The Pacific (Asia) Association of Quantity Surveyors

Motivational Factors & Benefits ofGreen Building Developments

Final Report

Submitted on 10th April 2019

Prepared by:Isabelle Chan, University of Hong Kong
Mei-yung Leung, City University of Hong Kong

Contents
1. Background ......................................................................................................................... 1
2. Systematic Literature Review .............................................................................................. 1
2.1 Influencing Factors .................................................................................................................... 1
2.1.1 Industrial‐level factors ........................................................................................................... 1
2.1.2 Project‐level Factors .............................................................................................................. 3
2.2 Outcomes of Green Building Developments ............................................................................ 4
2.2.1 Tangible Outcomes ................................................................................................................ 4
2.2.2 Intangible Outcomes .............................................................................................................. 4
3. Survey Design ...................................................................................................................... 4
4. Sample................................................................................................................................. 5
5. Findings ............................................................................................................................... 7
5.1 Factors affecting Green Building Projects................................................................................. 7
5.1.1 Industrial‐level Factors........................................................................................................... 7
5.1.2 Project‐level Factors .............................................................................................................. 9
5.2 Tangible and Intangible Outcomes of Green Building Projects .............................................. 11
5.2.1 Tangible Outcomes .............................................................................................................. 11
5.2.2 Intangible Outcomes ............................................................................................................ 14
5.3 Regression Modelling for the Predicting Effects of Project‐ and Industrial‐level Factors on
Project Outcomes ......................................................................................................................... 15
6. Limitations......................................................................................................................... 17
7. Closing Remarks ................................................................................................................ 18
8. Acknowledgement ............................................................................................................. 19
9. References ......................................................................................................................... 20
10. Appendix – Full Survey ............................................................................................................ 23

1. Background
Sustainability is an inevitable trend. However, the number of green developments is still limited
worldwide. Previous studies have attributed this to the influence of various factors, such as
regional policies, green building assessment processes, integrative project management,
individuals’ perception on upfront costs, and so on (e.g., Chan et al., 2009; Bartlett and Howard,2000). However, it is uncertain which factors are more critical in motivating or hindering
sustainable developments. More importantly, in addition to the above mentioned businessrationale and related social concerns, the performance and tangible benefits of green buildings
are also uncertain. Hence, to foster sustainable development worldwide, there is an urging needto investigate the influencing factors, performance and tangible benefits related to green
buildings in the AEC (Architectural, Engineering and Construction) sector. As such, the study
aims to investigate the factors, performance and benefits of green buildings worldwide. To
achieve this aim, the objectives of the study include:- to identify the motivational and hindrance factors affecting green building developments; and- to investigate performance and benefits of green building developments.
2. Systematic Literature Review
Based on the extensive literature review, factors affecting green building developments can be
categorized into two main groups, namely industrial- and project-level factors.
2.1 Influencing Factors
2.1.1 Industrial-level factors
Sustainability Climate
Though facing criticisms for years, the linear supply chain approach is still dominating the AEC
industry. Under this approach, clients are the key in initiating any innovation or changes(Manley, 2006). Although there are certain levels of awareness and interests in green
developments in the construction sector (Abidin, 2010; Abidin and Powmya, 2014), various
studies have indicated that the current social awareness and perception are insufficient for
fostering sustainable developments in the industry (e.g., Liu and He, 2011 William and Dair,
2007; Zhang, 2014). Clients’ leadership and demand for green are also found to be inadequate(Griffin, 2010; Zhang, 2014). In general, sustainable developments are perceived as more
expensive, requiring workers with higher-level competencies, and higher technological knowhow (e.g., Simpeh, 2015). These risk perceptions hinder AEC firms from developing sustainably(Du Plessis et al., 2002).

Sustainability Policies
Governments around the world have launched various green policies to encourage sustainable
developments in the AEC sector. However, success of these policies depends on four key factors.
1Firstly, a comprehensive policy package is essential in fostering full-cycle sustainability. For
instance, the sustainable policy in Australia has been criticized for putting too much emphasis onenergy efficiency, while lacking consistent focus on systematic green construction (Yang andYang, 2015). Secondly, complexity of codes and regulations may also affect developers’
decision-making for sustainability. For instance, previous studies revealed that developers haveencountered difficulties in estimating the initial costs of a green building project, due to thecomplex codes and regulations (e.g., Hwang and Tan, 2012). Thirdly, fiscal incentives topromote green buildings, such as taxes benefits, rebates and discount on application fee, can also
be critical (Olubumi, 2014). In view of the high initial cost and long payback period ofsustainable developments (Li, Yang, He and Zhao, 2014), fiscal incentives have been considered
as inadequate in motivating developers to invest in sustainable developments (Olubunmi, 2014).
Fourthly, non-fiscal incentives for green buildings, such as technical assistance, expedited
permitting, business planning assistance, market assistance, etc., have also been commented as
inadequate (Olanipekun et al., 2016; Olanipekun et al., 2017).

