determinants of rework in building construction projects

16
Determinants of rework in building construction projects Peter E.D. Love and David J. Edwards The authors Peter E.D. Love is based at the We-B Centre, School of Management Information Systems, Edith Cowan University, Churchlands, Perth, Australia. David J. Edwards is based at the Department of Civil and Building Engineering, Loughborough University, Off-highway Plant and Equipment Research Centre (OPERC), Loughborough, East Midlands, UK. Keywords Australia, Construction works, Production costs, Costs Abstract Rework represents the unnecessary effort of redoing a process or activity that is incorrectly implemented the first time. Using a structured questionnaire survey, the causes and costs of rework in 161 Australian construction projects were identified. Respondents were invited to indicate direct and indirect rework costs that would be subsequently combined to produce a total rework cost (TRC) figure. Stepwise linear multiple regression analysis was then used to determine a model that included an optimum mixture of significant variables that contributed or lead to a reduction in TRC for the projects sampled. The research revealed that rework per se can negatively influence project safety. Client initiated changes and ineffective use of information technology by the design professionals were identified as being significant variables contributing to rework occurrence. Contrary to an earlier presupposition, design scope freezing was also identified as being a significant factor that can contribute to rework. Electronic access The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0969-9988.htm Introduction Time and schedule overruns, quality deviations and poor safety are perennial problems in the Australian construction industry (DIST, 1998; Gyles, 1992; Love, 2002a; Walker, 1994). Numerous government initiated reports have sought to address this imbalance and have concluded that the industry lacks coordination and communication between participants, creates unnecessarily adversarial contractual relationships, lacks any formal customer-supplier focus, relies heavily upon price-based selection and is slow to adopt information technology (IT) best practice (APCC, 1997; CIDA, 1993; DIST, 1999; Gyles, 1992; NWPC and NBCC, 1990). These inept organizational and management practices have contributed to time wasting, unnecessary costs, increased errors and misunderstandings, which have invariably resulted in rework occurring in projects (Abdul-Rahman, 1993; Josephson and Hammarlund, 1999; Love et al., 1999a). Indeed, research reveals that rework is a significant factor that contributes to project time and cost overruns (Chan and Kumaraswamy, 1997; Love, 2002a; Thomas and Neapolitan, 1994). Love (2002a) revealed that rework typically adds 10 per cent to total project costs. These costs may, however, be substantially higher because they do not account for schedule delays, litigation costs and other intangible costs of poor quality. In 2000, the Australian construction industry’s turnover was approximately $A57 billion, so an additional 10 per cent in rework would increase the turnover by $A5.7 billion! Earlier research has provided anecdotal evidence of the root causes of rework, but limited work has sought to quantify these determinants (Love et al., 1999a). Consequently, the research herein reported upon aims to determine the extent to which project characteristics, organizational management and project management practices influence rework occurrence. Although the research presented is focused upon the Australian industry, it is envisaged that the research outcome would be widely applicable in other nations because of the inherent synergy that exists between contractors and the like internationally. Determinants of rework Earlier studies have shown that rework costs vary between 3 and 15 per cent of a project’s contract value (Abdul-Rahman, 1997; Burati et al., 1992; CIDA, 1993; Josephson and Hammurlund, 1999). Differences in the definition of rework and data collection methods used, indicates that rework costs could be significantly higher than figures Engineering, Construction and Architectural Management Volume 11 · Number 4 · 2004 · pp. 259–274 q Emerald Group Publishing Limited · ISSN 0969-9988 DOI 10.1108/09699980410547612 259

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Determinants of reworkin building constructionprojects

Peter E.D. Love and

David J. Edwards

The authors

Peter E.D. Love is based at the We-B Centre, School ofManagement Information Systems, Edith Cowan University,Churchlands, Perth, Australia.David J. Edwards is based at the Department of Civil andBuilding Engineering, Loughborough University, Off-highwayPlant and Equipment Research Centre (OPERC), Loughborough,East Midlands, UK.

Keywords

Australia, Construction works, Production costs, Costs

Abstract

Rework represents the unnecessary effort of redoing a process oractivity that is incorrectly implemented the first time. Using astructured questionnaire survey, the causes and costs of reworkin 161 Australian construction projects were identified.Respondents were invited to indicate direct and indirect reworkcosts that would be subsequently combined to produce a totalrework cost (TRC) figure. Stepwise linear multiple regressionanalysis was then used to determine a model that included anoptimum mixture of significant variables that contributed or leadto a reduction in TRC for the projects sampled. The researchrevealed that rework per se can negatively influence projectsafety. Client initiated changes and ineffective use of informationtechnology by the design professionals were identified as beingsignificant variables contributing to rework occurrence. Contraryto an earlier presupposition, design scope freezing was alsoidentified as being a significant factor that can contribute torework.

Electronic access

The Emerald Research Register for this journal isavailable atwww.emeraldinsight.com/researchregister

The current issue and full text archive of this journal isavailable atwww.emeraldinsight.com/0969-9988.htm

Introduction

Time and schedule overruns, quality deviations

and poor safety are perennial problems in the

Australian construction industry (DIST, 1998;

Gyles, 1992; Love, 2002a; Walker, 1994).

Numerous government initiated reports have

sought to address this imbalance and have

concluded that the industry lacks coordination and

communication between participants, creates

unnecessarily adversarial contractual

relationships, lacks any formal customer-supplier

focus, relies heavily upon price-based selection and

is slow to adopt information technology (IT) best

practice (APCC, 1997; CIDA, 1993; DIST, 1999;

Gyles, 1992; NWPC and NBCC, 1990). These

inept organizational and management practices

have contributed to time wasting, unnecessary

costs, increased errors and misunderstandings,

which have invariably resulted in rework occurring

in projects (Abdul-Rahman, 1993; Josephson and

Hammarlund, 1999; Love et al., 1999a). Indeed,

research reveals that rework is a significant factor

that contributes to project time and cost overruns

(Chan and Kumaraswamy, 1997; Love, 2002a;

Thomas and Neapolitan, 1994). Love (2002a)

revealed that rework typically adds 10 per cent to

total project costs. These costs may, however, be

substantially higher because they do not account

for schedule delays, litigation costs and other

intangible costs of poor quality. In 2000, the

Australian construction industry’s turnover was

approximately $A57 billion, so an additional

10 per cent in rework would increase the turnover

by $A5.7 billion!

Earlier research has provided anecdotal

evidence of the root causes of rework, but limited

work has sought to quantify these determinants

(Love et al., 1999a). Consequently, the research

herein reported upon aims to determine the extent

to which project characteristics, organizational

management and project management practices

influence rework occurrence. Although the

research presented is focused upon the Australian

industry, it is envisaged that the research outcome

would be widely applicable in other nations

because of the inherent synergy that exists between

contractors and the like internationally.

Determinants of rework

Earlier studies have shown that rework costs vary

between 3 and 15 per cent of a project’s contract

value (Abdul-Rahman, 1997; Burati et al., 1992;

CIDA, 1993; Josephson and Hammurlund, 1999).

Differences in the definition of rework and data

collection methods used, indicates that rework

costs could be significantly higher than figures

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · pp. 259–274

q Emerald Group Publishing Limited · ISSN 0969-9988

DOI 10.1108/09699980410547612

259

reported in the normative literature (Love and

Smith, 2003). Indeed, Barber et al. (2000)

suggested that rework costs could be as high as

23 per cent of the contract value. Typically,

research efforts have focused on determining

direct rework costs at the expense of indirect costs

which remain relatively unknown ( Josephson,

2000). Love (2002b) sought to address this

imbalance and found that indirect costs can be as

much as five times the cost of rectification.

