Journal of Financial Risk Management
2012. Vol.1, No.3, 42-51
Published Online September 2012 in SciRes (
Copyright © 2012 SciRes. 42
Qualitative Approach Risk Period in Construction Projects
Abdelhak Challal, Mohamed Tkiouat
Mohammadia School of Engineering, Studies and Research Laboratory in Applied Mathematics (LERMA)
Mohammed V University, Rabat, Morocco
Received June 16th, 2012; revised July 19th, 2012; accepted July 28th, 2012
The construction projects have experienced failure in meeting schedule deadlines. This is due to the unan-
ticipated events and factors causing delays. These delays give rise to dissatisfaction to all involved parties;
such fact leads to seek identifying delay factors according to their importance level. To achieve this aim, a
qualitative analysis of risk is proposed as a decision support tool to achieve project success.
Keywords: Project; Construction; Cause Delays; Time; Risk
The problem of delays in the field of construction is a com-
mon phenomenon worldwide. In Saudi Arabia, Assaf and Al-
Hejji (2006) found out that only 30% of construction projects
have been completed within the contracted deadlines, and the
average slipping period was between 10% and 30%. In Nigeria,
Ajanlekok (1987) identified through a questionnaire survey that
the delays have effects on 61 construction projects. The results
demonstrated that deadline slippage and cost overruns were
frequent and quite significant. The project manager is generally
responsible for those causes. Odeyinka and Yusif (1997) also
illustrated that 7 projects out of 10 studied had experienced
deadline slippage during their execution. Chan and Kumaras-
wamy (1997) studied the delays in industrial construction in
Hong Kong, they underlined the success index of a project and
its delivery within the deadlines, respecting the quality norms
and the budget allotted to it.
Normally, when we realise that the projects will experience
some deadline slippage, we provide a deadline extension or we
accelerate the pace of the works execution. As a consequence,
we allow for additional expenses, normal practices which gen-
erally permit an addition of a supplementary cost percentage
based on a prior study (Hatush & Skitmore, 1997).
Time performance is one of the key measures of the project’s
success (Hatush & Skitmore, 1997; Belassi & Tukel, 1996;
Walker, 1995 and 1996).
According to Faridi and El-Sayedgh (Faridi) delays have a
negative impact on the success of the project in terms of time,
cost, quality and security For Aibium and Jagbor (2002) the
entrepreneur and the Project Manager are jointly or separately
responsible for the delay in executing construction projects.
The delays can not be minimised unless their causes are known,
and in order to have an accurate estimate of costs and deadlines,
reliable methods and commonly agreed practices must be ap-
plied. Faridi and El-Sayedgh also emphasised that these causes
must be controlled during the life time of the project. Moreover,
an important economy of resources can be obtained while iden-
tifying and controlling the causes.
The main objectives of this study are as follows.
Identifying the causes of delays in construction projects in
several regions of Morocco as well as comparing them with
those identified by researchers in over the last two decades;
Ranking the inherent risks in terms of the probability and
importance perceived by the participants, such as, the pro-
ject manager, the clients and the contractors;
Identifying risks control measures.
This article is organised as follows: section 1 deals with the
previous studies on the causes of deadline slippage in construc-
tion projects. Section 2 explains the methodology adopted its
limitations and acquisitions. Section 3 discusses the results.
Section 4 presents the actions and measures which minimise -
construction project delays Section 5 attempts to draw conclu-
sions and perspectives.
Literature review
Many articles and studies conducted on the causes of con-
struction project delays worldwide have been examined. Ubaid
(1991) concluded in his surveys on the projects completed in
Saudi Arabia that lack of entrepreneurial performance is one of
the major causes of delays. He also identified the principle
measures to reinforce resources and improve entrepreneurial
skills. Assaf et al. (1995) Ghafly observed that the major causes
linked to construction projects in Saudi Arabia are due to finan-
cial problems, changes in project conception, projects’ contri-
butions, delay in decisions-taking, getting owners’ approval,
difficulties in getting a work permit, communication and coor-
dination problems. Chan and Kumaraswamy (1998) have car-
ried out a survey to evaluate the relative importance of 83 fac-
tors of potential delays in construction projects in Hong Kong.