Green Building Assessment Processes & Methods
In recent decades, various schemes are developed for green building assessment and certificationworldwide. Commonly adopted green building assessment systems include LEED (Leadershipin Energy and Environmental Design), BEAM (Building Environmental Assessment Method),
BREEAM (BRE Environmental Assessment Method), GBCA (Green building council ofAustralia Green Star), Green Mark Scheme, DGNB (The German Sustainable Building Council)
system, CASBEE (Comprehensive Assessment System for Building Environment Efficiency),
and so on (Zuo and Zhao, 2014). Their common focuses are on energy efficiency, indoor
environment quality, and environmental impacts (Zhang, 2018).
Although these assessment schemes have different objectives and assessment scopes, they are
similar in terms of assessment framework. Using a score-based rating system, different points
are assigned to different checklist elements. The sum of the total element score indicates thesustainability level of a building (Retzlaff, 2008). However, developed based on different
regional situations and needs, element weighting differs across schemes. For instance, theweight of water is 10% in assessment scheme adopted in Northern Territory; while it is 15% in
assessment scheme adopted in Queensland (Zuo and Zhao, 2014). There is uncertainty about
which, or any, of these scheme(s) can accurately reflect how sustainable a building project is(Suzer, 2014).
On the other hand, some of the green building assessment processes have been commented as too
rigorous and too time-demanding, which act as barriers for developers to join the schemes (Chan,
Qian and Lam, 2009; Hes, 2007). For instance, LEED is one of the most popular green building
assessment schemes in the world. However, it has been commented as too complex, challenging
and time consuming (Ding, 2007).

22.1.2 Project-level Factors
Project Management in Green Building Developments
Project sustainability starts with managing or engineering stakeholders’ values and a principledapproach to manage green performance throughout the project lifecycle. Previous studies haveindicated that early incorporation of sustainability issues in value management can reduce capitalcosts of a green project (Bartlett and Howard, 2000). When comparing with conventional
projects, green building projects demand more new knowledge from multi-disciplinary project
parties, more project meetings are thus required to foster knowledge exchange and advanced
problem solving (Hwang and Ng, 2013). Communication and collaboration have been identified
as key successful factors in green building developments (Rohracher, 2001; Zhang, 2014). In
addition, previous studies have indicated that the approval process for green feature is generally
longer (Hwang and Ng, 2013). This puts an additional burden on time management in green
building projects.

Green Knowledge and Information
Knowledge and information in green designs, building systems, construction methods, products,
and so on, are the keys to successful green developments. However, previous studies haveindicated that there is still a lack of knowledge and information regarding green products,
building systems, and cost data in the AEC sector (e.g., Hwang and Tan, 2012). Professional
education and training on sustainable development have also been criticized as insufficient in the
sector (Ying Liu, Pheng Low, and He, 2012; Yang and Yang, 2015). Due to the lack of green
knowledge, firms are conservative in adopting green products, technologies or methods; and theytend to encounter more difficulties in green projects (Zhang, 2014). As such, there is a strong
need of demonstration projects to promote and showcase any efficient green technologies andconstruction methods in the sector (Chan et al, 2009; Potbhare et al., 2009). On the other hand,cost data, including both capital and operation costs, are the key to motivate developers to invest
in sustainability. Therefore, it is suggested that different cost estimation methods should beapplied to fully understand the economic benefits of green buildings (Nguyen et al., 2017).

Perceived Risks
Due to the various factors mentioned above, green projects are considered to have higher risks interms of project cost, time and quality. For instance, the project may fail to get a green
certification and/or fail in achieving a higher return after investment is made (Nguyen et al.,2017; Yang and Yang, 2015). Due to the higher complexity in green building projects, delay
may occur due to prolonged certification and permission processes (Simpeh, 2005), and morealterations and variations may arise during the construction stage (Hwang and Ng, 2013). Theserisk perceptions hinder AEC firms from attaining sustainability (Du Plessis et al., 2002).

3

2.2 Outcomes of Green Building Developments
2.2.1 Tangible Outcomes
Even though the concept of “green costs more” has been prevailing in the AEC sector in the past
decades (e.g., Bartlett and Howard, 2000), previous studies indicate that green buildings canresult in higher rents and asset values (e.g., Eichholtz, Kok and Quigley, 2013; Wiley, Benefield
and Johnson, 2010). In fact, a large amount of buildings, commercial buildings in particular, inmetropolitan cities like Hong Kong are owned and managed by developers and occupied bytenants. For these properties, rental rate acts as an important economic factor affecting
developers’ decision-making for sustainability. Previous studies have found that green buildings
can attract more anchor tenants and international tenants (Smit and Toit, 2015), while
commercial tenants are more willing to pay higher rent for green buildings (Eichholtz, Kok andQuigley, 2013). Meanwhile, in view of the lower operational costs, commercial tenants in green
buildings are found to be more loyal (Smit and Toit, 2015). The higher economic return may
motivate developers to invest in green building developments.

