Comparison of Environmental and Political Risks in Two Highway Projects
K. Srinivas1, Prof. Y. S. Kiranmayi2
1Assistant Professor, NICMAR, Hyderabad.
2Head, Department of Management, Dr. B. R. Ambedkar Open University, Hyderabad
*Corresponding Author Email: k_Srinivas@nicmar.ac.in, kiranmayi.ys@gmail.com
ABSTRACT:
Construction industry as such is prone to risks and more so, infrastructure projects. Risk Management is becoming an increasingly challenging activity. Risk is defined as that variable, the occurrence of which has an adverse impact on the project in terms of time and cost overrun and in the process losing the track of the objectives of the project. Managing risks is a strategic tool for reaping the full benefits of the critical initiatives that are implemented in any organization. Organizations which implement good risk management practices tend to extract the maximum advantage. Application of risk informed approach to any infrastructure project is still in its infancy as far as India is concerned. Considering this aspect in mind, a study was conducted on two road projects i.e 1)Moradabad-Bareilly project 2)Yamuna Express way (connecting Noida and Agra) both of which are in the state of Uttar Pradesh.. This study was carried out for the selected projects by considering 5 factors each for Environmental and Political risks. Risk Severity Index (RSI) was calculated for each of the 5 risk factors. The standard deviation and coefficient of variation (CV) for each of the identified factors for both the risks were calculated. Based on the RSI, Anova analysis was carried out which significantly indicated that the risks were better managed in the second project as compared to the first project.
KEYWORDS: Risk Management, Risk Severity Index, Environmental risk, Political Risk.
INTRODUCTION:
Construction industry right from the initial investment appraisal to commissioning of project is subjected to risks which needs to be managed by the stakeholders concerned. In recent times, the nature, incident and impact of risk in construction industry has become a topic of interest because of its effects on quality, time and cost of construction projects ( Ojo, 2010,Windap et al 2010 and Joshua 2010) Risk is important to stakeholders i.e Contractors, Clients and Consultants within the construction industry. Construction activities are subjected to plethora of risks which have to be considered by the management if they are to achieve their objectives. As per Project Management Institute (PMI, 1996) “Risk is uncertainty and result of the uncertainty or lack of predictability about structure, outcome or consequences in a planning or decision situation”. Risk management is defined as “entire set of activities and measures that are aimed at dealing with risks in order to maintain control over the project” Construction risk management is the process of identifying, analyzing and mitigating the risks in the project by proper response (PMI,2003).According to www.antive.net(2012),project risk management involves risk identification, risk analysis, creating a risk response action plan, monitoring and controlling of risks in a project. An infrastructure project by its very nature is subjected to barrage of risks and hence the effect of risks on cost and time is substantial. This study is confined to a two highway projects in state of Uttar Pradesh by considering environmental and political risks. Based on the RSI, Anova analysis was carried out to find the effect of both these risks on the both the projects
LITERATURE SURVEY:
Anil Kumar Gupta1 and others in their study on Risk variation assessment of Indian road PPP projects have concluded setting up of a regulator for road projects which would oversee the fast changing overall Socio-economic environment and suggested means to lessen the risk and create win-win situation for all stake holders. .Ahmed et al2 (1999) in his study has concluded that complexities of projects, locations and type of contracts are significant contributors to risk in construction projects Al-Bahar and Crandall3 on systematic risk management approach for construction projects have concluded that brainstorming sessions and analysis of historical data of similar projects were found to be the most preferred methods of risk identification in construction industry and that formal risk management process is used infrequently. Baloi and Price4 did a modeling study on global risk factors affecting the cost performance in construction projects and have concluded that there is need to incorporate global risk factors in any project for effective project mitigation Florence and Londa5 in their study have concluded that every infrastructure project is subjected to multiple risks and it is the responsibility of promoter to promoter to mitigate the risks by having a strong management team and a comprehensive risk management should be conducted and mitigation plan be prepared for ensuing the success of project Ijigah Edoka Augustine and others6 in their study on risk management practices in Nigerian construction industry have concluded that risks are not properly managed and that there is need for strategy to reduce the risks by way of formulation of effective risk management index. Kansal and Manoj Sharma7 in their study on risk assessment methods and application in construction have concluded that various methods of risk assessment like brainstorming, checklist, delphi method and risk significant index methods are used and each method has its own limitation and that risk assessment methods can be integrated for applying risk management effectively. Martina Claudia Garrido and others8 in their study have concluded that formal risk identification and application techniques in Brazilian construction industry is rarely used and that more informal methods are applied for risk identification. Mohammed. F. Diab and others9 in their study on Risk assessment to improve the highway construction project performance have concluded that use of risk management tolls and techniques in the reported projects has improved the project and construction management practices. Nerija Banaitiene and Audrius Babaitis10 have concluded that risk management is the core of project management and that success of any project depends on how effectively uncertainties are handled, complete absence of formal risk management techniques in construction industry and joint venture tool is widely used for risk transfer.. Rasheed Adavale11 and others in their paper on review of Risk assessment models for highway construction projects have concluded that one and two dimension modeling approach is grossly inadequate and have developed a “RM 3 method” which will identify areas of weakness and strength of shareholders on projects and will enhance decision on risk response planning. Sameh.M.El-Sayegh12 and others on their paper on Risk assessment and allocation in highway construction projects in UAE have concluded by recommending suitable allocation of risks and that risks need to be estimated and proper risk mitigation measures to be framed prior to commencement of projects Shehu and Sommerville13 have stressed that construction is a risk prone industry with poor track record of coping with risks as a result of which clients are not able to reap full benefits of their investment. Shen LY and others14 in their study on risk assessment for construction joint ventures in china have observed that risk transfer is an effective tool for mitigating the risks in infrastructure projects. Yukiya Sato and others15 in their study on Quantitative risk analysis of road projects in Japan based on empirical data have concluded the necessity to conduct risk analysis based on appropriate types of distribution and application of simulation methods for quantification of risks to a certain extent.
