Tender Pricing of Infrastructure Projects: Affecting Factors

Abstract

Infrastructure projects are what keep the important functions of any state alive. This paper is about a study concerning the factors affecting the tender pricing for infrastructure projects. A questionnaire was designed according to the collected factors form the literature, which were classified into six clusters (owner, consultant, contractor, donor, market, and project). The final version of the questionnaire was distributed to the owners, constructors, and consultants after the pilot study. The analysis shows that: the highest cluster is consultant related with RII of 81.33%. The second cluster is donor related cluster with RII of 79.92%. On the other hand, the highest two factors from the contractor cluster are: contractor visits to the project site, and study tender documents accurately, with RII 88.33% and 86.67%, respectively. It can be recommended that the contractor should be aware of the conditions of the project site, and the nature of the soil, taking into account the different nature of the land from one location to another, knowing that the rocky land requires a high cost and a longer period of time to complete the work. Also contract terms and the executive regulations should be accurately reviewed, which may bear additional costs.

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Tender Pricing of Infrastructure Projects: Affecting Factors
Bassam A. Tayeh1; Wesam Salah Alaloul2; and Noor K. Al-Ghazalli3
1Civil Engineering Dept., Faculty of Engineering, Islamic Univ. of Gaza, Gaza, Palestine. E-
mail: btayeh@iugaza.edu.ps
2Dept. of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Bandar Seri
Iskandar 32610, Tronoh, Perak, Malaysia. E-mail: wesam.alaloul@utp.edu.my
3Civil Engineering Dept., Faculty of Engineering, Islamic Univ. of Gaza, Gaza, Palestine
ABSTRACT
Infrastructure projects are what keep the important functions of any state alive. This paper is
about a study concerning the factors affecting the tender pricing for infrastructure projects. A
questionnaire was designed according to the collected factors form the literature, which were
classified into six clusters (owner, consultant, contractor, donor, market, and project). The final
version of the questionnaire was distributed to the owners, constructors, and consultants after the
pilot study. The analysis shows that: the highest cluster is consultant related with RII of 81.33%.
The second cluster is donor related cluster with RII of 79.92%. On the other hand, the highest
two factors from the contractor cluster are: contractor visits to the project site, and study tender
documents accurately, with RII 88.33% and 86.67%, respectively. It can be recommended that
the contractor should be aware of the conditions of the project site, and the nature of the soil,
taking into account the different nature of the land from one location to another, knowing that the
rocky land requires a high cost and a longer period of time to complete the work. Also contract
terms and the executive regulations should be accurately reviewed, which may bear additional
costs.
Keywords: Infrastructure projects, tender pricing, Gaza Strip.
INTRODUCTION
The number of competitors in the construction sector is much higher than in most economic
sectors. As a result of this severe competition, many construction firms in the developing
countries fall out of business within the first five years of establishment (Li et al., 2012b). The
construction industry players are facing the dilemma of bidding under a competitive environment
where the bid must be low enough to win the contract and high enough to attain the expected
profit margi (Fernández-Sánchez and Rodríguez-López, 2010, Alaloul et al., 2016c). In tender
pricing the distribution of risk among contracting parties is the most important criteria.
Contractors have to bid competitively for most of their projects and at the same time deal with
risks and uncertainties connected with bid submission (Flyvbjerg et al., 2004). The high level of
price competition and low capital intensity which characterizes the infrastructure projects often
combine to cause depressed profit margins. If the contractor is selected, the estimate should also
provide the basis for project budgeting and control
(Li et al., 2013, Alaloul et al., 2016b). In coping with this situation, the contractor will
normally ensure that appropriate cost estimate is determined with adequate mark up. The cost
estimating function, an important element in the contractors bidding process, provides a basis for
the contractor to submit a tender price for a project (Enshassi et al., 2009, Li et al., 2012a,
Alaloul et al., 2015a).
