Searching for an optimal level of prefabrication in construction: An analytical
framework
Weisheng Lu1, Ke Chen2, Fan Xue3, and Wei Pan4

Abstract
Many countries or regions, in recent years, show a rising interest in prefabrication as a
“cleaner” production strategy to meet their enormous construction demand, e.g. for housing
and infrastructure. Along with this trend is the observation that many governments tend to set
forth a high level of prefabrication as a part of their ambitious construction plan. This paper
argues that unnecessarily a higher level of prefabrication is better and develops an analytical
framework for questing the optimal level of prefabrication adoption in a certain PEST
(political, economic, social and technological) background. This framework contains thirteen
PEST factors affecting the prefabrication adoption, including policy, supply, labor, social
attitude, user acceptance, and so on. These factors in combination will determine the optimal
prefabrication adoption level from 0 to 4, which was defined by Gibb 2001 to represent the
range from entire cast-in-situ construction to complete prefabricated building, respectively.
The framework was substantiated by using Hong Kong’s prominent offshore prefabrication
construction as a case. It was identified that Levels 2 and 3 are the optimal level of
prefabrication adoption subject to the current PEST background in Hong Kong. This paper
helps to clarify the prevailing misconception that “the higher the prefabrication level, the
better”. The developed framework can be used by other economies to devise their proper
prefabrication roadmaps.

1

Associate Professor, Department of Real Estate and Construction, The University of Hong Kong,
Hong Kong, e-mail: wilsonlu@hku.hk;
2
PhD Candidate, Corresponding Author, Department of Real Estate and Construction, The University
of Hong Kong, Hong Kong, e-mail: chenk726@hku.hk, Tel.: 852-64867971;
3
Research Assistant Processor, Department of Real Estate and Construction, The University of Hong
Kong, Hong Kong, e-mail: xuef@hku.hk;
4
Associate Professor, Department of Civil Engineering, The University of Hong Kong, Hong Kong,
e-mail: wpan@hku.hk;

Searching for an optimal level of prefabrication in construction: An analytical
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framework
Weisheng Lu1, Ke Chen2, Fan Xue3, and Wei Pan4

Abstract
Many countries or regions, in recent years, show a rising interest in prefabrication as a
“cleaner” production strategy to meet their enormous construction demand, e.g. for housing
and infrastructure. Along with this trend is the observation that many governments tend to set
forth a high level of prefabrication as a part of their ambitious construction plan. This paper
argues that unnecessarily a higher level of prefabrication is better and develops an analytical
framework for questing the optimal level of prefabrication adoption in a certain PEST
(political, economic, social and technological) background. This framework contains thirteen
PEST factors affecting the prefabrication adoption, including policy, supply, labor, social
attitude, user acceptance, and so on. These factors in combination will determine the optimal
prefabrication adoption level from 0 to 4, which was defined by Gibb 2001 to represent the
range from entire cast-in-situ construction to complete prefabricated building, respectively.
The framework was substantiated by using Hong Kong’s prominent offshore prefabrication
construction as a case. It was identified that Levels 2 and 3 are the optimal level of
prefabrication adoption subject to the current PEST background in Hong Kong. This paper
helps to clarify the prevailing misconception that “the higher the prefabrication level, the
better”. The developed framework can be used by other economies to devise their proper
prefabrication roadmaps.

Keywords: prefabrication; construction; analytical framework; Hong Kong

1

Associate Professor, Department of Real Estate and Construction, The University of Hong Kong,
Hong Kong, e-mail: wilsonlu@hku.hk;
2
Post-doctoral Fellow, Corresponding Author, Department of Real Estate and Construction, The
University of Hong Kong, Hong Kong, e-mail: chenk726@hku.hk, Tel.: 852-64867971;
3
Research Assistant Processor, Department of Real Estate and Construction, The University of Hong
Kong, Hong Kong, e-mail: xuef@hku.hk;
4
Associate Professor, Department of Civil Engineering, The University of Hong Kong, Hong Kong,
e-mail: wpan@hku.hk;
1

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1.

Introduction

Great challenges caused by the rising construction demand, sharp cost pressures, and
increasingly acute environmental problems have attracted extensive attention to
prefabrication in the global construction industry. In a traditional and still popular way,
construction work was built on site using “cast-in-situ” technologies characterized by fixed
jobsite, formwork and falsework, wet trades, scaffolding, and extensive waste. It was
delivered by using projects, which are a temporary organizational form that has a designed
beginning and end (Turner and Müller, 2003; Bakker et al., 2016). The basic idea of
prefabrication is to transfer a certain proportion of the construction work from the traditional
sites to factory or other manufacturing sites (Tatum et al., 1986), so it favors the way of
massive production as seen in the manufacturing industry. A construction project is
considered as prefabrication if it either uses individual prefabricated building components
(e.g. façade, staircase, and slab) or is entirely based on the assembly of prefabricated building
modules.
Particularly, prefabrication is widely considered as a way of 'cleaner production', which is “a
concept that aims at preventing the production of waste, while increasing efficiencies in the
uses of energy, water, resources, and human capital” (JCLP, 2018). Many studies have
unanimously discovered that prefabrication is a ‘cleaner’ strategy of production by having the
following benefits:


