Table 4. The house customisation criterion which consisted of sub-criteria, façade
width, house floor area, and house location, obtained the highest score of importance (0.401).
The second most important criterion was the house price with the score of 0.4. House price
contained labour costs (0.133) and material costs (0.267) sub-criteria respectively. On the
other hand, house completion time projected as the third important criterion with the score of
0.199. Under this criterion, construction methods (0.067), level of skilled labour (0.066) and
number of houses under construction (0.066) were tested.
It can be concluded that house customisation and house price were the most significant
criteria for strategy selection according to data obtained in this research from five major
builders in Australia. The results provided a clear-sighted on the factors affecting the
Australian housing delivery which could lead to the implications and decision making of the
house builders based on house customers’ demand. The house completion time, house
customisation, and house price are directly affected by the builder strategy to complete a
house. The adoption of the leagile strategies will support the uptake of OSM and enhance the
house deliver.
VI. II. IMPLICATIONS OF THE MODEL FOR HOUSE BUILDING DECISION
The results from the examination of the proposed AHP model indicated that SBH
strategy performed most effectively along the three factors. The SBH strategy could be
suggested to the Australian house builders based on the research results that the strategy was
the most suitable for the different combinations of the three factors. Furthermore, the results of
scenarios demonstration is supported by the AHURI report undertaken by Dalton et al. [17]
that 63 per cent of the Australian residential dwellings in 2009 were constructed by small
builders or in the form of self-building houses. According to the case study of the state of
Victoria presented earlier, a group self-build initiative was introduced to support individuals
building their own houses. A key role of OSM in Australia is to supply variety of house
modules and components to house-module suppliers so that OSM could meet the different
types of house needs. The SBH strategy is the best in achieving minimum house cost which
enhances the house affordability for the low- and medium-income Australians.
According to the research results, the MTS strategy ranked the second from overall
alternatives. This strategy could be used for mass house building projects where the builders
may have to complete the project within the contract timeframe. Nevertheless, this research
showed that the MTS strategy was the last alternative for house customisation in the model. A
major drawback of the MTS strategy derives from low/none house customisations. The
strategy may be suitable only for the construction of standard house designs.
VII. CONCLUSIONS
The Australian house building sector has experienced continuous growth and unmet
housing demand. The house customisation, house cost and completion time add more
complexities to the design specifications. Furthermore, customer demands are ambiguous and
dynamically changed. The four strategies have been proposed in this paper to answer the
different situations of demand and balance the trade-off between house builders and
customers. This study was carried out using the AHP model to facilitate the selection of the
OSM strategies with respect to the three main factors contributing to the imbalance of
housing supply and demand in Australia.
45


For future research, more house builders and housing undersupply factors can be added
to the current study. This may include other factors such as coordination and scheduling
among the stake holders, land supply, and demographic factors (e.g. economic circumstances
of household, number of overseas migrations). It is important to understand the effects caused
by these factors in order to improve the housing delivering system. These nominated criteria
have been addressed in the Australian housing supply and demand literature. Therefore, the
future study could conduct surveys with the Australian house building experts (e.g. house
builders, residential developers, architects, and house owners) in order to verify or to refine the
model. Questionnaire and interview surveys may need to be designed using the proposed AHP
model.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]

[13]