Over the past few years, many construction projects in Gaza have bypassed the timeline with
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additional costing problems. Especially in infrastructure projects, many obstacles were faced
which lead to low project performance and poor owner satisfaction. Therefore, this study
investigates the factors affecting tender pricing in infrastructure projects in the Gaza Strip from
the perspective of contractors and consultants (Al-Najjar, 2008, Cheng et al., 2001, Gramlich,
1994, Alaloul et al., 2017).
LITERATURE REVIEW
Infrastructure project pricing is complex due to the nature of the construction industry which
is fragmented and competitive. Contractors must provide competitive bids dealing with risks and
uncertainties associated with bidding. A great deal of current information such as demand, cost,
competition, etc. should be forecasted, to set and adjust bids to the required profit levels. There
are many pricing objectives that can be identified. (Cheng et al., 2001) determined three main
types of pricing objectives: cost related, competition related, and demand related (Li et al.,
2012b, Oke et al., 2017, Alaloul et al., 2016a).
Pricing strategy is a pre-selection of a set of alternative prices (or price table) that can aim to
maximize profits during a planning period in response to a given scenario. Flanagan and Norman
(1989) Explained that there are variety of pricing systems used in the construction industry,
which are determined by the contract between the client and the contractor. (Morris and
Calantone, 1990) categorized pricing strategies into cost-based pricing, including government-
controlled profit prices, and market pricing including customer-oriented pricing and
competitiveness. According to (Kwatsima, 2017), the tender costing is the process by which the
indirect costs and markup will be distributed among the items of the bill of quantities so that the
bid price is ready to be submitted to the client. The contractor should decide the percentage of
the encoding that makes the bid low enough to win and at the same time high enough to make a
reasonable profit (Li et al., 2013, Flyvbjerg et al., 2004). Based on the systematic literature
review, the collected factors were classified into six clusters related to (owner, consultant,
contractor, donor, market, and project), which will be presented in the results and discussion.
RESEARCH METHODOLOGY
The review of the previous studies has been carried out and a pilot study was conducted to
ensure the structure of the questionnaire validity and the reliability of the collected data.
Arbitration of the questionnaire was implemented by 12 experts in infrastructure sector in the
Gaza Strip in addition to academicians. Then the questionnaire was modified based on the pilot
study results and the final version was adopted to be used for the study design (Krosnick, 2018,
Alaloul et al., 2015b). To determine the sample size; the following statistical formula was
utilized (Boddy, 2016):
 
2
2
1 Z P P
SS C
  

(1)
Where:
SS: The size of sample.
Z: Z value (for example: when confidence interval 95%, Z value =1.96).
P: Percentage picking a choice, expressed as decimal, (0.50 used for sample size needed).
C: Maximum estimation error (0.05). Correction for finite population
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 
SS
SS 1
1Population
SS new 



(2)
where the population; in this study is 169 contracting firms and consultants. The prior
calculations showed that the minimum number of the questionnaires required to be collected is
120. The questionnaire was distributed to 122 participants involved (owners, contractors and,
consultants). For the respondents’ profile, 53.3% are Contractors, 24.2% are Consultants, and
22.5% are owners. On the other hands, 15.8% Respondent's experience in an infrastructure sector
is "Less than 5 years", 34.2% is "5- less than 10 years", 16.7 % is 10- 15 years", and 33.3 % is
"more than 15 years".
The validity of the questionnaire structure was statically tested as shown in Table 1. The
significance values are less than 0.05 or 0.01, so the correlation coefficients for all fields are
statistically significant at α = 0.01 or α = 0.05. Therefore the fields are valid for measuring what
is in order to achieve the objective of the study (Hill et al., 2015).
Table 1. Structure validity of the questionnaire
No.
Section
Pearson correlation
coefficient
P-value
1
Factors related to the owner
0.653
0.000
2
Factors related to the consultant
0.671
0.000
3
Factors related to the contractor
0.730
0.000
4
Factors related to the donor
0.737
0.000
5
Factors related to the market
0.645
0.000
6
Factors related to the project
0.785
0.000
However, the reliability test was conducted as shown in Table 2. The Alpha Cronbach
coefficient was calculated for the first area of the claims, the second area of the joint proceedings
and the third area of the special claims (Trizano-Hermosilla and Alvarado, 2016). The results
were in the range of 0.863 and 0.925 and the overall reliability of all items is equal to 0.904. This
is a high range; the result ensures the reliability of the questionnaire.
