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International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 9, Issue 1, Jan - Feb 2018, pp. 33–42, Article ID: IJARET_09_01_004

Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=9&IType=1

ISSN Print: 0976-6480 and ISSN Online: 0976-6499

© IAEME Publication

ESTIMATION OF CONSTRUCTION PHASE

RISK IN ROADWAYS PROJECT

Dineshkumar B

Research Scholar, Department of Civil and Structural Engineering,

Annamalai University, Tamilnadu, India

Dr. Deiveegan A

Assistant Professor, Department of Civil and Structural Engineering,


Dr. Kamal S

Assistant Professor, Department of Civil and Structural Engineering,


ABSTRACT

Risk is unavoidable in almost all road construction projects and is the biggest

challenge in construction industry as it results in time overrun, cost overrun and

degradation of quality of the project. The focus of this paper is to identifying the

impact on construction phase in the effects of occurrences of risk in the roadways

project. The questionnaire template was prepared based on a literature review and

expert’s opinion. The questionnaire was consisting of the Project details, various

factors related to causes for execution of the project. The responses of the

questionnaire survey collected from 286 projects were considered the analysis

through management tools. The descriptive analysis shows the 59 factors influence in

the roadways project and those factors grouped under 11 categories were disused.

The result of descriptive analysis shows the effect on project execution. Later, the

regression analysis was made to create a model for finding the probability of the risk

in construction phase of the roadways project. The result of study shows the project

scope, project construction management, and Regulation Social and legal risk are

having high chance of risk in construction phases. The study concludes with

appropriate suggestions and recommendations to control cost escalation in

construction projects.

Key words: Construction phase, Project Construction Management, Project Scope,

Project Regulation and Safety issue.

Cite this Article: Dineshkumar B, Dr. Deiveegan A, Dr. Kamal S, Estimation of

Construction Phase Risk in Roadways Project. International Journal of Advanced

Research in Engineering and Technology, 9(1), 2018, pp 33–42.

http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=9&IType=1

Estimation of Construction Phase Risk in Roadways Project


1. INTRODUCTION

Roadway construction is a multifaceted business involving activities from the purchase of raw

land, formation of road, laying, operating and maintaining. Roadway construction is different

from other type construction in several ways like stretch involved, confinement of area,

activities involved, etc.

Roadway construction comprises the following major phases.

Initiation and Planning phases – Field study, population study and also include the

purchase of land, formation of embankment, construction of Curvets and bridges.

Construction phases – way works – include earth cutting and embanking, spreading and

compaction of ballast, laying, placing of bitumen.

Operation and Maintenances – Includes batch work, periodical Maintenances.

Transfers phases – Includes transfers to public use and to government.

The overall complexity of the project decreases during stages of the development process,

ability to influence the project with commitment of capital declines. A high level of

uncertainty occurs in the early stages of a project and also when decisions of major impact of

project are made. The developers should consider the risks in the projects by proper analysis

and adjust the project suitably to minimize them where possible.

Risk and uncertainties are always incurred in all projects, especially in the complicated

projects. Risk can strongly influence each project level from the project conceptual design,

feasibility studies, design and planning, construction and execution, Operation and

maintenance and Transfer stage. Irrespective of the size and type of the project, roadway

construction is subjected to risk that are related to Environmental Permission, Emotional

Issue, Land Acquisition, Political, Quality, Time, Money, Machinery, Rebound development

around road analysis, Labour, Natural Obstruction, Knowledge level of lead group. The risk

arising from these factors occurs in the various stages of the project lifecycles or Phases and

they have effect on overall project. However, Subjective factors such as community or social

objection of a project has been identified as having indirect consequence on the project

progress which in turn leads to delay in completion.

Risks in roadway construction are knotted up by factors and the decisions of participants

in the project. The interaction of all these factors coupled with the wide range of variables

involved in the roadway construction process needs sophisticated risk analysis which could

also help developers to frame the decision making process in development stage (Khumpaisal

2007). The object is to establish the equation for occurrences of risk in construction phases of

road construction index by Regression analysis

2. BACKGROUND OF THE STUDY

The review of the literature begins with studies of risk in road construction and then studies of

risk in construction phase or execution phase of road construction that are brought in. From

the 1990‟s onwards there has been significant research on the risk management through the

analysis of completed and on-going projects. Most of these are dedicated to the examination

of causes and effects of risk.

