Interpretive Structural Model-based for Analysis of Causes of Delays

in Construction Projects: The Portuguese Case

Amílcar Arantes

and Luis Miguel D. F. Ferreira

CERIS, CESUR, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, Lisboa,1049-001, Portugal

Univ. Coimbra, CEMMPRE, Department of Mechanical Engineering, Pólo II,

Rua Luis Reis Santos, 3030-788 Coimbra, Portugal

Keywords: Construction Delays, Construction Industry, Project Management, Interpretive Structural Modelling.

Abstract: Delays are a common issue in construction projects worldwide, and they can frequently have an influence on

time and cost overruns, among other problems. This study aims to add to the knowledge on construction

project management theory and practice by identifying the leading causes of Delays in Construction Projects

(DCP) in Portugal, modeling their interrelationships, and determining their main causes. The study presented

herein adopted a two-phase methodology. First, based on the literature, the causes of DCP in Portugal are

identified. Then the hierarchical structure of the causes of DCP is determined, using integrated Interpretive

Structural Modelling (ISM), and an ISM-based Model is developed. The results show that the 16 causes of

DCP taken into consideration are hierarchized in six different influence levels. The causes Bidding and

contract award process and Lack of communication between parties are the most influential causes, and are

thus considered to be the root causes of DCP in Portugal. Additionally, the results show that the causes of

DCP can be divided into four different categories relating to Relationships and contract, Material, the

Developer, and the Contractor. Finally, these results provide fundamental insights for practitioners and

researchers to develop effective measures to mitigate the causes of DCP.

1 INTRODUCTION

Regardless of the type of construction project, delays

are a global problem. A delay in construction is an

overrun either past the date the contract parties agree

upon to deliver a project or past the conclusion date

stated in the contract. A project must be finished on

time and meet the cost and quality requirements.

Accordingly, the timely completion of a project is

regarded as a significant parameter for measuring a

project’s success. Projects are prolonged or hastened

to overcome delays, incurring unavoidable additional

costs (Oyegoke & Al Kiyumi, 2017). The complexity

of construction projects often makes it difficult to

identify the causes of delays, which are frequently

interrelated.

The Portuguese construction industry is no

exception here, and delays are a disturbance for a

significant number of construction projects.

Accordingly, Portuguese construction companies

https://orcid.org/0000-0003-1207-5854

https://orcid.org/0000-0003-0459-0020

must be alert to and comprehend the origins of delays.

Such delays can be the cause of late conclusion of

projects, reduced productivity, augmented costs, and

even termination of the contract, all of which

contribute to construction companies’ ability to

compete.

There has already been several studies on this

issue in the literature. However, depending on the

context, the origins of delays may differ. For

example, they may be due to differences in culture,

environment, construction methods, management

system, geography, organizations involved, public

policies, economic context, availability of resources,

and the political climate (Zidane & Andersen, 2018).

Additionally, for the most part, the existing studies

focus on determining and ranking the causes of delay

in construction projects and proposing some

mitigation measures, in doing so, failing to

understand the interrelationships. The main objective

of this study is, therefore, to hierarchize the causes of

366

Arantes, A. and Ferreira, L.

Interpretive Structural Model-based for Analysis of Causes of Delays in Construction Projects: The Portuguese Case.

DOI: 10.5220/0010315303660374

In Proceedings of the 10th International Conference on Operations Research and Enterpr ise Systems (ICORES 2021), pages 366-374

ISBN: 978-989-758-485-5

delays in construction projects according to levels of

influence and determine their root causes in the

Portuguese context, with a view to improving

construction project management.

This research project is structured as follows: first,

a review of the literature on the causes of delays in

construction projects is carried out; second, the

research methods are presented; in the third section,

the results are presented and analyzed; and fourth, and

lastly, the conclusions and implications are drawn.

2 LITERATURE REVIEW

Given that the construction project process is a very

complex one, incorporating the various stakeholders’

priorities and concerns, covering numerous works,

and requiring a long period to conclude, the causes of

delays are multiple. Several researchers have studied

the causes of delays in construction projects. Odeh

and Battaineh (2002) concluded that the main causes

of delays were inexperienced contractors, owner

interference, delays in progress payments by the

developer, slow decision-making by the developer,

unsuitable planning, the low productivity level of the

labor force, and difficulties with subcontractors.