Table 2. Cronbach's coefficient alpha
Number
Section
Cronbach's Alpha
1
Factors related to the owner
0.863
2
Factors related to the consultant
0.889
3
Factors related to the contractor
0.901
4
Factors related to the donor
0.925
5
Factors related to the market
0.896
6
Factors related to the project itself
0.899
A single K-S sample test is used to determine whether the data follow a normal distribution.
This test is necessary for test hypotheses since most standard tests presume the data are normally
distributed (Mbah and Paothong, 2015). The test result is shown in Table 3, the calculated P-
value is greater than the important level of 0.05 (P-value> 0.05), which in turn indicates that the
data follows the usual distribution, and so should be used for border tests.
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Table 3. One -sample K-S test for normality
Number
Sub Section
Statistic
P-value
1
Factors related to the owner
0.566
0.907
2
Factors related to the consultant
1.226
0.098
3
Factors related to the contractor
1.282
0.075
4
Factors related to the donor
1.348
0.053
5
Factors related to the market
0.885
0.413
6
Factors related to the project itself
0.953
0.324
The relative importance index RII technique has been widely used in construction research
for measuring attitudes with respect to surveyed variables. Several researches (Enshassi et al.,
2010; Enshassi et al., 2011; Enshassi et al., 2012; El-Hallaq and Tayeh, 2015; Albhaisi et al.,
2016; Tayeh et al., 2016; Tayeh et al., 2017; Tayeh et al., 2018; Tayeh et al., 2018 and Mahfuth
et al.,2018) used the RII in their analysis. To determine the relative order of factors affecting the
tender pricing, the scores have become important formula-based indicators as following
(Crowder, 2017):
5 4 3 2 1
Relative Importance 5 4 3 2 1
Index 5
wn n n n n
AN N
   
 
(3)
Where W is the weighting given to each factor by the respondent, ranging from 1 to 5, (n5 =
number of respondents for Big, n4 = number of respondents for Very Big, n3 = number of
respondents for moderate, n2 = number of respondents for weak, n1 = number of respondents for
Not Available). A is the highest weight (i.e. 5 in the study) and N is the total number of samples.
The relative importance index ranges from 0 to 1 (Crowder, 2017).
RESULTS AND DISCUSSION
The statistical results of the six major clusters (owner, consultant, contractor, donor, market,
and the project) show that the highest cluster is consultant related with RII of 81.33% followed
by the After that donor related cluster with RII of 79.92%. The rest of the cluster results are as
following: (market-related cluster) with RII of 79.00% is the third rank, (owner relating cluster
with RII of 78.89% is the fourth rank, contractor related cluster to with RII of 78.89% was the
fifth rank, and finally project related cluster with RII of 75.93% was the sixth rank.
The complete statistical results of the six major clusters factors (owner, consultant,
contractor, donor, market, and the project) affecting the tender pricing with the mean, standard
deviation (SD), Relative Importance Index (RII) and the rank are represented in Table 4. One
sample t-test was also used for test the opinion of the respondent about each factor (Kim, 2015).
For Owners Related Factors, the first factor according to RII is (The financial performance)
with RII of 83.67%, and P-value equal 0.000 < 0.05, The owner's misunderstanding of the
financial assets management in relation to an infrastructure project leads to a defect in bid
pricing. The second factor is (The accuracy in evaluating the works which will be completed)
with RII of 82.67%, and P-value equal 0.000 < 0.05. The owner's lack of interest in evaluating
the mechanisms of implementation of infrastructure projects, or the weakness of his experience
in evaluating the work that will be done, affects negatively on the contractor's pricing of the
tender (Wondimu et al., 2016).
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Table 4. RII and P-value for tender pricing factors
Factor
Mean
Std.
Deviation
RII
t-
value
P-
value
Rank
Owners Related Factors
The financial performance.
4.18
0.745
83.67
17.410
0.000
1
The accuracy in evaluating the works which will be complete.
