AN INNOVATIVE TOOL SELECTION METHOD FOR CONSTRUCTION PROJECTS IN NEW ZEALAND

AN INNOVATIVE TOOL SELECTION METHOD
FOR CONSTRUCTION PROJECTS IN NEW ZEALAND
A research report presented in partial fulfilment of the requirements
for the degree of
Master of Construction
in
Quantity Surveying
at Massey University, Albany, New Zealand
Toan Canh Nguyen
2016

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Abstract
This research’s aim is to build a practical model to help decision-makers in construction projects select
an appropriate innovative construction tool that can significantly contribute to labour productivity rate
improvement. Innovation is one of the biggest issues currently in construction industry all over the
world. Many studies have confirmed that the benefits from implementing innovation activities in both
firm and project levels are significant and remarkable. Among those benefits, labour productivity
improvement is one of the crucial outcomes. Especially in New Zealand context, low labour
productivity rate in construction industry is very alarming. In order to achieve the aim, literature has
been reviewed to identify key innovation types, components and levels in New Zealand construction
projects accounting for labour productivity rate improvement. Based on several relevant alternative
selection models, the research proposes a model that evaluates both innovative options’ Benefit and
Cost factors. The evaluation processes use Analytic Hierarchy Process (AHP) method to derive the
alternatives’ priorities. Findings from the proposed selection model survey, which was responded by
eight project decision-makers, indicate following characteristics that an innovative tool should have:
worker safety in terms of less general loss-time injuries, less rework and good observability (or “high-
visibility”). The proposed AHP hierarchy structure is proved that it can be used in real jobs to assist
project managers’ decisions on new tool investment. Further study is needed to carry out the
integration of Delphi technique and AHP to gain more confidence in the AHP factors selection.
Keywords: Construction innovation; Implementing innovation in project level; Analytic Hierarchy
Process method; Alternative selection model; Decision-making support model; Construction innovative
tools; Labour productivity rate improvement.

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Acknowledgements
I wish to express my sincere appreciation to all lecturers for their whole-hearted instructions
throughout the program. Particularly, I would be very grateful to Dr. Kenneth Sungho Park for his
valuable guidance and comments. This research report cannot be accomplished well without his
advices.
Besides, I would like to thank all Massey staff and all my classmates for their kind support throughout
the program. This very useful program gives me many chances, not only for my career but also for my
life.
And finally, many thanks to the restless encouragement and support from my beloved family. This
study is dedicated to them.

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Table of Contents
Abstract ii
Acknowledgements iii
1. Introduction 1
1.1. Background 1
1.2. Problem statement 4
1.3. Research Aim and Objectives 5
2. Literature Review 6
2.1. Introduction 6
2.2. Definitions 6
2.3. Market-based innovation and resource-based innovation 7
2.4. Components of Innovation 7
2.5. Innovation process in construction projects 11
2.6. Innovation process in construction firms 12
2.7. Categories and types of construction innovations 14
2.8. Summary 17
3. Research Methodology 19
3.1. Introduction 19
3.2. Selection method with MCDM techniques 19
3.3. Proposed decision support system 23
3.4. Data collection 28
4. Data analysis 31
4.2. Survey respondent characteristics 31
4.3. Data validation 31
4.4. Combining group judgements 32
4.5. Benefits synthesis and sensitivity analysis 33
4.6. The alternatives’ cost estimates and priorities with respect to cost 34
4.7. Priorities of Benefits and Costs combination 35
5. Discussion 36
5.2. Discussing the results 36
5.3. Research report limitation and recommendation for further study 37
6. Conclusion 38
7. Appendix 39
Survey questionnaire 39
8. References 46

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List of abbreviation
AHP – Analytic Hierarchy Process
ANP – Analytic Network Process
CRE-MSD - Centre of Research Expertise for the Prevention of Musculoskeletal Disorders
MBIE – Ministry of Business, Innovation and Employment
MED – Ministry of Economic Development (Replaced with MBIE in 2012)
NZIER – New Zealand Institute of Economic Research
OECD - Organisation for Economic Co-operation and Development
SNZ – Statistics New Zealand
List of figures
Figure 1-1: Sector employment (total hours paid) vs sector GDP (real) per hour paid............................2
Figure 2-1: Synthesis of market-based and resource-based views of innovation ...................................7
Figure 2-2 Motivational needs............................................................................................................... 10
Figure 2-3: Innovation Process in Construction Projects ...................................................................... 11
Figure 2-4 The process of innovation.................................................................................................... 12
Figure 2-5 Reaction forces and Action forces in innovation process .................................................... 13
Figure 2-6: Framework for innovation performance measurement....................................................... 13
Figure 2-7: Innovation Categories......................................................................................................... 15
Figure 3-1: Three-level Hierarchical Structure of AHP.......................................................................... 20
Figure 3-2: Network Structure of ANP................................................................................................... 20
Figure 3-3: Evaluation of Technology Alternatives Hierarchical Structure............................................ 23
Figure 3-4: Model of equipment selection ............................................................................................. 25
Figure 3-5: Proposed Tool Innovation Selection Model ........................................................................ 27
Figure 3-6: Proposed Hierarchy of Best Tool Innovation Selection ...................................................... 28
Figure 3-7: AHP hierarchy structure for model test............................................................................... 29
Figure 4-1: Pairwise comparison of criteria with respect to (wrt) the Goal............................................ 32
Figure 4-2: Pairwise comparison of sub-criteria wrt the criterion Project Performance ........................ 32
Figure 4-3: Pairwise comparison of sub-criteria wrt the criterion Worker Safety .................................. 32
Figure 4-4: Pairwise comparison of sub-criteria wrt the criterion Training............................................ 32
Figure 4-5: Pairwise comparison of alternatives wrt the sub-criterion Productivity Improvement ........ 32
Figure 4-6: Pairwise comparison of alternatives wrt the sub-criterion Quality Improvement................ 32
Figure 4-7: Pairwise comparison of alternatives wrt the sub-criterion Tool Duration............................ 32
Figure 4-8: Pairwise comparison of alternatives wrt the sub-criterion Musculoskeletal Disorders
Reduction .............................................................................................................................................. 32
Figure 4-9: Pairwise comparison of alternatives wrt the sub-criterion Injuries Reduction .................... 32
Figure 4-10: Pairwise comparison of alternatives wrt the sub-criterion Observability .......................... 33
Figure 4-11: Pairwise comparison of alternatives wrt the sub-criterion Complexity ............................. 33
Figure 4-12: Sensitivity analysis of the alternatives’ ranks for the criterion Worker Safety .................. 34
Figure 4-13: Sensitivity analysis of the alternatives’ ranks for the criterion Training ............................ 34
Figure 4-14: Sensitivity analysis of the alternatives’ ranks for the sub-criterion MSDs Reduction ....... 34

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Figure 4-15: Sensitivity analysis of the alternatives’ ranks for the sub-criterion Injuries Reduction ..... 34
List of tables
Table 1-1: Benefits of construction innovation .........................................................................................2
Table 2-1: Innovation Components and their indicators ..........................................................................8
Table 2-2: Comparison of key significant innovation indicators in firm and project level...................... 13
Table 2-3: Classification of various innovation types ............................................................................ 16
Table 2-4: Key subcomponents having highest impact on labour productivity ..................................... 17
Table 3-1: Fundamental Scale for making judgements......................................................................... 20
Table 3-2: Random Consistency Indices. ............................................................................................. 21
Table 3-3: Decision Attribute Hierarchy ................................................................................................ 24
Table 3-4: Equipment selection hierarchical structure .......................................................................... 24
Table 3-5: Criteria for innovation alternatives evaluation at project and company level....................... 24
Table 4-1: Priorities and Ranking of the Alternatives............................................................................ 33
Table 4-2: Alternatives' cost estimate ................................................................................................... 35
Table 4-3: Priorities of the alternatives' cost ......................................................................................... 35
Table 4-4: Combination of Benefits and Costs priorities....................................................................... 35

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1. Introduction
1.1. Background
The construction sector in New Zealand has been known as one of the major engines of the economy.
It has contributed “one in seven new jobs and a dollar invested in the industry generates three dollars
in economic activity” (Keeley, Pikkel, Quinn, & Walters, 2013; Pricewaterhouse Coopers, 2011, pp. 32-
33). However, this sector has its own characteristics such as adversarial behaviour, litigious
orientation, poor communication and coordination, lack of customer focus and low investment in
research and development activity as well as low productivity and skills retention rate (Barrett, Sexton,
& Lee, 2008; Pricewaterhouse Coopers, 2011).
New Zealand’s construction sector has a large portion of small and medium-sized construction firms
(with less than 19 employees), approximately 66%, of the total number of firms in the sector (MBIE,
2014a, p. 49). The fifth largest industry contributed around 6% to the nominal GDP in 2011 and had
7.2% nominal GDP growth in the period from 2001 to 2011 (MBIE, 2014a, p. 32 and 33). This sector
was the third sector in top three generating jobs from 2002 to 2012 and the sixth largest sector
employing 7.6% of the economy’s workforces, over 170,000 people, as reported by the MBIE (2014a).
However, this industry has been undergoing a remarkably and worryingly low rate of labour
productivity than other sectors (MBIE, 2013, p. 19). According to the report, construction could only
create $34 real GDP per hour worked which is 29% below the New Zealand average labour
productivity of $48 per hour. The industry is just above other four sectors such as education,
administration & other services, retail trade and accommodation & restaurants (shown in Figure 1-1).
This is not uncommon as Nam and Tatum (1997) also found the same finding in US construction
industry as well as in Australia’s (Chancellor, Abbott, & Carson, 2015), to name a few similar
examples.
On the whole economy scale, improvement in labour productivity in New Zealand construction sector
could create noticeable benefits. Boosting 1% of labour productivity could generate $300 million more
to the economy (Pricewaterhouse Coopers, 2011). But in fact, from 1996 to 2011, the growth rate of
productivity in New Zealand was just 0.8%/pa (NZIER, 2013). According to MBIE (2013), low
productivity in this sector has been identified as the key issue and many initiatives has been
established to solve it (to compare with Australia’s productivity rate, New Zealand’s is about 30%
below). For example, the New Zealand Productivity Commission began operating in 2011 to provide
advice to the Government on improving productivity issues; or the Building and Construction
Productivity Partnership existed from 2010 to 2014 to address the issue with the aim to raise the
sector productivity rate by 20% by 2020 (The Building and Construction Sector Productivity
Partnership, 2012). Lacking improvement in innovation and technology was found as one of the key
areas that needed fundamental changes (The Building and Construction Sector Productivity
Partnership, 2013).