A study carried out by Assaf and Al-Hejji (2006)

showed that, in Saudi Arabia, contractors

acknowledged that the leading causes of delays had

to do with the developer, and developers and

consultants considered that the highest recurrent

cause of delay is the awarding of the contract to the

lowest bidder. However, they all agreed that the

developer changing orders during the construction

phase is a fundamental cause of delay.

Fallahnejad (2013) studied the causes of delays in

construction in Iran and concluded that the main

causes were: incapacity of the contractors to deliver

imported materials, questionable contract timelines

imposed by the developer, slow provision of

materials by the developer, time-consuming land

expropriation due to resistance from occupants and

changes to orders by the developer. For future

research, the author acknowledged the necessity to

define the root causes of delays and then develop

mitigation measures accordingly.

Ruqaishi and Bashir (2015) determined that the

main causes of construction project delays in the oil

industry in Oman were: reduced site management by

the contractor, difficulties with subcontractors, poor

scheduling and planning by contractors, delays in the

provision of materials, absence of proper

communication between project stakeholders and

little collaboration with vendors during the stages of

engineering and procurement.

Oyegoke and Al Kiyumi (2017) studied the

causes of delays and their effects on projects in

Oman. They found that the primary causes were:

selecting the lowest bid, the main contractor’s poor

financial situation, slow decision-making by the

developer, and inappropriate construction planning

by the contractor. As far as the major effects of the

delays are concerned, the authors pointed to

additional costs and project delays.

Zidane and Andersen (2018) researched the top

ten universal causes of delay in construction projects.

They compiled multiple studies conducted in

different countries on the causes and used a global

ranking index to select the “top ten universal delay

causes” from the top ten delay causes for 46

individual countries. The top ten universal delay

causes are changes to orders, late payments to the

contractor, weak planning and scheduling, poor site

management and control, poor design, inadequate

contractor experience and building processes,

contractor financial problems, developer financial

difficulties, resource rupture, and low labor

productivity and lack of skills.

More recently, Arantes and Ferreira (2020)

identified the causes and the main underlying causes

of delays in construction projects in Portugal. Six out

of the ten most important causes of delays are also in

the top ten universal delays (Zidane & Andersen,

2018). Factor analysis revealed six underlying

causes: improper planning, poor consultant

performance, inefficient site management, developer

influence, bureaucracy, and sub-standard contracts.

Based on the literature, the leading causes of

delays in construction projects reveal some variation

in accordance with the type of project and the

context/geography in which the project is carried out;

this is aligned with the opinion of other authors (Lind

& Brunes, 2015; Sambasivan & Soon, 2007; Sanni-

Anibire et al., 2020). While there is a certain degree

of consensus on the more significant causes of

delays, these authors did find different, although

related, sets of causes and present slightly different

rankings for the importance of causes. However,

some emerge as the most important causes (Zidane

& Andersen, 2018). Moreover, to the best knowledge

of the authors of this work, no studies consider the

root causes of the delays based on the

interrelationships between them.

The work presented here looks at the Portuguese

context and emphasizes owners, consultants, and

contractors in the construction industry. It intends to

contribute to project management by hierarchizing

Interpretive Structural Model-based for Analysis of Causes of Delays in Construction Projects: The Portuguese Case

367

the causes of delays in construction projects by

influencing factors, determining their root causes in

the Portuguese context.

3 RESEARCH METHOD

The present work adopted the two-phase

methodology presented in Figure 1. In the first phase,

the causes of Delays in Construction Projects (DCP)

in the Portuguese context are identified. And in the

second phase, it is established the hierarchical

structure of the causes of DCP using the ISM

methodology.

Figure 1: Methodology framework.

In phase I, a literature review is carried out on the

causes of DCP in order to identify the leading causes

of DCP in Portugal, as the focus group meeting

experts belong to Portuguese construction

companies.

In phase II, the ISM technique is used to identify

and evaluate the interrelationships between the

causes of DCP in Portugal, presenting a structural

map of the causes and the interconnections between

them, and highlighting the critical causes impelling

the generation of DCP.