4.13
0.709
82.67
17.504
0.000
2
Time period to run out the project according to tender
documents.
4.06
0.853
81.17
13.591
0.000
3
The owner tender awarding method.
4.04
0.873
80.83
13.064
0.000
4
Quality and accuracy of tender documents.
4.03
0.907
80.67
12.482
0.000
5
Owner's financial reputation.
4.00
0.889
80.00
12.325
0.000
6
Time period afforded to fill and award tender.
3.83
0.956
76.67
9.553
0.000
7
Negative relationships between work parties and the owner.
3.81
0.964
76.17
9.185
0.000
8
Information and data about construction costs.
3.80
0.885
76.00
9.903
0.000
9
Tender documents contradiction.
3.78
1.008
75.50
8.422
0.000
10
Repeated changes which the owner requests.
3.73
0.952
74.50
8.340
0.000
11
Consultants Related Factors
The accuracy of the quantities included in the Bill of quantities.
4.32
0.673
86.33
21.418
0.000
1
Quality and accuracy of tender documents.
4.08
0.780
81.50
15.105
0.000
2
Consultant's ability to control quality.
4.03
0.766
80.67
14.773
0.000
3
Technical skills and management experience of the consultant
team.
4.03
0.727
80.50
15.441
0.000
4
The mechanism for carrying out the required works from the
contractor specified.
3.98
0.869
79.67
12.389
0.000
5
Ease of implementation of the designs proposed.
3.97
0.755
79.33
14.022
0.000
6
Contractors Related Factors
Contractor visits to the project site.
4.44
0.708
88.83
22.317
0.000
1
Study tender documents accurately.
4.33
0.760
86.67
19.228
0.000
2
Follow correct steps in evaluating bids from subcontractors.
4.12
0.852
82.33
14.359
0.000
3
Contractor's ability to take risk factors during bid pricing.
3.92
0.885
78.33
11.349
0.000
14
Contractor's ownership of machinery and equipment.
3.74
0.992
74.83
8.194
0.000
21
Maintenance costs of machinery and equipment.
3.63
0.869
72.67
7.984
0.000
23
Interest rate because of financial loans.
3.68
0.953
73.67
7.859
0.000
22
Evaluation of works according to the bill of quantities.
3.78
0.874
75.50
9.712
0.000
20
Understand the tender items.
4.12
0.724
82.33
16.897
0.000
3
Taking into account the productivity of workers.
3.97
0.829
79.33
12.767
0.000
9
Administrative and technical competence of the contractor's
staff.
4.05
0.849
81.00
13.554
0.000
5
Wages of skilled workers according to work experience.
4.08
0.866
81.67
13.710
0.000
4
Coordination between Contractor and Subcontractors.
3.80
0.958
76.00
9.148
0.000
19
The relationship between managers and employees.
3.81
0.998
76.17
8.870
0.000
18
Financial Capacity of the Contractor.
3.98
0.907
79.67
11.872
0.000
7
Contractor performance in previous similar projects.
4.03
0.849
80.67
13.326
0.000
6
The current work size of the contractor at the time of bid
pricing.
3.84
1.037
76.83
8.890
0.000
17
The number of competitors entering the tender.
3.98
0.772
79.50
13.835
0.000
8
The current workload of the bidder.
3.88
0.791
77.67
12.241
0.000
16
Availability of other projects in the market.
3.91
0.926
78.17
10.748
0.000
15
Contractor's execution mechanism .
3.88
1.022
77.67
9.465
0.000
16
Contractor's ability to control costs.
3.93
0.881
78.50
11.504
0.000
13
Granted time to the contractor in pricing.
3.84
1.045
76.83
8.822
0.000
17
Guarantee of the project maintenance period.
3.95
0.829
79.00
12.560
0.000
10
The financial value of the tender.
3.93
0.941
78.67
10.860
0.000
12
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Factor
Mean
Std.
Deviation
RII
t-
value
P-
value
Rank
Determine the degree of classification of companies to enter the
tender.
3.93
0.923
78.67
11.072
0.000
12
Maintain the technical staff, workers and equipment in the
company.