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Many researchers suggested that implementing innovative activities in construction will create many
benefits. Beside productivity improvement, other key benefits of innovative practices in construction
are shown in the Table 1-1. In general, implementation of innovation in construction can help firms
maintain healthy performance as well as their competitiveness in the market.
Table 1-1: Benefits of construction innovation
Benefits Authors
- Increasing economic growth; reductions in the production cost,
creating new markets based upon innovation, reducing the
environmental impacts of construction related activities,
increasing firm’s competitive position, improving reputation, ease
of work, attraction of promising new hires or increasing the
technical feasibility of construction undertakings
Slaughter (1998)
- Increasing productivity, reducing material costs, improving the
quality of the work, preventing musculoskeletal disorders
(MSDs) in workplace.
Kramer et al. (2010)
- Reducing project duration and cost, improving quality and
environmental performance, enhancing company’s reputation,
support future decisions through knowledge transfer, satisfying
clients and end-users.
Ozorhon, Abbott, Aouad,
and Powell (2010)
- Faster delivery, no defects, reducing operation, maintenance
and energy costs, less waste and pollution, fewer illnesses and
injuries incurred by workers.
Duncan (2002)
- Project-level benefits: decrease in project duration and cost,
increase in productivity and client satisfaction; firm-level benefits:
gaining experience, company image improvement, technical and
managerial capability improvement, long-term profitability,
intellectual property, future business collaborations.
Ozorhon, Oral, and
Demirkesen (2015)
Figure 1-1: Sector employment (total hours paid) vs sector GDP (real) per hour paid
Source: MBIE (2014a)

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MBIE (2014a) observed that construction firms’ reported Research & Development (R&D) and
Innovation activities in New Zealand have shown incommensurate with the sector’s $33 billion scale.
R&D contributed 9% and Innovation activities contributed 41% which were below New Zealand all-
sector average value. Innovation in the construction industry therefore has been required to boost the
productivity to a higher level with the aim of 20% productivity increase by 2020 (NZIER, 2013).
However, there have been barriers that this aim has to overcome as follows:
 According to Pries and Janszen (1995), key barrier is the fragmentation nature of
construction processes (specialization of smaller companies). Nam and Tatum (1997)
agreed with this opinion when mentioned that specialization of many involved contractors
cause many coordination and integration issues.
 Another barrier found by Blayse and Manley (2004) is that the clients tend to use known
methods rather than innovation due to long construction delivery time.
 Lack of technical capabilities, not applicable to all projects, long payback period, project
delivery method, reluctance to change, lack of innovation value recognition, lack of
communication between construction firms and clients, lack of resources, low on
investment return, and strict regulations and codes are other barriers that construction
firms need to overcome when they want to implement innovation (Gambatese &
Hallowell, 2011b; Slaughter, 1993).
 In the New Zealand context, MBIE (2013) reported that lack of scale and cost of
implementing innovation involving intensive training and changes in practice are key
barriers of innovation implementation in construction firms.
 Chancellor et al. (2015) mentioned that New Zealand’s construction industry has faced
problems of scale, residential construction concentration and fairly substantial cyclical
fluctuations all together making a worrying low rate of productivity.
 Large firms so far have more R&D and Innovation activities than small and medium firms
according to (MBIE, 2014a). However, they are dominating heavy and civil engineering
subsector while small and medium firms (SMEs) are taking preponderant role in other
sub-sectors, i.e. residential buildings, non-residential buildings and construction services
(MBIE, 2014a). The Building and Construction Sector Productivity Partnership (2013)
confirmed that bigger firms are relatively more productive. On the other hand, SMEs are
less productive despite they are dominating high volume and value subsector, i.e.
residential construction.
With all the background related to current productivity rate in New Zealand construction industry, the
target of this research report will focus on project-level innovation and study a selection method to help
project managers make decision on which innovation types will be implemented to boost productivity
to higher levels.

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1.2. Problem statement
Lim, Schultmann, and Ofori (2010) defined innovation as “the purposeful search for new knowledge
and the systematic application of this knowledge in production”. Many types of innovation have been
researched and applied to both construction firm level and project level. Some of them are Product
innovation, Process innovation, Tool innovation, Procurement innovation, or Marketing methods
(details will be discussed later). Choosing which innovation type, how and where to implement it
effectively are always critical questions for the management in both firm and project levels.
There has been a worrying fact that construction sector has not spent much in Research and
Development (R&D). In New Zealand, it is reported that R&D expenditure in construction industry only
accounts for less than 5% of the total expenditure in the sector and 62% of construction businesses
have no innovation activity (Statistics New Zealand, 2007). Many authors have agreed that resources
used to innovate such as R&D spending will increase the growth of productivity (Chancellor, 2015;
Hardie, Miller, Manley, & McFallan, 2012; Ozorhon, 2013). Besides, the main objectives of innovation
implementation of construction firms in New Zealand, according to Statistics New Zealand (2007), are
increase in revenue, costs reduction, and productivity improvement. Yet, the construction sector has
been undergoing 44% of innovation rate in the period from 2009 to 2013 which is lower than all
industries’ average rate of 46%.
On the lower scale, the most significant benefit of implementing innovation at project-level is
productivity improvement (Ozorhon et al., 2015). This relationship between innovation and productivity
in the construction industry has been examined and confirmed by Noktehdan, Shahbazpour, and
Wilkinson (2015). They also found that Tool, including construction tools or machinery equipment, is
the key innovation type in construction projects (henceforth, Tool in this research means construction
tools or machinery equipment used by labors in construction projects). On the other hand, Durdyev
and Mbachu (2011) found in their research, that major internal constraints including Level of skill and
experience of the workforce, Adequacy of construction method and Suitability or adequacy of the plant
& equipment employed are significantly slowing down productivity growth rate in New Zealand
construction industry. Lack of clear benefits of investing in construction technology or afraid of failure
are the most influencing innovation barriers (MBIE, 2013; Ozorhon et al., 2015).
In New Zealand context, there have been a few types of research on selection methodology for
investment decision on innovation, particularly innovations relating to construction tools, in
construction projects. There are many Multi-criteria Decision Making methods that can be of help. For
example, Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Delphi technique,
Complex Proportional Assessment (COPRAS), Technique for order of preference by similarity to ideal
solution (TOPSIS), etc. (Jato-Espino, Castillo-Lopez, Rodriguez-Hernandez, & Canteras-Jordana,
2014). Among those methods, AHP is the most popular, robust yet easy to use (Jato-Espino et al.,
2014). This research attempts to fill the gap by applying AHP to aid project managers to select the
most appropriate innovation to implement in their projects.

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1.3. Research Aim and Objectives
This research aims to build a practical model to help decision-makers in construction projects select
an appropriate innovative Tool that can significantly contribute to labour productivity rate improvement.
The aim will be approached by following steps. Firstly, construction innovation key components, types
and levels in project level will be explored. Secondly, studying the relationship between innovation and
productivity and major constraints of productivity growth rate in New Zealand context will be also
discussed. Finally, AHP models relevant to Tool innovation selection will be examined, analysed and
modified to match the situation.
In order to achieve the aim, the study has three objectives as follows:
 To explore and critically analyse innovation key components, types, and levels and to
examine the relationship of those factors in the innovation process, especially in project
level.
 To identify key or dominant types of innovation in New Zealand construction projects
accounting for labour productivity rate improvement.
 To examine and analyse major AHP method models that can be used for innovation type
selection, and to modify and propose one model that can aid decision makers in
construction projects to select one appropriate innovative Tool for their projects’ need.

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2. Literature Review
2.1. Introduction
In this section, literature on the topic of innovation and particularly innovation in project level will be
discussed. Levels or novelty of innovation implementation, components of innovation process and the
relationship between innovation and productivity in New Zealand construction context will also be
explored. Further part of this section will study various types of innovation and which are the most
eminent types in New Zealand construction sector. Finally this research will review the gap in the
literature and explore how it could approach the research scope and objective with some research
questions.
As discussed in Chapter 1, the construction industry in New Zealand consists of four sub-sectors
including Heavy and Civil Engineering, Residential buildings, Non-residential or Commercial buildings,
and Construction Services. Taking preponderant roles in the industry, SMEs are key players in all sub-
sectors except only Heavy and Civil Engineering sub-sector where only big firms are dominant (MBIE,
2013, 2014a, 2014b, 2015; The Building and Construction Sector Productivity Partnership, 2013).
Moreover, there has been a surging trend of residential and non-residential building work in New
Zealand, particularly in Auckland and Canterbury, with rises of 5.5% and 5.0% respectively (Statistics
New Zealand, 2016). This trend is the answer to housing issue which is very critical in the two regions.
Therefore, any improvement in labour productivity rate through innovation and new technology
implementation will likely bring remarkable benefits to SMEs’ performance.
2.2. Definitions
There have been several definitions proffered for innovation at different levels as follows:
 At nation and industry levels, Urabe (1988, p. 3) defined innovation as “the generation of
a new idea and its implementation into a new product, process, or service, leading to the
dynamic growth of the national economy and the increase in employment as well as the
creation of pure profit for the innovative business enterprise”.
 At firm and project levels, Lim et al. (2010) defined innovation as “the purposeful search
for new knowledge and the systematic application of this knowledge in production”.
Focusing on project-based problem solving, an innovation is defined as a new idea
implemented in a construction project with the intention of deriving additional benefits
although there might have been associated risks and uncertainties (Ling, 2003). She also
mentioned that the novel idea may involve new design, technology, material component
or construction method deployed in a project.