2.2.2 Intangible Outcomes
Along with the increasing social awareness towards sustainability, more and more AEC firms seea huge market potential for green developments. For instance, integrating green ideas into
construction projects has found to help generate free publicity and media coverage opportunities
for AEC firms (Smit and Toit, 2015), which can enhance a company’s brand equities (Abidin
and Powmya, 2014; Smit and Toit, 2015). Meanwhile, previous studies have also indicated thatgreen experience can help firms in taking a leading position in the AEC market (e.g., in the
Chinese AEC market, Jung, Sui and Xi, 2012). In general, creation of a green company image
through investments in green buildings can result in more future project opportunities (Abidin
and Powmya, 2014; Nurul and Abidin, 2013). In addition to market positioning at firm-level,
green building design and construction have also been found to have different impacts on
project-level outcomes, such as environmental sustainability, like energy and water consumption(e.g., Oates and Sullivan, 2011), and social sustainability, like health and safety (Rajendran et al.,2009).

3. Survey Design
Based on the above literature review, key factors influencing green developments are identified.
The survey is then designed to measure all these factors, using well-validated measurement
instruments as indicated in Table 1 (refer to Appendix for the full survey). A 5-point likert
measurement scale is adopted, in which respondents are invited to indicate their degree ofagreement to each statement by ‘strongly disagree’, ‘disagree’, ‘neutral’, ‘agree’, and ‘strongly
agree’.

4

Table 1 Survey Design Framework

Factors

Key References

Industrial Factors
Sustainability climate

Griffin et al., 2010, Zhang, 2014

Sustainability policies
Green building
assessment processes
and methods
Project Factors
Project management

Yang and Yang, 2015
Abidin and Powmya, 2014, Hwang and Tan, 2012, Shen et al.,2017

Chan et al., 2009, Griffin et al., 2010, Hwang and Ng, 2013, Jung,
Sui, and Xi, 2012, Yang and Yang, 2015, Zhang, 2014, Zhang etal., 2012

Green knowledge andinformation

Chan et al., 2009, Hwang and Ng, 2013, Hwang and Tan, 2012,
Potbhare et al., 2009, Simpeh and Smallwood, 2015, Yang andYang, 2015, Zhang, 2014, Zhang et al, 2012

Perceived Risks

Hwang and Ng, 2013, Simpeh, 2015, Yang and Yang, 2015, Zhao
et al., 2016

Outcomes /Benefits
Marketing benefits
Project benefits
Changes in time, costand income

Abidin and Powmya, 2014, Jung, Sui, and Xi, 2012, Nurul and
Abidin, 2013, Smit and Toit, 2015
Smit and Toit, 2015-

4. Sample
A purposive sampling method is adopted, in which only AEC professionals who have been
involved in green project(s) in the previous two years are invited to complete the survey.
Invitations are mainly sent with the support of the Pacific (Asia) Association of Quantity
Surveyors (PAQS) and the Hong Kong Institute of Surveyors (HKIS), and through the personal
network of the project team members. In total, 62 responses are received. The followings show
the preliminary demographic information of the respondents. The majority of the respondents
are from developers (34%), followed by contractors (16%), green building consultant (15%), QS
consultant (10%), and design firm (6%) (refer to Figure 1). Meanwhile, respondents are fromdifferent professional disciplines, including quantity surveying (18%), project management(18%), building surveying (13%), building services engineering (13%), structural engineering(5%), and general practice surveying (3%) (refer to Figure 2). More than 60% of the green
projects are located in Mainland China (refer to Figure 3). There are 44% of public projects,
37% of private projects, and 19% of semi-public projects (refer to Figure 4). Green Star is themost highly adopted green building assessment scheme (24%), followed by BEAM Plus (20%),
LEED (17%), and BREEAM (14%) (refer to Figure 5).
5Figure 1 Respondents’ Organization

Figure 2 Respondents’ Professional Disciplines

Figure 3 Project Location
6

Figure 4 Project Ownership

Figure 5 Green Building Assessment Schemes

5. Findings
5.1

Factors affecting Green Building Projects

5.1.1

Industrial-level Factors

There are three groups of industrial factors categorized in the study, namely sustainability
climate, sustainability policy and green building assessment (refer to Figures 6-8). Respondents
were invited to rate their degree of agreement towards statements related to these areas using a 5point Likert scale in the survey, in which 1 refers to strongly disagree, 3 refers to neutral, and 5
refers to strongly agree.
As shown in Figure 6, mean scores of all of the three items related to sustainability climate areabove 3, while the two items related to “insufficient consumers’ demands for green” and ‘lack of
7

atmosphere to pursue green’ receive the highest score (x̄ = 3.51 out of 5 for both of the items; SD= 0.994 and 1.043 respectively).

Figure 6 Sustainability climate in the industry

With reference to Figure 7, mean scores of all of the four items related to sustainability policy
are above 3. The two items related to ‘insufficient fiscal and non-fiscal incentives from thegovernment’ receive the highest score (x̄ = 3.92 out of 5 and 3.80 out of 5; SD = 0.822 and 0.997
respectively).

