India is a developing country and in the recent years there has been a rapid economic growth. This growth has resulted in the need for well established Infrastructure development and investment.Strong Infrastructure facilities form the backbone on nation’s economy. However the ability of the current Infrastructure sectors to keep up with the fast expansion has been constrained by the availability of investment. Indian Government has shown keen interest on improving the standards of its Infrastructure sectors by promoting active participation of private involvement in many large scale Infrastructure projects.

1. Risk Analysis of Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
www.iaeme.com/ijciet.asp 108 editor@iaeme.com
*P.G student, Department of Civil Engineering, CEG, Anna University, Chennai.
ABSTRACT
India is a developing country and in the recent years there has been a rapid economic growth.
This growth has resulted in the need for well established Infrastructure development and investment.
Strong Infrastructure facilities form the backbone on nation’s economy. However the ability of the
current Infrastructure sectors to keep up with the fast expansion has been constrained by the
availability of investment. Indian Government has shown keen interest on improving the standards of
its Infrastructure sectors by promoting active participation of private involvement in many large
scale Infrastructure projects. Public Private Partnership are increasingly becoming the preferred
mode for construction and operation of commercially viable Infrastructure projects by effective
combination of private and public investment. Interviews were conducted to investigate the risk in
such projects. The data collected are analyzed with SPSS software. A fuzzy logic model is developed
and validated to quantify the risk occurring in infrastructure projects under public private
partnerships. This model will provide the concessionaire and the government authority about the
detailed analysis of risk in such infrastructure projects; finally some recommendations and
suggestions will be given to the construction industry.
Key words: Infrastructure Projects, Public Private Partnerships, Risk, Statistical Software and Fuzzy
Logic
I. INTRODUCTION
The term Infrastructure projects refers to the technical structures that support a society, such
as roads, bridges, water supply, sewers, electrical grids, telecommunications, and can be defined as
the physical components of interrelated systems providing commodities and services essential to
enable, sustain, or enhance social living conditions of peoples.
A Public Private Partnership is an agreement between a public agency (central or state) and a
private sector in a contractual manner. It involves bringing in creative skills and management
efficiency from business practice and reducing government risk involvement in the provision of
public services by using private companies. Public Private Partnerships can provide services or
infrastructure in a cost-effective manner by putting together the strengths of both the public and
private sectors. In several parts of the world, Public Private Partnership arrangements have been
RISK ANALYSIS OF INFRASTRUCTURE PROJECTS
UNDER PUBLIC PRIVATE PARTNERSHIPS
M.A.Ravindhar Raja*
Volume 6, Issue 6, June (2015), Pp. 108-113
Article ID: 20320150606011
International Journal of Civil Engineering and Technology (IJCIET)
© IAEME: www.iaeme.com/Ijciet.asp
ISSN 0976 – 6308 (Print)
ISSN 0976 – 6316 (Online)
IJCIET
© I A E M E

2. Risk Analysis of Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
www.iaeme.com/ijciet.asp 109 editor@iaeme.com
extensively utilized and have been considerably accepted. Sector wise Investments in Infrastructure
projects are shown in Table 1. At least 110 infrastructure projects in India have been delayed in the
past due to regulatory hurdles, resulting in cost overruns of more than Rs 1.57 lakh crores. This
project is concentrated on risk analysis of infrastructure projects under Public Private Partnerships
and suggesting suitable solutions.
Table 1.Sector wise Investments in Infrastructure projects
Fig 1 shows the Investments made by Central, State and Private sectors in Infrastructure projects
Fig 1.Investments in Infrastructure projects
II. BACKGROUND STUDY
Literature reviews of research work published over the last five years were taken to study.
According to Yelin Xu et al (2010), government intervention and corruption may be the major
hurdles to the success of PPP highway projects in China.
According to Hiren M Maniar (2011), it is crucial for foreign investors to identify and
manage the critical risks associated with the infrastructure project investment. Questionnaire survey
is conducted and the data are analyzed using six degrees of rating system for the criticality of risk
and the effectiveness of mitigation measures. It is concluded by developing risk management
framework for Build Operate Transfer infrastructure project.
