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Evaluation of the Adequacy and Utilization of Contingency Fund in Building Projects in Nigeria

Authors:
Open Access Library Journal
2016, Volume 3, e2925
ISSN Online: 2333-9721
ISSN Print: 2333-9705
DOI: 10.4236/oalib.1102925 September 28, 2016
Evaluation of the Adequacy and Utilization of
Contingency Fund in Building Projects in Nigeria
O. F. Akinradewo*, O. A. Awodele
Department of Quantity Surveying, Federal University of Technology, Akure, Nigeria
Abstract
Contingency fund is allowed in the cost estimate to cater for risks which always lead
to additional cost. The study used archival data to assess the accuracy of contingency
sum and utilization among various types of claims. Data collected were analysed u
s-
ing percentile and Pearson’s coefficient of correlation. The study reveals
that the
current allowance as contingency is 5% of the base line estimates while additional
cost is
18% which implies a shortfall of 13%. Furthermore, the study shows that the
relationship among contingencies, base line estimates and final cost is
statistically
significant at 0.01. The study concludes that using percentage in allocating conti
n-
gency base
d on subjective approach or at the discretion of the consultants is grossly
inadequate. The study recommends
that allocation of contingency sum should be
based on cost analysis of similar completed projects and that a realistic contingency
sum should be about 20% of the base line estimate.
Subject Areas
Environmental Sciences
Keywords
Additional Cost, Base Line Estimate, Contingency Fund, Final Cost and Nigeria
1. Introduction
Execution phase of construction projects involves various human activities and ma-
nipulation of series of resources in achieving the finish product. In this complex situa-
tion, an accurate cost estimate cannot be achieved at planning phase of the project.
Therefore, there is a need for contingency fund to cater for unforeseen conditions or
deviations that may occur during the construction phase of the project. [1] observed
that there was no standard definition for contingency. However, contingency has been
How to cite this paper: Akinradewo, O.F.
and O. A. Awodele, O.A.
(2016)
Evaluation
of the Adequacy and Utilization of Con-
tingency
Fund in Building Projects in
Nigeria
.
Open Access Library Journal
,
3:
e2925
.
http://dx.doi.org/10.4236/oalib.1102925
Received:
August 25, 2016
Accepted:
September 25, 2016
Published:
September 28, 2016
Copyright © 201
6 by authors and Open
Access Library Inc
.
This work is licensed under the Creative
Commons Attribution International
License (CC BY
4.0).
http://creativecommons.org/licenses/by/4.0/
Open Access
O. F. Akinradewo, O. A. Awodele
2/12
OALib Journal
defined in various ways by several authors. [2] described contingency as funds included
in project budgets to manage risk and achieve project goals. [3] defined contingency as
the amount of money needed above the estimate to reduce the risk overruns of project
objectives to a level acceptable to the organisation. [4] described contingency as an
amount the contractor was instructed to add to his tender in order to absorb or cushion
unforeseen extras. [5] observed that contingency fund was not intent to cover changes
in scope or schedule, profit, overhead, acts of God, force majeure situations and earth-
quakes.
According to [5], any serious changes to construction project budget that is not ca-
tered for by contingency fund may hamper the progress of work or even lead to aban-
donment of the project which the client never wishes. The study concludes that an as-
surance of reliable and effective construction contingency is essential to client’s satis-
faction on the final cost. [6] observed that accuracy of cost estimation was measured by
the magnitude of deviation between estimated cost of a project and its final cost. The
study also concluded that the relative percentage variance between estimated project
cost and actual project cost was expected to be less when contingency fund was in-
cluded in the base line estimate than when it was not.
Several research studies have been carried out in the area of contingency fund in Ni-
geria. Notable among them were [6], which worked on appraisal of the performance of
contingency cost provision for building projects in Nigeria; [7] which studied the effec-
tiveness of construction contingency—a statistical analysis and [8], which researched
on effectiveness of contingency sum as risk tool for construction projects in Niger
Delta, Nigeria. Some of these studies were based on questionnaire survey while the
geographical location of some of the previous studies was different from the current
area of study. This prompts a further study of contingency fund.