More controlled conditions for weather, quality control, improved supervision of labor,
easier access to tools, and fewer material deliveries (Construction Industry Institute,
2002);



Fewer job-site environmental impacts because of reductions in material waste, air and
water pollution, dust and noise, and overall energy costs (Lu and Yuan, 2013; Jaillon
and Poon, 2014; Tam et al., 2015; Hong et al., 2016);



Increased worker safety through reduced exposures to inclement weather, temperature
extremes, and ongoing or hazardous operations; better working conditions (e.g.
components traditionally constructed on-site at heights or in confined spaces can be
fabricated off-site and then hoisted into place using cranes);



Compressed project schedules that result from changing the sequencing of work flow
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(e.g. allowing for the assembly of components off-site while foundations are being
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poured on-site; allowing for the assembly of components off-site while permits are
being processed);


Fewer conflicts in work crew scheduling and better sequencing of crafts persons; and



Reduced requirements for on-site materials storage, and fewer losses or
misplacements of materials (Tam et al., 2015).

In view of the promising benefits of prefabrication, policy-makers (e.g. governments,
authoritative institutions) in many countries or regions have recognized prefabrication to be a
matter of course in their construction strategies. The Central Government in China, for
example, has recently set forth a ten-year goal to apply prefabrication to 30% of the domestic
newly constructed buildings (General Office of the State Council, 2016). In Singapore,
prefabricated prefinished volumetric construction (PPVC) is mandatory for selected
non-landed residential government land sale sites from 2014 onwards (Building and
Construction Authority, 2015). In Malaysia, a public project that costs over Malaysia Ringgit
(MYR)10 million or a private venture over MYR50 million is required to obtain a minimum
Industrialized Building System (IBS) score of 70 (The Edge Property, 2016). Likewise, the
Government of Hong Kong also has aggressively promoted the use of prefabrication.

In this context, a general observation is that the governments tend to stipulate a high level of
prefabrication as part of their ambitious construction plans; similar to a prefabrication “race”.
There should be an optimal level of prefabrication rather than being “the higher, the better”.
Differences in policies, regional economic developments, social or cultural background, and
technological factors all could be either enablers or barriers to the prefabrication adoption in
different economies (Murtaza and Fisher, 1994; Pan et al., 2012; Liu et al., 2017). The
combinational effects of these factors could suggest an optimal level of prefabrication that is
not necessarily high but suitable for a certain PEST (political, economic, social and
technological) context. Nevertheless, there is no such analytical method in place to articulate
the PEST factors and to examine how they will determine the optimal prefabrication level.

The aim of this paper is to develop a framework for comprehensively analyzing the optimal
level of prefabrication adoption which is suitable for a certain PEST background. In this
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paper, an ‘optimal level of prefabrication adoption’ represents the level at which
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prefabrication implementation has the optimum, overall suitability towards a certain PEST
context, and in turn, its implementation will allow achieving the optimal performance
measured by time, quality, cost, safety, environment or a combination thereof. The framework
considers thirteen factors from political, economic, social, and technological perspectives. To
offer an intelligible description of its applicability, the developed framework will be applied
to the context of Hong Kong to discuss the prefabrication adoption status therein. By doing so
this study can provide information to construction stakeholders regarding their either
grudging adoption behaviors or essentialism about prefabrication. This study is also of
relevance to policy-makers as they are keen to know the impacts a prefabrication-related
policy would exert on the regional or national development of the construction industry.

The rest of this paper is structured as follows. The research methods are outlined in Section 2.
Factors affecting prefabrication adoption in construction projects are reviewed in Section 3.
Section 4 presents a review of indicators that depict the level of prefabrication adoption.
Section 5 describes a framework for identifying the optimal level of prefabrication adoption.
Section 6 shows the analytic results of the optimal level of prefabrication adoption in Hong
Kong. The last section presents conclusions and recommendations for future research.

2.

Research methods

This study follows a four-step research design and adopts the hybrid research methods that
consist of the literature review, survey studies, focus group meetings, and interviews. In the
first step, a literature review was conducted to provide a comprehensive understanding of the
recognized factors affecting the prefabrication adoption. The authors searched representative
papers from relevant journals and conference proceedings by using the Google Scholar search
engine. Keywords used for searching included “prefab*”, “precast*”, “modular*” and
“off-site”. The title and abstract of each paper were screened to check if it is related to the
target topic. In addition, relevant white papers and industrial reports were also collected by
using the Google search engine. By doing so, a total of 35 papers and reports were qualified
for review in this study. Based on the authors’ perusal of these selected papers and reports,
factors affecting the prefabrication adoption were summarized and analyzed.
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Secondly, the authors reviewed existing measurements of the level of prefabrication adoption.
Different from the literature searching process, the information search at this step was mainly
based on the authors’ knowledge due to the relatively small amount of papers that offer the
required information. The authors comparatively analyzed both quantitative and qualitative
measurements in order to select the one suitable for this study. Debates on the definitions of
prefabrication and its measurements, as will be shown later on, are pluralistic. The authors
joined in some of the debates in conferences, writing, or other occasions meanwhile bearing
in the mind the operability of such measurements for the analytical framework to be
developed in this study. As a result, Gibb’s (2001) taxonomy and measurement is adopted.