They observed that 5 major causes of deadline slippage related
to mismanagement of risk, bad supervision, condition of the
site, delay in taking decisions, varying customer needs, varia-
tion of working time. Kaming et al. (1997) has studied the
causes of slippage of the completion date of 31 skyscrappers in
Indonesia. He noticed that cost overruns happen most fre-
quently and are most significant than deadline slippage. He
underlined that the main causes of this slippage are: the in-
crease due to inflation, the underestimate of material cost as
well as the degree of complexity of the construction project
itself, those relating to slippage are: change of design concep-
tion, weak productivity, inadequate planning, shortage of re-
sources. Kumaraswamy and Chan noted in a study that the
causes in construction projects conducted in Honk Kong were
differing perceptions by the different parties. Noulmanee et al.
(1999) concluded in a study on the causes of delays in the con-
struction of highways in Tahaland that the major causes are due
to sub-contractors’ income-petency and poor project conception
(incomplete and inaccurate design). They also suggested that
the delay could be minimised by devising a good project con-
ception, close coordination and an effective communication
among the participants. Al-Momani (2000) in his survey on 130
public projects in Jordan pointed out that the main causes of
delay are: poor project conception, climate, poor site manage-
ment, delay in delivery, economic situation and the amend-
ments. He recommended that managers of public projects take
the necessary time to start carrying out thorough studies by
using real quantitative data in order to formulate pertinent terms
before starting attributing the said project. The study also sug-
gested that special attention be given to industrialists in the
field of construction to reduce the purchasing costs. Conse-
quently, the delays are essential due to poor contractors produc-
tivity. According to (Koushk et al.; Assaf & Al-Hajji, 2006;
Meeampol & Ogunlana, 2006), Sambasivan and Soon (2007),
Le-Hoai et al. (2008) deadline slippage could lead to a number
of negative effects, such as cost overruns Sambasivan and so on,
Tow-hid and Amiruddin (2011) noted that major delay conse-
quences are related to: arbitration conflicts, litigations, and total
abandonment. Toor and Ogunlana (2008) and Saleh Al Hadi,
Tumi et al. (2009) believe that poor planning and lack of com-
munication are the principle causes of deadline slippage in
construction projects in Libya. Hamidreza et al. (2010) quali-
fied certain causes as unacceptable in order to respect the con-
tractual deadline for the completion of the construction projects
in Hong Kong. These causes are relative to delays of supply
and subcontractors’ incompetence. M. Haseeb1 et al. (2011)
consider that to avoid delays, the project manager must settle
the corporate discount on time. Also the enterprise must do the
same thing for the subcontractors. Ogunlana et al. (1996) no-
ticed that time and cost overruns in construction projects of
sky-scrappers in Bankok and Thailand resulted from three fac-
tors: lack of infrastructure, default in payment by both custom-
ers and consultants, and contractors incompetency, they rec-
ommended that managers and associations specialize in the
field of construction, make more efforts to streamline and build
the infrastructure which would allow easy supply of materials
and boost efficiency in the field of construction. Frimpong et al.
(2003) conducted a survey through a questionnaire on under-
ground construction projects in Ghana in order to identify and
evaluate the importance related to the factors leading to time
and cost overruns of the said projects. The findings revealed
that the main causes are: late payment on the part of the project
managers, shortage of raw materials, implementation of obso-
lete construction processes, and the high cost of raw materials.
They recommended that to minimise the delays in carrying out
the construction works, the projects should be well in advance,
and a follow-up should be insured as well as the control and
respect of the accomplishment planning.
Over the last decade, researchers have looked into the causes
and effects of delays in construction projects and confirm that
51% of the responsibility lies with the enterprises, followed by
the project manager 30% and the client 19% and that 90% of
these causes arise from the field and the internal organisation of
the intervening parties.
Also the researchers have shown that the causes which occur
frequently can be summarised as follows:
Poor management of the site;
The company’s financial difficulties;
Modifications made by the employer during the construc-
tion phase;
Delay in plan examination and approval by the project
Delay in issuing plans.