3.94
0.513
78.89
20.163
0.000
11
Donors Related Factors
Coordination between the owner and the donor of the project.
4.17
0.792
83.33
16.134
0.000
1
Requirements of payment guarantee of the project.
4.10
0.653
82.00
18.443
0.000
2
Financial status of the donor.
4.06
0.833
81.17
13.916
0.000
3
The nature of political conditions in the country.
3.95
0.951
79.00
10.939
0.000
4
Available fund.
3.85
0.941
77.00
9.898
0.000
5
Deferred discount of payments to the final payment.
3.85
0.932
77.00
9.994
0.000
5
Market Related Factors
Status of crossing.
4.19
0.990
83.83
13.188
0.000
1
Change in local and global market conditions.
4.12
0.881
82.33
13.884
0.000
2
Currency prices change in the local market.
4.11
0.951
82.17
12.769
0.000
3
Inflation in raw material prices within the market.
3.99
0.939
79.83
11.565
0.000
4
Materials and equipment size for the projects.
3.98
0.809
79.67
13.308
0.000
5
Updated contractor's information in local market.
3.95
0.808
79.00
12.879
0.000
6
Considering potential increases in customs duties and taxes
3.95
0.934
79.00
11.148
0.000
7
Contractor's workload during bid pricing period.
3.88
0.846
77.50
11.333
0.000
8
Available other projects in the construction market.
3.82
0.944
76.33
9.480
0.000
9
Providing experienced and skilled suppliers.
3.78
1.073
75.50
7.915
0.000
10
Subcontractors' commitment to the provided prices to the
Contractor.
3.69
0.933
73.83
8.121
0.000
11
Project Related Factors
Political conditions within the country.
3.98
0.948
79.50
11.268
0.000
1
Customs duties on imported materials.
3.93
0.932
78.67
10.965
0.000
2
Project access costs.
3.92
0.846
78.33
11.870
0.000
3
Meet domestic production of raw materials.
3.90
0.938
78.00
10.506
0.000
4
The nature of the project.
3.81
0.929
76.17
9.537
0.000
5
The size of the required site equipment and tools.
3.58
0.875
71.67
7.301
0.000
6
Consider changing weather conditions.
3.46
1.044
69.17
4.808
0.000
7
In Consultants Related Factors, the highest two factors according to RII are: (The accuracy of
the quantities included in the Bill of quantities) with RII of 86.33%, and P-value equal 0.000 <
0.05. The consultant does not place the quantities listed in the table of quantities accurately,
unlike the contractor, where the consultant protects himself from the appearance of any
additional works or faults during implementation and (Quality and accuracy of tender
documents) with RII of 81.50%, and P-value equal 0.000 < 0.05. One of the tasks of the
consultant is to prepare the tender documents with high accuracy and quality. In some cases, the
projects are implemented several years after the preparation of the project proposal and the
preparation of its documents, then the nature of the site has changed (Robertson and Newling,
2015).
In Contractors Related Factors, the highest two factors according to RII are: (Contractor
visits to the project site) with RII of 88.83%, and P-value equal 0.000 < 0.05. The contractor in
many infrastructure projects does not undertake a field visit to the site to be executed. It depends
on his previous experience in how to implement it, knowing that each project differs from the
other in its characteristics, mechanism of implementation and nature (Signor et al., 2016), and
(Study tender documents accurately) with RII = 86.67%, and P-value equal 0.000 < 0.05. Most
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of the contractors in Gaza do not study all the tender documents accurately, due to the limited
time period given to the contractor in the pricing of the tender, which results in errors that may
be serious in pricing, so costs become more than estimated (Oshodi et al., 2017, Signor et al.,
2016).