ABS, 2012 Year Book Australia. Canberra, ACT: Australian Bureau of Statistics,
2012.
COAG, Housing Supply and Affordability Reform. Canberra ACT, Australia:
Council of Australian Governements, 2012.
NHSC, Housing Supply and Affordability: Key Indicators, Canberra ACT, Australia:
National Housing Supply Counci, 2012.
E.Gharaie, House Completion Time in Australia: Workflow Planning Approach.
(Doctor of Philosophy), RMIT University, Melbourne, Australia, 2011.
HIA, Housing to 2020 : The states of Australian housing to the year 2020, Campbell
ACT, Australia, Housing Industry Association Economics Group, 2011.
NHSC, Housing supply and affordability issues 2012-13. Canberra, National Housing
Supply Council,2013.
J. Liu, and K. London, Analysing the Relationship between New Housing Supply and
Residential Construction Costs with Regional Heterogeneities,Australasian Journal of
Construction Economics and Building, 11(3),2011, 58-67.
K. London, and J. Siva, Housing Supply Chain Model for Innovation Research
Report. Melbourne, Victoria: Australian Housing Supply Chain Alliance members,
2011.
H. Elnaas, K. Gidado and P. Ashton, Factors and Drivers Effecting the Decision of
Using Off-Site Manufacturing (OSM) Systems in House Building Industry, Journal
of Engineering, Project, and Production Management, 4(1), 2014, 51-58.
N. Blismas, Off-site manufacture in Australia: Current state and future directions.
Brisbane, QLD: Cooperative Research Centre for Construction Innovation, 2007.
K. D.Hampson, and P. Brandon, Construction 2020-A Vision For Australia's
Property And Construction Industry. Brisbane, QLD: CRC Construction Innovation,
2004.
PATH, Technology roadmap: whole house and building process redesign, one year
progress report, In Prepared for US Department of Housing and Urban Development
(Ed.), Partenership for Advanced Technology in Housing. Washington DC, USA:
Office of Policy Development and Research, 2002.
PATH. (2003). Technology roadmap for manufactured housing, In Prepared for US
Department of Housing and Urban Development, Partenership for Advanced
Technology in Housing, New York, USA: Office of Policy Development and
Research, 2003.
46


[14] N. Blismas, and R. Wakefield, Drivers, constraints and the future of offsite
manufacture in Australia,Construction Innovation: Information, Process,
Management, 9(1), 2009, 72-83.
[15] M. Naim, and J. Barlow, An innovative supply chain strategy for customized housing.
Construction Management and Economics, 21(6), 2003, 593-602. doi:
10.1080/0144619032000134129.
[16] T. L. Saaty, The analytic hierarchy process : planning, priority setting, resource
allocation. (London McGraw-Hill International Book Co., 1980).
[17] T. Dalton, R. Wakefield, and R. Horne, Australian suburban house building: industry
organisation, practices and constraints, Australian Housing and Urban Research
Institute Positioning Paper Series, 2011, 1-56.
[18] R. Fox, R., andR. Finlay, Dwelling Prices and Household Income, In Reserve Bank
of Australia , Sydney, Australia, 2013.
[19] AFTS, Australia’s future tax system: Report to the Treasurer, Attorney-General’s
Department,Barton ACT, Australia,2010.
[20] NHSC, Key findings of the 2011 State of supply report, Canberra ACT, National
Housing Supply Council, 2011.
[21] ABS, Building Approvals, Australia. Canberra ACT, Australian Bureau of Statistics,
2010.
[22] HIA, Housing 100 : Australia’s Largest Homebuilders and Residential Developers
2012/2013, Campbell ACT, Housing Industry Association, 2013.
[23] ABS, Average quarterly completion times for new houses, Building Approvals,
Australia, Canberra ACT, Australian Bureau of Statistics, 2008.
[24] E. Gharaie, R. Wakefield, and N. Blismas, Explaining the Increase in the Australian
Average House Completion Time:Activity-based versus Workflow-based Approach,
Australasian Journal of Construction Economics and Building, 10(4), 2010, 34-49.
[25] W. Nadim, W., Modern Methods of Construction, In A. G. Akintoye, Jack.; Zawdie,
Girm (Ed.), Construction innovation and process improvement (Chichester, West
Sussex, U.K. : Wiley-Blackwell, 2012) 209-233.
[26] K. Russell, S. Kanjanabootra, C. Ouyang, and M.T. Wynn, Procuring OSM: base-line
models of off-site manufacture business processes in Australia, 16th Pacific
Association of Quantity Surveyors Congress-Innovation and Sustaining: Challenges
and Opportunities, Darussalam, Brunei, 2012.
[27] W. Pan, and C. Goodier, House-building business models and off-site construction
take-up,Journal of Architectural Engineering, 18(2), 2011, 84-93.
[28] V. W. Y. Tam, C. Tam,and W. C. Y. Ng, On prefabrication implementation for
different project types and procurement methods in Hong Kong,Journal of
Engineering, Design and Technology, 5(1), 2007, 68-80.
[29] X. Zhai, R. Reed, and A. Mills, Factors impeding the offsite production of housing
construction in China: an investigation of current practice, Construction Management
and Economics, 2013, 1-13.
[30] A. Gibb, and F. Isack, (2003), Re-engineering through pre-assembly: client
expectations and drivers. Building Research & Information, 31(2), 2003, 146-160.
[31] A. Gibb, Off-site fabrication: prefabrication, pre-assembly and modularisation
(Latheronwheel, Whittles, 1999).
[32] K. Manley, S. Mckell, and T. Rose, Innovative Practices in the Australian Built
Environment Sector: An Information Resource for Industry, Brisbane, Australia,
2009.
47