Integrating the analytic results from the first two steps, the third step was to develop a
framework that helps to identify the optimal level of prefabrication adoption. This was
gradually shaped through three focus group meetings facilitated by the authors. The first one
was held in the Headquarters of the Hong Kong Housing Authority (HKHA), as the biggest
user and promoter of prefabrication in Hong Kong. One Swedish professor and two frontline
Swedish project managers and three senior officers from the HKHA joined the meeting. This
provides an excellent comparative perspective to developing the framework. The second
meeting was held in one of the largest precast yards in Huizhou, China, with the general
managers and engineers from the factory and academics from Hong Kong joined for a whole
afternoon discussion. The offshore factory only provides prefabricated products for
construction projects in Hong Kong. The third meeting was held in another large precast
factory in Dongguan, China, with general managers, engineers, project managers from the
main contractor, transporters and academics joined. That also provided an interesting lens
through which PEST factors and their effects on prefabrication adoption were effectively
examined.

In the fourth step, the developed framework was applied to Hong Kong to analyze the
optimal levels of prefabrication adoption in Hong Kong with particular PEST background.
The data for analysis consisted of both first- and second-hand data. The second-hand data
was sourced from the official statistics published by governmental organizations. The
first-hand data was collected through the authors’ site surveys on a public housing project
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operated by the HKHA. During the site surveys, the authors conducted interviews with a
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number of stakeholders including one government staff member, two staff members from a
main contractor, and two knowledgeable retired experts who claimed to familiar with the
whole history of prefabrication development in Hong Kong. Both first- and second-hand data
were then provided to a group of experts to evaluate the optimal levels of prefabrication
adoption in Hong Kong by using the Delphi method. Although they are discussed in sequence
here, Steps 2, 3, and 4 are actually blended together when the study was conducted. This
concurrent conduction of research activities allows an on-going triangulation of data from
different sources and finally a robust, operable analytical framework to be developed. We
have purposely “jumped out” from the specific contexts in analyzing the general factors and
developing the framework, although a close link to the specific PEST context has never been
disconnected.

3.

Factors affecting prefabrication adoption

Many researchers have initiated studies about the identification and analysis of factors
affecting the prefabrication adoption. In this study, a factor that has been mentioned by at
least two papers was deemed as a major one. Based on the literature review, a total of thirteen
factors were identified as the major ones affecting the prefabrication adoption in an industrial
setting (See Table 1). These are broad factors falling into political, economic, social and
technological categories.

Table 1 Summary of factors affecting prefabrication adoption
Political

Economic

Social

Technological

Factor

Times being mentioned

Policy

18

Standards, codes and guidelines

10

Supply

22

Schedule

15

Type and scope

11

Repetitive components

10

Labor

15

Social attitude

9

User acceptance

14

Resources

12
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Familiarity

15

Construction tolerances

7

Site logistics

12

Political factors
The political factors include Policy and Standards, codes and guidelines. Policy has been
regarded as the major factor that would directly raise the incentive of the prefabrication
adoption (e.g. Blismas, 2005; Jiang et al., 2017). Murtaza and Fisher (1994), Kamar et al.
(2009), and Liu et al. (2017) have found that, under some circumstances, Policy can
effectively encourage the prefabrication adoption by offering financial incentives if a project
has achieved certain requirements in using prefabrication. In addition, the authoritatively
designed Standards, codes and guidelines are important in the sense of guiding clients,
designers, contractors, and suppliers to fluently practice their prefabrication adoption
processes (Smith, 2016).

Economic factors
The major economic factors include Supply, Schedule, Type and scope, and Repetitive
components. The demand and supply of prefabricated components and associated materials
affect prefabrication adoption as they are the necessary condition for maintaining a smooth
process of production and on-site construction (Pan et al., 2012; CII, 2012). The adoption of
prefabricated components would unavoidably change the project Schedule as well as logistics
(Li et al., 2017). Thus, when making decisions on the prefabrication adoption, one would
consider the supply- and schedule- related issues (e.g. the need of a long lead time when the
manufacturing factories are far away from the construction site) (Pan et al., 2007).