Overview of Approach
A construction project is commonly acknowledged as suc-
cessful when it is completed on time, within budgetary costs
and in accordance with the specifications and to participating
parties’ satisfaction. Being within the deadline of a construc-
tion,the project is important after issuing the construction con-
tract, so all concerned involved parties must be able to meet
schedule deadlines.
However, when construction industry gets compared to other
industries, several interesting facts are to be conveyed, the con-
struction industry is in fact where a combination of various
businesses come together, interact and collaborate to complete
the project. The intersection of activities and functions make it
a difficult task for UCI to identify and determine which one
will cause the delay, in fact, in each new project, the UCI have
to work each time with new different project team members.
Therefore, UCI are found compelled to adapt to such new team
and coordinate its members leading them altogether to achieve
project success by meeting schedule deadlines.
However, most construction projects are subject to delays
because of one actor or more. By the identification of actors
causing the delay, the UCI will be allowed to know well before
the bidding stage which factor needs to be more emphasized in
order to generate a better decision.
This approach is intended to allow the UCI driver to know
the important factors causing the delay in building projects.
These factors may also be called sources of risk delay in build-
ing projects.
The followed method of risk analysis is a qualitative method
dedicated to building projects. This analysis allows determining
all factors causing the delay. However, the existence of a large
number of delay factors doesn’t leave to decision maker the
possibility to have a clear vision to decide which one to be the
most important. Therefore, it becomes his choice to quantify
the importance of these factors by the calculation of relative
importance index of each factor, all done on the basis of sound
expertise of highly skilled experts in building projects. This
index serves to quantify each deadline risk in the project delay.
These delay factors can’t be conceived significant unless they
cause a probability of project delay beyond the accepted margin
by the clients; it is generally between 20% and 30%. It is also
necessary to be able to quantify the probability of a project
delay in case the identified delay factors are not controlled.
Fuzzy logic is also employed here to link causes to effects in
order to determine the probability of project delay in case the
identified risks are not controlled.
Copyright © 2012 SciRes. 43
The stages of this analysis are:
Identification of factors delaying building projects;
Ranking of factors delaying building projects using Ishi-
kawa diagrams;
Quantification of relative importance and ranking of fac-
tors according to their importance level;
Identification of linguistic variables and fuzzy matching
Codification of input and output variables;
Construction of fuzzy rules;
Determination of the weights of fuzzy rules by using the
results of the method of relative importance index
Aggregation and defuzzification results to estimate the
probability of delay in the materialisation of risks.
According to the “top-down” process adopted so far by the
previous so-called macroscopic studies, and which helped to
investigate and assess major risks on the macro-process, through
interviews and questionnaires, by starting the evaluation of
frequent occurrences, the severity and importance related to the
causes by the contractors, the project manager, and the owners.
These risks were ranked according to the retained criteria lead-
ing to the establishment of a mapping of risk causes
The “top-down” is certainly offering us here an advantage
since it makes risk mapping available in a short time.
Assessment Grids
The grids of reference that help reconcile the requirements
are presented as follows:
Grid A.1
A summary of probability and assessment of risks.
Level 1 Rare or very rare
Level 2 Regular/frequent
level 3 Very fréquent to systematic
Grid A.2
A summary of assessment of potential risk impact.
Level 1 Weak (0 - 4)
Level 2 Moderate (4 - 7)
Livel 3 Strong (7 - 10)
Grid A.3
A summary of severity evaluation.
High : 7-10
Weak : 0-4
Risk = probability *
High :
Moderate: 4-7 Weak : 0-4
First of all, these elements have been debated with the top
management of different participating parties, the actors with
the knowledge but lacking a keen interest vis-à-vis risk man-
agement. The choice of these people (or what we may also call
“casting”) turned out to be crucial to the success of the process
insofar as we will be led to move from the “project” mode to
the “process” mode in the medium-term. Equally the choice of
individuals interviewed (who should share their own visions of
risks within the enterprise, the project manager, and the owners)
was meticulously made.
Research Results
The General Characteristics of Respondents
The field survey consisted of 10 entrepreneurs, two owners.