Hillson (2002) proposed Risk Break down structure (RBS) in which project risks are

arranged by risk category in a hierarchical manner. Source oriented grouping of project risk

that organizes and defines total risk exposure of the project. Other benefits of RBS suck as

risk identification, risk reporting and comparison of projects.

Dineshkumar B, Dr. Deiveegan A, Dr. Kamal S


Wang, and Chou (2003) done a research on analytic procedures to recognize the risk

allocation of construction projects and investigate the influences of risk allocation to

contractors risk handling decisions. These procedures help contactors define their risk

responsibilities and made risk handling decisions more properly. Decision on risk

management strategies by contractor must be done by considering aspects such as risk

responsibilities, risk patterns, risk management capabilities, etc. This paper investigates the

effects of risk allocation and risk event conditions on contractors risk handling decisions

because owners and contractors usually have disagreements over risk responsibilities. The

owner allocates risks in a construction project by contract clauses. Contractors will not get

satisfying outcomes from risk management without a clear understanding of the risk

allocation.

Zayed et al (2008) developed levels to categorize the risks. Risk was classified into micro

level and Marco level. The micro level includes technology, construction, contract, quality,

design and resources. The macro level includes financial, cultural, political and market factor.

All the factors in both the levels were further classified to third level.

Lin et al (2011) stated that the risk management of railroad engineering is a complicated.

Simple and effective risk management is important to improve the level of railroad

engineering risk management, to reduce project‟s risk, to improve the construction quality and

to effectively control the project cost. It‟s proved that the risk management is a practical

method in the construction phase of railroad engineering.

Tang, et al (2011) proposed to take use of fuzzy ANP for carrying out evaluation on

project risks due to complexity of risks in urban rail transit project. Network analysis, as a

method combining qualitative method and quantitative method, possesses obvious advantages

on handling complex problems. Introduction of fuzzy evaluation theory can effectively handle

on risk factors which are hard to accurately describe and of unclear borders, so as to improve

effectiveness of model evolution. It is proved by example analysis results that, evaluation

method of urban rail transit based on fuzzy ANP is scientific and effective, which can provide

decision reference for project risk management.

Rezakhani (2012) has stated that construction projects potential risk was identified and

they were classified as External risk which are relatively uncontrollable

(predictable/unpredictable), Internal risk which are relatively controlled (technical/non-

technical) and Legal risk.

Odeyinka, et al (2013) researched on the risk factors affecting the construction cost flow

and ANN cost flow forecasting model has been created. The model helps the contractor to

forecast the likely changes to a cost flow profile due to risks occurring in the construction

stages.

Serpella et al, (2014) has presented on the purpose of creating a knowledge-based

approach to risk management in construction projects. The knowledge based approach enable

owners and contractors to have a more systematic and formal approach to risk management

by making use of their own knowledge and experience.

Min An, et al (2013) proposed intelligent system for railway safety risk assessment. The

relationship between the risk factors and risk level expressions represented by the fuzzy rules

are described. The fuzzy reasoning approach offers a great potential in the safety risk

modeling of railway systems, particularly, when the safety risk data are incomplete or there is

a high level of uncertainty involved in the safety risk data. Safety risk analysis by using fuzzy



reasoning approaches can formulate domain human experts‟ knowledge and engineering

judgment.

Mahendra, et al (2013) stated the risk management technique rarely used by the

participants in construction projects. The participants used to handle the risks with an

informal approach. This technique is not employed because of less knowledge and awareness

among the construction industry. The risk management technique should be applied into any

construction project at the initial stage of the project to get maximum benefit of the

techniques. Hence there is thriving need to have a well-documented procedure which should

be a one stop solution to all hazards that are likely to occur during project life cycle. There

should be wholesome approach towards risk management instead of the sporadic approach

towards the risks.

From the background study, concludes the following are the major risk occurrences

phases in the roadways project life cycle. The road construction was mainly divided in to six

phases

Initiation phase – planning and surveying stage, project proposal, initiation of project

budget and duration.

Tendering phase – agreement stage between the owners and contractors.