Type and scope of projects directly determine what type of and how many prefabricated
components could be used (Gerth et al., 2013). Whether projects use Repetitive components is
also important because, if it is the case, the use of prefabrication in such projects can gain
benefits from the “economy of scale” than projects falling in the otherwise case and do not
have bulk orders if using prefabrication (Chen et al., 2010; Bildsten, 2011). Similarly, for
small-scope projects or uniquely designed buildings, as they generally involve a quite small
number of repetitive components, it could be difficult and infeasible for them to adopt
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prefabrication.
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Social factors
The major social factors include Labor, Social attitude, and User acceptance. Labor is a
major factor that affects the prefabrication adoption (e.g. Chiang et al., 2006; Wong et al.,
2017). While it might reduce the required traditional manpower, particularly carpenters and
concreters, the use of prefabrication generally would lead to the demand of skilled labors for
the machine operation, transporting, lifting, on-site assembly of prefabricated components,
connecting the prefabricated components with the in-situ ones, etc. (Chiang et al., 2006). The
lack of expertise of these trades in the market would significantly impede the prefabrication
adoption.

About Social attitude, prefabrication has long been considered as monotonous design without
much flexibility (Alinaitwe et al., 2006), which may reduce end-users’ enthusiasm toward
prefabrication. As a result, prefabrication has been traditionally adopted in social housing,
wherein end users have no much choice unfortunately. The market for prefabricated
construction could be affected if there is no continuous improvement and innovation of
prefabrication technology to satisfy diversity and personality requirements of consumers (Luo
et al., 2015).
User acceptance refers to the attitude of client. Researchers generally agree that the client’s
opinion on prefabrication would practically determine the final level of prefabrication
adoption in a project (e.g. Gibb and Isack, 2003; Zhai et al., 2013). The clients’ less
confidence in prefabrication or misinterpretation on its benefits and risks has been found to
constrain the prefabrication adoption (Kamar et al., 2009). For example, Liu et al. (2017)
have found that the clients’ higher awareness of the potentials of prefabrication is positively
related to the actual prefabrication adoption in their projects.

Technological factors
The technological factors include Resources, Familiarity, Construction tolerances, and Site
logistics. Resources, such as production and installation machines, have a close relationship
with the quality of the prefabricated components (Song et al., 2005). Familiarity refers to the
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experience that organizations have learned from its previous project using prefabrication
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(Azhar et al., 2013). Some studies point out that some contractors are reluctant to adopt
prefabrication since they are already familiar with the conventional method of in-situ
construction (e.g. Azhar et al., 2013; Rahman, 2014).

Construction tolerances refer to the tolerances of quality for the project. Luo et al. (2015)
pointed out that, in situations where there is a lack of skilled workers, the risks such as
sealing joints might come along with the assembly of prefabricated components. Thus, for
projects that only the high installation precision is acceptable (i.e., with small construction
tolerances), stakeholder might be inclined to the traditional construction methods instead of
using the prefabrication (Luo et al., 2015).

Finally, compared with the traditional cast-in-situ method, the prefabrication construction
seems to be facing greater challenges in Site logistics. A congested site could constrain the
use of prefabricated components, especially for those large-sized, heavy ones (Azhar et al.,
2013). In addition, when planning the site arrangement in a prefabricated construction project,
it should be considered that the lifting of prefabricated components would need heavy lift and
the site transport equipment with higher capacities than before (Pan et al., 2012).

4.

Measuring the level of prefabrication adoption

Measuring the level of prefabrication adoption is largely inconclusive in terms of definitions,
approaches, and results. The measurements can be perceived from two generic categories:
quantitative and qualitative. Quantitative measurements are employed by both scholarly
papers and regulations in some economies. For example, Alinaitwe et al. (2006) suggested
that the level of prefabrication adoption can be measured by the ratio of value of work done
on site to off site. Wong et al. (2008) used the approximate percentage of the off-site
production among all construction components. Hong et al. (2016) proposed a “prefabrication
rate” that is derived from the adopted prefabrication volume over the total volume of building
materials. The Construction Industry Development Board (CIDB) of Malaysia also
introduced a scoring mechanism of the IBS to measure the level of prefabrication adoption.
An IBS score is calculated by summing up the score of structural systems, the score of wall
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systems, and the score of all other simplified construction solutions (CIDB, 2004).
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Quantitative measurements could offer a clear, index-style understanding of the portion of
prefabrication in overall construction. They can also be an independent variable to produce
the quantitative links to other construction-related variables, e.g., to measure how much
energy consumption can be saved when using prefabrication to a certain extent (Hong et al.,
2016). However, using the value or volume relating to prefabrication alone as the
measurements could be problematic in some situations. For example, consider two
prefabricated projects, one using a certain volume of precast façades and the other using the
same volume of precast bathroom. If the total volume of the materials used in these two
projects were the same, they would have the same prefabrication rate. However, this rate
clearly cannot reflect the real situation.