As rework contributes to time and cost overruns

(Love, 2002a), the literature on change orders, and

time and cost performance is drawn upon to build

a conceptual model of rework determinants.

Figure 1 shows that project characteristics, the

organizational management practices of individual

firms and the project management practices

employed can influence rework and project

performance. Organizational and project

management practices are interrelated, but for the

purposes of this research they have been separated

so that specific factors that influence rework can be

determined. Some projects experience significant

rework costs and resultant delays, yet despite these

setbacks are delivered ahead of schedule (Love

et al., 1999b). Thus, it is necessary to examine not

only traditional performance measures such as

time and cost, but also the satisfaction levels of

project team members.

Project characteristics

Project characteristics (also known as project

scope factors) have been identified as predictors of

project time for Australian construction projects

(Bromilow et al., 1980; Walker, 1994). Walker

(1994) considered project characteristics to be

a reliable measure of project size (in terms of

physical size and area of development and cost).

These characteristics include construction costs,

project duration, gross floor area (GFA), number

of stories, building type and procurement method.

Watkinson (1992) suggested that projects that use

traditional methods of procurement perform

poorly in terms of their time performance.

Contrary to this, Chan (1996) and Walker (1994)

have found that procurement methods have little

influence upon the time performance of projects.

Refurbishment and renovation projects are

prone to additional “unforeseen” rework costs,

when compared to new build projects because of

the higher degree of uncertainty and complexity

associated with such works (Love and Wyatt,

1997). Likewise, Jaafari et al. (1994) suggested

that quality failure (rework) costs are positively

correlated to project type and size. That is, larger

projects incur lower quality failure costs.

In addition, quality failure costs were observed to

be higher in commercial buildings and road

construction, and lower in industrial buildings.

Reasons for lower quality costs in industrial

buildings centre upon the fact that such projects

tend to have “orderly” site operations. Because of

this, they are typically characterized as having an

effective integrated design and planning process

coupled with synchronized site assembly, which is

often carried out by experienced personnel ( Jaafari

et al., 1994).

In the case of small to medium sized housing

and bridge projects ($A1m-$A5m), Jaafari et al.

(1994) noted that project tasks can be relatively

simple, and therefore, it is easier to control and

manage production quality. For commercial

buildings, Jaafari et al. (1994) acknowledged the

need for coordination of and input from multiple

professional disciplines, and numerous specialized

subcontractors who are integrated into the project

team. Thus, Jaafari et al. (1994) derived the

inevitable conclusion that commercial building

projects are prone to higher rework costs than

other project types.

Hester et al. (1991) and Ibbs and Allen (1993)

have suggested that change orders were not

a function of project complexity.Moreover,Walker

(1994) identified that project complexity was

positively correlated with time performance.

Naoum and Mustapha (1994) and NEDO (1987)

argued that building types (e.g. airports, hospitals,

offices) were linked to the concept of complexity,

and thus, influenced project performance. Bresnen

et al. (1988) countered this viewpoint and stated

that building type was an attribute rather than

a causal factor and could not influence project

performance.

Organizational and project management

practices

The modus operandi of construction is typically

detection-focused and so emphasis is invariably

placed on the product, procedures and/or

service deliverables and the downstream

production and delivery processes. Dale

(1999, p. 6) stated that in such an environment

“considerable effort is expended on after-the-event

inspecting, trouble shooting, checking, and testing

of the product and/or service and providing

reactive ‘quick fixes’ in a bid to ensure that only

conforming product and services are delivered to

the customer”. Using this traditional approach,

there is a notable lack of creative and systematic

work activities, with planning and improvements

being neglected. Defects are also identified at

a later stage in the procurement process and may

subsequently lead to rework. Delays in defect

identification increase the cost of rectification,

especially if work activities have already been

completed.

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

260

Figure

1Conceptualmodelof

reworkdeterm

inants

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

261

While a detection system may prevent

non-conforming products or services being

delivered to a customer (either internal or

external), it cannot curtail their occurrence in the

production process (Love and Irani, 2003).

Indeed, it is questionable whether such a system

does, in fact, find and remove all non-conforming

items. Design and construction organizations work

within an operational environment that places

considerable emphasis on making good

non-conforming products rather than preventing

them from arising in the first place; a reactive

vis-a-vis proactive stance. This reactive

environment is not conducive to developing

a cohesive project team that will support

customer-supplier communication structures

within and between organizations in the supply

chain (Carter and Miller, 1989).

According to Nesan and Holt (1999), design

and construction organizations that operate in

a “detection manner” are often preoccupied with

immediate business survival, and less concerned

with forging ahead with product or service

improvements. This is because design and

construction organizations typically focus on

“the bottom-line” in the short-term, and therefore,

are myopic and frequently fail to capitalize upon

ideas that could develop effective market

differentiation (Gibson, 1997).

Gardiner (1994), Powell (1997), Richardson

(1996) and Stasiowski and Burstein (1994), have

all suggested that the insularity and aversion of

architectural organizations to “management” has

resulted in poor service quality and their

marginalization within the industry. This is

because architects have been historically inflexible

and failed to respond to the changing environment

and/or provide a service that meets customer

demands. From a simplistic perspective, a gap

exists between consumers’ service expectations

and their perceptions of the actual service

delivered by an organization. Powell (1997, p. 84)

stated, “architects still cling to the notion that their

future lies in building original works of art to last

forever”. Symes et al. (1995, p. 55) concluded

from their study that, “without more training in

how to manage a firm and adapt to the needs of

their customers most architects may well be

doomed to work in small practices and thereby

be further marginalized in the building process”.

This situation is not, however, unique to architects

as engineering design consultants have been

confronting a similar dilemma (Culp, 1993; Syam,

1995; Tilley and McFallen, 2000a, b, c).

Management practices and the design process

All organisations involved in construction

procurement, especially those providing

professional services, should recognize that

demonstrable improvements in service quality

requires the presence of an organizational wide

quality culture (Barrett, 1993; Bubshait et al.,

1999; Rounce, 1998; Stasiowski and Burstein,

1994). The absence of a quality focus in design

organisations has meant that the concept of service

quality has not been given any serious recognition

(Richardson, 1996; Stasiowski and Burstein,

1994; Tilley and McFallen, 2000a). As a result,

contractors and their subcontractors act as

“quality buffers” as they are left to identify quality

deviations in contract documentation.

Burroughs (1993) reported that a major

Australian contractor had experienced rework

costs that equated to 5 per cent of the contract

value during the construction of a major project;

these costs were subsequently attributed to poor

documentation produced by design consultants.

Gardiner (1994) estimates are more alarming as

they suggest that rework costs attributed to design

consultants could be as high as 20 per cent of their

fee for a given project. Documentation quality may

suffer when a firm submits a low design fee for

a project, especially when design tasks are subject

to “time boxing”. That is, a fixed period of time

may be allocated to complete each task,

irrespective of whether the documentation or each

individual task is complete or not.

Poor planning of workload within design

organisations can also contribute to “time boxing”

and result in inadequate time to prepare complete

design documents (Coles, 1990; Love et al., 2000;

Rounce, 1998; Stasiowski and Burstein, 1994).

Moreover, Coles (1990) noted that the use of

inexperienced and under-qualified staff that lack

technical knowledge could also lead to errors and

omissions in contract documentation being made.

Svelinger (1996) studied the technical designs of

buildings and found the most frequent causes of

severe deviations during design were attributable

to deficient planning and/or resource allocation,

deficient or missing input and changes.