The causes of delay were identified after having researches,
actions and control measures explored.
Identification and Ranking of Delay Factors in
Building Projects
Identification and Ranking of Delay Factors by Utilizing
Ishikawa Diagram
The Ishikawa Diagram, also known as the Fishbone Diagram
or the Cause-and-Effect Diagram, is a tool used for systemati-
cally identifying and presenting all the possible causes of a
particular effect. The possible causes are presented at various
levels of detail in connected branches. The head box of the
diagram contains the statement of the problem.
After identifying the factors of delay in the building projects,
these factors have been classified in groups of factors, depend-
ing on whether they belong to the contractor, the owner or to
external factors.
Delay factors related to the project manager identified are 13
in number. They were listed in the Ishikawa diagram in Figure
A. Delay factors related to the project manager identified
are 13 in number. They were listed in the Ishikawa dia-
gram in Figure A.1. Delay factors related to the project
manager identified are 13 in number. They were listed in
the Ishikawa diagram in Figure A.1.
Factors Related to Owner
Delay factors related to the owner have been counted
in nine key players. They are listed in the Ishikawa dia-
gram in Figure A.2.
Factors related to the contractor
Factors related to the contractor have been identified and
listed in the Ishikawa diagram in Figure A.3. They are number
20. (Table A.1, Table A.2)
External Factors
Regarding external factors, 12 main factors have been identi-
fied as shown in Figure A.4.
Quantifying the Importance Related to these Factors
This part aims to quantify the importance related to delays in
construction projects. The results of this quantification have
Copyright © 2012 SciRes.
Copyright © 2012 SciRes. 45
Figure A.1.
Ishikawa Diagram of prime contractor related delay factors.
Figure A.2.
Ishikawa Diagram of owner related delay factors.
Figure A.3.
Ishikawa Diagram of contractor related delay factors.
Figure A.4.
Ishikawa Diagram of external related delay factors
Table A.1.
IIR and ranks of delay factors.
Groups of factors N° Delay factors 1 2 3 4 5 IIR Rank
1 Lack of experience of the MOE in construction projects 2 1 0 3 4 0.72 10
2 Conflicts between the office and the architect 0 2 4 3 1 0.66 12
3 Delay in approving major changes in the work of the EOM 0 0 4 4 2 0.76 8
4 Delay in inspection and testing 1 1 7 1 0 0.56 18
5 Inaccurate site survey 1 1 6 1 1 0.6 16
6 Assistance in project management inadequate 0 1 4 5 0 0.68 11
7 Poor communication and coordination with other parties 1 0 4 5 0 0.66 12
8 Complexity of the project design 0 2 4 2 2 0.68 11
9 Design errors 1 1 2 0 6 0.78 7
10 Data collection and insufficient investigation before conception 1 0 4 4 1 0.68 11
11 Errors and delays in the production of design documents 0 0 1 5 4 0.86 3
12 Misunderstanding of the requirements of the client by the architect 0 0 4 1 5 0.82 5
1) Owner related factors
13 Inaccurate and insufficient details in the drawings 1 1 0 3 5 0.8 6
1 Change Orders 0 2 5 0 3 0.68 12
2 Delay in approving design documents 0 2 4 0 4 0.72 9
3 Delay in payment of advance 0 0 2 6 2 0.8 6
4 Delay in delivering the Site 0 1 3 4 2 0.74 2
5 Feasibility Study Project inappropriate 0 1 5 2 2 0.7 11
6 Lack of appropriate MOD 0 0 2 6 2 0.8 6
7 Lack of experience of the client in construction projects 0 0 0 6 4 0.88 2
8 Lack of communication and coordination with other actors 1 0 1 6 2 0.76 8
2) Client related factors
9 Design changes by the MO or MOD during the construction 0 0 1 3 6 0.9 6
Table A.2.
IIR and ranks of delay factors.