Qualitative measurements also prevail. Gibb (2001), for example, proposed a five-level
taxonomy of prefabrication adoption. In Gibb’s (2001) taxonomy, Level 0 means a project
does not use any form prefabrication at all, e.g. fully cast-in-situ; Level 1: Component and
sub-assembly (e.g. lintels); Level 2: Non-volumetric assembly (e.g. 2-dimensional precast
concrete wall panels, precast components with no usage space enclosed); Level 3: Volumetric
assembly (e.g. volumetric bathrooms, kitchens with usable space enclosed); and Level 4:
Modular building (e.g. 3-dimensional modules which form the fabric of the building
structure). Similarly, Steinhardt et al. (2014) introduced a six-level taxonomy, in which
Levels 0 to 5 represent none, prefabricated trusses and beams, prefabricated structural panels,
specialized pods, modules, and fully completed houses delivered to site respectively.
Likewise, Goodrum et al. (2009) and Sierra and Zamora (2013) introduced their qualitative
measuring taxonomies in different levels, and in different terms.

Qualitative measurements cannot represent the amount of prefabrication used, but they can
tell what kind of prefabrication is adopted. Hence, qualitative measurements are more
suitable than their quantitative counterparts to describe which type of prefabrication is fitting
into a certain PEST background. The taxonomy proposed by Gibb (2001) is used as the
measurement of prefabrication adoption in this study owing to two reasons: (1) it is a
widely-known qualitative measurement that has been introduced to the industry for over 15
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years; (2) it helps to clearly identify the level of prefabrication adoption that has been
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achieved based on the types of prefabricated components used.

5.

The framework to search for the optimal level of prefabrication adoption

Each level of the prefabrication adoption has its own strengths and weaknesses in comparison
with the conventional construction method subject to a certain context. Given a context in
which only a low level of prefabrication adoption would be suitable, the use of prefabrication
at a high level might be confronting a loss due to that constrains from the contextual factors
as listed above. Therefore, it is proposed that there should be an optimal level of
prefabrication suitable to a certain context that is characterized by various PEST factors. This
is the major proposition of this paper (See Figure 1), which is based on reflections from the
three focus meetings described in Section 2. The horizontal axis is the different levels of
prefabrication adoption, in this particular study, adopting Gibb’s (2001) taxonomy. The
vertical axis is the suitability of adopting a certain level of prefabrication. The inverted
U-shaped curves mean that for a certain context there is an optimal level of prefabrication
adoption. A too low or too high level means the overall performance of prefabrication
implementation could be negatively affected owing to the supports and constraints imposed
by the PEST factors associated with the particular context. For example, for Context A, to
pursue a Level 3 prefabrication (i.e. volumetric assembly, such as volumetric bathrooms,
kitchens with usable space enclosed) needs strong design expertise, manufacturing capability,
and also the sufficient hoisting power that might not be readily accessible. Instead, a Level 2
(i.e. non-volumetric 2-dimensional precast concrete wall panels, precast components) might
be more suitable.

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Figure 1 A conceptual illustration of the optimal level of prefabrication adoption in different
contexts

Based on the proposition, the analytical framework for determining the optimal level of
prefabrication adoption is developed (See Figure 2). The left-hand side of the framework
illustrates that the PEST factors altogether affect a certain level of prefabrication to perform.
The right-hand side of the framework illustrates how the framework can be applied in
real-life scenario analyses. Subject to a given Context X, the application of the analytical
framework involves three steps. At the first step, the Delphi method is adopted to ask a group
of experts to give an evaluation of potential support or constraint of each factor to a certain
level of prefabrication adoption. The Delphi method used the first step, in a sense, is to remap
these experts’ knowledge from their mind. This is because, from the focus group meetings as
introduced in Section 2, the authors found that experienced experts tended to put the PEST
context as an overall background and were more aware of the supporting or constraining
influence of the entire context, instead of individual PEST factors, on levels of prefabrication
adoption. Thus, in Round 1 Delphi, the experts are asked to mark “++”, “+”, “0”, “-”, “--” for
each PEST factor regarding individual prefabrication adoption levels by using the form in
Figure 2. These five signs denote “strong support” (scores 2), “moderate support” (scores 1),
“neutral” (scores 0), “moderate constrain” (scores -1), and “strong constrain” (scores -2)
respectively. For example, marked “++” to P1 for Level 4, it indicates that this expert
12

considered the current policy strongly supporting the use of module building (i.e., Level 4).
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Then, in Round 2 Delphi, experts are asked to reassess their evaluation in the light of the
consolidated results from Round 1. The statistical technique of Kendall’s coefficient of
concordance could be used to assess the degree of consensus arrived by all experts (Ameyaw
et al., 2016). With significant consensus, the ‘correct’ evaluation results, i.e., the signs of
individual PEST factors, were regarded as being attained (Rowe and Wright, 1999).

At the second step of framework application, the overall suitability of individual
prefabrication adoption levels for that given Context X is measured by summing up the signs
of all PEST factors. At the third step, values of the overall suitability of the five
prefabrication adoption levels are plotted and linked to form the curve. Based on the curve,
the optimal level of prefabrication adoption fitting Context X can be identified.