The ISM methodology evaluates if and how the

multifaceted problem variables are linked, based on

the judgment of experts (Gan et al., 2018). These

judgments allow for the hierarchization of the

interrelationships between the variables, and the

translation of unclear mental models into visible and

well-deﬁned systems.

In the literature there are three Multi-Criteria

Decision-Making (MCDM) techniques to develop

structural hierarchies: DEMATEL, Fuzzy Cognition

Map (FCM), and ISM. However, FCM and

DEMATEL have clear limitations in comparison to

the ISM methodology.

DEMATEL defines the ranking of alternatives

based on their dependency but does not take into

consideration all criteria, and the relative weights of

experts are not aggregated to personal decisions of

experts within the group assessments (Malek &

Desai, 2019). Moreover, FCM requires hard

optimization of all the membership functions’

parameters and, sometimes, converges towards an

undesired steady state. ISM overcomes these

constraints; it classifies the multifaceted problem in

various groups, which individually represent one

segment of the problem. This is obtained through the

practical experience and knowledge of the

specialists. ISM provides insight into the

interrelationships among different variables and

assists in understanding the hierarchical way those

variables are established, thus determining the order

and direction of the multifaceted relationships among

the variables of the complex system (Xu & Zou,

2020). These characteristics make ISM the most

frequently used method in the literature and a secure

approach for developing the hierarchy structural

model (Malek & Desai, 2019). Furthermore, ISM can

capture dynamic complexities, while other MCDM

methodologies have difficulty representing real-life

multifaceted problems and capturing dynamic

behaviors (Shahabadkar et al., 2012).

ISM has been recently adopted in several studies

related to the construction Industry. For example,

Alzebdeh et al. (2015) examined ISM as a practical

technique for modeling multifaceted

interrelationships between factors in cost overruns in

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368

construction projects in the Sultanate of Oman. They

verified that the application of ISM makes it possible

to organize these factors in a hierarchical structure,

demonstrating their interrelationships. Four factors

were established as the root causes of cost overruns:

instability of the US dollar, changes in governmental

regulations, incorrect cost estimation, and weak

coordination among parties involved in projects.

Gan et al. (2018) realized that few studies

endeavored to investigate the complex

interrelationships among barriers to the transition

towards off-site construction in China.

Consequently, they adopted the ISM technique to

explore said interrelationships. The results show that

attention should be paid to inadequate policy and

regulations, lacking knowledge and expertise,

dominated traditional project process, and low

standardization. In particular, the findings provide

valuable information for policymakers on the overall

structure between barriers.

Sarhan et al. (2019) proposed a framework for

implementing lean construction strategies using the

ISM technique to improve performance levels in the

construction industry in Saudi Arabia. They

concluded that the framework constitutes

considerable progress over existing frameworks, as it

specifies the hierarchical relationships among the

different factors that contribute to the successful

implementation of lean construction, reflecting the

socio-cultural and operational contexts in the Saudi

Arabia construction industry. Therefore, based on the

above arguments, ISM was the chosen technique for

this research project.

The works of Shen et al. (2016) and Gan et al.

(2018) served as guide in the implementation of ISM.

In accordance with the aforementioned works, the

steps to develop ISM are as follows: (i) identification

and listing of the variables that comprise the system

to be studied; (ii) identification of the contextual

interrelationships by experts between each pair of

variables and registering them in a Structural Self-

Interaction Matrix (SSIM); (iii) translation of the

SSIM into an Initial Reachability Matrix (IRM),

which is a binary matrix representing the direct

interrelationships among the variables; (iv) checking

IRM for transitivity to also capture the indirect links

between variables, which will be transformed into the

Final Reachability Matrix (FRM), which considers

all the interrelationships (direct and indirect) among

the variables; (v) applying level partitioning to the

FRM, ranking the elements according to their levels;

(vi) drawing the ISM-based model by connecting the

variables at each level, based on their IRM

relationships; and lastly, (vii) presenting the ISM-

based model to experts to establish its consistency.

A Focus Group Meeting (FGM) was conducted

to implement the ISM. An FGM is defined as a

primary research technique that collects data through

group interaction on a subject set by the moderator

(Morgan et al., 1996). This qualitative research

approach provided detailed knowledge of a

phenomenon experienced by the FGM participants.