Groups of factors N° Delay factors 1 2 3 4 5 IIR Rank
1 Use more subcontractors 0 1 0 5 4 0.84 4
2 Inappropriate construction methods 0 0 2 4 4 0.84 4
3 Labor incompetent 0 1 0 6 3 0.82 5
4 Ineffective planning and scheduling 0 0 0 5 5 0.9 1
5 Poor communication and coordination with other parties 0 0 4 5 1 0.74 9
6 Poor management and site supervision 0 0 1 6 3 0.84 4
7 Reconstruction due to errors 0 0 2 5 3 0.82 5
8 Unreliable Subcontractors 1 0 4 2 3 0.72 10
9 Equipment allocation problem 0 2 4 2 2 0.68 12
10 Frequent breakdowns of equipment 0 1 3 5 1 0.72 10
11 Absenteeism 2 0 1 3 2 0.54 19
12 Lack of employee motivation 1 1 4 3 1 0.64 14
13 Low labor productivity 0 1 5 2 2 0.7 11
14 Strikes 2 1 3 3 1 0.6 16
15 Change in type of materials and specifications during construction 0 3 3 2 2 0.66 13
16 Damage to the materials 1 2 4 3 0 0.58 17
17 Rising prices for materials 1 2 4 2 1 0.6 16
18 Late delivery of materials 0 2 3 3 2 0.7 11
19 Shortage of building materials 0 2 1 5 2 0.74 9
3) Contractor related
20 Poor quality of materials construction 0 1 3 6 0 0.7 11
1 Accidents during the construction 2 7 1 0 0 0.38 21
2 Changes in regulations and laws 4 3 3 0 0 0.38 21
3 Delay in obtaining the permit from the municipality 0 1 5 2 2 0.7 11
4 Delay in final inspection and certification by the third party 0 3 4 2 1 0.62 15
5 Delay in the delivery of public services (such as water, electricity) 0 3 5 1 5 0.68 12
6 Price fluctuations 1 5 3 0 1 0.5 20
7 unfavorable weather conditions 0 2 4 1 3 0.7 11
8 Unexpected conditions in the basement 0 1 3 3 3 0.76 8
9 Ineffective delay penalties 1 2 4 2 1 0.6 16
10 Legal disputes between the project stakeholders 1 0 2 1 6 0.82 5
11 Short initial contract term 0 2 1 1 6 0.82 5
4) external related
12 Unfavorable contract terms 1 2 1 2 4 0.72 10
Copyright © 2012 SciRes.
Copyright © 2012 SciRes. 47
permitted to rank the causes on the basis of their importance
level vis-à-vis the project delay.
To count the importance indexes peculiar to each factor, a
Likert scale of 5 points has been selected. This scale contains
dominance ranging from 1 (very weak importance) to 5 (very
high importance).
Likert’s scale measures the intensity or the degree of agree-
ment on the part of the respondents which describes a certain
Data analysis method
This scale ranges between 4 and 7 degrees, but Likert’s scale
is the most widely used with 5 degrees.
This scale is favoured by researchers and seems to be the
most widely used because of a number of advantages:
It easily transforms the feeling on an interval scale which
can lead to a statistical analysis;
It is flexible ,and consequently can be used to measure the
degree of intensity of a feeling or an attitude;
Data analysis method
The method used to analyse data is the relative importance
index method. This index quantifies the relative importance of
diverse delay causes following the experts’ hindsight judge-
ments. It is calculated as follows:
Equation (A.1): relative importance index.
ni: the number of respondents having given an importance of
i to the factor in question
A: the highest importance that is 5 in our case
N: the total number of respondents
This relative importance indices ranges between 0 and 1 (0
excluded). Plus IIR is high, plus this factor contributes largely
to project delays.
The choice of the number of experts to be interviewed has
been limited to 10, including architects, contractors, project ma-
nagers, owners with great experience in construction projects.
Results Analysis
The relative importance indices has been computed for each
factor to identify the most significant delay factor in construc-
tion projects.
The following tables transmit the data collected; a rank is at-
tributed to each factor according to its importance index.
Groups and factors that may cause delays in construction
After calculating the IIR of each factor, it becomes possible
to calculate the probability of delay of a project in case the
deadline risks identified above are not controlled. The values
included in IIR reflect one certain persuasion, it is the impact of
each factor on the delay of construction project.