RESEARCH METHODOLOGY:
NH-24 is an important highway connecting New Delhi with Lucknow passing through the cities of Moradabad, Rampur, Bareilly, Sitapur etc. The present study pertains to the 114 km long Moradabad- Bareilly section of the four lane highway which was built on Design, Build, Finance, Operate basis (DBFO). Yamuna expressway which is 165 km long connects Greater Noida with Agra and has reduced the travel time between the two cities considerably. A study was conducted by taking 5 factors each for political and environmental risks for both the projects by administering the questionnaire containing 4 questions for each factor to 100 respondents in each of the projects. The distribution of questionnaire to respondents is as follows: Senior Executive-10, Middle level Executive-15, Junior Engineer-35, Works Supervisor-40. The response received from the projects was 65 and 55 respectively. The respondents were asked to rate the severity of the each of the factors that were identified for political and environmental risks on a scale of 1-5. The severity of the risk was classified as follows:
Table-1
|
Scale of risk |
Severity of risk |
|
1 |
Insignificant |
|
2 |
Fairly significant |
|
3 |
Significant |
|
4 |
critical |
|
5 |
Catastrophic |
The responses were subjected to ANOVA to find out whether there was any significant difference of means of severity between the projects and also the coefficient of variation and also standard deviation was calculated.
Analysis:
Table- 2 Assessment of Environmental risk drivers for Moradabad- Bareilly highway
|
Sl. No |
Risk Indicators |
Degree of severity quoted by respondents |
Score |
RSI |
Standard deviation (SD) |
Rank as per SD |
CV |
||||
|
|
|
5 |
4 |
3 |
2 |
1 |
|
|
|
|
|
|
1 |
Resettlement and Rehabilitation |
20 |
25 |
10 |
8 |
2 |
248 |
3.815 |
8.342 |
II |
0.641692 |
|
2 |
Ecological damages in the vicinity of site |
15 |
20 |
12 |
10 |
8 |
219 |
3.369 |
4.195 |
IV |
0.322692 |
|
3 |
Ground water/Surface water/pollution |
17 |
15 |
13 |
13 |
7 |
217 |
3.338 |
3.346 |
V |
0.257385 |
|
4 |
Air Pollution |
25 |
20 |
11 |
7 |
2 |
254 |
3.907 |
8.414 |
I |
0.647231 |
|
5 |
Soil pollution |
13 |
17 |
18 |
11 |
6 |
215 |
3.307 |
4.335 |
III |
0.333462 |
Table-3 Assessment of Environmental risk drivers for Yamuna Expressway
|
Sl. No |
Risk Indicators |
Degree of severity quoted by respondents |
Score |
RSI |
Standard deviation |
Rank as per SD |
CV |
||||
|
|
|
5 |
4 |
3 |
2 |
1 |
|
|
|
|
|
|
1 |
Resettlement and Rehabilitation |
15 |
20 |
8 |
7 |
5 |
198 |
3.6 |
6.284 |
II |
05713 |
|
2 |
Ecological damages in the vicinity of site |
12 |
15 |
13 |
8 |
7 |
182 |
3.309 |
3.391 |
V |
0.3082 |
|
3 |
Ground Water/Surface Water pollution |
15 |
10 |
12 |
10 |
8 |
179 |
3.254 |
2.645 |
IV |
0.2405 |
|
4 |
Air Pollution |
18 |
15 |
13 |
7 |
2 |
205 |
3.7272 |
6.442 |
I |
0.5856 |
|
5 |
Soil pollution |
13 |
14 |
12 |
10 |
6 |
183 |
3.327 |
3.162 |
III |
0.2874 |
ANOVA analysis was carried out for finding the impact of Environmental risk for both the projects by taking the Risk Severity Index and by making assumptions as follows:
Null Hypothesis:
There is no variation in difference of means between the projects i.e there is no significant effect of this risk on the projects
Alternate hypothesis:
There is significant effect of this risk on both the projects
Table-4
|
ANOVA: Single Factor |
||||||
|
SUMMARY |
||||||
|
Groups |
Count |
Sum |
Average |
Variance |
||
|
Column 1 |
5 |
17.736 |
3.5472 |
0.083597 |
||
|
Column 2 |
5 |
17.2172 |
3.44344 |
0.043138 |
||
|
ANOVA |
||||||
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
0.026915 |
1 |
0.026915 |
0.42475 |
0.532848 |
5.317655 |
|
Within Groups |
0.506939 |
8 |
0.063367 |
|||
|
Total |
0.533855 |
9 |
|
|
|
|
The value of F being less than F (critical), hence alternate hypothesis is rejected . This means that effect of environmental risk on the projects is not significant.