According to Heather Jones et al (2012), cost benefit analysis is a major evaluation tool for
infrastructure investments. Residual value is an important component of cost benefit analysis. It
Sector wise investments Rs in Thousand Crores Share in %
Electricity 1820.29 32.7
Roads and bridges 914.54 16.4
Telecommunications 943.90 16.9
Railways 643.38 11.5
Irrigation 504.37 9.1
Water supply and sanitation 255.32 4.6
Harbor and ports 197.78 3.5
Airports 87.71 1.6
Storage 148.93 2.7
Oil and gas pipelines 58.44 1.0
Total 5574.66 100%
3.5
8.6
16
3
6.8
12.9
1.9
8.8
26.8
0
5
10
15
20
25
30
Tenth Eleventh Twelfth
RsinLakhCrores
Five Year Plans
Central
State
Private

3. Risk Analysis of Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
www.iaeme.com/ijciet.asp 110 editor@iaeme.com
concluded accurate residual value helps to allocate resources efficiently in cost benefit analysis and
to improve use of scarce financial resources in the project.
According to Anil Kumar Gupta et al (2013), risk in Build Operate Transfer project rise up as
project progresses and the project faces highest risk during its construction phase. It is suggested to
setup a regulator to the road projects for suggesting measures.
According to Khaldi Almarri and Paul Blackwell (2014), success of Public Private
Partnership projects is mainly depends on contracts to allow a hybrid structure for a level of
flexibility to survive contingencies and to improve the risk simulation approach in investment
appraisal process through improving the type and quality of input variables.
III. OBJECTIVES OF THE STUDY
The main objectives of the study are
• To study the various infrastructure ongoing and completed projects under Public Private
Partnership.
• To study the various stages of infrastructure projects under Public Private Partnership.
• To identify risk in the infrastructure projects under Public Private Partnership and assess the
severity of the risk using fuzzy logic.
• Provide a valuable tool to the Project managers in understanding the level of influence of each
identified risk in order to reduce the project time and cost and suggesting measures to
overcome it.
IV. RESEARCH METHODOLOGY
The questionnaire preparation began with a review of relevant materials from journals and
industrial experts. Finally questionnaire template is prepared comprising two components. First part
consists of demographic details, company details and project details. Second part consists of 4
Critical Risk Group (CRG) with 22 Critical Risk Factors (CRF) causing risk in Public Private
Partnership projects. The survey is planned to conduct with government officials and various
construction companies. Questionnaires are sent to various respondents designations such as project
manager, project engineer, assistant engineer and concessionaire to get the most valuable opinions.
The survey is conducted by asking the field experts to rate the 22 Critical Risk Factors on
five point scale. Data were collected from different experts in public private partnership projects.
The scale ratings are as follows very low, low, moderate, high, and very high. Data were analyzed
using statistical tool and factors were measured and ranked using mean impact index. Finally results
are obtained from fuzzy model and suitable recommendations will be given.
V. RESULTS AND DISCUSSION
Mean impact of various risks under public private partnerships projects are shown in Fig 2.
Preliminary results show that land acquisition and compensation is a high risk factor with a mean
impact of 3.75 from analysis of 40 samples. Meanwhile, construction risk group is the highest
critical risk group it contributes about 43% of overall risk which affects the successful completion of
the infrastructure projects under Public Private Partnerships. Comparison of Major risks based on
funding to the project is shown in Table 2
Fuzzy logic refers to a logical system that generalizes classical two-valued logic for
reasoning under uncertainty. Fuzzy set theory generalizes classical set theory to allow partial

4. Risk Analysis of Infrastructure Projects Under Public Private Partnerships
Raja, M.Gayathri, G.M.Samuel Knight
www.jifactor.com
www.iaeme.com/ijciet.asp
memberships. A fuzzy set is a set with smooth boundary ranging from 0 to1. A membership function
is a curve that defines how degree of membership is mapped to a membership value between 0 and 1.