As a result of this, the study focuses on the evaluation of the adequacy of allowed
construction contingency fund in building projects. It went further to evaluate the
utilization of contingency fund among various types of claims. The study also reviewed
the challenges associated with the management of contingency fund. In line with the
specific objectives of the study as stated above, two null hypotheses were postulated,
which would help to determine the statistical relationship among the allowed contin-
gency fund, the base line cost estimate and final contract cost. These null hypotheses
are as follows:
Ho1: There is no significant relationship between contingency fund and base line es-
timate.
Ho2: There is no significant relationship between contingency fund and final contract
sum.
2. Challenges Associated with the Management of Contingency
Fund in Building Projects
Several studies such as [5] [9]-[12] have confirmed that contingency is not managed or
reported by project and cost managers. This is due to the challenges associated with the
O. F. Akinradewo, O. A. Awodele
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management of contingency fund. [12] and [13] submitted that the problem of incor-
porating project complexity into actual management is affecting the construction con-
tingency management. [2] also confirmed that project complexity and inherent uncer-
tainty of the financial performance of constructed facilities, development funding, con-
trol of cost and schedules make exact budget needs impossible to forecast accurately.
According to [2], contingency fund management are not organised by clearly defined
procedures compared to other managerial duties, such as estimating and scheduling.
[14] stressed the important of skills possessed by the proposed project manager in order
to handle contingency fund and the entire project effectively. These skills required in
managing contingency include communication, leadership, motivation, problem solv-
ing and negotiation. “Majority of these skills are not possessed by those who are man-
aging contingency [14]”. Another challenge is misuse of contingency fund by project
managers. Contingency fund is not intended to cover such as changes in schedule, force
majeure, profit and overhead. “However, in most cases contingency fund are used for
these additional works[10] [15]-[20].
[16] confirmed that many cost practitioners and project managers do not formally
manage construction contingency fund. [5] asserted that most contingency fund is ex-
hausted before completion of the project requiring additional fund. This has accounted
for cost overrun in construction projects in Nigeria. Another important challenge of
contingency is the way the fund is allocated in construction projects. [5] [16] [17]
[21]-[23] submitted that contingency sum is usually expressed as a percentage mark-up
on the base cost estimate. In Nigerian context, this percentage is usually based on sub-
jective or intuition approach. “This has resulted in the inadequacy of the contingency
fund as confirmed by previous studies such as [6] [7]”. [8] also argued that contingency
allowed for projects in Niger Delta area of Nigeria are based on the discretions of the
consultants and contractors, not a function of the estimated contract value and it is in-
adequate. Therefore, the challenges highlighted above needs to be addressed before a
robust and adequate contingency fund can be achieved and managed for successful
projects delivery within budgets.
3. Research Methodology
Archival data for the study was collected from 53 projects that had been completed with
their attendant construction claims in Ondo State, Nigeria. Ondo State was established
in 1976, its land area is about 15, 500 square kilometres and with population of about
3.5 million people according to 2006 census. Ondo State is an oil producing State in
Nigeria with a gross domestic product (GDP) of about $8.41. All the projects consid-
ered were constructed over a period of nine years (2006 to 2014).These comprise of 5
health services buildings; 34 institutional building projects; 2 residential buildings; 3
social services buildings; and 9 office buildings. The information collected on claims
contained the activities of both main and subcontractors. “Thirty five percent” (35%) of
the projects had more than 4 floors, while the remaining “sixty five percent” (65%) had
less than 4 floors.
O. F. Akinradewo, O. A. Awodele
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The costs of the projects ranged from 24 million to 4.1 billion. The contracts were
based on traditional system of project procurement. The assumptions made in the
study includes that (i) the type of claims used as independent variables are linearly re-
lated to the initial contract sum/completion cost, (ii) change in projects characteristics
and specifications do not materially affect the relationship between the types of claims
and initial contract sums. The data collected were analysed with percentile and Pearson
correlation using Excel and SPSS version 22 software. The base line cost estimate is the
initial or original contract sum less the amount included therein as contingency fund.
Percentile was used to compute average contingency and average claims while correla-
tion was used to calculate the relationship between contingency fund and base line es-
timate/final contract sum.
4. Results of Analysis
Table 1 show that the average contingency allowed for the projects is about 5% while
average claim is about 18%. This implies that contingency is inadequate by 13%. The
table also indicate that all the projects had cost overruns.