The use of fuzzy logic serves to identify relationships be-
tween risk sources and their consequences through cause and
effect relationships in order to determine the likelihood of pro-
ject delay.
Fuzzy logic allows representing mental systems (cause to ef-
fect relationship, preference degree) in mathematical forms.
Bearing in mind that the mental systems enjoys a specificity, it
is that they don’t abide by the principle of Boolean or classical
logic. In fact, in classical or Boolean logic, a variable can’t take
no more than two values, 1 for “true” and 0 for “false” it is a
two-valued logic, in contrast, in fuzzy logic, there is a range of
values from “true” to “false”. The value may range between
completely true and completely false. Thus, a variable can be
“somewhat true” with a percentage of 50% of “true” or
“slightly wrong” with a percentage of 25% of “false”.
The definition of membership percentages of the variable to
one or the other of states gets one back to define membership
functions. These membership functions, also called “fuzzy
functions”, are used to represent states that can take the variable
with the membership percentages in one or the other states.
Fuzzy model as an effective probability analysis technique
serves to estimate the delay probability of a project. However,
the adopted stages to its development are not controlled; the
model inputs are delay factors and also their relative impor-
tance while the output is the probability of project delays.
Fuzzy Logic Toolbox™ de MATLAB® is the tool employed
to develop the model.
Using Fuzzy Logic to Estimate the Probability of
Determination of linguistic Variables and Fuzzy Functions
The linguistic variables were selected from five variables:
“Very low (VL)”, “Low (L)”, “Medium (M)”, “high (H)”,
“Very high (VH),” in a scale ranges from 0 to 100. The scale is
similar to the 5-point Likert scale described above.
At this point, language assessment factors were transformed
to a combination of triangular and trapezoidal functions as
shown in Figure A.5.
The operator “Membership Function Editor” of the Fuzzy
Logic Toolbox™ MATLAB® allows the definition of mem-
bership functions of inputs and outputs. Figure A.6 shows the
input window of the membership functions of input data.
The Figure A.7 shows the input window of the membership
functions of output data. These functions are similar to those of
the input data.
Consolidation of Input Variables and Output
To enable linguistic variables to be easily manipulated, a three-
letter acronym has been chosen.
An example of this coding is presented in Table A.3.
The codification of the factor groups is as follows:
Factors related to the supervisor (FME)
Figure A.5.
Membership functions of linguistic variables.
Figure A.6.
Definition of membership functions of inputs.
Figure A.7.
Definition of membership functions of output.
Table A.3.
Example of coding delay factors.
Factors Acronyms
MOE lack of experience in construction projects MEM
Conflicts between the office and the architect CBA
Delay in approval of major changes in the work of the EOM RAC
Delay in inspection and testing RIE
Inaccurate site Inspection ESI
Factors related to client (FMO)
Factors relating to the contractor (FEN)
External Factors (FEX)
Fuzzy Rules and Aggregation & Defuzzification Rules
The construction of fuzzy rules has been employed to estab-
lish the interrelationships between the input data (the causes of
delay) and the output data (the probability of delay overall pro-
ject) in a natural language format. This form allows the free-
dom of expressing all delay factors in a simple language.
Copyright © 2012 SciRes.
In this article, Mamdani approach (“If ... Then”) has been
implemented, its fuzzy rules have widespread acceptance due to
their simplicity, adaptation and for being well suited to human
The calculated relative importance indices (IIR) have been
assigned as weighs to construct the fuzzy assessment model to
estimate the probability delay.
Table A.4: Example the fuzzy rules’ weights
After determining fuzzy rules with assigned weights as
shown in Figure A.8, it is a must to aggregate and defuzzify
results for each group of factors in order to know its contribu-
tion to the project delay. The results obtained for each group of
factors are, in turn, aggregated and defuzzified the same as the
factors in order to reach the overall likelihood of project delays.
The aggregation method has been selected as “max” for be-
ing the most popular in the literature. As for the defuzzification,
it has been decided to be the Centre Gravity due to the fact that
it is the most common adopted method. The result of the ag-
gregation gives a percentage of 71.2%. Therefore, the contribu-
tion of the client related delay factor of the project is calculated
as 71.2% as shown in Figure A.9.