Figure 7 Sustainability Policy

As shown in Figure 8, mean scores of all of the four items related to green building assessment
schemes and methods are above 3. The item related to ‘green building assessment method being
time-consuming’ receive the highest score (x̄ = 3.41 out of 5; SD = 1.131).
8

Figure 8 Green Building Assessments

5.1.2 Project-level Factors
There are four groups of project-level factors categorized in this study, namely good project
management practice, hindering project management practice, lack of knowledge, and perceived
risks (refer to Figures 9-12). Similar to the industrial section, respondents were invited to rate
their degree of agreement towards the related statements using a 5-point Likert scale, in which 1
refers to strongly disagree, 3 refers to neutral, and 5 refers to strongly agree.
As shown in Figure 9, mean scores of all of the four items related to good project management
practices in green projects are above 3, while the two items related to ‘clear green goal setting at
project inception’ (x̄ = 3.97 out of 5; SD = 0.706) and ‘proactive value management for green
design’ receive the highest scores (x̄ = 3.84 out of 5; SD = 0.820).

Figure 9 Good Project Management Practice9

As shown in Figure 10, mean scores of all of the 5 items related to hindering project
management practices in green projects are above 3, while the three highest-score items include‘more meetings required for green projects’ (x̄ = 3.87 out of 5; SD = 0.922), ‘lengthy approval
process for new green technologies and recycled materials’ (x̄ = 3.74 out of 5; SD = 0.929) and‘lack of communication and collaboration between stakeholders’ (x̄ = 3.69 out of 5; SD = 1.057).

Figure 10 Hindering Project Management Practice

As illustrated in Figure 11, mean scores of all of the 6 items related to lack of green knowledge,
data, and information are above 3, while the item related to ‘different methods of costestimation’ scores the highest (x̄ = 3.98 out of 5; SD = 0.695), followed by ‘lack of green
demonstration projects’ (x̄ = 3.37 out of 5; SD = 1.012) and ‘inadequate cost-benefit analysis ofgreen buildings’ (x̄ = 3.61 out of 5; SD = 1.005).

Figure 11 Lack of Knowledge & Information10

As illustrated in Figure 12, mean scores of all of the 5 items related to perceived risks in green
projects are above 3, while the item related to ‘technical difficulties in green design’ receives thehighest score (x̄ = 3.67 out of 5; SD = 1.012), followed by ‘technical difficulties in green
construction’ (x̄ = 3.66 out of 5; SD = 0.998) and ‘higher project investment risks’ (x̄ = 3.56 outof 5; SD = 1.041).

Figure 12 Perceived Risks

Overall, the three fostering items score the highest are ‘clear green goal setting at project
inception’ (x̄ = 3.97 out of 5; SD = 0.706), ‘proactive value management for green design’ (x̄ =3.84 out of 5; SD = 0.820), and ‘financial rewards for the extra effort put by design team’ (x̄ =3.48 out of 5; SD = 1.010), while the three hindering items score the highest are ‘different costestimation methods’ (x̄ = 3.98 out of 5; SD = 0.695), ‘insufficient fiscal incentives fromgovernment’ (x̄ = 3.92 out of 5; SD = 0.822), and ‘more meetings required for green projects’ (x̄= 3.87 out of 5; SD = 0.922).

5.2 Tangible and Intangible Outcomes of Green Building Projects
5.2.1 Tangible Outcomes
In this section, tangible project outcomes in terms of cost, income and time are analyzed (refer toFigures 13-15). Respondents were invited to compare their green building projects withconventional ones, and indicate whether there was an ‘increase’, ‘decrease’ or ‘no change’ in thecost, income and time dimensions.
As shown in Figure 13, when comparing their green building projects with conventional ones,nearly 68% of the respondents experienced an increase in construction cost, followed by 27.4%of them experienced no change, and 3.2% of them experienced a decrease. For life cycle cost,11there is no big difference on the percentage of the respondents who experienced a decrease(29%), increase (33.9%) or no change (35.5).

Figure 13 Change in Project Cost (when comparing with conventional projects)

As illustrated in Figure 14, when comparing with conventional projects, more than half of the
respondents experienced an increase in selling price (53%), rental price (56.5%), and premium inmarket valuation (54.8%) in their green projects. While there are not many respondents who
have experienced a decrease in these three income levels (<3.5), around 40% of the respondents
experienced no change.

Figure 14 Change in Project Income (when comparing with conventional projects)

With reference to Figure 15, when comparing with conventional projects, more than half of the
respondents experienced an increase in design time (53.2%) in their green projects, followed by12

no change (41.9%) and a decrease (3.2%). In terms of construction time, half of the respondents
experienced no change (50%), followed by an increase (45.2%) and a decrease (3.2%). For
payback period, the majority of the respondents experienced no change (40.3%), followed by anincrease (38.7%) and a decrease (19.4%).