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Moreover, innovation in construction can also be described as “the successful development and/or
implementation of new ideas, products, process or practices, in order to increase organizational
efficiency and performance” (Akintoyle, Goulding, & Zawdie, 2012, p. 5).
2.3. Market-based innovation and resource-based innovation
There is an “optimal balance of market-based or externally driven innovation and resource-based or
internally driven innovation” (Barrett et al., 2008). Akintoyle et al. (2012) confirmed these perspectives
of innovation. They had further explanation that “market-based view of innovation is a variation of
‘demand pull’ innovation, which utilizes the role of institutional and market factors to stimulate
innovation at the firm level”; meanwhile “the resource-based view of innovation is based on the
understanding of firms identifying and developing resources that enable them to shape market
conditions”. Sexton and Barrett (2003a) suggested the synthesis of market-based and resource-based
views of innovation as follows:
Figure 2-1: Synthesis of market-based and resource-based views of innovation
Source: Sexton and Barrett (2003a)
Barrett et al. (2008) suggested two principal modes of innovation to provide “better understanding of
the shifting balance between market-based and resource-based innovation”. They are Mode 1 –
Single-project, focusing on cost orientated client relationship, which is driven by market-based; and
Mode 2 – Multi-project, focusing on value orientated client relationship, which is aligned to “an equal
balance between market-based and resource-based innovation market, and enhancing the
effectiveness of its resources”. Since these modes help innovators know what type of innovation
activity to pursue in any given interaction environment, the authors suggested to have a “hybrid” mode
of innovation rather than fixing one mode of innovation activity.
2.4. Components of Innovation
As suggested by Ozorhon (2013), there are seven components of innovation such as Drivers, Inputs,
Innovative activities, Barriers, Enablers, Benefits and Impacts. Key indicators of each component are

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shown in the Table 2-1 below. Some additional indicators were proposed in the later research by
Ozorhon et al. (2015) are put in the Table for better reference. The authors found that, in project level
innovation implementation:
(i) The top two indicators among the others are Lack of clear benefits and Unavailability of
Materials to obstruct innovation;
(ii) Training policy and Reward schemes to enable innovation;
(iii) Environmental sustainability and Design trends to drive innovation;
(iv) External and Internal knowledge resources to activate innovation;
(v) Productivity and Client satisfaction increases at project-level benefits; and
(vi) Company image and Technical & Managerial capability improvement at firm-level
benefits.
It can be observed from the research that the labor force at projects can work productively with new
tools and equipment if sufficient training provided to the workers.
Besides, other interesting results from the research may draw our attention. Firstly, Regulation,
Legislation, and Corporate responsibility are not significant indicators to drive innovation in a project.
However, this could affect the innovation motivation indirectly via Consultants and Designers as
mentioned in Ozorhon (2013). Secondly, the Barriers having unexpectedly negative influence to the
Inputs. It means that challenges occurring in the process of innovation could not hinder the resources
put into the innovation development. Thirdly, research and development (R&D) spending are in direct
proportion to the construction productivity growth. Other authors such as Chancellor (2015) and Hardie
et al. (2012) also shared the same opinion about this finding. Finally, collaborative partnering, e.g.
partnership between construction firms and suppliers, subcontractors, or universities, is a key strategy
to cope with obstructions during the innovation process. Similar evidence could be observed in
Brewer, Gajendran, and Runeson (2013) or Broechner and Lagerqvist (2016).
Table 2-1: Innovation Components and their indicators
(Adapted from Ozorhon, 2013; Ozorhon et al., 2015)
Innovation Components and Their Indicators
Barriers (Obstacles/Challenges) Enablers (Factors overcoming the barriers/Increasing
innovation rate)
Financial risks Collaborative partnering
Lack of clear benefits Commitment (from stakeholders)
Lack of collaboration among project partners Early contractor involvement
Lack of experienced and qualified staff Innovation policy
Lack of financial resources Knowledge management practices
Temporary nature of projects Leadership (with critical role of project managers)
Time constraints Reward schemes
Unavailability of materials Supportive work environment
Unsupportive organizational culture Training policy
Unwillingness to change
Benefits Impacts (Wider-outputs on project participants such as
Client, Designer, Contractor and Supplier)

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Innovation Components and Their Indicators
Firm-level outputs Better company image
Company image and reputation improvement Decrease in cost and duration
Future business collaborations and market growth Future business collaborations with project parties
Gaining experience HR improvement
Intellectual property Increase in technical and organizational capability
Long-term profitability Market penetration and growth
Technical and managerial capability improvement Product quality improvement
Project-level outputs Productivity
Client satisfaction improved
Cost and duration decreased
Product quality improved
Productivity increased
Drivers (Primary motivation encourages and fosters
innovations)
Innovative activities (New or Improved products and
processes)
Competition level Automation of processes
Corporate responsibility Energy efficient materials
Design trends ICT
End user requirements OR Client requirements Integrated design
Environmental sustainability Lean construction
Project and corporate performance improvement New organizational methods and relations
Regulations Off-site manufacturing
Technological developments
Project environment (where innovation is
implemented)
Inputs (Resources used to develop/adopt innovation
types such as Product, Process or Organization)
Parties involved Capital
Primary objectives Consultancy
Project achievement(s) External knowledge resources (transferred from
suppliers, partners, universities, institutions)
Size of project HR or Innovation team
Type of project Internal knowledge resources
New ideas and concepts
R&D spending
Further exploration of motivations or drivers of innovation implementation in construction firms, other
authors have found some key findings such as commitment and organizational motivation will be
increased as consequences of high-expected goals and favorable innovation results (Dulaimi, Ling, &
Bajracharya, 2003). Clients’ requirements indicator is also shared by Ling (2003) that pressures from
clients on construction firms to improve quality, reduce costs and speed up construction processes will
lead to innovation. Or there are some suggestions by Dulaimi, Ling, and Bajracharya (2002) on
motivating innovators such as firms should create a reward system to recognize innovators and
promote innovation, give staff more time for them to have a chance to develop, and test new ideas are
also supported by Ozorhon et al. (2015).
In project level, it is also important to note that leadership indicator is considered one of the main
innovation enablers, similarly evidenced in Tatum (1987); Ozorhon, Abbott, and Aouad (2014).
Decisions made by the project managers are very critical to direct the projects’ innovation activities
under tight budget and timeframe, especially if the construction firms are in survival stage when the

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risk of innovation is higher than benefits it may generate. One good example can be the investment of
pneumatic mortar/screed conveyor in high-rise building construction. Instead of moving mixed mortar
on the ground to upper floors by wheelbarrows, this machine can pump mortar directly to working area
and therefore it will save a lot of time. This innovation is not new, its benefit is obvious, however, due
to the initial cost, and availability of the machine delivered to the project on time, the project manager
may not decide to invest.
According to Barrett et al. (2008), there are three folds of the motivation for construction firms to
innovate as follows:
- In survival stage, smaller firms are not always motivated to innovate since they want to
limit their exposure to costs and risks of innovation as much as possible due to their lack
of organizational resources.
- Hierarchy of motivational drivers for innovation are dynamic and cyclical.
- Not all small firms want to grow indefinitely in size as long as they find it is stable at that
level in terms of customer’s satisfaction.
Survival – small construction firms, owing to the type of markets they operate in and their lack
of organizational resources and concentrate foremost on project-based innovation focusing on
survival.
Stability – once survival has been confidently achieved, over the medium term, firms are
sufficiently motivated to look towards consolidating and stabilizing their market or resource
position or both to ensure steady state.
Development – this stability provides the necessary motivation to exploit the prevailing stability
and to develop and grow.
Figure 2-2 Motivational needs.
Source: Barrett et al. (2008)
It is important to notice that most of clients will desire their project to be quickly delivered on the strict
budget and with good quality. Therefore, in the long run, firms must innovate to keep their business
profitable and secure future businesses (Ozorhon et al., 2015).
Development
Stability
Survival

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2.5. Innovation process in construction projects
As mentioned in the Introduction part, there is currently a great deal of research focusing on innovation
at firm level. Blayse and Manley (2004) explained the reason behind this fact is due to high
fragmentation level of construction projects that mean many activities performed by many involved
parties. In order to deal with the problem, Ozorhon (2013) proposed a framework for innovation
process in construction projects as shown in Figure 2-3. In the model, all innovation components build
up a system where the process is cyclic:
 The Drivers will motivate the innovation process;
 The Enablers are factors that overcome the Barriers and increase innovation rate;
 The Inputs are resources used in the process;
 The Barriers will hinder the innovation process.
Each part in the system will contribute to and benefit from the innovative activities. All of them will
interact in the project environment determined by project type and size; parties involved; primary
objectives and project achievements. The author also pointed out that experience and knowledge
obtained in this project can be transferred to future projects with similar or different innovations. For
example, if one client requires their architecture firm to design façade of a high-rise residential building
to achieve green building standard, the benefit that can reduce the energy consumption in that
building will help the firm gain experience and knowledge that could be used in future similar projects.
Figure 2-3: Innovation Process in Construction Projects
Source: Ozorhon (2013)
By studying four case studies, Ozorhon (2013) concluded that, firstly, many construction firms usually
seek joint innovation in various collaborative partnership forms. They can be such as the partnership
between client and contractor, contractor and supplier or early involvement of contractor in the design
stage. Contractor’s early involvement can be seen in Design and Build contract. This type of
procurement will bring more value and benefits to the client than the traditional way as reported by

12
Hardie and Saha (2012). Collaboration with other businesses is also typical in New Zealand (Statistics
New Zealand, 2014). Secondly, difficult changing the traditional way of working and the unguaranteed
return on investment hinder innovation. This is evidenced in Kramer et al. (2010). The authors argued
that despite multiple advantages of innovation, the barrier for innovation adoption was the traditional
culture of construction sector rather than financial matters. Thirdly, good innovation management is
critical to provide cost-effective innovative solutions such as reward schemes to encourage
creativeness. Finally, innovation performance should be measured accordingly to innovation
objectives, e.g. material cost reduction, quality of the work improvement, less occupational health
issues, etc. Next section will review innovation process in construction firms to compare the major
differences between two levels.
2.6. Innovation process in construction firms
Barrett et al. (2008), via case study, found that the innovation process most likely tends to be
behavioral rather than rational innovation. Five parts of this process include Diagnosis, Action plan,
Taking action, Evaluation and Specific learning. These form a research cycle starting with “sensing an
opportunity or need to innovate in response to market, project and/or client conditions”, the authors
mentioned.
Figure 2-4 The process of innovation
Throughout the innovation process, in order to be successful and able to achieve the desired
performance, Barrett et al. (2008) suggested “action forces” should be stronger than “reaction forces”.
An example of “action force” can be support from top management, or sufficient funding for needed
DIAGNOSING
(Identifying the
innovation
gap)
ACTION
PLANNING
(Considering
alternative
courses of
action)
TAKING
ACTION
(Selecting a
course of
action)
EVALUATING
(Studying the
consequences
of the
innovation)
SPECIFYING
LEARNING
(Identifying
areas for
improvement)