Care was taken to select experts with a view to

avoiding any bias within the group; the set of experts

was made up of two practitioners from each entity,

namely developers, consultants, and contractors. All

participants had more than ten years’ experience.

Furthermore, in the FGM, all experts had equal

weighting in the decision-making process, and their

opinions were only considered when the majority

were in agreement, as suggested by Shen et al.

(2016), in order to ensure consensus. The FGM was

moderated by one of the authors of this paper.

Particular attention was paid to the moderator’s role.

The moderator was well knowledgeable on

construction project management, and the discussion

advanced from the general to specific issues with a

view to stimulating sincerity and reducing bias

(Prince & Davies, 2001).

After implementing the ISM methodology, we

forwarded the hierarchical structure to the experts.

Later, ad hoc contacts were made with some of the

experts to ensure consistency of the results.

4 RESULTS AND DISCUSSION

4.1 Causes of DCP in Portugal

(Phase I)

A literature review was carried out to find and review

relevant literature on the causes of DCP in general,

and in Portugal in particular. The literature review

was also useful for defining descriptions for each

cause, which was central to guiding the FGM with the

experts. We selected the causes of DCP presented in

Arantes and Ferreira (2020), who analyzed the

Portuguese case. Of the 46 causes they studied, only

the 16 most important ones were selected for this

study. The selection criterion was having a median

value of the importance of the cause higher than the

threshold value of 4. The main causes are presented

in Table 1.

Interpretive Structural Model-based for Analysis of Causes of Delays in Construction Projects: The Portuguese Case

369

Table 1: Causes of DCP in Portugal.

No. Cause of DCP

C1 Slow decision making by the developer

C2 Change in orders

C3 Unrealistic schedule and specifications in the

contract

C4 Improper planning and scheduling

C5 Bidding and contract award process

C6 Delay in progress payments by the owner

C7 Delay in quality control

C8 Developer interference

C9 Increase in scope of work

C10 Mistakes and discrepancies in drawings

C11 Delay in obtaining permits from authorities

C12 Delay in the procurement of materials

C13 Changes in material specifications during

construction

C14 Delay in delivery of materials

C15 Disputes and negotiations between parties

C16 Lack of communication between parties

4.2 ISM Methodology (Phase II)

In the FGM, the experts were asked to make pair-wise

comparisons of the 16 causes of DCP in Portugal by

responding to the question, “Does cause i directly

influence cause j?” Four letters were used to represent

the direction of the interrelationship between each

pair of causes. “V” means that cause “i” influences

directly cause “j”; “A” means that cause “j”

influences directly cause “I”; “X” means that causes

“i” and “j” influence each other; and “O” means that

there is no interrelationship between causes “i” and

“j”. However, different experts may judge the pair-

wise comparison of two causes differently.

Accordingly, when consensus was not reached in this

study, the interrelationships among the causes were

settled by the rule, “the minority gives way to the

majority” (Shen et al. (2016). The interrelationships

among the causes of DCP in the Portuguese context

are presented in the Structural Self-Interaction Matrix

(SSIM) (Table 2).

Next, the SSIM is transformed into the Initial

Reachability Matrix (IRM) by substituting “V”, “A”,

“X” and “O” in accordance with the following rules:

(i) if the (i, j) entry is “V”, then the (i, j) entry in the

IRM becomes “1” and the (j, i) entry becomes “0”;

(ii) if the (i, j) entry is “A”, then the (i, j) entry in the

IRM becomes “0” and the (j, i) entry becomes “1”;

(iii) if the (i, j) entry is “X”, then the (i, j) and (j, i)

entries in the IRM become “1”; and, (iv) if the (i, j)

entry is “O”, then the (i, j) and (j, i) entries in the IRM

become “0”. Finally, the IRM was then checked for

transitivity. Transitivity means that if cause “i” is

directly related to cause “j” and cause “j” is directly

related to cause “k”, then causes “i” and “k” are

indirectly related through cause j, and if the entry (i,

k) in the IRM is “0”, then it must be changed to a

“1*”. This process converts the IRM into the FRM

(see Table 3), which considers all interrelationships

among the causes (direct and indirect). Table 3 also

presents each cause’s driving and dependence

powers, which are the sum of the rows and columns

of the FRM, respectively.