Finance phase- budget and cash flow in the project

Construction phase – execution phases of the project

O&M phase and- operation and maintains phase or service stage of the road.

Transfer phase – handover phase of the project to the client.

3. RESEARCH METHODOLOGY

Study includes the process of identifying effects of risk in the road construction project and

evaluates those issues using corrective scenario. This study explores the risk factors in

roadway construction and impact execution phase or construction phase of the project. To

ensure the accuracy of results it is therefore important to choose an appropriate solution. The

structured questionnaire was used to collect the data from completed project in Tamilnadu

road projects.

The preparations of questionnaire are consist based on the literature review towards risk

issues in the project. Mostly the questionnaires were asked directly so that it can predict the

impact of the problem. Initially the questionnaire were developed and circulated to engineers

who involved in those projects to provide the suggestion. Later the questionnaires were

finalized as the parts. The questionnaire survey is divided into two parts. The first part

consists of Project characteristics about project details like Location of the Project, Length of

the road, Type of Contract, Type of Road project, Type of work, Cost of the Project, Duration

of the Project in roadway projects and second part consist of various risk factors for

evaluation. However in the project details were retrieved the information related to the

completed project of respondent‟s participated in the time of execution. The roadways project

seeks responses on a five point (0 to 5), Likert scale weight age of the impact considered for

study for Severe impact (S=5), High impact (H=4), Medium impact (M=3), Low impact

(L=2), Very Low impact (VL=1), Nil (N=0).

The study adopted the systematic random sampling technique. The justification for this

technique is based on the fact that it enables every subject in the sampling frame to have equal

opportunity to be selected without bias in a systematic manner (Ogbeide 1997). The



distribution questionnaire mainly focused on type of roads to obtain the equality responses

among the issue in roadways project. Fifty nine factors are identified as the risks in the

construction projects. These factors were further grouped under eleven categories, namely,

Project Scope,

Regulation Social and legal risk

Utility Conflicts

A/E services

Environmental & Force Majeure

Construction Risk

Project Construction Management

Operation & Maintenance Risk

Commercial Risk

Transfer Risk

Financial Risk

Later, data was analysed using differential statistic, and inferential statistical analyses.

Consequently the regression procedure was used for creating a model for estimating the risk

in construction phase.

4. RESULT AND DISCUSSION

In the previous section on methodology, the approach adopted to understand the influence of

risk in the construction phase of the project. Moreover, the impacts on project due to risk were

measured to predict the probability of risk in execution phase. Those parameters will help the

organization to achieve the success in the project at early stage of project.

Fifty nine risk factors, identified as the risk factors which influence the execution of the

project. The responses of all the 286 respondents were collected and the descriptive analysis

was carried out to calculate means and mode for each one of the factors.