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Figure 2 The analytical framework for questing the optimal level of prefabrication adoption

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A case of Hong Kong

To illustrate how the analytical framework is implemented, and to add to the debates on an
optimal prefabrication level, a case study was conducted in Hong Kong. Prefabrication is
hardly new to the construction industry in Hong Kong. With a 30-year’s development under
the Government’s strong promotion, prefabrication has been widely implemented in buildings,
especially public housing projects. By the end of March 2016, there were 1.5 million units of
private housing, 0.79 million units of public rental housing, and 0.40 million units of
subsidized housing (Transport and Housing Bureau, 2016a). Prefabricated components are
widely used in the construction of public housing blocks for better workmanship and quality
control and to maximize construction efficiency (HKHA, 2017a).

Data about the Hong Kong’s PEST factors were collected from the official statistics,
publications, reports, and site surveys. For some factors, such as user acceptance and
resources, the officially-published data is triangulated with data collected from site surveys
for corroboration. The data were then analyzed by a group of 6 local experts (See Table 3)
using the Delphi method as introduced in Section 5. For simplified and concise presentation,
the sign of each PEST factor for a certain prefabrication adoption level is the one marked by
most experts rather than the mean value from all experts. The results are summarized in
Figure 3(a) and plotted to form the curves in Figure 3(b). The Kendall’s coefficient of
concordance of 0.779 (p_value=.000 for the significance level of 0.05) indicates that the
statistically significant agreement among the experts has been arrived. As shown in Figure
3(b), Levels 2 and 3 are the most optimal level of prefabrication adoption in the current PEST
background of Hong Kong.
Table 3 Profile of the experts participated in the evaluation
No.

Position

Years of experience in prefabrication

1

Project manager of a government agency

21

2

Senior engineer of a private developer in Hong Kong

15

3

Senior engineer of a leading main contractor in Hong Kong

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Technical director of a leading main contractor in Hong Kong

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Professor of a Hong Kong local university

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Associate Professor of a Hong Kong local university

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Level 0

Level 1

Level 2

Level 3

Level 4

(Cast in-situ)

(Component and (Non-volumetric (Volumetric

(Modular

sub-assembly)

assembly)

assembly)

building)

P1

-

+

++

++

++

P2

++

++

+

+

-

E1

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+

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+

E2

0

0

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E3

-

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++

++

++

E4

-

+

++

++

++

S1

--

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0

+

-

S2

+

0

0

0

0

S3

+

+

+

+

0

Technological (T) T1

+

+

+

+

+

T2

+

+

+

+

0

T3

++

++

+

0

0

T4

++

+

-

-

--

4

9

12

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5

Political (P)

Economic (E)

Social (S)

Total scores

Kendall’s coefficient of concordance = 0.779;
p_value = .000;
significance level = 0.05.
Notes: “++” means strong support (scores 2); “+” means moderate support (scores 1); “0” means neutral
(scores 0); “-” means moderate constrain (Scores -1); and “--” means strong constrain (scores -2).

(a)

(b)
Figure 3 Evaluation results of the optimal level of prefabrication adoption in Hong Kong
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The evaluation results can be better interpreted by connecting them with qualitative
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discussions on the PEST factors in Hong Kong.

P1: Policy
Figure 3(a) shows that P1 strongly supports the prefabrication adoption in Hong Kong. Such
evaluation results are consistent with the fact that the Hong Kong Government has been
taking an active role in promoting the use of prefabrication through public policies. In the
2016 Policy Address, the Government highlighted that prefabrication will enhance the
standardization of project design, promote mechanization and construction. The HKHA has
introduced the use of precast secondary members such as secondary beams, slabs, and
external facades in its public housing projects since the mid-1980s. Precast façade has been a
mandatory requirement for all standard domestic blocks of public housings (Construction
Industry Review Committee, 2001). For private sector projects, the Government of Hong
Kong promotes the use of prefabrication by providing the gross floor area (GFA) concession.
Specifically, in 2001 and 2002, Joint Practice Notes (JPN) 1 and 2 were issued by
government departments, respectively. According to the JPNs, building developers could
receive GFA concession if they adopt prefabrication or other green building technologies.
JPNs indeed have provided incentives to private developers about adopting prefabrication in
their projects.

P2: Standards, codes and guidelines
Prefabricated construction projects, like other construction projects in Hong Kong, must obey
the Buildings Ordinance (CAP 123) and several complementary regulations. To provide
particular information about the design, construction and quality control in prefabrication
projects, the Building Department (BD) published the “Code of Practice for Precast Concrete
Construction” (hereafter called “the CoP”) in 2003 and an updated version in 2016 to (BD,
2016). The Hong Kong Institution of Engineers (HKIE) also published a precast concrete
construction handbook to elaborate the Code on major concerns and adopts the same
paragraphing of the Code for easy referencing (HKIE, 2015). The existence of standards,
codes, and guidelines is particularly important for construction, including prefabrication,
which will be bewildering if without such. However, guidelines for implementing
prefabricated volumetric units are currently in absence in the context of Hong Kong.
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adoption in Hong Kong.