For Donors Related Factors, the first factor according to RII is (Coordination between the
owner and the donor of the project) with RII of 83.33%, and P-value equal 0.000 < 0.05, due to
the conflict of interest between the owner and the financier, and therefore the dissatisfaction of
the financier with the project proposed by the owner. It may often be that the financier is linked
to a certain budget that may not be sufficient for the implementation of the project proposals
submitted by the owner (Fuentes Bargues et al., 2016). The second factor is (Requirements of
payment guarantee of the project) with RII of 82.00%, and P-value equal 0.000 < 0.05. Many
financiers resort to delaying the payment of financial payments to the contractor. The contractor
is obliged to raise or reduce the price according to the period in which the transfer of the
contractor's payments is made in any new tenders (Urquhart et al., 2017).
For Market-Related Factors, the first factor according to RII is (Status of crossing) with RII
of 83.83%, and P-value equal 0.000 < 0.05. The continuous closures of crossings in the Gaza
Strip, leading to the scarcity of materials or high prices, and this negatively affects the pricing of
the tender (Amadi and Omotayo, 2017). The second factor is (Change in local and global market
conditions) with RII of 82.33%, and P-value equal 0.000 < 0.05. The researcher attributed this to
the fact that the continuous changes between the period and the other in the prices of materials
related to the local or global market, especially the basic materials such as cement and iron,
negatively affect the pricing of the tender (Al-Najjar, 2008).
For Market-Related Factors, the first factor according to RII is (Political conditions within
the country) with RII of 79.50%, and P-value equal 0.000 < 0.05. The researchers believe that
the political situation in the Gaza Strip, especially after the division in 2007, has deteriorated
significantly, leading to the imposition of a siege on Gaza, the shortage of basic materials
available in the market and the deterioration of the economy of Gaza. The second factor is
(Customs duties on imported materials) with RII of 78.67%, and P-value equal 0.000 < 0.05. The
researchers found that the contractor in Gaza after the events of division led to an increase in
customs duties on materials imported from abroad. The payment of taxes to the West Bank and
Gaza, which led to higher prices, leads to an increase in pricing errors between the periods
(Enshassi et al., 2009).
CONCLUSIONS
The focal point of this study was to assess the perspectives of construction professionals on
factors influencing tender prices of infrastructure projects. These factors should be considered by
contractors who are willing to bid for infrastructure projects during the preparation of tender. A
questionnaire survey was conducted to collect the perceptions of construction professionals.
Respondents were asked to give their opinions about the importance of 61 factors adopted from
the literature review and piloting study.
The highest two factors are from the contractor cluster: Contractor visits the project site, and
study tender documents accurately, with RII 88.33 % and 86.67%, respectively.
In the Gaza strip, the contractor in many infrastructure projects does not undertake a field
visit to the site. Also, most of the contractors do not study all the tender documents accurately,
due to the limited time period given to the contractor in the pricing of the tender, which results in
errors that may be serious in pricing, so costs become more than estimated. It can be
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recommended that the contractor should be aware of the conditions of the project site, and the
nature of the soil, taking into account the different nature of the land from one location to
another, knowing that the rocky land requires a high cost and a longer period of time to complete
the work. Also, they need to accurately review the contract terms and the executive regulations
as they are binding materials to the contractor, which may bear the contractor additional costs
such as insurance and social insurance. After the owner's approval of the preliminary designs and
any necessary modifications to the work program or budget, the relationship becomes more
general and detailed. Summarizing an accurate description of the nature and size of the project,
including its structural, architectural, and electrical components through drawings, details,
sections, tables and curves. The preliminary specifications of the project are developed and cost
estimation is developed more accurately.
REFERENCES
AL-NAJJAR, J. M. (2008). Factors influencing time and cost overruns on construction projects
in the Gaza Strip. Factors Influencing Time and Cost Overruns on Construction Projects in
the Gaza Strip.
ALALOUL, W. S., LIEW, M. S. & ZAWAWI, N. (2016a). Coordination process in construction
projects management. Engineering Challenges for Sustainable Future. ROUTLEDGE in
association with GSE Research.
ALALOUL, W. S., LIEW, M. S. & ZAWAWI, N. A. W. A. (2016c). Identification of
coordination factors affecting building projects performance. Alexandria Engineering
Journal, 55, 2689-2698.
Albhaisi M.A., Tayeh, B.A., El-Hallaq, Kh., (2016). Variation Orders in Construction Projects in
Gaza Strip (Case Study: Qatar Projects). International Journal of Engineering and
Management Research. 6 (5), 262-270.