Table 1 Influencing factors for occurrence of Risk in roadway project

S.No Influencing factors for occurrence of Risk in roadway project Mean Mode

1 Purpose of Project is poorly defined 2.80 3

2 Changes to unforeseen site environment requirements 2.90 3

3 Change in Law & Regulation 3.25 3

4 Environmental and Clearance Pollution 3.55 4

5 Land acquisition/ compensation/ Social impact assessment 3.62 4

6 Inadequate plan reviews by designers and contractors/ design errors 3.01 3

7 Poor involvement of Contractors in Planning stage 3.04 3

8 High number of utilities in the site 3.58 4

9 Inaccuracy of existing utility locations and survey data 3.26 3

10 Poor coordination among utility agencies, designers, and contractors 3.54 4

11 Increased utility relocation costs 3.45 4

12 Poor Engineering Practice 3.32 3

13 Utility damages by contractors/subcontractors faults in Improvements 2.97 3

14 Delay in Surveys and/or surveying in error 3.27 3

15 Inexperienced professionals for this type of project 3.04 3

16 Design errors and omissions 3.62 4

17 Inadequate constructability reviews 3.45 3



18 Delay in Quality Assurance/Quality Control (QA/QC) services 3.38 3

19 Poor preliminary soil information and investigations 3.34 3

20 Unforeseen and/or different geotechnical conditions 3.15 3

21 Unforeseen hazard conditions 3.47 3

22 Inaccurate structures design 3.39 3

23 Social unrest problem 3.40 3

24 Natural calamity 3.49 3

25 Historical findings 2.86 3

26 Rebellion/ Terrorism 2.68 3

27 Poor geotechnical condition 3.30 3

28 Poor contract management/ non-performance of vendors/

subcontractors 3.07 3

29 Availability of Labour/ Material 2.98 3

30 Bad weather 3.60 4

31 Cost overrun 2.97 3

32 Time overrun 3.14 3

33 Technology Risk (Unproven tech./ design deficiency) 2.37 3

34 Poor communication with owner and contractor 3.27 3

35 Delay of permits 2.75 3

36 Constraints in Improvements work frame 3.62 4

37 Material availability and price inflation 3.71 4

38 Subcontractors errors and delays 3.15 3

39 Maintenance of traffic/staging/auxiliary lanes 3.17 3

40 Inexperienced project manager 2.89 3

41 Safety issues 3.05 4

42 Warranty issues 3.15 3

43 Unexpected/ Unforeseen deterioration 3.45 3

44 Design deficiency/ bad workmanship /low quality during

Improvements. 3.67 4

45 Tolling technology 2.82 3

46 Overloading control 3.20 3

47 Traffic/Incident management 3.43 3

48 Cost overrun Risk 3.58 4

49 No outstanding value 2.73 3

50 Transmission failure 3.00 2

51 Inflation rate instability 2.87 2

52 Interest rate instability 3.18 4

53 Financial closure risk 2.76 2

54 Poor financial market 2.31 2

55 High cost of financing Risk 2.38 2

56 Traffic/ level of demand risk 2.55 2

57 Non competing facility 2.32 2

58 Lack of demand/ slow economic development of the country 2.67 2

59 Delay by govt. notification of toll collection. 2.75 2

The following are some of the observations made from Table 1are: (i) “Material

availability and price inflation”, has a mean of 3.71 (ii) “Design deficiency/ bad workmanship

/low quality during Improvements.” has a mean of 3.67. (iii) The least mean of 2.31 was for

the reason “Poor financial market”. (iv) “Non competing facility” has a mean of 2.32. (v)

“High cost of financing Risk” also has a very low mean of 2.38. The rest of the reasons have

means higher than that of 2 or the halfway mark between the minimum of 0 and the maximum of 5,

which could be attributed to any reason. From the above table concludes that the materials

inventory, technical support and coordination among the stakeholders are most critical factors

during the execution time of road construction.

Table 1 shows the modal value for each reason is give column 4, and it could be seen that

for twelve numbers of factors respondents had given a value of 4 in the Likert scale (High



impact). The topmost factor opt by the engineers are Material availability and price inflation,

Poor coordination among utility agencies, designers, and contractors, Environmental and

Clearance Pollution, Safety issues, and Cost overrun Risk. It could be noticed that though the

modal value was 4 for these reasons, they did not have the maximum mean (Table 1), because

there were a substantial number of respondents who had denoted lower values of 0 to 2 to

these reasons, thereby bringing down the mean value which are given in the Table 1 in the

percentage of responses. Similarly the thirty seven number of factors had a maximum number

of respondents marking a value of 3 (medium impact) as their response. However the least

value was obtained for “Poor financial market”, Poor financial market and Non competing

facility has a value 2. From Table 1 concluded that material management, Technical Support

and safety are most important risk factors which influence the project.

5. REGRESSION MODEL FOR PREDICTING RISK IN

CONSTRUCTION PHASE

The regression procedure was used for creating a model for predicting the probability of risk

in construction phase. Regression is a method by which one could classify the subjects based

on a set of predictor values. The dependent variable here is continues data which generated

from the three groups such as Commercial Risk, Transfer Risk, Financial Risk. The

independent variable consider the following data, like the Project Scope, Regulation Social

and legal risk, Utility Conflicts, A/E services, Environmental & Force Majeure, Construction

Risk, Project Construction Management, Operation & Maintenance Risk which had a

significant relationship with the dependent variable, were also included in this approach. The

probability of risk in construction phase lies between zero to five. Zero denotes Nil and five

denotes Severe Impact. For the analysis, the category has been considered as „Nil‟ to „Severe

impact‟, i.e. the answer for the risk in construction phase in the project is Nil or Severe

impact.