Table-5 Analysis of both the project based on Coefficient of Variation ( CV)
|
Sl. No |
Risk Indicators |
CV of Moradabad-Bareilly project |
CV of Yamuna Expressway project |
|
1 |
Resettlement and Rehabilitation ( R and R) |
0.6416 |
0.5713 |
|
2 |
Ecological damages in the vicinity of site |
0.3226 |
0.3082 |
|
3 |
Ground water/Surface water pollution |
0.2573 |
0.2405 |
|
4 |
Air Pollution |
0.6472 |
0.5856 |
|
5 |
Soil pollution |
0.3334 |
0.2874 |
Analysis of both the projects based on their Coefficient of Variation indicates that the 1st project is having higher CV in all the 5 parameters that were considered and hence the effect of risk is more pronounced in the first project as compared to the second project and risk mitigation measures to counter the air pollution , soil pollution and R and R needs to be taken accordingly.
Table-6 Assessment of Political risk drivers for Moradabad- Bareilly highway
|
Sl. No |
Risk Indicators |
Degree of severity quoted by respondents |
Score |
Risk severity Index (RSI) |
Standard deviation (SD) |
Rank as per SD |
CV |
||||
|
|
|
5 |
4 |
3 |
2 |
1 |
|
|
|
|
|
|
1 |
Political instability |
20 |
15 |
12 |
10 |
8 |
224 |
3.446 |
4.690 |
V |
0.3608 |
|
2 |
Change in Government and their policies |
17 |
13 |
18 |
11 |
6 |
219 |
3.369 |
4.847 |
IV |
0.3728 |
|
3 |
Internal disturbances |
18 |
20 |
15 |
8 |
4 |
235 |
3.615 |
6.782 |
II |
0.5217 |
|
4 |
Politically induced agitations |
15 |
17 |
19 |
9 |
5 |
223 |
3.430 |
5.830 |
III |
0.4485 |
|
5 |
Change in scope of the project due to political factors |
22 |
18 |
14 |
7 |
4 |
242 |
3.723 |
7.483 |
I |
0.5756 |
Table-7 Assessment of Political risk d rivers for Yamuna Expressway
|
Sl. No |
Risk Indicators |
Degree of severity quoted by respondents |
Score |
Risk severity Index (RSI) |
Standard deviation (SD) |
Rank as per SD |
CV |
||||
|
|
|
5 |
4 |
3 |
2 |
1 |
|
|
|
|
|
|
1 |
Political instability |
17 |
13 |
10 |
9 |
6 |
191 |
3.472 |
4.183 |
I |
0.3803 |
|
2 |
Change in Government and their policies |
14 |
11
|
12 |
10 |
8 |
178 |
3.236 |
2.236 |
IV |
0.2032 |
|
3 |
Internal disturbances |
12 |
13 |
10 |
12 |
8 |
174 |
3.163 |
2.000 |
V |
0.1818 |
|
4 |
Political induced agitations |
10 |
12 |
13 |
14 |
6 |
171 |
3.109 |
3.162 |
II |
0.2874 |
|
5 |
Change in scope of the project due to political factors |
15 |
10 |
12 |
11 |
7 |
180 |
3.272 |
2.915 |
III |
0.2650 |
ANOVA analysis was carried out for finding the impact of Political risk for both the projects by taking the Risk Severity Index and by making assumptions as follows:
Null Hypothesis:
There is no variation in difference of means between the projects i.e there is no significant effect of this risk on the projects
Alternate hypothesis:
There is significant effect of this risk on both the projects
Table-8
|
ANOVA: Single Factor |
||||||
|
SUMMARY |
||||||
|
Groups |
Count |
Sum |
Average |
Variance |
||
|
Column 1 |
5 |
17.583 |
3.5166 |
0.021638 |
||
|
Column 2 |
5 |
16.252 |
3.2504 |
0.019353 |
||
|
ANOVA |
||||||
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
0.177156 |
1 |
0.177156 |
8.643532 |
0.01871 |
5.317655 |
|
Within Groups |
0.163966 |
8 |
0.020496 |
|||
|
Total |
0.341123 |
9 |
|
|
|
|
The result indicates that the value of F is greater than F(critical) which implies that there is significant effect of this risk on the projects and that difference in means of both the projects are not equal i.e the effect of this risk is not the same in both the projects
Table-9 Analysis of both the project based on Coefficient of Variation ( CV)
|
Sl.No |
Risk Indicators |
CV of Moradabad-Bareilly project |
CV of Yamuna Expressway project |
|
1 |
Political instability |
0.3608 |
0.3803 |
|
2 |
Change in Government and their policies |
0.3728 |
0.2032 |
|
3 |
Internal disturbances |
0.5217 |
0.1818 |
|
4 |
Politically induced agitations |
0.4485 |
0.2874 |
|
5 |
Change in scope of the project due to political factors |
0.5756 |
0.2650 |
Perusal of the above table indicates that second project has got greater consistency in management of risks and that the risk due to internal disturbances and change in scope was very high in the first project. Moreover, due to better management of political risks, the second project was completed ahead of schedule.