Figure 15 Change in Time (when comparing with conventional projects)

The magnitude of change in the above cost, income and time dimensions are illustrated in Figure
16. On average, when comparing with conventional projects, the construction cost, life cycle
cost, design time, construction time and payback period of green projects are found to haveincreased by 11.8%, 0.9%, 8.0%, 4.5% and 3.3% respectively. However, the selling price, rental
price and market premium of these green projects have also increased by 4.4%, 4.6% and 6.0%.

Figure 16 Magnitude of Change

135.2.2 Intangible Outcomes
There are two types of intangible benefits identified, namely perceived marketing benefits andperceived project benefits (refer to Figures 17-18). Respondents were invited to rate their degreeof agreement towards statements related to these areas using a 5-point Likert scale in the survey,
in which 1 refers to strongly disagree, 3 refers to neutral, and 5 refers to strongly agree.
As shown in Figure 17, mean scores of all of the three items related to perceived marketing
benefits are above 3, while the highest score item is ‘more opportunities for future projects’ (x̄ =4.08 out of 5; SD = 0.759), followed by ‘free publicity and media coverage’ (x̄ = 4.03 out of 5;
SD = 0.816) and ‘leading position in the industry’ (x̄ = 3.89 out of 5; SD = 0.819).

Figure 17 Perceived Marketing Benefits
With reference to Figure 18, mean scores of all of the four items related to perceived project
benefits are above 3, while the highest score item is ‘environmental sustainability’ (x̄ = 3.98 outof 5; SD = 0.785), followed by ‘social impacts’ (x̄ = 3.95 out of 5; SD = 0.884) and ‘projectschedule’ (x̄ = 3.84 out of 5; SD = 0.637).

Figure 18 Perceived Project Benefits145.3 Regression Modelling for the Predicting Effects of Project- and Industrial-level
Factors on Project OutcomesTo further investigate the predicting effects of project-level factors and industrial-level factors on
project outcomes, multiple regression modelling was conducted. First of all, all project-levelfactors are inputted into the model as independent variables, and cost performance is put as
dependent variable. As shown in Model 1 (refer to Table 2), ‘extra financial rewards toconstruction team’ is found to predict project cost performance significantly (p<0.01). The
model explains 16.6 percent of variance to cost performance. The process is then repeated, withall project-level factors being inputted as independent variables and with time performance,
environmental sustainability performance, social sustainability performance and marketing
benefits being inputted as dependent variable in different models (refer to Models 2-5 in Table 2).
As shown in Model 2, ‘extra financial rewards to design team’ is found to predict project time
performance significantly (p<0.01). The model explains 12.7 percent of variance to time
performance. For Model 3, ‘extra financial rewards to construction team’, ‘proactive value
management’ and ‘clear green goal setting in project inception’ are found to predict
environmental sustainability performance significantly (p<0.01). The model explains 46.9
percent of variance to time performance. Then, for Model 4, ‘extra financial rewards toconstruction team’ and ‘clear green goal setting in project inception’ are found to predict social
sustainability performance significantly (p<0.05). The model explains 22.7 percent of varianceto time performance. Then, Model 5 indicates that ‘clear green goal setting in project inception’and ‘deficient green building technologies’ predict marketing benefits of a company significantly(p<0.01). The model explains 38.5 percent of variance to time performance.

Table 2 Regression modelling for the predicting effects of project-level factors on green project
outcomes
Model Dependent
Independent variables
variables
1
Cost Performance (Constant)
Extra financial rewards toconstruction team2
Time(Constant)
Performance Extra financial rewards todesign team3
Environmental (Constant)
Sustainability Extra financial rewards to
Performance
construction teamProactive value
management
Clear green goal setting in
project inception
4
Social(Constant)
Sustainability Extra financial rewards to
Performance
construction team
Clear green goal setting in
project inception

R2

Beta
UnSTD S.E.
2.761
.319

t

Sig.

R

8.659

.000

.408

Sig.
(ANOVA)
.166
.001

.312

.091

3.430

.001

3.055

.278 11.007 .000

.356

.127

.005

.225

.077

2.928

.005

2.452

.494

4.966

.000

.685

.469

.000

.407

.079

5.120

.000

-.411

.104

-3.960 .000

.441

.115

3.847

.000

1.678

.605

2.773

.007

.476

.227

.001

.259

.100

2.586

.012

.355

.151

2.357

.022

15

Table 2 Regression modelling for the predicting effects of project-level factors on green project
outcomes (con’t)
Model Dependent
variables
5
Perceived
marketingbenefits

Independent variables(Constant)
Clear green goal setting in
project inception
Deficient green building
technologies

Beta
UnSTD S.E.
4.044 1.338

t

Sig.