[33]
[34]
[35]
[36]
[37]
[38]
[39]
[40]
[41]
[42]
[43]
[44]
[45]
[46]
[47]
[48]
[49]
[50]
[51]

T. Ohno, T., Toyota production system: beyond large-scale production (Portland, OR:
Productivity Press, 1988).
A.S. Chang, and K.P. Lee, Nature of construction technology, Proceedings of the 12th
Annual Conference of the IGLC, Copenhagen, Denmark, 2004.
P. Childerhouse, S.M. Hong-Minh, and M.M. Naim, House building supply chain
strategies: selecting the right strategy to meet customer requirements, Proceedings of the
8th Annual conference of the IGLC, Brighton, UK, 2000.
S.D. Green, S. Fernie, and S. Weller, Making sense of supply chain management: a
comparative study of aerospace and construction, Construction Management and
Economics, 23(6), 2005, 579-593.
M. Höök, and L. Stehn, Applicability of lean principles and practices in industrialized
housing production, Construction Management and Economics, 26(10), 2008, 1091-1100.
M. Naim, J. Naylor, and J. Barlow, Developing lean and agile supply chains in the UK
housebuilding industry, proceedings of the 7th Annual Conference of the IGLC,
Berkeley, 1999.
C. Vidalakis, J.E. Tookey, and J. Sommerville, Demand uncertainty in construction
supply chains: a discrete event simulation study, Journal of the Operational Research
Society, 64(6), 2013, 1-11.
O. Bayazit, Use of AHP in decision-making for flexible manufacturing systems, Journal
of Manufacturing Technology Management, 16(7), 2005, 808-819.
E. Hofmann, and S. Knébel, Alignment of manufacturing strategies to customer
requirements using analytical hierarchy process,Production & Manufacturing Research,
1(1), 2013,19-43.
W. C. Wang, W. D. Yu, I. T. Yang, , C. C. Lin, , M. T. Lee, and Y. Y. Cheng, Applying
the AHP to support the best-value contractor selection – lessons learned from two case
studies in Taiwan, Journal of Civil Engineering and Management, 19(1), 2013 24-36.
F. T. S. Chan, Interactive selection model for supplier selection process: an analytical
hierarchy process approach, International Journal of Production Research, 41(15), 2003,
3549-3579.
H. Doloi, Application of AHP in improving construction productivity from a management
perspective, Construction Management and Economics, 26(8), 2008 841-854.
P. Raisbeck, , and L. C. M. Tang, Identifying design development factors in Australian
PPP projects using an AHP framework, Construction Management and Economics, 31(1),
2012, 20-39.
F. Steinberg, and R. Woll, Application of analytical hierarchy process to support selection
of difficult-to-quantify characteristics in new product development, Total Quality
Management & Business Excellence, 24(7-8), 2013, 797-810.
M. Álvarez, A. Moreno, and C. Mataix, The analytic hierarchy process to support
decision-making processes in infrastructure projects with social impact, Total Quality
Management & Business Excellence, 24(5-6), 2012, 596-606.
A. B., Borade,G. Kannan, and S. V. Bansod, Analytical hierarchy process-based
framework for VMI adoption, International Journal of Production Research, 51(4), 2012,
963-978.
Chan, H. K., & Wang, X., Fuzzy Hierarchical Model for Risk Assessment (Springer
London, 2013).
Q. Wang, and S. Pan, On Influence Factors of Wuhan Housing Industry Based on the
AHP. Systems Engineering Procedia, 3(0), 2012 158-165.
ABS, Building Activity, Australia, Jun 2013, Building Activity, Australian Bureau of
Statistics, Canberra, Australia, 2013.
48