Table 1. Base line estimate, contingency fund, final contract sum and amount of claims in completed building projects.
S/N
Base Line Estimate
in Naira & Kobo
(
. K)
Final Contract
Sum in Naira &
Kobo (
. K)
% of Contingency/
Base Line Estimate
Amount of
Claims in Naira
& Kobo (
. K)
% of Amount of Claims/
Base Line Estimate
1 200,663,366.51 8,489,891.46 231,710,952.20 4.23 31,047,585.69 15.47
2 108,289,145.12 6,237,605.00 137,217,395.10 5.76 28,928,249.98 26.71
3 110,990,135.51 6,550,000.00 148,125,131.10 5.90 37,134,995.59 33.46
4 84,542,005.07 4,560,114.10 107,317,125.29 5.39 22,775,120.22 26.94
5 231,380,932.03 10,411,185.11 288,417,114.13 4.50 57,036,182.10 24.65
6 165,230,013.29 9,876,104.17 205,085,117.14 5.98 39,855,103.85 24.12
7 116,992,830.43 4,825,281.95 148,916,487.61 4.12 31,923,657.18 27.29
8 163,642,995.36 6,502,607.89 205,532,620.80 3.97 41,889,625.44 25.60
9 115,050,211.48 5,514,859.15 138,627,014.33 4.79 23,576,802.85 20.49
10 139,624,781.91 5,478,167.95 205,724,900.88 3.92 66,100,118.97 47.34
11 148,106,198.32 6,057,208.13 196,411,379.55 4.09 48,305,181.23 32.62
12 696,107,476.19 50,721,799.30 824,829,275.49 7.29 128,721,799.30 18.49
13 3,137,970,229.00 152,857,305.00 4,115,378,212.00 4.87 977,407,983.00 31.15
14 245,114,382.00 30,000,000.00 415,173,218.00 12.24 170,058,836.00 69.38
15 70,200,000.00 7,800,000.00 98,000,000.00 11.11 27,800,000.00 39.60
16 118,800,000.00 13,200,000.00 132,000,000.00 11.11 13,200,000.00 11.11
17 31,308,069.45 745,430.23 40,056,891.11 2.38 8,748,821.66 27.94
18 86,421,052.20 8,230,576.40 99,857,128.60 9.52 13,436,076.40 15.55
19 111,486,525.00 6,000,000.00 186,785,260.00 5.38 75,298,735.00 67.54
O. F. Akinradewo, O. A. Awodele
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OALib Journal
Continued
20 232,425,525.00 11,500,000.00 266,535,890.00 4.95 34,110,365.00 14.68
21 52,705,988.60 2,500,000.00 55,203,556.55 4.74 2,497,567.95 4.74
22 47,868,450.50 2,000,000.00 57,963,685.25 4.18 10,095,234.75 21.09
23 271,789,523.12 15,000,000.00 285,479,264.65 5.52 13,689,741.53 5.04
24 36,345,936.45 2,000,000.00 37,852,525.30 5.50 1,506,588.85 4.15
25 50,636,789.70 2,171,517.40 54,860,816.10 4.29 4,224,026.40 8.34
26 29,591,690.00 1,408,310.00 31,000,000.00 4.76 1,408,310.00 4.76
27 21,533,935.64 2,500,000.00 24,033,935.64 11.61 2,500,000.00 11.61
28 21,610,000.00 2,540,000.00 24,150,000.00 11.75 2,540,000.00 11.75
29 69,020,313.88 6,500,000.00 83,717,955.87 9.42 14,697,641.99 21.29
30 116,525,073.80 3,324,538.48 119,672,156.02 2.85 3,147,082.22 2.70
31 125,536,679.64 5,963,737.75 131,809,384.64 4.75 6,272,705.00 5.00
32 75,704,705.20 3,596,423.05 84,641,028.25 4.75 8,936,323.05 11.80
33 94,002,829.76 5,997,170.24 101,662,615.00 6.38 7,659,785.24 8.15
34 111,164,338.44 5,500,000.00 113,506,234.27 4.95 2,341,895.83 2.11
35 103,027,172.31 5,000,000.00 105,142,668.45 4.85 2,115,496.14 2.05
36 97,425,316.36 2,500,000.00 99,925,316.36 2.57 2,500,000.00 2.57
37 86,672,011.50 1,000,000.00 90,477,586.50 1.15 3,805,575.00 4.39
38 188,206,457.40 3,500,000.00 210,000,000.00 1.86 21,793,542.60 11.58
39 110,639,637.04 1,200,000.00 115,866,810.44 1.08 5,227,173.40 4.72
40 30,186,408.94 600,000.00 30,186,408.94 1.99 600,000.00 1.99
41 43,428,740.00 500,000.00 45,300,740.00 1.15 1,872,000.00 4.31
42 146,539,631.70 7,500,000.00 172,603,287.70 5.12 26,063,656.00 17.79
43 68,361,121.28 1,100,000.00 79,585,000.00 1.61 11,223,878.72 16.42
44 68,278,630.00 1,500,000.00 92,731,072.88 2.20 24,452,442.88 35.81