AMADI, A. & OMOTAYO, T. (2017). The nomenclature of geotechnical error traps as a
theoretical framework for assessing financial risk in transportation infrastructure projects.
BODDY, C. R. 2016. Sample size for qualitative research. Qualitative Market Research: An
International Journal, 19, 426-432.
CHENG, E. W., LI, H., DREW, D. & YEUNG, N. (2001). Infrastructure of partnering for
construction projects. Journal of Management in Engineering, 17, 229-237.
CROWDER, M. J. (2017). Statistical analysis of reliability data, Routledge.
El-Hallaq, Kh., Tayeh, B.A., (2015). Strategic Planning in Construction Companies in Gaza
Strip. Journal of Engineering Research and Technology, 2(2) 167-174.
Enshassi, A., Faisal, M.A. & Tayeh, B.A. (2010). Subcontractor prequalification practices in
Palestine. The International Journal of Construction Management, 10, 45-75.
Enshassi, A., Faisal, M.A. & Tayeh, B.A. (2011) Relationship between general contractors and
subcontractors in the palestinian construction industry. International Journal of Project
Planning and Finance, 2, 41-65.
Enshassi, A., Arain, F., & Tayeh, B.A. (2012). Major causes of problems between contractors
and subcontractors in the Gaza Strip. Journal of Financial Management of Property and
Construction, 17(1), 92-112.
ENSHASSI, A., MOHAMED, S. & ABUSHABAN, S. (2009). Factors affecting the
performance of construction projects in the Gaza strip. Journal of Civil engineering and
Management, 15, 269-280.
FERNáNDEZ-SáNCHEZ, G. & RODRíGUEZ-LóPEZ, F. (2010). A methodology to identify
International Conference on Sustainable Infrastructure 2019
Downloaded from ascelibrary.org by University of Melbourne on 11/09/19. Copyright ASCE. For personal use only; all rights reserved.

International Conference on Sustainable Infrastructure 2019 328
© ASCE
sustainability indicators in construction project management—Application to infrastructure
projects in Spain. Ecological Indicators, 10, 1193-1201.
FLYVBJERG, B., SKAMRIS HOLM, M. K. & BUHL, S. L. (2004). What causes cost overrun
in transport infrastructure projects? Transport reviews, 24, 3-18.
FUENTES BARGUES, J. L., GONZáLEZ-CRUZ, M.-C. & GONZáLEZ-GAYA, C. (2016).
Abnormally Low Tenders in Non-pricing Criteria: the Need for Control. In: Universal
Journal of Management, 2016. Horizon Research Publishing, 659-669.
GRAMLICH, E. M. (1994). Infrastructure investment: A review essay. Journal of economic
literature, 32, 1176-1196.
HILL, R. M., REY, Y., MARIN, C. E., SHARP, C., GREEN, K. L. & PETTIT, J. W. (2015).
Evaluating the Interpersonal Needs Questionnaire: Comparison of the reliability, factor
structure, and predictive validity across five versions. Suicide and Life Threatening Behavior,
45, 302-314.
KIM, T. K. (2015). T test as a parametric statistic. Korean journal of anesthesiology, 68, 540-
546.
KROSNICK, J. A. 2018. Questionnaire design. The Palgrave Handbook of Survey Research.
Springer.
KWATSIMA, S. A. (2017). An Investigation into the Causes of Delay in Large Construction
Projects in Kenya. COETEC, JKUAT.
LI, T. H., NG, S. T. & SKITMORE, M. (2012a). Conflict or consensus: An investigation of
stakeholder concerns during the participation process of major infrastructure and construction
projects in Hong Kong. Habitat international, 36, 333-342.
LI, T. H., NG, S. T. & SKITMORE, M. (2012b). Public participation in infrastructure and
construction projects in China: From an EIA-based to a whole-cycle process. Habitat
International, 36, 47-56.