Quality management

Findings published by the Building Research

Establishment (BRE) (1982) provided the impetus

for examining how quality management (QM) can

be used by design organisations during the early

stages of a project. The BRE demonstrated that

the introduction of QM would help to realise

significant cost benefits. Jaafari (1996) suggested

that contractors’ QA practice, which is based on

post-production quality control, has stimulated

cost increases without commensurate savings.

Lomas (1996) of Barclay Construction Ltd

(Australia) reported that prior to the

implementation of a QA system, it was estimated

that their rework costs were 5 per cent of the

contract value. However, subsequent to QA

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

262

implementation, rework was reduced to less than

1 per cent of contract value in almost all projects.

Lomas (1996) found that QA practices

implemented, secured a company by a savings of

$A4.2m in 1996, which equates to approximately

1 per cent of their turnover. Similarly, Dissanayaka

et al. (2001) found that contractors who use a QA

system will experience a significant reduction in

rework or repair costs.

Having installed QM activities in a project,

minimal effort should be needed for its

implementation, assuming that personnel have

been trained to undertake this task (Jaafari et al.,

1994). Yet, in Australia, QM activities are

generally not being effectively utilized during the

design and construction process (Chan, 1996;

Karim et al., 2000; Tucker et al., 1996).

According to Cusack (1992), for example, projects

without a quality system in place typically

experience a 10 per cent cost increase because of

rework.

Client/Design team

Clients and their project team members must

communicate and work together harmoniously if

projects are to be delivered on or ahead of time

(Walker, 1994). In particular, Sidwell (1982)

recognized the potential positive influence of client

involvement in projects. By empowering clients in

the design process, change orders (specifically

design-related) during the construction phase can

be minimized. However, this observation typically

holds only for those clients who procure projects

on a regular basis (Love et al., 1998). In fact,

NEDO (1988) charted a significant reduction in

the time performance of projects where clients are

actively involved in project delivery. Design related

rework in the form of change orders is the major

source of rework in construction projects (Abdul-

Rahman, 1993; Barber et al., 2000; Burati et al.,

1992; Josephson, and Hammarlund, 1999; Love

et al., 1999b). A dearth in communication flow

between the client and design team members can

result in documentation errors and omissions

occurring (Dalty and Crawshaw, 1973). Client

and design team factors that have been identified

as contributing to rework include:. inadequate funding provided during site

investigations (Love and Wyatt, 1997);. inadequate time and funds attributed to the

briefing process (NEDO, 1987);. payment of low fees for preparing

contract documentation (Tilley and

McFallen, 2000a). ineffective use of IT (eg, visualization) (Li and

Love, 1998); and. poor design coordination between design

team members (Crawshaw, 1976).

Site management team and subcontractors

Project success is dependent upon the

effectiveness of the main contractor’s (and their

subcontractors and suppliers) construction

planning efforts (i.e. planning, coordination)

(Chan, 1998; Faniran et al., 1999; Ireland, 1985;

Walker, 1994). The site management team must

work with their subcontractors to plan the work

that needs to be undertaken. QM, particularly

quality assurance (QA), can be used as

a mechanism to ensure that appropriate controls

are put in place to monitor work activities.

However, contractors and subcontractors have

been found to often “pay lip service” to QA

because of the perceived increase in administration

and additional work that is required (Love et al.,

1999b; Tucker et al., 1996). Besides the ineffective

use of QM by site management, other factors that

contribute to rework include:. setting-out errors ( Josephson and

Hammarlund, 1999),. staff turnover and reallocation to other

projects (Love et al., 1999b), and. failure to provide protection to works (Barber

et al., 2000).

In the case of subcontractors, specific factors that

have been found to contribute to rework include

( Josephson et al., 2002; Love and Smith, 2003;

Love et al., 1999b):. inadequate supervision,. damage to other trade’s work due to

carelessness,. low skill level of designers or construction

labour, and. poor use or choice of materials.

It can be seen from the above discussion that a wide

range of factors contribute to project rework.

Nonetheless, a key question remains unaddressed

in the construction management literature: What

are the key determinants of rework? When this

question is adequately addressed, then appropriate

mitigation and prevention strategies can be

identified.

Research methodology

The research methodology sought to provide a

framework with which to determine the influence

that project characteristics, organizational

management practices and project management

practices have on rework costs in construction

projects. In doing so, the following hypotheses

were tested:

H1. Project characteristics significantly

influence rework costs.

H2. Management practices of firms involved in

projects influence rework costs.

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

263

H3. Project management practices employed to

deliver projects influence rework costs.

For the purposes of this research, the operational

definition of rework is “the unnecessary effort of

redoing a process or activity that was incorrectly

implemented the first time” (Love, 2002a). Rather

than developing a questionnaire survey that sought

to elicit general opinions about rework,

respondents were asked to select a recently

completed project most familiar to them and

answer questions about the perceived causes of

rework, associated costs, and the project

management practices implemented. In essence,

each project identified by respondents was treated

as a separate case.

Questionnaire survey

A questionnaire was developed that contained

116 independent variables (identified from the

literature review), which sought to examine the

influence of project characteristics, organizational

management practices and project management

practice influences on rework costs in construction

projects. Respondents were asked to provide an

estimate of rework (direct and indirect) costs

incurred during the project that they had selected.

These figures would later be combined to produce

a total rework cost (TRC) figure that would be

predicted using regression analysis. Using a

five-point Likert scale, respondents were asked to

indicate their extent of agreement as to how much

the identified factors contributed to the occurrence

of rework.

Stratified random sampling was used to

select the study sample from the telephone

directory, Yellow Pages, by location in Australia.

In addition, to increase the representativeness

of samples, stratified random sampling was a

useful technique that made general statements

about the portions of the population possible.

Prior to determining the sample size for the

main study, a pilot survey was undertaken with

30 selected firms, which comprised of architects,

project managers and contractors from the

Geelong and Melbourne region, in the State of

Victoria, Australia. This was undertaken to test

the potential response rate, suitability and

comprehensibility of the questionnaire. Each firm

was contacted by telephone and informed of the

research aims.

On obtaining their consent, the questionnaire

was mailed with a stamped addressed return

envelope enclosed for respondents’ returns.

The respondents were also asked to critically

review the survey’s design and structure. A total

of 25 responses were received (representing an

83 per cent response rate) and positive feedback

obtained indicated that the questionnaire

should remain unaltered for the main survey.

The composition of respondents that returned that

questionnaire were architects (30 per cent),

contractors (50 per cent) and project managers

(20 per cent).

For the main survey, 420 questionnaires were

distributed to industry practitioners throughout

Australia. One hundred and thirty six valid

responses were received from the main survey and

were added to the pilot questionnaires to produce

161 valid responses in total (this represented

a response rate of 36 per cent). This response

rate was considered acceptable for a survey

focusing on gaining responses from industry

practitioners (Alreck and Settle, 1985). Figure 2

shows a breakdown of the valid responses by

respondents.

Figure 3 shows a breakdown of the respondents

who answered the questionnaire by State.

Considering the number of construction projects

being undertaken in Australia, at any given time,

Figure 3 Respondents by State

Figure 2 Respondents by profession

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

264

the likelihood of the respondents selecting the

same project was significantly reduced because of

the diversity of data sources from each State.

Data analysis

To examine the relationship between TRC and the

independent variables (IVs), stepwise regression

was used. Stepwise regression has an advantage

over other multivariate techniques in terms of

the number of potential subset models checked

before the model for each subset is decided.