Fig 2. Results of Mean Impact factor (risk impact)
Table 2.Comparison of Major risks based on funding
Funding Public Sector
1 Construction Risk
2
Operation and
Maintenance Risk
3 Force Majeure Risk
4 Design Risk
5
Regulatory and
Administration Risk
The only condition a membership function must really satisfy is that it must vary between 0
and 1. The fuzzy average aggregate method is used to determine the mean of evaluator opinions by
using Triangular Average Formula. The fuzzy weighted average is com
in Fig 3.
10%
10%
10%
10%
9%
f Infrastructure Projects Under Public Private Partnerships
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated
111
A fuzzy set is a set with smooth boundary ranging from 0 to1. A membership function
is a curve that defines how degree of membership is mapped to a membership value between 0 and 1.
Results of Mean Impact factor (risk impact)
Comparison of Major risks based on funding
Public Sector Private Sector Both Public & Private
Construction Risk Approvals Risk Construction Risk
Operation and
Maintenance Risk
Land Acquisition and
Compensation
Operation and
Maintenance Risk
Force Majeure Risk Construction Risk Social and Legal Risk
Design Risk Time Overrun Risk Environmental Risk
Regulatory and
Administration Risk
Operation and
Maintenance Risk
Time Overrun Risk
The only condition a membership function must really satisfy is that it must vary between 0
and 1. The fuzzy average aggregate method is used to determine the mean of evaluator opinions by
using Triangular Average Formula. The fuzzy weighted average is computed and results are
11%
11%
10%
10%10%
9%
Construction Risk
Approvals Risk
Land Acquisition and
Compensation
Operation and Maintenance
Risk
Time Overrun Risk
Force Majeure Risk
Financial Risk
Environmental Risk
Design Risk
Social and Legal Risk
f Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
editor@iaeme.com
A fuzzy set is a set with smooth boundary ranging from 0 to1. A membership function
is a curve that defines how degree of membership is mapped to a membership value between 0 and 1.
Both Public & Private
Construction Risk
Operation and
Maintenance Risk
Social and Legal Risk
Environmental Risk
Time Overrun Risk
The only condition a membership function must really satisfy is that it must vary between 0
and 1. The fuzzy average aggregate method is used to determine the mean of evaluator opinions by
puted and results are shown
Construction Risk
Approvals Risk
Land Acquisition and
Compensation
Operation and Maintenance
Time Overrun Risk
Force Majeure Risk
Financial Risk
Environmental Risk
Social and Legal Risk

5. Risk Analysis of Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
www.iaeme.com/ijciet.asp 112 editor@iaeme.com
Fig 3. Triangular Fuzzy Values
A Euclidean distance formula is used for mapping the resultant fuzzy intervals back to
linguistic terms. Table 3 shows the results from the Euclidean distance formula.
Table 3.Results from the Euclidean distance formula
Risk Rating Values Range
Very Low 0.8815 (0-0.25)
Low 0.5694 (0-0.5)
Moderate 0.1379 (0.25-0.75)
High 0.2976 (0.5-1)
Very High 0.6137 (0.75-1)
The closest Euclidean distance is 0.5694 which means that the risk in Public Private
Partnership projects is considered as Low.
VI. SUMMARY
This paper discussed a review of literatures over past 5 years on risk impact of infrastructure
projects under public private partnerships. It mainly focused on the development of models for
assessing the risk impact factors in infrastructure projects. The findings of the review are presented
above. An extensive literature survey revealed that the researchers have shown a remarkable
contribution towards public private partnerships projects mainly in developed countries. In India,
only few researcher works have been done in this area. This paper concentrates on analysis of
infrastructure projects under Public Private Partnerships in Tamilnadu. Preliminary analysis was
carried out using statistical package for social science and with their results fuzzy logic model was
created. Results from the fuzzy logic model shows that the risk in carrying out public private
partnerships projects is low and hence public private partnerships can be used successfully to carry
out infrastructural projects in Tamilnadu. Finally the suitable recommendations are to be suggested,
to mitigate the risk during the various stages of infrastructure project under public private
partnerships.