LI, T. H., NG, S. T. & SKITMORE, M. (2013). Evaluating stakeholder satisfaction during public
participation in major infrastructure and construction projects: A fuzzy approach. Automation
in construction, 29, 123-135.
MBAH, A. K. & PAOTHONG, A. (2015). Shapiro–Francia test compared to other normality test
using expected p-value. Journal of Statistical Computation and Simulation, 85, 3002-3016.
MORRIS, M. H. & CALANTONE, R. G. (1990). Four components of effective pricing.
Industrial Marketing Management, 19, 321-329.
OKE, A., IJIE, O. & AIGBAVBOA, C. (2017). Appraisal of qualitative factors affecting
contractors' tender price in a developing country.
OSHODI, O. S., EJOHWOMU, O. A., FAMAKIN, I. O. & CORTEZ, P. (2017). Comparing
univariate techniques for tender price index forecasting: Box-Jenkins and neural network
model. Construction Economics and Building, 17, 109.
ROBERTSON, M. & NEWLING, G. (2015). Stakeholder engagement and infrastructure-South
west priority growth area wastewater servicing project. Water: Journal of the Australian
Water Association, 42, 35.
SIGNOR, R., LOVE, P. E. & OLATUNJI, O. (2016). Determining overpricing in Brazilian
infrastructure projects: A forensic approach. Journal of Construction Engineering and
Management, 142, 06016001.
Tayeh, B.A., Al-Hallaq, K., & Sabha F.A. (2016). Effects of Faulty Design Phase on School
Buildings Maintenance in Gaza Strip. American Journal of Civil Engineering and
Architecture. 4(6), 199-210
International Conference on Sustainable Infrastructure 2019
Downloaded from ascelibrary.org by University of Melbourne on 11/09/19. Copyright ASCE. For personal use only; all rights reserved.

International Conference on Sustainable Infrastructure 2019 329
© ASCE
Tayeh, B.A., Al-Hallaq, K., Yusuf, M. O. & Sabha F.A. (2017). Effects of construction phase
errors on maintenance of school buildings in Gaza strip. International Journal of
Management, Information Technology and Engineering (BEST: IJMITE). 5(01), 21-34
Tayeh, O.A., El-Hallaq, K., & Tayeh, B.A. (2018). Importance of Organizational Culture for
Gaza Strip Construction Companies. International Journal of Engineering and Management
Research (IJEMR), 8(1), 35-39.
Tayeh, O.A., El-Hallaq, K., & Tayeh, B.A. (2018) The Organizational Culture of Gaza Strip
Construction Companies. Journal
International Journal of Engineering and Management
Research. 8,(01),40-64.
Tayeh, B.A., Al-Hallaq, K., Alaloul, W.S., & Kuhail, A.R. (2018). Factors Affecting the Success
of Construction Projects in Gaza Stripp. The Open Civil Engineering Journal, 12, 301-315.
Tayeh, B.A., Al-Hallaq, K., Al Faqawi, A.H., Alaloul, W.S., Kim, S.Y. (2018). Success Factors
and Barriers of Last Planner System Implementation in the Gaza Strip Construction Industry.
The Open Construction and Building Technology Journal, 12(1), 389-403
TRIZANO-HERMOSILLA, I. & ALVARADO, J. M. (2016). Best alternatives to Cronbach's
alpha reliability in realistic conditions: congeneric and asymmetrical measurements. Frontiers
in psychology, 7, 769.
URQUHART, S., WHYTE, A. & LLOYD, N. (2017). The development of a more efficient
internal tender procedure framework for Australian construction contractors. In: Proceeding
of the 33rd Annual ARCOM Conference, 2017. 693-702.
WONDIMU, P. A., HOSSEINI, A., LOHNE, J., HAILEMICHAEL, E. & LæDRE, O. (2016).
Early Contractor Involvement in Public Infrastructure Projects. In: Proc. 24th Ann. Conf. of
the Int’l. Group for Lean Construction, Boston, MA, USA, 2016. 13-22.
International Conference on Sustainable Infrastructure 2019
Downloaded from ascelibrary.org by University of Melbourne on 11/09/19. Copyright ASCE. For personal use only; all rights reserved.