E1: Supply
Most precast concrete suppliers to construction projects in Hong Kong have set up their
fabrication yards in the Pearl River Delta (PRD) such as Huizhou and Shunde in Guangdong
Province, China (Lu, 2013). The considerable number of public housing projects in Hong
Kong helps to maintain a stable demand for prefabricated components. The highly efficient
road and water transportation network between Hong Kong and the PRD facilitate the
delivery of prefabricated components. Figure 4 shows one of the major transportation route,
about 130 miles, from fabrication yards to Hong Kong. A 2.5m width limit of the
prefabricated components to be transported is set based on the capacity of trucks (Mak, 2013).
The transportation is generally carried out by third-party logistics companies which own
trucks, trailers (See Figure 5) and even transshipment warehouses. The relatively long
distances between suppliers and construction sites require much attention about preventing
the prefabricated components from damages.

Figure 4 One of the major transportation routines from fabrication yards to Hong Kong
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Figure 5 The truck and trailer

E2: Schedule
The public housing projects of HKHA follow a six-day cycle (Mak, 2013). Although the
interviewed government staff member admitted that a four- or five-day cycle could be
achievable, a six-day cycle is suitable for the current practice due to the availability of tower
crane and other resources. The six-day cycle also allocates time in advance for the production
of the prefabricated components until they can be accumulated to sufficient numbers for
delivery to site for installation. Comparatively, the private sector projects normally do not
follow a six-day cycle; they accomplish a cycle as fast as possible. Combined the difference
in the schedules of public and private sector projects, E2 is assessed to moderately support
the prefabrication adoption in Hong Kong.

E3: Type and scope
The public housing project in Hong Kong generally has a standardized layout with symmetry
in design. Such standardized layout is suitable for the adoption of prefabricated components.
In comparison, the private sector projects are unique in design and could face more design
changes during the construction process. The feature of design in private projects could
hinder the use of prefabrication for maintaining design flexibilities. However, Hong Kong has
been operating a prominent public housing sector for decades. Recently, the Government set
a housing supply target of 460,000 units for the next ten-year period from 2016-17 to
2025-26, with a public-private split of 60:40 (Transport and Housing Bureau, 2016b). The
considerable stock of public housing units could be an important reason why E3 is considered
to strongly support the prefabrication adoption in Hong Kong’s construction industry as a
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E4: Repetitive components
Explanations for the strong support of E4 shown in Figure 3(a) are similar to those for the
positive effects of E3. In 2008, in line with the principle of “functional and cost-effective”
design, the HKHA has developed a new library of “modular flat design” covering several
types of flat units for mass production in public housing projects (See Figure 6). Designers of
the selected public projects can follow these standard modular flats to draw building blocks
that are suitable for different site configurations. The module flat design results in the use of
may repetitive components in the public housing projects. Thus, the benefit of mass
production can be leveraged.

Figure 6 Standardized flat units of public housing in Hong Kong (LegCo 2015)

S1: Labor
The labor shortage is a problem plagued Hong Kong’s construction industry for long. The
Construction Industry Council (HKCIC) (2016) has forecasted a shortage of up to 15,000
skilled workers for the next few years in Hong Kong. Actually, one of the initial thoughts
about promoting prefabrication is to alleviate the labor shortage in several trades such as
formwork and bar bending, by exploiting the relatively cheaper manpower, material, and land
in adjacent cities such as cities of the Pearl River Delta in Mainland China. The prominent
economic development in Mainland, however, have raised challenges to the development of
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increased greatly, making the set-up of precast yards gradually unaffordable. On the top of
these labor issues, there is always a lack of skilled workers on the erection of prefabricated
building structures, making it difficult to transfer to the complete use of prefabricated
modular units in one step (Li et al., 2017).

S2: Social attitude
The effects of S2 on Levels 2 and 3 of prefabrication adoption are assessed to be neutral.
These results imply the importance of the general education to the public about the benefits
of prefabrication. In Hong Kong, the public used to have limited understandings about the
promotion of prefabrication. This might cause an unfavorable impression of prefabrication to
the public of Hong Kong. If the public could be more aware of the potentials of
prefabrication, such as allowing the sustainable design, construction, and operation of
buildings, they may become more willing to consume buildings constructed by prefabricated
components.

S3: User acceptance
S3 is assessed to moderately support the prefabrication adoption in Hong Kong. The HKHA
has been the pioneer in adopting prefabrication and contributed to the major prefabrication
innovations. Various types of prefabricated components such as precast façade, precast
staircase, precast panel wall and semi-precast slab are widely-adopted in public housing
projects. Precast ground floor water tank and volumetric precast bathroom are also accepted
in some of these projects (HKHA, 2017a). For the public sector, facades units are the most
common prefabricated components used in Hong Kong’s construction industry. In addition,
the non-structure prefabricated wall is more acceptable to private sectors since its usage can
receive GFA concession.