Consequently, there is a greater chance of

choosing the best subsets in the sample data

when there are a large number of potentially

relevant regressor variables (Rawlings, 1988).

No significant regressor variables were identified

for organizational management practices and in

this instance, Pearson’s correlation analysis was

used to demonstrate the strength and direction of

the relationships with TRC.

Results and discussion

Prior to undertaking a detailed analysis of the

responses, each of the constructs that were used to

identify the causes of rework within the research

instrument was tested for reliability. The reliability

of the research instrument was evaluated through

the use of Cronbach’s coefficient alpha (a).

Because a values of 0.70 or above indicate

a reliable measurement instrument, it was

concluded that the measurement instrument was

robust (Table I) (Nunnally, 1978).

Sample characteristics

The contract values for projects were found to

range widely from $25,500 to $390,000,000

(mean (M) ¼ $25,521,927, standard deviation

(SD) ¼ $51,957,899. Similarly, contract duration

ranged from 2 to 450 weeks (M ¼ 66 weeks, SD ¼

46 weeks). Figures 4 and 5 shows thse number of

projects and the costs of rework (direct and

indirect) by contract value.

The ground floor area (GFA) for the sample

projects was found to range from 116m2 for

a fit-out project with a contract value of $25,000

to 238,000m2 for a new build airport terminal

with a contract value of $390,000,000

(M ¼ 13; 583m2; SD ¼ 23; 617m2).

Total rework costs

TRC were calculated by adding the direct and

indirect estimates provided by respondents.

The mean and standard deviation of TRCs for the

sample were found to be M ¼ 12:0 per cent, and

SD ¼ 13:56 per cent. Direct rework costs were

Table I Reliability and consistency measures for scales

Scales Mean (N 5 161) Cronbach’s a

Pearson

correlation

Organizational learning 2.85 0.814 0.515

QM 2.15 0.710 0.501

Project performance 2.95 0.747 0.485

Productivity 2.29 0.853 0.669

Client causes 2.71 0.767 0.513

Design team causes 2.67 0.863 0.639

Site management causes 2.59 0.805 0.564

Subcontractor causes 2.94 0.830 0.628

Project scope 3.04 0.703 0.460

Communication 3.44 0.846 0.630

Contract documentation 2.74 0.759 0.492

Figure 5 Mean rework costs for projects by contract value

Figure 4 Number of projects by contract value

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

265

found to be M ¼ 6:4 per cent, and

SD ¼ 7:78 per cent, and indirectM ¼ 5:6 per cent,and SD ¼ 7:19 per cent. The maximum direct

rework cost was 50 per cent and the minimum

0.1 per cent. Similarly, the maximum indirect cost

was 50 per cent and the minimum 0.

Respondents were asked to provide the

following details so that cost and schedule growth

could be calculated for each project: original

contract value, its expected duration in weeks,

actual contract value on practical completion and

the actual construction period (Hester et al., 1991;

Ibbs and Allen, 1995; Love, 2002a; Zeitoun and

Oberlander, 1993). The mean cost and

schedule growth were M ¼ 12:6 per cent,

SD ¼ 24:22 per cent and M ¼ 20:7 per cent,

SD ¼ 28 per cent, respectively. Noteworthy, direct

rework costs as a “percentage of cost growth”

were found to have M ¼ 52:1 per cent, and

SD ¼ 88:9 per cent. In other words, rework

contributed 52 per cent of the cost increase

experienced in projects.

Rework predictors

The stepwise multiple regression analysis was

performed using SPSS (Version 10.00)

REGRESSION and SPSS FREQUENCIES for

evaluation of assumptions. Variables required no

transformations to reduce skewness, reduce

outliers and improve normality, linearity and

homoscedasticity of residuals. This ensured that

any model produced could be interpreted from the

variable scales directly and without further

manipulation (Tabachnick and Fidell, 1996).

However, categorical variables such as

procurement method and project type were

converted using a binary coding of 1s and 0s so

that they could be used in the regression analysis.

For a given variable, the option assigned the value

1 is arbitrary because rework costs will be the

same, regardless of coding procedure used. Binary

codes, therefore, act as a switch between variable

category options presented.

With the use of a p , 0:001 criterion, for

Mahalanbois distance identified one multivariate

outlier, x2ð18Þ ¼ 40:790: Similarly, Cook’s d , 1

identified four outliers that influence the precision

of the estimation of the regression weights and

were subsequently left in because their deletion

would not have significantly affected them.

The test for multicollinearity revealed that

variables were not highly correlated with one

another ðp . 0:9Þ: No cases had missing data and

no suppressor variables were found, n ¼ 161:

Project characteristics

Regression was performed between TRCs and cost

growth, schedule growth, project type,

procurement method, tender type, GFA, number

of storeys, and project drivers. Table II reproduces

the regression output and includes the

unstandardized regression coefficients (B) and the

intercept, the standardized regression coefficients

(b), semi-partial correlations ðsr2i Þ and R, R2 and

adjusted R2 for the appropriate predictors of

TRCs. The analysis was undertaken with and

without the identified outliers. The deletion of the

outliers did not significantly affect the regression

weights and so the outliers remained in the dataset

for the entire analysis.

The regression analysis identified three models

(Table II). Only three of the 18 variables, namely

cost growth, schedule growth and safety were

found to significantly contribute to regression

ðp , 0:01Þ: Semi-partial correlations, which

indicate the amount by whichR2 would be reduced

if an IV were omitted from the equation, were

sr2i ¼ 0:44 for cost growth, sr2i ¼ 0:29 for

schedule growth and sr2i ¼ 20:16 for safety.

The introduction of safety as a predictor does,

therefore, not significantly improve the value of r2

when it is entered into the model. Thus, model 3,

R2 ¼ 0:27; F ð3; 157Þ ¼ 20:66; p , 0:01 is the

most appropriate, as cost and schedule growth

explain 27 per cent of the variability in TRCs in

construction projects. The regression equation is

expressed as

TRC ¼ 13:07þ 0:20ðcost growthÞ

þ 0:13ðschedule growthÞ

2 1:66ðsafetyÞ

ð1Þ

Cost and schedule growth do not influence rework

costs, they are simply used to determine the

amount that can occur in a project. It would

appear, however, that as rework costs increase,

safety is perhaps compromised as the pressure to

complete the project on time and to budget

increases. Safety should not be overlooked and

precautionary measures must be implemented

when a project is running behind schedule and

over budget. According to Chan (2000), safety is

a significant factor that contributes to project

success, and thus must never be compromised.

Project management practices

In this instance, regression was performed between

TRC and the project management practice

variables identified in Figure 1. It can be seen from

Table III that four models were identified as being

significant. Four of the 87 variables, namely

CCAUSE_4 (changes initiated by a client or

occupier when a product or process had been

completed), DESMAN_1 (value management),

PMDESN_2 (ineffective use of IT by the design

team) and DESMAN_6 (design scope freezing)

were found to significantly contribute to

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

266

regression ð p , 0:01Þ: Semi-partial correlations

were sr2i ¼ 0:57 CCAUSE_1, sr2i ¼ 20:47DESMAN_1, sr2i ¼ 20:67 PMDESN_2 and

sr2i ¼ 0:50 for DESMAN_6. Considering that all

four variables, particularly DESMAN_1, make a

significant contribution to the regression analysis,

model 4, R2 ¼ 0:78; F ð4; 156Þ ¼ 13:65; p , 0:01is the most appropriate, as it explains 78 per cent of

the variability in rework costs (Table III).