45 60,682,382.25 3,034,119.11 66,891,800.00 5.00 6,209,417.75 10.23
46 2,250,779,163.37 45,650,000.00 3,228,368,695.50 2.03 977,589,532.13 43.43
47 23,237,915.68 250,000.00 24,515,110.68 1.08 1,277,195.00 5.50
48 61,774,095.61 2,510,815.64 71,856,106.17 4.06 10,082,010.56 16.32
49 40,929,601.05 4,500,000.00 47,840,857.41 10.99 6,911,256.36 16.89
50 179,237,215.16 8,489,891.46 210,384,800.85 4.74 31,147,585.69 17.38
51 200,564,615.90 9,528,010.26 221,503,573.20 4.75 20,938,957.30 10.44
52 177,233,174.09 8,410,157.96 187,111,737.75 4.75 9,878,563.66 5.57
53 190,813,496.34 5,000,000.00 199,689,278.25 2.62 8,875,781.91 4.65
Grand Total
270.57
954.70
Average
5.11
18.01
O. F. Akinradewo, O. A. Awodele
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OALib Journal
Table 2 indicates that the average amount expended from the contingency fund on
contract ambiguity claims averaged (N31,433,379.46) about 54% which is the highest
while the least amount was spent on acceleration claims (N2,396,195.03) which is about
4% and no amount was spent on delay claims. It is evident from (Table 2) that five out
of the six types of claims headings used in this study should be given priority when de-
cision is to be taken on the allocation of contingency fund on similar projects in the
study area.
Table 3 presents the result correlation coefficient analysis carried out to establish the
significance of the relationship between contingency fund and base line estimate/final
contract sum. Table 3 shows that the relationship between contingency fund and base
line estimate/final contract sum were statistically significant at 0.01 level of significant.
This implies that the null hypothesis which states that there is no significant relation-
ship between contingency fund and base line estimate is rejected. This is equally true of
the second hypothesis that states that there is no significant relationship between con-
tingency fund and final contract sum. P values of 0.922 and 0.905 respectively signified
a strong positive correlation.
5. Discussion of Results
The study reveals that contingency fund is inadequate by 13%. This implies contin-
gency fund cover only 28% of approved contract claims but did not cater for 72% of
approved construction claims. This can be ascribed to uncontrollable inflation and for-
eign currency exchange rates in Nigeria. “A realistic contingency fund is about 20%
from the analysis, this finding agrees with the 15% - 20% contingency allowance previ-
Table 2. Distribution of the utilization of contingency fund among various types of claims.
Types of Claims
Average amount of claims in
naira & kobo (
. K)
Percentage
(%)
Rank
Contract ambiguity claims 31,433,379.46 54.40 1
Change claims 13,839,799.76 23.95 2
Different site Conditions claims 5,125,888.4 8.87 3
Extra works claims 4,983,336.03 8.63 4
Acceleration claims 2,396,195.28 4.15 5
Delay claims 0.00 0.00 6
Total
100.00
See Appendix 1 for the calculation of average amount of claims
Table 3. Relationship between contingency sum and base line estimate/final contract sum.
Base line estimate
Final contract sum
Contingency sum
Correlation value 0.922** 0.905**
Contingency sum
Sign (2-tailed) 0.000 0.000
**Correlation is significant at the 0.01 level (2-tailed)
O. F. Akinradewo, O. A. Awodele
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OALib Journal
ously suggested by [24] and [25]”. The result of this study also concurs with [8].