From Table 3 gives the model summary, contains five models. Model 1 refers to the first

stage in the hierarchy when an only A/E service is use as predicators. Model 2 refers the

second stage contains A/E service and Project scope. Similarly the final model five contains

Project Scope, Project Construction Management, Regulation Social and legal risk

From Table 3, in the column two the R values of the multiple correlation coefficient

between the predictors and the outcome. When only A/E service is used as predictors, this is

the simple correlation between risk in construction phase and A/E service (0.742) in the next

column shows the R2 values. This was the measures of how much of the variability in the

outcome is accounted for by the predictors. For the first model its value is 0.551, which

means that A/E service accounts for 55.1% of the risk in construction phase. However, for the

final model (Model 5), value increase to 0.803 or 64.4% of the Risk in construction phase.

Therefore, the variables entered the model account for an extra (64.4 – 55.1) 9.3% of the risk

in construction phase.

The next column shows the adjusted R2 gave the idea of the model to generalize and ideal

values of model fitness. The difference of final model is affair (0.638 -0.548 = 0.09 or 1%).

The shrinkage means that if the model were derived from the respondents rather than sample

it would account for approximately 1% less variance in the outcome.



Table 3 Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 0.742(a) 0.551 0.548 0.38076

2 0.787(b) 0.619 0.615 0.35153

3 0.796(c) 0.633 0.627 0.34603

4 0.803(d) 0.646 0.637 0.34122

5 0.803(e) 0.644 0.638 0.34095

a Predictors: (Constant), A/E services

b Predictors: (Constant), A/E services, Project Scope

c Predictors: (Constant), A/E services, Project Scope, Project Construction Management

d Predictors: (Constant), A/E services, Project Scope, Project Construction Mgt, Regulation Social

and legal risk

e Predictors: (Constant), Project Scope, Project Construction Mgt, Regulation Social and legal risk

From Table 4 shows the Stepwise regression model output. In the regression model gives

the form of equation that contains a coefficient (B) for each predictor. The table gives the

estimates for the B values and these values indicate the individual contribution of each

predictor to the model. The B values are the relation between risk in construction phase and

each predictor. If the value is positive then the relation between the predictor and outcome is

positive and vice versa. Form Table 4, in the final model all group variables are in positive

relationship. It states that risk in construction phase was increase if all variables increase.

Table 4 Regression model for predicting risk in construction phase

Model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B Std. Error Beta

1

(Constant) 0.75 0.14 5.29 0.00

A/E services 0.62 0.04 0.74 14.70 0.00

2

(Constant) 0.75 0.13 5.72 0.00

A/E services 0.43 0.05 0.51 8.13 0.00

Project Scope 0.22 0.04 0.35 5.61 0.00

3

(Constant) 0.73 0.13 5.68 0.00

A/E services 0.23 0.09 0.27 2.48 0.01

Project Scope 0.21 0.04 0.34 5.58 0.00

Project Construction Management 0.21 0.08 0.27 2.57 0.01

4

(Constant) 0.63 0.13 4.71 0.00

A/E services 0.09 0.11 0.11 0.85 0.39

Project Scope 0.20 0.04 0.32 5.28 0.00


Regulation Social and legal risk 0.14 0.06 0.18 2.44 0.01

5

(Constant) 0.65 0.13 4.87 0.00

Project Scope 0.21 0.04 0.34 5.59 0.00


Regulation Social and legal risk 0.17 0.05 0.21 3.40 0.00

a Dependent Variable: Probability of Risk in Construction Phase

The beta (B) values has an associated standard error (column 3) indicating to what extent

these variables would vary across different and these standard error are used to determine

whether or not the B value differ significantly from zero. The column significant is less than

0.05 then the predictor is making a significant contribution to the model. For this final model

all the predictor variables are less than 0.05 and significant to risk in construction phase. From

Table 4 the project construction management had more impact than other variables.



The standardized Beta (column 4) values and their significance are important statistics to

interpret because they are not dependent on the units of measurement of the variables. The

value of Beta states that the number of standard deviation that the outcome would change as a

result of one standard deviation change in the predictor. The standardized betas values in

Table 4 shows the standard deviation and are directly comparable to provide a better insight

into the importance of a predictor in the model. The beta value for project scope (0.34),

project construction management (0.38), regulation social and legal risk (0.21) form above

value states that project construction management has more impact than the other variables.