Table 2: Structural Self-Interaction Matrix.

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16

V O O O V V X A A V V A V V O

O O O O V X X V V V V V V O

A A V V V O O O V V V V O

O V V A A A O V O A V O

O O O O V O O O O V O

A A A O O V O O V A

A A A O O A A V O

V V V V V O V O

V V V V O V O

C10

V V A O V A

C11

V O O V A

C12

X O O A

C13

X V A

C14

V O

C15

C16

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Table 3: Final reachability matrix.

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16

C1 1 1 0 1* 0 1 1 1 1* 1* 1 1 1* 1 1 0

C2 1* 1 0 1* 0 1* 1 1 1 1 1 1 1 1 1 0

C3 1* 1* 1 1* 0 1 1 1 1* 1* 1* 1 1 1 1 0

C4 1* 1* 1 1 0 1 1 1* 1* 1* 1* 1 1* 1* 1 0

C5 1* 1* 1 1* 1 1* 1* 1* 1* 1 1* 1* 1* 1* 1 0

C6 1* 0 0 1* 0 1 1* 0 0 1* 0 1 1* 1* 1 0

C7 1* 0 0 1* 0 1 1 0 0 1* 1* 1* 1* 1* 1 0

C8 1 1 1* 1 0 1 1 1 1 1 1 1 1 1* 1 0

C9 1 1 1* 1 0 1 1 1* 1 1 1 1 1 1* 1 0

C10 1 1* 1* 1 0 1* 1 1* 1* 1 1 1 1* 1* 1 0

C11 1* 0 0 1* 0 0 1* 0 0 1* 1 1 1* 1* 1 0

C12 1* 0 0 1* 0 0 1* 0 0 1* 0 1 1 1* 1* 0

C13 1 1* 1* 1* 0 1* 1 1* 1* 1 1* 1 1 1 1 0

C14 1* 1* 1* 1 0 1* 1 1* 1* 1* 1* 1* 1 1 1 0

C15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0

C16 1* 1* 1* 1* 0 1 1* 1* 1* 1 1 1 1 1* 1 1

Table 4: Level partitioning results.

Causes Reachability Set Antecedent Set Intersection Set Level

C1 1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 13,

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

13, 14, 16

1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14 2

C2 2, 8, 9 2, 3, 5, 8, 9, 16 2, 8, 9 4

C3 3 3, 5, 16 3 5

C4 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12,

13, 14

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

13, 14, 16

1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13,

C5 5 5 5 6

C6 6 2, 3, 5, 6, 8, 9, 16 6 3

C7 1, 4, 6, 7, 10, 11, 12, 13, 14 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,

13, 14, 16

1, 4, 6, 7, 10, 11, 12, 13, 14 2

C8 2, 3, 8, 9 2, 3, 5, 8, 9, 16 2, 3, 8, 9 4

C9 2, 3, 8, 9 2, 3, 5, 8, 9, 16 2, 3, 8, 9 4

C10 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12,

13, 14

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

13, 14, 16

1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13,

C11 11 2, 3, 5, 8, 9, 11, 16 11 3

C12 1, 4, 7, 10, 12, 13, 14 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,

13, 14, 16

1, 4, 7, 10, 12, 13, 14 2

C13 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12,

13, 14

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

13, 14, 16

1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13,

C14 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12,

13, 14

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

13, 14, 16

1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13,

C15 15 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,

13, 14, 15, 16

15 1

C16 16 16 16 6

After the FRM, level partitioning was carried out.

For each cause of DCP, the reachability set, the

antecedent set, and the intersection set were created

to measure each cause’s influence levels. The

reachability set of cause “i” comprises all causes that

are influenced by cause “i" (which are represented by

“1s” in the row of the FRM corresponding to cause

“i"); the antecedent set of cause “i“ comprises all

causes that influence cause “i" (which are

represented by “1s” in the column of the FRM

corresponding to cause “i”); plus, the intersection set

contains the common causes found in both the

reachability and antecedent sets. When the

intersection set is equal to the reachability set of a

Interpretive Structural Model-based for Analysis of Causes of Delays in Construction Projects: The Portuguese Case

371

particular cause, then that cause is allocated to the

level of that iteration. The causes assigned to one

level are then detached from the remaining

reachability and intersection sets for the next

iteration. The same process is applied until all the

causes are partitioned into levels. Table 4 shows the

level partitioning results of the 16 causes of DCP. All

causes were partitioned into levels after six iterations,

meaning now the ISM-based model can be

represented.