R

3.022

.004

.620

1.537

.292

5.263

.000

.543

.201

2.696

.009

R2

Sig.
(ANOVA).385.000

Then, regression modelling is applied to investigate the predicting effects of industrial-levelfactors on green project outcomes. Similarly, all industrial-level factors are inputted as
independent variables, while different outcome factors are put as dependent variable in eachmodel (refer to Models 6-8 in Table 3). As shown in Model 6, ‘lack of comprehensive policy
packages’ is found to predict project cost performance significantly (p<0.01). The model
explains 11.5 percent of variance to cost performance. Then, Model 7 reveals that ‘lack ofcomprehensive policy packages’ predicts time performance significantly (p<0.05). The model
explains 6.7 percent of variance to time performance. Lastly, Model 8 shows that ‘insufficient
fiscal incentives from government’ predicts perceived marketing benefits significantly (p<0.01).
The model explains 13.7 percent of variance to perceived marketing benefits.
Table 3 Regression modelling for the predicting effects of industrial-level factors on green
project outcomes
Model Dependent
Independent variables
Betavariables
UnSTD S.E.
6
Cost Performance (Constant)
2.884 0.346
Lack of comprehensive
policy packages to guide .270
0.097
sustainability actions
7
Time(Constant)
3.287
.279
Performance Lack of comprehensive
policy packages to guide .161.078
sustainability actions
8
Perceived(Constant)
11.296 1.588
marketingInsufficient fiscal
benefits
incentives from
1.213
.397
government

R2

t

Sig.

R

8.329

.000

.339

Sig.
(ANOVA)
.115
.007

2.770

.007
.258

.067

.044

.370

.137

.003

11.792 .000
2.054

.044

7.113

.000

3.057

.003

The predicting effects of both project-level and industrial-level factors on green building project
outcomes are summarized and illustrated in Figure 19 as shown below.

16Figure 19 Statistical model showing the predicting effects of project- and industrial-level factors
on perceived green project outcomes
Note:

-

Positive predicting effect as revealed in regression analysis (refer to Tables 2-3)
Negative predicting effect as revealed in regression analysis (refer to Table 2)

6. Limitations
It is acknowledged that the sample size of this study is limited and the majority of projects arelocated in Mainland China. A larger sample size collected from more evenly distributed regions
would enhance the reliability and representativeness of the study results. However, it should be
noted that the survey respondents in this study are all AEC professionals who have primaryexperience in green projects and thereby are able to provide reliable data to the study.
Meanwhile, a good balance between public and non-public projects, and between respondents
from different types of firms are achieved. Lastly, the measurement scales adopted in this study
were identified from an extensive literature review, in which they have been validated inprevious studies. Therefore, despite the limitations, the evidences collected in this study
provides a reliable platform for investigating the influencing factors and outcomes of green
building projects.

This study adopts a quantitative approach, i.e., questionnaire survey, which aims to establish‘what’ the general phenomenon, in terms of influencing factors, performance and benefits of17

green projects, are. To further develop in-depth understandings of ‘how’ and ‘why’ suchphenomenon happened, qualitative approaches, such as case study and focus group interviews,
are proposed for further studies. Cross validation can then be done by comparing the results ofboth qualitative and qualitative studies.

7. Closing Remarks
Even though green projects are found to incur higher cost and longer time, when comparing withconventional ones, they can result in higher selling price (+4.44%), rental price (+4.58%) andpremium in market valuation (+5.94%). In addition to these tangible benefits, green projects arealso found to contribute to better market positioning of a company. For instance, company withgreen experience can take a leading position in the industry, they can also ensure more
opportunities for future projects; and green development projects can result in free publicity andmedia coverage for a company as well. Furthermore, besides enhancing time- and costefficiencies, green projects can also result in better project performance in terms ofenvironmental and social sustainability. In fact, these intangible benefits can indirectly enhancetangible benefits of a firm in the long run.
Building on previous studies investigating various factors affecting sustainable developments
around the world, this study identified 3 industrial-level factors, namely sustainability climate,sustainability policy, and green building assessment methods, and 4 project-level factors, namely
good project management practice, hindering project management practice, lack of knowledge
and information, and perceived risks. To provide empirical support on their roles on green
project outcomes, i.e., fostering vs. hindering; this study takes a step further to adopt regression
modeling for investigating the predicting effects of these factors on the outcomes in terms ofproject cost, project time, environmental sustainability, social sustainability and marketing
benefits. Based on the findings of the regression analyses (refer to Figure 19), the following
recommendations are made to enhance outcomes and benefits of green projects:-

Provide financial rewards to the construction team for their extra efforts and skills put in
adding values to green construction ( enhance performances in cost, environmental
sustainability & social sustainability)-

Provide financial rewards to the design team for their extra efforts and skills put in
adding values to green building designs and features ( enhance time performance)-

Set the goal for green design and construction clearly at the project inception stage (enhance environmental sustainability, social sustainability, and marketing benefits)-

Include a clear goal for environmental sustainability in proactive value management (enhance environmental sustainability performance)-

Be early adopter /pioneer in the industry, i.e., go for sustainability even when green
technologies are still deficient and when there is still insufficient fiscal incentives fromthe government ( enhance company’s marketing benefits)18

-Prevent overly rigorous policy packages to guide actions on sustainability ( enhance
project performance in terms of cost and time)

8. Acknowledgement
The authors acknowledge the contributions of members of the Pacific Association of Quantity
Surveyors (PAQS) and Hong Kong Institute of Surveyors (HKIS) in the data collection process,and acknowledge the funding supported by the PAQS.