13
technology. In contrast, example of “reaction force” can be subcontractors refuse to change, or new
technology is difficult for workers to apply on site and therefore they are reluctant to change.
Figure 2-5 Reaction forces and Action forces in innovation process
Ozorhon et al. (2010) proposed a model (shown in Figure 2-6) consisting of innovation components to
measure the performance of innovation in construction firm level. This model happens in the project
life cycle consisting of three stages namely Ideas, Conversion and Diffusion. The findings of the
research are shown in Table 2-2 in comparison with the top innovation influences in project level
mentioned above.
Figure 2-6: Framework for innovation performance measurement
Source: Ozorhon et al. (2010)
Table 2-2: Comparison of key significant innovation indicators in firm and project level
Components Key significant innovation indicators in
firm level
Key significant innovation indicators in
project level
Drivers  Firm performance such as cost
reduction, productivity and effectiveness
 Environmental sustainability
 Environmental sustainability
 Design trends
Inputs  Internal knowledge resources:  Internal knowledge resources such as:

14
Components Key significant innovation indicators in
firm level
Key significant innovation indicators in
project level
o Innovation information provision
o Investment in training and education
 External knowledge resources:
o Clients
o Partners
o Company’s knowledge data.
o Staff’s knowledge data.
 External knowledge resources such as:
o Partners
o Clients and end-users
Enablers  Leadership
 Supportive work
environment/Collaboration with partners
 Training policy
 Reward schemes
Barriers  Economic conditions
 Availability of financial resources
 Lack of clear benefits
 Unavailability of materials
Innovation
practices
 Collaborative practices
 Contract management/Client relations
N/A
Innovators  Suppliers/manufacturers
 Design teams
N/A
Benefits/Impacts  Better company image
 Services/Client satisfaction/Product
quality/Process Improvement
 Company image improvement
 Technical and Managerial capability
improvement
 Productivity growth
 Client satisfaction growth
Major findings from Ozorhon et al. (2010) include:
(i) Construction firms focus more on process innovation rather than suppliers who incline
toward to product or material innovation. It is because suppliers have more R&D
spending than contractors and their innovations are considered more significant than
contractors’ innovations. A report from Statistics New Zealand (2014) confirms this
evidence when it shows that almost 0% of total expenditure spent on product
development in construction sector;
(ii) Construction firms are better at generating ideas (in Ideas stage) rather than developing
ideas into feasible products/services/businesses (in Conversion stage) and spreading
developed ideas (in Diffusion stage);
(iii) Innovation ideas are mainly come from both internal and external knowledge resources.
Statistics New Zealand (2014) supports this fact by showing that around 65% of
innovation ideas are from internal and external in construction sector; and
(iv) Clients and partners drive contractors to innovate their processes and services which
represent the “Market-Pull” rather than “Resource-Push” effort from the contractors.
These innovative activities are organisation-based and have incremental changes in
concept rather than product-based and radical changes.
As mentioned in Slaughter (2000), incremental change and radical change are among five innovation
categories. Construction innovation categories and types will be discussed further in the next section.
2.7. Categories and types of construction innovations
Slaughter (2000) proposed an approach to categorizing innovations based on their advancement of
the state of knowledge and their links to other systems. The categorisation of innovations includes

15
Incremental innovation, Architectural innovation, Modular innovation, System Innovation and Radical
Innovation as follows:
 Incremental is a small change and has fewer impacts on other system components. For
example, using plastic rebar supports instead of concrete ones help contractors save time and
cost but this small innovation does not affect to the concept or links to other systems.
 Architectural is a small change within a specific area or core concept but resulting in a
significant modification of other systems or components. For example, using superplasticizer
concrete and bottom-up pumping minimize concrete consolidation problems (Sommers, 1986)
is an architectural innovation since it uses an available material, which is concrete, but results
in major changes in related processes.
 Modular is a significant innovation (or new concept) within a specific region but resulting in no
change in other systems or components. For example, using autoclaved aerated concrete
(AAC) block instead of traditional burnt clay block is a modular innovation with a high
modification in the concept but no change in links to other systems.
 System is a set of multiple innovations that work together to provide new attributes or
functions or significantly advance the state of practice or knowledge. A new construction
method for external walls, which uses gang formwork with openings catering for windows
instead of traditional formwork, foam concrete instead of normal weight concrete, and
reinforcing mesh instead of normal reinforcing bars, would be an example of a system
innovation, integrating three different innovations to obtain new external wall heat insulation
performance level.
 Radical is a completely new concept that often changes the character and nature of an
industry. Radical innovations are rare and unpredictable and often cause previous solutions to
be obsolete. For instance, Building Information Modelling (BIM) is a new technology with the
ability of radically changing the way construction industry has been doing.
Figure 2-7: Innovation Categories
Source: Slaughter (2000)
Incremental changes are more frequent in the construction industry but radical changes are the most
powerful, as also emphasized by Koskela and Vrijhoef (2001). Beside the categorization of innovation,
we will review other innovation classification system, which is based on the type of innovation. Table
2-3 summarizes a few various innovation types classification by different authors. Two common

16
innovation types can be seen from the Table are Product innovation and Process innovation that
involves Tool and Task improvement.
Table 2-3: Classification of various innovation types
Innovation types Authors
- Disruptive, Application, Product, Platform, Line-extension,
Enhancement, Marketing, Experiential, Value-engineering, Integration,
Process, Value-migration, Organic, and Acquisition.
Moore (2005)
- Product (good or service), Process, Marketing methods, and New
organizational method in business practices, workplace organization or
external relations.
OECD and Eurostat (2005)
- Product, Procurement, Process. Abbott, Jeong, and Allen
(2006)
- Profit model, Network, Structure, Process, Product performance,
Product system, Service, Channel, Brand and Customer engagement
Keeley et al. (2013)
- Product, Process, Position, Paradigm. Tidd and Bessant (2013)
- Product (goods or service), Process (Operational process,
Organizational or Managerial process), Marketing method.
Statistics New Zealand
(2014)
- Product, Design, Tool, Function/Task, Technology (Design & Product),
Method (Tool & Function/Task).
Noktehdan et al. (2015)
As mentioned in Section 2.6, contractors focus more on process innovation in firm level. In project
level, Noktehdan et al. (2015) show that Tool and Function appear to be the most popular innovation
types. Modular innovations incline toward to Tool and Function and this category happens when
project objectives focus on single benefit (such as Cost savings, Time reduction, Quality improvement,
Sustainability, or Safety, etc.). Therefore, productivity has a high chance to be boosted through the
Modular innovation involving significant modifications for Tool and Function.
However, according to a report conducted by Durdyev and Mbachu (2011), there are several key on-
site labour productivity constraints in New Zealand construction industry that project managers should
be cautious when implementing productivity improvement in construction projects. The authors defined
that there are two types of constraint, i.e. Internal and External. Internal constraints include Project
finance, Workforce, Technology/Process, Project Characteristics, and Project Management/Project
Team Characteristics. Meanwhile, External constraints include Statutory Compliance, Unforeseen
events, and other external forces such as economy, political issues, etc. The report shows that Internal
constraints are more dominant than External constraints. Findings related to subcomponents that have
the highest impact on labour productivity are shown in the table below.

17
Table 2-4: Key subcomponents having highest impact on labour productivity
Source: Durdyev and Mbachu (2011)
2.8. Summary
This chapter reviews current literature on Innovation and its components in both construction firm level
and construction project level. Two models used for innovation performance measurement in firm and
project level are also discussed. The relationship between innovation implementation and productivity
improvement in New Zealand construction context is reviewed alongside with the popularity of each
innovation type. Summarily, the key findings based on the literature review are:
(i) Most of the innovation types in construction firm level are Process innovation. On the
other hand, there is evidence that Tool innovation, a lower level of Process innovation, is
more popular in project level.
(ii) Incremental innovations are dominant in construction firm level, while Modular
innovations happen more in project level.
(iii) In project level, project managers often think about key barriers such as the lack of clear
benefits and availability of materials when making decisions on innovation
implementation. However, barriers, in fact, have a negligible effect on innovation
activities.
(iv) Since Tool and Function/Task innovation are more popular in project level, collaborative
partnership with equipment suppliers are more feasible and recommended.
(v) Training policy is the most important innovation enabler in project level. Therefore, new
tools should be user-friendly or less training required in order to reduce workers’
reluctance to change.
(vi) Project managers should choose Tool innovation with the intention of defect-free
operation in mind since rework is considered as one of the key constraints of on-site
productivity improvement.
(vii) There is no clear evidence of interdependencies among innovation components such as
Drivers, Barriers, and Enablers in project level.

18
(viii) There is a missing decision support system integrating quantitative and qualitative data
that project managers could refer to when selecting appropriate Tool innovation for their
projects.
Next chapter will examine methodology related to Multi-criteria Decision-making (MCDM) techniques
and attempt to outline a model based on existing literature to help project managers choose the most
suitable option.

19
3. Research Methodology
3.1. Introduction
This chapter will discuss Multi-criteria Decision-making (MCDM) techniques, particularly Analytic
Hierarchy Process (AHP) and Analytic Network Process (ANP). Further examination will be conducted
to justify which technique shall be used for this research. Based on the literature review, a decision
support system including objective, criteria and alternatives shall be built. Then a questionnaire for
pairwise comparison shall be designed to survey the target group. Finally, synthesis of priorities
combined with sensitivity analysis shall be reviewed. These steps can help determine whether the
solution is implementable and robust (T. L. Saaty & Vargas, 2013).
3.2. Selection method with MCDM techniques
3.2.1. Key terminologies
Rezaei (2015) mentioned that a MCDM problem includes a number of alternatives evaluated with
regard to a number of criteria in order to obtain the ranking of alternatives. According to the author, the
MCDM problem is shown as a matrix as following:
𝑨 =
𝒄 𝟏 𝒄 𝟐 ⋯ 𝒄 𝒏
𝒂 𝟏
𝒂 𝟐
⋮
𝒂 𝒏
(
𝒑 𝟏𝟏 𝒑 𝟏𝟐 ⋯ 𝒑 𝟏𝒏
𝒑 𝟐𝟏 𝒑 𝟐𝟐 ⋯ 𝒑 𝟐𝒏
⋮ ⋮ ⋱ ⋮
𝒑 𝒎𝟏 𝒑 𝒎𝟐 ⋯ 𝒑 𝒎𝒎
)
In the matrix above, {𝑎1, 𝑎2, … , 𝑎 𝑛} is a set of alternatives; {𝑐1, 𝑐2, … , 𝑐 𝑛} is a set of criteria; 𝑝𝑖𝑗 is the
score of alternative 𝑖 with regard to criterion 𝑗. The objective is to choose an alternative 𝑖 with highest
overall value. Overall value 𝑉𝑖, which can be obtained by multiplying vector of weights 𝑤 = (𝑤1, … , 𝑤 𝑛)
with the 𝑝𝑖𝑗.
Among several other MCDM techniques, AHP and ANP, which were developed by Thomas L. Saaty,
are the most popular methods used in construction (Jato-Espino et al., 2014). AHP and its
generalization ANP are the natural psychophysical way with absolute scales to measure tangible and
intangible factors using pairwise comparisons with judgements representing the dominance of one
element over another (T. L. Saaty & Islam, 2015). AHP is a theory of measurement through pairwise
comparisons and relies on the judgements of experts to derive priority scales (T. L. Saaty, 2008b),
while ANP is a generalization of the AHP with dependence and feedback within clusters of elements
(inner dependence) and between clusters (outer dependence) (R. W. Saaty, 2003). AHP and ANP
have been used widely around the world to gain better insights in many sophisticated decision
problems (T. L. Saaty, 2008a, 2009, 2012; T. L. Saaty & Cillo, 2008; T. L. Saaty & Islam, 2015; T. L.
Saaty & Vargas, 2013). In the construction industry, AHP application is more dominant with many
decision problems solved such as selection process of construction equipment or materials, bidder
selection, resources allocation, etc. (Jato-Espino et al., 2014).