The regression equation is expressed as

TRC ¼ 31:55þ 4:5ðclient changesÞ

2 6:92ðvalue managementÞ

þ 6:48ðineffective use of ITÞ

þ 3:32ðdesign scope freezingÞ

ð2Þ

Value management is a technique that can be used

to re-evaluate the functionality and the

requirements of clients, and thus, can be used to

minimize client-initiated changes, which may

occur downstream during construction. Model 4

notes that the ineffective application of IT by

design team members (PMDESN_2) contributes

to rework in projects. Additionally, the ineffective

use of IT, specifically lack of interoperability, can

lead to inappropriate and non-timely information

transfer between design team members, and

resultantly impose significant restrictions on

decision-making. When IT is used effectively by

design team members it can improve information

flow and communication, decision-making, design

coordination and be used to monitor changes in

projects.

While it has been posited by the Construction

Industry Institute CII (1987) that “design scope

freezing” (DESMAN_6) can result in the

minimization of changes in projects, this research

has identified that, as a factor, it can contribute to

changes in the context of rework. When clients or

occupiers, especially those who are inexperienced,

are confronted with a design scope freeze, they

may feel intimidated as it reduces their

decision-making flexibility about their final

investment. If project scope is not adequately

defined and specific client (or occupier) needs are

determined by the time that contract

documentation is finalized, then necessary changes

during construction may result in rework, which

may have detrimental consequences on project

cost and schedule. Notwithstanding this

proposition, it is preffered that design scope

freezing may ameliorate the likelihood of rework

occurring in projects if used in conjunction with

a rigorous and structured project scoping program

that encapsulates a change in control mechanism,

constructability analysis and value management

workshop.

Table III Project management predictors of TRC

Model Variable B Std. error b sri2 R R2 Adjusted R2

1 (Constant) 0.45 5.24

CCAUSE_4 5.47 1.86 0.57 0.57 0.57 0.36 0.29

2 (Constant) 9.35 6.29

CCAUSE_4 5.83 1.70 0.60 0.64

DESMAN_1 23.71 1.71 20.35 20.47 0.68 0.47 0.41

3 (Constant) 35.17 8.52

CCAUSE_4 4.71 1.33 0.50 0.66

DESMAN_1 25.75 1.42 20.60 20.71

PMDESN_2 5.94 1.65 0.55 0.67 0.84 0.71 0.66

4 (Constant) 31.55 7.79

CCAUSE_4 4.50 1.19 0.47 0.70

DESMAN_1 26.92 1.37 20.72 20.80

PMDESN_2 6.48 1.47 0.60 0.75

DESMAN_6 3.32 1.48 0.29 0.50 0.87 0.78 0.73

Table II Project characteristic predictors of TRC

Model Variable B Std. error b sri2 R R2 Adjusted R2

1 (Constant) 8.92 1.08

Cost growth 0.25 0.40 0.44 0.44 0.44 0.19 0.19

2 (Constant) 6.76 1.18

Cost growth 0.20 0.40 0.35 0.36

Schedule growth 0.13 0.34 0.28 0.29 0.51 0.27 0.26

3 (Constant) 13.07 3.40

Cost growth 0.20 0.04 0.37 0.37

Schedule growth 0.130 0.03 0.27 0.29

Safety 21.66 0.84 20.13 20.16 0.53 0.28 0.27

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

267

The analysis of rework costs clearly indicates that it

is a major source of cost growth in projects and that

reduction in its occurrence must be made in order

to improve project performance. Moreover, the

results concur with earlier studies that have

investigated the causes of change orders in

construction (CII, 1990; Cox et al., 1999; Ibbs and

Allen, 1993; Zeitoun and Oberlander, 1993). This

is not surprising as changes, whether they are

initiated by the client, contractor or design team

members, were identified as a determinant of

rework. However, the fact remains that

Australian projects are experiencing considerable

amounts of change, which invariably results in

rework, even though techniques for managing and

controlling its occurrence are well-known amongst

industry practitioners. This is perhaps because

construction organisations focus on preparing the

next bid and as such, no time is allowed for

reflection, which is a critical part of the learning

process.

Organizational management practices

Table IV gives demonstrable evidence that there

are no significant negative correlations between

organizational management practices and rework

costs. Consequently, the regression analysis was

unable to identify any significant predictors of

rework costs. This is a surprising finding

considering the importance that has been attached

to the adoption of QM tools and techniques by

organisations for eliminating waste, typically in the

form of rework, and thus, improving the

effectiveness of processes. Likewise, organizational

learning mechanisms, which form a pivotal aspect

of the continuous improvement process, were also

found not to reduce project rework costs.

The extent of implementation of learning and

quality practices identified in the survey was

“low”, that is, there use in practice was not

a common occurrence (Love et al., 2003).

For example, 50 per cent of firms sampled did not

measure quality costs, nor did 79 per cent use

quality function deployment (QFD). Likewise,

only 12 per cent of firms sampled stated that they

used some form of internal and external

benchmarking. The absence of such organizational

management practices can hinder a firms “learning

capability”, as there is no support mechanism in

place to encourage best practice. Further research

is required to examine in greater detail how and

why, if at all, a firm’s learning practices can reduce

rework costs.

Influence of rework on productivity and

project performance

Rework, specifically in the form of changes, can

have a negative impact on productivity and

project performance (CII, 1990). The assignment

of responsibility for rework also causes conflict,

especially when errors or an omission in

contract documentation occur (Love et al.,

1999b). In addition, when rework occurs,

resources are often diverted, which causes

supervision to be diluted in other parts of a

project. The effects of this dilution are threefold.

First, additional supervision may be required, as

subcontractors may be delayed by the rework

event; this may cause the “stacking” of

subcontract trades to occur. Second, rework has

the potential to occur in areas where supervision

is inadequate to cover project needs, and third,

safety can be compromised. Having to work

longer hours than necessary to rectify earlier

undertaken work can be demoralising, lead to

fatigue, and even absenteeism, which again

can lead to more project rework.

Productivity factors that were found to have a

significant influence on rework costs were

(Table V):. “poor morale”, rs ¼ þ0:31; n ¼ 161;

p , 0:01; two tails;. “dilution of supervision”, rs ¼ þ0:22;

n ¼ 161; p , 0:01; two tails; and. “conflict”, rs ¼ þ0:33; n ¼ 161; p , 0:01; two

tails.

Variables that significantly correlated with rework

costs at the 95 per cent significance level were,

“fatigue”, rs ¼ þ0:17; n ¼ 161; p , 0:05; twotails, and “absenteeism”, rs ¼ þ0:15; n ¼ 161;p , 0:05; two tails.

Various measures for project performance can

be found in the construction and project

management literature, however, the variables

identified in the questionnaire are considered to be

representative for measuring the impact that

rework has on project performance (Hester et al.,

1991). The correlation analysis revealed that

rework costs were significantly correlated with

(Table V):. “cost overruns”, rs ¼ þ0:48; n ¼ 161;

p , 0:01; two tails;. “time overruns”, rs ¼ þ0:37; n ¼ 161;

p , 0:01; two tails;. “contractual claims”, rs ¼ þ0:44; n ¼ 161;

p , 0:01; two tails, and. “client dissatisfaction”, rs ¼ þ0:17; n ¼ 161;

p , 0:05; two tails.

Interestingly, rework costs were not significantly

correlated with design team and contractor

dissatisfaction.

Rework mitigation in projects

The findings confirm the earlier research that has

been undertaken in the area of change orders.