Finally, a digraph is drawn up by positioning the

causes vertically according to the level partitioning

(Table 3) and linking the causes according to the IRM

using arrows. The ISM-based model (Figure 2) shows

the hierarchical structure of the causes of DCP in

Portugal, emphasizing their interrelationships.

Figure 2 shows six different levels of influence.

The first level of the ISM-based model is comprised

of the cause Disputes and negotiations between

parties (C15).

The second level directly influences the first level.

It is comprised of the Slow decision making by the

developer (C1), Improper planning and scheduling

(C4), Delay in quality control (C7), Mistakes and

discrepancies in drawings (C10), Delay in the

procurement of materials (C12), Changes in material

specifications during construction (C13) and Changes

in material specifications during construction (C14).

The third level directly influences the second level

and comprises Delay in progress payments by the

owner (C6) and Delay in obtaining permits from

authorities (C11).

Figure 2: The ISM-based model of the causes of DCP in Portugal.

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372

The fourth level of the ISM-based model directly

influences the third level and includes Developer

interference (C8), Change in orders (C2), and

Increase in scope of work (C9). The fifth level

contains Unrealistic schedule and specifications in

the contract (C3) and directly influences the fourth

level. Lastly, the sixth and final level of the ISM-

based model directly influences the fifth and the third

levels and has the most influence over the other

causes considered, comprising Bidding and contract

award process (C5) and Lack of communication

between parties (C16).

From the assessment of the ISM-based model, see

Figure 2, it became clear that the causes of DCP can

be divided into Relationships and contract-related

causes (C3, C5, C15, and C16), Material causes (C12,

C13, and C14), Developer-related causes (C1, C2,

C6, C8, and C9) and Contractor-related causes (C4

and C7).

4.3 Discussion

The six levels of causes of DCP presented in the ISM-

based model in Figure 2 make it possible to

understand their impact on DCP in the Portuguese

context. According to the ISM technique, measures

that lessen the causes originating at a higher level will

also help lessen the causes originating at a lower

level. However, corrective measures taken at lower

levels will have little to no effect at higher levels.

Therefore, stakeholders and practitioners from the

Portuguese construction industry must pay particular

care to the causes originating at level six when

developing mitigation measures to DCP, given that

said measures will mitigate those causes and also the

causes from other lower levels.

As a result, based on the ISM-based model

developed in this work, the causes of DCP that make

up the sixth level of the ISM-based model –

i.e.,

Bidding and contract award process (C5), and Lack

of communication between parties (C16) – are

considered to be most influential causes of DCP.

These causes have already been indicated as

important to DCP by other authors (Arantes &

Ferreira, 2020; Assaf & Al-Hejji, 2006; Fallahnejad,

2013; Ruqaishi & Bashir, 2015), and, as such, special

mitigation measures should be foreseen. This result

supports the consistency and value of the model

developed.

5 CONCLUSIONS

In this study, the interrelationships between 16 causes

of DCP in Portugal were modeled. The ISM

methodology was applied to structure the selected

causes into a hierarchy and divide them into six

different influence levels. Two root causes of DCP

were identified: Bidding and contract award process

and Lack of communication between parties. This

study also reveals how the causes of DCP affect each

other and provides guidelines for researchers and

practitioners to develop effective measures to

mitigate the causes of DCP. Moreover, the results

show that the causes of DCP are essentially of four

different types that can be related to Relationships

and contract, Material, the Developer, and the

Contractor.

Even though this paper contributes to the

discussion on the causes of DCP in Portugal, namely

the interrelationships between them, it also has

certain limitations. Firstly, the results are dependent

on the opinions of a small number of experts; and,

secondly, the results may not be generalizable to other

contexts. However, these limitations also constitute

future research opportunities.

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