[52]
[53]
[54]
[55]
[56]
[57]
[58]
[59]
[60]
[61]
[62]
[63]
[64]
[65]
[66]

[67]
[68]
[69]
[70]

M. Christopher, and D. R. Towill, Supply chain migration from lean and functional to
agile and customised. Supply Chain Management: An International Journal, 5(4), 2000,
206-213.
R. Shah, A. Chandrasekaran, andK. Linderman, In pursuit of implementation patterns: the
context of Lean and Six Sigma,International Journal of Production Research, 46(23),
2008, 6679-6699.
A. Mossman, Why isn’t the UK construction industry going lean with gusto? Lean
Construction Journal, 5(1), 2009, 24-36.
L. Koskela, Application of the New Production Philosophy to Construction, CIFE,
Stanford University, Stanford, CA, 1992.
S. Bertelsen, Bridging the gap–towards a comprehensive understanding of lean
construction, Proceedings of the 10th Annual Conference of the IGLC, Gramado, Brazil,
2002.
H. Sharifi, and Z. Zhang, A methodology for achieving agility in manufacturing
organisations: An introduction. International Journal of Production Economics, 62(1),
1999, 7-22.
S. Lee, The Agile Peformance Improvement Databse: A tool to improve construction
performance, School of Management, University of Bath, 2003.
P. Daneshgari, Agile Construction : Impact of Project Resource Management on Profits,
IEC Insights, 2009, 10-12.
A. Agarwal, R. Shankar, and M.K. Tiwari, Modeling the metrics of lean, agile and leagile
supply chain: An ANP-based approach., European Journal of Operational Research,
173(1), 2006, 211-225.
B. J. Naylor, M. Naim, and D. Berry, Leagility: Integrating the lean and agile
manufacturing paradigms in the total supply chain, International Journal of Production
Economics, 62(1–2), 1999, 107-118.
R. Mason-Jones, and D. R. Towill, Total cycle time compression and the agile supply
chain, International Journal of Production Economics, 62(1), 1999, 61-73.
R. Arbulu, G. Ballard, and N. Harper, Kanban in construction, Proceedings of the 11th
Annual Conference of the IGLC, Blacksburgh, VA, 2003.
L. H.Forbes, and S. M. Ahmed, Modern construction: lean project delivery and integrated
practices ( Boca Raton, FL: CRC Press, 2011).
J. Barlow, and R. Ozaki, Building mass customised housing through innovation in the
production system: lessons from Japan, Environment and Planning A, 37(1), 2005, 9-20.
Department of Human Services, Group Self Build, Housing and Community Building,
Housing & Community Building: Finance & Business Services.Retrieved 1/2/2013, 2013,
from
http://www.dhs.vic.gov.au/for-individuals/housing-and-accommodation/home-ownersupport/group-self-build, 2011.
D. Marshall, D. Worthing, N. Dann, and R. Heath, The construction of houses (5th Edition
edn. Oxon: Routledge, 2013).
T. L. Saaty, How to make a decision: The analytic hierarchy process, European Journal
of Operational Research, 48(1), 1990, 9-26.
T. L. Saaty, How to Make a Decision: The Analytic Hierarchy Process, Interfaces, 24(6),
1994, 19-43.
R. L. Armacost, P. J.Componation, M. A.Mullens, and W. W. Swart, An AHP framework
for prioritizing customer requirements in QFD: an industrialized housing, IIE
Transactions, 26(4), 1994, 72-79.

49

30420130403003

Recommended

Recommended

More Related Content

Viewers also liked

Viewers also liked (6)

Similar to 30420130403003

Similar to 30420130403003 (20)

More from IAEME Publication

More from IAEME Publication (20)

Recently uploaded

Recently uploaded (20)

30420130403003