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

268

Table

IVCorrelationmatrix

fororganizationalmanagem

entpractices

andreworkcosts

VAR

12

34

56

78

910

11

12

13

14

15

16

17

11.00

20.17*

1.00

30.41**

0.30**

1.00

40.26**

0.15

0.34**

1.00

50.47**

0.21**

0.44**

0.47**

1.00

60.43**

0.26**

0.47**

0.40**

0.31**

1.00

70.35**

0.26**

0.38**

0.30**

0.53**

0.26**

1.00

80.40**

0.09

0.38**

0.06

0.29**

0.28**

0.41**

1.00

90.42**

0.11

0.31**

0.39**

0.39**

0.35**

0.35**

0.27**

1.00

10

0.18*

0.02

0.17*

0.05

0.22**

0.10

0.16*

0.00

0.04

1.00

11

0.20**

0.06

0.15*

0.14

0.31**

0.17*

0.26**

0.19*

0.22**

0.19

1.00

12

0.11

0.12

0.04

20.06

0.08

0.07

0.07

0.09

20.09

0.24**

0.11

1.00

13

0.27**

0.16*

0.20*

0.18*

0.36**

0.26**

0.23**

0.22**

0.12

0.36**

0.23**

0.31**

1.00

14

0.13

0.10

0.02

0.07

0.18*

0.14

0.18*

0.07

0.12

0.28**

0.15*

0.18

0.37

1.00

15

0.26**

20.09

0.16*

20.01

0.22**

20.12

20.07

0.17*

0.04

0.23**

0.16*

20.03

0.10

0.01

1.00

16

0.25**

20.17*

0.08

0.05

0.18*

20.08

20.03

0.14

0.15

0.05

0.26**

20.04

0.02

0.03

0.78**

1.00

17

20.10

20.10

20.05

0.02

20.11

0.12

20.05

20.02

20.01

0.07

20.09

0.08

0.07

0.04

20.09

20.05

1.00

Notes:**

Correlationissignificant

atthe0.01

level(2-tailed);*C

orrelationissignificant

atthe0.05

level(two-tailed),(1)¼

Training

programmes,(2)¼

Selflearning,(3)¼

Collaborationwith

organisations,

(4)¼

R&D,(5)

¼Externalbenchm

arking,(6)

¼CPD,(7)

¼Internalbenchm

arking,(8)

¼Projectreview

s,(9)¼

Internalseminarson

newdevelopm

ents,(10)¼

Measurementofquality

costs,(11)

¼ISO9000,

(12)

¼QFD,(13)

¼TQ

M,(14)

¼Improvem

ent/workteam

s,(15)

¼Turnover,(16)

¼Em

ployed,and(17)

¼Totalcostof

rework

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

269

Of quintessential importance is the fact that

rework can account for approximately 50 per cent

of a project’s cost overrun, most of which is due to

client initiated changes. It has been known for a

considerable amount of time that client-initiated

changes represent a primary source of time and

cost overruns. Design scope freezing has been

identified as a suitable technique for reducing

changes, if done progressively. An early design

freeze, however, can conflict with meeting client

requirements and result in costly changes, which

also impact the project’s programme.

The pressure to complete a project due to

“changes” may, in some circumstances, leave a

contractor susceptible to giving less attention to

safety issues. Focusing attention on the variables

identified in Figure 6 should reduce rework in

projects.

The testing of the research hypotheses has

enabled those key variables, that influence and

can reduce rework costs, to be isolated. In

doing so, allows practitioners to focus their

prevention strategies on those identified.

However, it is not possible to accept or reject the

hypotheses that were proposed, as only a limited

number of variables were identified. Moreover,

earlier case study based research indicates that

organizational management and learning

practices influence rework, but in this research this

is not the case. The identification of rework

determinants is a complex issue in as much as it

can be influenced indirectly by a series of latent

variables.

Conclusion

To date, there had been no rigorous attempt

to conduct a definitive empirical study to

quantify these variables in terms of their

relative impact. This has led to spiralling rework

costs in the Australian and international

construction industries and resultantly,

reduced their business efficiency and profitability.

More knowledge is now available, particularly in

Australia, about the determinants of rework in

projects. This research, adds depth to the

existing body of knowledge by providing a

series of causal links to rework, productivity

and project performance where, previously

speculative conjecture existed.

Three subsets of this investigation into TRC

were modelled using multiple linear regression

analysis, namely organizational management

practices, project characteristics and project

management practices. Analysis revealed that

there were no significant correlations between

TRCs and organizational management practices.

Similarly, project characteristics produced a weak

model equation (as exhibited by an R2 of 0.27).

However, for the latter, site safety was shown to

be compromised as rework costs increase.

For project management practices, four from

87 variables recorded were shown to be significant

predictors:

(1) Client changes (+)

(2) Value management (2)

(3) Ineffective use of IT (+)

(4) Design scope freezing (+)

These model equations were revealed to be both

reliable and robust predictors of TRCs as

exhibited by the R2 value of 0.78, p , 0:1:

Future work is now required to expand upon this

work and develop a rework prevention strategy

toolkit that can be used by members of the

construction project team.

Table V Correlation matrix for project performance, productivity, and rework costs

VAR 1 2 3 4 5 6 7 8 9 10 11 12

1 1.00

2 0.69** 1.00

3 0.61** 0.53** 1.00

4 0.14 0.16 0.33** 1.00

5 0.16* 0.22** 0.16 0.27** 1.00

6 0.15* 0.19 0.23** 0.49** 0.44** 1.00

7 0.37** 0.38** 0.36** 0.13 0.15 0.24** 1.00

8 0.31** 0.36** 0.38** 0.12 0.24** 0.27** 0.65** 1.00

9 0.25** 0.25** 0.28** 0.08 0.16* 0.29** 0.64** 0.62** 1.00

10 0.30** 0.26** 0.30** 0.13 0.24** 0.24** 0.61** 0.54** 0.52** 1.00

11 0.16* 0.21** 0.29** 0.08 0.12 0.17* 0.41** 0.42** 0.47** 0.30** 1.00

12 0.48** 0.37** 0.44** 0.17* 0.08 0.14 0.31** 0.22** 0.17* 0.33** 0.15* 1.00

Notes: ** Correlation is significant at the 0.01 level (2-tailed), * Correlation is significant at the 0.05 level (two-tailed), (1) ¼ Costoverrun, (2) ¼ Time overrun, (3) ¼ Contractual claims, (4) ¼ Client dissatisfaction, (5) ¼ Contractor dissatisfaction, (6) ¼ Designteam dissatisfaction, (7) ¼ Poor morale (8) ¼ Dilution of supervision, (9) ¼ Fatigue, (10) ¼ Conflict, (11) ¼ Absenteeism, and(12) ¼ Total cost of rework

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

270

Figure

6Keydeterm

inantsof

reworkandits

influence

productivity

andprojectperformance

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

271

References

Abdul-Rahman, H. (1993), “The management and cost of qualityfor civil engineering projects”, PhD thesis, University ofManchester Institute of Science and Technology (UMIST),Manchester, UK.

Abdul-Rahman, H. (1997), “Some observations on the issues ofquality cost in construction”, International Journal ofQuality and Reliability Management, Vol. 14 No. 5,pp. 464-81.

Alreck, P.L. and Settle, R.B. (1985), The Survey ResearchHandbook, Richard D, Irwin Inc., Homewood, IL.

Australian Procurement and Construction Council (APCC) (1997),Construct Australia: Building a Better ConstructionIndustry in Australia, The Australian Procurement andConstruction Council Inc., Deakin West, ACT, Australia.

Barber, P., Sheath, D., Tomkins, C. and Graves, A. (2000),“The cost of quality failures in major civil engineeringprojects”, International Journal of Quality and ReliabilityManagement, Vol. 17 Nos 4/5, pp. 479-92.