20
AHP elements (or nodes) include an objective (or goal), criteria and alternatives (R. W. Saaty, 2003).
All elements in the decision problem are presented in a hierarchical structure as shown in Figure 3-1.
Meanwhile, ANP, which is shown in Figure 3-2, uses network structures to formulate decision
problems with dependence and feedback (T. L. Saaty & Cillo, 2008). The authors mentioned that ANP
works without making assumptions about the independence of higher-level nodes from lower-level
nodes or from nodes in the same level of hierarchy. In addition, the alternatives in the ANP will be
determined partially by the importance of the criteria, while only the criteria will determine the
importance of the alternatives in the AHP.
Figure 3-1: Three-level Hierarchical Structure of AHP.
Figure 3-2: Network Structure of ANP.
AHP and ANP share the same fundamental scale, is shown in Table 3-1, used for the judgements
while performing the pairwise comparisons. The number of pairwise comparisons, which will be done,
is calculated by the formula
𝑛(𝑛−1)
2
(Rezaei, 2015).
Table 3-1: Fundamental Scale for making judgements
Adapted from T. L. Saaty and Islam (2015)
Fundamental Scale Explanation
1 Equal importance/preference/likelihood Two activities contribute equally to the objective
2 Between Equal and Moderate
3 Moderate importance/preference/likelihood of one
over another
Experience and judgement slightly favour one
activity over another
4 Between Moderate and Strong
5 Strong or essential importance/preference/likelihood Experience and judgement strongly favour one
6 Between Strong and Very strong
7 Very strong or demonstrated
importance/preference/likelihood
An activity is favoured very strongly over
another; its dominance demonstrated in practice
8 Between Very strong and Extreme
9 Extreme importance/preference/likelihood The evidence favouring one activity over

21
another is of the highest possible order of
affirmation
Use reciprocals for inverse comparisons If activity i has a number assigned to it when
compared with activity j, then activity j has the
reciprocal value when compared with activity i
The pairwise comparison results on n criteria will be presented in a square matrix A of order n in which
every matrix element 𝑎𝑖𝑗(𝑖, 𝑗 = 1, … , 𝑛) is the weight of the criteria drawn from the fundamental scale
(Görener, 2012; T. L. Saaty & Cillo, 2008). The diagonal (𝑎11, 𝑎22, … , 𝑎 𝑛𝑛) always equals 1 and the
lower triangular matrix elements are 𝑎𝑗𝑖 =
1
𝑎 𝑖𝑗
.
𝐴 𝑛𝑥𝑛 = [
𝑎11 𝑎12 ⋯ 𝑎1𝑛
𝑎21 𝑎22 ⋯ 𝑎2𝑛
⋮ ⋮ ⋱ ⋮
𝑎 𝑛1 𝑎 𝑛2 ⋯ 𝑎 𝑛𝑛
]
After that, the reciprocal matrix will be normalized by dividing each matrix element by the sum of its
column. Vector of weights (also known as priority vector) can be calculated by averaging rows of the
normalized matrix. Normalized matrix 𝐴 (also known as normalized relative weights) will then multiply
with the vector of weights 𝑤⃗⃗ = (𝑤1, … , 𝑤 𝑛) to determine the eigenvalue of 𝐴 as follows:
𝑨𝒘⃗⃗⃗ =
𝑨 𝟏 𝑨 𝟐 ⋯ 𝑨 𝒏
𝑨 𝟏
𝑨 𝟐
⋮
𝑨 𝒏
[
𝒂 𝟏𝟏 𝒂 𝟏𝟐 ⋯ 𝒂 𝟏𝒏
𝒂 𝟐𝟏 𝒂 𝟐𝟐 ⋯ 𝒂 𝟐𝒏
⋮ ⋮ ⋱ ⋮
𝒂 𝒏𝟏 𝒂 𝒏𝟐 ⋯ 𝒂 𝒏𝒏
][
𝒘 𝟏
𝒘 𝟐
⋮
𝒘 𝒏
]
= 𝝀
[
𝒘 𝟏
𝒘 𝟐
⋮
𝒘 𝒏
]
= 𝝀𝒘⃗⃗⃗
𝑨𝒘⃗⃗⃗ = 𝝀𝒘⃗⃗⃗ ⟺ (𝑨 − 𝝀𝑰)𝒘⃗⃗⃗ = 𝟎 is a system of linear equation with a nontrivial solution if and only
if 𝒅𝒆𝒕(𝑨 − 𝝀𝑰) = 𝟎, so 𝝀 is an eigenvalue of matrix A. Next we will calculate the Consistency Index (CI)
of pairwise comparisons which given by 𝑪𝑰 =
𝝀 𝒎𝒂𝒙−𝒏
𝒏−𝟏
, where 𝝀 𝒎𝒂𝒙 is the largest eigenvalue and 𝒏 is the
order of the reciprocal matrix. Consistency Ratio (CR) is calculated by 𝑪𝑹 =
𝑪𝑰
𝑹𝑰
, where Random
Consistency Index RI is shown below. CR is recommended to be ≤ 5% when three elements are
compared; ≤ 8% when four elements are compared and ≤ 10% when more than four elements are
compared (T. L. Saaty & Cillo, 2008).
Table 3-2: Random Consistency Indices.
(T. L. Saaty & Cillo, 2008)
Order of matrix (n) 1 2 3 4 5 6 7 8 9 10
RI 0.00 0.00 0.52 0.86 1.11 1.25 1.35 1.40 1.45 1.49
Summarily, AHP concept includes following steps (R. W. Saaty, 2003):
(i) Determine decision problem elements (Goal/Objective, Criteria, Sub-criteria, and
Alternatives);
(ii) Build hierarchical structure.

22
(iii) Make judgements using The Fundamental Scale.
(iv) Perform pairwise comparisons of elements in lower hierarchical level with respect to their
importance/preference/likelihood towards their higher hierarchical level.
(v) Calculate priorities and consistency ratio.
(vi) Synthesize the priorities and select the best alternative.
(vii) Perform sensitivity analysis.
While ANP technique comprises following steps (T. L. Saaty & Vargas, 2006):
(i) Build decision problem network.
(ii) Perform pairwise comparisons among the clusters as well as nodes that are
interdependent on each other.
(iii) Present the priorities derived from pairwise comparisons in super matrix.
(iv) Synthesize the priorities of the criteria and alternatives and select the best alternatives.
3.2.2. Pros and Cons of AHP and ANP
According to Goepel (2011), AHP and ANP have their own advantages and disadvantages as
followings:
 Advantages:
o AHP:
 Can combine multiple responses from several participants to a consolidated
result.
 People usually agree with the final ranking as the technique is mathematically
based, neutral and objective.
 Can easily calculate with Excel sheet.
o ANP:
 General approach for any decision problem and some problems can only be
solved by ANP (since they involve feedbacks and dependence of higher level
elements/nodes in a hierarchy on lower level elements/nodes).
 Can gain deeper understanding of a specific problem and its relationship with
relevant factors.
 Disadvantages:
o AHP:
 Although this technique is called psychophysical way, pairwise comparison is
quite artificial when comparing a set of elements.
 It is required to reconsider the inputs from participants if the Consistency
Ratio (CR) is above 0.10.
 It is recommended that the number of criteria or sub-criteria should be less
than 5.

23
 It is important to carefully introduce the scale of pairwise comparisons to
participants without AHP knowledge and ensure that they have full
understanding of the questions pose during pairwise comparisons. This is
confirmed by Shapira and Goldenberg (2005) since there is problematic
correspondence between the verbal and the numeric scales.
o ANP:
 It is extremely challenging to explain the concept and process to
management.
 Special software is required to calculate results.
 It is impossible to verify the result due to feedback loops and interrelations.
 It is too complex in order to be a standard tool for practical decision making in
an organization.
Due to characteristic of construction projects and objective of this research that a practical decision
support system would be more suitable than a complex one. Therefore, AHP approach is chosen as
the research method. Next section will examine selection model based on existing literature and adjust
it to suit the research’s objective.
3.3. Proposed decision support system
3.3.1. Selection models based on literature
Skibniewski and Chao (1992) introduced a model of evaluating advanced construction technology with
AHP method. This model is structured in a hierarchy of evaluation elements as shown in Figure 3-3.
The Criteria at level 2 of the hierarchy consists of two elements labelled Cost and Benefit factors which
are tangible and intangible. In an illustrative example, the authors structured the decision problem of
choosing two tower cranes as shown in Table 3-3.
Figure 3-3: Evaluation of Technology Alternatives Hierarchical Structure
Adapted from Skibniewski and Chao (1992)