The same approach has been adopted for the four groups of
delay factor. The following table is used to display the prob-
ability that each group of factors contributes to the overall delay
of the project.
Aggregation and déffuzification fuzzy rules for the four
groups of factors give the probability of overall delay project.
The following figure highlights the output window of fuzzy
evaluation model, which gives a net outflow representing the
probability of delay of a construction project in case identified
delay risks materialize. This probability is estimated at 69.1%
as shown in Figure A.10.
Interpretation of Results
The probability of delay of a construction project including
possible and uncontrolled risks has been estimated at 69.1%.
(Table A.5, Figure A.10)
The group of factors related to owner has the greatest likeli-
hood of contributing to the delay (Pr = 78%) this is due in par-
ticular to “design changes by the client or the client representa-
tive at construction” (RII = 0.9), the “lack of experience of the
client in construction projects” (RII = 0.88) and lack of com-
munication and coordination with other project stakeholders
(IIR = 0.76).
The second largest group is that factors related to the con-
tractor (Pr = 72.4%). Factors that contributed most are “ineffec-
tive planning and scheduling” (RII = 0.9), “poor site manage-
ment and supervision” (RII = 0.84) and “inappropriate con-
struction methods” (IIR = 0.84).
The group of factors related to the supervisor ranks third (Pr
= 71.2%). Factors that have contributed most are “errors and
delays in the production of design documents” (RII = 0.86),
“vague and inadequate details in the drawings” (RII = 0.82) and
“misunderstanding requirements of the client by the architect”
(RII = 0.8).
The group of external factors ranked last (Pr = 62.7%). The
most important factors in this group are “legal disputes between
project stakeholders” (RII = 0.82), “short initial contract term”
(RII = 0.82) and “unexpected conditions in the basement” (RII
= 0.76).
Since experts estimate that building projects likely to delay a
project of between 20% and 30% is acceptable, the probability
obtained, which is 69.1%, is largely unacceptable. It is there-
fore essential to take steps to respond to the identified risks.
Table A.4.
An example of Assigning Weights to the Fuzzy Rules presented in.
Rule Probability of delay rules Consequence Rules weight
1 If MEM Is TFo Then FME Is TFo 0.72
2 If CBA Is Fo Then FME Is Fo 0.66
3 If RAC Is Mo Then FME Is Mo 0.76
4 If RIE Is Fa Then FME Is Fa 0.56
5 If ESI Is TFa Then FME Is TFa 0.6
Figure A.8.
Entry Window fuzzy rules of the operator “Rule Editor”.
Copyright © 2012 SciRes. 49
Figure A.9.
Viewing results on the operator “Rule Viewer”.
Table A5.
Relative importance Indices of groups of factors.
Groups of factors Probability of contributing factor in the delay of the project (Pr) Rang
Prime contractor related factors 0.712 3
Client related factors 0.780 1
The contractor related factors 0.724 2
External related factors 0.627 4
Figure A.10.
Result on four groups of factors.
Recommendations and Action Plan
Development of Responses to Risks Identified and
Action Plan
This section aims to present the proposed strategies for each
risk identified, to justify the choice of type of response, and to
suggest remedial actions.
The following table represents the answer key to main risks
identified following qualitative analysis. This grid displays the
label of risk, its relative importance index, rank, the risk re-
sponse strategy and the proposed action for the implementa-
tion of the response strategy.
This paper aims to shed light on the importance of delay
risks in the preliminary stages of a building project. The state of
uncertainty due to poor estimate of tasks duration of building
projects has been explained by the identification of delay
factors, these factors have also been ranked according to their
importance level. Then, certain actions have been developed as
a respond to the risks of delay followed by technical proposals
to control and monitor those risks.
Finally, a decision support tool has been proposed as a
process in managing the risk of delay with the intention of
making it a part of the global project management process.
Every new project presents new situations that require
special treatments to be coped with. Thus, the risk register must
be kept updated by the UCI supported by the experience gained
through previous projects. The new identified risks are to be
met with risk responses as well as monitoring and controlling
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