Barrett, P. (1993), Profitable Practice Management for theConstruction Professional, E&F Spon, London.

Bresnen, M.J., Haslam, C.O., Beardsworth, A.D., Bryman, A.E.and Hell, T.E. (1988), Performance on site and the buildingclient, Occasional Paper 42, Chartered Institute ofBuilding, Ascot, UK.

Bromilow, F.J., Hinds, M.F. and Moody, N.F. (1980), “AIQS surveyof building contract time performance”, The BuildingEconomist, Vol. 19, pp. 79-82.

Bubshait, A.A., Farooq, G., Jannadi, M.O. and Assaf, S.A. (1999),“Quality practices in design firms”, ConstructionManagement and Economics, Vol. 17, pp. 799-809.

Building Research Establishment (1982), Quality in TraditionalHousing – An Investigation into Faults and theirAvoidance, BRE, Garston, UK.

Burati, J.L., Farrington, J.J. and Ledbetter, W.B. (1992), “Causesof quality deviations in design and construction”, Journalof Construction Engineering and Management, Vol. 118No. 1, pp. 34-49.

Burroughs, G. (1993), Concrete Quality Assurance: TheContractors Role, Quality Assurance in the ConstructionIndustry, Concrete Institute of Australia, Melbourne,Australia.

Carter, J.R. and Miller, J.G. (1989), “The impact of alternativevendor/buyer communication structures of quality ofpurchased materials”, Decision Sciences, Vol. 20,pp. 759-76.

Chan, A.P.C. (1996), “Determinants of project success in theconstruction industry of Hong Kong”, unpublishedPhD thesis, University of South Australia, South Australia,Australia.

Chan, D.W.M. (1998), “Modelling construction durations forpublic housing projects in Hong Kong”, unpublishedPhD thesis, The University of Hong, Hong Kong.

Chan, A.P.C. (2000), “Relationship of safety programs andproject performance”, Construction and Real EstateReview, Vol. 4 No. 2, pp. 1-4.

Chan, D.W.M. and Kumaraswamy, M.M. (1997), “A comparativestudy of causes of time overruns in Hong Kongconstruction projects”, International Journal of ProjectManagement, Vol. 15 No. 1, pp. 55-63.

CIDA (1993), A Report on the Time and Cost Performance ofAustralian Building Projects Completed 1988-1993,Construction Industry Development Agency (CIDA) inconjunction with the Australian Institute of QuantitySurveyors, Sydney, NSW, Australia.

Coles, E.J. (1990), Design Management: A Study of Practice inthe Building Industry, The Chartered Institute of Building,Occasional Paper, No. 42, UK, p. 32.

Construction Industry Institute (CII) (1987), Input VariablesImpacting Design Effectiveness, Construction IndustryInstitute Design Task Force, University of Texas at Austin,Publication 8-2 July, USA.

Construction Industry Institute (CII) (1990), The Impact ofChanges on Construction Cost and Schedule, ConstructionIndustry Institute (CII), The University of Texas at Austin,Austin, Texas, Publication 6-10 April, USA.

Cox, I.D., Morris, J., Rogerson, J.H. and Jared, G.E. (1999),“A quantitative study of post contract award designchanges in construction”, Construction Management andEconomics, Vol. 17 No. 4, pp. 427-39.

Crawshaw, D.T. (1976), Co-ordinating Working Drawings,Building Research Establishment, Current Paper CP 60/76,Watford, UK.

Culp, G. (1993), “Implementation of TQM in a consultingengineering firm”, ASCE Journal of Management inEngineering, Vol. 9 No. 4, pp. 340-66.

Cusack, D. (1992), “Implementation of ISO 9000 inconstruction”, ISO 9000 Forum Symposium, November,Gold Coast, Australia.

Dale, B. (1999), Managing Quality, 3rd ed., Blackwell Business,Oxford, UK.

Dalty, C.D. and Crawshaw, D.T. (1973), Working Drawings in Use,Building Research Establishment, Current Paper CP 18/73,Watford, UK.

Department of Industry Science and Tourism (DIST) (1998),Building for Growth: A Draft Strategy for the Building andConstruction Industry, Department of Industry Science andTourism, Commonwealth of Australia Publication,February, Canberra, Australia.

Department of Industry Science and Tourism (DIST) (1999),A Report for Government by the National Building andConstruction Committee, Building for Growth: An ActionAgenda for the Building and Construction Industries.The Department of Industry Science and Tourism,Canberra, Australia.

Dissanayaka, S.M., Kurmaraswamy, M.M., Karim, K. andMarosszkey, M. (2001), “Evaluating outcomes from ISO9000-certified quality systems of Hong Kong contractors”,Total Quality Management, Vol. 12 No. 1, pp. 29-40.

Faniran, O.O., Love, P.E.D. and Li, H. (1999), “Optimal allocationof construction planning resources”, ASCE Journal ofConstruction Engineering and Management, Vol. 125No. 5, pp. 311-19.

Gardiner, J. (1994), “Management of design documentation,where do we go from here?”, in Wakefield, R.R. andCarmichael, D.G. (eds), Construction and Management,Recent Advances, Balkema, Rotterdam, pp. 113-18.

Gibson, P.R. (1997), “Strategic re-engineering of theconstruction industry organisation”, Proceedings of theInternational Conference on Construction Process Re-engineering, 13-14 July, Gold Coast, Australia, pp. 367-74.

Gyles, R. (1992), Royal Commission into Productivity in theBuilding Industry in New South Wales, Vols 1-10, Sydney,Australia.

Hester, W.T., Kuprenas, J.A. and Chang, T.C. (1991), ConstructionChanges and Change Orders: Their Magnitude and Impact,Source Document 66, Construction Industry Institute,The University of Texas at Austin, TX.

Ibbs, C.W. and Allen, W.E. (1993), Quantitative Impacts ofProject Change, Source Document 108, ConstructionIndustry Institute, The University of Texas at Austin, Tx.

Determinants of rework in building construction projects

Peter E.D. Love and David J. Edwards

Engineering, Construction and Architectural Management

Volume 11 · Number 4 · 2004 · 259–274

272

Ireland, V. (1985), “The role of managerial actions in the cost,time and quality performance of high rise commercialprojects”, Construction Management and Economics,Vol. 3 No. 1, pp. 59-87.

Jaafari, A. (1996), “Human factors in the Australian constructionindustry: towards total quality management”, AustralianJournal of Management, Vol. 21 No. 2, pp. 159-85.

Jaafari, A., Chan, M.A. and Cassab, R. (1994), “Qualitymanagement in the Australian construction industry”, inWakefield, R.R. and Carmichael, D.G. (Eds), Constructionand Management, Recent Advances, Balkema, Rotterdam,pp. 89-112.

Josephson, P-E. (2000), “What we know and not know aboutpoor quality costs in building projects: some experiences”,Proceedings of International Conference CIB TG36Implementation of Construction Quality and relatedSystems, Lisbon, 18-21 June, pp. 281-90.

Josephson, P-E. and Hammarlund, Y. (1999), “The causes andcosts of defects in construction. A study of seven buildingprojects”, Automation in Construction, Vol. 8 No. 6.

Josephson, P-E., Larsson, B. and Li, H. (2002), “Illustrativebenchmarking rework and rework costs in Swedishconstruction industry”, ASCE Journal of Management inEngineering, Vol. 18 No. 2, pp. 76-83.