24
Table 3-3: Decision Attribute Hierarchy
Adapted from Skibniewski and Chao (1992)
Level 1 Level 2 Level 3 Level 4 Level 5
Goal Criteria and Sub-criteria Alternatives
Overall
assessment
Cost factors
NPW Costs
Initial Investment
Traditional Tower
Crane
Semi-automated
Tower Crane
Operating Costs
Risk Concerns
Safety Problems
System Flexibility
System Reliability
Benefit factors
Strategic Benefits Competitive Leading-edge
Operational Benefits
Quality Performance
Schedule Performance
Shapira and Goldenberg (2005) proposed a framework (exhibited in Figure 3-4) with the objective of
selecting the best alternative based on total evaluation integrating both cost and benefit evaluation.
The framework consists of three main modules, i.e. Cost Evaluation, Benefits Evaluation and Total
Evaluation. The core concept of the framework is an AHP-based selection process. The four-level
decision problem hierarchy is shown in Table 3-4. In this model, if cost difference between one
alternative and others is too great to be covered by any possible benefits in the future with respect to
the project budget, the model process will be stopped at selecting the alternative that has the lowest
cost.
Table 3-4: Equipment selection hierarchical structure
Adapted from Shapira and Goldenberg (2005)
GOAL
Work safety Progress delays Operational efficiency Managerial
convenience
Obstruction of crane
operator view
Heavy traffic Coverage of staging
areas by crane(s)
Previous experience with
equipment
Obstacles on site Site accessibility Pieces of equipment to
manage (flexibility)
Dependence on
outsourcing
Strong winds (safety) Strong winds (work
breaks)
Site congestion Pieces of equipment to
manage (complication)
Working on night shifts
(safety)
Labour availability Previous experience with
equipment
Working on night shifts
(management)
Overlapping of crane
work envelopes
Equipment age and
reliability
Alternative 1 Alternative 2 Alternative 3
Slaughter (2000) suggested project and company criteria to evaluate innovation alternatives as shown
in Table 3-5. Performance, worker safety, and complexity in project level are common criteria.
Table 3-5: Criteria for innovation alternatives evaluation at project and company level
Adapted from Slaughter (2000)
Project Criteria Company Criteria
 Cost
 Long-term facility performance
 Construction performance
 Duration (design, planning, and construction)
 Technical feasibility
 Worker safety
 Environmental impacts
 Risk of failure
 Implementation complexity
 Reputation impacts
 Unique capability
 New market
 Compatibility with and utilization of existing
capabilities
 Improvement of existing capabilities
 Appropriability of benefits
 Effective use of innovation
 Size of initial commitment

25
Figure 3-4: Model of equipment selection
Adapted from Shapira and Goldenberg (2005)
It can be seen from all three evaluation methods that the authors separated evaluation criteria into two
main groups, i.e. costs and benefits. Slaughter (2000), Goldenberg and Shapira (2007); Shapira and
Goldenberg (2005) and Skibniewski and Chao (1992) considered risk factors in their proposed
evaluation criteria. Those risk factors are in either work safety or cost incurred if risk events happen or
cost incurred if innovation activity fails. However, Slaughter (2000) argued that even if innovation
benefits in project level could not offset the expected cost, there will still be benefits in long-term at firm
level.
Another key finding from models of Shapira and Goldenberg (2005); and Skibniewski and Chao (1992)
is that they deal with heavy construction equipment with very own characteristics. Those often relate to
a very large initial cost of investment or rental cost and other related costs such as maintenance,
insurance, tax, license, mobilization, accessories, operating cost, climbing cost and operator cost.
And the last but not least, none of the abovementioned models except Slaughter’s deals with benefits
relating to productivity improvement via innovation implementation.

26
3.3.2. Proposed selection method
Based on the reviewed models and the literature review, the research model of decision support
system is proposed in Figure 3-5. There are three different steps in the model. First one is the Benefit
evaluation of implementing Tool innovation into a construction project. The evaluation will use AHP
method to prioritize or rank alternatives. The next step will evaluate cost related factors of the
alternatives. The final step, which is called Total evaluation, involves combining cost with AHP score,
calculating benefits-costs ratio and performing sensitivity analysis to figure out the best Tool
alternative.
The major difference can be seen from the proposed model is the scale of the implemented
innovation. The objective of this research report decision support system emphasizes the Tool
innovation in Modular category. Tools in this research context are small machinery equipment used in
construction project tasks. In this scale, as suggested by Slaughter (2000), that innovation has only a
major change in a core concept but no or minor changes in the links to other components or areas. As
summarized in 2.8, Modular innovations are often developed by Suppliers/Manufacturers where R&D
spending is stronger than Contractors. Collaborative partnerships between Suppliers and Contractors
are strong and productive (Ozorhon, 2013; Ozorhon et al., 2010; Ozorhon et al., 2015) enough to
encourage Contractors to implement innovation in their projects. Furthermore, Modular innovations
boost productivity in project level significantly, particularly in New Zealand construction context, as
found by Noktehdan et al. (2015). Hence the cost estimate structure for that equipment should not be
complex.
Despite its simple cost structure, Haas and Meixner (n.d.) recommend that in complex decisions, cost
evaluation should be done after alternatives’ benefits are ranked. The reason is due to discussing
costs together with benefits may, on some occasions, bring forth many political and emotional
responses.

27
Figure 3-5: Proposed Tool Innovation Selection Model
3.3.3. Proposed Hierarchy for Tool selection
Internal constraints of productivity improvement in New Zealand context (Durdyev & Mbachu, 2011)
mentioned in the Literature Review chapter will be used as part of the selection criteria. To reiterate
some key points from the study, the most relatively influent internal factors are:
(i) coordination and supervision of subcontractors (in Project Management/Project Team
characteristics category);

28
(ii) reworks (in Project Finance category); and
(iii) skill and experience level of the workforce (in Workforce category).
Those key factors are reflected in the level 2 and 3 of the proposed hierarchy. Other selection criteria
are from the key findings suggested by Ozorhon et al. (2010) and Kramer et al. (2010) such as
Training policy to improve workers’ skills and encourage them to change the old low productive way of
working; Worker safety issues relating to Musculoskeletal Disorders and Injuries in construction when
using inappropriate tools; or promoting awareness of the innovated Tool to workers so that they will
easily accept and use it. Further elaboration will be shown in the next paragraph.
Based on the above-mentioned findings, the proposed hierarchy for Tool selection is shown below.
Criterion Project Performance and its sub-criteria focus on increasing units produced per hours of
labour worked (Productivity Improvement), decreasing reworks (Quality improvement), and decreasing
lost-time equipment breakdown due to its low-quality built. Criterion Worker Safety and its sub-criteria
focus on decreasing occupational injuries that could harm the workers. And criterion Training and its
sub-criteria focus on increasing the chance that the workers will easily observe the benefits of the tool
innovation and can, therefore, reduce their reluctance to change (Observability), and the novel tools
are easy to use, no or minimum training required (Complexity).
Figure 3-6: Proposed Hierarchy of Best Tool Innovation Selection
3.4. Data collection
The data was collected through a survey questionnaire. The invitation was sent to the target group
consisting of 5 to 10 respondents who are decision makers at construction projects. According to
Ahmadi, Nilashi, and Ibrahim (2015), since AHP is not a statistically based method, small sample size

29
of participants is enough for decision implementation. Decision problem solved by AHP method can be
made by one decision maker or a group of experts. When group decision making is required,
geometric mean can be used to combine individual judgements (T. L. Saaty & Islam, 2015).
Respondents were requested to make judgements on pairwise comparisons using the Fundamental
Scale (from 1 to 9). The primary data was collected through online surveying tool named Google
Forms. Then the data was analysed with a freeware called PriEsT (Priority Estimation Tool) developed
by Siraj, Mikhailov, and Keane (2015).
Figure 3-7: AHP hierarchy structure for model test
Where:
 “Best Tool Innovation Selection” is the goal or objective of this Analytic Hierarchy
Process structure. In this research context, Tool Innovation is a significant change or
improvement in construction equipment or tools that helps boosting labour productivity
rate in construction project level.
 Criterion “Project Performance (PP)” and its sub-criteria focus on increasing units
produced per hours of labour worked (Productivity Improvement - PI), decreasing reworks
(Quality Improvement - QI) and decreasing lost-time equipment breakdown due to its low
quality built (Tool Duration - TD). Choosing a right tool that helps paying less effort while
producing more products is the aim of this criterion.
 Criterion “Worker Safety (WS)” and its sub-criteria (MSDs Reduction - MR and Injuries
Reduction - IR) focus on decreasing occupational injuries that could harm the workers.
Occupational health and safety issues will affect significantly to the labour productivity
rate.

30
 Criterion “Training (TR)” and its sub-criteria focus on increasing the chance that the
workers will easily observe the benefits of the tool innovation and can, therefore, reduce
their reluctance to change (Observability - OB), and the novel tools are easy to use, no or
minimum training required (Complexity - CO). The selected tool must be user-friendly and
require minimum training.
Three proposed alternatives used to test the model are:
 Rebar tying machine (A1), which is a battery powered tool with the size and weight of a
large drill. Key benefits suggested by CRE-MSD (2016c) include: iron workers tie
reinforcing bars twice as fast as tying by hand; workers experience fewer injuries related
to their hands, wrists and low back; and iron workers will highly recommend this tool to
other workers.
 Wall lifter (A2), which is a jacking device, allows carpentry trade workers to raise walls
from the floor in low-rise residential buildings with only one or two workers. Key benefits
from CRE-MSD (2016a) show that risk of serious injuries will be significantly reduced;
over-allocation of carpenters will be taken off weight since small crew consisting of 1-2
workers will be used; and due to a very effective use of workers, productivity rate will be
dramatically increased.
 Plaster pump (A3), also known as pneumatic wall finishing system, is a machine
consisting of a mixer and an air compressor that can spray plaster to render walls. The
traditional way of rendering walls takes a lot of time and effort when workers need to go
back and forth to take plaster mixed on the tray laid on the ground and then apply it to the
wall surface. CRE-MSD (2016b) highlighted that workers using this machine experience
less tiredness and more comfort compared to the traditional way with hand tools. Another
physical benefit includes reduction of arm and back injuries risk. Furthermore, labour
productivity rate for the large scale finishing work is also improved, as the study
mentioned.
According to Kramer et al. (2010), Wall lifter and Rebar tying machine have been used from
moderately to widely in Canada. A summary of questionnaire responses will be shown in the
Appendices section.

31
4. Data analysis
4.1. Introduction
To begin with, this chapter will discuss how the collected data will be validated and key findings from
the survey responses. Other part of this chapter includes the process of combining respondents’
judgements for pairwise comparisons of elements of the hierarchical structure. Next, priorities and
consistency ratio of the AHP model will be calculated and synthesized so that the best alternative can
be selected. Finally, sensitivity analysis of the model will be performed.
4.2. Survey respondent characteristics
Preliminary findings from the survey respondents include:
(i) The majority of them are from large firms with greater than 20 employees, accounting for
77.8% of total respondents.
(ii) But only one of them has R&D department, accounting for 11.1% of total respondents.
(iii) Two from firms with consultancy service that have the separate fund for innovation
activity, and surprisingly, only one firm that has R&D department. Two of them account
for 22.2% of total respondents.
(iv) Only one has involved in Heavy and Civil Engineering projects most, accounting for
11.1% of total respondents. The rest of them have involved in Residential and Non-
residential Building Projects.
(v) Only three respondents have taken place in innovation activity in their firms.
(vi) 44.4% of the respondents have made decisions on investment in innovative construction
equipment or tools for their projects.
(vii) The preponderance of the investment decision-makers mentioned above, 3 out of 4, said
Cost-Benefit Analysis is the technique that they often use to make investment decisions.
The last one said never use any technique.
(viii) The surveyor has not received any direct feedback from the respondents about the
difficulty of making their judgements on the pairwise comparisons.
4.3. Data validation
There are nine respondents answering the survey questionnaire. The targeted respondents of this
research are decision makers in construction projects such as project manager or construction
manager. Among the respondents, six are project managers, two are construction managers and one
is estimator which is not a targeted participant of this survey. Hence, there are eight valid responses
with complete answers finally.