19

9. References
Abidin, N. Z. (2010). Investigating the Awareness and Application of Sustainable Construction
Concept by Malaysian Developers. Habitat International, 344), 421-426. doi:
10.1016/j.habitatint.2009.11.011.
Abidin, N. Z., & Powmya, A. (2014). Perceptions on Motivating Factors and Future Prospects ofGreen Construction in Oman. Journal of Sustainable Development, 75). doi:
10.5539/jsd.v7n5p231.
Bartlett, E., & Howard, N. (2000). Informing the Decision Makers on The Cost and Value ofGreen Building. Building Research and Information, 285-6), 315-324.
Bordass, W., (2000) Cost and value: fact and fiction, Building Research and Information, 285-6),Taylor & Francis Ltd. London, 338-352.
Chan, E. H., Qian, Q. K., & Lam, P. T. (2009). The market for green building in developed
Asian cities—the perspectives of building designers. Energy Policy, 378), 3061-3070.
Cole, R.J., (2000). Editorial: Cost and Value in Building Green. Building research andinformation, 28 5/6), 304–309.
Ding, G. (2008). Sustainable Construction—The Role of Environmental Assessment
Tools. JournalofEnvironmental
Management, 863),
451-464.
doi:
10.1016/j.jenvman.2006.12.025.
Dodge Data & Analytics. (2016). World Green Building Trends 2016 [Ebook]. Dodge Data andAnalytics.
Retrievedfromhttps://www.worldgbc.org/sites/default/files/World%20Green%20Building%20Trends%
202016%20SmartMarket%20Report%20FINAL-2.pdf.
Du Plessis, C. (2007). A Strategic Framework for Sustainable Construction in Developing
Countries. Construction Management and Economics, 251), 67-76.
Eichholtz, P., Kok, N., & Quigley, J. (2013). The Economics of Green Building. Review of
Economics and Statistics, 951), 50-63. doi: 10.1162/rest_a_00291.
Gov.HK(2018).
Green
Buildings.
Retrievedfromhttps://www.gov.hk/en/residents/environment/sustainable/buildings.htm.
Griffin, C. T., Knowles, C., Theodropoulos, C., & Allen, J. H. (2010). Barriers to theimplementation of sustainable structural materials in green buildings. ICSA 2010-1st
International Conference on Structures & Architecture, Guimaraes, Portugal. CRC Press.
Hes, D. (2007). Effectiveness of Green Building Rating Tools: A Review of Performance.
International Journal of Environmental, Cultural, Economic and Social Sustainability,34), 143-152.
Hill, R.C. & Bowen, P.A. (1997). Sustainable Construction: Principles and a Framework for
Attainment. Construction Management and Economics, 15, 223-239.
Hwang, B. G., & Tan, J. S. (2012). Green building project management: obstacles and solutions
for sustainable development. Sustainable Development, 205), 335-349.
Hwang, B. G., & Ng, W. J. (2013). Are Project Managers Ready for Green Construction?Challenges, Knowledge Areas, and Skills. Smart and Sustainable Built Environments,2013): 25.
IPCC.
2015).
ClimateChange(2014:
Synthesis
Report.
Retrievedfrom
http://www.ipcc.ch/report/ar5/syr/.
IPCC. (2018). Global Warming of 1.5 °C. Retrieved from http://www.ipcc.ch/report/sr15/.
Isa, M., Rahman, M. M. G. M. A., Sipan, I., & Hwa, T. K. (2013). Factors affecting green officebuilding investment in Malaysia. Procedia-Social and Behavioral Sciences, 105, 138-148.
20