0.8118, 0
0.594, 1
0.3299, 0
0
1
0 0.2 0.4 0.6 0.8 1
MembershipValues
Likelihood/Severity
Triangular
Fuzzy

6. Risk Analysis of Infrastructure Projects Under Public Private Partnerships, M.A.Ravindhar
Raja, M.Gayathri, G.M.Samuel Knight, Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
www.iaeme.com/ijciet.asp 113 editor@iaeme.com
REFERENCES
1. Anil Kumar Gupta, M.K. Trivedi and R. Kansal (2013), “Risk Variation Assessment of
Indian Road PPP Projects”, International Journal of Science, Environment and Technology,
Vol. 2, pp. 1017 -1026.
2. Ashish P. Waghmare and S.S.Pimplikar (2012), “Financial Analysis of Infrastructure project
– A Case Study on Built – Operate – Transfer Project in India”, International Journal of
Engineering and Advanced Technology, Vol. 1, pp. 193-200.
3. Harun al-Rasyid Lubis and Nik Nasir Majid (2013), “Developing a Standardized Assessment
for PPP Infrastructure Project”, Proceedings of the Eastern Asia Society for Transportation
Studies, Vol. 9, pp. 345-378.
4. Heather Jones, Filipe Moura, Tiago Domingos (2012), “Transport infrastructure Project
evaluation using cost-benefit analysis”, Procedia Social and Behavioral Science, Vol. 111,
pp. 400-409.
5. Hiren M Maniar (2010), “A case study on risk analysis in Infrastructure Highway Projects in
India”, The IUP Journal of Financial Risk Management, Vol. 2, pp. 1-27.
6. Khalid Almarri and Paul Blackwell (2014), “Improving risk sharing and Investment appraisal
for PPP procurement success in large green projects”, Procedia Social and Behavioral
Sciences, Vol. 119, pp. 847 - 856.
7. Mahalingam A (2010), “PPP Experiences in Indian Cities; Barriers, Enablers and the Way
Forward”, Journal of Construction Engineering and Management, American Society of Civil
Engineers, Vol. 136, No.4, pp. 419-429.
8. Marques, R. and Berg, S. (2011), “Risks, Contracts and Private-Sector Participation in
Infrastructure”, Journal of Construction Engineering and Management, American Society of
Civil Engineers, Vol. 137, No.11, pp.925-932.
9. Matteo Rossi and Renato Civitillo (2014), “Public Private Partnership: A General Overview
in Italy”, Journal of Social and Behavioral Science, Vol. 109, pp.140-149.
10. Suharman Hamizah, Sakthi A Sasmita, Tri Harianto, Saleh M Pallu (2014), “Private
Involvement in Sustainable Management of Indonesia Port; Need and Strategy with PPP
Scheme”, Journal of Procedia Environmental Science, Vol. 20, pp. 187-196.
11. Xueqing Zhang and Shu Chen (2012), “A systematic framework for Infrastructure
development through public private partnerships”, International Association of Traffic and
Social Science Research, Vol. 36, pp. 88-97.
12. Yelin Xu, John F.Y. Yeung, Albert P.C. Chan, Daniel W.M. Chan, Shou Qing Wang,
Yongjian Ke (2010), “Developing a risk assessment model for PPP projects in China - A
fuzzy synthetic evaluation approach”, Journal of automation in construction, Volume 19, pp.
929-943.
13. Ms. Ashly Babu and Dr. S. Kanchana, “Role of Insurance In Construction and Infrastructure
Projects” International Journal of Civil Engineering & Technology (IJCIET), Volume 5,
Issue 12, 2014, pp. 206 - 210, ISSN Print: 0976 – 6308, ISSN Online: 0976 – 6316.
14. Dr. Ibrahim Abed Mohammed, Dr. Faiq Mohammed Sarhan and Duha Sameer, “Evaluation
The Performance of The Infrastructure Project Using Earned Value Management”
International Journal of Civil Engineering & Technology (IJCIET), Volume 5, Issue 9, 2014,
pp. 145 - 155, ISSN Print: 0976 – 6308, ISSN Online: 0976 – 6316.