32
4.4. Combining group judgements
Respondents’ judgements for pairwise comparisons will be combined by using geometric mean, as
suggested by T. L. Saaty and Islam (2015), to produce a consolidated judgement for each pairwise
comparison. Then, those consolidated judgements will be presented in matrices as below.
Figure 4-1: Pairwise comparison of criteria with
respect to (wrt) the Goal
PP WS TR
PP 1 0.455 1.316
WS 2.196 1 3.170
TR 0.760 0.315 1
Figure 4-2: Pairwise comparison of sub-criteria
wrt the criterion Project Performance
PI QI TD
PI 1 0.471 1.740
QI 2.122 1 2.568
TD 0.575 0.389 1
wrt the criterion Worker Safety
MR IR
MR 1 0.244
IR 4.105 1
wrt the criterion Training
OB CO
OB 1 1.539
CO 0.650 1
Figure 4-5: Pairwise comparison of alternatives
wrt the sub-criterion Productivity Improvement
A1 A2 A3
A1 1 0.879 1.043
A2 1.137 1 2.447
A3 0.959 0.409 1
wrt the sub-criterion Quality Improvement
A1 A2 A3
A1 1 1.056 1.632
A2 0.947 1 1.275
A3 0.613 0.784 1
wrt the sub-criterion Tool Duration
A1 A2 A3
A1 1 1.243 1.070
A2 0.804 1 2.320
A3 0.935 0.431 1
wrt the sub-criterion Musculoskeletal Disorders
Reduction
A1 A2 A3
A1 1 1.556 1.431
A2 0.643 1 1.632
A3 0.699 0.613 1
wrt the sub-criterion Injuries Reduction
A1 A2 A3
A1 1 0.932 0.625
A2 1.072 1 1.749
A3 1.600 0.572 1

33
wrt the sub-criterion Observability
A1 A2 A3
A1 1 1.334 0.938
A2 0.750 1 1.701
A3 1.066 0.588 1
wrt the sub-criterion Complexity
A1 A2 A3
A1 1 1.251 1.939
A2 0.799 1 1.196
A3 0.516 0.836 1
4.5. Benefits synthesis and sensitivity analysis
Calculation results for priorities and ranks of the alternatives from PriEsT software are shown below.
Consistency Ratios are all less than 10%, therefore the pairwise comparisons are consistent.
Table 4-1: Priorities and Ranking of the Alternatives
Level 1
GOAL
Best Tool Innovation Selection
Final
Priorities
Ranking
Level 2
Criteria
CR = 0.09%
PP
(0.250)
WS
(0.566)
TR
(0.184)
Level 3
Sub-criteria
CR = 1.42% CR = 0.00% CR = 0.00%
PI
(0.283)
QI
(0.533)
TD
(0.184)
MR
(0.196)
IR
(0.804)
OB
(0.606)
CO
(0.394)
Level 4
Alternatives
CR =
5.62%
CR =
0.40%
CR =
10.00%
CR =
3.53%
CR =
9.90%
CR =
8.34%
CR =
0.72%
A1 0.313 0.393 0.358 0.425 0.274 0.357 0.436 0.335 2
A2 0.452 0.350 0.401 0.330 0.406 0.360 0.319 0.382 1
A3 0.235 0.257 0.241 0.245 0.320 0.283 0.245 0.284 3
Following figures will exhibit the sensitivity analyses for Criteria and Sub-criteria that see changes of
the alternatives’ ranks.

34
Figure 4-12: Sensitivity analysis of the
alternatives’ ranks for the criterion Worker
Safety
alternatives’ ranks for the criterion Training
alternatives’ ranks for the sub-criterion MSDs
Reduction
alternatives’ ranks for the sub-criterion Injuries
Reduction
4.6. The alternatives’ cost estimates and priorities with respect to cost
The assumption of the cost estimate in this research report is the contractor will buy the tools instead
of hiring them. One major reason is due to the tools’ small capital cost so that every contractor can
afford it. Following cost estimate will calculate all relevant costs of owning the tools as suggested by
Cartlidge (2013).

35
Table 4-2: Alternatives' cost estimate
Table 4-3: Priorities of the alternatives' cost
Alternatives Costs
(NZD)
Normalized Costs
A1 1,268 0.040
A2 1,344 0.042
A3 29,250 0.918
Sum 31,862 1
4.7. Priorities of Benefits and Costs combination
The combination of Benefits and Costs of the alternatives are shown below.
Table 4-4: Combination of Benefits and Costs priorities
Alternatives Benefits
Priorities
Costs
Priorities
Benefit to Cost
ratio
Ranks
A1 0.335 0.040 0.335/0.040 =
8.15
2
A2 0.382 0.042 0.382/0.042 =
9.06
1
A3 0.284 0.918 0.284/0.918 =
0.31
3
Sum 1 1
What-if analysis shows that, based on the cost assumptions, if the cost of A3 remains unchanged, the
threshold that Benefit to Cost based ranking of A1 equals A2 is when the A1’s total cost is $165
cheaper than A2’s.

36
5. Discussion
5.1. Introduction
First part of this chapter will discuss the results and findings in Chapter 4. Second part consists of
discussion of the research report limitation and recommendation for further study.
5.2. Discussing the results
There are several key findings from the results such as:
 The majority of respondents replied that no or low R&D spending in their firms. This is
common as indicated by Ozorhon et al. (2010) and Statistics New Zealand (2014).
 Worker Safety is the highest ranked criterion. The majority of the respondents consider
this criterion is more important than Performance Improvement and Training factor when
selecting options. This may be related to the study of Durdyev and Mbachu (2011) where
the authors found that Health and Safety in Employment Act is the 3
rd
highest ranked
statutory compliance related constraint affecting productivity rate in the construction
industry.
 Respondents preferred Quality Improvement or Rework Reduction over Productivity
Improvement and Tool Duration when giving judgements about priorities of the sub-
criteria with respect to the Project Performance. Rework factor also had the highest
impact on labour productivity at the project level (Durdyev & Mbachu, 2011). This is to
confirm that Rework in construction projects is the crucial internal constraint that lowering
productivity score in any project.
 Respondents ranked Injuries Reduction (other loss-time injuries) significantly higher than
Musculoskeletal Disorders Reduction. This is, in fact, contrary to Kramer et al. (2010)
where the authors mentioned that MSDs are the “most common and costly compensated
work-related injuries”. Further awareness of MSDs among New Zealander construction
practitioners should be improved to reflect this issue in their risk management for
occupational health and safety.
 The preponderance of the respondents ranked sub-criterion Observability higher than
Complexity. This is very important to the peripatetic construction workforce characteristic.
The chosen innovative tool needs to have “high-visibility” in order to encourage more
workers to change their old way of working. And this factor is very helpful to reduce
“Reaction force” (including the reluctance to change) which is a barrier to innovation
implementation in construction project (Barrett et al., 2008; Gambatese & Hallowell,
2011b; Kramer et al., 2010; Slaughter, 1993).
 Generally, decision maker can choose the alternative Wall Lifter for it is ranked higher
than Rebar Tying Machine and Plaster Pump. However, the sensitivity analyses show
some thresholds where the ranks between Wall Lifter and Rebar Tying Machine change.

37
o Figure 4-12 shows that Rebar Tying Machine is ranked higher than Wall Lifter
when the weight of the criterion Worker Safety is less than 0.055 (0.566 currently).
o If the weight of the criterion Training increased to higher than 0.603 (0.184
currently), Rebar Tying Machine would be ranked higher than Wall Lifter, as
suggested by Figure 4-13.
o MSDs Reduction weight increased to 0.564 (0.196 currently) would help lift the
rank of Rebar Tying Machine as referred to Figure 4-14. Meanwhile, the
counterpart of MSDs Reduction factor observes the threshold where Rebar Tying
Machine has a higher rank than Wall Lifter at the weight of 0.436 (0.804 currently)
in Figure 4-15.
o In terms of Benefit to Cost ratio in the proposed selection model test, if the Benefit
priorities remain unchanged, Rebar Tying Machine will have overall higher rank
than Wall Lifter if its total cost is $166 cheaper than the Wall Lifter (based on the
cost assumptions). In reality, cost factor may change the priorities or rankings of
the alternatives if one option has more competitive cost and the gap of benefit
priorities is not so big.
5.3. Research report limitation and recommendation for further study
It was on a random basis when respondents were invited to give their judgements on the selection of
the alternatives. They are considered as the experts in their fields or at the senior level enough to be
able to make decisions for their projects. However, there are questions about how expert are the
experts? If they are not truly experts, will their judgements be reliable? Or will there be biased
opinions towards alternatives that they know best? Baker, Lovell, and Harris (2006) hinted to adopt
Delphi technique to overcome those issues and more importantly, to determine consensus on the
problem. Due to the limited time frame, professional networking, and scale of this research, the
performance of such technique could not be possible. Therefore, this technique should be used in a
further study to gain the confidence that the selection of criteria, sub-criteria, and alternatives or the
build-up of the proposed AHP hierarchical structure are on firm ground. Similar integration can be
found in Lee, Kim, Lee, and Han (2012); Vidal, Marle, and Bocquet (2011).
Developing and spreading new ideas in construction are not the strength of construction firms as
confirmed by Ozorhon et al. (2010). The authors suggested that new ideas are most likely coming
from suppliers. Therefore, further study should test whether the proposed model can be used by
construction tools manufacturers or not. Comparison of alternatives’ priorities or criteria’s priorities, on
the other hand, could be very useful for the manufacturers as a good market research tool.

