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

ii

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.

iii

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.

iv

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

v

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

1

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).

2

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 =

𝒄𝟏 𝒄𝟐 ⋯ 𝒄𝒏𝒂𝟏

𝒂𝟐

⋮𝒂𝒏

(

𝒑𝟏𝟏 𝒑𝟏𝟐 ⋯ 𝒑𝟏𝒏

𝒑𝟐𝟏 𝒑𝟐𝟐 ⋯ 𝒑𝟐𝒏

⋮ ⋮ ⋱ ⋮𝒑𝒎𝟏 𝒑𝒎𝟐 ⋯ 𝒑𝒎𝒎

)

In the matrix above, {𝑎1, 𝑎2, … , 𝑎𝑛} is a set of alternatives; {𝑐1, 𝑐2, … , 𝑐𝑛} 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, … , 𝑤𝑛)

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 activity over another

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, … , 𝑎𝑛𝑛) always equals 1 and the

lower triangular matrix elements are 𝑎𝑗𝑖 =1

𝑎𝑖𝑗.

𝐴𝑛𝑥𝑛 = [

𝑎11 𝑎12 ⋯ 𝑎1𝑛

𝑎21 𝑎22 ⋯ 𝑎2𝑛

⋮ ⋮ ⋱ ⋮𝑎𝑛1 𝑎𝑛2 ⋯ 𝑎𝑛𝑛

]

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 �⃗⃗� = (𝑤1, … , 𝑤𝑛) to determine the eigenvalue of 𝐴 as follows:

𝑨�⃗⃗⃗� =

𝑨𝟏 𝑨𝟐 ⋯ 𝑨𝒏

𝑨𝟏

𝑨𝟐

⋮𝑨𝒏

[

𝒂𝟏𝟏 𝒂𝟏𝟐 ⋯ 𝒂𝟏𝒏

𝒂𝟐𝟏 𝒂𝟐𝟐 ⋯ 𝒂𝟐𝒏

⋮ ⋮ ⋱ ⋮𝒂𝒏𝟏 𝒂𝒏𝟐 ⋯ 𝒂𝒏𝒏

][

𝒘𝟏

𝒘𝟐

⋮𝒘𝒏

]= 𝝀

[

𝒘𝟏

𝒘𝟐

⋮𝒘𝒏

]= 𝝀�⃗⃗⃗�

𝑨�⃗⃗⃗� = 𝝀�⃗⃗⃗� ⟺ (𝑨 − 𝝀𝑰)�⃗⃗⃗� = 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 =𝝀𝒎𝒂𝒙−𝒏

𝒏−𝟏, where 𝝀𝒎𝒂𝒙 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 O

ve

rall

asse

ssm

en

t

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 3rd

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 [email protected] or [email protected] or my

number 022 188 4034. My supervisor is Dr Kenneth Sungho Park, his email address is

[email protected].

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 [email protected].

mailto:[email protected]



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

activity over another

4 Between Moderate and Strong

5 Strong or essential

importance/preference/likelihood

Experience and judgement strongly favour one

activity over another

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 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

46

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AN INNOVATIVE TOOL SELECTION METHOD FOR CONSTRUCTION PROJECTS IN NEW ZEALAND

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