CONCLUSION:
In the two projects that was compared, the effect of environmental risk is not significant in both the projects whereas there is significant effect of political risk in the first project and hence is reflected in the high value of Coefficient of Variation as compared to the second project. Even in Environmental risk, the value of CV for the first project is higher which indicates that the project is less consistent and more prone to risks. Overall, it can be inferred that the Yamuna-Expressway project is more consistent and the risks have been managed in a better manner as compared to the Moradabad- Bareilly project.
REFERENCES:
1 Anil Kumar Gupta et al ( 2013), Risk Variation Assessment of Indian Road PPP Projects, International Journal of Science, Engineering and Technology, 2(5),pp 1017-1026
2 Ahmed, et al (1990),Decision support system for modeling bid/no-bid decision problems, Journal of Construction Engineering and Management, ASCE,116(4), pp595-608
3 Al-Bahar J and Crandall K(1990), Systematic Risk Management Approach for Construction Projects, Journal of Construction Engineering and Management,116(3),pp533-546
4 Baloi D and Price ADF (2003),Modelling Global Risk factors Affecting Construction Cost Performance, International Journal of Project Management,21(4),pp261-269
5 Florence YYL and Linda H (2006),Risk faced by Singapore Firms When undertaking Construction projects in India, International Journal of Project Management,24(38),pp261-270
6 Ijigah Edoka Augustine, Jimoh Richard Ajayi, et al, (2013), Assessment of Risk Management Practices in Nigerian Construction Industry-Toward establishing Risk Management Index, International Journal of Pure and Applied Sciences and Technology,16(2), pp20-31
7 Kansal RK and Manoj Sharma (2012),Risk Assessment methods and Applications in Construction Projects,2(3),pp1081-1085
8 Martina Claudia Garrido et al (2011),Risk Identification Techniques Knowledge and Application in Brazilian Construction,2(11), pp242-252
9 Mohammed. F. Diab et al (2012), Using Risk Assessment to Improve Highway Construction Project Performance in USA, 48th ASC Annual International Conference Proceedings, USA
10 Nerija Banaitiene and Audrius Banaitis (2012),Risk Management-Current Issues and Challenges, ISBN 978-953-51-0747-7, In Tech, September, 2012
11 Rasheed Adewale Salawu and Fadhlin Abdullah ( 2014), Review of Risk assessment Models for Highway Construction Projects, International Journal of Engineering, Research and Technology, 3(12), December, 2014
12 Sameh M. El-Sayegh and Mohamoud. H. Mansour(2015), Risk Assessment and Allocation in Highway Projects in UAE, Journal of Management in Engineering, 31(6), 04015004
13 Shehu Z and Sommerville J (2006),Real Time Risk Management Approach in Construction Projects, Glasgow University, Glasgow, United Kingdom
14 Shen LY et al(2001),Risk assessment for Construction Joint Venture in China, Journal of Construction Engineering and Management,127(1),pp76-81
15 Yukiva Sato et al ( 2005), Quantitative risk Analysis of Road Projects based on Empirical data in Japan, Journal of Eastern Asia Society for Transportation Studies, Vol.6, pp 3971-3984
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Received on 15.11.2015 Accepted on 18.12.2015 © EnggResearch.net All Right Reserved Int. J. Tech. 5(2): July-Dec., 2015; Page 204-208 DOI: 10.5958/2231-3915.2015.00022.X |
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