T1: Resources
The moderate support of T1 to the prefabrication adoption in Hong Kong is related to the
particular structure of the local construction industry. Hong Kong’s construction industry is
structured by a few number of large contractors and a great number of small companies
working as subcontractors. The large contractors in Hong Kong own heavy machines and are
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financially resourceful in adopting prefabrication in their projects. In Contrast, most of Hong
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Kong’s subcontractors are small in size (Hong Kong Trade Development Council [HKTDC],
2016) and in a lack of recourses for adopting prefabrication. In addition, some large
contractors have a tight bond with subcontractors who are afraid of losing their jobs after
shifting construction process to prefabrication (Mak, 2003). These issues are believed to be
the obstacle for increasing the prefabrication adoption in Hong Kong construction projects.

T2: Familiarity
Explanations for the effects of T2 on Hong Kong’s prefabrication adoption are similar to
those for the effects of T1. In Hong Kong, a few large contractors have been adapting their
skills and expertise to the use of prefabrication, especially those participating in public
housing projects. With the gained experience, these contractors can more effectively arrange
the installation and handle the collaboration between prefabrication and in-situ concreting
components (Tam et al., 2015). However, prefabrication is still technologically unfamiliar to
the majority of local contractors. Most of them might have experienced projects using a few
types of prefabricated components such as precast slabs, facades, and staircases, but have less
experience in more complex prefabrication system that could be more complicated in
arrangement and installation.

T3: Construction tolerances
In order to meet the requirements of construction tolerances, the quality of both production
and installation must be controlled. The Housing Department follows the Buildings
Department’s requirements on quality control and supervision of prefabrication production in
Mainland (Legislative Council [LegCo], 2017). However, when more complicated
prefabricated components (i.e., Levels 3 and 4) are used, it is relatively difficult to control the
quality of installation since there is no much regulative mechanism on controlling the
standard and quality of workmanship. In addition, since technical issues about structural
supporting have not been fully addressed, the prefabricated structural components may not
able to be effectively used in construction projects. Thus, effects of T3 on the Levels 2 and 3
of prefabrication adoption are assessed to be moderate support and neutral, respectively

T4: Site logistics
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site in Hong Kong is in the congested urban area and will become even congested since both
storage and pre-installation handling of prefabricated components require extra working
space. The congested environment makes access and delivery of heavy prefabricated
components to the work spot become difficult (Jaillon and Poon, 2014). Workers have to
conduct installation at high altitude under very congested floor layout. The limited space for
site logistics generally constrains the use of heavy prefabricated components, such as precast
water tank and bathroom, in many construction sites in Hong Kong.

7.

Discussions and conclusions

Prefabrication has great potential to overweigh conventional construction methods in many
aspects. Nevertheless, prefabrication is not a cure-all solution that automatically promises
shortened construction time, lower construction cost, as well as other benefits, without due
consideration paid to a PEST context that supports or constrains its implementation. This
study argues that the optimal level of prefabrication is produced by bounded up forces from
PEST factors. This argument, however, has not been well recognized by some strategic
decision-makers, particularly of emerging construction markets, in devising their
prefabricated construction development plans. These strategic decision-makers often intend
to make ambitious plans about setting forth high, sometimes unrealistically high, levels of
prefabrication adoption in construction markets of cities, regions, or countries.

In espousing this argument, this study developed an analytical framework to analyze a PEST
background and determine the optimal level of prefabrication under this background.
Thirteen PEST factors, including Policy, Standards, codes and guidelines, Supply, Schedule,
Type and scope, Repetitive components, Labor, Social attitude, User acceptance, Resources,
Familiarity, Construction tolerances, and Site logistics, were identified based on the literature
review and interviews with the industrialists. These PEST factors provided sound directions
for determining the optimal level of prefabrication adoption in a certain context. It is also
suggested to use the analytical framework periodically to examine the dynamic changes in
PEST factors in a certain context and their implications on the appropriate prefabrication
adoption level. This is because that the PEST conditions of an economy would rarely be static
but change as time elapses, though the change may not be radical within a short term (e.g. 3-5
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To illustrate the applicability of the proposed framework, the framework was substantiated in
Hong Kong, a place known for a high-rise, high-density built environment, as a case. This
case vividly showed that Levels 2 and 3 of prefabrication adoption are the most suitable to
Hong Kong’s current PEST context. The framework can also be used by cities, regions or
countries that have low-rise construction projects for rationalizing their prefabrication
construction strategies. That is, the framework is not meant to be a closed system and its
included factors should not be considered unchangeable. More studies are encouraged to
further refine the PEST factors and evaluation tools of the framework.

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