The result also indicates that contingency fund is used for five out of six types of
claims adopted in the study. Contract ambiguity top the list in the usage of contingency
fund, this may be due to inadequate time frame usually allowed by the clients for the
preparation of contract documents. Interviews with the some consultants showed that
in most cases, site investigations were not carry out prior to contract documentation.
This may be the reason for ranking change claims as second among the six types of
claims.
Finally, the result of the analysis shows that there is strong positive relationship be-
tween contingency fund and base line estimate/final project cost. This agreed with [26]
that concluded realistic contingency fund must serve as the basis for decision making
concerning financial viability of the variations and a base line for their control.
6. Conclusions
The following conclusions have been drawn from the results of the analysis.
1) The contingency sum allowed for building contracts is inadequate to cater for con-
struction claims. This suggests that there is significant room for improvement in the
method of allocating contingency through subjective or intuition approach in the
study area.
2) The study reveals that contingency is used mostly for projects with contract ambi-
guity claims. This implies that these claim heads should be considered as part of the
likely risks and uncertainties in allocating contingency fund.
3) The study shows that there is significant relationship between contingency fund and
base line estimate/final contract cost. This implies that accurate prediction of con-
tingency will be required to reduce cost overrun.
7. Recommendations
Based on the aforementioned findings, the following recommendations are made:
1) The calculation of contingency should be based on accurate cost analysis of similar
completed projects with due consideration of design risks associated with the new
contract so as to accommodate other factors that can lead to claims.
2) A realistic contingency should be 20% of the base line estimate in order to ensure
that the building projects are executed within budget.
3) The provisions of the conditions of contract concerning the preparation final ac-
count should be amended to make it mandatory for the Quantity Surveyors to re-
view and report contingency fund in building projects. This type of report will stand
as lesson learnt from previous project which other can take a cue from in a similar
situation.
References
[1] Moselhi, O. (1997) Risk Assessment and Contingency Estimating.
AACE Transactions
,
Dallas, 13-16 July 1997, D&RM/A 06.
O. F. Akinradewo, O. A. Awodele
8/12
OALib Journal
[2] Ford, D.N. (2002) Achieving Multiple Project Objectives through Contingency Manage-
ment.
Journal of Construction Engineering and Management
, 128, 30-39.
http://dx.doi.org/10.1061/(ASCE)0733-9364(2002)128:1(30)
[3] PMI (2000) A Guide to the Project Management Body of Knowledge. Project Management
Institute, Upper Darby.
[4] Kirkham, C.R. (2007) Ferry and Brandon’s Cost Planning of Building. 8th Edition, Black-
well Publishing, Oxford.
[5] Bello, W.A. and Odusami, K.T. (2013) Weak Management of the Predictability of Contin-
gency Allowance in Construction Projects in Nigeria. In: Smith, S.D. and Ahiaga Dagbui,
D.D., Eds.,
Proceedings of
29
th Annual ARCOM Conference
, Association of Researchers in
Construction Management, Reading, 2-4 September 2013, 969-978.
[6] Musa, M.M., Zubairu, I.K. and Bala, K. (2011) Appraisal of the Performance of Contin-
gency Cost Provision for Building Projects in Nigeria.
Journal of Environmental Technol-
ogy
,
4, 41-48.
[7] Bello, W.A and Odusami K.T. (2012) The Effectiveness of Construction Contingency in
Contract Delivery in Nigeria. In: Kashiwagi, D., Ed.,
Proceedings of the Construction and
Building Research Conference of the Royal Institution of Chartered Surveyors RICS
COBRA
2012
,
Las Vegas, 10-13 September 2012, 1627-1636.
[8] Otali, M. and Odesola, I.A. (2014) Effectiveness Evaluation of Contingency Sum as a Risk
Management Tool for Construction Projects in Niger Delta Nigeria.
Ethiopian Journal of
Environmental Studies & Management
, 7, 588-598. http://dx.doi.org/10.4314/ejesm.v7i6.1
[9] Rowe, J.F. (2006) A Construction Cost Contingency Tracking System (CTS).
Cost Engi-
neering
, 48, 31-37.