38
6. Conclusion
The research aim is to build a practical model to help decision-makers in construction projects select a
right innovative Tool that can significantly contribute to the project performance improvement. Project
performance to this extent is related to the increase of labour productivity rate. Less effort will be spent
for the same project outcomes through implementing Modular category innovation.
The research objectives to achieve the aim have been met. Key innovation components, types, and
levels together with their relationship with innovation process in project level have been explored and
analysed in Literature Review chapter. Dominant innovation types in New Zealand construction
context accounting for reducing working hours required to deliver a project has been identified. Major
AHP method models have been examined, analysed, and modified to propose a model that can be
practically used by the industry practitioners at senior levels in construction projects.
Findings from the test of the proposed selection model and AHP hierarchy structure emphasise on
following characteristics that an innovative tool should have: worker safety in terms of less general
loss-time injuries, less rework and “high-visibility”. The proposed hierarchy structure is proved that it
can be used in real jobs to assist project managers’ decisions on new tool investment.
However, there is a limitation of the research that the level of confidence in the selection of the AHP
structure’s factors is not mentioned. The further study therefore is needed to carry out the Delphi
technique integrating with AHP to gain the consensus on the selection of the AHP hierarchy structure
factors. And the targeted respondents should be extended to key personnel in construction tool
manufacturers or suppliers to test the workability of the proposed model.

39
7. Appendix
Survey questionnaire
SCHOOL OF ENGINEERING AND ADVANCED TECHNOLOGY
MASTER OF CONSTRUCTION PROGRAM
PROJECT TITLE
A SELECTION METHOD OF INNOVATION IMPLEMENTATION
IN CONSTRUCTION PROJECTS IN NEW ZEALAND
INFORMATION SHEET
Researcher Introduction
 My name is Toan C. Nguyen. This is my Research Report project performed in partial
fulfilment of the requirements for the degree of Master of Construction specializing in Quantity
Surveying at Massey University, New Zealand.
Project Description and Invitation
 My research deals with selection method of innovation tools in construction project level. The
aim is to improve productivity rate of labour force in construction projects (including residential
and non-residential buildings in New Zealand market) by implementing innovative working
equipment. Innovation in Tools is known as a reliable way to boost productivity rate in
construction projects. However, decision makers in project-level may struggle when it comes
to selecting which Tools will yield best outcomes for their projects. This research proposes a
model using Analysis Hierarchy Process (AHP) as selection method to aid project managers.
A proposed Tool Innovation Alternatives Hierarchical Structure will be sent to project
managers to test the model’s workability and practicality. Findings from the survey will improve
the model and make it more user-friendly and reliable.
 If you are project manager who has experience of residential and non-residential projects in
New Zealand, please complete this Questionnaire. The survey has two sections and will take
approximately 15 minutes to complete. Thank you very much for your valuable time.

40
Data Management
 The obtained data will be used and analysed for the research only. No personal details will be
collected.
Participant’s Rights
 You are under no obligation to accept this invitation. If you decide to participate, you have the
right to decline to answer any particular question. However, completion and return of the
Questionnaire implies consent.
Project Contacts
 Should you have any questions about this Questionnaire as well as the project, please contact
me via my email address ngcanhtoan@gmail.com or toan.nguyen.1@uni.massey.ac.nz or my
number 022 188 4034. My supervisor is Dr Kenneth Sungho Park, his email address is
k.park@massey.ac.nz.
Disclaimer
 This project has been evaluated by peer review and judged to be low risk. Consequently, it
has not been reviewed by one of the University’s Human Ethics Committees. The researcher
named in this document is responsible for the ethical conduct of this research.
 If you have any concerns about the conduct of this research that you wish to raise with
someone other than the researcher(s), please contact Dr. Brian Finch, Director, Research
Ethics, telephone 06 356 9099 ext 86015, email humanethics@massey.ac.nz.

41
QUESTIONNAIRE: TOOL INNOVATION SELECTION
General Information
GI-1. What is the main registered
business/service of your company?
a. ☐ Heavy and Civil
Engineering
b. ☐ Residential Building
c. ☐ Non-residential Building
d. ☐ Construction Services
e. ☐ Consultancy
f. ☐ Suppliers
GI-2. When was your company established?
a. ☐ Less than 1 year
b. ☐ From 1 to 5 years
c. ☐ From 5 to 10 years
d. ☐ From 10 to 15 years
e. ☐ Over 15 years
GI-3. How many employee(s) does your
company have?
a. ☐ 0
b. ☐ 1 to 5
c. ☐ 6 to 9
d. ☐ 10 to 19
e. ☐ 20 to 49
f. ☐ 50 to 99
g. ☐ 100+
GI-4. Does your company have Research and
Development (R&D) department?
a. ☐ Yes
b. ☐ No
GI-5. Does your company provide a separate
fund for innovation activity?
a. ☐ Yes
b. ☐ No
GI-6. What is your current position or
responsibility?
a. ☐ Project manager
b. ☐ Construction manager
c. ☐ Other. Please
specify________________
__________
GI-7. How long have you been in the
business?
a. ☐ Less than 1 year
b. ☐ From 1 – 5 years
c. ☐ Over 5 years but less
than 10 years
d. ☐ Over 10 years
GI-8. What type of project have you involved in
most?
a. ☐ Heavy and Civil
Engineering Projects
b. ☐ Residential Building
Projects
c. ☐ Non-residential Building
Projects
d. ☐ Other. Please
specify________________
__________
GI-9. Have you ever been trained about new
technology, process, etc. in your company?
a. ☐ Yes.
b. ☐ No.
GI-10. Have you ever taken place in any
innovation activity in your company?
a. ☐ Yes.
b. ☐ No.
GI-11. Have you ever made any decision on
investment in innovative construction
equipment or tools for your project?

42
a. ☐ Yes. If Yes, please
answer Question GI-12.
b. ☐ No. If No, please go to
Section 2.
GI-12. If you decided to invest in innovative
construction equipment or tools for your
project, which decision making support
technique did you use?
a. ☐ Cost-Benefit Analysis.
b. ☐ Delphi technique.
c. ☐ Multi-criteria Decision
Making Method such as
AHP, ANP, etc.
d. ☐ Other. Please
specify________________
_________________
Main questionnaire
HOW TO ANSWER:
1. Please have a look at the hierarchy structure as shown in Figure 1.
Figure 1: AHP hierarchy structure for model test.
Where:
 “Best Tool Innovation Selection” is the goal or objective of this Analytic Hierarchy
Process structure. In this research context, Tool Innovation is a significant change or
improvement in construction equipment or tools that helps boosting labour productivity
rate in construction project level.
 Criterion “Project Performance (PP)” and its sub-criteria focus on increasing units
produced per hours of labour worked (Productivity Improvement - PI), decreasing reworks
(Quality Improvement - QI) and decreasing lost-time equipment breakdown due to its low
quality built (Tool Duration - TD). Choosing a right tool that help paying less effort while
producing more products is the aim of this criterion.

43
 Criterion “Worker Safety (WS)” and its sub-criteria (MSDs Reduction - MR and Injuries
Reduction - IR) focus on decreasing occupational injuries that could harm the workers.
Occupational health and safety issues will affect significantly to the labour productivity
rate.
 Criterion “Training (TR)” and its sub-criteria focus on increasing the chance that the
workers will easily observe the benefits of the tool innovation and can therefore reduce
their reluctance to change (Observability - OB), and the novel tools are easy to use, no or
minimum training required (Complexity - CO). The selected tool must be user-friendly and
require minimum training.
Three proposed alternatives used to test the model are:
 Rebar tying machine (A1), which is a battery powered tool with the size and weight of a
large drill, helps iron workers tie reinforcing bars faster than the traditional manual tool;
 Wall lifter (A2), which is a jacking device, allows carpentry trade workers to raise walls
from the floor in low rise residential buildings with only one or two workers; and
 Plaster pump (A3) is a machine attached with a mixer that can spray plaster for
rendering walls. Traditional way of rendering walls takes a lot of time and effort when
workers need to go back and forth to take plaster mixed on the tray laid on the ground and
then apply it to the wall surface.
2. Based on your judgement, please answer the pairwise comparisons for all criteria from 2.1 to
2.11 by ticking on the box of Criterion which is more important and Scale number (from 1 to 9).
Fundamental Scale Explanation
1 Equal importance/preference/likelihood Two activities contribute equally to the objective
2 Between Equal and Moderate
3
Moderate importance/preference/likelihood
of one over another
Experience and judgement slightly favour one
4 Between Moderate and Strong
5
Strong or essential
Experience and judgement strongly favour one
6 Between Strong and Very strong
7
Very strong or demonstrated
An activity is favoured very strongly over another;
its dominance demonstrated in practice
8 Between Very strong and Extreme
9 Extreme importance/preference/likelihood
The evidence favouring one activity over another is
of the highest possible order of affirmation
For example:
Pairwise comparisons for Criteria with respect to Goal “Best Tool Innovation Selection”
With respect to the Goal
A important or B?
Equal How much more?
1 ☒PP Or ☐WS ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☒7 ☐8 ☐9

44
PLEASE COMPLETE ALL PAIRWISE COMPARISONS:
o Pairwise comparisons for Criteria with respect to Goal “Best Tool Innovation
Selection”
With respect to the Goal
A important or B?
1 ☐PP Or ☐WS ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐PP Or ☐TR ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐WS Or ☐TR ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Sub-Criteria with respect to Project Performance
With respect to Project Performance
A important or B?
1 ☐PI Or ☐QI ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐PI Or ☐TD ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐QI Or ☐TD ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Sub-Criteria with respect to Worker Safety
With respect to Worker Safety
A important or B?
1 ☐MR Or ☐IR ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Sub-Criteria with respect to Training
With respect to Training
A important or B?
1 ☐OB Or ☐CO ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Productivity Improvement
With respect to Productivity
Improvement
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Quality Improvement
With respect to Quality
Improvement
A preferred or B?

45
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Tool Duration
With respect to Tool Duration
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to MSDs Reduction
With respect to MSDs Reduction
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Injuries Reduction
With respect to Injuries Reduction
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Observability
With respect to Observability
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
o Pairwise comparisons for Alternatives with respect to Complexity
With respect to Complexity
A preferred or B?
1 ☐A1 Or ☐A2 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
2 ☐A1 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9
3 ☐A2 Or ☐A3 ☐1 ☐2 ☐3 ☐4 ☐5 ☐6 ☐7 ☐8 ☐9

AN INNOVATIVE TOOL SELECTION METHOD FOR CONSTRUCTION PROJECTS IN NEW ZEALAND

AN INNOVATIVE TOOL SELECTION METHOD FOR CONSTRUCTION PROJECTS IN NEW ZEALAND

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