Jung, Y., Sui, P., & Xi, H. (2012). Green Practices in The Chinese Building Industry: Drivers
and Impediments. Journal of Technology Management in China, 71), 50-63. doi:
10.1108/17468771211207349.
Li, Y., Yang, L., He, B., & Zhao, D. (2014). Green Building in China: Needs great
promotion. Sustainable Cities and Society, 11, 1-6. doi: 10.1016/j.scs.2013.10.002.
Liu, J., He X. (2011). Influence Factors on Real Estate Companies’ Decision to Develop Green
Building Projects. International Economic Cooperation, 3: 82-85.
Manley, K. (2006) The innovation competence of repeat public sector clients in the Australianconstruction industry, Construction Management and Economics, 24, 1295-1304.
Nguyen, T., Toroghi, S., & Jacobs, F. (2017). Automated Green Building Rating System for
Building Designs. Journal of Architectural Engineering, 224), A4015001. doi:
10.1061/asce)ae.1943-5568.0000168.
Nurul, D. A. & Abidin, N. Z. (2013). Motivation and Expectation of Developers on Green
Construction: A Conceptual View. International Journal of Humanities and Social
Sciences, 74), 914-918.
Oates, D., & Sullivan, K. T. (2011). Postoccupancy energy consumption survey of Arizona’s
LEED new construction population. Journal of Construction Engineering andManagement, 138(6), 742-750.
Olanipekun, A. O., Xia, B., Hon, C., & Hu, Y. (2017). Project Owners’ Motivation for
Delivering Green Building Projects. Journal of Construction Engineering andManagement, 1439), 04017068.
Olanipekun, A. O., Xia, P. B., & Skitmore, M. (2016). Green Building Incentives: A Review.
Renewable and Sustainable Energy Reviews, 59, 1611-1621.
Potbhare, V., Syal, M., & Korkmaz, S. (2009). Adoption of Green Building Guidelines in
Developing Countries Based on US and India Experiences. Journal of Green Building,42), 158-174.
Rajendran, S., Gambatese, J. A., & Behm, M. G. (2009). Impact of green building design andconstruction on worker safety and health. Journal of construction engineering andmanagement, 135(10), 1058-1066. Retzlaff, R. C. (2008). Green Building Assessment
Systems: A Framework and Comparison for Planners. Journal of the American Planning
Association, 744), 505-519.
Pitt, M., Tucker, M., Riley, M., & Longden, J. (2009). Towards sustainable construction:
promotion and best practices. Construction Innovation, 92), 201-224.
Rohracher, H. (2001). “Managing the technological transition to sustainable construction ofbuildings: a socio-technical perspective.” Technology Analysis and Strategic
Management, 131), 137-150.
Qian, Q. K., Fan, K., & Chan, E. H. ( 2016). Regulatory incentives for green buildings: grossfloor area concessions. Building Research and Information, 445-6), 675-693.
Ren, Y. (2007). Obstacles and Countermeasures in Promoting Green Building. Development
Research, 10, 47-49.
Samari, M., Ghodrati, N., Esmaeilifar, R., Olfat, P., & Shafiei, M. W. M. (2013). The
investigation of the barriers in developing green building in Malaysia. Modern Applied
Science, 72), 1.
Shen, L., Zhang, Z., and Long, Z. (2017). Significant barriers to green procurement in real estatedevelopment. Resources, Conservation and Recycling, 116, 160-168.

21

Simpeh, E. K. (2015). Factors Influencing the Growth of Green Building in the South African
Construction Industry. In Smart and Sustainable Built Environment SASBE) Conference
2015 p. 311).
Smit, A. M. & Toit, F. D. (2015). Investigating the Financial Benefits of Green Buildings.
Environmental Economics, 63), 61-71.
Sustainable Development Commission. (2011). What is sustainable development. Retrieved fromhttp://www.sd-commission.org.uk/pages/what-is-sustainable-development.html.
Suzer, O. (2015). A Comparative Review of Environmental Concern Prioritization: LEED vs
Other Major Certification Systems. Journal of Environmental Management, 154, 266-283.
Tam, V. W. Y., (2007), The Effectiveness of the Green Building Evaluation and Labelling
System. Architectural Science Review, 504), pp.323.
Van Bueren, E. M., & Priemus, H. (2002). Institutional barriers to sustainable construction.
Environment and Planning, 291), 75-86.
Wiley, J. A., Benefield, J. D., & Johnson, K. H. (2010). Green design and the market forcommercial office space. The Journal of Real Estate Finance and Economics, 41(2), 228243.
Williams, K., & Dair, C. (2007). What Is Stopping Sustainable Building in England? Barriers
Experienced by Stakeholders in Delivering Sustainable Developments. Sustainable
Development, 153), 135-147. doi: 10.1002/sd.308.
Yang, J., & Yang, Z. (2015). Critical Factors Affecting The Implementation of Sustainable
Housing in Australia. Journal of Housing and The Built Environment, 302), 275-292. doi:
10.1007/s10901-014-9406-5.
Zhang, B., Zhang, L. (2010). Problems Encountered on Green Building Development inTangshan City. Energy Research and Management, 3: 56-67.
Zhang, L., Wu, J., & Liu, H. (2018). Turning Green into Gold: A Review on the Economics of
Green
Buildings. Journalof
Cleaner
Production, 172,2234-2245.
doi:
10.1016/j.jclepro.2017.11.188.
Zhang, X. (2014). Investigation of Factors Restraining the Implementation of Green Buildings in
Mainland China. Organization, Technology and Management in Construction: An
International Journal, 63). doi: 10.5592/otmcj.2014.3.8.
Zhang, X., Shen, L., Tam, V. W., & Lee, W. W. Y.( 2012). Barriers to implement extensive
green roof systems: a Hong Kong study. Renewable and Sustainable Energy Reviews,161), 314-319.
Zhao, X., Hwang, B. G., & Gao, Y. (2016). A fuzzy synthetic evaluation approach for risk
assessment: a case of Singapore's green projects. Journal of Cleaner Production, 115,203-213.
Zuo, J., & Zhao, Z. Y. (2014). Green Building Research–Current Status and Future Agenda: A
Review. Renewable and Sustainable Energy Reviews, 30, 271-281.

22

10. Appendix – Full Survey

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40