[10] Baccarini, D. (2005) Understanding Project Cost Contingency: A Survey
. Proceedings of
the Queensland University of Technology Research Week
, Brisbane, 4-8 July 2005, ID:
20855.
[11] Hogg, K. (2003) The Role of Quantity Surveying Profession in Accommodating Client Risk.
Journal of Financial Management of Property and Construction
, 8, 49-56.
[12] Sterman, J.D. (1994) Learning in about Complex Systems.
System Dynamics Review
, 10,
291-330. http://dx.doi.org/10.1002/sdr.4260100214
[13] Simon, H. (1995) The Sciences of the Artificial. MIT Press, Cambridge.
[14] Odusami, K.T. (2002) Perceptions of Construction Professionals Concerning Important
Skills of Effective Project Leaders.
Journal of Management in Engineering
, 18, 61-67.
http://dx.doi.org/10.1061/(ASCE)0742-597X(2002)18:2(61)
[15] Ahmad. I. (1992) Contingency Allocation: A Computer-Aided Approach.
AACE transac-
tion
, Orlando, 28th June-1st July 1992, F. 5. 1-7.
[16] Touran, A. (1993) Probabilistic Cost Estimating with Subjective Correlations.
Journal of
Construction Engineering and Management
, 119, 58-71.
http://dx.doi.org/10.1061/(ASCE)0733-9364(1993)119:1(58)
[17] Baccarini, D. (2004) ACCURACY in Estimating Project Cost Construction Contin-
gencyA Statistical Analysis.
Proceedings of the Construction and Building Research
Conference of RICS
, Leeds, 7-8 September 2004, 7-8.
[18] Parsons Jr., E.L. (1999) Waste Management Project Contingency Analysis. US Department
of Energy, Federal Energy Technology Centre. Morgantown, West Virginia.
http://dx.doi.org/10.2172/10667
[19] Stevenson Jr., J.J. (1984) Determining Meaningful Estimate Contingency.
Cost Engineering
,
O. F. Akinradewo, O. A. Awodele
9/12
OALib Journal
26, 35-41.
[20] PMI (Project Management Institute) (2004) A Guide to the Project Management Body of
Knowledge. 3rd Edition, PMI, Newtown Square.
[21] Picken, D.H. and Mak, S. (2001) Risk Analysis in Cost Planning and Its Effect on Efficiency
in Capital Cost Budgeting.
Logistics Information Management
, 14, 318-329.
http://dx.doi.org/10.1108/EUM0000000006244
[22] Mak, S., Wong, J. and Picken, D. (1998) The Effect on Contingency Allowances of Using
Risk Analysis in Capital Cost Estimating: A Hong Kong Case Study.
Construction Man-
agement and Economics
, 16, 615-619. http://dx.doi.org/10.1080/014461998371917
[23] Asamoah, O.R. (2008) Determining and Monitoring of Project Contingency Sum for
Building Developments in Ghana. A Case Study in Ashanti and Greater Accra Regions. An
Unpublished MSc Thesis Submitted to the Department of Building Technology, Faculty of
Environmental and Developmental Studies.
[24] Aibinu, A.A. and Jagboro, G.O. (2002) The Effects of Construction Delays on Project De-
livery in the Nigerian Construction Industry.
International Journal of Project Management
,
20, 593-599. http://dx.doi.org/10.1016/S0263-7863(02)00028-5
[25] Omoregie, A. and Radford, D. (2006) Infrastructure Delay and Cost Escalations Causes and
Effects in Nigeria. De Montford University, School of Architecture, Leicester LE 19BH
England.
[26] Akinsola, A.O. (1996) Neural Networks, Model for Predicting Building Projects’ Contin-
gency Allowance.
Proceeding of Association of Reseachers in Construction Management
(
ARCOM Conference
), Sheffield Hallam University, 11-13 September 1996, 507-516.
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... The method is deemed to be arbitrary and undefendable (Thompson and Perry, 1992), unscientific (Chen and Hartman, 2000), and implies a degree of certainty that is not justified (Mak et al., 1998). Multiple studies have demonstrated that subjective judgments and arbitrary decisions on the amount of cost contingency are inefficient and imprecise (Akinradewo and Awodele, 2016). Despite the weaknesses of this approach, it is the most famous and used method in practice (Baccarini, 2005;Asamoah et al., 2013). ...
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