Based on the variables having a significant value less than 0.05 (Table 4) the utility

equation for calculating the probability of risk in construction phase in the project is predicted

which is as follows:

Risk in construction phase = 0.21 x Project scope + 0.30 x Project construction

management + 0.17 x Regulation social and legal risk

+ 0.65 (1)

6. FINDING AND CONCLUSIONS

The study is about risk in construction phase in roadways projects. The effect of risk in road

projects has been recognized to have a high impact on execution of the project. This study

investigated the risk factors influencing execution of roadways construction and the

probability of risk in construction phase of the project. In view of this, the questionnaire

survey comprising the 59 identified risk factors was conducted with field experts. Then about

286 project responses are collected from Tamilnadu, India projects. All the data collected

from various engineers who worked in those projects.

The main purpose of the study is to minimise the risk in roadways project through

identifying the critical risk factors. The top risk factors scoring high mean are i. Material

availability and price inflation, ii. Design deficiency/ bad workmanship /low quality during

Improvements, iii. Constraints in Improvements work frame, iv. Design errors and omissions,

v. Land acquisition/ compensation/ Social impact assessment, vi. Poor coordination among

utility agencies, designers, and contractors.

The model was developed and suggests the equation 1 to predict the probability of risk in

construction phase of the project. However, the critical risk factors are identified and

discussed in this study. The remedies to overcome the risk in construction phase in project are

the owner/ client should arrange the proper materials vendor or systemised inventory system

in organization, consider the experience technical team to issue the proper technical support

and sort the design error in the project. Owner to need implies the proper mentors or superiors

to develop the wealthy coordination between the stakeholders.

7. RECOMMENDATION AND SUGGESTION

The following are the recommendations given to construction professionals to assess and take

proactive measures to mitigate the adverse risk in the construction phase in the roadways

construction.

Materials procurement and inventory system need to be channelized before the initiation

of the project

Planning team need to stimulate the fluctuation of prices hike of materials before the

project.



Provide the separate technical monitoring team to minimize the design deficiency, quality

and workmanship in the project.

Contractors should have a proper knowledge on design of roadways construction.

Owner should encourage the stakeholders to do the Field study and project appraisals in

detail before initiate the project.

This study provides a good tool to control the occurrence of risk in construction phase in

the project.

REFERENCES

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Cost Estimation. Journal of Construction Engineering and Management, 124(1), 18-24

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management in construction projects: a knowledge-based approach, Procedia - Social and

Behavioral Sciences, 119,653-62

[3] David Hillson, (2002), Use a risk breakdown structure (RBS) to understand your risks”,

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Antonio, Texas, USA.

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[5] Khumpaisal, S. (2007), Risks in the construction project procurement process and the

mitigation methods‖, Journal of Architectural/Planning Research and Studies, 5(2).

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Transportation Journal, 7, 27-42

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[8] Ogbeide U (1997) Statistical Techniques for Social and Management Sciences, Lagos:

Amfitop Books.

[9] Patel Ankit Mahendra , Jayeshkumar R. Pitroda , J. J. Bhavsar (2013), A Study of Risk

Management Techniques for Construction Projects in Developing Countries, International

Journal of Innovative Technology and Exploring Engineering (IJITEE), 3(5),139-142

[10] Rezakhani, P. (2012), A review of fuzzy risk assessment model for construction projects,

Slovak Journal of Civil Engineering, 20(3),35-40

[11] Wang Lin et al (2011).”Fuzzy AHP-Based Risk Assessment Methodology for PPP

project”, Journal of Construction Engineering and Management, 1205-1209

[12] Wenbin Tang, Feilian Zhang, Ze Ye, Jingjing Li,(2011), Research on Risk Evaluation in

Urban Rail Transit Project, Procedia Engineering, 15, 5094 – 5099

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https://ascelibrary.org/author/Wang%2C+Ming-Teh

https://ascelibrary.org/author/Chou%2C+Hui-Yu

https://ascelibrary.org/journal/jmenea

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