Karim, K., Marosszkey, M., Chung, H.W., Kurmaraswamy, M. andLow, S.P. (2000), “A comparative study of ISO 9000 qualitymanagement systems in the construction industry:Australia, Hong Kong, and Singapore”, Proceedings of theFifth International Conference on ISO 9000 and TQM,25-27 April, Shangri-La’s Rasa Sentosa Resort, Singapore,pp. 440-4.

Li, H. and Love, P.E.D. (1998), “Visualisation of building interiordesign to reduce rework”, Proceedings of theInternational Conference on Information Visualisation,School of Oriental and African Studies, University ofLondon, 29-31 July, London, pp. 187-91.

Lomas, K. (1996), Quality Pays, Engineers Australia, p. 26.Love, P.E.D. (2002a), “Influence of project type and procurement

method on rework costs in building construction projects”,ASCE Journal of Construction Engineering andManagement, Vol. 128 No. 1, pp. 18-29.

Love, P.E.D. (2002b), “Auditing the indirect consequences ofrework in construction: a case based approach”,Managerial Auditing Journal, Vol. 17 No. 3, pp. 138-46.

Love, P.E.D. and Irani, Z. (2003), “A project management qualitycost information system for construction”, Informationand Management, Vol. 40, pp. 649-61.

Love, P.E.D. and Smith, J. (2003), “Benchmarking, bench-actionand bench-learning: rework mitigation in projects”, ASCEJournal of Management in Engineering, Vol. 19 No. 4,pp. 147-59.

Love, P.E.D. and Wyatt, A.D. (1997), Communication andRework: Case Studies of Construction Projects, CSIRO,DBCE DOC 97/38 (B), Australia.

Love, P.E.D., Irani, Z. and Edwards, D. (2003), “Learning toreduce rework in projects: analysis of firms learning andquality practices”, Project Management Journal, Vol. 34No. 3, pp. 13-25.

Love, P.E.D., Li, H. and Mandal, P. (1999a), “Rework: a symptomof a dysfunctional supply chain”, European Journal ofPurchasing and Supply Management, Vol. 5 No. 1,pp. 1-11.

Love, P.E.D., Mandal, P. and Li, H. (1999b), “Determining thecausal structure of rework”, Construction Managementand Economics, Vol. 17 No. 4, pp. 505-15.

Love, P.E.D., Skitmore, R.M. and Earl, G. (1998), “Selecting asuitable procurement method for a building project”,

Construction Management and Economics, Vol. 16 No. 2,pp. 221-33.

Love, P.E.D., Mandal, P., Smith, J. and Li, H. (2000), “Modellingthe dynamics of design error induced rework inconstruction”, Construction Management and Economics,Vol. 18 No. 5, pp. 575-86.

Naoum, S. and Mustapha, F.H. (1994), “Influences of the client,designer and procurement methods on projectperformance”, Proceedings of CIB W-92 ProcurementSystems Symposium, 4-7 December, East Meets West,Department of Surveying, The University of Hong Kong,Hong Kong, pp. 221-8.

National Economic Development Office (NEDO) (1987),Achieving Quality on Building Sites, Millbank, London, UK,pp. 18-19.

National Economic Development Office (NEDO) (1988), FasterBuilding for Commerce, Millbank, London, UK.

Nesan, J-L. and Holt, G.D. (1999), Empowerment in Construction:The Way Forward for Performance Improvement, SomersetResearch Studies Press, Hertfordshire.

Nunnally, J.C. (1978), Psychometric Theory, 2nd ed.,McGraw-Hill, New York, NY.

NWPC and NBCC (1990), “No dispute – strategies forimprovement in the Australian building and constructionindustry”, A Report by the National Public WorksConference and National Building and ConstructionCouncil Joint Working Party, May, Canberra, ACT,Australia.

Powell, C. (1997), “Responding to marginalisation”,Architectural Research Quarterly, Vol. 2, pp. 84-9.

Rawlings, J.O. (1988), Applied Regression Analysis – A ResearchTool, Wadsworth and Brooks/Cole, Belmont, California,USA.

Richardson, B. (1996), Marketing for Architects and Engineers:A New Approach, E&F Spon, London.

Rounce, G. (1998), “Quality, waste, and cost consideration inarchitectural building design management”, InternationalJournal of Project Management, Vol. 16 No. 2, pp. 123-7.

Sidwell, A.C. (1982), “A critical study of project teamorganisational forms within the building process”,unpublished PhD thesis, University of Aston,Birmingham, UK.

Stasiowski, F.A. and Burstein, D. (1994), Total QualityManagement for the Design Firm, Wiley, New York, NY.

Svelinger, P-O. (1996), Organisatorisk samordning vidprojektering, (Organisational Coordination in the DesignPhase). Report 44, Institution for byggnadsekonomi ochbyggnadsoganisation, Chalmers techiska hogskola,Goteborg, Sweden.

Syam, A. (1995), “Editorial”, Journal of the Australian Instituteof Steel Construction, Vol. 29 No. 1, p. 1.

Symes, M., Eley, J. and Seidal, A.D. (1995), Architects and TheirPractices: A Changing Profession, Butterworths, London.

Tabachnick, B. and Fidell, L.S. (1996), Using MultivariateStatistics, 3rd ed., Harper & Collins, New York, NY.

Tilley, P.A. and McFallan, S.L. (2000a), Design andDocumentation Quality Survey Designers’ Perspectives,BCE DOC 00/113. CSIRO - Building, Construction andEngineering, Melbourne, Australia.

Tilley, P.A. and McFallan, S.L. (2000b), Design andDocumentation Quality Survey Contractors’ Perspectives,BCE DOC 00/114 CSIRO - Building, Construction andEngineering, Melbourne, Australia.

Tilley, P.A. and McFallan, S.L. (2000c), Design andDocumentation Quality Survey Comparison of Designers’and Contractors’ Perspectives, BCE DOC 00/115, CSIRO

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Building, Construction and Engineering, Melbourne,Australia.

Tucker, S.N., Love, P.E.D., Tilley, P.A., Salomonsson, G.S.,MacSporran, C. and Mohamed, S. (1996), Perspective’s ofConstruction Contractors Communication andPerformance Practices: Pilot Survey Report, May, DBCEDOC 96/29 (M).

Thomas, H.R. and Neapolitan, C. (1994), “The effects of changeson labour productivity: why and how much?”, A Report forthe Construction Industry Institute by The PennsylvaniaState University, University Park, Pennsylvania, SourceDocument 94.

Walker, D.H.T. (1994), “An investigation into the factors thatdetermine building construction time performance”,unpublished PhD thesis, Department of Building andConstruction Economics, Faculty of Environmental Designand Construction, Royal Melbourne Institute ofTechnology, Melbourne, Australia.

Watkinson, E.D. (1992), “Procurement alternatives”, Faculty ofBuilding Journal, Autumn, Nottingham: Faculty of BuildingLtd, pp. 4-6.

Zeitoun, A. and Oberlander, G. (1993), “Early warning signs ofproject changes”, Source Document 91, ConstructionIndustry Institute, The University of Texas at Austin,Texas, USA.

Further reading

Construction Industry Development Agency (CIDA) (1994),Transforming Construction: The Total Project Approach –Managing Change-Achieving Integrated Solutions,Construction Industry Development Agency and MastersBuilders Australia, Sydney, Australia.

Hoxley, M. (2000), “Are competitive fee tendering andconstruction professional service quality mutuallyexclusive”, Construction Management and Economics,Vol. 18 No. 5, pp. 599-605.

Oppenheim, A.N. (1992), Questionnaire Design, Interviewing,and Attitude Measurement, Pinter, Publishers, London.

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